bump to 3.2.5

(grafted from devel branch)

.hgeol

@@ -0,0 +1,8 @@
+[patterns]
+scripts/*.in = LF
+debug/msvc/*.dat = CRLF
+unsupported/test/mpreal/*.* = CRLF
+** = native
+
+[repository]
+native = LF

.hgignore

@@ -0,0 +1,32 @@
+syntax: glob
+qrc_*cxx
+*.orig
+*.pyc
+*.diff
+diff
+*.save
+save
+*.old
+*.gmo
+*.qm
+core
+core.*
+*.bak
+*~
+build*
+*.moc.*
+*.moc
+ui_*
+CMakeCache.txt
+tags
+.*.swp
+activity.png
+*.out
+*.php*
+*.log
+*.orig
+*.rej
+log
+patch
+a
+a.*

.krazy

@@ -1,3 +0,0 @@
-SKIP /disabled/
-SKIP /bench/
-SKIP /build/

CMakeLists.txt

@@ -1,102 +1,420 @@
 project(Eigen)
-set(EIGEN_VERSION_NUMBER "2.0.2")
 
-#if the svnversion program is absent, this will leave the SVN_REVISION string empty,
-#but won't stop CMake.
-execute_process(COMMAND svnversion -n ${CMAKE_SOURCE_DIR}
-                OUTPUT_VARIABLE EIGEN_SVNVERSION_OUTPUT)
+cmake_minimum_required(VERSION 2.8.2)
 
-#we only want EIGEN_SVN_REVISION if it is an actual revision number, not a string like "exported"
-string(REGEX MATCH "^[0-9]+.*" EIGEN_SVN_REVISION "${EIGEN_SVNVERSION_OUTPUT}")
+# guard against in-source builds
 
-if(EIGEN_SVN_REVISION)
-  set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER} (SVN revision ${EIGEN_SVN_REVISION})")
-else(EIGEN_SVN_REVISION)
+if(${CMAKE_SOURCE_DIR} STREQUAL ${CMAKE_BINARY_DIR})
+  message(FATAL_ERROR "In-source builds not allowed. Please make a new directory (called a build directory) and run CMake from there. You may need to remove CMakeCache.txt. ")
+endif()
+
+# guard against bad build-type strings
+
+if (NOT CMAKE_BUILD_TYPE)
+  set(CMAKE_BUILD_TYPE "Release")
+endif()
+
+string(TOLOWER "${CMAKE_BUILD_TYPE}" cmake_build_type_tolower)
+if(    NOT cmake_build_type_tolower STREQUAL "debug"
+   AND NOT cmake_build_type_tolower STREQUAL "release"
+   AND NOT cmake_build_type_tolower STREQUAL "relwithdebinfo")
+  message(FATAL_ERROR "Unknown build type \"${CMAKE_BUILD_TYPE}\". Allowed values are Debug, Release, RelWithDebInfo (case-insensitive).")
+endif()
+
+
+#############################################################################
+# retrieve version infomation                                               #
+#############################################################################
+
+# automatically parse the version number
+file(READ "${PROJECT_SOURCE_DIR}/Eigen/src/Core/util/Macros.h" _eigen_version_header)
+string(REGEX MATCH "define[ \t]+EIGEN_WORLD_VERSION[ \t]+([0-9]+)" _eigen_world_version_match "${_eigen_version_header}")
+set(EIGEN_WORLD_VERSION "${CMAKE_MATCH_1}")
+string(REGEX MATCH "define[ \t]+EIGEN_MAJOR_VERSION[ \t]+([0-9]+)" _eigen_major_version_match "${_eigen_version_header}")
+set(EIGEN_MAJOR_VERSION "${CMAKE_MATCH_1}")
+string(REGEX MATCH "define[ \t]+EIGEN_MINOR_VERSION[ \t]+([0-9]+)" _eigen_minor_version_match "${_eigen_version_header}")
+set(EIGEN_MINOR_VERSION "${CMAKE_MATCH_1}")
+set(EIGEN_VERSION_NUMBER ${EIGEN_WORLD_VERSION}.${EIGEN_MAJOR_VERSION}.${EIGEN_MINOR_VERSION})
+
+# if the mercurial program is absent, this will leave the EIGEN_HG_CHANGESET string empty,
+# but won't stop CMake.
+execute_process(COMMAND hg tip -R ${CMAKE_SOURCE_DIR} OUTPUT_VARIABLE EIGEN_HGTIP_OUTPUT)
+execute_process(COMMAND hg branch -R ${CMAKE_SOURCE_DIR} OUTPUT_VARIABLE EIGEN_BRANCH_OUTPUT)
+
+# if this is the default (aka development) branch, extract the mercurial changeset number from the hg tip output...
+if(EIGEN_BRANCH_OUTPUT MATCHES "default")
+string(REGEX MATCH "^changeset: *[0-9]*:([0-9;a-f]+).*" EIGEN_HG_CHANGESET_MATCH "${EIGEN_HGTIP_OUTPUT}")
+set(EIGEN_HG_CHANGESET "${CMAKE_MATCH_1}")
+endif(EIGEN_BRANCH_OUTPUT MATCHES "default")
+#...and show it next to the version number
+if(EIGEN_HG_CHANGESET)
+  set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER} (mercurial changeset ${EIGEN_HG_CHANGESET})")
+else(EIGEN_HG_CHANGESET)
   set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER}")
-endif(EIGEN_SVN_REVISION)
+endif(EIGEN_HG_CHANGESET)
 
-cmake_minimum_required(VERSION 2.6.2)
+
+include(CheckCXXCompilerFlag)
 
 set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
 
-option(EIGEN_BUILD_TESTS "Build tests" OFF)
-option(EIGEN_BUILD_DEMOS "Build demos" OFF)
-if(NOT WIN32)
-  option(EIGEN_BUILD_LIB "Build the binary shared library" OFF)
-endif(NOT WIN32)
-option(EIGEN_BUILD_BTL "Build benchmark suite" OFF)
+#############################################################################
+# find how to link to the standard libraries                                #
+#############################################################################
 
-if(EIGEN_BUILD_LIB)
-  option(EIGEN_TEST_LIB "Build the unit tests using the library (disable -pedantic)" OFF)
-endif(EIGEN_BUILD_LIB)
+find_package(StandardMathLibrary)
+
+
+set(EIGEN_TEST_CUSTOM_LINKER_FLAGS  "" CACHE STRING "Additional linker flags when linking unit tests.")
+set(EIGEN_TEST_CUSTOM_CXX_FLAGS     "" CACHE STRING "Additional compiler flags when compiling unit tests.")
+
+set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "")
+
+if(NOT STANDARD_MATH_LIBRARY_FOUND)
+
+  message(FATAL_ERROR
+    "Can't link to the standard math library. Please report to the Eigen developers, telling them about your platform.")
+
+else()
+
+  if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO)
+    set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO} ${STANDARD_MATH_LIBRARY}")
+  else()
+    set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "${STANDARD_MATH_LIBRARY}")
+  endif()
+
+endif()
+
+if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO)
+  message(STATUS "Standard libraries to link to explicitly: ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO}")
+else()
+  message(STATUS "Standard libraries to link to explicitly: none")
+endif()
+
+option(EIGEN_BUILD_BTL "Build benchmark suite" OFF)
+if(NOT WIN32)
+  option(EIGEN_BUILD_PKGCONFIG "Build pkg-config .pc file for Eigen" ON)
+endif(NOT WIN32)
 
 set(CMAKE_INCLUDE_CURRENT_DIR ON)
 
-if(CMAKE_COMPILER_IS_GNUCXX)
-  if(CMAKE_SYSTEM_NAME MATCHES Linux)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wnon-virtual-dtor -Wno-long-long -ansi -Wundef -Wcast-align -Wchar-subscripts -Wall -W -Wpointer-arith -Wwrite-strings -Wformat-security -Wextra -fno-exceptions -fno-check-new -fno-common -fstrict-aliasing")
-    if(NOT EIGEN_TEST_LIB)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pedantic")
-    endif(NOT EIGEN_TEST_LIB)
+option(EIGEN_SPLIT_LARGE_TESTS "Split large tests into smaller executables" ON)
 
-    option(EIGEN_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF)
-    if(EIGEN_TEST_SSE2)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse2")
-      message("Enabling SSE2 in tests/examples")
-    endif(EIGEN_TEST_SSE2)
+option(EIGEN_DEFAULT_TO_ROW_MAJOR "Use row-major as default matrix storage order" OFF)
+if(EIGEN_DEFAULT_TO_ROW_MAJOR)
+  add_definitions("-DEIGEN_DEFAULT_TO_ROW_MAJOR")
+endif()
 
-    option(EIGEN_TEST_SSE3 "Enable/Disable SSE3 in tests/examples" OFF)
-    if(EIGEN_TEST_SSE3)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse3")
-      message("Enabling SSE3 in tests/examples")
-    endif(EIGEN_TEST_SSE3)
+set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320")
 
-    option(EIGEN_TEST_SSSE3 "Enable/Disable SSSE3 in tests/examples" OFF)
-    if(EIGEN_TEST_SSSE3)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mssse3")
-      message("Enabling SSSE3 in tests/examples")
-    endif(EIGEN_TEST_SSSE3)
+macro(ei_add_cxx_compiler_flag FLAG)
+  string(REGEX REPLACE "-" "" SFLAG ${FLAG})
+  check_cxx_compiler_flag(${FLAG} COMPILER_SUPPORT_${SFLAG})
+  if(COMPILER_SUPPORT_${SFLAG})
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${FLAG}")
+  endif()
+endmacro(ei_add_cxx_compiler_flag)
 
-    option(EIGEN_TEST_ALTIVEC "Enable/Disable altivec in tests/examples" OFF)
-    if(EIGEN_TEST_ALTIVEC)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec")
-      message("Enabling AltiVec in tests/examples")
-    endif(EIGEN_TEST_ALTIVEC)
-
-  endif(CMAKE_SYSTEM_NAME MATCHES Linux)
-endif(CMAKE_COMPILER_IS_GNUCXX)
-
-if(MSVC)
-  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ")
+if(NOT MSVC)
+  # We assume that other compilers are partly compatible with GNUCC
+  
+  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fexceptions")
+  set(CMAKE_CXX_FLAGS_DEBUG "-g3")
+  set(CMAKE_CXX_FLAGS_RELEASE "-g0 -O2")
+  
+  # clang outputs some warnings for unknwon flags that are not caught by check_cxx_compiler_flag
+  # adding -Werror turns such warnings into errors
+  check_cxx_compiler_flag("-Werror" COMPILER_SUPPORT_WERROR)
+  if(COMPILER_SUPPORT_WERROR)
+    set(CMAKE_REQUIRED_FLAGS "-Werror")
+  endif()
+  
+  ei_add_cxx_compiler_flag("-pedantic")
+  ei_add_cxx_compiler_flag("-Wall")
+  ei_add_cxx_compiler_flag("-Wextra")
+  #ei_add_cxx_compiler_flag("-Weverything")              # clang
+  
+  ei_add_cxx_compiler_flag("-Wundef")
+  ei_add_cxx_compiler_flag("-Wcast-align")
+  ei_add_cxx_compiler_flag("-Wchar-subscripts")
+  ei_add_cxx_compiler_flag("-Wnon-virtual-dtor")
+  ei_add_cxx_compiler_flag("-Wunused-local-typedefs")
+  ei_add_cxx_compiler_flag("-Wpointer-arith")
+  ei_add_cxx_compiler_flag("-Wwrite-strings")
+  ei_add_cxx_compiler_flag("-Wformat-security")
+  
+  ei_add_cxx_compiler_flag("-Wno-psabi")
+  ei_add_cxx_compiler_flag("-Wno-variadic-macros")
+  ei_add_cxx_compiler_flag("-Wno-long-long")
+  
+  ei_add_cxx_compiler_flag("-fno-check-new")
+  ei_add_cxx_compiler_flag("-fno-common")
+  ei_add_cxx_compiler_flag("-fstrict-aliasing")
+  ei_add_cxx_compiler_flag("-wd981")                    # disable ICC's "operands are evaluated in unspecified order" remark
+  ei_add_cxx_compiler_flag("-wd2304")                   # disbale ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
+  
+  # The -ansi flag must be added last, otherwise it is also used as a linker flag by check_cxx_compiler_flag making it fails
+  # Moreover we should not set both -strict-ansi and -ansi
+  check_cxx_compiler_flag("-strict-ansi" COMPILER_SUPPORT_STRICTANSI)
+  ei_add_cxx_compiler_flag("-Qunused-arguments")        # disable clang warning: argument unused during compilation: '-ansi'
+  
+  if(COMPILER_SUPPORT_STRICTANSI)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -strict-ansi")
+  else()
+    ei_add_cxx_compiler_flag("-ansi")
+  endif()
+  
+  set(CMAKE_REQUIRED_FLAGS "")
 
   option(EIGEN_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF)
   if(EIGEN_TEST_SSE2)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:SSE2")
-    message("Enabling SSE2 in tests/examples")
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse2")
+    message(STATUS "Enabling SSE2 in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_SSE3 "Enable/Disable SSE3 in tests/examples" OFF)
+  if(EIGEN_TEST_SSE3)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse3")
+    message(STATUS "Enabling SSE3 in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_SSSE3 "Enable/Disable SSSE3 in tests/examples" OFF)
+  if(EIGEN_TEST_SSSE3)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mssse3")
+    message(STATUS "Enabling SSSE3 in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_SSE4_1 "Enable/Disable SSE4.1 in tests/examples" OFF)
+  if(EIGEN_TEST_SSE4_1)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse4.1")
+    message(STATUS "Enabling SSE4.1 in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_SSE4_2 "Enable/Disable SSE4.2 in tests/examples" OFF)
+  if(EIGEN_TEST_SSE4_2)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse4.2")
+    message(STATUS "Enabling SSE4.2 in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_ALTIVEC "Enable/Disable AltiVec in tests/examples" OFF)
+  if(EIGEN_TEST_ALTIVEC)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec")
+    message(STATUS "Enabling AltiVec in tests/examples")
+  endif()
+
+  option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF)
+  if(EIGEN_TEST_NEON)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon -mcpu=cortex-a8")
+    message(STATUS "Enabling NEON in tests/examples")
+  endif()
+
+  check_cxx_compiler_flag("-fopenmp" COMPILER_SUPPORT_OPENMP)
+  if(COMPILER_SUPPORT_OPENMP)
+    option(EIGEN_TEST_OPENMP "Enable/Disable OpenMP in tests/examples" OFF)
+    if(EIGEN_TEST_OPENMP)
+      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fopenmp")
+      message(STATUS "Enabling OpenMP in tests/examples")
+    endif()
+  endif()
+
+else(NOT MSVC)
+
+  # C4127 - conditional expression is constant
+  # C4714 - marked as __forceinline not inlined (I failed to deactivate it selectively)
+  #         We can disable this warning in the unit tests since it is clear that it occurs
+  #         because we are oftentimes returning objects that have a destructor or may
+  #         throw exceptions - in particular in the unit tests we are throwing extra many
+  #         exceptions to cover indexing errors.
+  # C4505 - unreferenced local function has been removed (impossible to deactive selectively)
+  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /EHsc /wd4127 /wd4505 /wd4714")
+
+  # replace all /Wx by /W4
+  string(REGEX REPLACE "/W[0-9]" "/W4" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+
+  check_cxx_compiler_flag("/openmp" COMPILER_SUPPORT_OPENMP)
+  if(COMPILER_SUPPORT_OPENMP)
+    option(EIGEN_TEST_OPENMP "Enable/Disable OpenMP in tests/examples" OFF)
+    if(EIGEN_TEST_OPENMP)
+      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /openmp")
+      message(STATUS "Enabling OpenMP in tests/examples")
+    endif()
+  endif()
+
+  option(EIGEN_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF)
+  if(EIGEN_TEST_SSE2)
+    if(NOT CMAKE_CL_64)
+      # arch is not supported on 64 bit systems, SSE is enabled automatically.
+      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:SSE2")
+    endif(NOT CMAKE_CL_64)
+    message(STATUS "Enabling SSE2 in tests/examples")
   endif(EIGEN_TEST_SSE2)
-endif(MSVC)
+endif(NOT MSVC)
 
 option(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION "Disable explicit vectorization in tests/examples" OFF)
+option(EIGEN_TEST_X87 "Force using X87 instructions. Implies no vectorization." OFF)
+option(EIGEN_TEST_32BIT "Force generating 32bit code." OFF)
+
+if(EIGEN_TEST_X87)
+  set(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION ON)
+  if(CMAKE_COMPILER_IS_GNUCXX)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpmath=387")
+    message(STATUS "Forcing use of x87 instructions in tests/examples")
+  else()
+    message(STATUS "EIGEN_TEST_X87 ignored on your compiler")
+  endif()
+endif()
+
+if(EIGEN_TEST_32BIT)
+  if(CMAKE_COMPILER_IS_GNUCXX)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -m32")
+    message(STATUS "Forcing generation of 32-bit code in tests/examples")
+  else()
+    message(STATUS "EIGEN_TEST_32BIT ignored on your compiler")
+  endif()
+endif()
+
 if(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
   add_definitions(-DEIGEN_DONT_VECTORIZE=1)
-  message("Disabling vectorization in tests/examples")
-endif(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
+  message(STATUS "Disabling vectorization in tests/examples")
+endif()
+
+option(EIGEN_TEST_NO_EXPLICIT_ALIGNMENT "Disable explicit alignment (hence vectorization) in tests/examples" OFF)
+if(EIGEN_TEST_NO_EXPLICIT_ALIGNMENT)
+  add_definitions(-DEIGEN_DONT_ALIGN=1)
+  message(STATUS "Disabling alignment in tests/examples")
+endif()
+
+option(EIGEN_TEST_C++0x "Enables all C++0x features." OFF)
 
 include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
 
+# the user modifiable install path for header files
+set(EIGEN_INCLUDE_INSTALL_DIR ${EIGEN_INCLUDE_INSTALL_DIR} CACHE PATH "The directory where we install the header files (optional)")
+
+# set the internal install path for header files which depends on wether the user modifiable
+# EIGEN_INCLUDE_INSTALL_DIR has been set by the user or not.
+if(EIGEN_INCLUDE_INSTALL_DIR)
+  set(INCLUDE_INSTALL_DIR
+    ${EIGEN_INCLUDE_INSTALL_DIR}
+    CACHE INTERNAL
+    "The directory where we install the header files (internal)"
+  )
+else()
+  set(INCLUDE_INSTALL_DIR
+    "${CMAKE_INSTALL_PREFIX}/include/eigen3"
+    CACHE INTERNAL
+    "The directory where we install the header files (internal)"
+  )
+endif()
+
+# similar to set_target_properties but append the property instead of overwriting it
+macro(ei_add_target_property target prop value)
+
+  get_target_property(previous ${target} ${prop})
+  # if the property wasn't previously set, ${previous} is now "previous-NOTFOUND" which cmake allows catching with plain if()
+  if(NOT previous)
+    set(previous "")
+  endif(NOT previous)
+  set_target_properties(${target} PROPERTIES ${prop} "${previous} ${value}")
+endmacro(ei_add_target_property)
+
+install(FILES
+  signature_of_eigen3_matrix_library
+  DESTINATION ${INCLUDE_INSTALL_DIR} COMPONENT Devel
+  )
+
+if(EIGEN_BUILD_PKGCONFIG)
+    SET(path_separator ":")
+    STRING(REPLACE ${path_separator} ";" pkg_config_libdir_search "$ENV{PKG_CONFIG_LIBDIR}")
+    message(STATUS "searching for 'pkgconfig' directory in PKG_CONFIG_LIBDIR ( $ENV{PKG_CONFIG_LIBDIR} ), ${CMAKE_INSTALL_PREFIX}/share, and ${CMAKE_INSTALL_PREFIX}/lib")
+    FIND_PATH(pkg_config_libdir pkgconfig ${pkg_config_libdir_search} ${CMAKE_INSTALL_PREFIX}/share ${CMAKE_INSTALL_PREFIX}/lib ${pkg_config_libdir_search})
+    if(pkg_config_libdir)
+        SET(pkg_config_install_dir ${pkg_config_libdir})
+        message(STATUS "found ${pkg_config_libdir}/pkgconfig" )
+    else(pkg_config_libdir)
+        SET(pkg_config_install_dir ${CMAKE_INSTALL_PREFIX}/share)
+        message(STATUS "pkgconfig not found; installing in ${pkg_config_install_dir}" )
+    endif(pkg_config_libdir)
+
+    configure_file(eigen3.pc.in eigen3.pc)
+    install(FILES ${CMAKE_CURRENT_BINARY_DIR}/eigen3.pc
+        DESTINATION ${pkg_config_install_dir}/pkgconfig
+        )
+endif(EIGEN_BUILD_PKGCONFIG)
+
 add_subdirectory(Eigen)
 
-if(EIGEN_BUILD_TESTS)
-  include(CTest)
-  add_subdirectory(test)
-endif(EIGEN_BUILD_TESTS)
+add_subdirectory(doc EXCLUDE_FROM_ALL)
 
-add_subdirectory(doc)
+include(EigenConfigureTesting)
 
-if(EIGEN_BUILD_DEMOS)
-  add_subdirectory(demos)
-endif(EIGEN_BUILD_DEMOS)
+# fixme, not sure this line is still needed:
+enable_testing() # must be called from the root CMakeLists, see man page
 
+
+if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
+  add_subdirectory(test) # can't do EXCLUDE_FROM_ALL here, breaks CTest
+else()
+  add_subdirectory(test EXCLUDE_FROM_ALL)
+endif()
+
+if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
+  add_subdirectory(blas)
+  add_subdirectory(lapack)
+else()
+  add_subdirectory(blas EXCLUDE_FROM_ALL)
+  add_subdirectory(lapack EXCLUDE_FROM_ALL)
+endif()
+
+add_subdirectory(unsupported)
+
+add_subdirectory(demos EXCLUDE_FROM_ALL)
+
+# must be after test and unsupported, for configuring buildtests.in
+add_subdirectory(scripts EXCLUDE_FROM_ALL)
+
+# TODO: consider also replacing EIGEN_BUILD_BTL by a custom target "make btl"?
 if(EIGEN_BUILD_BTL)
-  add_subdirectory(bench/btl)
+  add_subdirectory(bench/btl EXCLUDE_FROM_ALL)
 endif(EIGEN_BUILD_BTL)
+
+if(NOT WIN32)
+  add_subdirectory(bench/spbench EXCLUDE_FROM_ALL)
+endif(NOT WIN32)
+
+configure_file(scripts/cdashtesting.cmake.in cdashtesting.cmake @ONLY)
+
+ei_testing_print_summary()
+
+message(STATUS "")
+message(STATUS "Configured Eigen ${EIGEN_VERSION_NUMBER}")
+message(STATUS "")
+
+option(EIGEN_FAILTEST "Enable failtests." OFF)
+if(EIGEN_FAILTEST)
+  add_subdirectory(failtest)
+endif()
+
+string(TOLOWER "${CMAKE_GENERATOR}" cmake_generator_tolower)
+if(cmake_generator_tolower MATCHES "makefile")
+  message(STATUS "Some things you can do now:")
+  message(STATUS "--------------+--------------------------------------------------------------")
+  message(STATUS "Command       |   Description")
+  message(STATUS "--------------+--------------------------------------------------------------")
+  message(STATUS "make install  | Install to ${CMAKE_INSTALL_PREFIX}. To change that:")
+  message(STATUS "              |     cmake . -DCMAKE_INSTALL_PREFIX=yourpath")
+  message(STATUS "              |   Eigen headers will then be installed to:")
+  message(STATUS "              |     ${INCLUDE_INSTALL_DIR}")
+  message(STATUS "              |   To install Eigen headers to a separate location, do:")
+  message(STATUS "              |     cmake . -DEIGEN_INCLUDE_INSTALL_DIR=yourpath")
+  message(STATUS "make doc      | Generate the API documentation, requires Doxygen & LaTeX")
+  message(STATUS "make check    | Build and run the unit-tests. Read this page:")
+  message(STATUS "              |   http://eigen.tuxfamily.org/index.php?title=Tests")
+  message(STATUS "make blas     | Build BLAS library (not the same thing as Eigen)")
+  message(STATUS "--------------+--------------------------------------------------------------")
+else()
+  message(STATUS "To build/run the unit tests, read this page:")
+  message(STATUS "  http://eigen.tuxfamily.org/index.php?title=Tests")
+endif()
+
+message(STATUS "")

COPYING.BSD

@@ -0,0 +1,26 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
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COPYING.LESSER

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COPYING.LGPL

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+conditions either of that version or of any later version published by
+the Free Software Foundation.  If the Library does not specify a
+license version number, you may choose any version ever published by
+the Free Software Foundation.
+
+  14. If you wish to incorporate parts of the Library into other free
+programs whose distribution conditions are incompatible with these,
+write to the author to ask for permission.  For software which is
+copyrighted by the Free Software Foundation, write to the Free
+Software Foundation; we sometimes make exceptions for this.  Our
+decision will be guided by the two goals of preserving the free status
+of all derivatives of our free software and of promoting the sharing
+and reuse of software generally.
+
+                            NO WARRANTY
+
+  15. BECAUSE THE LIBRARY IS LICENSED FREE OF CHARGE, THERE IS NO
+WARRANTY FOR THE LIBRARY, TO THE EXTENT PERMITTED BY APPLICABLE LAW.
+EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR
+OTHER PARTIES PROVIDE THE LIBRARY "AS IS" WITHOUT WARRANTY OF ANY
+KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE
+LIBRARY IS WITH YOU.  SHOULD THE LIBRARY PROVE DEFECTIVE, YOU ASSUME
+THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN
+WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY
+AND/OR REDISTRIBUTE THE LIBRARY AS PERMITTED ABOVE, BE LIABLE TO YOU
+FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR
+CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE
+LIBRARY (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING
+RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A
+FAILURE OF THE LIBRARY TO OPERATE WITH ANY OTHER SOFTWARE), EVEN IF
+SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
+DAMAGES.
+
+                     END OF TERMS AND CONDITIONS
+
+           How to Apply These Terms to Your New Libraries
+
+  If you develop a new library, and you want it to be of the greatest
+possible use to the public, we recommend making it free software that
+everyone can redistribute and change.  You can do so by permitting
+redistribution under these terms (or, alternatively, under the terms of the
+ordinary General Public License).
+
+  To apply these terms, attach the following notices to the library.  It is
+safest to attach them to the start of each source file to most effectively
+convey the exclusion of warranty; and each file should have at least the
+"copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the library's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This library is free software; you can redistribute it and/or
+    modify it under the terms of the GNU Lesser General Public
+    License as published by the Free Software Foundation; either
+    version 2.1 of the License, or (at your option) any later version.
+
+    This library is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+    Lesser General Public License for more details.
+
+    You should have received a copy of the GNU Lesser General Public
+    License along with this library; if not, write to the Free Software
+    Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+Also add information on how to contact you by electronic and paper mail.
+
+You should also get your employer (if you work as a programmer) or your
+school, if any, to sign a "copyright disclaimer" for the library, if
+necessary.  Here is a sample; alter the names:
+
+  Yoyodyne, Inc., hereby disclaims all copyright interest in the
+  library `Frob' (a library for tweaking knobs) written by James Random Hacker.
+
+  <signature of Ty Coon>, 1 April 1990
+  Ty Coon, President of Vice
+
+That's all there is to it!

COPYING.MINPACK

@@ -0,0 +1,52 @@
+Minpack Copyright Notice (1999) University of Chicago.  All rights reserved
+
+Redistribution and use in source and binary forms, with or
+without modification, are permitted provided that the
+following conditions are met:
+
+1. Redistributions of source code must retain the above
+copyright notice, this list of conditions and the following
+disclaimer.
+
+2. Redistributions in binary form must reproduce the above
+copyright notice, this list of conditions and the following
+disclaimer in the documentation and/or other materials
+provided with the distribution.
+
+3. The end-user documentation included with the
+redistribution, if any, must include the following
+acknowledgment:
+
+   "This product includes software developed by the
+   University of Chicago, as Operator of Argonne National
+   Laboratory.
+
+Alternately, this acknowledgment may appear in the software
+itself, if and wherever such third-party acknowledgments
+normally appear.
+
+4. WARRANTY DISCLAIMER. THE SOFTWARE IS SUPPLIED "AS IS"
+WITHOUT WARRANTY OF ANY KIND. THE COPYRIGHT HOLDER, THE
+UNITED STATES, THE UNITED STATES DEPARTMENT OF ENERGY, AND
+THEIR EMPLOYEES: (1) DISCLAIM ANY WARRANTIES, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO ANY IMPLIED WARRANTIES
+OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE
+OR NON-INFRINGEMENT, (2) DO NOT ASSUME ANY LEGAL LIABILITY
+OR RESPONSIBILITY FOR THE ACCURACY, COMPLETENESS, OR
+USEFULNESS OF THE SOFTWARE, (3) DO NOT REPRESENT THAT USE OF
+THE SOFTWARE WOULD NOT INFRINGE PRIVATELY OWNED RIGHTS, (4)
+DO NOT WARRANT THAT THE SOFTWARE WILL FUNCTION
+UNINTERRUPTED, THAT IT IS ERROR-FREE OR THAT ANY ERRORS WILL
+BE CORRECTED.
+
+5. LIMITATION OF LIABILITY. IN NO EVENT WILL THE COPYRIGHT
+HOLDER, THE UNITED STATES, THE UNITED STATES DEPARTMENT OF
+ENERGY, OR THEIR EMPLOYEES: BE LIABLE FOR ANY INDIRECT,
+INCIDENTAL, CONSEQUENTIAL, SPECIAL OR PUNITIVE DAMAGES OF
+ANY KIND OR NATURE, INCLUDING BUT NOT LIMITED TO LOSS OF
+PROFITS OR LOSS OF DATA, FOR ANY REASON WHATSOEVER, WHETHER
+SUCH LIABILITY IS ASSERTED ON THE BASIS OF CONTRACT, TORT
+(INCLUDING NEGLIGENCE OR STRICT LIABILITY), OR OTHERWISE,
+EVEN IF ANY OF SAID PARTIES HAS BEEN WARNED OF THE
+POSSIBILITY OF SUCH LOSS OR DAMAGES.
+

COPYING.MPL2

@@ -0,0 +1,373 @@
+Mozilla Public License Version 2.0
+==================================
+
+1. Definitions
+--------------
+
+1.1. "Contributor"
+    means each individual or legal entity that creates, contributes to
+    the creation of, or owns Covered Software.
+
+1.2. "Contributor Version"
+    means the combination of the Contributions of others (if any) used
+    by a Contributor and that particular Contributor's Contribution.
+
+1.3. "Contribution"
+    means Covered Software of a particular Contributor.
+
+1.4. "Covered Software"
+    means Source Code Form to which the initial Contributor has attached
+    the notice in Exhibit A, the Executable Form of such Source Code
+    Form, and Modifications of such Source Code Form, in each case
+    including portions thereof.
+
+1.5. "Incompatible With Secondary Licenses"
+    means
+
+    (a) that the initial Contributor has attached the notice described
+        in Exhibit B to the Covered Software; or
+
+    (b) that the Covered Software was made available under the terms of
+        version 1.1 or earlier of the License, but not also under the
+        terms of a Secondary License.
+
+1.6. "Executable Form"
+    means any form of the work other than Source Code Form.
+
+1.7. "Larger Work"
+    means a work that combines Covered Software with other material, in 
+    a separate file or files, that is not Covered Software.
+
+1.8. "License"
+    means this document.
+
+1.9. "Licensable"
+    means having the right to grant, to the maximum extent possible,
+    whether at the time of the initial grant or subsequently, any and
+    all of the rights conveyed by this License.
+
+1.10. "Modifications"
+    means any of the following:
+
+    (a) any file in Source Code Form that results from an addition to,
+        deletion from, or modification of the contents of Covered
+        Software; or
+
+    (b) any new file in Source Code Form that contains any Covered
+        Software.
+
+1.11. "Patent Claims" of a Contributor
+    means any patent claim(s), including without limitation, method,
+    process, and apparatus claims, in any patent Licensable by such
+    Contributor that would be infringed, but for the grant of the
+    License, by the making, using, selling, offering for sale, having
+    made, import, or transfer of either its Contributions or its
+    Contributor Version.
+
+1.12. "Secondary License"
+    means either the GNU General Public License, Version 2.0, the GNU
+    Lesser General Public License, Version 2.1, the GNU Affero General
+    Public License, Version 3.0, or any later versions of those
+    licenses.
+
+1.13. "Source Code Form"
+    means the form of the work preferred for making modifications.
+
+1.14. "You" (or "Your")
+    means an individual or a legal entity exercising rights under this
+    License. For legal entities, "You" includes any entity that
+    controls, is controlled by, or is under common control with You. For
+    purposes of this definition, "control" means (a) the power, direct
+    or indirect, to cause the direction or management of such entity,
+    whether by contract or otherwise, or (b) ownership of more than
+    fifty percent (50%) of the outstanding shares or beneficial
+    ownership of such entity.
+
+2. License Grants and Conditions
+--------------------------------
+
+2.1. Grants
+
+Each Contributor hereby grants You a world-wide, royalty-free,
+non-exclusive license:
+
+(a) under intellectual property rights (other than patent or trademark)
+    Licensable by such Contributor to use, reproduce, make available,
+    modify, display, perform, distribute, and otherwise exploit its
+    Contributions, either on an unmodified basis, with Modifications, or
+    as part of a Larger Work; and
+
+(b) under Patent Claims of such Contributor to make, use, sell, offer
+    for sale, have made, import, and otherwise transfer either its
+    Contributions or its Contributor Version.
+
+2.2. Effective Date
+
+The licenses granted in Section 2.1 with respect to any Contribution
+become effective for each Contribution on the date the Contributor first
+distributes such Contribution.
+
+2.3. Limitations on Grant Scope
+
+The licenses granted in this Section 2 are the only rights granted under
+this License. No additional rights or licenses will be implied from the
+distribution or licensing of Covered Software under this License.
+Notwithstanding Section 2.1(b) above, no patent license is granted by a
+Contributor:
+
+(a) for any code that a Contributor has removed from Covered Software;
+    or
+
+(b) for infringements caused by: (i) Your and any other third party's
+    modifications of Covered Software, or (ii) the combination of its
+    Contributions with other software (except as part of its Contributor
+    Version); or
+
+(c) under Patent Claims infringed by Covered Software in the absence of
+    its Contributions.
+
+This License does not grant any rights in the trademarks, service marks,
+or logos of any Contributor (except as may be necessary to comply with
+the notice requirements in Section 3.4).
+
+2.4. Subsequent Licenses
+
+No Contributor makes additional grants as a result of Your choice to
+distribute the Covered Software under a subsequent version of this
+License (see Section 10.2) or under the terms of a Secondary License (if
+permitted under the terms of Section 3.3).
+
+2.5. Representation
+
+Each Contributor represents that the Contributor believes its
+Contributions are its original creation(s) or it has sufficient rights
+to grant the rights to its Contributions conveyed by this License.
+
+2.6. Fair Use
+
+This License is not intended to limit any rights You have under
+applicable copyright doctrines of fair use, fair dealing, or other
+equivalents.
+
+2.7. Conditions
+
+Sections 3.1, 3.2, 3.3, and 3.4 are conditions of the licenses granted
+in Section 2.1.
+
+3. Responsibilities
+-------------------
+
+3.1. Distribution of Source Form
+
+All distribution of Covered Software in Source Code Form, including any
+Modifications that You create or to which You contribute, must be under
+the terms of this License. You must inform recipients that the Source
+Code Form of the Covered Software is governed by the terms of this
+License, and how they can obtain a copy of this License. You may not
+attempt to alter or restrict the recipients' rights in the Source Code
+Form.
+
+3.2. Distribution of Executable Form
+
+If You distribute Covered Software in Executable Form then:
+
+(a) such Covered Software must also be made available in Source Code
+    Form, as described in Section 3.1, and You must inform recipients of
+    the Executable Form how they can obtain a copy of such Source Code
+    Form by reasonable means in a timely manner, at a charge no more
+    than the cost of distribution to the recipient; and
+
+(b) You may distribute such Executable Form under the terms of this
+    License, or sublicense it under different terms, provided that the
+    license for the Executable Form does not attempt to limit or alter
+    the recipients' rights in the Source Code Form under this License.
+
+3.3. Distribution of a Larger Work
+
+You may create and distribute a Larger Work under terms of Your choice,
+provided that You also comply with the requirements of this License for
+the Covered Software. If the Larger Work is a combination of Covered
+Software with a work governed by one or more Secondary Licenses, and the
+Covered Software is not Incompatible With Secondary Licenses, this
+License permits You to additionally distribute such Covered Software
+under the terms of such Secondary License(s), so that the recipient of
+the Larger Work may, at their option, further distribute the Covered
+Software under the terms of either this License or such Secondary
+License(s).
+
+3.4. Notices
+
+You may not remove or alter the substance of any license notices
+(including copyright notices, patent notices, disclaimers of warranty,
+or limitations of liability) contained within the Source Code Form of
+the Covered Software, except that You may alter any license notices to
+the extent required to remedy known factual inaccuracies.
+
+3.5. Application of Additional Terms
+
+You may choose to offer, and to charge a fee for, warranty, support,
+indemnity or liability obligations to one or more recipients of Covered
+Software. However, You may do so only on Your own behalf, and not on
+behalf of any Contributor. You must make it absolutely clear that any
+such warranty, support, indemnity, or liability obligation is offered by
+You alone, and You hereby agree to indemnify every Contributor for any
+liability incurred by such Contributor as a result of warranty, support,
+indemnity or liability terms You offer. You may include additional
+disclaimers of warranty and limitations of liability specific to any
+jurisdiction.
+
+4. Inability to Comply Due to Statute or Regulation
+---------------------------------------------------
+
+If it is impossible for You to comply with any of the terms of this
+License with respect to some or all of the Covered Software due to
+statute, judicial order, or regulation then You must: (a) comply with
+the terms of this License to the maximum extent possible; and (b)
+describe the limitations and the code they affect. Such description must
+be placed in a text file included with all distributions of the Covered
+Software under this License. Except to the extent prohibited by statute
+or regulation, such description must be sufficiently detailed for a
+recipient of ordinary skill to be able to understand it.
+
+5. Termination
+--------------
+
+5.1. The rights granted under this License will terminate automatically
+if You fail to comply with any of its terms. However, if You become
+compliant, then the rights granted under this License from a particular
+Contributor are reinstated (a) provisionally, unless and until such
+Contributor explicitly and finally terminates Your grants, and (b) on an
+ongoing basis, if such Contributor fails to notify You of the
+non-compliance by some reasonable means prior to 60 days after You have
+come back into compliance. Moreover, Your grants from a particular
+Contributor are reinstated on an ongoing basis if such Contributor
+notifies You of the non-compliance by some reasonable means, this is the
+first time You have received notice of non-compliance with this License
+from such Contributor, and You become compliant prior to 30 days after
+Your receipt of the notice.
+
+5.2. If You initiate litigation against any entity by asserting a patent
+infringement claim (excluding declaratory judgment actions,
+counter-claims, and cross-claims) alleging that a Contributor Version
+directly or indirectly infringes any patent, then the rights granted to
+You by any and all Contributors for the Covered Software under Section
+2.1 of this License shall terminate.
+
+5.3. In the event of termination under Sections 5.1 or 5.2 above, all
+end user license agreements (excluding distributors and resellers) which
+have been validly granted by You or Your distributors under this License
+prior to termination shall survive termination.
+
+************************************************************************
+*                                                                      *
+*  6. Disclaimer of Warranty                                           *
+*  -------------------------                                           *
+*                                                                      *
+*  Covered Software is provided under this License on an "as is"       *
+*  basis, without warranty of any kind, either expressed, implied, or  *
+*  statutory, including, without limitation, warranties that the       *
+*  Covered Software is free of defects, merchantable, fit for a        *
+*  particular purpose or non-infringing. The entire risk as to the     *
+*  quality and performance of the Covered Software is with You.        *
+*  Should any Covered Software prove defective in any respect, You     *
+*  (not any Contributor) assume the cost of any necessary servicing,   *
+*  repair, or correction. This disclaimer of warranty constitutes an   *
+*  essential part of this License. No use of any Covered Software is   *
+*  authorized under this License except under this disclaimer.         *
+*                                                                      *
+************************************************************************
+
+************************************************************************
+*                                                                      *
+*  7. Limitation of Liability                                          *
+*  --------------------------                                          *
+*                                                                      *
+*  Under no circumstances and under no legal theory, whether tort      *
+*  (including negligence), contract, or otherwise, shall any           *
+*  Contributor, or anyone who distributes Covered Software as          *
+*  permitted above, be liable to You for any direct, indirect,         *
+*  special, incidental, or consequential damages of any character      *
+*  including, without limitation, damages for lost profits, loss of    *
+*  goodwill, work stoppage, computer failure or malfunction, or any    *
+*  and all other commercial damages or losses, even if such party      *
+*  shall have been informed of the possibility of such damages. This   *
+*  limitation of liability shall not apply to liability for death or   *
+*  personal injury resulting from such party's negligence to the       *
+*  extent applicable law prohibits such limitation. Some               *
+*  jurisdictions do not allow the exclusion or limitation of           *
+*  incidental or consequential damages, so this exclusion and          *
+*  limitation may not apply to You.                                    *
+*                                                                      *
+************************************************************************
+
+8. Litigation
+-------------
+
+Any litigation relating to this License may be brought only in the
+courts of a jurisdiction where the defendant maintains its principal
+place of business and such litigation shall be governed by laws of that
+jurisdiction, without reference to its conflict-of-law provisions.
+Nothing in this Section shall prevent a party's ability to bring
+cross-claims or counter-claims.
+
+9. Miscellaneous
+----------------
+
+This License represents the complete agreement concerning the subject
+matter hereof. If any provision of this License is held to be
+unenforceable, such provision shall be reformed only to the extent
+necessary to make it enforceable. Any law or regulation which provides
+that the language of a contract shall be construed against the drafter
+shall not be used to construe this License against a Contributor.
+
+10. Versions of the License
+---------------------------
+
+10.1. New Versions
+
+Mozilla Foundation is the license steward. Except as provided in Section
+10.3, no one other than the license steward has the right to modify or
+publish new versions of this License. Each version will be given a
+distinguishing version number.
+
+10.2. Effect of New Versions
+
+You may distribute the Covered Software under the terms of the version
+of the License under which You originally received the Covered Software,
+or under the terms of any subsequent version published by the license
+steward.
+
+10.3. Modified Versions
+
+If you create software not governed by this License, and you want to
+create a new license for such software, you may create and use a
+modified version of this License if you rename the license and remove
+any references to the name of the license steward (except to note that
+such modified license differs from this License).
+
+10.4. Distributing Source Code Form that is Incompatible With Secondary
+Licenses
+
+If You choose to distribute Source Code Form that is Incompatible With
+Secondary Licenses under the terms of this version of the License, the
+notice described in Exhibit B of this License must be attached.
+
+Exhibit A - Source Code Form License Notice
+-------------------------------------------
+
+  This Source Code Form is subject to the terms of the Mozilla Public
+  License, v. 2.0. If a copy of the MPL was not distributed with this
+  file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+If it is not possible or desirable to put the notice in a particular
+file, then You may include the notice in a location (such as a LICENSE
+file in a relevant directory) where a recipient would be likely to look
+for such a notice.
+
+You may add additional accurate notices of copyright ownership.
+
+Exhibit B - "Incompatible With Secondary Licenses" Notice
+---------------------------------------------------------
+
+  This Source Code Form is "Incompatible With Secondary Licenses", as
+  defined by the Mozilla Public License, v. 2.0.

COPYING.README

@@ -0,0 +1,18 @@
+Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
+  http://www.mozilla.org/MPL/2.0/
+  http://www.mozilla.org/MPL/2.0/FAQ.html
+
+Some files contain third-party code under BSD or LGPL licenses, whence the other
+COPYING.* files here.
+
+All the LGPL code is either LGPL 2.1-only, or LGPL 2.1-or-later.
+For this reason, the COPYING.LGPL file contains the LGPL 2.1 text.
+
+If you want to guarantee that the Eigen code that you are #including is licensed
+under the MPL2 and possibly more permissive licenses (like BSD), #define this
+preprocessor symbol:
+  EIGEN_MPL2_ONLY
+For example, with most compilers, you could add this to your project CXXFLAGS:
+  -DEIGEN_MPL2_ONLY
+This will cause a compilation error to be generated if you #include any code that is
+LGPL licensed.

CTestConfig.cmake

@@ -3,11 +3,11 @@
 ## project to incorporate the testing dashboard.
 ## # The following are required to uses Dart and the Cdash dashboard
 ##   ENABLE_TESTING()
-##   INCLUDE(Dart)
-set(CTEST_PROJECT_NAME "Eigen")
-set(CTEST_NIGHTLY_START_TIME "05:00:00 UTC")
+##   INCLUDE(CTest)
+set(CTEST_PROJECT_NAME "Eigen3.2")
+set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
 
 set(CTEST_DROP_METHOD "http")
-set(CTEST_DROP_SITE "www.cdash.org")
-set(CTEST_DROP_LOCATION "/CDashPublic/submit.php?project=Eigen")
+set(CTEST_DROP_SITE "manao.inria.fr")
+set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen3.2")
 set(CTEST_DROP_SITE_CDASH TRUE)

CTestCustom.cmake.in

@@ -0,0 +1,3 @@
+
+set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "2000")
+set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS   "2000")

Doxyfile

@@ -1,281 +0,0 @@
-# Doxyfile 1.5.3
-
-#---------------------------------------------------------------------------
-# Project related configuration options
-#---------------------------------------------------------------------------
-DOXYFILE_ENCODING      = UTF-8
-PROJECT_NAME           = Eigen
-PROJECT_NUMBER         = 2.0
-OUTPUT_DIRECTORY       = ./
-CREATE_SUBDIRS         = NO
-OUTPUT_LANGUAGE        = English
-BRIEF_MEMBER_DESC      = YES
-REPEAT_BRIEF           = YES
-ABBREVIATE_BRIEF       = "The $name class" \
-                         "The $name widget" \
-                         "The $name file" \
-                         is \
-                         provides \
-                         specifies \
-                         contains \
-                         represents \
-                         a \
-                         an \
-                         the
-ALWAYS_DETAILED_SEC    = NO
-INLINE_INHERITED_MEMB  = NO
-FULL_PATH_NAMES        = NO
-STRIP_FROM_PATH        = 
-STRIP_FROM_INC_PATH    = 
-SHORT_NAMES            = NO
-JAVADOC_AUTOBRIEF      = NO
-QT_AUTOBRIEF           = NO
-MULTILINE_CPP_IS_BRIEF = NO
-DETAILS_AT_TOP         = NO
-INHERIT_DOCS           = YES
-SEPARATE_MEMBER_PAGES  = NO
-TAB_SIZE               = 8
-ALIASES                = 
-OPTIMIZE_OUTPUT_FOR_C  = NO
-OPTIMIZE_OUTPUT_JAVA   = NO
-BUILTIN_STL_SUPPORT    = NO
-CPP_CLI_SUPPORT        = NO
-DISTRIBUTE_GROUP_DOC   = NO
-SUBGROUPING            = YES
-#---------------------------------------------------------------------------
-# Build related configuration options
-#---------------------------------------------------------------------------
-EXTRACT_ALL            = NO
-EXTRACT_PRIVATE        = NO
-EXTRACT_STATIC         = NO
-EXTRACT_LOCAL_CLASSES  = NO
-EXTRACT_LOCAL_METHODS  = NO
-EXTRACT_ANON_NSPACES   = NO
-HIDE_UNDOC_MEMBERS     = YES
-HIDE_UNDOC_CLASSES     = YES
-HIDE_FRIEND_COMPOUNDS  = YES
-HIDE_IN_BODY_DOCS      = NO
-INTERNAL_DOCS          = NO
-CASE_SENSE_NAMES       = YES
-HIDE_SCOPE_NAMES       = YES
-SHOW_INCLUDE_FILES     = YES
-INLINE_INFO            = YES
-SORT_MEMBER_DOCS       = YES
-SORT_BRIEF_DOCS        = NO
-SORT_BY_SCOPE_NAME     = NO
-GENERATE_TODOLIST      = YES
-GENERATE_TESTLIST      = YES
-GENERATE_BUGLIST       = YES
-GENERATE_DEPRECATEDLIST= YES
-ENABLED_SECTIONS       = 
-MAX_INITIALIZER_LINES  = 30
-SHOW_USED_FILES        = YES
-SHOW_DIRECTORIES       = NO
-FILE_VERSION_FILTER    = 
-#---------------------------------------------------------------------------
-# configuration options related to warning and progress messages
-#---------------------------------------------------------------------------
-QUIET                  = NO
-WARNINGS               = YES
-WARN_IF_UNDOCUMENTED   = YES
-WARN_IF_DOC_ERROR      = YES
-WARN_NO_PARAMDOC       = NO
-WARN_FORMAT            = "$file:$line: $text"
-WARN_LOGFILE           = 
-#---------------------------------------------------------------------------
-# configuration options related to the input files
-#---------------------------------------------------------------------------
-INPUT                  = ./
-INPUT_ENCODING         = UTF-8
-FILE_PATTERNS          = *.c \
-                         *.cc \
-                         *.cxx \
-                         *.cpp \
-                         *.c++ \
-                         *.d \
-                         *.java \
-                         *.ii \
-                         *.ixx \
-                         *.ipp \
-                         *.i++ \
-                         *.inl \
-                         *.h \
-                         *.hh \
-                         *.hxx \
-                         *.hpp \
-                         *.h++ \
-                         *.idl \
-                         *.odl \
-                         *.cs \
-                         *.php \
-                         *.php3 \
-                         *.inc \
-                         *.m \
-                         *.mm \
-                         *.dox \
-                         *.py \
-                         *.C \
-                         *.CC \
-                         *.C++ \
-                         *.II \
-                         *.I++ \
-                         *.H \
-                         *.HH \
-                         *.H++ \
-                         *.CS \
-                         *.PHP \
-                         *.PHP3 \
-                         *.M \
-                         *.MM \
-                         *.PY
-RECURSIVE              = NO
-EXCLUDE                = 
-EXCLUDE_SYMLINKS       = NO
-EXCLUDE_PATTERNS       = 
-EXCLUDE_SYMBOLS        = 
-EXAMPLE_PATH           = doc/examples/
-EXAMPLE_PATTERNS       = *
-EXAMPLE_RECURSIVE      = NO
-IMAGE_PATH             = 
-INPUT_FILTER           = 
-FILTER_PATTERNS        = 
-FILTER_SOURCE_FILES    = NO
-#---------------------------------------------------------------------------
-# configuration options related to source browsing
-#---------------------------------------------------------------------------
-SOURCE_BROWSER         = NO
-INLINE_SOURCES         = NO
-STRIP_CODE_COMMENTS    = YES
-REFERENCED_BY_RELATION = YES
-REFERENCES_RELATION    = YES
-REFERENCES_LINK_SOURCE = YES
-USE_HTAGS              = NO
-VERBATIM_HEADERS       = YES
-#---------------------------------------------------------------------------
-# configuration options related to the alphabetical class index
-#---------------------------------------------------------------------------
-ALPHABETICAL_INDEX     = NO
-COLS_IN_ALPHA_INDEX    = 5
-IGNORE_PREFIX          = 
-#---------------------------------------------------------------------------
-# configuration options related to the HTML output
-#---------------------------------------------------------------------------
-GENERATE_HTML          = YES
-HTML_OUTPUT            = html
-HTML_FILE_EXTENSION    = .html
-HTML_HEADER            = 
-HTML_FOOTER            = 
-HTML_STYLESHEET        = 
-HTML_ALIGN_MEMBERS     = YES
-GENERATE_HTMLHELP      = NO
-HTML_DYNAMIC_SECTIONS  = NO
-CHM_FILE               = 
-HHC_LOCATION           = 
-GENERATE_CHI           = NO
-BINARY_TOC             = NO
-TOC_EXPAND             = NO
-DISABLE_INDEX          = NO
-ENUM_VALUES_PER_LINE   = 4
-GENERATE_TREEVIEW      = NO
-TREEVIEW_WIDTH         = 250
-#---------------------------------------------------------------------------
-# configuration options related to the LaTeX output
-#---------------------------------------------------------------------------
-GENERATE_LATEX         = YES
-LATEX_OUTPUT           = latex
-LATEX_CMD_NAME         = latex
-MAKEINDEX_CMD_NAME     = makeindex
-COMPACT_LATEX          = NO
-PAPER_TYPE             = a4wide
-EXTRA_PACKAGES         = 
-LATEX_HEADER           = 
-PDF_HYPERLINKS         = NO
-USE_PDFLATEX           = NO
-LATEX_BATCHMODE        = NO
-LATEX_HIDE_INDICES     = NO
-#---------------------------------------------------------------------------
-# configuration options related to the RTF output
-#---------------------------------------------------------------------------
-GENERATE_RTF           = NO
-RTF_OUTPUT             = rtf
-COMPACT_RTF            = NO
-RTF_HYPERLINKS         = NO
-RTF_STYLESHEET_FILE    = 
-RTF_EXTENSIONS_FILE    = 
-#---------------------------------------------------------------------------
-# configuration options related to the man page output
-#---------------------------------------------------------------------------
-GENERATE_MAN           = NO
-MAN_OUTPUT             = man
-MAN_EXTENSION          = .3
-MAN_LINKS              = NO
-#---------------------------------------------------------------------------
-# configuration options related to the XML output
-#---------------------------------------------------------------------------
-GENERATE_XML           = NO
-XML_OUTPUT             = xml
-XML_SCHEMA             = 
-XML_DTD                = 
-XML_PROGRAMLISTING     = YES
-#---------------------------------------------------------------------------
-# configuration options for the AutoGen Definitions output
-#---------------------------------------------------------------------------
-GENERATE_AUTOGEN_DEF   = NO
-#---------------------------------------------------------------------------
-# configuration options related to the Perl module output
-#---------------------------------------------------------------------------
-GENERATE_PERLMOD       = NO
-PERLMOD_LATEX          = NO
-PERLMOD_PRETTY         = YES
-PERLMOD_MAKEVAR_PREFIX = 
-#---------------------------------------------------------------------------
-# Configuration options related to the preprocessor   
-#---------------------------------------------------------------------------
-ENABLE_PREPROCESSING   = YES
-MACRO_EXPANSION        = NO
-EXPAND_ONLY_PREDEF     = NO
-SEARCH_INCLUDES        = YES
-INCLUDE_PATH           = 
-INCLUDE_FILE_PATTERNS  = 
-PREDEFINED             = 
-EXPAND_AS_DEFINED      = 
-SKIP_FUNCTION_MACROS   = YES
-#---------------------------------------------------------------------------
-# Configuration::additions related to external references   
-#---------------------------------------------------------------------------
-TAGFILES               = 
-GENERATE_TAGFILE       = 
-ALLEXTERNALS           = NO
-EXTERNAL_GROUPS        = YES
-PERL_PATH              = /usr/bin/perl
-#---------------------------------------------------------------------------
-# Configuration options related to the dot tool   
-#---------------------------------------------------------------------------
-CLASS_DIAGRAMS         = YES
-MSCGEN_PATH            = 
-HIDE_UNDOC_RELATIONS   = YES
-HAVE_DOT               = YES
-CLASS_GRAPH            = YES
-COLLABORATION_GRAPH    = YES
-GROUP_GRAPHS           = YES
-UML_LOOK               = NO
-TEMPLATE_RELATIONS     = NO
-INCLUDE_GRAPH          = YES
-INCLUDED_BY_GRAPH      = YES
-CALL_GRAPH             = NO
-CALLER_GRAPH           = NO
-GRAPHICAL_HIERARCHY    = YES
-DIRECTORY_GRAPH        = YES
-DOT_IMAGE_FORMAT       = png
-DOT_PATH               = 
-DOTFILE_DIRS           = 
-DOT_GRAPH_MAX_NODES    = 50
-MAX_DOT_GRAPH_DEPTH    = 1000
-DOT_TRANSPARENT        = NO
-DOT_MULTI_TARGETS      = NO
-GENERATE_LEGEND        = YES
-DOT_CLEANUP            = YES
-#---------------------------------------------------------------------------
-# Configuration::additions related to the search engine   
-#---------------------------------------------------------------------------
-SEARCHENGINE           = NO

Eigen/Array

@@ -1,39 +1,11 @@
 #ifndef EIGEN_ARRAY_MODULE_H
 #define EIGEN_ARRAY_MODULE_H
 
+// include Core first to handle Eigen2 support macros
 #include "Core"
 
-#include "src/Core/util/DisableMSVCWarnings.h"
-
-namespace Eigen {
-
-/** \defgroup Array_Module Array module
-  * This module provides several handy features to manipulate matrices as simple array of values.
-  * In addition to listed classes, it defines various methods of the Cwise interface
-  * (accessible from MatrixBase::cwise()), including:
-  *  - matrix-scalar sum,
-  *  - coeff-wise comparison operators,
-  *  - sin, cos, sqrt, pow, exp, log, square, cube, inverse (reciprocal).
-  *
-  * This module also provides various MatrixBase methods, including:
-  *  - \ref MatrixBase::all() "all", \ref MatrixBase::any() "any",
-  *  - \ref MatrixBase::Random() "random matrix initialization"
-  *
-  * \code
-  * #include <Eigen/Array>
-  * \endcode
-  */
-
-#include "src/Array/CwiseOperators.h"
-#include "src/Array/Functors.h"
-#include "src/Array/BooleanRedux.h"
-#include "src/Array/Select.h"
-#include "src/Array/PartialRedux.h"
-#include "src/Array/Random.h"
-#include "src/Array/Norms.h"
-
-} // namespace Eigen
-
-#include "src/Core/util/EnableMSVCWarnings.h"
+#ifndef EIGEN2_SUPPORT
+  #error The Eigen/Array header does no longer exist in Eigen3. All that functionality has moved to Eigen/Core.
+#endif
 
 #endif // EIGEN_ARRAY_MODULE_H

Eigen/CMakeLists.txt

@@ -1,34 +1,19 @@
-set(Eigen_HEADERS Core LU Cholesky QR Geometry Sparse Array SVD LeastSquares QtAlignedMalloc StdVector)
+include(RegexUtils)
+test_escape_string_as_regex()
 
-if(EIGEN_BUILD_LIB)
-    set(Eigen_SRCS
-      src/Core/CoreInstantiations.cpp
-      src/Cholesky/CholeskyInstantiations.cpp
-      src/QR/QrInstantiations.cpp
-    )
+file(GLOB Eigen_directory_files "*")
 
-    add_library(Eigen2 SHARED ${Eigen_SRCS})
+escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
 
-    install(TARGETS Eigen2
-            RUNTIME DESTINATION bin
-            LIBRARY DESTINATION lib
-            ARCHIVE DESTINATION lib)
-endif(EIGEN_BUILD_LIB)
-
-if(CMAKE_COMPILER_IS_GNUCXX)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g1 -O2")
-    set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "${CMAKE_CXX_FLAGS_RELWITHDEBINFO} -g1 -O2")
-endif(CMAKE_COMPILER_IS_GNUCXX)
-
-set(INCLUDE_INSTALL_DIR
-    "${CMAKE_INSTALL_PREFIX}/include/eigen2"
-    CACHE PATH
-    "The directory where we install the header files"
-    FORCE)
+foreach(f ${Eigen_directory_files})
+  if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/src")
+    list(APPEND Eigen_directory_files_to_install ${f})
+  endif()
+endforeach(f ${Eigen_directory_files})
 
 install(FILES
-  ${Eigen_HEADERS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen
+  ${Eigen_directory_files_to_install}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen COMPONENT Devel
   )
 
 add_subdirectory(src)

Eigen/Cholesky

@@ -3,22 +3,11 @@
 
 #include "Core"
 
-#include "src/Core/util/DisableMSVCWarnings.h"
-
-// Note that EIGEN_HIDE_HEAVY_CODE has to be defined per module
-#if (defined EIGEN_EXTERN_INSTANTIATIONS) && (EIGEN_EXTERN_INSTANTIATIONS>=2)
-  #ifndef EIGEN_HIDE_HEAVY_CODE
-  #define EIGEN_HIDE_HEAVY_CODE
-  #endif
-#elif defined EIGEN_HIDE_HEAVY_CODE
-  #undef EIGEN_HIDE_HEAVY_CODE
-#endif
-
-namespace Eigen {
+#include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup Cholesky_Module Cholesky module
   *
-  * \nonstableyet
+  *
   *
   * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
   * Those decompositions are accessible via the following MatrixBase methods:
@@ -30,36 +19,14 @@ namespace Eigen {
   * \endcode
   */
 
-#include "src/Array/CwiseOperators.h"
-#include "src/Array/Functors.h"
+#include "src/misc/Solve.h"
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
-
-} // namespace Eigen
-
-#define EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MATRIXTYPE,PREFIX) \
-  PREFIX template class Cholesky<MATRIXTYPE>; \
-  PREFIX template class CholeskyWithoutSquareRoot<MATRIXTYPE>
-
-#define EIGEN_CHOLESKY_MODULE_INSTANTIATE(PREFIX) \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix2f,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix2d,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix3f,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix3d,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix4f,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix4d,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXf,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXd,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXcf,PREFIX); \
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MatrixXcd,PREFIX)
-
-#ifdef EIGEN_EXTERN_INSTANTIATIONS
-
-namespace Eigen {
-  EIGEN_CHOLESKY_MODULE_INSTANTIATE(extern);
-} // namespace Eigen
+#ifdef EIGEN_USE_LAPACKE
+#include "src/Cholesky/LLT_MKL.h"
 #endif
 
-#include "src/Core/util/EnableMSVCWarnings.h"
+#include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_CHOLESKY_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/CholmodSupport

@@ -0,0 +1,45 @@
+#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H
+#define EIGEN_CHOLMODSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+extern "C" {
+  #include <cholmod.h>
+}
+
+/** \ingroup Support_modules
+  * \defgroup CholmodSupport_Module CholmodSupport module
+  *
+  * This module provides an interface to the Cholmod library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * It provides the two following main factorization classes:
+  * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
+  * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
+  *
+  * For the sake of completeness, this module also propose the two following classes:
+  * - class CholmodSimplicialLLT
+  * - class CholmodSimplicialLDLT
+  * Note that these classes does not bring any particular advantage compared to the built-in
+  * SimplicialLLT and SimplicialLDLT factorization classes.
+  *
+  * \code
+  * #include <Eigen/CholmodSupport>
+  * \endcode
+  *
+  * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies.
+  * The dependencies depend on how cholmod has been compiled.
+  * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/CholmodSupport/CholmodSupport.h"
+
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_CHOLMODSUPPORT_MODULE_H
+

Eigen/Core

@@ -1,8 +1,43 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2007-2011 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_CORE_H
 #define EIGEN_CORE_H
 
-// first thing Eigen does: prevent MSVC from committing suicide
-#include "src/Core/util/DisableMSVCWarnings.h"
+// first thing Eigen does: stop the compiler from committing suicide
+#include "src/Core/util/DisableStupidWarnings.h"
+
+// then include this file where all our macros are defined. It's really important to do it first because
+// it's where we do all the alignment settings (platform detection and honoring the user's will if he
+// defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization.
+#include "src/Core/util/Macros.h"
+
+// Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3)
+// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
+#if defined(__MINGW32__) && EIGEN_GNUC_AT_LEAST(4,6)
+  #pragma GCC optimize ("-fno-ipa-cp-clone")
+#endif
+
+#include <complex>
+
+// this include file manages BLAS and MKL related macros
+// and inclusion of their respective header files
+#include "src/Core/util/MKL_support.h"
+
+// if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into
+// account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks
+#if !EIGEN_ALIGN
+  #ifndef EIGEN_DONT_VECTORIZE
+    #define EIGEN_DONT_VECTORIZE
+  #endif
+#endif
 
 #ifdef _MSC_VER
   #include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
@@ -11,33 +46,74 @@
     // a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP.
     #if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(_M_X64)
       #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
-    #endif   
+    #endif
+  #endif
+#else
+  // Remember that usage of defined() in a #define is undefined by the standard
+  #if (defined __SSE2__) && ( (!defined __GNUC__) || (defined __INTEL_COMPILER) || EIGEN_GNUC_AT_LEAST(4,2) )
+    #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
   #endif
 #endif
 
-#ifdef __GNUC__
-  #define EIGEN_GNUC_AT_LEAST(x,y) ((__GNUC__>=x && __GNUC_MINOR__>=y) || __GNUC__>x)
-#else
-  #define EIGEN_GNUC_AT_LEAST(x,y) 0
-#endif
-
-// Remember that usage of defined() in a #define is undefined by the standard
-#if (defined __SSE2__) && ( (!defined __GNUC__) || EIGEN_GNUC_AT_LEAST(4,2) )
-  #define EIGEN_SSE2_BUT_NOT_OLD_GCC
-#endif
-
 #ifndef EIGEN_DONT_VECTORIZE
-  #if defined (EIGEN_SSE2_BUT_NOT_OLD_GCC) || defined(EIGEN_SSE2_ON_MSVC_2008_OR_LATER)
+
+  #if defined (EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC) || defined(EIGEN_SSE2_ON_MSVC_2008_OR_LATER)
+
+    // Defines symbols for compile-time detection of which instructions are
+    // used.
+    // EIGEN_VECTORIZE_YY is defined if and only if the instruction set YY is used
     #define EIGEN_VECTORIZE
     #define EIGEN_VECTORIZE_SSE
-    #include <emmintrin.h>
-    #include <xmmintrin.h>
+    #define EIGEN_VECTORIZE_SSE2
+
+    // Detect sse3/ssse3/sse4:
+    // gcc and icc defines __SSE3__, ...
+    // there is no way to know about this on msvc. You can define EIGEN_VECTORIZE_SSE* if you
+    // want to force the use of those instructions with msvc.
     #ifdef __SSE3__
-      #include <pmmintrin.h>
+      #define EIGEN_VECTORIZE_SSE3
     #endif
     #ifdef __SSSE3__
-      #include <tmmintrin.h>
+      #define EIGEN_VECTORIZE_SSSE3
     #endif
+    #ifdef __SSE4_1__
+      #define EIGEN_VECTORIZE_SSE4_1
+    #endif
+    #ifdef __SSE4_2__
+      #define EIGEN_VECTORIZE_SSE4_2
+    #endif
+
+    // include files
+
+    // This extern "C" works around a MINGW-w64 compilation issue
+    // https://sourceforge.net/tracker/index.php?func=detail&aid=3018394&group_id=202880&atid=983354
+    // In essence, intrin.h is included by windows.h and also declares intrinsics (just as emmintrin.h etc. below do).
+    // However, intrin.h uses an extern "C" declaration, and g++ thus complains of duplicate declarations
+    // with conflicting linkage.  The linkage for intrinsics doesn't matter, but at that stage the compiler doesn't know;
+    // so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too.
+    // notice that since these are C headers, the extern "C" is theoretically needed anyways.
+    extern "C" {
+      // In theory we should only include immintrin.h and not the other *mmintrin.h header files directly.
+      // Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus:
+      #if defined(__INTEL_COMPILER) && __INTEL_COMPILER >= 1110
+        #include <immintrin.h>
+      #else
+        #include <emmintrin.h>
+        #include <xmmintrin.h>
+        #ifdef  EIGEN_VECTORIZE_SSE3
+        #include <pmmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSSE3
+        #include <tmmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSE4_1
+        #include <smmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSE4_2
+        #include <nmmintrin.h>
+        #endif
+      #endif
+    } // end extern "C"
   #elif defined __ALTIVEC__
     #define EIGEN_VECTORIZE
     #define EIGEN_VECTORIZE_ALTIVEC
@@ -47,20 +123,53 @@
     #undef bool
     #undef vector
     #undef pixel
+  #elif defined  __ARM_NEON
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_NEON
+    #include <arm_neon.h>
   #endif
 #endif
 
+#if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
+  #define EIGEN_HAS_OPENMP
+#endif
+
+#ifdef EIGEN_HAS_OPENMP
+#include <omp.h>
+#endif
+
+// MSVC for windows mobile does not have the errno.h file
+#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
+#define EIGEN_HAS_ERRNO
+#endif
+
+#ifdef EIGEN_HAS_ERRNO
+#include <cerrno>
+#endif
+#include <cstddef>
 #include <cstdlib>
 #include <cmath>
-#include <complex>
 #include <cassert>
 #include <functional>
-#include <iostream>
+#include <iosfwd>
 #include <cstring>
 #include <string>
 #include <limits>
+#include <climits> // for CHAR_BIT
+// for min/max:
+#include <algorithm>
 
-#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(EIGEN_NO_EXCEPTIONS)
+// for outputting debug info
+#ifdef EIGEN_DEBUG_ASSIGN
+#include <iostream>
+#endif
+
+// required for __cpuid, needs to be included after cmath
+#if defined(_MSC_VER) && (defined(_M_IX86)||defined(_M_X64)) && (!defined(_WIN32_WCE))
+  #include <intrin.h>
+#endif
+
+#if defined(_CPPUNWIND) || defined(__EXCEPTIONS)
   #define EIGEN_EXCEPTIONS
 #endif
 
@@ -68,14 +177,66 @@
   #include <new>
 #endif
 
-// this needs to be done after all possible windows C header includes and before any Eigen source includes
-// (system C++ includes are supposed to be able to deal with this already):
-// windows.h defines min and max macros which would make Eigen fail to compile.
-#if defined(min) || defined(max)
-#error The preprocessor symbols 'min' or 'max' are defined. If you are compiling on Windows, do #define NOMINMAX to prevent windows.h from defining these symbols.
+/** \brief Namespace containing all symbols from the %Eigen library. */
+namespace Eigen {
+
+inline static const char *SimdInstructionSetsInUse(void) {
+#if defined(EIGEN_VECTORIZE_SSE4_2)
+  return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
+#elif defined(EIGEN_VECTORIZE_SSE4_1)
+  return "SSE, SSE2, SSE3, SSSE3, SSE4.1";
+#elif defined(EIGEN_VECTORIZE_SSSE3)
+  return "SSE, SSE2, SSE3, SSSE3";
+#elif defined(EIGEN_VECTORIZE_SSE3)
+  return "SSE, SSE2, SSE3";
+#elif defined(EIGEN_VECTORIZE_SSE2)
+  return "SSE, SSE2";
+#elif defined(EIGEN_VECTORIZE_ALTIVEC)
+  return "AltiVec";
+#elif defined(EIGEN_VECTORIZE_NEON)
+  return "ARM NEON";
+#else
+  return "None";
+#endif
+}
+
+} // end namespace Eigen
+
+#define STAGE10_FULL_EIGEN2_API             10
+#define STAGE20_RESOLVE_API_CONFLICTS       20
+#define STAGE30_FULL_EIGEN3_API             30
+#define STAGE40_FULL_EIGEN3_STRICTNESS      40
+#define STAGE99_NO_EIGEN2_SUPPORT           99
+
+#if   defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE40_FULL_EIGEN3_STRICTNESS
+#elif defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
+#elif defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE20_RESOLVE_API_CONFLICTS
+#elif defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE10_FULL_EIGEN2_API
+#elif defined EIGEN2_SUPPORT
+  // default to stage 3, that's what it's always meant
+  #define EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
+  #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
+#else
+  #define EIGEN2_SUPPORT_STAGE STAGE99_NO_EIGEN2_SUPPORT
 #endif
 
-namespace Eigen {
+#ifdef EIGEN2_SUPPORT
+#undef minor
+#endif
+
+// we use size_t frequently and we'll never remember to prepend it with std:: everytime just to
+// ensure QNX/QCC support
+using std::size_t;
+// gcc 4.6.0 wants std:: for ptrdiff_t 
+using std::ptrdiff_t;
 
 /** \defgroup Core_Module Core module
   * This is the main module of Eigen providing dense matrix and vector support
@@ -87,12 +248,11 @@ namespace Eigen {
   * \endcode
   */
 
-#include "src/Core/util/Macros.h"
 #include "src/Core/util/Constants.h"
 #include "src/Core/util/ForwardDeclarations.h"
 #include "src/Core/util/Meta.h"
-#include "src/Core/util/XprHelper.h"
 #include "src/Core/util/StaticAssert.h"
+#include "src/Core/util/XprHelper.h"
 #include "src/Core/util/Memory.h"
 
 #include "src/Core/NumTraits.h"
@@ -101,54 +261,116 @@ namespace Eigen {
 
 #if defined EIGEN_VECTORIZE_SSE
   #include "src/Core/arch/SSE/PacketMath.h"
+  #include "src/Core/arch/SSE/MathFunctions.h"
+  #include "src/Core/arch/SSE/Complex.h"
 #elif defined EIGEN_VECTORIZE_ALTIVEC
   #include "src/Core/arch/AltiVec/PacketMath.h"
+  #include "src/Core/arch/AltiVec/Complex.h"
+#elif defined EIGEN_VECTORIZE_NEON
+  #include "src/Core/arch/NEON/PacketMath.h"
+  #include "src/Core/arch/NEON/Complex.h"
 #endif
 
-#ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
-#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 16
-#endif
+#include "src/Core/arch/Default/Settings.h"
 
 #include "src/Core/Functors.h"
+#include "src/Core/DenseCoeffsBase.h"
+#include "src/Core/DenseBase.h"
 #include "src/Core/MatrixBase.h"
-#include "src/Core/Coeffs.h"
+#include "src/Core/EigenBase.h"
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN // work around Doxygen bug triggered by Assign.h r814874
                                 // at least confirmed with Doxygen 1.5.5 and 1.5.6
   #include "src/Core/Assign.h"
 #endif
 
-#include "src/Core/MatrixStorage.h"
+#include "src/Core/util/BlasUtil.h"
+#include "src/Core/DenseStorage.h"
 #include "src/Core/NestByValue.h"
-#include "src/Core/Flagged.h"
+#include "src/Core/ForceAlignedAccess.h"
+#include "src/Core/ReturnByValue.h"
+#include "src/Core/NoAlias.h"
+#include "src/Core/PlainObjectBase.h"
 #include "src/Core/Matrix.h"
-#include "src/Core/Cwise.h"
+#include "src/Core/Array.h"
 #include "src/Core/CwiseBinaryOp.h"
 #include "src/Core/CwiseUnaryOp.h"
 #include "src/Core/CwiseNullaryOp.h"
+#include "src/Core/CwiseUnaryView.h"
+#include "src/Core/SelfCwiseBinaryOp.h"
 #include "src/Core/Dot.h"
-#include "src/Core/Product.h"
-#include "src/Core/DiagonalProduct.h"
-#include "src/Core/SolveTriangular.h"
+#include "src/Core/StableNorm.h"
 #include "src/Core/MapBase.h"
+#include "src/Core/Stride.h"
 #include "src/Core/Map.h"
 #include "src/Core/Block.h"
-#include "src/Core/Minor.h"
+#include "src/Core/VectorBlock.h"
+#include "src/Core/Ref.h"
 #include "src/Core/Transpose.h"
 #include "src/Core/DiagonalMatrix.h"
-#include "src/Core/DiagonalCoeffs.h"
-#include "src/Core/Sum.h"
+#include "src/Core/Diagonal.h"
+#include "src/Core/DiagonalProduct.h"
+#include "src/Core/PermutationMatrix.h"
+#include "src/Core/Transpositions.h"
 #include "src/Core/Redux.h"
 #include "src/Core/Visitor.h"
 #include "src/Core/Fuzzy.h"
 #include "src/Core/IO.h"
 #include "src/Core/Swap.h"
 #include "src/Core/CommaInitializer.h"
-#include "src/Core/Part.h"
-#include "src/Core/CacheFriendlyProduct.h"
+#include "src/Core/Flagged.h"
+#include "src/Core/ProductBase.h"
+#include "src/Core/GeneralProduct.h"
+#include "src/Core/TriangularMatrix.h"
+#include "src/Core/SelfAdjointView.h"
+#include "src/Core/products/GeneralBlockPanelKernel.h"
+#include "src/Core/products/Parallelizer.h"
+#include "src/Core/products/CoeffBasedProduct.h"
+#include "src/Core/products/GeneralMatrixVector.h"
+#include "src/Core/products/GeneralMatrixMatrix.h"
+#include "src/Core/SolveTriangular.h"
+#include "src/Core/products/GeneralMatrixMatrixTriangular.h"
+#include "src/Core/products/SelfadjointMatrixVector.h"
+#include "src/Core/products/SelfadjointMatrixMatrix.h"
+#include "src/Core/products/SelfadjointProduct.h"
+#include "src/Core/products/SelfadjointRank2Update.h"
+#include "src/Core/products/TriangularMatrixVector.h"
+#include "src/Core/products/TriangularMatrixMatrix.h"
+#include "src/Core/products/TriangularSolverMatrix.h"
+#include "src/Core/products/TriangularSolverVector.h"
+#include "src/Core/BandMatrix.h"
+#include "src/Core/CoreIterators.h"
 
-} // namespace Eigen
+#include "src/Core/BooleanRedux.h"
+#include "src/Core/Select.h"
+#include "src/Core/VectorwiseOp.h"
+#include "src/Core/Random.h"
+#include "src/Core/Replicate.h"
+#include "src/Core/Reverse.h"
+#include "src/Core/ArrayBase.h"
+#include "src/Core/ArrayWrapper.h"
 
-#include "src/Core/util/EnableMSVCWarnings.h"
+#ifdef EIGEN_USE_BLAS
+#include "src/Core/products/GeneralMatrixMatrix_MKL.h"
+#include "src/Core/products/GeneralMatrixVector_MKL.h"
+#include "src/Core/products/GeneralMatrixMatrixTriangular_MKL.h"
+#include "src/Core/products/SelfadjointMatrixMatrix_MKL.h"
+#include "src/Core/products/SelfadjointMatrixVector_MKL.h"
+#include "src/Core/products/TriangularMatrixMatrix_MKL.h"
+#include "src/Core/products/TriangularMatrixVector_MKL.h"
+#include "src/Core/products/TriangularSolverMatrix_MKL.h"
+#endif // EIGEN_USE_BLAS
+
+#ifdef EIGEN_USE_MKL_VML
+#include "src/Core/Assign_MKL.h"
+#endif
+
+#include "src/Core/GlobalFunctions.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#ifdef EIGEN2_SUPPORT
+#include "Eigen2Support"
+#endif
 
 #endif // EIGEN_CORE_H

Eigen/Dense

@@ -0,0 +1,7 @@
+#include "Core"
+#include "LU"
+#include "Cholesky"
+#include "QR"
+#include "SVD"
+#include "Geometry"
+#include "Eigenvalues"

Eigen/Eigen

@@ -0,0 +1,2 @@
+#include "Dense"
+//#include "Sparse"

Eigen/Eigen2Support

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

Eigen/Eigenvalues

@@ -0,0 +1,48 @@
+#ifndef EIGEN_EIGENVALUES_MODULE_H
+#define EIGEN_EIGENVALUES_MODULE_H
+
+#include "Core"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+#include "Cholesky"
+#include "Jacobi"
+#include "Householder"
+#include "LU"
+#include "Geometry"
+
+/** \defgroup Eigenvalues_Module Eigenvalues module
+  *
+  *
+  *
+  * This module mainly provides various eigenvalue solvers.
+  * This module also provides some MatrixBase methods, including:
+  *  - MatrixBase::eigenvalues(),
+  *  - MatrixBase::operatorNorm()
+  *
+  * \code
+  * #include <Eigen/Eigenvalues>
+  * \endcode
+  */
+
+#include "src/Eigenvalues/Tridiagonalization.h"
+#include "src/Eigenvalues/RealSchur.h"
+#include "src/Eigenvalues/EigenSolver.h"
+#include "src/Eigenvalues/SelfAdjointEigenSolver.h"
+#include "src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h"
+#include "src/Eigenvalues/HessenbergDecomposition.h"
+#include "src/Eigenvalues/ComplexSchur.h"
+#include "src/Eigenvalues/ComplexEigenSolver.h"
+#include "src/Eigenvalues/RealQZ.h"
+#include "src/Eigenvalues/GeneralizedEigenSolver.h"
+#include "src/Eigenvalues/MatrixBaseEigenvalues.h"
+#ifdef EIGEN_USE_LAPACKE
+#include "src/Eigenvalues/RealSchur_MKL.h"
+#include "src/Eigenvalues/ComplexSchur_MKL.h"
+#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h"
+#endif
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_EIGENVALUES_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/Geometry

@@ -3,20 +3,19 @@
 
 #include "Core"
 
-#include "src/Core/util/DisableMSVCWarnings.h"
+#include "src/Core/util/DisableStupidWarnings.h"
 
-#include "Array"
+#include "SVD"
+#include "LU"
 #include <limits>
 
 #ifndef M_PI
 #define M_PI 3.14159265358979323846
 #endif
 
-namespace Eigen {
-
 /** \defgroup Geometry_Module Geometry module
   *
-  * \nonstableyet
+  *
   *
   * This module provides support for:
   *  - fixed-size homogeneous transformations
@@ -32,20 +31,33 @@ namespace Eigen {
   */
 
 #include "src/Geometry/OrthoMethods.h"
-#include "src/Geometry/RotationBase.h"
-#include "src/Geometry/Rotation2D.h"
-#include "src/Geometry/Quaternion.h"
-#include "src/Geometry/AngleAxis.h"
 #include "src/Geometry/EulerAngles.h"
-#include "src/Geometry/Transform.h"
-#include "src/Geometry/Translation.h"
-#include "src/Geometry/Scaling.h"
-#include "src/Geometry/Hyperplane.h"
-#include "src/Geometry/ParametrizedLine.h"
-#include "src/Geometry/AlignedBox.h"
 
-} // namespace Eigen
+#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
+  #include "src/Geometry/Homogeneous.h"
+  #include "src/Geometry/RotationBase.h"
+  #include "src/Geometry/Rotation2D.h"
+  #include "src/Geometry/Quaternion.h"
+  #include "src/Geometry/AngleAxis.h"
+  #include "src/Geometry/Transform.h"
+  #include "src/Geometry/Translation.h"
+  #include "src/Geometry/Scaling.h"
+  #include "src/Geometry/Hyperplane.h"
+  #include "src/Geometry/ParametrizedLine.h"
+  #include "src/Geometry/AlignedBox.h"
+  #include "src/Geometry/Umeyama.h"
 
-#include "src/Core/util/EnableMSVCWarnings.h"
+  #if defined EIGEN_VECTORIZE_SSE
+    #include "src/Geometry/arch/Geometry_SSE.h"
+  #endif
+#endif
+
+#ifdef EIGEN2_SUPPORT
+#include "src/Eigen2Support/Geometry/All.h"
+#endif
+
+#include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_GEOMETRY_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */
+

Eigen/Householder

@@ -0,0 +1,23 @@
+#ifndef EIGEN_HOUSEHOLDER_MODULE_H
+#define EIGEN_HOUSEHOLDER_MODULE_H
+
+#include "Core"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+/** \defgroup Householder_Module Householder module
+  * This module provides Householder transformations.
+  *
+  * \code
+  * #include <Eigen/Householder>
+  * \endcode
+  */
+
+#include "src/Householder/Householder.h"
+#include "src/Householder/HouseholderSequence.h"
+#include "src/Householder/BlockHouseholder.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_HOUSEHOLDER_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/IterativeLinearSolvers

@@ -0,0 +1,40 @@
+#ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
+#define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
+
+#include "SparseCore"
+#include "OrderingMethods"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+/** 
+  * \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module
+  *
+  * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
+  * Those solvers are accessible via the following classes:
+  *  - ConjugateGradient for selfadjoint (hermitian) matrices,
+  *  - BiCGSTAB for general square matrices.
+  *
+  * These iterative solvers are associated with some preconditioners:
+  *  - IdentityPreconditioner - not really useful
+  *  - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices.
+  *  - IncompleteILUT - incomplete LU factorization with dual thresholding
+  *
+  * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
+  *
+  * \code
+  * #include <Eigen/IterativeLinearSolvers>
+  * \endcode
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
+#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
+#include "src/IterativeLinearSolvers/ConjugateGradient.h"
+#include "src/IterativeLinearSolvers/BiCGSTAB.h"
+#include "src/IterativeLinearSolvers/IncompleteLUT.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H

Eigen/Jacobi

@@ -0,0 +1,26 @@
+#ifndef EIGEN_JACOBI_MODULE_H
+#define EIGEN_JACOBI_MODULE_H
+
+#include "Core"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+/** \defgroup Jacobi_Module Jacobi module
+  * This module provides Jacobi and Givens rotations.
+  *
+  * \code
+  * #include <Eigen/Jacobi>
+  * \endcode
+  *
+  * In addition to listed classes, it defines the two following MatrixBase methods to apply a Jacobi or Givens rotation:
+  *  - MatrixBase::applyOnTheLeft()
+  *  - MatrixBase::applyOnTheRight().
+  */
+
+#include "src/Jacobi/Jacobi.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_JACOBI_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */
+

Eigen/LU

@@ -3,9 +3,7 @@
 
 #include "Core"
 
-#include "src/Core/util/DisableMSVCWarnings.h"
-
-namespace Eigen {
+#include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup LU_Module LU module
   * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
@@ -18,12 +16,26 @@ namespace Eigen {
   * \endcode
   */
 
-#include "src/LU/LU.h"
+#include "src/misc/Solve.h"
+#include "src/misc/Kernel.h"
+#include "src/misc/Image.h"
+#include "src/LU/FullPivLU.h"
+#include "src/LU/PartialPivLU.h"
+#ifdef EIGEN_USE_LAPACKE
+#include "src/LU/PartialPivLU_MKL.h"
+#endif
 #include "src/LU/Determinant.h"
 #include "src/LU/Inverse.h"
 
-} // namespace Eigen
+#if defined EIGEN_VECTORIZE_SSE
+  #include "src/LU/arch/Inverse_SSE.h"
+#endif
 
-#include "src/Core/util/EnableMSVCWarnings.h"
+#ifdef EIGEN2_SUPPORT
+  #include "src/Eigen2Support/LU.h"
+#endif
+
+#include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_LU_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/LeastSquares

@@ -1,15 +1,20 @@
 #ifndef EIGEN_REGRESSION_MODULE_H
 #define EIGEN_REGRESSION_MODULE_H
 
+#ifndef EIGEN2_SUPPORT
+#error LeastSquares is only available in Eigen2 support mode (define EIGEN2_SUPPORT)
+#endif
+
+// exclude from normal eigen3-only documentation
+#ifdef EIGEN2_SUPPORT
+
 #include "Core"
 
-#include "src/Core/util/DisableMSVCWarnings.h"
+#include "src/Core/util/DisableStupidWarnings.h"
 
-#include "QR"
+#include "Eigenvalues"
 #include "Geometry"
 
-namespace Eigen {
-
 /** \defgroup LeastSquares_Module LeastSquares module
   * This module provides linear regression and related features.
   *
@@ -18,10 +23,10 @@ namespace Eigen {
   * \endcode
   */
 
-#include "src/LeastSquares/LeastSquares.h"
+#include "src/Eigen2Support/LeastSquares.h"
 
-} // namespace Eigen
+#include "src/Core/util/ReenableStupidWarnings.h"
 
-#include "src/Core/util/EnableMSVCWarnings.h"
+#endif // EIGEN2_SUPPORT
 
 #endif // EIGEN_REGRESSION_MODULE_H

Eigen/MetisSupport

@@ -0,0 +1,28 @@
+#ifndef EIGEN_METISSUPPORT_MODULE_H
+#define EIGEN_METISSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+extern "C" {
+#include <metis.h>
+}
+
+
+/** \ingroup Support_modules
+  * \defgroup MetisSupport_Module MetisSupport module
+  *
+  * \code
+  * #include <Eigen/MetisSupport>
+  * \endcode
+  * This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis). 
+  * It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink
+  */
+
+
+#include "src/MetisSupport/MetisSupport.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_METISSUPPORT_MODULE_H

Eigen/OrderingMethods

@@ -0,0 +1,66 @@
+#ifndef EIGEN_ORDERINGMETHODS_MODULE_H
+#define EIGEN_ORDERINGMETHODS_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+/** 
+  * \defgroup OrderingMethods_Module OrderingMethods module
+  *
+  * This module is currently for internal use only
+  * 
+  * It defines various built-in and external ordering methods for sparse matrices. 
+  * They are typically used to reduce the number of elements during 
+  * the sparse matrix decomposition (LLT, LU, QR).
+  * Precisely, in a preprocessing step, a permutation matrix P is computed using 
+  * those ordering methods and applied to the columns of the matrix. 
+  * Using for instance the sparse Cholesky decomposition, it is expected that 
+  * the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A).
+  * 
+  * 
+  * Usage : 
+  * \code
+  * #include <Eigen/OrderingMethods>
+  * \endcode
+  * 
+  * A simple usage is as a template parameter in the sparse decomposition classes : 
+  * 
+  * \code 
+  * SparseLU<MatrixType, COLAMDOrdering<int> > solver;
+  * \endcode 
+  * 
+  * \code 
+  * SparseQR<MatrixType, COLAMDOrdering<int> > solver;
+  * \endcode
+  * 
+  * It is possible as well to call directly a particular ordering method for your own purpose, 
+  * \code 
+  * AMDOrdering<int> ordering;
+  * PermutationMatrix<Dynamic, Dynamic, int> perm;
+  * SparseMatrix<double> A; 
+  * //Fill the matrix ...
+  * 
+  * ordering(A, perm); // Call AMD
+  * \endcode
+  * 
+  * \note Some of these methods (like AMD or METIS), need the sparsity pattern 
+  * of the input matrix to be symmetric. When the matrix is structurally unsymmetric, 
+  * Eigen computes internally the pattern of \f$A^T*A\f$ before calling the method.
+  * If your matrix is already symmetric (at leat in structure), you can avoid that
+  * by calling the method with a SelfAdjointView type.
+  * 
+  * \code
+  *  // Call the ordering on the pattern of the lower triangular matrix A
+  * ordering(A.selfadjointView<Lower>(), perm);
+  * \endcode
+  */
+
+#ifndef EIGEN_MPL2_ONLY
+#include "src/OrderingMethods/Amd.h"
+#endif
+
+#include "src/OrderingMethods/Ordering.h"
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_ORDERINGMETHODS_MODULE_H

Eigen/PaStiXSupport

@@ -0,0 +1,46 @@
+#ifndef EIGEN_PASTIXSUPPORT_MODULE_H
+#define EIGEN_PASTIXSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+#include <complex.h>
+extern "C" {
+#include <pastix_nompi.h>
+#include <pastix.h>
+}
+
+#ifdef complex
+#undef complex
+#endif
+
+/** \ingroup Support_modules
+  * \defgroup PaStiXSupport_Module PaStiXSupport module
+  * 
+  * This module provides an interface to the <a href="http://pastix.gforge.inria.fr/">PaSTiX</a> library.
+  * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver.
+  * It provides the two following main factorization classes:
+  * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization.
+  * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization.
+  * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern).
+  * 
+  * \code
+  * #include <Eigen/PaStiXSupport>
+  * \endcode
+  *
+  * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be linked to the PaSTiX library and its dependencies.
+  * The dependencies depend on how PaSTiX has been compiled.
+  * For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/PaStiXSupport/PaStiXSupport.h"
+
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_PASTIXSUPPORT_MODULE_H

Eigen/PardisoSupport

@@ -0,0 +1,30 @@
+#ifndef EIGEN_PARDISOSUPPORT_MODULE_H
+#define EIGEN_PARDISOSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+#include <mkl_pardiso.h>
+
+#include <unsupported/Eigen/SparseExtra>
+
+/** \ingroup Support_modules
+  * \defgroup PardisoSupport_Module PardisoSupport module
+  *
+  * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers.
+  *
+  * \code
+  * #include <Eigen/PardisoSupport>
+  * \endcode
+  *
+  * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be linked to the MKL library and its dependencies.
+  * See this \ref TopicUsingIntelMKL "page" for more information on MKL-Eigen integration.
+  * 
+  */
+
+#include "src/PardisoSupport/PardisoSupport.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_PARDISOSUPPORT_MODULE_H

Eigen/QR

@@ -3,71 +3,43 @@
 
 #include "Core"
 
-#include "src/Core/util/DisableMSVCWarnings.h"
+#include "src/Core/util/DisableStupidWarnings.h"
 
 #include "Cholesky"
-
-// Note that EIGEN_HIDE_HEAVY_CODE has to be defined per module
-#if (defined EIGEN_EXTERN_INSTANTIATIONS) && (EIGEN_EXTERN_INSTANTIATIONS>=2)
-  #ifndef EIGEN_HIDE_HEAVY_CODE
-  #define EIGEN_HIDE_HEAVY_CODE
-  #endif
-#elif defined EIGEN_HIDE_HEAVY_CODE
-  #undef EIGEN_HIDE_HEAVY_CODE
-#endif
-
-namespace Eigen {
+#include "Jacobi"
+#include "Householder"
 
 /** \defgroup QR_Module QR module
   *
-  * \nonstableyet
   *
-  * This module mainly provides QR decomposition and an eigen value solver.
+  *
+  * This module provides various QR decompositions
   * This module also provides some MatrixBase methods, including:
   *  - MatrixBase::qr(),
-  *  - MatrixBase::eigenvalues(),
-  *  - MatrixBase::operatorNorm()
   *
   * \code
   * #include <Eigen/QR>
   * \endcode
   */
 
-#include "src/QR/QR.h"
-#include "src/QR/Tridiagonalization.h"
-#include "src/QR/EigenSolver.h"
-#include "src/QR/SelfAdjointEigenSolver.h"
-#include "src/QR/HessenbergDecomposition.h"
+#include "src/misc/Solve.h"
+#include "src/QR/HouseholderQR.h"
+#include "src/QR/FullPivHouseholderQR.h"
+#include "src/QR/ColPivHouseholderQR.h"
+#ifdef EIGEN_USE_LAPACKE
+#include "src/QR/HouseholderQR_MKL.h"
+#include "src/QR/ColPivHouseholderQR_MKL.h"
+#endif
 
-// declare all classes for a given matrix type
-#define EIGEN_QR_MODULE_INSTANTIATE_TYPE(MATRIXTYPE,PREFIX) \
-  PREFIX template class QR<MATRIXTYPE>; \
-  PREFIX template class Tridiagonalization<MATRIXTYPE>; \
-  PREFIX template class HessenbergDecomposition<MATRIXTYPE>; \
-  PREFIX template class SelfAdjointEigenSolver<MATRIXTYPE>
+#ifdef EIGEN2_SUPPORT
+#include "src/Eigen2Support/QR.h"
+#endif
 
-// removed because it does not support complex yet
-//  PREFIX template class EigenSolver<MATRIXTYPE>
+#include "src/Core/util/ReenableStupidWarnings.h"
 
-// declare all class for all types
-#define EIGEN_QR_MODULE_INSTANTIATE(PREFIX) \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix2f,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix2d,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix3f,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix3d,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix4f,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(Matrix4d,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXf,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXd,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXcf,PREFIX); \
-  EIGEN_QR_MODULE_INSTANTIATE_TYPE(MatrixXcd,PREFIX)
-
-#ifdef EIGEN_EXTERN_INSTANTIATIONS
-  EIGEN_QR_MODULE_INSTANTIATE(extern);
-#endif // EIGEN_EXTERN_INSTANTIATIONS
-
-} // namespace Eigen
-
-#include "src/Core/util/EnableMSVCWarnings.h"
+#ifdef EIGEN2_SUPPORT
+#include "Eigenvalues"
+#endif
 
 #endif // EIGEN_QR_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/QtAlignedMalloc

@@ -6,24 +6,29 @@
 
 #if (!EIGEN_MALLOC_ALREADY_ALIGNED)
 
-inline void *qMalloc(size_t size)
+#include "src/Core/util/DisableStupidWarnings.h"
+
+void *qMalloc(size_t size)
 {
-  return Eigen::ei_aligned_malloc(size);
+  return Eigen::internal::aligned_malloc(size);
 }
 
-inline void qFree(void *ptr)
+void qFree(void *ptr)
 {
-  Eigen::ei_aligned_free(ptr);
+  Eigen::internal::aligned_free(ptr);
 }
 
-inline void *qRealloc(void *ptr, size_t size)
+void *qRealloc(void *ptr, size_t size)
 {
-  void* newPtr = Eigen::ei_aligned_malloc(size);
+  void* newPtr = Eigen::internal::aligned_malloc(size);
   memcpy(newPtr, ptr, size);
-  Eigen::ei_aligned_free(ptr);
+  Eigen::internal::aligned_free(ptr);
   return newPtr;
 }
 
+#include "src/Core/util/ReenableStupidWarnings.h"
+
 #endif
 
 #endif // EIGEN_QTMALLOC_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/SPQRSupport

@@ -0,0 +1,29 @@
+#ifndef EIGEN_SPQRSUPPORT_MODULE_H
+#define EIGEN_SPQRSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+#include "SuiteSparseQR.hpp"
+
+/** \ingroup Support_modules
+  * \defgroup SPQRSupport_Module SuiteSparseQR module
+  * 
+  * This module provides an interface to the SPQR library, which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  *
+  * \code
+  * #include <Eigen/SPQRSupport>
+  * \endcode
+  *
+  * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...).
+  * For a cmake based project, you can use our FindSPQR.cmake and FindCholmod.Cmake modules
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+#include "src/CholmodSupport/CholmodSupport.h"
+#include "src/SPQRSupport/SuiteSparseQRSupport.h"
+
+#endif

Eigen/SVD

@@ -1,29 +1,37 @@
 #ifndef EIGEN_SVD_MODULE_H
 #define EIGEN_SVD_MODULE_H
 
-#include "Core"
+#include "QR"
+#include "Householder"
+#include "Jacobi"
 
-#include "src/Core/util/DisableMSVCWarnings.h"
-
-namespace Eigen {
+#include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup SVD_Module SVD module
   *
-  * \nonstableyet
   *
-  * This module provides SVD decomposition for (currently) real matrices.
+  *
+  * This module provides SVD decomposition for matrices (both real and complex).
   * This decomposition is accessible via the following MatrixBase method:
-  *  - MatrixBase::svd()
+  *  - MatrixBase::jacobiSvd()
   *
   * \code
   * #include <Eigen/SVD>
   * \endcode
   */
 
-#include "src/SVD/SVD.h"
+#include "src/misc/Solve.h"
+#include "src/SVD/JacobiSVD.h"
+#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
+#include "src/SVD/JacobiSVD_MKL.h"
+#endif
+#include "src/SVD/UpperBidiagonalization.h"
 
-} // namespace Eigen
+#ifdef EIGEN2_SUPPORT
+#include "src/Eigen2Support/SVD.h"
+#endif
 
-#include "src/Core/util/EnableMSVCWarnings.h"
+#include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_SVD_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/Sparse

@@ -1,130 +1,27 @@
 #ifndef EIGEN_SPARSE_MODULE_H
 #define EIGEN_SPARSE_MODULE_H
 
-#include "Core"
-
-#include "src/Core/util/DisableMSVCWarnings.h"
-
-#include <vector>
-#include <map>
-#include <cstdlib>
-#include <cstring>
-#include <algorithm>
-
-#ifdef EIGEN_GOOGLEHASH_SUPPORT
-  #include <google/dense_hash_map>
-#endif
-
-#ifdef EIGEN_CHOLMOD_SUPPORT
-  extern "C" {
-    #include "cholmod.h"
-  }
-#endif
-
-#ifdef EIGEN_TAUCS_SUPPORT
-
-  // taucs.h declares a lot of mess
-  #define isnan
-  #define finite
-  #define isinf
-  extern "C" {
-    #include "taucs.h"
-  }
-  #undef isnan
-  #undef finite
-  #undef isinf
-
-  #ifdef min
-    #undef min
-  #endif
-  #ifdef max
-    #undef max
-  #endif
-
-#endif
-
-#ifdef EIGEN_SUPERLU_SUPPORT
-  typedef int int_t;
-  #include "superlu/slu_Cnames.h"
-  #include "superlu/supermatrix.h"
-  #include "superlu/slu_util.h"
-
-  namespace SuperLU_S {
-  #include "superlu/slu_sdefs.h"
-  }
-  namespace SuperLU_D {
-  #include "superlu/slu_ddefs.h"
-  }
-  namespace SuperLU_C {
-  #include "superlu/slu_cdefs.h"
-  }
-  namespace SuperLU_Z {
-  #include "superlu/slu_zdefs.h"
-  }
-  namespace Eigen { struct SluMatrix; }
-#endif
-
-#ifdef EIGEN_UMFPACK_SUPPORT
-  #include "umfpack.h"
-#endif
-
-namespace Eigen {
-
-/** \defgroup Sparse_Module Sparse module
+/** \defgroup Sparse_Module Sparse meta-module
   *
-  * \nonstableyet
-  *
-  * See the \ref TutorialSparse "Sparse tutorial"
+  * Meta-module including all related modules:
+  * - \ref SparseCore_Module
+  * - \ref OrderingMethods_Module
+  * - \ref SparseCholesky_Module
+  * - \ref SparseLU_Module
+  * - \ref SparseQR_Module
+  * - \ref IterativeLinearSolvers_Module
   *
   * \code
-  * #include <Eigen/QR>
+  * #include <Eigen/Sparse>
   * \endcode
   */
 
-#include "src/Sparse/SparseUtil.h"
-#include "src/Sparse/SparseMatrixBase.h"
-#include "src/Sparse/CompressedStorage.h"
-#include "src/Sparse/AmbiVector.h"
-#include "src/Sparse/RandomSetter.h"
-#include "src/Sparse/SparseBlock.h"
-#include "src/Sparse/SparseMatrix.h"
-#include "src/Sparse/DynamicSparseMatrix.h"
-#include "src/Sparse/MappedSparseMatrix.h"
-#include "src/Sparse/SparseVector.h"
-#include "src/Sparse/CoreIterators.h"
-#include "src/Sparse/SparseTranspose.h"
-#include "src/Sparse/SparseCwise.h"
-#include "src/Sparse/SparseCwiseUnaryOp.h"
-#include "src/Sparse/SparseCwiseBinaryOp.h"
-#include "src/Sparse/SparseDot.h"
-#include "src/Sparse/SparseAssign.h"
-#include "src/Sparse/SparseRedux.h"
-#include "src/Sparse/SparseFuzzy.h"
-#include "src/Sparse/SparseFlagged.h"
-#include "src/Sparse/SparseProduct.h"
-#include "src/Sparse/TriangularSolver.h"
-#include "src/Sparse/SparseLLT.h"
-#include "src/Sparse/SparseLDLT.h"
-#include "src/Sparse/SparseLU.h"
-
-#ifdef EIGEN_CHOLMOD_SUPPORT
-# include "src/Sparse/CholmodSupport.h"
-#endif
-
-#ifdef EIGEN_TAUCS_SUPPORT
-# include "src/Sparse/TaucsSupport.h"
-#endif
-
-#ifdef EIGEN_SUPERLU_SUPPORT
-# include "src/Sparse/SuperLUSupport.h"
-#endif
-
-#ifdef EIGEN_UMFPACK_SUPPORT
-# include "src/Sparse/UmfPackSupport.h"
-#endif
-
-} // namespace Eigen
-
-#include "src/Core/util/EnableMSVCWarnings.h"
+#include "SparseCore"
+#include "OrderingMethods"
+#include "SparseCholesky"
+#include "SparseLU"
+#include "SparseQR"
+#include "IterativeLinearSolvers"
 
 #endif // EIGEN_SPARSE_MODULE_H
+

Eigen/SparseCholesky

@@ -0,0 +1,47 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2013 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSECHOLESKY_MODULE_H
+#define EIGEN_SPARSECHOLESKY_MODULE_H
+
+#include "SparseCore"
+#include "OrderingMethods"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+/** 
+  * \defgroup SparseCholesky_Module SparseCholesky module
+  *
+  * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) matrices.
+  * Those decompositions are accessible via the following classes:
+  *  - SimplicialLLt,
+  *  - SimplicialLDLt
+  *
+  * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
+  *
+  * \code
+  * #include <Eigen/SparseCholesky>
+  * \endcode
+  */
+
+#ifdef EIGEN_MPL2_ONLY
+#error The SparseCholesky module has nothing to offer in MPL2 only mode
+#endif
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+#include "src/SparseCholesky/SimplicialCholesky.h"
+
+#ifndef EIGEN_MPL2_ONLY
+#include "src/SparseCholesky/SimplicialCholesky_impl.h"
+#endif
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_SPARSECHOLESKY_MODULE_H

Eigen/SparseCore

@@ -0,0 +1,64 @@
+#ifndef EIGEN_SPARSECORE_MODULE_H
+#define EIGEN_SPARSECORE_MODULE_H
+
+#include "Core"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+#include <vector>
+#include <map>
+#include <cstdlib>
+#include <cstring>
+#include <algorithm>
+
+/** 
+  * \defgroup SparseCore_Module SparseCore module
+  *
+  * This module provides a sparse matrix representation, and basic associatd matrix manipulations
+  * and operations.
+  *
+  * See the \ref TutorialSparse "Sparse tutorial"
+  *
+  * \code
+  * #include <Eigen/SparseCore>
+  * \endcode
+  *
+  * This module depends on: Core.
+  */
+
+namespace Eigen {
+
+/** The type used to identify a general sparse storage. */
+struct Sparse {};
+
+}
+
+#include "src/SparseCore/SparseUtil.h"
+#include "src/SparseCore/SparseMatrixBase.h"
+#include "src/SparseCore/CompressedStorage.h"
+#include "src/SparseCore/AmbiVector.h"
+#include "src/SparseCore/SparseMatrix.h"
+#include "src/SparseCore/MappedSparseMatrix.h"
+#include "src/SparseCore/SparseVector.h"
+#include "src/SparseCore/SparseBlock.h"
+#include "src/SparseCore/SparseTranspose.h"
+#include "src/SparseCore/SparseCwiseUnaryOp.h"
+#include "src/SparseCore/SparseCwiseBinaryOp.h"
+#include "src/SparseCore/SparseDot.h"
+#include "src/SparseCore/SparsePermutation.h"
+#include "src/SparseCore/SparseRedux.h"
+#include "src/SparseCore/SparseFuzzy.h"
+#include "src/SparseCore/ConservativeSparseSparseProduct.h"
+#include "src/SparseCore/SparseSparseProductWithPruning.h"
+#include "src/SparseCore/SparseProduct.h"
+#include "src/SparseCore/SparseDenseProduct.h"
+#include "src/SparseCore/SparseDiagonalProduct.h"
+#include "src/SparseCore/SparseTriangularView.h"
+#include "src/SparseCore/SparseSelfAdjointView.h"
+#include "src/SparseCore/TriangularSolver.h"
+#include "src/SparseCore/SparseView.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_SPARSECORE_MODULE_H
+

Eigen/SparseLU

@@ -0,0 +1,49 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSELU_MODULE_H
+#define EIGEN_SPARSELU_MODULE_H
+
+#include "SparseCore"
+
+/** 
+  * \defgroup SparseLU_Module SparseLU module
+  * This module defines a supernodal factorization of general sparse matrices.
+  * The code is fully optimized for supernode-panel updates with specialized kernels.
+  * Please, see the documentation of the SparseLU class for more details.
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+// Ordering interface
+#include "OrderingMethods"
+
+#include "src/SparseLU/SparseLU_gemm_kernel.h"
+
+#include "src/SparseLU/SparseLU_Structs.h"
+#include "src/SparseLU/SparseLU_SupernodalMatrix.h"
+#include "src/SparseLU/SparseLUImpl.h"
+#include "src/SparseCore/SparseColEtree.h"
+#include "src/SparseLU/SparseLU_Memory.h"
+#include "src/SparseLU/SparseLU_heap_relax_snode.h"
+#include "src/SparseLU/SparseLU_relax_snode.h"
+#include "src/SparseLU/SparseLU_pivotL.h"
+#include "src/SparseLU/SparseLU_panel_dfs.h"
+#include "src/SparseLU/SparseLU_kernel_bmod.h"
+#include "src/SparseLU/SparseLU_panel_bmod.h"
+#include "src/SparseLU/SparseLU_column_dfs.h"
+#include "src/SparseLU/SparseLU_column_bmod.h"
+#include "src/SparseLU/SparseLU_copy_to_ucol.h"
+#include "src/SparseLU/SparseLU_pruneL.h"
+#include "src/SparseLU/SparseLU_Utils.h"
+#include "src/SparseLU/SparseLU.h"
+
+#endif // EIGEN_SPARSELU_MODULE_H

Eigen/SparseQR

@@ -0,0 +1,33 @@
+#ifndef EIGEN_SPARSEQR_MODULE_H
+#define EIGEN_SPARSEQR_MODULE_H
+
+#include "SparseCore"
+#include "OrderingMethods"
+#include "src/Core/util/DisableStupidWarnings.h"
+
+/** \defgroup SparseQR_Module SparseQR module
+  * \brief Provides QR decomposition for sparse matrices
+  * 
+  * This module provides a simplicial version of the left-looking Sparse QR decomposition. 
+  * The columns of the input matrix should be reordered to limit the fill-in during the 
+  * decomposition. Built-in methods (COLAMD, AMD) or external  methods (METIS) can be used to this end.
+  * See the \link OrderingMethods_Module OrderingMethods\endlink module for the list 
+  * of built-in and external ordering methods.
+  * 
+  * \code
+  * #include <Eigen/SparseQR>
+  * \endcode
+  * 
+  * 
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "OrderingMethods"
+#include "src/SparseCore/SparseColEtree.h"
+#include "src/SparseQR/SparseQR.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif

Eigen/StdDeque

@@ -0,0 +1,27 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_STDDEQUE_MODULE_H
+#define EIGEN_STDDEQUE_MODULE_H
+
+#include "Core"
+#include <deque>
+
+#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
+
+#define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)
+
+#else
+
+#include "src/StlSupport/StdDeque.h"
+
+#endif
+
+#endif // EIGEN_STDDEQUE_MODULE_H

Eigen/StdList

@@ -0,0 +1,26 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_STDLIST_MODULE_H
+#define EIGEN_STDLIST_MODULE_H
+
+#include "Core"
+#include <list>
+
+#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */    
+
+#define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)
+
+#else
+
+#include "src/StlSupport/StdList.h"
+
+#endif
+
+#endif // EIGEN_STDLIST_MODULE_H

Eigen/StdVector

@@ -1,133 +1,27 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
 #ifndef EIGEN_STDVECTOR_MODULE_H
 #define EIGEN_STDVECTOR_MODULE_H
 
-#if defined(_GLIBCXX_VECTOR) || defined(_VECTOR_)
-#error you must include Eigen/StdVector before std::vector
-#endif                                                    
+#include "Core"
+#include <vector>
 
-#ifndef EIGEN_GNUC_AT_LEAST
-#ifdef __GNUC__
-  #define EIGEN_GNUC_AT_LEAST(x,y) ((__GNUC__>=x && __GNUC_MINOR__>=y) || __GNUC__>x)
-#else
-  #define EIGEN_GNUC_AT_LEAST(x,y) 0
-#endif
-#endif
+#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
 
-#define vector std_vector
-#include <vector>        
-#undef vector
-
-namespace Eigen {
-
-template<typename T> class aligned_allocator;
-
-// meta programming to determine if a class has a given member
-struct ei_does_not_have_aligned_operator_new_marker_sizeof {int a[1];};
-struct ei_has_aligned_operator_new_marker_sizeof {int a[2];};
-
-template<typename ClassType>
-struct ei_has_aligned_operator_new {
-    template<typename T>
-    static ei_has_aligned_operator_new_marker_sizeof
-    test(T const *, typename T::ei_operator_new_marker_type const * = 0);
-    static ei_does_not_have_aligned_operator_new_marker_sizeof
-    test(...);
-
-    // note that the following indirection is needed for gcc-3.3
-    enum {ret =  sizeof(test(static_cast<ClassType*>(0))) 
-              == sizeof(ei_has_aligned_operator_new_marker_sizeof) };
-};
-
-#ifdef _MSC_VER
-  
-  // sometimes, MSVC detects, at compile time, that the argument x
-  // in std::vector::resize(size_t s,T x) won't be aligned and generate an error
-  // even if this function is never called. Whence this little wrapper.
-  #define _EIGEN_WORKAROUND_MSVC_STD_VECTOR(T) Eigen::ei_workaround_msvc_std_vector<T>
-  template<typename T> struct ei_workaround_msvc_std_vector : public T
-  {
-    inline ei_workaround_msvc_std_vector() : T() {}
-    inline ei_workaround_msvc_std_vector(const T& other) : T(other) {}
-    inline operator T& () { return *static_cast<T*>(this); }
-    inline operator const T& () const { return *static_cast<const T*>(this); }
-    template<typename OtherT>
-    inline T& operator=(const OtherT& other)
-    { T::operator=(other); return *this; }
-    inline ei_workaround_msvc_std_vector& operator=(const ei_workaround_msvc_std_vector& other)
-    { T::operator=(other); return *this; }
-  };
+#define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)
 
 #else
 
-  #define _EIGEN_WORKAROUND_MSVC_STD_VECTOR(T) T
+#include "src/StlSupport/StdVector.h"
 
 #endif
 
-}
-
-namespace std {
-
-#define EIGEN_STD_VECTOR_SPECIALIZATION_BODY \
-  public:  \
-    typedef T value_type; \
-    typedef typename vector_base::allocator_type allocator_type; \
-    typedef typename vector_base::size_type size_type;  \
-    typedef typename vector_base::iterator iterator;  \
-    explicit vector(const allocator_type& __a = allocator_type()) : vector_base(__a) {}  \
-    vector(const vector& c) : vector_base(c) {}  \
-    vector(size_type num, const value_type& val = value_type()) : vector_base(num, val) {} \
-    vector(iterator start, iterator end) : vector_base(start, end) {}  \
-    vector& operator=(const vector& __x) {  \
-      vector_base::operator=(__x);  \
-      return *this;  \
-    }
-
-template<typename T,
-         typename AllocT = std::allocator<T>,
-         bool HasAlignedNew = Eigen::ei_has_aligned_operator_new<T>::ret>
-class vector : public std::std_vector<T,AllocT>
-{
-  typedef std_vector<T, AllocT> vector_base;
-  EIGEN_STD_VECTOR_SPECIALIZATION_BODY
-};
-
-template<typename T,typename DummyAlloc>
-class vector<T,DummyAlloc,true>
-  : public std::std_vector<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T),
-                           Eigen::aligned_allocator<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T)> >          
-{
-  typedef std_vector<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T),
-                     Eigen::aligned_allocator<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T)> > vector_base;
-  EIGEN_STD_VECTOR_SPECIALIZATION_BODY
-
-  void resize(size_type __new_size)
-  { resize(__new_size, T()); }     
-
-  #if defined(_VECTOR_)
-  // workaround MSVC std::vector implementation
-  void resize(size_type __new_size, const value_type& __x)                 
-  {                                                              
-    if (vector_base::size() < __new_size)                                 
-      vector_base::_Insert_n(vector_base::end(), __new_size - vector_base::size(), __x);
-    else if (__new_size < vector_base::size())
-      vector_base::erase(vector_base::begin() + __new_size, vector_base::end());
-  }
-  #elif defined(_GLIBCXX_VECTOR) && EIGEN_GNUC_AT_LEAST(4,1)
-  // workaround GCC std::vector implementation
-  // Note that before gcc-4.1 we already have: std::vector::resize(size_type,const T&),
-  // no no need to workaround !
-  void resize(size_type __new_size, const value_type& __x)
-  {                                              
-    if (__new_size < vector_base::size())               
-      vector_base::_M_erase_at_end(this->_M_impl._M_start + __new_size);
-    else                       
-      vector_base::insert(vector_base::end(), __new_size - vector_base::size(), __x); 
-  }                                                              
-  #else
-  using vector_base::resize;
-  #endif  
-};
-
-}
-
 #endif // EIGEN_STDVECTOR_MODULE_H

Eigen/SuperLUSupport

@@ -0,0 +1,59 @@
+#ifndef EIGEN_SUPERLUSUPPORT_MODULE_H
+#define EIGEN_SUPERLUSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+#ifdef EMPTY
+#define EIGEN_EMPTY_WAS_ALREADY_DEFINED
+#endif
+
+typedef int int_t;
+#include <slu_Cnames.h>
+#include <supermatrix.h>
+#include <slu_util.h>
+
+// slu_util.h defines a preprocessor token named EMPTY which is really polluting,
+// so we remove it in favor of a SUPERLU_EMPTY token.
+// If EMPTY was already defined then we don't undef it.
+
+#if defined(EIGEN_EMPTY_WAS_ALREADY_DEFINED)
+# undef EIGEN_EMPTY_WAS_ALREADY_DEFINED
+#elif defined(EMPTY)
+# undef EMPTY
+#endif
+
+#define SUPERLU_EMPTY (-1)
+
+namespace Eigen { struct SluMatrix; }
+
+/** \ingroup Support_modules
+  * \defgroup SuperLUSupport_Module SuperLUSupport module
+  *
+  * This module provides an interface to the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library.
+  * It provides the following factorization class:
+  * - class SuperLU: a supernodal sequential LU factorization.
+  * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods).
+  *
+  * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting.
+  *
+  * \code
+  * #include <Eigen/SuperLUSupport>
+  * \endcode
+  *
+  * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be linked to the superlu library and its dependencies.
+  * The dependencies depend on how superlu has been compiled.
+  * For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/SuperLUSupport/SuperLUSupport.h"
+
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_SUPERLUSUPPORT_MODULE_H

Eigen/UmfPackSupport

@@ -0,0 +1,36 @@
+#ifndef EIGEN_UMFPACKSUPPORT_MODULE_H
+#define EIGEN_UMFPACKSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+extern "C" {
+#include <umfpack.h>
+}
+
+/** \ingroup Support_modules
+  * \defgroup UmfPackSupport_Module UmfPackSupport module
+  *
+  * This module provides an interface to the UmfPack library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * It provides the following factorization class:
+  * - class UmfPackLU: a multifrontal sequential LU factorization.
+  *
+  * \code
+  * #include <Eigen/UmfPackSupport>
+  * \endcode
+  *
+  * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies.
+  * The dependencies depend on how umfpack has been compiled.
+  * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/UmfPackSupport/UmfPackSupport.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_UMFPACKSUPPORT_MODULE_H

Eigen/src/Array/BooleanRedux.h

@@ -1,145 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_ALLANDANY_H
-#define EIGEN_ALLANDANY_H
-
-template<typename Derived, int UnrollCount>
-struct ei_all_unroller
-{
-  enum {
-    col = (UnrollCount-1) / Derived::RowsAtCompileTime,
-    row = (UnrollCount-1) % Derived::RowsAtCompileTime
-  };
-
-  inline static bool run(const Derived &mat)
-  {
-    return ei_all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col);
-  }
-};
-
-template<typename Derived>
-struct ei_all_unroller<Derived, 1>
-{
-  inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
-};
-
-template<typename Derived>
-struct ei_all_unroller<Derived, Dynamic>
-{
-  inline static bool run(const Derived &) { return false; }
-};
-
-template<typename Derived, int UnrollCount>
-struct ei_any_unroller
-{
-  enum {
-    col = (UnrollCount-1) / Derived::RowsAtCompileTime,
-    row = (UnrollCount-1) % Derived::RowsAtCompileTime
-  };
-
-  inline static bool run(const Derived &mat)
-  {
-    return ei_any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
-  }
-};
-
-template<typename Derived>
-struct ei_any_unroller<Derived, 1>
-{
-  inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
-};
-
-template<typename Derived>
-struct ei_any_unroller<Derived, Dynamic>
-{
-  inline static bool run(const Derived &) { return false; }
-};
-
-/** \array_module
-  * 
-  * \returns true if all coefficients are true
-  *
-  * \addexample CwiseAll \label How to check whether a point is inside a box (using operator< and all())
-  *
-  * Example: \include MatrixBase_all.cpp
-  * Output: \verbinclude MatrixBase_all.out
-  *
-  * \sa MatrixBase::any(), Cwise::operator<()
-  */
-template<typename Derived>
-inline bool MatrixBase<Derived>::all() const
-{
-  const bool unroll = SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost)
-                      <= EIGEN_UNROLLING_LIMIT;
-  if(unroll)
-    return ei_all_unroller<Derived,
-                           unroll ? int(SizeAtCompileTime) : Dynamic
-     >::run(derived());
-  else
-  {
-    for(int j = 0; j < cols(); ++j)
-      for(int i = 0; i < rows(); ++i)
-        if (!coeff(i, j)) return false;
-    return true;
-  }
-}
-
-/** \array_module
-  * 
-  * \returns true if at least one coefficient is true
-  *
-  * \sa MatrixBase::all()
-  */
-template<typename Derived>
-inline bool MatrixBase<Derived>::any() const
-{
-  const bool unroll = SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost)
-                      <= EIGEN_UNROLLING_LIMIT;
-  if(unroll)
-    return ei_any_unroller<Derived,
-                           unroll ? int(SizeAtCompileTime) : Dynamic
-           >::run(derived());
-  else
-  {
-    for(int j = 0; j < cols(); ++j)
-      for(int i = 0; i < rows(); ++i)
-        if (coeff(i, j)) return true;
-    return false;
-  }
-}
-
-/** \array_module
-  * 
-  * \returns the number of coefficients which evaluate to true
-  *
-  * \sa MatrixBase::all(), MatrixBase::any()
-  */
-template<typename Derived>
-inline int MatrixBase<Derived>::count() const
-{
-  return this->cast<bool>().cast<int>().sum();
-}
-
-#endif // EIGEN_ALLANDANY_H

Eigen/src/Array/CMakeLists.txt

@@ -1,6 +0,0 @@
-FILE(GLOB Eigen_Array_SRCS "*.h")
-
-INSTALL(FILES
-  ${Eigen_Array_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Array
-  )

Eigen/src/Array/CwiseOperators.h

@@ -1,453 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_ARRAY_CWISE_OPERATORS_H
-#define EIGEN_ARRAY_CWISE_OPERATORS_H
-
-// -- unary operators --
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise square root of *this.
-  *
-  * Example: \include Cwise_sqrt.cpp
-  * Output: \verbinclude Cwise_sqrt.out
-  *
-  * \sa pow(), square()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_sqrt_op)
-Cwise<ExpressionType>::sqrt() const
-{
-  return _expression();
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise exponential of *this.
-  *
-  * Example: \include Cwise_exp.cpp
-  * Output: \verbinclude Cwise_exp.out
-  *
-  * \sa pow(), log(), sin(), cos()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_exp_op)
-Cwise<ExpressionType>::exp() const
-{
-  return _expression();
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise logarithm of *this.
-  *
-  * Example: \include Cwise_log.cpp
-  * Output: \verbinclude Cwise_log.out
-  *
-  * \sa exp()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_log_op)
-Cwise<ExpressionType>::log() const
-{
-  return _expression();
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise cosine of *this.
-  *
-  * Example: \include Cwise_cos.cpp
-  * Output: \verbinclude Cwise_cos.out
-  *
-  * \sa sin(), exp()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_cos_op)
-Cwise<ExpressionType>::cos() const
-{
-  return _expression();
-}
-
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise sine of *this.
-  *
-  * Example: \include Cwise_sin.cpp
-  * Output: \verbinclude Cwise_sin.out
-  *
-  * \sa cos(), exp()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_sin_op)
-Cwise<ExpressionType>::sin() const
-{
-  return _expression();
-}
-
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise power of *this to the given exponent.
-  *
-  * Example: \include Cwise_pow.cpp
-  * Output: \verbinclude Cwise_pow.out
-  *
-  * \sa exp(), log()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_pow_op)
-Cwise<ExpressionType>::pow(const Scalar& exponent) const
-{
-  return EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_pow_op)(_expression(), ei_scalar_pow_op<Scalar>(exponent));
-}
-
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise inverse of *this.
-  *
-  * Example: \include Cwise_inverse.cpp
-  * Output: \verbinclude Cwise_inverse.out
-  *
-  * \sa operator/(), operator*()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_inverse_op)
-Cwise<ExpressionType>::inverse() const
-{
-  return _expression();
-}
-
-/** \array_module
-  *
-  * \returns an expression of the coefficient-wise square of *this.
-  *
-  * Example: \include Cwise_square.cpp
-  * Output: \verbinclude Cwise_square.out
-  *
-  * \sa operator/(), operator*(), abs2()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_square_op)
-Cwise<ExpressionType>::square() const
-{
-  return _expression();
-}
-
-/** \array_module
-  *
-  * \returns an expression of the coefficient-wise cube of *this.
-  *
-  * Example: \include Cwise_cube.cpp
-  * Output: \verbinclude Cwise_cube.out
-  *
-  * \sa square(), pow()
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_cube_op)
-Cwise<ExpressionType>::cube() const
-{
-  return _expression();
-}
-
-
-// -- binary operators --
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \< operator of *this and \a other
-  *
-  * Example: \include Cwise_less.cpp
-  * Output: \verbinclude Cwise_less.out
-  *
-  * \sa MatrixBase::all(), MatrixBase::any(), operator>(), operator<=()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)
-Cwise<ExpressionType>::operator<(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)(_expression(), other.derived());
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \<= operator of *this and \a other
-  *
-  * Example: \include Cwise_less_equal.cpp
-  * Output: \verbinclude Cwise_less_equal.out
-  *
-  * \sa MatrixBase::all(), MatrixBase::any(), operator>=(), operator<()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)
-Cwise<ExpressionType>::operator<=(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)(_expression(), other.derived());
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \> operator of *this and \a other
-  *
-  * Example: \include Cwise_greater.cpp
-  * Output: \verbinclude Cwise_greater.out
-  *
-  * \sa MatrixBase::all(), MatrixBase::any(), operator>=(), operator<()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)
-Cwise<ExpressionType>::operator>(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)(_expression(), other.derived());
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \>= operator of *this and \a other
-  *
-  * Example: \include Cwise_greater_equal.cpp
-  * Output: \verbinclude Cwise_greater_equal.out
-  *
-  * \sa MatrixBase::all(), MatrixBase::any(), operator>(), operator<=()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)
-Cwise<ExpressionType>::operator>=(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)(_expression(), other.derived());
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise == operator of *this and \a other
-  *
-  * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
-  * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
-  * generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
-  * MatrixBase::isMuchSmallerThan().
-  *
-  * Example: \include Cwise_equal_equal.cpp
-  * Output: \verbinclude Cwise_equal_equal.out
-  *
-  * \sa MatrixBase::all(), MatrixBase::any(), MatrixBase::isApprox(), MatrixBase::isMuchSmallerThan()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)
-Cwise<ExpressionType>::operator==(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)(_expression(), other.derived());
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise != operator of *this and \a other
-  *
-  * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
-  * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
-  * generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
-  * MatrixBase::isMuchSmallerThan().
-  *
-  * Example: \include Cwise_not_equal.cpp
-  * Output: \verbinclude Cwise_not_equal.out
-  *
-  * \sa MatrixBase::all(), MatrixBase::any(), MatrixBase::isApprox(), MatrixBase::isMuchSmallerThan()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline const EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)
-Cwise<ExpressionType>::operator!=(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)(_expression(), other.derived());
-}
-
-// comparisons to scalar value
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \< operator of *this and a scalar \a s
-  *
-  * \sa operator<(const MatrixBase<OtherDerived> &) const
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)
-Cwise<ExpressionType>::operator<(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \<= operator of *this and a scalar \a s
-  *
-  * \sa operator<=(const MatrixBase<OtherDerived> &) const
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)
-Cwise<ExpressionType>::operator<=(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \> operator of *this and a scalar \a s
-  *
-  * \sa operator>(const MatrixBase<OtherDerived> &) const
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)
-Cwise<ExpressionType>::operator>(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise \>= operator of *this and a scalar \a s
-  *
-  * \sa operator>=(const MatrixBase<OtherDerived> &) const
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)
-Cwise<ExpressionType>::operator>=(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise == operator of *this and a scalar \a s
-  *
-  * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
-  * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
-  * generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
-  * MatrixBase::isMuchSmallerThan().
-  *
-  * \sa operator==(const MatrixBase<OtherDerived> &) const
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)
-Cwise<ExpressionType>::operator==(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-/** \array_module
-  * 
-  * \returns an expression of the coefficient-wise != operator of *this and a scalar \a s
-  *
-  * \warning this performs an exact comparison, which is generally a bad idea with floating-point types.
-  * In order to check for equality between two vectors or matrices with floating-point coefficients, it is
-  * generally a far better idea to use a fuzzy comparison as provided by MatrixBase::isApprox() and
-  * MatrixBase::isMuchSmallerThan().
-  *
-  * \sa operator!=(const MatrixBase<OtherDerived> &) const
-  */
-template<typename ExpressionType>
-inline const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)
-Cwise<ExpressionType>::operator!=(Scalar s) const
-{
-  return EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)(_expression(),
-            typename ExpressionType::ConstantReturnType(_expression().rows(), _expression().cols(), s));
-}
-
-// scalar addition
-
-/** \array_module
-  *
-  * \returns an expression of \c *this with each coeff incremented by the constant \a scalar
-  *
-  * Example: \include Cwise_plus.cpp
-  * Output: \verbinclude Cwise_plus.out
-  *
-  * \sa operator+=(), operator-()
-  */
-template<typename ExpressionType>
-inline const typename Cwise<ExpressionType>::ScalarAddReturnType
-Cwise<ExpressionType>::operator+(const Scalar& scalar) const
-{
-  return typename Cwise<ExpressionType>::ScalarAddReturnType(m_matrix, ei_scalar_add_op<Scalar>(scalar));
-}
-
-/** \array_module
-  *
-  * Adds the given \a scalar to each coeff of this expression.
-  *
-  * Example: \include Cwise_plus_equal.cpp
-  * Output: \verbinclude Cwise_plus_equal.out
-  *
-  * \sa operator+(), operator-=()
-  */
-template<typename ExpressionType>
-inline ExpressionType& Cwise<ExpressionType>::operator+=(const Scalar& scalar)
-{
-  return m_matrix.const_cast_derived() = *this + scalar;
-}
-
-/** \array_module
-  *
-  * \returns an expression of \c *this with each coeff decremented by the constant \a scalar
-  *
-  * Example: \include Cwise_minus.cpp
-  * Output: \verbinclude Cwise_minus.out
-  *
-  * \sa operator+(), operator-=()
-  */
-template<typename ExpressionType>
-inline const typename Cwise<ExpressionType>::ScalarAddReturnType
-Cwise<ExpressionType>::operator-(const Scalar& scalar) const
-{
-  return *this + (-scalar);
-}
-
-/** \array_module
-  *
-  * Substracts the given \a scalar from each coeff of this expression.
-  *
-  * Example: \include Cwise_minus_equal.cpp
-  * Output: \verbinclude Cwise_minus_equal.out
-  *
-  * \sa operator+=(), operator-()
-  */
-
-template<typename ExpressionType>
-inline ExpressionType& Cwise<ExpressionType>::operator-=(const Scalar& scalar)
-{
-  return m_matrix.const_cast_derived() = *this - scalar;
-}
-
-#endif // EIGEN_ARRAY_CWISE_OPERATORS_H

Eigen/src/Array/Functors.h

@@ -1,305 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_ARRAY_FUNCTORS_H
-#define EIGEN_ARRAY_FUNCTORS_H
-
-/** \internal
-  * \array_module
-  *
-  * \brief Template functor to add a scalar to a fixed other one
-  *
-  * \sa class CwiseUnaryOp, Array::operator+
-  */
-/* If you wonder why doing the ei_pset1() in packetOp() is an optimization check ei_scalar_multiple_op */
-template<typename Scalar>
-struct ei_scalar_add_op {
-  typedef typename ei_packet_traits<Scalar>::type PacketScalar;
-  // FIXME default copy constructors seems bugged with std::complex<>
-  inline ei_scalar_add_op(const ei_scalar_add_op& other) : m_other(other.m_other) { }
-  inline ei_scalar_add_op(const Scalar& other) : m_other(other) { }
-  inline Scalar operator() (const Scalar& a) const { return a + m_other; }
-  inline const PacketScalar packetOp(const PacketScalar& a) const
-  { return ei_padd(a, ei_pset1(m_other)); }
-  const Scalar m_other;
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_add_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = ei_packet_traits<Scalar>::size>1 }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the square root of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::sqrt()
-  */
-template<typename Scalar> struct ei_scalar_sqrt_op EIGEN_EMPTY_STRUCT {
-  inline const Scalar operator() (const Scalar& a) const { return ei_sqrt(a); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_sqrt_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the exponential of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::exp()
-  */
-template<typename Scalar> struct ei_scalar_exp_op EIGEN_EMPTY_STRUCT {
-  inline const Scalar operator() (const Scalar& a) const { return ei_exp(a); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_exp_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the logarithm of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::log()
-  */
-template<typename Scalar> struct ei_scalar_log_op EIGEN_EMPTY_STRUCT {
-  inline const Scalar operator() (const Scalar& a) const { return ei_log(a); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_log_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the cosine of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::cos()
-  */
-template<typename Scalar> struct ei_scalar_cos_op EIGEN_EMPTY_STRUCT {
-  inline const Scalar operator() (const Scalar& a) const { return ei_cos(a); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_cos_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the sine of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::sin()
-  */
-template<typename Scalar> struct ei_scalar_sin_op EIGEN_EMPTY_STRUCT {
-  inline const Scalar operator() (const Scalar& a) const { return ei_sin(a); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_sin_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to raise a scalar to a power
-  *
-  * \sa class CwiseUnaryOp, Cwise::pow
-  */
-template<typename Scalar>
-struct ei_scalar_pow_op {
-  // FIXME default copy constructors seems bugged with std::complex<>
-  inline ei_scalar_pow_op(const ei_scalar_pow_op& other) : m_exponent(other.m_exponent) { }
-  inline ei_scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {}
-  inline Scalar operator() (const Scalar& a) const { return ei_pow(a, m_exponent); }
-  const Scalar m_exponent;
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_pow_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the inverse of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::inverse()
-  */
-template<typename Scalar>
-struct ei_scalar_inverse_op {
-  inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; }
-  template<typename PacketScalar>
-  inline const PacketScalar packetOp(const PacketScalar& a) const
-  { return ei_pdiv(ei_pset1(Scalar(1)),a); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_inverse_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = int(ei_packet_traits<Scalar>::size)>1 }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the square of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::square()
-  */
-template<typename Scalar>
-struct ei_scalar_square_op {
-  inline Scalar operator() (const Scalar& a) const { return a*a; }
-  template<typename PacketScalar>
-  inline const PacketScalar packetOp(const PacketScalar& a) const
-  { return ei_pmul(a,a); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_square_op<Scalar> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = int(ei_packet_traits<Scalar>::size)>1 }; };
-
-/** \internal
-  *
-  * \array_module
-  *
-  * \brief Template functor to compute the cube of a scalar
-  *
-  * \sa class CwiseUnaryOp, Cwise::cube()
-  */
-template<typename Scalar>
-struct ei_scalar_cube_op {
-  inline Scalar operator() (const Scalar& a) const { return a*a*a; }
-  template<typename PacketScalar>
-  inline const PacketScalar packetOp(const PacketScalar& a) const
-  { return ei_pmul(a,ei_pmul(a,a)); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_cube_op<Scalar> >
-{ enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = int(ei_packet_traits<Scalar>::size)>1 }; };
-
-// default ei_functor_traits for STL functors:
-
-template<typename T>
-struct ei_functor_traits<std::multiplies<T> >
-{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::divides<T> >
-{ enum { Cost = NumTraits<T>::MulCost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::plus<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::minus<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::negate<T> >
-{ enum { Cost = NumTraits<T>::AddCost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::logical_or<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::logical_and<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::logical_not<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::greater<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::less<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::greater_equal<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::less_equal<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::equal_to<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::not_equal_to<T> >
-{ enum { Cost = 1, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::binder2nd<T> >
-{ enum { Cost = ei_functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::binder1st<T> >
-{ enum { Cost = ei_functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::unary_negate<T> >
-{ enum { Cost = 1 + ei_functor_traits<T>::Cost, PacketAccess = false }; };
-
-template<typename T>
-struct ei_functor_traits<std::binary_negate<T> >
-{ enum { Cost = 1 + ei_functor_traits<T>::Cost, PacketAccess = false }; };
-
-#ifdef EIGEN_STDEXT_SUPPORT
-
-template<typename T0,typename T1>
-struct ei_functor_traits<std::project1st<T0,T1> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct ei_functor_traits<std::project2nd<T0,T1> >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct ei_functor_traits<std::select2nd<std::pair<T0,T1> > >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct ei_functor_traits<std::select1st<std::pair<T0,T1> > >
-{ enum { Cost = 0, PacketAccess = false }; };
-
-template<typename T0,typename T1>
-struct ei_functor_traits<std::unary_compose<T0,T1> >
-{ enum { Cost = ei_functor_traits<T0>::Cost + ei_functor_traits<T1>::Cost, PacketAccess = false }; };
-
-template<typename T0,typename T1,typename T2>
-struct ei_functor_traits<std::binary_compose<T0,T1,T2> >
-{ enum { Cost = ei_functor_traits<T0>::Cost + ei_functor_traits<T1>::Cost + ei_functor_traits<T2>::Cost, PacketAccess = false }; };
-
-#endif // EIGEN_STDEXT_SUPPORT
-
-#endif // EIGEN_ARRAY_FUNCTORS_H

Eigen/src/Array/Norms.h

@@ -1,80 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_ARRAY_NORMS_H
-#define EIGEN_ARRAY_NORMS_H
-
-template<typename Derived, int p>
-struct ei_lpNorm_selector
-{
-  typedef typename NumTraits<typename ei_traits<Derived>::Scalar>::Real RealScalar;
-  inline static RealScalar run(const MatrixBase<Derived>& m)
-  {
-    return ei_pow(m.cwise().abs().cwise().pow(p).sum(), RealScalar(1)/p);
-  }
-};
-
-template<typename Derived>
-struct ei_lpNorm_selector<Derived, 1>
-{
-  inline static typename NumTraits<typename ei_traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
-  {
-    return m.cwise().abs().sum();
-  }
-};
-
-template<typename Derived>
-struct ei_lpNorm_selector<Derived, 2>
-{
-  inline static typename NumTraits<typename ei_traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
-  {
-    return m.norm();
-  }
-};
-
-template<typename Derived>
-struct ei_lpNorm_selector<Derived, Infinity>
-{
-  inline static typename NumTraits<typename ei_traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
-  {
-    return m.cwise().abs().maxCoeff();
-  }
-};
-
-/** \array_module
-  * 
-  * \returns the \f$ \ell^p \f$ norm of *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values
-  *          of the coefficients of *this. If \a p is the special value \a Eigen::Infinity, this function returns the \f$ \ell^p\infty \f$
-  *          norm, that is the maximum of the absolute values of the coefficients of *this.
-  *
-  * \sa norm()
-  */
-template<typename Derived>
-template<int p>
-inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<Derived>::lpNorm() const
-{
-  return ei_lpNorm_selector<Derived, p>::run(*this);
-}
-
-#endif // EIGEN_ARRAY_NORMS_H

Eigen/src/Array/PartialRedux.h

@@ -1,342 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_PARTIAL_REDUX_H
-#define EIGEN_PARTIAL_REDUX_H
-
-/** \array_module \ingroup Array
-  *
-  * \class PartialReduxExpr
-  *
-  * \brief Generic expression of a partially reduxed matrix
-  *
-  * \param MatrixType the type of the matrix we are applying the redux operation
-  * \param MemberOp type of the member functor
-  * \param Direction indicates the direction of the redux (Vertical or Horizontal)
-  *
-  * This class represents an expression of a partial redux operator of a matrix.
-  * It is the return type of PartialRedux functions,
-  * and most of the time this is the only way it is used.
-  *
-  * \sa class PartialRedux
-  */
-
-template< typename MatrixType, typename MemberOp, int Direction>
-class PartialReduxExpr;
-
-template<typename MatrixType, typename MemberOp, int Direction>
-struct ei_traits<PartialReduxExpr<MatrixType, MemberOp, Direction> >
-{
-  typedef typename MemberOp::result_type Scalar;
-  typedef typename MatrixType::Scalar InputScalar;
-  typedef typename ei_nested<MatrixType>::type MatrixTypeNested;
-  typedef typename ei_cleantype<MatrixTypeNested>::type _MatrixTypeNested;
-  enum {
-    RowsAtCompileTime = Direction==Vertical   ? 1 : MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = Direction==Vertical   ? 1 : MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = Direction==Horizontal ? 1 : MatrixType::MaxColsAtCompileTime,
-    Flags = (unsigned int)_MatrixTypeNested::Flags & HereditaryBits,
-    TraversalSize = Direction==Vertical ? RowsAtCompileTime : ColsAtCompileTime
-  };
-  #if EIGEN_GNUC_AT_LEAST(3,4)
-  typedef typename MemberOp::template Cost<InputScalar,int(TraversalSize)> CostOpType;
-  #else
-  typedef typename MemberOp::template Cost<InputScalar,TraversalSize> CostOpType;
-  #endif
-  enum {
-    CoeffReadCost = TraversalSize * ei_traits<_MatrixTypeNested>::CoeffReadCost + int(CostOpType::value)
-  };
-};
-
-template< typename MatrixType, typename MemberOp, int Direction>
-class PartialReduxExpr : ei_no_assignment_operator,
-  public MatrixBase<PartialReduxExpr<MatrixType, MemberOp, Direction> >
-{
-  public:
-
-    EIGEN_GENERIC_PUBLIC_INTERFACE(PartialReduxExpr)
-    typedef typename ei_traits<PartialReduxExpr>::MatrixTypeNested MatrixTypeNested;
-    typedef typename ei_traits<PartialReduxExpr>::_MatrixTypeNested _MatrixTypeNested;
-
-    PartialReduxExpr(const MatrixType& mat, const MemberOp& func = MemberOp())
-      : m_matrix(mat), m_functor(func) {}
-
-    int rows() const { return (Direction==Vertical   ? 1 : m_matrix.rows()); }
-    int cols() const { return (Direction==Horizontal ? 1 : m_matrix.cols()); }
-
-    const Scalar coeff(int i, int j) const
-    {
-      if (Direction==Vertical)
-        return m_functor(m_matrix.col(j));
-      else
-        return m_functor(m_matrix.row(i));
-    }
-
-  protected:
-    const MatrixTypeNested m_matrix;
-    const MemberOp m_functor;
-};
-
-#define EIGEN_MEMBER_FUNCTOR(MEMBER,COST)                           \
-  template <typename ResultType>                                    \
-  struct ei_member_##MEMBER EIGEN_EMPTY_STRUCT {                    \
-    typedef ResultType result_type;                                 \
-    template<typename Scalar, int Size> struct Cost                 \
-    { enum { value = COST }; };                                     \
-    template<typename Derived>                                      \
-    inline ResultType operator()(const MatrixBase<Derived>& mat) const     \
-    { return mat.MEMBER(); } \
-  }
-
-EIGEN_MEMBER_FUNCTOR(squaredNorm, Size * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost);
-EIGEN_MEMBER_FUNCTOR(norm, (Size+5) * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost);
-EIGEN_MEMBER_FUNCTOR(sum, (Size-1)*NumTraits<Scalar>::AddCost);
-EIGEN_MEMBER_FUNCTOR(minCoeff, (Size-1)*NumTraits<Scalar>::AddCost);
-EIGEN_MEMBER_FUNCTOR(maxCoeff, (Size-1)*NumTraits<Scalar>::AddCost);
-EIGEN_MEMBER_FUNCTOR(all, (Size-1)*NumTraits<Scalar>::AddCost);
-EIGEN_MEMBER_FUNCTOR(any, (Size-1)*NumTraits<Scalar>::AddCost);
-EIGEN_MEMBER_FUNCTOR(count, (Size-1)*NumTraits<Scalar>::AddCost);
-
-/** \internal */
-template <typename BinaryOp, typename Scalar>
-struct ei_member_redux {
-  typedef typename ei_result_of<
-                     BinaryOp(Scalar)
-                   >::type  result_type;
-  template<typename _Scalar, int Size> struct Cost
-  { enum { value = (Size-1) * ei_functor_traits<BinaryOp>::Cost }; };
-  ei_member_redux(const BinaryOp func) : m_functor(func) {}
-  template<typename Derived>
-  inline result_type operator()(const MatrixBase<Derived>& mat) const
-  { return mat.redux(m_functor); }
-  const BinaryOp m_functor;
-};
-
-/** \array_module \ingroup Array
-  *
-  * \class PartialRedux
-  *
-  * \brief Pseudo expression providing partial reduction operations
-  *
-  * \param ExpressionType the type of the object on which to do partial reductions
-  * \param Direction indicates the direction of the redux (Vertical or Horizontal)
-  *
-  * This class represents a pseudo expression with partial reduction features.
-  * It is the return type of MatrixBase::colwise() and MatrixBase::rowwise()
-  * and most of the time this is the only way it is used.
-  *
-  * Example: \include MatrixBase_colwise.cpp
-  * Output: \verbinclude MatrixBase_colwise.out
-  *
-  * \sa MatrixBase::colwise(), MatrixBase::rowwise(), class PartialReduxExpr
-  */
-template<typename ExpressionType, int Direction> class PartialRedux
-{
-  public:
-
-    typedef typename ei_traits<ExpressionType>::Scalar Scalar;
-    typedef typename ei_meta_if<ei_must_nest_by_value<ExpressionType>::ret,
-        ExpressionType, const ExpressionType&>::ret ExpressionTypeNested;
-
-    template<template<typename _Scalar> class Functor> struct ReturnType
-    {
-      typedef PartialReduxExpr<ExpressionType,
-                               Functor<typename ei_traits<ExpressionType>::Scalar>,
-                               Direction
-                              > Type;
-    };
-
-    template<typename BinaryOp> struct ReduxReturnType
-    {
-      typedef PartialReduxExpr<ExpressionType,
-                               ei_member_redux<BinaryOp,typename ei_traits<ExpressionType>::Scalar>,
-                               Direction
-                              > Type;
-    };
-
-    typedef typename ExpressionType::PlainMatrixType CrossReturnType;
-    
-    inline PartialRedux(const ExpressionType& matrix) : m_matrix(matrix) {}
-
-    /** \internal */
-    inline const ExpressionType& _expression() const { return m_matrix; }
-
-    template<typename BinaryOp>
-    const typename ReduxReturnType<BinaryOp>::Type
-    redux(const BinaryOp& func = BinaryOp()) const;
-
-    /** \returns a row (or column) vector expression of the smallest coefficient
-      * of each column (or row) of the referenced expression.
-      *
-      * Example: \include PartialRedux_minCoeff.cpp
-      * Output: \verbinclude PartialRedux_minCoeff.out
-      *
-      * \sa MatrixBase::minCoeff() */
-    const typename ReturnType<ei_member_minCoeff>::Type minCoeff() const
-    { return _expression(); }
-
-    /** \returns a row (or column) vector expression of the largest coefficient
-      * of each column (or row) of the referenced expression.
-      *
-      * Example: \include PartialRedux_maxCoeff.cpp
-      * Output: \verbinclude PartialRedux_maxCoeff.out
-      *
-      * \sa MatrixBase::maxCoeff() */
-    const typename ReturnType<ei_member_maxCoeff>::Type maxCoeff() const
-    { return _expression(); }
-
-    /** \returns a row (or column) vector expression of the squared norm
-      * of each column (or row) of the referenced expression.
-      *
-      * Example: \include PartialRedux_squaredNorm.cpp
-      * Output: \verbinclude PartialRedux_squaredNorm.out
-      *
-      * \sa MatrixBase::squaredNorm() */
-    const typename ReturnType<ei_member_squaredNorm>::Type squaredNorm() const
-    { return _expression(); }
-
-    /** \returns a row (or column) vector expression of the norm
-      * of each column (or row) of the referenced expression.
-      *
-      * Example: \include PartialRedux_norm.cpp
-      * Output: \verbinclude PartialRedux_norm.out
-      *
-      * \sa MatrixBase::norm() */
-    const typename ReturnType<ei_member_norm>::Type norm() const
-    { return _expression(); }
-
-    /** \returns a row (or column) vector expression of the sum
-      * of each column (or row) of the referenced expression.
-      *
-      * Example: \include PartialRedux_sum.cpp
-      * Output: \verbinclude PartialRedux_sum.out
-      *
-      * \sa MatrixBase::sum() */
-    const typename ReturnType<ei_member_sum>::Type sum() const
-    { return _expression(); }
-
-    /** \returns a row (or column) vector expression representing
-      * whether \b all coefficients of each respective column (or row) are \c true.
-      *
-      * \sa MatrixBase::all() */
-    const typename ReturnType<ei_member_all>::Type all() const
-    { return _expression(); }
-
-    /** \returns a row (or column) vector expression representing
-      * whether \b at \b least one coefficient of each respective column (or row) is \c true.
-      *
-      * \sa MatrixBase::any() */
-    const typename ReturnType<ei_member_any>::Type any() const
-    { return _expression(); }
-    
-    /** \returns a row (or column) vector expression representing
-      * the number of \c true coefficients of each respective column (or row).
-      *
-      * Example: \include PartialRedux_count.cpp
-      * Output: \verbinclude PartialRedux_count.out
-      *
-      * \sa MatrixBase::count() */
-    const PartialReduxExpr<ExpressionType, ei_member_count<int>, Direction> count() const
-    { return _expression(); }
-
-    /** \returns a 3x3 matrix expression of the cross product
-      * of each column or row of the referenced expression with the \a other vector.
-      *
-      * \geometry_module
-      *
-      * \sa MatrixBase::cross() */
-    template<typename OtherDerived>
-    const CrossReturnType cross(const MatrixBase<OtherDerived>& other) const
-    {
-      EIGEN_STATIC_ASSERT_MATRIX_SPECIFIC_SIZE(CrossReturnType,3,3)
-      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(OtherDerived,3)
-      EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename OtherDerived::Scalar>::ret),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-
-      if(Direction==Vertical)
-        return (CrossReturnType()
-                                 << _expression().col(0).cross(other),
-                                    _expression().col(1).cross(other),
-                                    _expression().col(2).cross(other)).finished();
-      else
-        return (CrossReturnType() 
-                                 << _expression().row(0).cross(other),
-                                    _expression().row(1).cross(other),
-                                    _expression().row(2).cross(other)).finished();
-    }
-
-  protected:
-    ExpressionTypeNested m_matrix;
-};
-
-/** \array_module
-  *
-  * \returns a PartialRedux wrapper of *this providing additional partial reduction operations
-  *
-  * Example: \include MatrixBase_colwise.cpp
-  * Output: \verbinclude MatrixBase_colwise.out
-  *
-  * \sa rowwise(), class PartialRedux
-  */
-template<typename Derived>
-inline const PartialRedux<Derived,Vertical>
-MatrixBase<Derived>::colwise() const
-{
-  return derived();
-}
-
-/** \array_module
-  *
-  * \returns a PartialRedux wrapper of *this providing additional partial reduction operations
-  *
-  * Example: \include MatrixBase_rowwise.cpp
-  * Output: \verbinclude MatrixBase_rowwise.out
-  *
-  * \sa colwise(), class PartialRedux
-  */
-template<typename Derived>
-inline const PartialRedux<Derived,Horizontal>
-MatrixBase<Derived>::rowwise() const
-{
-  return derived();
-}
-
-/** \returns a row or column vector expression of \c *this reduxed by \a func
-  *
-  * The template parameter \a BinaryOp is the type of the functor
-  * of the custom redux operator. Note that func must be an associative operator.
-  *
-  * \sa class PartialRedux, MatrixBase::colwise(), MatrixBase::rowwise()
-  */
-template<typename ExpressionType, int Direction>
-template<typename BinaryOp>
-const typename PartialRedux<ExpressionType,Direction>::template ReduxReturnType<BinaryOp>::Type
-PartialRedux<ExpressionType,Direction>::redux(const BinaryOp& func) const
-{
-  return typename ReduxReturnType<BinaryOp>::Type(_expression(), func);
-}
-
-#endif // EIGEN_PARTIAL_REDUX_H

Eigen/src/Array/Random.h

@@ -1,156 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_RANDOM_H
-#define EIGEN_RANDOM_H
-
-template<typename Scalar> struct ei_scalar_random_op EIGEN_EMPTY_STRUCT {
-  inline ei_scalar_random_op(void) {}
-  inline const Scalar operator() (int, int) const { return ei_random<Scalar>(); }
-};
-template<typename Scalar>
-struct ei_functor_traits<ei_scalar_random_op<Scalar> >
-{ enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false, IsRepeatable = false }; };
-
-/** \array_module
-  * 
-  * \returns a random matrix (not an expression, the matrix is immediately evaluated).
-  *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
-  * the returned matrix. Must be compatible with this MatrixBase type.
-  *
-  * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a rows and \a cols as arguments, so ei_random() should be used
-  * instead.
-  *
-  * \addexample RandomExample \label How to create a matrix with random coefficients
-  *
-  * Example: \include MatrixBase_random_int_int.cpp
-  * Output: \verbinclude MatrixBase_random_int_int.out
-  *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(int), MatrixBase::Random()
-  */
-template<typename Derived>
-inline const CwiseNullaryOp<ei_scalar_random_op<typename ei_traits<Derived>::Scalar>, Derived>
-MatrixBase<Derived>::Random(int rows, int cols)
-{
-  return NullaryExpr(rows, cols, ei_scalar_random_op<Scalar>());
-}
-
-/** \array_module
-  * 
-  * \returns a random vector (not an expression, the vector is immediately evaluated).
-  *
-  * The parameter \a size is the size of the returned vector.
-  * Must be compatible with this MatrixBase type.
-  *
-  * \only_for_vectors
-  *
-  * This variant is meant to be used for dynamic-size vector types. For fixed-size types,
-  * it is redundant to pass \a size as argument, so ei_random() should be used
-  * instead.
-  *
-  * Example: \include MatrixBase_random_int.cpp
-  * Output: \verbinclude MatrixBase_random_int.out
-  *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(int,int), MatrixBase::Random()
-  */
-template<typename Derived>
-inline const CwiseNullaryOp<ei_scalar_random_op<typename ei_traits<Derived>::Scalar>, Derived>
-MatrixBase<Derived>::Random(int size)
-{
-  return NullaryExpr(size, ei_scalar_random_op<Scalar>());
-}
-
-/** \array_module
-  * 
-  * \returns a fixed-size random matrix or vector
-  * (not an expression, the matrix is immediately evaluated).
-  *
-  * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
-  * need to use the variants taking size arguments.
-  *
-  * Example: \include MatrixBase_random.cpp
-  * Output: \verbinclude MatrixBase_random.out
-  *
-  * \sa MatrixBase::setRandom(), MatrixBase::Random(int,int), MatrixBase::Random(int)
-  */
-template<typename Derived>
-inline const CwiseNullaryOp<ei_scalar_random_op<typename ei_traits<Derived>::Scalar>, Derived>
-MatrixBase<Derived>::Random()
-{
-  return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, ei_scalar_random_op<Scalar>());
-}
-
-/** \array_module
-  * 
-  * Sets all coefficients in this expression to random values.
-  *
-  * Example: \include MatrixBase_setRandom.cpp
-  * Output: \verbinclude MatrixBase_setRandom.out
-  *
-  * \sa class CwiseNullaryOp, setRandom(int), setRandom(int,int)
-  */
-template<typename Derived>
-inline Derived& MatrixBase<Derived>::setRandom()
-{
-  return *this = Random(rows(), cols());
-}
-
-/** Resizes to the given \a size, and sets all coefficients in this expression to random values.
-  *
-  * \only_for_vectors
-  *
-  * Example: \include Matrix_setRandom_int.cpp
-  * Output: \verbinclude Matrix_setRandom_int.out
-  *
-  * \sa MatrixBase::setRandom(), setRandom(int,int), class CwiseNullaryOp, MatrixBase::Random()
-  */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setRandom(int size)
-{
-  resize(size);
-  return setRandom();
-}
-
-/** Resizes to the given size, and sets all coefficients in this expression to random values.
-  *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
-  *
-  * Example: \include Matrix_setRandom_int_int.cpp
-  * Output: \verbinclude Matrix_setRandom_int_int.out
-  *
-  * \sa MatrixBase::setRandom(), setRandom(int), class CwiseNullaryOp, MatrixBase::Random()
-  */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setRandom(int rows, int cols)
-{
-  resize(rows, cols);
-  return setRandom();
-}
-
-#endif // EIGEN_RANDOM_H

Eigen/src/Array/Select.h

@@ -1,159 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_SELECT_H
-#define EIGEN_SELECT_H
-
-/** \array_module \ingroup Array
-  *
-  * \class Select
-  *
-  * \brief Expression of a coefficient wise version of the C++ ternary operator ?:
-  *
-  * \param ConditionMatrixType the type of the \em condition expression which must be a boolean matrix
-  * \param ThenMatrixType the type of the \em then expression
-  * \param ElseMatrixType the type of the \em else expression
-  *
-  * This class represents an expression of a coefficient wise version of the C++ ternary operator ?:.
-  * It is the return type of MatrixBase::select() and most of the time this is the only way it is used.
-  *
-  * \sa MatrixBase::select(const MatrixBase<ThenDerived>&, const MatrixBase<ElseDerived>&) const
-  */
-
-template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
-struct ei_traits<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
-{
-  typedef typename ei_traits<ThenMatrixType>::Scalar Scalar;
-  typedef typename ConditionMatrixType::Nested ConditionMatrixNested;
-  typedef typename ThenMatrixType::Nested ThenMatrixNested;
-  typedef typename ElseMatrixType::Nested ElseMatrixNested;
-  enum {
-    RowsAtCompileTime = ConditionMatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = ConditionMatrixType::MaxColsAtCompileTime,
-    Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & HereditaryBits,
-	CoeffReadCost = ei_traits<typename ei_cleantype<ConditionMatrixNested>::type>::CoeffReadCost
-	+ EIGEN_ENUM_MAX(ei_traits<typename ei_cleantype<ThenMatrixNested>::type>::CoeffReadCost,
-	                 ei_traits<typename ei_cleantype<ElseMatrixNested>::type>::CoeffReadCost)
-  };
-};
-
-template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMatrixType>
-class Select : ei_no_assignment_operator,
-  public MatrixBase<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
-{
-  public:
-
-    EIGEN_GENERIC_PUBLIC_INTERFACE(Select)
-
-    Select(const ConditionMatrixType& conditionMatrix,
-           const ThenMatrixType& thenMatrix,
-           const ElseMatrixType& elseMatrix)
-      : m_condition(conditionMatrix), m_then(thenMatrix), m_else(elseMatrix)
-    {
-      ei_assert(m_condition.rows() == m_then.rows() && m_condition.rows() == m_else.rows());
-      ei_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols());
-    }
-
-    int rows() const { return m_condition.rows(); }
-    int cols() const { return m_condition.cols(); }
-
-    const Scalar coeff(int i, int j) const
-    {
-      if (m_condition.coeff(i,j))
-        return m_then.coeff(i,j);
-      else
-        return m_else.coeff(i,j);
-    }
-    
-    const Scalar coeff(int i) const
-    {
-      if (m_condition.coeff(i))
-        return m_then.coeff(i);
-      else
-        return m_else.coeff(i);
-    }
-
-  protected:
-    const typename ConditionMatrixType::Nested m_condition;
-    const typename ThenMatrixType::Nested m_then;
-    const typename ElseMatrixType::Nested m_else;
-};
-
-
-/** \array_module
-  *
-  * \returns a matrix where each coefficient (i,j) is equal to \a thenMatrix(i,j)
-  * if \c *this(i,j), and \a elseMatrix(i,j) otherwise.
-  *
-  * Example: \include MatrixBase_select.cpp
-  * Output: \verbinclude MatrixBase_select.out
-  *
-  * \sa class Select
-  */
-template<typename Derived>
-template<typename ThenDerived,typename ElseDerived>
-inline const Select<Derived,ThenDerived,ElseDerived>
-MatrixBase<Derived>::select(const MatrixBase<ThenDerived>& thenMatrix,
-                            const MatrixBase<ElseDerived>& elseMatrix) const
-{
-  return Select<Derived,ThenDerived,ElseDerived>(derived(), thenMatrix.derived(), elseMatrix.derived());
-}
-
-/** \array_module
-  *
-  * Version of MatrixBase::select(const MatrixBase&, const MatrixBase&) with
-  * the \em else expression being a scalar value.
-  *
-  * \sa MatrixBase::select(const MatrixBase<ThenDerived>&, const MatrixBase<ElseDerived>&) const, class Select
-  */
-template<typename Derived>
-template<typename ThenDerived>
-inline const Select<Derived,ThenDerived, NestByValue<typename ThenDerived::ConstantReturnType> >
-MatrixBase<Derived>::select(const MatrixBase<ThenDerived>& thenMatrix,
-                            typename ThenDerived::Scalar elseScalar) const
-{
-  return Select<Derived,ThenDerived,NestByValue<typename ThenDerived::ConstantReturnType> >(
-    derived(), thenMatrix.derived(), ThenDerived::Constant(rows(),cols(),elseScalar));
-}
-
-/** \array_module
-  *
-  * Version of MatrixBase::select(const MatrixBase&, const MatrixBase&) with
-  * the \em then expression being a scalar value.
-  *
-  * \sa MatrixBase::select(const MatrixBase<ThenDerived>&, const MatrixBase<ElseDerived>&) const, class Select
-  */
-template<typename Derived>
-template<typename ElseDerived>
-inline const Select<Derived, NestByValue<typename ElseDerived::ConstantReturnType>, ElseDerived >
-MatrixBase<Derived>::select(typename ElseDerived::Scalar thenScalar,
-                            const MatrixBase<ElseDerived>& elseMatrix) const
-{
-  return Select<Derived,NestByValue<typename ElseDerived::ConstantReturnType>,ElseDerived>(
-    derived(), ElseDerived::Constant(rows(),cols(),thenScalar), elseMatrix.derived());
-}
-
-#endif // EIGEN_SELECT_H

Eigen/src/CMakeLists.txt

@@ -1,9 +1,7 @@
-ADD_SUBDIRECTORY(Core)
-ADD_SUBDIRECTORY(LU)
-ADD_SUBDIRECTORY(QR)
-ADD_SUBDIRECTORY(SVD)
-ADD_SUBDIRECTORY(Cholesky)
-ADD_SUBDIRECTORY(Array)
-ADD_SUBDIRECTORY(Geometry)
-ADD_SUBDIRECTORY(LeastSquares)
-ADD_SUBDIRECTORY(Sparse)
+file(GLOB Eigen_src_subdirectories "*")
+escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
+foreach(f ${Eigen_src_subdirectories})
+  if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" )
+    add_subdirectory(${f})
+  endif()
+endforeach()

Eigen/src/Cholesky/CMakeLists.txt

@@ -2,5 +2,5 @@ FILE(GLOB Eigen_Cholesky_SRCS "*.h")
 
 INSTALL(FILES
   ${Eigen_Cholesky_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Cholesky
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Cholesky COMPONENT Devel
   )

Eigen/src/Cholesky/LDLT.h

@@ -1,198 +1,611 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2009 Keir Mierle <mierle@gmail.com>
+// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2011 Timothy E. Holy <tim.holy@gmail.com >
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LDLT_H
 #define EIGEN_LDLT_H
 
-/** \ingroup cholesky_Module
+namespace Eigen { 
+
+namespace internal {
+  template<typename MatrixType, int UpLo> struct LDLT_Traits;
+
+  // PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef
+  enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite };
+}
+
+/** \ingroup Cholesky_Module
   *
   * \class LDLT
   *
-  * \brief Robust Cholesky decomposition of a matrix and associated features
+  * \brief Robust Cholesky decomposition of a matrix with pivoting
   *
-  * \param MatrixType the type of the matrix of which we are computing the LDL^T Cholesky decomposition
+  * \param MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition
+  * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
+  *             The other triangular part won't be read.
   *
-  * This class performs a Cholesky decomposition without square root of a symmetric, positive definite
-  * matrix A such that A = L D L^* = U^* D U, where L is lower triangular with a unit diagonal
-  * and D is a diagonal matrix.
+  * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite
+  * matrix \f$ A \f$ such that \f$ A =  P^TLDL^*P \f$, where P is a permutation matrix, L
+  * is lower triangular with a unit diagonal and D is a diagonal matrix.
   *
-  * Compared to a standard Cholesky decomposition, avoiding the square roots allows for faster and more
-  * stable computation.
+  * The decomposition uses pivoting to ensure stability, so that L will have
+  * zeros in the bottom right rank(A) - n submatrix. Avoiding the square root
+  * on D also stabilizes the computation.
   *
-  * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
-  * the strict lower part does not have to store correct values.
+  * Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky
+  * decomposition to determine whether a system of equations has a solution.
   *
   * \sa MatrixBase::ldlt(), class LLT
   */
-template<typename MatrixType> class LDLT
+template<typename _MatrixType, int _UpLo> class LDLT
 {
   public:
-
+    typedef _MatrixType MatrixType;
+    enum {
+      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      Options = MatrixType::Options & ~RowMajorBit, // these are the options for the TmpMatrixType, we need a ColMajor matrix here!
+      MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
+      UpLo = _UpLo
+    };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
+    typedef typename MatrixType::Index Index;
+    typedef Matrix<Scalar, RowsAtCompileTime, 1, Options, MaxRowsAtCompileTime, 1> TmpMatrixType;
 
+    typedef Transpositions<RowsAtCompileTime, MaxRowsAtCompileTime> TranspositionType;
+    typedef PermutationMatrix<RowsAtCompileTime, MaxRowsAtCompileTime> PermutationType;
+
+    typedef internal::LDLT_Traits<MatrixType,UpLo> Traits;
+
+    /** \brief Default Constructor.
+      *
+      * The default constructor is useful in cases in which the user intends to
+      * perform decompositions via LDLT::compute(const MatrixType&).
+      */
+    LDLT() 
+      : m_matrix(), 
+        m_transpositions(), 
+        m_sign(internal::ZeroSign),
+        m_isInitialized(false) 
+    {}
+
+    /** \brief Default Constructor with memory preallocation
+      *
+      * Like the default constructor but with preallocation of the internal data
+      * according to the specified problem \a size.
+      * \sa LDLT()
+      */
+    LDLT(Index size)
+      : m_matrix(size, size),
+        m_transpositions(size),
+        m_temporary(size),
+        m_sign(internal::ZeroSign),
+        m_isInitialized(false)
+    {}
+
+    /** \brief Constructor with decomposition
+      *
+      * This calculates the decomposition for the input \a matrix.
+      * \sa LDLT(Index size)
+      */
     LDLT(const MatrixType& matrix)
-      : m_matrix(matrix.rows(), matrix.cols())
+      : m_matrix(matrix.rows(), matrix.cols()),
+        m_transpositions(matrix.rows()),
+        m_temporary(matrix.rows()),
+        m_sign(internal::ZeroSign),
+        m_isInitialized(false)
     {
       compute(matrix);
     }
 
-    /** \returns the lower triangular matrix L */
-    inline Part<MatrixType, UnitLowerTriangular> matrixL(void) const { return m_matrix; }
+    /** Clear any existing decomposition
+     * \sa rankUpdate(w,sigma)
+     */
+    void setZero()
+    {
+      m_isInitialized = false;
+    }
+
+    /** \returns a view of the upper triangular matrix U */
+    inline typename Traits::MatrixU matrixU() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return Traits::getU(m_matrix);
+    }
+
+    /** \returns a view of the lower triangular matrix L */
+    inline typename Traits::MatrixL matrixL() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return Traits::getL(m_matrix);
+    }
+
+    /** \returns the permutation matrix P as a transposition sequence.
+      */
+    inline const TranspositionType& transpositionsP() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return m_transpositions;
+    }
 
     /** \returns the coefficients of the diagonal matrix D */
-    inline DiagonalCoeffs<MatrixType> vectorD(void) const { return m_matrix.diagonal(); }
+    inline Diagonal<const MatrixType> vectorD() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return m_matrix.diagonal();
+    }
 
-    /** \returns true if the matrix is positive definite */
-    inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
+    /** \returns true if the matrix is positive (semidefinite) */
+    inline bool isPositive() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign;
+    }
+    
+    #ifdef EIGEN2_SUPPORT
+    inline bool isPositiveDefinite() const
+    {
+      return isPositive();
+    }
+    #endif
 
-    template<typename RhsDerived, typename ResDerived>
-    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
+    /** \returns true if the matrix is negative (semidefinite) */
+    inline bool isNegative(void) const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return m_sign == internal::NegativeSemiDef || m_sign == internal::ZeroSign;
+    }
+
+    /** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * This function also supports in-place solves using the syntax <tt>x = decompositionObject.solve(x)</tt> .
+      *
+      * \note_about_checking_solutions
+      *
+      * More precisely, this method solves \f$ A x = b \f$ using the decomposition \f$ A = P^T L D L^* P \f$
+      * by solving the systems \f$ P^T y_1 = b \f$, \f$ L y_2 = y_1 \f$, \f$ D y_3 = y_2 \f$, 
+      * \f$ L^* y_4 = y_3 \f$ and \f$ P x = y_4 \f$ in succession. If the matrix \f$ A \f$ is singular, then
+      * \f$ D \f$ will also be singular (all the other matrices are invertible). In that case, the
+      * least-square solution of \f$ D y_3 = y_2 \f$ is computed. This does not mean that this function
+      * computes the least-square solution of \f$ A x = b \f$ is \f$ A \f$ is singular.
+      *
+      * \sa MatrixBase::ldlt()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<LDLT, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      eigen_assert(m_matrix.rows()==b.rows()
+                && "LDLT::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<LDLT, Rhs>(*this, b.derived());
+    }
+
+    #ifdef EIGEN2_SUPPORT
+    template<typename OtherDerived, typename ResultType>
+    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
+    {
+      *result = this->solve(b);
+      return true;
+    }
+    #endif
 
     template<typename Derived>
     bool solveInPlace(MatrixBase<Derived> &bAndX) const;
 
-    void compute(const MatrixType& matrix);
+    LDLT& compute(const MatrixType& matrix);
+
+    template <typename Derived>
+    LDLT& rankUpdate(const MatrixBase<Derived>& w, const RealScalar& alpha=1);
+
+    /** \returns the internal LDLT decomposition matrix
+      *
+      * TODO: document the storage layout
+      */
+    inline const MatrixType& matrixLDLT() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return m_matrix;
+    }
+
+    MatrixType reconstructedMatrix() const;
+
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+
+    /** \brief Reports whether previous computation was successful.
+      *
+      * \returns \c Success if computation was succesful,
+      *          \c NumericalIssue if the matrix.appears to be negative.
+      */
+    ComputationInfo info() const
+    {
+      eigen_assert(m_isInitialized && "LDLT is not initialized.");
+      return Success;
+    }
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+
     /** \internal
-      * Used to compute and store the cholesky decomposition A = L D L^* = U^* D U.
+      * Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
       * The strict upper part is used during the decomposition, the strict lower
       * part correspond to the coefficients of L (its diagonal is equal to 1 and
       * is not stored), and the diagonal entries correspond to D.
       */
     MatrixType m_matrix;
-
-    bool m_isPositiveDefinite;
+    TranspositionType m_transpositions;
+    TmpMatrixType m_temporary;
+    internal::SignMatrix m_sign;
+    bool m_isInitialized;
 };
 
-/** Compute / recompute the LLT decomposition A = L D L^* = U^* D U of \a matrix
-  */
-template<typename MatrixType>
-void LDLT<MatrixType>::compute(const MatrixType& a)
+namespace internal {
+
+template<int UpLo> struct ldlt_inplace;
+
+template<> struct ldlt_inplace<Lower>
 {
-  assert(a.rows()==a.cols());
-  const int size = a.rows();
-  m_matrix.resize(size, size);
-  m_isPositiveDefinite = true;
-  const RealScalar eps = ei_sqrt(precision<Scalar>());
-
-  if (size<=1)
+  template<typename MatrixType, typename TranspositionType, typename Workspace>
+  static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign)
   {
-    m_matrix = a;
-    return;
-  }
+    using std::abs;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    eigen_assert(mat.rows()==mat.cols());
+    const Index size = mat.rows();
 
-  // Let's preallocate a temporay vector to evaluate the matrix-vector product into it.
-  // Unlike the standard LLT decomposition, here we cannot evaluate it to the destination
-  // matrix because it a sub-row which is not compatible suitable for efficient packet evaluation.
-  // (at least if we assume the matrix is col-major)
-  Matrix<Scalar,MatrixType::RowsAtCompileTime,1> _temporary(size);
-
-  // Note that, in this algorithm the rows of the strict upper part of m_matrix is used to store
-  // column vector, thus the strange .conjugate() and .transpose()...
-
-  m_matrix.row(0) = a.row(0).conjugate();
-  m_matrix.col(0).end(size-1) = m_matrix.row(0).end(size-1) / m_matrix.coeff(0,0);
-  for (int j = 1; j < size; ++j)
-  {
-    RealScalar tmp = ei_real(a.coeff(j,j) - (m_matrix.row(j).start(j) * m_matrix.col(j).start(j).conjugate()).coeff(0,0));
-    m_matrix.coeffRef(j,j) = tmp;
-
-    if (tmp < eps)
+    if (size <= 1)
     {
-      m_isPositiveDefinite = false;
-      return;
+      transpositions.setIdentity();
+      if (numext::real(mat.coeff(0,0)) > 0) sign = PositiveSemiDef;
+      else if (numext::real(mat.coeff(0,0)) < 0) sign = NegativeSemiDef;
+      else sign = ZeroSign;
+      return true;
     }
 
-    int endSize = size-j-1;
-    if (endSize>0)
+    for (Index k = 0; k < size; ++k)
     {
-      _temporary.end(endSize) = ( m_matrix.block(j+1,0, endSize, j)
-                                  * m_matrix.col(j).start(j).conjugate() ).lazy();
+      // Find largest diagonal element
+      Index index_of_biggest_in_corner;
+      mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner);
+      index_of_biggest_in_corner += k;
 
-      m_matrix.row(j).end(endSize) = a.row(j).end(endSize).conjugate()
-                                   - _temporary.end(endSize).transpose();
+      transpositions.coeffRef(k) = index_of_biggest_in_corner;
+      if(k != index_of_biggest_in_corner)
+      {
+        // apply the transposition while taking care to consider only
+        // the lower triangular part
+        Index s = size-index_of_biggest_in_corner-1; // trailing size after the biggest element
+        mat.row(k).head(k).swap(mat.row(index_of_biggest_in_corner).head(k));
+        mat.col(k).tail(s).swap(mat.col(index_of_biggest_in_corner).tail(s));
+        std::swap(mat.coeffRef(k,k),mat.coeffRef(index_of_biggest_in_corner,index_of_biggest_in_corner));
+        for(int i=k+1;i<index_of_biggest_in_corner;++i)
+        {
+          Scalar tmp = mat.coeffRef(i,k);
+          mat.coeffRef(i,k) = numext::conj(mat.coeffRef(index_of_biggest_in_corner,i));
+          mat.coeffRef(index_of_biggest_in_corner,i) = numext::conj(tmp);
+        }
+        if(NumTraits<Scalar>::IsComplex)
+          mat.coeffRef(index_of_biggest_in_corner,k) = numext::conj(mat.coeff(index_of_biggest_in_corner,k));
+      }
 
-      m_matrix.col(j).end(endSize) = m_matrix.row(j).end(endSize) / tmp;
+      // partition the matrix:
+      //       A00 |  -  |  -
+      // lu  = A10 | A11 |  -
+      //       A20 | A21 | A22
+      Index rs = size - k - 1;
+      Block<MatrixType,Dynamic,1> A21(mat,k+1,k,rs,1);
+      Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
+      Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k);
+
+      if(k>0)
+      {
+        temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint();
+        mat.coeffRef(k,k) -= (A10 * temp.head(k)).value();
+        if(rs>0)
+          A21.noalias() -= A20 * temp.head(k);
+      }
+      
+      // In some previous versions of Eigen (e.g., 3.2.1), the scaling was omitted if the pivot
+      // was smaller than the cutoff value. However, soince LDLT is not rank-revealing
+      // we should only make sure we do not introduce INF or NaN values.
+      // LAPACK also uses 0 as the cutoff value.
+      RealScalar realAkk = numext::real(mat.coeffRef(k,k));
+      if((rs>0) && (abs(realAkk) > RealScalar(0)))
+        A21 /= realAkk;
+
+      if (sign == PositiveSemiDef) {
+        if (realAkk < 0) sign = Indefinite;
+      } else if (sign == NegativeSemiDef) {
+        if (realAkk > 0) sign = Indefinite;
+      } else if (sign == ZeroSign) {
+        if (realAkk > 0) sign = PositiveSemiDef;
+        else if (realAkk < 0) sign = NegativeSemiDef;
+      }
     }
+
+    return true;
   }
-}
 
-/** Computes the solution x of \f$ A x = b \f$ using the current decomposition of A.
-  * The result is stored in \a result
-  *
-  * \returns true in case of success, false otherwise.
-  *
-  * In other words, it computes \f$ b = A^{-1} b \f$ with
-  * \f$ {L^{*}}^{-1} D^{-1} L^{-1} b \f$ from right to left.
-  *
-  * \sa LDLT::solveInPlace(), MatrixBase::ldlt()
-  */
-template<typename MatrixType>
-template<typename RhsDerived, typename ResDerived>
-bool LDLT<MatrixType>
-::solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const
+  // Reference for the algorithm: Davis and Hager, "Multiple Rank
+  // Modifications of a Sparse Cholesky Factorization" (Algorithm 1)
+  // Trivial rearrangements of their computations (Timothy E. Holy)
+  // allow their algorithm to work for rank-1 updates even if the
+  // original matrix is not of full rank.
+  // Here only rank-1 updates are implemented, to reduce the
+  // requirement for intermediate storage and improve accuracy
+  template<typename MatrixType, typename WDerived>
+  static bool updateInPlace(MatrixType& mat, MatrixBase<WDerived>& w, const typename MatrixType::RealScalar& sigma=1)
+  {
+    using numext::isfinite;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+
+    const Index size = mat.rows();
+    eigen_assert(mat.cols() == size && w.size()==size);
+
+    RealScalar alpha = 1;
+
+    // Apply the update
+    for (Index j = 0; j < size; j++)
+    {
+      // Check for termination due to an original decomposition of low-rank
+      if (!(isfinite)(alpha))
+        break;
+
+      // Update the diagonal terms
+      RealScalar dj = numext::real(mat.coeff(j,j));
+      Scalar wj = w.coeff(j);
+      RealScalar swj2 = sigma*numext::abs2(wj);
+      RealScalar gamma = dj*alpha + swj2;
+
+      mat.coeffRef(j,j) += swj2/alpha;
+      alpha += swj2/dj;
+
+
+      // Update the terms of L
+      Index rs = size-j-1;
+      w.tail(rs) -= wj * mat.col(j).tail(rs);
+      if(gamma != 0)
+        mat.col(j).tail(rs) += (sigma*numext::conj(wj)/gamma)*w.tail(rs);
+    }
+    return true;
+  }
+
+  template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
+  static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, const typename MatrixType::RealScalar& sigma=1)
+  {
+    // Apply the permutation to the input w
+    tmp = transpositions * w;
+
+    return ldlt_inplace<Lower>::updateInPlace(mat,tmp,sigma);
+  }
+};
+
+template<> struct ldlt_inplace<Upper>
 {
-  const int size = m_matrix.rows();
-  ei_assert(size==b.rows() && "LLT::solve(): invalid number of rows of the right hand side matrix b");
-  *result = b;
-  return solveInPlace(*result);
+  template<typename MatrixType, typename TranspositionType, typename Workspace>
+  static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign)
+  {
+    Transpose<MatrixType> matt(mat);
+    return ldlt_inplace<Lower>::unblocked(matt, transpositions, temp, sign);
+  }
+
+  template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
+  static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, const typename MatrixType::RealScalar& sigma=1)
+  {
+    Transpose<MatrixType> matt(mat);
+    return ldlt_inplace<Lower>::update(matt, transpositions, tmp, w.conjugate(), sigma);
+  }
+};
+
+template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
+{
+  typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
+  typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return m; }
+  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+};
+
+template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
+{
+  typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
+  typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixU getU(const MatrixType& m) { return m; }
+};
+
+} // end namespace internal
+
+/** Compute / recompute the LDLT decomposition A = L D L^* = U^* D U of \a matrix
+  */
+template<typename MatrixType, int _UpLo>
+LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
+{
+  check_template_parameters();
+  
+  eigen_assert(a.rows()==a.cols());
+  const Index size = a.rows();
+
+  m_matrix = a;
+
+  m_transpositions.resize(size);
+  m_isInitialized = false;
+  m_temporary.resize(size);
+  m_sign = internal::ZeroSign;
+
+  internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign);
+
+  m_isInitialized = true;
+  return *this;
 }
 
-/** This is the \em in-place version of solve().
+/** Update the LDLT decomposition:  given A = L D L^T, efficiently compute the decomposition of A + sigma w w^T.
+ * \param w a vector to be incorporated into the decomposition.
+ * \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column vectors. Optional; default value is +1.
+ * \sa setZero()
+  */
+template<typename MatrixType, int _UpLo>
+template<typename Derived>
+LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename NumTraits<typename MatrixType::Scalar>::Real& sigma)
+{
+  const Index size = w.rows();
+  if (m_isInitialized)
+  {
+    eigen_assert(m_matrix.rows()==size);
+  }
+  else
+  {    
+    m_matrix.resize(size,size);
+    m_matrix.setZero();
+    m_transpositions.resize(size);
+    for (Index i = 0; i < size; i++)
+      m_transpositions.coeffRef(i) = i;
+    m_temporary.resize(size);
+    m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef;
+    m_isInitialized = true;
+  }
+
+  internal::ldlt_inplace<UpLo>::update(m_matrix, m_transpositions, m_temporary, w, sigma);
+
+  return *this;
+}
+
+namespace internal {
+template<typename _MatrixType, int _UpLo, typename Rhs>
+struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
+  : solve_retval_base<LDLT<_MatrixType,_UpLo>, Rhs>
+{
+  typedef LDLT<_MatrixType,_UpLo> LDLTType;
+  EIGEN_MAKE_SOLVE_HELPERS(LDLTType,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    eigen_assert(rhs().rows() == dec().matrixLDLT().rows());
+    // dst = P b
+    dst = dec().transpositionsP() * rhs();
+
+    // dst = L^-1 (P b)
+    dec().matrixL().solveInPlace(dst);
+
+    // dst = D^-1 (L^-1 P b)
+    // more precisely, use pseudo-inverse of D (see bug 241)
+    using std::abs;
+    using std::max;
+    typedef typename LDLTType::MatrixType MatrixType;
+    typedef typename LDLTType::RealScalar RealScalar;
+    const typename Diagonal<const MatrixType>::RealReturnType vectorD(dec().vectorD());
+    // In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon
+    // as motivated by LAPACK's xGELSS:
+    // RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() *NumTraits<RealScalar>::epsilon(),RealScalar(1) / NumTraits<RealScalar>::highest());
+    // However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest
+    // diagonal element is not well justified and to numerical issues in some cases.
+    // Moreover, Lapack's xSYTRS routines use 0 for the tolerance.
+    RealScalar tolerance = RealScalar(1) / NumTraits<RealScalar>::highest();
+    
+    for (Index i = 0; i < vectorD.size(); ++i) {
+      if(abs(vectorD(i)) > tolerance)
+        dst.row(i) /= vectorD(i);
+      else
+        dst.row(i).setZero();
+    }
+
+    // dst = L^-T (D^-1 L^-1 P b)
+    dec().matrixU().solveInPlace(dst);
+
+    // dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b
+    dst = dec().transpositionsP().transpose() * dst;
+  }
+};
+}
+
+/** \internal use x = ldlt_object.solve(x);
+  *
+  * This is the \em in-place version of solve().
   *
   * \param bAndX represents both the right-hand side matrix b and result x.
   *
+  * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD.
+  *
   * This version avoids a copy when the right hand side matrix b is not
   * needed anymore.
   *
   * \sa LDLT::solve(), MatrixBase::ldlt()
   */
-template<typename MatrixType>
+template<typename MatrixType,int _UpLo>
 template<typename Derived>
-bool LDLT<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
+bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
 {
-  const int size = m_matrix.rows();
-  ei_assert(size==bAndX.rows());
-  if (!m_isPositiveDefinite)
-    return false;
-  matrixL().solveTriangularInPlace(bAndX);
-  bAndX = (m_matrix.cwise().inverse().template part<Diagonal>() * bAndX).lazy();
-  m_matrix.adjoint().template part<UnitUpperTriangular>().solveTriangularInPlace(bAndX);
+  eigen_assert(m_isInitialized && "LDLT is not initialized.");
+  eigen_assert(m_matrix.rows() == bAndX.rows());
+
+  bAndX = this->solve(bAndX);
+
   return true;
 }
 
-/** \cholesky_module
-  * \returns the Cholesky decomposition without square root of \c *this
-  */
-template<typename Derived>
-inline const LDLT<typename MatrixBase<Derived>::PlainMatrixType>
-MatrixBase<Derived>::ldlt() const
+/** \returns the matrix represented by the decomposition,
+ * i.e., it returns the product: P^T L D L^* P.
+ * This function is provided for debug purpose. */
+template<typename MatrixType, int _UpLo>
+MatrixType LDLT<MatrixType,_UpLo>::reconstructedMatrix() const
 {
-  return derived();
+  eigen_assert(m_isInitialized && "LDLT is not initialized.");
+  const Index size = m_matrix.rows();
+  MatrixType res(size,size);
+
+  // P
+  res.setIdentity();
+  res = transpositionsP() * res;
+  // L^* P
+  res = matrixU() * res;
+  // D(L^*P)
+  res = vectorD().real().asDiagonal() * res;
+  // L(DL^*P)
+  res = matrixL() * res;
+  // P^T (LDL^*P)
+  res = transpositionsP().transpose() * res;
+
+  return res;
 }
 
+/** \cholesky_module
+  * \returns the Cholesky decomposition with full pivoting without square root of \c *this
+  */
+template<typename MatrixType, unsigned int UpLo>
+inline const LDLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
+SelfAdjointView<MatrixType, UpLo>::ldlt() const
+{
+  return LDLT<PlainObject,UpLo>(m_matrix);
+}
+
+/** \cholesky_module
+  * \returns the Cholesky decomposition with full pivoting without square root of \c *this
+  */
+template<typename Derived>
+inline const LDLT<typename MatrixBase<Derived>::PlainObject>
+MatrixBase<Derived>::ldlt() const
+{
+  return LDLT<PlainObject>(derived());
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_LDLT_H

Eigen/src/Cholesky/LLT.h

@@ -1,37 +1,30 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LLT_H
 #define EIGEN_LLT_H
 
-/** \ingroup cholesky_Module
+namespace Eigen { 
+
+namespace internal{
+template<typename MatrixType, int UpLo> struct LLT_Traits;
+}
+
+/** \ingroup Cholesky_Module
   *
   * \class LLT
   *
   * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
   *
   * \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
+  * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
+  *             The other triangular part won't be read.
   *
   * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
   * matrix A such that A = LL^* = U^*U, where L is lower triangular.
@@ -41,146 +34,465 @@
   * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other
   * situations like generalised eigen problems with hermitian matrices.
   *
-  * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
-  * the strict lower part does not have to store correct values.
+  * Remember that Cholesky decompositions are not rank-revealing. This LLT decomposition is only stable on positive definite matrices,
+  * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations
+  * has a solution.
   *
+  * Example: \include LLT_example.cpp
+  * Output: \verbinclude LLT_example.out
+  *    
   * \sa MatrixBase::llt(), class LDLT
   */
-template<typename MatrixType> class LLT
+ /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH)
+  * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
+  * the strict lower part does not have to store correct values.
+  */
+template<typename _MatrixType, int _UpLo> class LLT
 {
-  private:
+  public:
+    typedef _MatrixType MatrixType;
+    enum {
+      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      Options = MatrixType::Options,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
+    typedef typename MatrixType::Index Index;
 
     enum {
-      PacketSize = ei_packet_traits<Scalar>::size,
-      AlignmentMask = int(PacketSize)-1
+      PacketSize = internal::packet_traits<Scalar>::size,
+      AlignmentMask = int(PacketSize)-1,
+      UpLo = _UpLo
     };
 
-  public:
+    typedef internal::LLT_Traits<MatrixType,UpLo> Traits;
+
+    /**
+      * \brief Default Constructor.
+      *
+      * The default constructor is useful in cases in which the user intends to
+      * perform decompositions via LLT::compute(const MatrixType&).
+      */
+    LLT() : m_matrix(), m_isInitialized(false) {}
+
+    /** \brief Default Constructor with memory preallocation
+      *
+      * Like the default constructor but with preallocation of the internal data
+      * according to the specified problem \a size.
+      * \sa LLT()
+      */
+    LLT(Index size) : m_matrix(size, size),
+                    m_isInitialized(false) {}
 
     LLT(const MatrixType& matrix)
-      : m_matrix(matrix.rows(), matrix.cols())
+      : m_matrix(matrix.rows(), matrix.cols()),
+        m_isInitialized(false)
     {
       compute(matrix);
     }
 
-    /** \returns the lower triangular matrix L */
-    inline Part<MatrixType, LowerTriangular> matrixL(void) const { return m_matrix; }
+    /** \returns a view of the upper triangular matrix U */
+    inline typename Traits::MatrixU matrixU() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return Traits::getU(m_matrix);
+    }
 
-    /** \returns true if the matrix is positive definite */
-    inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
+    /** \returns a view of the lower triangular matrix L */
+    inline typename Traits::MatrixL matrixL() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return Traits::getL(m_matrix);
+    }
 
-    template<typename RhsDerived, typename ResDerived>
-    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * Since this LLT class assumes anyway that the matrix A is invertible, the solution
+      * theoretically exists and is unique regardless of b.
+      *
+      * Example: \include LLT_solve.cpp
+      * Output: \verbinclude LLT_solve.out
+      *
+      * \sa solveInPlace(), MatrixBase::llt()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<LLT, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      eigen_assert(m_matrix.rows()==b.rows()
+                && "LLT::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<LLT, Rhs>(*this, b.derived());
+    }
+
+    #ifdef EIGEN2_SUPPORT
+    template<typename OtherDerived, typename ResultType>
+    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
+    {
+      *result = this->solve(b);
+      return true;
+    }
+    
+    bool isPositiveDefinite() const { return true; }
+    #endif
 
     template<typename Derived>
-    bool solveInPlace(MatrixBase<Derived> &bAndX) const;
+    void solveInPlace(MatrixBase<Derived> &bAndX) const;
 
-    void compute(const MatrixType& matrix);
+    LLT& compute(const MatrixType& matrix);
+
+    /** \returns the LLT decomposition matrix
+      *
+      * TODO: document the storage layout
+      */
+    inline const MatrixType& matrixLLT() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return m_matrix;
+    }
+
+    MatrixType reconstructedMatrix() const;
+
+
+    /** \brief Reports whether previous computation was successful.
+      *
+      * \returns \c Success if computation was succesful,
+      *          \c NumericalIssue if the matrix.appears to be negative.
+      */
+    ComputationInfo info() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return m_info;
+    }
+
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+
+    template<typename VectorType>
+    LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
 
   protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
     /** \internal
       * Used to compute and store L
       * The strict upper part is not used and even not initialized.
       */
     MatrixType m_matrix;
-    bool m_isPositiveDefinite;
+    bool m_isInitialized;
+    ComputationInfo m_info;
 };
 
-/** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix
-  */
-template<typename MatrixType>
-void LLT<MatrixType>::compute(const MatrixType& a)
+namespace internal {
+
+template<typename Scalar, int UpLo> struct llt_inplace;
+
+template<typename MatrixType, typename VectorType>
+static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
 {
-  assert(a.rows()==a.cols());
-  const int size = a.rows();
-  m_matrix.resize(size, size);
-  const RealScalar eps = ei_sqrt(precision<Scalar>());
+  using std::sqrt;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::ColXpr ColXpr;
+  typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
+  typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
+  typedef Matrix<Scalar,Dynamic,1> TempVectorType;
+  typedef typename TempVectorType::SegmentReturnType TempVecSegment;
 
-  RealScalar x;
-  x = ei_real(a.coeff(0,0));
-  m_isPositiveDefinite = x > eps && ei_isMuchSmallerThan(ei_imag(a.coeff(0,0)), RealScalar(1));
-  m_matrix.coeffRef(0,0) = ei_sqrt(x);
-  m_matrix.col(0).end(size-1) = a.row(0).end(size-1).adjoint() / ei_real(m_matrix.coeff(0,0));
-  for (int j = 1; j < size; ++j)
+  Index n = mat.cols();
+  eigen_assert(mat.rows()==n && vec.size()==n);
+
+  TempVectorType temp;
+
+  if(sigma>0)
   {
-    Scalar tmp = ei_real(a.coeff(j,j)) - m_matrix.row(j).start(j).squaredNorm();
-    x = ei_real(tmp);
-    if (x < eps || (!ei_isMuchSmallerThan(ei_imag(tmp), RealScalar(1))))
+    // This version is based on Givens rotations.
+    // It is faster than the other one below, but only works for updates,
+    // i.e., for sigma > 0
+    temp = sqrt(sigma) * vec;
+
+    for(Index i=0; i<n; ++i)
     {
-      m_isPositiveDefinite = false;
-      return;
-    }
-    m_matrix.coeffRef(j,j) = x = ei_sqrt(x);
+      JacobiRotation<Scalar> g;
+      g.makeGivens(mat(i,i), -temp(i), &mat(i,i));
 
-    int endSize = size-j-1;
-    if (endSize>0) {
-      // Note that when all matrix columns have good alignment, then the following
-      // product is guaranteed to be optimal with respect to alignment.
-      m_matrix.col(j).end(endSize) =
-        (m_matrix.block(j+1, 0, endSize, j) * m_matrix.row(j).start(j).adjoint()).lazy();
-
-      // FIXME could use a.col instead of a.row
-      m_matrix.col(j).end(endSize) = (a.row(j).end(endSize).adjoint()
-        - m_matrix.col(j).end(endSize) ) / x;
+      Index rs = n-i-1;
+      if(rs>0)
+      {
+        ColXprSegment x(mat.col(i).tail(rs));
+        TempVecSegment y(temp.tail(rs));
+        apply_rotation_in_the_plane(x, y, g);
+      }
     }
   }
+  else
+  {
+    temp = vec;
+    RealScalar beta = 1;
+    for(Index j=0; j<n; ++j)
+    {
+      RealScalar Ljj = numext::real(mat.coeff(j,j));
+      RealScalar dj = numext::abs2(Ljj);
+      Scalar wj = temp.coeff(j);
+      RealScalar swj2 = sigma*numext::abs2(wj);
+      RealScalar gamma = dj*beta + swj2;
+
+      RealScalar x = dj + swj2/beta;
+      if (x<=RealScalar(0))
+        return j;
+      RealScalar nLjj = sqrt(x);
+      mat.coeffRef(j,j) = nLjj;
+      beta += swj2/dj;
+
+      // Update the terms of L
+      Index rs = n-j-1;
+      if(rs)
+      {
+        temp.tail(rs) -= (wj/Ljj) * mat.col(j).tail(rs);
+        if(gamma != 0)
+          mat.col(j).tail(rs) = (nLjj/Ljj) * mat.col(j).tail(rs) + (nLjj * sigma*numext::conj(wj)/gamma)*temp.tail(rs);
+      }
+    }
+  }
+  return -1;
 }
 
-/** Computes the solution x of \f$ A x = b \f$ using the current decomposition of A.
-  * The result is stored in \a result
-  *
-  * \returns true in case of success, false otherwise.
-  *
-  * In other words, it computes \f$ b = A^{-1} b \f$ with
-  * \f$ {L^{*}}^{-1} L^{-1} b \f$ from right to left.
-  *
-  * Example: \include LLT_solve.cpp
-  * Output: \verbinclude LLT_solve.out
-  *
-  * \sa LLT::solveInPlace(), MatrixBase::llt()
-  */
-template<typename MatrixType>
-template<typename RhsDerived, typename ResDerived>
-bool LLT<MatrixType>::solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const
+template<typename Scalar> struct llt_inplace<Scalar, Lower>
 {
-  const int size = m_matrix.rows();
-  ei_assert(size==b.rows() && "LLT::solve(): invalid number of rows of the right hand side matrix b");
-  return solveInPlace((*result) = b);
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  template<typename MatrixType>
+  static typename MatrixType::Index unblocked(MatrixType& mat)
+  {
+    using std::sqrt;
+    typedef typename MatrixType::Index Index;
+    
+    eigen_assert(mat.rows()==mat.cols());
+    const Index size = mat.rows();
+    for(Index k = 0; k < size; ++k)
+    {
+      Index rs = size-k-1; // remaining size
+
+      Block<MatrixType,Dynamic,1> A21(mat,k+1,k,rs,1);
+      Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
+      Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k);
+
+      RealScalar x = numext::real(mat.coeff(k,k));
+      if (k>0) x -= A10.squaredNorm();
+      if (x<=RealScalar(0))
+        return k;
+      mat.coeffRef(k,k) = x = sqrt(x);
+      if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint();
+      if (rs>0) A21 *= RealScalar(1)/x;
+    }
+    return -1;
+  }
+
+  template<typename MatrixType>
+  static typename MatrixType::Index blocked(MatrixType& m)
+  {
+    typedef typename MatrixType::Index Index;
+    eigen_assert(m.rows()==m.cols());
+    Index size = m.rows();
+    if(size<32)
+      return unblocked(m);
+
+    Index blockSize = size/8;
+    blockSize = (blockSize/16)*16;
+    blockSize = (std::min)((std::max)(blockSize,Index(8)), Index(128));
+
+    for (Index k=0; k<size; k+=blockSize)
+    {
+      // partition the matrix:
+      //       A00 |  -  |  -
+      // lu  = A10 | A11 |  -
+      //       A20 | A21 | A22
+      Index bs = (std::min)(blockSize, size-k);
+      Index rs = size - k - bs;
+      Block<MatrixType,Dynamic,Dynamic> A11(m,k,   k,   bs,bs);
+      Block<MatrixType,Dynamic,Dynamic> A21(m,k+bs,k,   rs,bs);
+      Block<MatrixType,Dynamic,Dynamic> A22(m,k+bs,k+bs,rs,rs);
+
+      Index ret;
+      if((ret=unblocked(A11))>=0) return k+ret;
+      if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
+      if(rs>0) A22.template selfadjointView<Lower>().rankUpdate(A21,-1); // bottleneck
+    }
+    return -1;
+  }
+
+  template<typename MatrixType, typename VectorType>
+  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
+  {
+    return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
+  }
+};
+  
+template<typename Scalar> struct llt_inplace<Scalar, Upper>
+{
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+
+  template<typename MatrixType>
+  static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat)
+  {
+    Transpose<MatrixType> matt(mat);
+    return llt_inplace<Scalar, Lower>::unblocked(matt);
+  }
+  template<typename MatrixType>
+  static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat)
+  {
+    Transpose<MatrixType> matt(mat);
+    return llt_inplace<Scalar, Lower>::blocked(matt);
+  }
+  template<typename MatrixType, typename VectorType>
+  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
+  {
+    Transpose<MatrixType> matt(mat);
+    return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
+  }
+};
+
+template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
+{
+  typedef const TriangularView<const MatrixType, Lower> MatrixL;
+  typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return m; }
+  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  static bool inplace_decomposition(MatrixType& m)
+  { return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
+};
+
+template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
+{
+  typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
+  typedef const TriangularView<const MatrixType, Upper> MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixU getU(const MatrixType& m) { return m; }
+  static bool inplace_decomposition(MatrixType& m)
+  { return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; }
+};
+
+} // end namespace internal
+
+/** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix
+  *
+  * \returns a reference to *this
+  *
+  * Example: \include TutorialLinAlgComputeTwice.cpp
+  * Output: \verbinclude TutorialLinAlgComputeTwice.out
+  */
+template<typename MatrixType, int _UpLo>
+LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
+{
+  check_template_parameters();
+  
+  eigen_assert(a.rows()==a.cols());
+  const Index size = a.rows();
+  m_matrix.resize(size, size);
+  m_matrix = a;
+
+  m_isInitialized = true;
+  bool ok = Traits::inplace_decomposition(m_matrix);
+  m_info = ok ? Success : NumericalIssue;
+
+  return *this;
 }
 
-/** This is the \em in-place version of solve().
+/** Performs a rank one update (or dowdate) of the current decomposition.
+  * If A = LL^* before the rank one update,
+  * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector
+  * of same dimension.
+  */
+template<typename _MatrixType, int _UpLo>
+template<typename VectorType>
+LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma)
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType);
+  eigen_assert(v.size()==m_matrix.cols());
+  eigen_assert(m_isInitialized);
+  if(internal::llt_inplace<typename MatrixType::Scalar, UpLo>::rankUpdate(m_matrix,v,sigma)>=0)
+    m_info = NumericalIssue;
+  else
+    m_info = Success;
+
+  return *this;
+}
+    
+namespace internal {
+template<typename _MatrixType, int UpLo, typename Rhs>
+struct solve_retval<LLT<_MatrixType, UpLo>, Rhs>
+  : solve_retval_base<LLT<_MatrixType, UpLo>, Rhs>
+{
+  typedef LLT<_MatrixType,UpLo> LLTType;
+  EIGEN_MAKE_SOLVE_HELPERS(LLTType,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dst = rhs();
+    dec().solveInPlace(dst);
+  }
+};
+}
+
+/** \internal use x = llt_object.solve(x);
+  * 
+  * This is the \em in-place version of solve().
   *
   * \param bAndX represents both the right-hand side matrix b and result x.
   *
+  * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD.
+  *
   * This version avoids a copy when the right hand side matrix b is not
   * needed anymore.
   *
   * \sa LLT::solve(), MatrixBase::llt()
   */
-template<typename MatrixType>
+template<typename MatrixType, int _UpLo>
 template<typename Derived>
-bool LLT<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
+void LLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
 {
-  const int size = m_matrix.rows();
-  ei_assert(size==bAndX.rows());
-  if (!m_isPositiveDefinite)
-    return false;
-  matrixL().solveTriangularInPlace(bAndX);
-  m_matrix.adjoint().template part<UpperTriangular>().solveTriangularInPlace(bAndX);
-  return true;
+  eigen_assert(m_isInitialized && "LLT is not initialized.");
+  eigen_assert(m_matrix.rows()==bAndX.rows());
+  matrixL().solveInPlace(bAndX);
+  matrixU().solveInPlace(bAndX);
+}
+
+/** \returns the matrix represented by the decomposition,
+ * i.e., it returns the product: L L^*.
+ * This function is provided for debug purpose. */
+template<typename MatrixType, int _UpLo>
+MatrixType LLT<MatrixType,_UpLo>::reconstructedMatrix() const
+{
+  eigen_assert(m_isInitialized && "LLT is not initialized.");
+  return matrixL() * matrixL().adjoint().toDenseMatrix();
 }
 
 /** \cholesky_module
   * \returns the LLT decomposition of \c *this
   */
 template<typename Derived>
-inline const LLT<typename MatrixBase<Derived>::PlainMatrixType>
+inline const LLT<typename MatrixBase<Derived>::PlainObject>
 MatrixBase<Derived>::llt() const
 {
-  return LLT<PlainMatrixType>(derived());
+  return LLT<PlainObject>(derived());
 }
 
+/** \cholesky_module
+  * \returns the LLT decomposition of \c *this
+  */
+template<typename MatrixType, unsigned int UpLo>
+inline const LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
+SelfAdjointView<MatrixType, UpLo>::llt() const
+{
+  return LLT<PlainObject,UpLo>(m_matrix);
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_LLT_H

Eigen/src/Cholesky/LLT_MKL.h

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

Eigen/src/CholmodSupport/CMakeLists.txt

@@ -0,0 +1,6 @@
+FILE(GLOB Eigen_CholmodSupport_SRCS "*.h")
+
+INSTALL(FILES 
+  ${Eigen_CholmodSupport_SRCS}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/CholmodSupport COMPONENT Devel
+  )

Eigen/src/CholmodSupport/CholmodSupport.h

@@ -0,0 +1,607 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CHOLMODSUPPORT_H
+#define EIGEN_CHOLMODSUPPORT_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Scalar, typename CholmodType>
+void cholmod_configure_matrix(CholmodType& mat)
+{
+  if (internal::is_same<Scalar,float>::value)
+  {
+    mat.xtype = CHOLMOD_REAL;
+    mat.dtype = CHOLMOD_SINGLE;
+  }
+  else if (internal::is_same<Scalar,double>::value)
+  {
+    mat.xtype = CHOLMOD_REAL;
+    mat.dtype = CHOLMOD_DOUBLE;
+  }
+  else if (internal::is_same<Scalar,std::complex<float> >::value)
+  {
+    mat.xtype = CHOLMOD_COMPLEX;
+    mat.dtype = CHOLMOD_SINGLE;
+  }
+  else if (internal::is_same<Scalar,std::complex<double> >::value)
+  {
+    mat.xtype = CHOLMOD_COMPLEX;
+    mat.dtype = CHOLMOD_DOUBLE;
+  }
+  else
+  {
+    eigen_assert(false && "Scalar type not supported by CHOLMOD");
+  }
+}
+
+} // namespace internal
+
+/** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
+  * Note that the data are shared.
+  */
+template<typename _Scalar, int _Options, typename _Index>
+cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
+{
+  cholmod_sparse res;
+  res.nzmax   = mat.nonZeros();
+  res.nrow    = mat.rows();;
+  res.ncol    = mat.cols();
+  res.p       = mat.outerIndexPtr();
+  res.i       = mat.innerIndexPtr();
+  res.x       = mat.valuePtr();
+  res.z       = 0;
+  res.sorted  = 1;
+  if(mat.isCompressed())
+  {
+    res.packed  = 1;
+    res.nz = 0;
+  }
+  else
+  {
+    res.packed  = 0;
+    res.nz = mat.innerNonZeroPtr();
+  }
+
+  res.dtype   = 0;
+  res.stype   = -1;
+  
+  if (internal::is_same<_Index,int>::value)
+  {
+    res.itype = CHOLMOD_INT;
+  }
+  else if (internal::is_same<_Index,UF_long>::value)
+  {
+    res.itype = CHOLMOD_LONG;
+  }
+  else
+  {
+    eigen_assert(false && "Index type not supported yet");
+  }
+
+  // setup res.xtype
+  internal::cholmod_configure_matrix<_Scalar>(res);
+  
+  res.stype = 0;
+  
+  return res;
+}
+
+template<typename _Scalar, int _Options, typename _Index>
+const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>& mat)
+{
+  cholmod_sparse res = viewAsCholmod(mat.const_cast_derived());
+  return res;
+}
+
+/** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
+  * The data are not copied but shared. */
+template<typename _Scalar, int _Options, typename _Index, unsigned int UpLo>
+cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
+{
+  cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived());
+  
+  if(UpLo==Upper) res.stype =  1;
+  if(UpLo==Lower) res.stype = -1;
+
+  return res;
+}
+
+/** Returns a view of the Eigen \b dense matrix \a mat as Cholmod dense matrix.
+  * The data are not copied but shared. */
+template<typename Derived>
+cholmod_dense viewAsCholmod(MatrixBase<Derived>& mat)
+{
+  EIGEN_STATIC_ASSERT((internal::traits<Derived>::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  typedef typename Derived::Scalar Scalar;
+
+  cholmod_dense res;
+  res.nrow   = mat.rows();
+  res.ncol   = mat.cols();
+  res.nzmax  = res.nrow * res.ncol;
+  res.d      = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride();
+  res.x      = (void*)(mat.derived().data());
+  res.z      = 0;
+
+  internal::cholmod_configure_matrix<Scalar>(res);
+
+  return res;
+}
+
+/** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
+  * The data are not copied but shared. */
+template<typename Scalar, int Flags, typename Index>
+MappedSparseMatrix<Scalar,Flags,Index> viewAsEigen(cholmod_sparse& cm)
+{
+  return MappedSparseMatrix<Scalar,Flags,Index>
+         (cm.nrow, cm.ncol, static_cast<Index*>(cm.p)[cm.ncol],
+          static_cast<Index*>(cm.p), static_cast<Index*>(cm.i),static_cast<Scalar*>(cm.x) );
+}
+
+enum CholmodMode {
+  CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt
+};
+
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodBase
+  * \brief The base class for the direct Cholesky factorization of Cholmod
+  * \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
+  */
+template<typename _MatrixType, int _UpLo, typename Derived>
+class CholmodBase : internal::noncopyable
+{
+  public:
+    typedef _MatrixType MatrixType;
+    enum { UpLo = _UpLo };
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef MatrixType CholMatrixType;
+    typedef typename MatrixType::Index Index;
+
+  public:
+
+    CholmodBase()
+      : m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
+    {
+      m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
+      cholmod_start(&m_cholmod);
+    }
+
+    CholmodBase(const MatrixType& matrix)
+      : m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
+    {
+      m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
+      cholmod_start(&m_cholmod);
+      compute(matrix);
+    }
+
+    ~CholmodBase()
+    {
+      if(m_cholmodFactor)
+        cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
+      cholmod_finish(&m_cholmod);
+    }
+    
+    inline Index cols() const { return m_cholmodFactor->n; }
+    inline Index rows() const { return m_cholmodFactor->n; }
+    
+    Derived& derived() { return *static_cast<Derived*>(this); }
+    const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    
+    /** \brief Reports whether previous computation was successful.
+      *
+      * \returns \c Success if computation was succesful,
+      *          \c NumericalIssue if the matrix.appears to be negative.
+      */
+    ComputationInfo info() const
+    {
+      eigen_assert(m_isInitialized && "Decomposition is not initialized.");
+      return m_info;
+    }
+
+    /** Computes the sparse Cholesky decomposition of \a matrix */
+    Derived& compute(const MatrixType& matrix)
+    {
+      analyzePattern(matrix);
+      factorize(matrix);
+      return derived();
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<CholmodBase, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<CholmodBase, Rhs>(*this, b.derived());
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::sparse_solve_retval<CholmodBase, Rhs>
+    solve(const SparseMatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::sparse_solve_retval<CholmodBase, Rhs>(*this, b.derived());
+    }
+    
+    /** Performs a symbolic decomposition on the sparsity pattern of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      * 
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    {
+      if(m_cholmodFactor)
+      {
+        cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
+        m_cholmodFactor = 0;
+      }
+      cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
+      m_cholmodFactor = cholmod_analyze(&A, &m_cholmod);
+      
+      this->m_isInitialized = true;
+      this->m_info = Success;
+      m_analysisIsOk = true;
+      m_factorizationIsOk = false;
+    }
+    
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    void factorize(const MatrixType& matrix)
+    {
+      eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
+      cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
+      cholmod_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, &m_cholmod);
+      
+      // If the factorization failed, minor is the column at which it did. On success minor == n.
+      this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
+      m_factorizationIsOk = true;
+    }
+    
+    /** Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations.
+     *  See the Cholmod user guide for details. */
+    cholmod_common& cholmod() { return m_cholmod; }
+    
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal */
+    template<typename Rhs,typename Dest>
+    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    {
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      const Index size = m_cholmodFactor->n;
+      EIGEN_UNUSED_VARIABLE(size);
+      eigen_assert(size==b.rows());
+
+      // note: cd stands for Cholmod Dense
+      Rhs& b_ref(b.const_cast_derived());
+      cholmod_dense b_cd = viewAsCholmod(b_ref);
+      cholmod_dense* x_cd = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &b_cd, &m_cholmod);
+      if(!x_cd)
+      {
+        this->m_info = NumericalIssue;
+      }
+      // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
+      dest = Matrix<Scalar,Dest::RowsAtCompileTime,Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),b.rows(),b.cols());
+      cholmod_free_dense(&x_cd, &m_cholmod);
+    }
+    
+    /** \internal */
+    template<typename RhsScalar, int RhsOptions, typename RhsIndex, typename DestScalar, int DestOptions, typename DestIndex>
+    void _solve(const SparseMatrix<RhsScalar,RhsOptions,RhsIndex> &b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+    {
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      const Index size = m_cholmodFactor->n;
+      EIGEN_UNUSED_VARIABLE(size);
+      eigen_assert(size==b.rows());
+
+      // note: cs stands for Cholmod Sparse
+      cholmod_sparse b_cs = viewAsCholmod(b);
+      cholmod_sparse* x_cs = cholmod_spsolve(CHOLMOD_A, m_cholmodFactor, &b_cs, &m_cholmod);
+      if(!x_cs)
+      {
+        this->m_info = NumericalIssue;
+      }
+      // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
+      dest = viewAsEigen<DestScalar,DestOptions,DestIndex>(*x_cs);
+      cholmod_free_sparse(&x_cs, &m_cholmod);
+    }
+    #endif // EIGEN_PARSED_BY_DOXYGEN
+    
+    
+    /** Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization.
+      *
+      * During the numerical factorization, an offset term is added to the diagonal coefficients:\n
+      * \c d_ii = \a offset + \c d_ii
+      *
+      * The default is \a offset=0.
+      *
+      * \returns a reference to \c *this.
+      */
+    Derived& setShift(const RealScalar& offset)
+    {
+      m_shiftOffset[0] = offset;
+      return derived();
+    }
+    
+    template<typename Stream>
+    void dumpMemory(Stream& /*s*/)
+    {}
+    
+  protected:
+    mutable cholmod_common m_cholmod;
+    cholmod_factor* m_cholmodFactor;
+    RealScalar m_shiftOffset[2];
+    mutable ComputationInfo m_info;
+    bool m_isInitialized;
+    int m_factorizationIsOk;
+    int m_analysisIsOk;
+};
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodSimplicialLLT
+  * \brief A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization
+  * using the Cholmod library.
+  * This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Therefore, it has little practical interest.
+  * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLLT
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodSimplicialLLT() : Base() { init(); }
+
+    CholmodSimplicialLLT(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodSimplicialLLT() {}
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 0;
+      m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+      m_cholmod.final_ll = 1;
+    }
+};
+
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodSimplicialLDLT
+  * \brief A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a simplicial LDL^T Cholesky factorization
+  * using the Cholmod library.
+  * This simplicial variant is equivalent to Eigen's built-in SimplicialLDLT class. Therefore, it has little practical interest.
+  * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLDLT
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodSimplicialLDLT() : Base() { init(); }
+
+    CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodSimplicialLDLT() {}
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 1;
+      m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+    }
+};
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodSupernodalLLT
+  * \brief A supernodal Cholesky (LLT) factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a supernodal LL^T Cholesky factorization
+  * using the Cholmod library.
+  * This supernodal variant performs best on dense enough problems, e.g., 3D FEM, or very high order 2D FEM.
+  * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodSupernodalLLT() : Base() { init(); }
+
+    CholmodSupernodalLLT(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodSupernodalLLT() {}
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 1;
+      m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
+    }
+};
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodDecomposition
+  * \brief A general Cholesky factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization
+  * using the Cholmod library. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * This variant permits to change the underlying Cholesky method at runtime.
+  * On the other hand, it does not provide access to the result of the factorization.
+  * The default is to let Cholmod automatically choose between a simplicial and supernodal factorization.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodDecomposition() : Base() { init(); }
+
+    CholmodDecomposition(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodDecomposition() {}
+    
+    void setMode(CholmodMode mode)
+    {
+      switch(mode)
+      {
+        case CholmodAuto:
+          m_cholmod.final_asis = 1;
+          m_cholmod.supernodal = CHOLMOD_AUTO;
+          break;
+        case CholmodSimplicialLLt:
+          m_cholmod.final_asis = 0;
+          m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+          m_cholmod.final_ll = 1;
+          break;
+        case CholmodSupernodalLLt:
+          m_cholmod.final_asis = 1;
+          m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
+          break;
+        case CholmodLDLt:
+          m_cholmod.final_asis = 1;
+          m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+          break;
+        default:
+          break;
+      }
+    }
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 1;
+      m_cholmod.supernodal = CHOLMOD_AUTO;
+    }
+};
+
+namespace internal {
+  
+template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
+struct solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+  : solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+{
+  typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
+struct sparse_solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+  : sparse_solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+{
+  typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CHOLMODSUPPORT_H

Eigen/src/Core/Array.h

@@ -0,0 +1,308 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ARRAY_H
+#define EIGEN_ARRAY_H
+
+namespace Eigen {
+
+/** \class Array 
+  * \ingroup Core_Module
+  *
+  * \brief General-purpose arrays with easy API for coefficient-wise operations
+  *
+  * The %Array class is very similar to the Matrix class. It provides
+  * general-purpose one- and two-dimensional arrays. The difference between the
+  * %Array and the %Matrix class is primarily in the API: the API for the
+  * %Array class provides easy access to coefficient-wise operations, while the
+  * API for the %Matrix class provides easy access to linear-algebra
+  * operations.
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
+  *
+  * \sa \ref TutorialArrayClass, \ref TopicClassHierarchy
+  */
+namespace internal {
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+{
+  typedef ArrayXpr XprKind;
+  typedef ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > XprBase;
+};
+}
+
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+class Array
+  : public PlainObjectBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+{
+  public:
+
+    typedef PlainObjectBase<Array> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Array)
+
+    enum { Options = _Options };
+    typedef typename Base::PlainObject PlainObject;
+
+  protected:
+    template <typename Derived, typename OtherDerived, bool IsVector>
+    friend struct internal::conservative_resize_like_impl;
+
+    using Base::m_storage;
+
+  public:
+
+    using Base::base;
+    using Base::coeff;
+    using Base::coeffRef;
+
+    /**
+      * The usage of
+      *   using Base::operator=;
+      * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
+      * the usage of 'using'. This should be done only for operator=.
+      */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other)
+    {
+      return Base::operator=(other);
+    }
+
+    /** Copies the value of the expression \a other into \c *this with automatic resizing.
+      *
+      * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
+      * it will be initialized.
+      *
+      * Note that copying a row-vector into a vector (and conversely) is allowed.
+      * The resizing, if any, is then done in the appropriate way so that row-vectors
+      * remain row-vectors and vectors remain vectors.
+      */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array& operator=(const ArrayBase<OtherDerived>& other)
+    {
+      return Base::_set(other);
+    }
+
+    /** This is a special case of the templated operator=. Its purpose is to
+      * prevent a default operator= from hiding the templated operator=.
+      */
+    EIGEN_STRONG_INLINE Array& operator=(const Array& other)
+    {
+      return Base::_set(other);
+    }
+
+    /** Default constructor.
+      *
+      * For fixed-size matrices, does nothing.
+      *
+      * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
+      * is called a null matrix. This constructor is the unique way to create null matrices: resizing
+      * a matrix to 0 is not supported.
+      *
+      * \sa resize(Index,Index)
+      */
+    EIGEN_STRONG_INLINE Array() : Base()
+    {
+      Base::_check_template_params();
+      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    }
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    // FIXME is it still needed ??
+    /** \internal */
+    Array(internal::constructor_without_unaligned_array_assert)
+      : Base(internal::constructor_without_unaligned_array_assert())
+    {
+      Base::_check_template_params();
+      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    }
+#endif
+
+    /** Constructs a vector or row-vector with given dimension. \only_for_vectors
+      *
+      * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
+      * it is redundant to pass the dimension here, so it makes more sense to use the default
+      * constructor Matrix() instead.
+      */
+    EIGEN_STRONG_INLINE explicit Array(Index dim)
+      : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Array)
+      eigen_assert(dim >= 0);
+      eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
+      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename T0, typename T1>
+    EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
+    {
+      Base::_check_template_params();
+      this->template _init2<T0,T1>(val0, val1);
+    }
+    #else
+    /** constructs an uninitialized matrix with \a rows rows and \a cols columns.
+      *
+      * This is useful for dynamic-size matrices. For fixed-size matrices,
+      * it is redundant to pass these parameters, so one should use the default constructor
+      * Matrix() instead. */
+    Array(Index rows, Index cols);
+    /** constructs an initialized 2D vector with given coefficients */
+    Array(const Scalar& val0, const Scalar& val1);
+    #endif
+
+    /** constructs an initialized 3D vector with given coefficients */
+    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
+      m_storage.data()[0] = val0;
+      m_storage.data()[1] = val1;
+      m_storage.data()[2] = val2;
+    }
+    /** constructs an initialized 4D vector with given coefficients */
+    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
+      m_storage.data()[0] = val0;
+      m_storage.data()[1] = val1;
+      m_storage.data()[2] = val2;
+      m_storage.data()[3] = val3;
+    }
+
+    explicit Array(const Scalar *data);
+
+    /** Constructor copying the value of the expression \a other */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array(const ArrayBase<OtherDerived>& other)
+             : Base(other.rows() * other.cols(), other.rows(), other.cols())
+    {
+      Base::_check_template_params();
+      Base::_set_noalias(other);
+    }
+    /** Copy constructor */
+    EIGEN_STRONG_INLINE Array(const Array& other)
+            : Base(other.rows() * other.cols(), other.rows(), other.cols())
+    {
+      Base::_check_template_params();
+      Base::_set_noalias(other);
+    }
+    /** Copy constructor with in-place evaluation */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array(const ReturnByValue<OtherDerived>& other)
+    {
+      Base::_check_template_params();
+      Base::resize(other.rows(), other.cols());
+      other.evalTo(*this);
+    }
+
+    /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
+      : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
+    {
+      Base::_check_template_params();
+      Base::_resize_to_match(other);
+      *this = other;
+    }
+
+    /** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
+      * data pointers.
+      */
+    template<typename OtherDerived>
+    void swap(ArrayBase<OtherDerived> const & other)
+    { this->_swap(other.derived()); }
+
+    inline Index innerStride() const { return 1; }
+    inline Index outerStride() const { return this->innerSize(); }
+
+    #ifdef EIGEN_ARRAY_PLUGIN
+    #include EIGEN_ARRAY_PLUGIN
+    #endif
+
+  private:
+
+    template<typename MatrixType, typename OtherDerived, bool SwapPointers>
+    friend struct internal::matrix_swap_impl;
+};
+
+/** \defgroup arraytypedefs Global array typedefs
+  * \ingroup Core_Module
+  *
+  * Eigen defines several typedef shortcuts for most common 1D and 2D array types.
+  *
+  * The general patterns are the following:
+  *
+  * \c ArrayRowsColsType where \c Rows and \c Cols can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size,
+  * and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c cd
+  * for complex double.
+  *
+  * For example, \c Array33d is a fixed-size 3x3 array type of doubles, and \c ArrayXXf is a dynamic-size matrix of floats.
+  *
+  * There are also \c ArraySizeType which are self-explanatory. For example, \c Array4cf is
+  * a fixed-size 1D array of 4 complex floats.
+  *
+  * \sa class Array
+  */
+
+#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix)   \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Size, Size> Array##SizeSuffix##SizeSuffix##TypeSuffix;  \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Size, 1>    Array##SizeSuffix##TypeSuffix;
+
+#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size)         \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Size, Dynamic> Array##Size##X##TypeSuffix;  \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Dynamic, Size> Array##X##Size##TypeSuffix;
+
+#define EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 2, 2) \
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 3, 3) \
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 4, 4) \
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \
+EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \
+EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \
+EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 4)
+
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(int,                  i)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(float,                f)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(double,               d)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<float>,  cf)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
+
+#undef EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES
+#undef EIGEN_MAKE_ARRAY_TYPEDEFS
+
+#undef EIGEN_MAKE_ARRAY_TYPEDEFS_LARGE
+
+#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
+using Eigen::Matrix##SizeSuffix##TypeSuffix; \
+using Eigen::Vector##SizeSuffix##TypeSuffix; \
+using Eigen::RowVector##SizeSuffix##TypeSuffix;
+
+#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(TypeSuffix) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
+
+#define EIGEN_USING_ARRAY_TYPEDEFS \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(i) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(f) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd)
+
+} // end namespace Eigen
+
+#endif // EIGEN_ARRAY_H

Eigen/src/Core/ArrayBase.h

@@ -0,0 +1,228 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ARRAYBASE_H
+#define EIGEN_ARRAYBASE_H
+
+namespace Eigen { 
+
+template<typename ExpressionType> class MatrixWrapper;
+
+/** \class ArrayBase
+  * \ingroup Core_Module
+  *
+  * \brief Base class for all 1D and 2D array, and related expressions
+  *
+  * An array is similar to a dense vector or matrix. While matrices are mathematical
+  * objects with well defined linear algebra operators, an array is just a collection
+  * of scalar values arranged in a one or two dimensionnal fashion. As the main consequence,
+  * all operations applied to an array are performed coefficient wise. Furthermore,
+  * arrays support scalar math functions of the c++ standard library (e.g., std::sin(x)), and convenient
+  * constructors allowing to easily write generic code working for both scalar values
+  * and arrays.
+  *
+  * This class is the base that is inherited by all array expression types.
+  *
+  * \tparam Derived is the derived type, e.g., an array or an expression type.
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN.
+  *
+  * \sa class MatrixBase, \ref TopicClassHierarchy
+  */
+template<typename Derived> class ArrayBase
+  : public DenseBase<Derived>
+{
+  public:
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** The base class for a given storage type. */
+    typedef ArrayBase StorageBaseType;
+
+    typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl;
+
+    using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
+                typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
+
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    typedef DenseBase<Derived> Base;
+    using Base::RowsAtCompileTime;
+    using Base::ColsAtCompileTime;
+    using Base::SizeAtCompileTime;
+    using Base::MaxRowsAtCompileTime;
+    using Base::MaxColsAtCompileTime;
+    using Base::MaxSizeAtCompileTime;
+    using Base::IsVectorAtCompileTime;
+    using Base::Flags;
+    using Base::CoeffReadCost;
+
+    using Base::derived;
+    using Base::const_cast_derived;
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::coeff;
+    using Base::coeffRef;
+    using Base::lazyAssign;
+    using Base::operator=;
+    using Base::operator+=;
+    using Base::operator-=;
+    using Base::operator*=;
+    using Base::operator/=;
+
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+
+#endif // not EIGEN_PARSED_BY_DOXYGEN
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal the plain matrix type corresponding to this expression. Note that is not necessarily
+      * exactly the return type of eval(): in the case of plain matrices, the return type of eval() is a const
+      * reference to a matrix, not a matrix! It is however guaranteed that the return type of eval() is either
+      * PlainObject or const PlainObject&.
+      */
+    typedef Array<typename internal::traits<Derived>::Scalar,
+                internal::traits<Derived>::RowsAtCompileTime,
+                internal::traits<Derived>::ColsAtCompileTime,
+                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
+                internal::traits<Derived>::MaxRowsAtCompileTime,
+                internal::traits<Derived>::MaxColsAtCompileTime
+          > PlainObject;
+
+
+    /** \internal Represents a matrix with all coefficients equal to one another*/
+    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
+#endif // not EIGEN_PARSED_BY_DOXYGEN
+
+#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase
+#   include "../plugins/CommonCwiseUnaryOps.h"
+#   include "../plugins/MatrixCwiseUnaryOps.h"
+#   include "../plugins/ArrayCwiseUnaryOps.h"
+#   include "../plugins/CommonCwiseBinaryOps.h"
+#   include "../plugins/MatrixCwiseBinaryOps.h"
+#   include "../plugins/ArrayCwiseBinaryOps.h"
+#   ifdef EIGEN_ARRAYBASE_PLUGIN
+#     include EIGEN_ARRAYBASE_PLUGIN
+#   endif
+#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
+
+    /** Special case of the template operator=, in order to prevent the compiler
+      * from generating a default operator= (issue hit with g++ 4.1)
+      */
+    Derived& operator=(const ArrayBase& other)
+    {
+      return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
+    }
+
+    Derived& operator+=(const Scalar& scalar)
+    { return *this = derived() + scalar; }
+    Derived& operator-=(const Scalar& scalar)
+    { return *this = derived() - scalar; }
+
+    template<typename OtherDerived>
+    Derived& operator+=(const ArrayBase<OtherDerived>& other);
+    template<typename OtherDerived>
+    Derived& operator-=(const ArrayBase<OtherDerived>& other);
+
+    template<typename OtherDerived>
+    Derived& operator*=(const ArrayBase<OtherDerived>& other);
+
+    template<typename OtherDerived>
+    Derived& operator/=(const ArrayBase<OtherDerived>& other);
+
+  public:
+    ArrayBase<Derived>& array() { return *this; }
+    const ArrayBase<Derived>& array() const { return *this; }
+
+    /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
+      * \sa MatrixBase::array() */
+    MatrixWrapper<Derived> matrix() { return derived(); }
+    const MatrixWrapper<const Derived> matrix() const { return derived(); }
+
+//     template<typename Dest>
+//     inline void evalTo(Dest& dst) const { dst = matrix(); }
+
+  protected:
+    ArrayBase() : Base() {}
+
+  private:
+    explicit ArrayBase(Index);
+    ArrayBase(Index,Index);
+    template<typename OtherDerived> explicit ArrayBase(const ArrayBase<OtherDerived>&);
+  protected:
+    // mixing arrays and matrices is not legal
+    template<typename OtherDerived> Derived& operator+=(const MatrixBase<OtherDerived>& )
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
+    // mixing arrays and matrices is not legal
+    template<typename OtherDerived> Derived& operator-=(const MatrixBase<OtherDerived>& )
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
+};
+
+/** replaces \c *this by \c *this - \a other.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
+{
+  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
+
+/** replaces \c *this by \c *this + \a other.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
+{
+  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
+
+/** replaces \c *this by \c *this * \a other coefficient wise.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
+{
+  SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
+
+/** replaces \c *this by \c *this / \a other coefficient wise.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
+{
+  SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_ARRAYBASE_H

Eigen/src/Core/ArrayWrapper.h

@@ -0,0 +1,264 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ARRAYWRAPPER_H
+#define EIGEN_ARRAYWRAPPER_H
+
+namespace Eigen { 
+
+/** \class ArrayWrapper
+  * \ingroup Core_Module
+  *
+  * \brief Expression of a mathematical vector or matrix as an array object
+  *
+  * This class is the return type of MatrixBase::array(), and most of the time
+  * this is the only way it is use.
+  *
+  * \sa MatrixBase::array(), class MatrixWrapper
+  */
+
+namespace internal {
+template<typename ExpressionType>
+struct traits<ArrayWrapper<ExpressionType> >
+  : public traits<typename remove_all<typename ExpressionType::Nested>::type >
+{
+  typedef ArrayXpr XprKind;
+  // Let's remove NestByRefBit
+  enum {
+    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags = Flags0 & ~NestByRefBit
+  };
+};
+}
+
+template<typename ExpressionType>
+class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
+{
+  public:
+    typedef ArrayBase<ArrayWrapper> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
+
+    typedef typename internal::conditional<
+                       internal::is_lvalue<ExpressionType>::value,
+                       Scalar,
+                       const Scalar
+                     >::type ScalarWithConstIfNotLvalue;
+
+    typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
+
+    inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
+
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
+
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
+    inline const Scalar* data() const { return m_expression.data(); }
+
+    inline CoeffReturnType coeff(Index rowId, Index colId) const
+    {
+      return m_expression.coeff(rowId, colId);
+    }
+
+    inline Scalar& coeffRef(Index rowId, Index colId)
+    {
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
+    }
+
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
+    {
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
+    }
+
+    inline CoeffReturnType coeff(Index index) const
+    {
+      return m_expression.coeff(index);
+    }
+
+    inline Scalar& coeffRef(Index index)
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
+
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index rowId, Index colId) const
+    {
+      return m_expression.template packet<LoadMode>(rowId, colId);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index index) const
+    {
+      return m_expression.template packet<LoadMode>(index);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index index, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
+    }
+
+    template<typename Dest>
+    inline void evalTo(Dest& dst) const { dst = m_expression; }
+
+    const typename internal::remove_all<NestedExpressionType>::type& 
+    nestedExpression() const 
+    {
+      return m_expression;
+    }
+
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index)  */
+    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index,Index)*/
+    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
+  protected:
+    NestedExpressionType m_expression;
+};
+
+/** \class MatrixWrapper
+  * \ingroup Core_Module
+  *
+  * \brief Expression of an array as a mathematical vector or matrix
+  *
+  * This class is the return type of ArrayBase::matrix(), and most of the time
+  * this is the only way it is use.
+  *
+  * \sa MatrixBase::matrix(), class ArrayWrapper
+  */
+
+namespace internal {
+template<typename ExpressionType>
+struct traits<MatrixWrapper<ExpressionType> >
+ : public traits<typename remove_all<typename ExpressionType::Nested>::type >
+{
+  typedef MatrixXpr XprKind;
+  // Let's remove NestByRefBit
+  enum {
+    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags = Flags0 & ~NestByRefBit
+  };
+};
+}
+
+template<typename ExpressionType>
+class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
+{
+  public:
+    typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
+
+    typedef typename internal::conditional<
+                       internal::is_lvalue<ExpressionType>::value,
+                       Scalar,
+                       const Scalar
+                     >::type ScalarWithConstIfNotLvalue;
+
+    typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
+
+    inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
+
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
+
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
+    inline const Scalar* data() const { return m_expression.data(); }
+
+    inline CoeffReturnType coeff(Index rowId, Index colId) const
+    {
+      return m_expression.coeff(rowId, colId);
+    }
+
+    inline Scalar& coeffRef(Index rowId, Index colId)
+    {
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
+    }
+
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
+    {
+      return m_expression.derived().coeffRef(rowId, colId);
+    }
+
+    inline CoeffReturnType coeff(Index index) const
+    {
+      return m_expression.coeff(index);
+    }
+
+    inline Scalar& coeffRef(Index index)
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
+
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index rowId, Index colId) const
+    {
+      return m_expression.template packet<LoadMode>(rowId, colId);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index index) const
+    {
+      return m_expression.template packet<LoadMode>(index);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index index, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
+    }
+
+    const typename internal::remove_all<NestedExpressionType>::type& 
+    nestedExpression() const 
+    {
+      return m_expression;
+    }
+
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index)  */
+    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index,Index)*/
+    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
+  protected:
+    NestedExpressionType m_expression;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_ARRAYWRAPPER_H

Eigen/src/Core/Assign.h

@@ -1,147 +1,191 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2007 Michael Olbrich <michael.olbrich@gmx.net>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ASSIGN_H
 #define EIGEN_ASSIGN_H
 
+namespace Eigen {
+
+namespace internal {
+
 /***************************************************************************
-* Part 1 : the logic deciding a strategy for vectorization and unrolling
+* Part 1 : the logic deciding a strategy for traversal and unrolling       *
 ***************************************************************************/
 
 template <typename Derived, typename OtherDerived>
-struct ei_assign_traits
+struct assign_traits
 {
 public:
   enum {
     DstIsAligned = Derived::Flags & AlignedBit,
+    DstHasDirectAccess = Derived::Flags & DirectAccessBit,
     SrcIsAligned = OtherDerived::Flags & AlignedBit,
-    SrcAlignment = DstIsAligned && SrcIsAligned ? Aligned : Unaligned
+    JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned
   };
 
 private:
   enum {
-    InnerSize = int(Derived::Flags)&RowMajorBit
-              ? Derived::ColsAtCompileTime
-              : Derived::RowsAtCompileTime,
-    InnerMaxSize = int(Derived::Flags)&RowMajorBit
-              ? Derived::MaxColsAtCompileTime
-              : Derived::MaxRowsAtCompileTime,
-    PacketSize = ei_packet_traits<typename Derived::Scalar>::size
+    InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
+              : int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
+              : int(Derived::RowsAtCompileTime),
+    InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
+              : int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
+              : int(Derived::MaxRowsAtCompileTime),
+    MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
+    PacketSize = packet_traits<typename Derived::Scalar>::size
   };
 
   enum {
-    MightVectorize = (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit)
-                  && ((int(Derived::Flags)&RowMajorBit)==(int(OtherDerived::Flags)&RowMajorBit)),
+    StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
+    MightVectorize = StorageOrdersAgree
+                  && (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
     MayInnerVectorize  = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
                        && int(DstIsAligned) && int(SrcIsAligned),
-    MayLinearVectorize = MightVectorize && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
-    MaySliceVectorize  = MightVectorize && int(InnerMaxSize)>=3*PacketSize /* slice vectorization can be slow, so we only
-      want it if the slices are big, which is indicated by InnerMaxSize rather than InnerSize, think of the case
-      of a dynamic block in a fixed-size matrix */
+    MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
+    MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
+                       && (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
+      /* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
+         so it's only good for large enough sizes. */
+    MaySliceVectorize  = MightVectorize && DstHasDirectAccess
+                       && (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
+      /* slice vectorization can be slow, so we only want it if the slices are big, which is
+         indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
+         in a fixed-size matrix */
   };
 
 public:
   enum {
-    Vectorization = int(MayInnerVectorize)  ? int(InnerVectorization)
-                  : int(MayLinearVectorize) ? int(LinearVectorization)
-                  : int(MaySliceVectorize)  ? int(SliceVectorization)
-                                            : int(NoVectorization)
+    Traversal = int(MayInnerVectorize)  ? int(InnerVectorizedTraversal)
+              : int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
+              : int(MaySliceVectorize)  ? int(SliceVectorizedTraversal)
+              : int(MayLinearize)       ? int(LinearTraversal)
+                                        : int(DefaultTraversal),
+    Vectorized = int(Traversal) == InnerVectorizedTraversal
+              || int(Traversal) == LinearVectorizedTraversal
+              || int(Traversal) == SliceVectorizedTraversal
   };
 
 private:
   enum {
-    UnrollingLimit      = EIGEN_UNROLLING_LIMIT * (int(Vectorization) == int(NoVectorization) ? 1 : int(PacketSize)),
-    MayUnrollCompletely = int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
-    MayUnrollInner      = int(InnerSize * OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
+    UnrollingLimit      = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
+    MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
+                       && int(OtherDerived::CoeffReadCost) != Dynamic
+                       && int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
+    MayUnrollInner      = int(InnerSize) != Dynamic
+                       && int(OtherDerived::CoeffReadCost) != Dynamic
+                       && int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
   };
 
 public:
   enum {
-    Unrolling = (int(Vectorization) == int(InnerVectorization) || int(Vectorization) == int(NoVectorization))
-              ? (
-                   int(MayUnrollCompletely) ? int(CompleteUnrolling)
-                 : int(MayUnrollInner)      ? int(InnerUnrolling)
-                                            : int(NoUnrolling)
-                )
-              : int(Vectorization) == int(LinearVectorization)
-              ? ( int(MayUnrollCompletely) && int(DstIsAligned) ? int(CompleteUnrolling) : int(NoUnrolling) )
+    Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
+                ? (
+                    int(MayUnrollCompletely) ? int(CompleteUnrolling)
+                  : int(MayUnrollInner)      ? int(InnerUnrolling)
+                                             : int(NoUnrolling)
+                  )
+              : int(Traversal) == int(LinearVectorizedTraversal)
+                ? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling) : int(NoUnrolling) )
+              : int(Traversal) == int(LinearTraversal)
+                ? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) : int(NoUnrolling) )
               : int(NoUnrolling)
   };
+
+#ifdef EIGEN_DEBUG_ASSIGN
+  static void debug()
+  {
+    EIGEN_DEBUG_VAR(DstIsAligned)
+    EIGEN_DEBUG_VAR(SrcIsAligned)
+    EIGEN_DEBUG_VAR(JointAlignment)
+    EIGEN_DEBUG_VAR(InnerSize)
+    EIGEN_DEBUG_VAR(InnerMaxSize)
+    EIGEN_DEBUG_VAR(PacketSize)
+    EIGEN_DEBUG_VAR(StorageOrdersAgree)
+    EIGEN_DEBUG_VAR(MightVectorize)
+    EIGEN_DEBUG_VAR(MayLinearize)
+    EIGEN_DEBUG_VAR(MayInnerVectorize)
+    EIGEN_DEBUG_VAR(MayLinearVectorize)
+    EIGEN_DEBUG_VAR(MaySliceVectorize)
+    EIGEN_DEBUG_VAR(Traversal)
+    EIGEN_DEBUG_VAR(UnrollingLimit)
+    EIGEN_DEBUG_VAR(MayUnrollCompletely)
+    EIGEN_DEBUG_VAR(MayUnrollInner)
+    EIGEN_DEBUG_VAR(Unrolling)
+  }
+#endif
 };
 
 /***************************************************************************
 * Part 2 : meta-unrollers
 ***************************************************************************/
 
+/************************
+*** Default traversal ***
+************************/
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct assign_DefaultTraversal_CompleteUnrolling
+{
+  enum {
+    outer = Index / Derived1::InnerSizeAtCompileTime,
+    inner = Index % Derived1::InnerSizeAtCompileTime
+  };
+
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    dst.copyCoeffByOuterInner(outer, inner, src);
+    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
+};
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct assign_DefaultTraversal_InnerUnrolling
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
+  {
+    dst.copyCoeffByOuterInner(outer, Index, src);
+    assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, outer);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
+};
+
 /***********************
-*** No vectorization ***
+*** Linear traversal ***
 ***********************/
 
 template<typename Derived1, typename Derived2, int Index, int Stop>
-struct ei_assign_novec_CompleteUnrolling
+struct assign_LinearTraversal_CompleteUnrolling
 {
-  enum {
-    row = int(Derived1::Flags)&RowMajorBit
-        ? Index / int(Derived1::ColsAtCompileTime)
-        : Index % Derived1::RowsAtCompileTime,
-    col = int(Derived1::Flags)&RowMajorBit
-        ? Index % int(Derived1::ColsAtCompileTime)
-        : Index / Derived1::RowsAtCompileTime
-  };
-
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
-    dst.copyCoeff(row, col, src);
-    ei_assign_novec_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
+    dst.copyCoeff(Index, src);
+    assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
   }
 };
 
 template<typename Derived1, typename Derived2, int Stop>
-struct ei_assign_novec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
+struct assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
-};
-
-template<typename Derived1, typename Derived2, int Index, int Stop>
-struct ei_assign_novec_InnerUnrolling
-{
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int row_or_col)
-  {
-    const bool rowMajor = int(Derived1::Flags)&RowMajorBit;
-    const int row = rowMajor ? row_or_col : Index;
-    const int col = rowMajor ? Index : row_or_col;
-    dst.copyCoeff(row, col, src);
-    ei_assign_novec_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, row_or_col);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Stop>
-struct ei_assign_novec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
-{
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
 };
 
 /**************************
@@ -149,49 +193,43 @@ struct ei_assign_novec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 **************************/
 
 template<typename Derived1, typename Derived2, int Index, int Stop>
-struct ei_assign_innervec_CompleteUnrolling
+struct assign_innervec_CompleteUnrolling
 {
   enum {
-    row = int(Derived1::Flags)&RowMajorBit
-        ? Index / int(Derived1::ColsAtCompileTime)
-        : Index % Derived1::RowsAtCompileTime,
-    col = int(Derived1::Flags)&RowMajorBit
-        ? Index % int(Derived1::ColsAtCompileTime)
-        : Index / Derived1::RowsAtCompileTime,
-    SrcAlignment = ei_assign_traits<Derived1,Derived2>::SrcAlignment
+    outer = Index / Derived1::InnerSizeAtCompileTime,
+    inner = Index % Derived1::InnerSizeAtCompileTime,
+    JointAlignment = assign_traits<Derived1,Derived2>::JointAlignment
   };
 
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
-    dst.template copyPacket<Derived2, Aligned, SrcAlignment>(row, col, src);
-    ei_assign_innervec_CompleteUnrolling<Derived1, Derived2,
-      Index+ei_packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src);
+    dst.template copyPacketByOuterInner<Derived2, Aligned, JointAlignment>(outer, inner, src);
+    assign_innervec_CompleteUnrolling<Derived1, Derived2,
+      Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src);
   }
 };
 
 template<typename Derived1, typename Derived2, int Stop>
-struct ei_assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
+struct assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, int Index, int Stop>
-struct ei_assign_innervec_InnerUnrolling
+struct assign_innervec_InnerUnrolling
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int row_or_col)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
   {
-    const int row = int(Derived1::Flags)&RowMajorBit ? row_or_col : Index;
-    const int col = int(Derived1::Flags)&RowMajorBit ? Index : row_or_col;
-    dst.template copyPacket<Derived2, Aligned, Aligned>(row, col, src);
-    ei_assign_innervec_InnerUnrolling<Derived1, Derived2,
-      Index+ei_packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src, row_or_col);
+    dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, Index, src);
+    assign_innervec_InnerUnrolling<Derived1, Derived2,
+      Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src, outer);
   }
 };
 
 template<typename Derived1, typename Derived2, int Stop>
-struct ei_assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
+struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
 };
 
 /***************************************************************************
@@ -199,53 +237,81 @@ struct ei_assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 ***************************************************************************/
 
 template<typename Derived1, typename Derived2,
-         int Vectorization = ei_assign_traits<Derived1, Derived2>::Vectorization,
-         int Unrolling = ei_assign_traits<Derived1, Derived2>::Unrolling>
-struct ei_assign_impl;
+         int Traversal = assign_traits<Derived1, Derived2>::Traversal,
+         int Unrolling = assign_traits<Derived1, Derived2>::Unrolling,
+         int Version = Specialized>
+struct assign_impl;
 
-/***********************
-*** No vectorization ***
-***********************/
+/************************
+*** Default traversal ***
+************************/
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, NoVectorization, NoUnrolling>
+template<typename Derived1, typename Derived2, int Unrolling, int Version>
+struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling, Version>
 {
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &, const Derived2 &) { }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
-    const int innerSize = dst.innerSize();
-    const int outerSize = dst.outerSize();
-    for(int j = 0; j < outerSize; ++j)
-      for(int i = 0; i < innerSize; ++i)
-      {
-        if(int(Derived1::Flags)&RowMajorBit)
-          dst.copyCoeff(j, i, src);
-        else
-          dst.copyCoeff(i, j, src);
-      }
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; ++inner)
+        dst.copyCoeffByOuterInner(outer, inner, src);
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, NoVectorization, CompleteUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
-    ei_assign_novec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, NoVectorization, InnerUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
-    const bool rowMajor = int(Derived1::Flags)&RowMajorBit;
-    const int innerSize = rowMajor ? Derived1::ColsAtCompileTime : Derived1::RowsAtCompileTime;
-    const int outerSize = dst.outerSize();
-    for(int j = 0; j < outerSize; ++j)
-      ei_assign_novec_InnerUnrolling<Derived1, Derived2, 0, innerSize>
-        ::run(dst, src, j);
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
+        ::run(dst, src, outer);
+  }
+};
+
+/***********************
+*** Linear traversal ***
+***********************/
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
+  {
+    const Index size = dst.size();
+    for(Index i = 0; i < size; ++i)
+      dst.copyCoeff(i, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Version>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+      ::run(dst, src);
   }
 };
 
@@ -253,46 +319,41 @@ struct ei_assign_impl<Derived1, Derived2, NoVectorization, InnerUnrolling>
 *** Inner vectorization ***
 **************************/
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, InnerVectorization, NoUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Version>
 {
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
-    const int innerSize = dst.innerSize();
-    const int outerSize = dst.outerSize();
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    for(int j = 0; j < outerSize; ++j)
-      for(int i = 0; i < innerSize; i+=packetSize)
-      {
-        if(int(Derived1::Flags)&RowMajorBit)
-          dst.template copyPacket<Derived2, Aligned, Aligned>(j, i, src);
-        else
-          dst.template copyPacket<Derived2, Aligned, Aligned>(i, j, src);
-      }
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index packetSize = packet_traits<typename Derived1::Scalar>::size;
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; inner+=packetSize)
+        dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, inner, src);
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, InnerVectorization, CompleteUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
-    ei_assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+    assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, InnerVectorization, InnerUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
-    const bool rowMajor = int(Derived1::Flags)&RowMajorBit;
-    const int innerSize = rowMajor ? Derived1::ColsAtCompileTime : Derived1::RowsAtCompileTime;
-    const int outerSize = dst.outerSize();
-    for(int j = 0; j < outerSize; ++j)
-      ei_assign_innervec_InnerUnrolling<Derived1, Derived2, 0, innerSize>
-        ::run(dst, src, j);
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      assign_innervec_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
+        ::run(dst, src, outer);
   }
 };
 
@@ -300,41 +361,71 @@ struct ei_assign_impl<Derived1, Derived2, InnerVectorization, InnerUnrolling>
 *** Linear vectorization ***
 ***************************/
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, LinearVectorization, NoUnrolling>
+template <bool IsAligned = false>
+struct unaligned_assign_impl
 {
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  template <typename Derived, typename OtherDerived>
+  static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, typename Derived::Index, typename Derived::Index) {}
+};
+
+template <>
+struct unaligned_assign_impl<false>
+{
+  // MSVC must not inline this functions. If it does, it fails to optimize the
+  // packet access path.
+#ifdef _MSC_VER
+  template <typename Derived, typename OtherDerived>
+  static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
+#else
+  template <typename Derived, typename OtherDerived>
+  static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
+#endif
   {
-    const int size = dst.size();
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    const int alignedStart = ei_assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                           : ei_alignmentOffset(&dst.coeffRef(0), size);
-    const int alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
-
-    for(int index = 0; index < alignedStart; ++index)
-      dst.copyCoeff(index, src);
-
-    for(int index = alignedStart; index < alignedEnd; index += packetSize)
-    {
-      dst.template copyPacket<Derived2, Aligned, ei_assign_traits<Derived1,Derived2>::SrcAlignment>(index, src);
-    }
-
-    for(int index = alignedEnd; index < size; ++index)
+    for (typename Derived::Index index = start; index < end; ++index)
       dst.copyCoeff(index, src);
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, LinearVectorization, CompleteUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
-    const int size = Derived1::SizeAtCompileTime;
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    const int alignedSize = (size/packetSize)*packetSize;
+    const Index size = dst.size();
+    typedef packet_traits<typename Derived1::Scalar> PacketTraits;
+    enum {
+      packetSize = PacketTraits::size,
+      dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
+      srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
+    };
+    const Index alignedStart = assign_traits<Derived1,Derived2>::DstIsAligned ? 0
+                             : internal::first_aligned(&dst.coeffRef(0), size);
+    const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
 
-    ei_assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
-    ei_assign_novec_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
+    unaligned_assign_impl<assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
+
+    for(Index index = alignedStart; index < alignedEnd; index += packetSize)
+    {
+      dst.template copyPacket<Derived2, dstAlignment, srcAlignment>(index, src);
+    }
+
+    unaligned_assign_impl<>::run(src,dst,alignedEnd,size);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    enum { size = Derived1::SizeAtCompileTime,
+           packetSize = packet_traits<typename Derived1::Scalar>::size,
+           alignedSize = (size/packetSize)*packetSize };
+
+    assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
+    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
   }
 };
 
@@ -342,104 +433,158 @@ struct ei_assign_impl<Derived1, Derived2, LinearVectorization, CompleteUnrolling
 *** Slice vectorization ***
 ***************************/
 
-template<typename Derived1, typename Derived2>
-struct ei_assign_impl<Derived1, Derived2, SliceVectorization, NoUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Version>
 {
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
-    const int packetSize = ei_packet_traits<typename Derived1::Scalar>::size;
-    const int packetAlignedMask = packetSize - 1;
-    const int innerSize = dst.innerSize();
-    const int outerSize = dst.outerSize();
-    const int alignedStep = (packetSize - dst.stride() % packetSize) & packetAlignedMask;
-    int alignedStart = ei_assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                     : ei_alignmentOffset(&dst.coeffRef(0,0), innerSize);
-
-    for(int i = 0; i < outerSize; ++i)
+    typedef typename Derived1::Scalar Scalar;
+    typedef packet_traits<Scalar> PacketTraits;
+    enum {
+      packetSize = PacketTraits::size,
+      alignable = PacketTraits::AlignedOnScalar,
+      dstIsAligned = assign_traits<Derived1,Derived2>::DstIsAligned,
+      dstAlignment = alignable ? Aligned : int(dstIsAligned),
+      srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
+    };
+    const Scalar *dst_ptr = &dst.coeffRef(0,0);
+    if((!bool(dstIsAligned)) && (Index(dst_ptr) % sizeof(Scalar))>0)
     {
-      const int alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
+      // the pointer is not aligend-on scalar, so alignment is not possible
+      return assign_impl<Derived1,Derived2,DefaultTraversal,NoUnrolling>::run(dst, src);
+    }
+    const Index packetAlignedMask = packetSize - 1;
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
+    Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned(dst_ptr, innerSize);
 
+    for(Index outer = 0; outer < outerSize; ++outer)
+    {
+      const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
       // do the non-vectorizable part of the assignment
-      for (int index = 0; index<alignedStart ; ++index)
-      {
-        if(Derived1::Flags&RowMajorBit)
-          dst.copyCoeff(i, index, src);
-        else
-          dst.copyCoeff(index, i, src);
-      }
+      for(Index inner = 0; inner<alignedStart ; ++inner)
+        dst.copyCoeffByOuterInner(outer, inner, src);
 
       // do the vectorizable part of the assignment
-      for (int index = alignedStart; index<alignedEnd; index+=packetSize)
-      {
-        if(Derived1::Flags&RowMajorBit)
-          dst.template copyPacket<Derived2, Aligned, Unaligned>(i, index, src);
-        else
-          dst.template copyPacket<Derived2, Aligned, Unaligned>(index, i, src);
-      }
+      for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
+        dst.template copyPacketByOuterInner<Derived2, dstAlignment, Unaligned>(outer, inner, src);
 
       // do the non-vectorizable part of the assignment
-      for (int index = alignedEnd; index<innerSize ; ++index)
-      {
-        if(Derived1::Flags&RowMajorBit)
-          dst.copyCoeff(i, index, src);
-        else
-          dst.copyCoeff(index, i, src);
-      }
+      for(Index inner = alignedEnd; inner<innerSize ; ++inner)
+        dst.copyCoeffByOuterInner(outer, inner, src);
 
-      alignedStart = std::min<int>((alignedStart+alignedStep)%packetSize, innerSize);
+      alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
     }
   }
 };
 
+} // end namespace internal
+
 /***************************************************************************
-* Part 4 : implementation of MatrixBase methods
+* Part 4 : implementation of DenseBase methods
 ***************************************************************************/
 
 template<typename Derived>
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>
-  ::lazyAssign(const MatrixBase<OtherDerived>& other)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
+  ::lazyAssign(const DenseBase<OtherDerived>& other)
 {
+  enum{
+    SameType = internal::is_same<typename Derived::Scalar,typename OtherDerived::Scalar>::value
+  };
+
+  EIGEN_STATIC_ASSERT_LVALUE(Derived)
   EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
-  EIGEN_STATIC_ASSERT((ei_is_same_type<typename Derived::Scalar, typename OtherDerived::Scalar>::ret),
-    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-  ei_assert(rows() == other.rows() && cols() == other.cols());
-  ei_assign_impl<Derived, OtherDerived>::run(derived(),other.derived());
+  EIGEN_STATIC_ASSERT(SameType,YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+
+#ifdef EIGEN_DEBUG_ASSIGN
+  internal::assign_traits<Derived, OtherDerived>::debug();
+#endif
+  eigen_assert(rows() == other.rows() && cols() == other.cols());
+  internal::assign_impl<Derived, OtherDerived, int(SameType) ? int(internal::assign_traits<Derived, OtherDerived>::Traversal)
+                                                       : int(InvalidTraversal)>::run(derived(),other.derived());
+#ifndef EIGEN_NO_DEBUG
+  checkTransposeAliasing(other.derived());
+#endif
   return derived();
 }
 
+namespace internal {
+
 template<typename Derived, typename OtherDerived,
-         bool EvalBeforeAssigning = (int(OtherDerived::Flags) & EvalBeforeAssigningBit) != 0,
-         bool NeedToTranspose = Derived::IsVectorAtCompileTime
-                && OtherDerived::IsVectorAtCompileTime
-                && int(Derived::RowsAtCompileTime) == int(OtherDerived::ColsAtCompileTime)
-                && int(Derived::ColsAtCompileTime) == int(OtherDerived::RowsAtCompileTime)
-                && int(Derived::SizeAtCompileTime) != 1>
-struct ei_assign_selector;
+         bool EvalBeforeAssigning = (int(internal::traits<OtherDerived>::Flags) & EvalBeforeAssigningBit) != 0,
+         bool NeedToTranspose = ((int(Derived::RowsAtCompileTime) == 1 && int(OtherDerived::ColsAtCompileTime) == 1)
+                              |   // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
+                                  // revert to || as soon as not needed anymore.
+                                  (int(Derived::ColsAtCompileTime) == 1 && int(OtherDerived::RowsAtCompileTime) == 1))
+                              && int(Derived::SizeAtCompileTime) != 1>
+struct assign_selector;
 
 template<typename Derived, typename OtherDerived>
-struct ei_assign_selector<Derived,OtherDerived,false,false> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
+struct assign_selector<Derived,OtherDerived,false,false> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
+  template<typename ActualDerived, typename ActualOtherDerived>
+  static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { other.evalTo(dst); return dst; }
 };
 template<typename Derived, typename OtherDerived>
-struct ei_assign_selector<Derived,OtherDerived,true,false> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
+struct assign_selector<Derived,OtherDerived,true,false> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
 };
 template<typename Derived, typename OtherDerived>
-struct ei_assign_selector<Derived,OtherDerived,false,true> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
+struct assign_selector<Derived,OtherDerived,false,true> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
+  template<typename ActualDerived, typename ActualOtherDerived>
+  static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { Transpose<ActualDerived> dstTrans(dst); other.evalTo(dstTrans); return dst; }
 };
 template<typename Derived, typename OtherDerived>
-struct ei_assign_selector<Derived,OtherDerived,true,true> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
+struct assign_selector<Derived,OtherDerived,true,true> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
 };
 
+} // end namespace internal
+
 template<typename Derived>
 template<typename OtherDerived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>
-  ::operator=(const MatrixBase<OtherDerived>& other)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
 {
-  return ei_assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
+  return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
 }
 
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
+{
+  return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
+{
+  return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
+}
+
+template<typename Derived>
+template <typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
+{
+  return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
+}
+
+template<typename Derived>
+template <typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
+{
+  return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
+{
+  return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_ASSIGN_H

Eigen/src/Core/Assign_MKL.h

@@ -0,0 +1,224 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to Intel(R) MKL
+ *   MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin()
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_ASSIGN_VML_H
+#define EIGEN_ASSIGN_VML_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Op> struct vml_call
+{ enum { IsSupported = 0 }; };
+
+template<typename Dst, typename Src, typename UnaryOp>
+class vml_assign_traits
+{
+  private:
+    enum {
+      DstHasDirectAccess = Dst::Flags & DirectAccessBit,
+      SrcHasDirectAccess = Src::Flags & DirectAccessBit,
+
+      StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
+      InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
+                : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
+                : int(Dst::RowsAtCompileTime),
+      InnerMaxSize  = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
+                    : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
+                    : int(Dst::MaxRowsAtCompileTime),
+      MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
+
+      MightEnableVml =  vml_call<UnaryOp>::IsSupported && StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess
+                     && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
+      MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
+      VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
+      LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD,
+      MayEnableVml = MightEnableVml && LargeEnough,
+      MayLinearize = MayEnableVml && MightLinearize
+    };
+  public:
+    enum {
+      Traversal = MayLinearize ? LinearVectorizedTraversal
+                : MayEnableVml ? InnerVectorizedTraversal
+                : DefaultTraversal
+    };
+};
+
+template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling,
+         int VmlTraversal = vml_assign_traits<Derived1, Derived2, UnaryOp>::Traversal >
+struct vml_assign_impl
+  : assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>
+{
+};
+
+template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
+struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, InnerVectorizedTraversal>
+{
+  typedef typename Derived1::Scalar Scalar;
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
+  {
+    // in case we want to (or have to) skip VML at runtime we can call:
+    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer) {
+      const Scalar *src_ptr = src.IsRowMajor ?  &(src.nestedExpression().coeffRef(outer,0)) :
+                                                &(src.nestedExpression().coeffRef(0, outer));
+      Scalar *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));
+      vml_call<UnaryOp>::run(src.functor(), innerSize, src_ptr, dst_ptr );
+    }
+  }
+};
+
+template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
+struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, LinearVectorizedTraversal>
+{
+  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
+  {
+    // in case we want to (or have to) skip VML at runtime we can call:
+    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
+    vml_call<UnaryOp>::run(src.functor(), dst.size(), src.nestedExpression().data(), dst.data() );
+  }
+};
+
+// Macroses
+
+#define EIGEN_MKL_VML_SPECIALIZE_ASSIGN(TRAVERSAL,UNROLLING) \
+  template<typename Derived1, typename Derived2, typename UnaryOp> \
+  struct assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>, TRAVERSAL, UNROLLING, Specialized>  {  \
+    static inline void run(Derived1 &dst, const Eigen::CwiseUnaryOp<UnaryOp, Derived2> &src) { \
+      vml_assign_impl<Derived1,Derived2,UnaryOp,TRAVERSAL,UNROLLING>::run(dst, src); \
+    } \
+  };
+
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,InnerUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,InnerUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(SliceVectorizedTraversal,NoUnrolling)
+
+
+#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
+#define  EIGEN_MKL_VML_MODE VML_HA
+#else
+#define  EIGEN_MKL_VML_MODE VML_LA
+#endif
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)     \
+  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
+    enum { IsSupported = 1 };                                                    \
+    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
+                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
+      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst);                           \
+    }                                                                            \
+  };
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)  \
+  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
+    enum { IsSupported = 1 };                                                    \
+    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
+                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
+      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
+      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst, vmlMode);                  \
+    }                                                                            \
+  };
+
+#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)       \
+  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
+    enum { IsSupported = 1 };                                                    \
+    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& func,        \
+                          int size, const EIGENTYPE* src, EIGENTYPE* dst) {      \
+      EIGENTYPE exponent = func.m_exponent;                                      \
+      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
+      VMLOP(&size, (const VMLTYPE*)src, (const VMLTYPE*)&exponent,               \
+                        (VMLTYPE*)dst, &vmlMode);                                \
+    }                                                                            \
+  };
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                   \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vs##VMLOP, float, float)             \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vd##VMLOP, double, double)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)                \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vc##VMLOP, scomplex, MKL_Complex8)   \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vz##VMLOP, dcomplex, MKL_Complex16)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP)                        \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                         \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)
+
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vms##VMLOP, float, float)         \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmd##VMLOP, double, double)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)             \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmc##VMLOP, scomplex, MKL_Complex8)  \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmz##VMLOP, dcomplex, MKL_Complex16)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(EIGENOP, VMLOP)                     \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                      \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)
+
+
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sin,  Sin)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos,  Cos)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan,  Tan)
+//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,  Abs)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp,  Exp)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log,  Ln)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sqrt, Sqrt)
+
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr)
+
+// The vm*powx functions are not avaibale in the windows version of MKL.
+#ifndef _WIN32
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16)
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_ASSIGN_VML_H

Eigen/src/Core/BandMatrix.h

@@ -0,0 +1,334 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_BANDMATRIX_H
+#define EIGEN_BANDMATRIX_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Derived>
+class BandMatrixBase : public EigenBase<Derived>
+{
+  public:
+
+    enum {
+      Flags = internal::traits<Derived>::Flags,
+      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
+      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
+      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
+      MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
+      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
+      Supers = internal::traits<Derived>::Supers,
+      Subs   = internal::traits<Derived>::Subs,
+      Options = internal::traits<Derived>::Options
+    };
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
+    typedef typename DenseMatrixType::Index Index;
+    typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
+    typedef EigenBase<Derived> Base;
+
+  protected:
+    enum {
+      DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic))
+                            ? 1 + Supers + Subs
+                            : Dynamic,
+      SizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime)
+    };
+
+  public:
+    
+    using Base::derived;
+    using Base::rows;
+    using Base::cols;
+
+    /** \returns the number of super diagonals */
+    inline Index supers() const { return derived().supers(); }
+
+    /** \returns the number of sub diagonals */
+    inline Index subs() const { return derived().subs(); }
+    
+    /** \returns an expression of the underlying coefficient matrix */
+    inline const CoefficientsType& coeffs() const { return derived().coeffs(); }
+    
+    /** \returns an expression of the underlying coefficient matrix */
+    inline CoefficientsType& coeffs() { return derived().coeffs(); }
+
+    /** \returns a vector expression of the \a i -th column,
+      * only the meaningful part is returned.
+      * \warning the internal storage must be column major. */
+    inline Block<CoefficientsType,Dynamic,1> col(Index i)
+    {
+      EIGEN_STATIC_ASSERT((Options&RowMajor)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+      Index start = 0;
+      Index len = coeffs().rows();
+      if (i<=supers())
+      {
+        start = supers()-i;
+        len = (std::min)(rows(),std::max<Index>(0,coeffs().rows() - (supers()-i)));
+      }
+      else if (i>=rows()-subs())
+        len = std::max<Index>(0,coeffs().rows() - (i + 1 - rows() + subs()));
+      return Block<CoefficientsType,Dynamic,1>(coeffs(), start, i, len, 1);
+    }
+
+    /** \returns a vector expression of the main diagonal */
+    inline Block<CoefficientsType,1,SizeAtCompileTime> diagonal()
+    { return Block<CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
+
+    /** \returns a vector expression of the main diagonal (const version) */
+    inline const Block<const CoefficientsType,1,SizeAtCompileTime> diagonal() const
+    { return Block<const CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
+
+    template<int Index> struct DiagonalIntReturnType {
+      enum {
+        ReturnOpposite = (Options&SelfAdjoint) && (((Index)>0 && Supers==0) || ((Index)<0 && Subs==0)),
+        Conjugate = ReturnOpposite && NumTraits<Scalar>::IsComplex,
+        ActualIndex = ReturnOpposite ? -Index : Index,
+        DiagonalSize = (RowsAtCompileTime==Dynamic || ColsAtCompileTime==Dynamic)
+                     ? Dynamic
+                     : (ActualIndex<0
+                     ? EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
+                     : EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
+      };
+      typedef Block<CoefficientsType,1, DiagonalSize> BuildType;
+      typedef typename internal::conditional<Conjugate,
+                 CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>,BuildType >,
+                 BuildType>::type Type;
+    };
+
+    /** \returns a vector expression of the \a N -th sub or super diagonal */
+    template<int N> inline typename DiagonalIntReturnType<N>::Type diagonal()
+    {
+      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
+    }
+
+    /** \returns a vector expression of the \a N -th sub or super diagonal */
+    template<int N> inline const typename DiagonalIntReturnType<N>::Type diagonal() const
+    {
+      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
+    }
+
+    /** \returns a vector expression of the \a i -th sub or super diagonal */
+    inline Block<CoefficientsType,1,Dynamic> diagonal(Index i)
+    {
+      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
+      return Block<CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
+    }
+
+    /** \returns a vector expression of the \a i -th sub or super diagonal */
+    inline const Block<const CoefficientsType,1,Dynamic> diagonal(Index i) const
+    {
+      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
+      return Block<const CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
+    }
+    
+    template<typename Dest> inline void evalTo(Dest& dst) const
+    {
+      dst.resize(rows(),cols());
+      dst.setZero();
+      dst.diagonal() = diagonal();
+      for (Index i=1; i<=supers();++i)
+        dst.diagonal(i) = diagonal(i);
+      for (Index i=1; i<=subs();++i)
+        dst.diagonal(-i) = diagonal(-i);
+    }
+
+    DenseMatrixType toDenseMatrix() const
+    {
+      DenseMatrixType res(rows(),cols());
+      evalTo(res);
+      return res;
+    }
+
+  protected:
+
+    inline Index diagonalLength(Index i) const
+    { return i<0 ? (std::min)(cols(),rows()+i) : (std::min)(rows(),cols()-i); }
+};
+
+/**
+  * \class BandMatrix
+  * \ingroup Core_Module
+  *
+  * \brief Represents a rectangular matrix with a banded storage
+  *
+  * \param _Scalar Numeric type, i.e. float, double, int
+  * \param Rows Number of rows, or \b Dynamic
+  * \param Cols Number of columns, or \b Dynamic
+  * \param Supers Number of super diagonal
+  * \param Subs Number of sub diagonal
+  * \param _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
+  *                 The former controls \ref TopicStorageOrders "storage order", and defaults to
+  *                 column-major. The latter controls whether the matrix represents a selfadjoint 
+  *                 matrix in which case either Supers of Subs have to be null.
+  *
+  * \sa class TridiagonalMatrix
+  */
+
+template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
+struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  typedef _Scalar Scalar;
+  typedef Dense StorageKind;
+  typedef DenseIndex Index;
+  enum {
+    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    RowsAtCompileTime = _Rows,
+    ColsAtCompileTime = _Cols,
+    MaxRowsAtCompileTime = _Rows,
+    MaxColsAtCompileTime = _Cols,
+    Flags = LvalueBit,
+    Supers = _Supers,
+    Subs = _Subs,
+    Options = _Options,
+    DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
+  };
+  typedef Matrix<Scalar,DataRowsAtCompileTime,ColsAtCompileTime,Options&RowMajor?RowMajor:ColMajor> CoefficientsType;
+};
+
+template<typename _Scalar, int Rows, int Cols, int Supers, int Subs, int Options>
+class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Subs,Options> >
+{
+  public:
+
+    typedef typename internal::traits<BandMatrix>::Scalar Scalar;
+    typedef typename internal::traits<BandMatrix>::Index Index;
+    typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
+
+    inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
+      : m_coeffs(1+supers+subs,cols),
+        m_rows(rows), m_supers(supers), m_subs(subs)
+    {
+    }
+
+    /** \returns the number of columns */
+    inline Index rows() const { return m_rows.value(); }
+
+    /** \returns the number of rows */
+    inline Index cols() const { return m_coeffs.cols(); }
+
+    /** \returns the number of super diagonals */
+    inline Index supers() const { return m_supers.value(); }
+
+    /** \returns the number of sub diagonals */
+    inline Index subs() const { return m_subs.value(); }
+
+    inline const CoefficientsType& coeffs() const { return m_coeffs; }
+    inline CoefficientsType& coeffs() { return m_coeffs; }
+
+  protected:
+
+    CoefficientsType m_coeffs;
+    internal::variable_if_dynamic<Index, Rows>   m_rows;
+    internal::variable_if_dynamic<Index, Supers> m_supers;
+    internal::variable_if_dynamic<Index, Subs>   m_subs;
+};
+
+template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+class BandMatrixWrapper;
+
+template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  typedef typename _CoefficientsType::Scalar Scalar;
+  typedef typename _CoefficientsType::StorageKind StorageKind;
+  typedef typename _CoefficientsType::Index Index;
+  enum {
+    CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
+    RowsAtCompileTime = _Rows,
+    ColsAtCompileTime = _Cols,
+    MaxRowsAtCompileTime = _Rows,
+    MaxColsAtCompileTime = _Cols,
+    Flags = LvalueBit,
+    Supers = _Supers,
+    Subs = _Subs,
+    Options = _Options,
+    DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
+  };
+  typedef _CoefficientsType CoefficientsType;
+};
+
+template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  public:
+
+    typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
+    typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
+    typedef typename internal::traits<BandMatrixWrapper>::Index Index;
+
+    inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
+      : m_coeffs(coeffs),
+        m_rows(rows), m_supers(supers), m_subs(subs)
+    {
+      EIGEN_UNUSED_VARIABLE(cols);
+      //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
+    }
+
+    /** \returns the number of columns */
+    inline Index rows() const { return m_rows.value(); }
+
+    /** \returns the number of rows */
+    inline Index cols() const { return m_coeffs.cols(); }
+
+    /** \returns the number of super diagonals */
+    inline Index supers() const { return m_supers.value(); }
+
+    /** \returns the number of sub diagonals */
+    inline Index subs() const { return m_subs.value(); }
+
+    inline const CoefficientsType& coeffs() const { return m_coeffs; }
+
+  protected:
+
+    const CoefficientsType& m_coeffs;
+    internal::variable_if_dynamic<Index, _Rows>   m_rows;
+    internal::variable_if_dynamic<Index, _Supers> m_supers;
+    internal::variable_if_dynamic<Index, _Subs>   m_subs;
+};
+
+/**
+  * \class TridiagonalMatrix
+  * \ingroup Core_Module
+  *
+  * \brief Represents a tridiagonal matrix with a compact banded storage
+  *
+  * \param _Scalar Numeric type, i.e. float, double, int
+  * \param Size Number of rows and cols, or \b Dynamic
+  * \param _Options Can be 0 or \b SelfAdjoint
+  *
+  * \sa class BandMatrix
+  */
+template<typename Scalar, int Size, int Options>
+class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
+{
+    typedef BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
+    typedef typename Base::Index Index;
+  public:
+    TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
+
+    inline typename Base::template DiagonalIntReturnType<1>::Type super()
+    { return Base::template diagonal<1>(); }
+    inline const typename Base::template DiagonalIntReturnType<1>::Type super() const
+    { return Base::template diagonal<1>(); }
+    inline typename Base::template DiagonalIntReturnType<-1>::Type sub()
+    { return Base::template diagonal<-1>(); }
+    inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const
+    { return Base::template diagonal<-1>(); }
+  protected:
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_BANDMATRIX_H

Eigen/src/Core/BooleanRedux.h

@@ -0,0 +1,154 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ALLANDANY_H
+#define EIGEN_ALLANDANY_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Derived, int UnrollCount>
+struct all_unroller
+{
+  enum {
+    col = (UnrollCount-1) / Derived::RowsAtCompileTime,
+    row = (UnrollCount-1) % Derived::RowsAtCompileTime
+  };
+
+  static inline bool run(const Derived &mat)
+  {
+    return all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col);
+  }
+};
+
+template<typename Derived>
+struct all_unroller<Derived, 0>
+{
+  static inline bool run(const Derived &/*mat*/) { return true; }
+};
+
+template<typename Derived>
+struct all_unroller<Derived, Dynamic>
+{
+  static inline bool run(const Derived &) { return false; }
+};
+
+template<typename Derived, int UnrollCount>
+struct any_unroller
+{
+  enum {
+    col = (UnrollCount-1) / Derived::RowsAtCompileTime,
+    row = (UnrollCount-1) % Derived::RowsAtCompileTime
+  };
+
+  static inline bool run(const Derived &mat)
+  {
+    return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
+  }
+};
+
+template<typename Derived>
+struct any_unroller<Derived, 0>
+{
+  static inline bool run(const Derived & /*mat*/) { return false; }
+};
+
+template<typename Derived>
+struct any_unroller<Derived, Dynamic>
+{
+  static inline bool run(const Derived &) { return false; }
+};
+
+} // end namespace internal
+
+/** \returns true if all coefficients are true
+  *
+  * Example: \include MatrixBase_all.cpp
+  * Output: \verbinclude MatrixBase_all.out
+  *
+  * \sa any(), Cwise::operator<()
+  */
+template<typename Derived>
+inline bool DenseBase<Derived>::all() const
+{
+  enum {
+    unroll = SizeAtCompileTime != Dynamic
+          && CoeffReadCost != Dynamic
+          && NumTraits<Scalar>::AddCost != Dynamic
+          && SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
+  };
+  if(unroll)
+    return internal::all_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
+  else
+  {
+    for(Index j = 0; j < cols(); ++j)
+      for(Index i = 0; i < rows(); ++i)
+        if (!coeff(i, j)) return false;
+    return true;
+  }
+}
+
+/** \returns true if at least one coefficient is true
+  *
+  * \sa all()
+  */
+template<typename Derived>
+inline bool DenseBase<Derived>::any() const
+{
+  enum {
+    unroll = SizeAtCompileTime != Dynamic
+          && CoeffReadCost != Dynamic
+          && NumTraits<Scalar>::AddCost != Dynamic
+          && SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost) <= EIGEN_UNROLLING_LIMIT
+  };
+  if(unroll)
+    return internal::any_unroller<Derived, unroll ? int(SizeAtCompileTime) : Dynamic>::run(derived());
+  else
+  {
+    for(Index j = 0; j < cols(); ++j)
+      for(Index i = 0; i < rows(); ++i)
+        if (coeff(i, j)) return true;
+    return false;
+  }
+}
+
+/** \returns the number of coefficients which evaluate to true
+  *
+  * \sa all(), any()
+  */
+template<typename Derived>
+inline typename DenseBase<Derived>::Index DenseBase<Derived>::count() const
+{
+  return derived().template cast<bool>().template cast<Index>().sum();
+}
+
+/** \returns true is \c *this contains at least one Not A Number (NaN).
+  *
+  * \sa allFinite()
+  */
+template<typename Derived>
+inline bool DenseBase<Derived>::hasNaN() const
+{
+  return !((derived().array()==derived().array()).all());
+}
+
+/** \returns true if \c *this contains only finite numbers, i.e., no NaN and no +/-INF values.
+  *
+  * \sa hasNaN()
+  */
+template<typename Derived>
+inline bool DenseBase<Derived>::allFinite() const
+{
+  return !((derived()-derived()).hasNaN());
+}
+    
+} // end namespace Eigen
+
+#endif // EIGEN_ALLANDANY_H

Eigen/src/Core/CMakeLists.txt

@@ -2,8 +2,9 @@ FILE(GLOB Eigen_Core_SRCS "*.h")
 
 INSTALL(FILES
   ${Eigen_Core_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core COMPONENT Devel
   )
 
+ADD_SUBDIRECTORY(products)
 ADD_SUBDIRECTORY(util)
 ADD_SUBDIRECTORY(arch)

Eigen/src/Core/CacheFriendlyProduct.h

@@ -1,753 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_CACHE_FRIENDLY_PRODUCT_H
-#define EIGEN_CACHE_FRIENDLY_PRODUCT_H
-
-template <int L2MemorySize,typename Scalar>
-struct ei_L2_block_traits {
-  enum {width = 8 * ei_meta_sqrt<L2MemorySize/(64*sizeof(Scalar))>::ret };
-};
-
-#ifndef EIGEN_EXTERN_INSTANTIATIONS
-
-template<typename Scalar>
-static void ei_cache_friendly_product(
-  int _rows, int _cols, int depth,
-  bool _lhsRowMajor, const Scalar* _lhs, int _lhsStride,
-  bool _rhsRowMajor, const Scalar* _rhs, int _rhsStride,
-  bool resRowMajor, Scalar* res, int resStride)
-{
-  const Scalar* EIGEN_RESTRICT lhs;
-  const Scalar* EIGEN_RESTRICT rhs;
-  int lhsStride, rhsStride, rows, cols;
-  bool lhsRowMajor;
-
-  if (resRowMajor)
-  {
-    lhs = _rhs;
-    rhs = _lhs;
-    lhsStride = _rhsStride;
-    rhsStride = _lhsStride;
-    cols = _rows;
-    rows = _cols;
-    lhsRowMajor = !_rhsRowMajor;
-    ei_assert(_lhsRowMajor);
-  }
-  else
-  {
-    lhs = _lhs;
-    rhs = _rhs;
-    lhsStride = _lhsStride;
-    rhsStride = _rhsStride;
-    rows = _rows;
-    cols = _cols;
-    lhsRowMajor = _lhsRowMajor;
-    ei_assert(!_rhsRowMajor);
-  }
-
-  typedef typename ei_packet_traits<Scalar>::type PacketType;
-
-  enum {
-    PacketSize = sizeof(PacketType)/sizeof(Scalar),
-    #if (defined __i386__)
-    // i386 architecture provides only 8 xmm registers,
-    // so let's reduce the max number of rows processed at once.
-    MaxBlockRows = 4,
-    MaxBlockRows_ClampingMask = 0xFFFFFC,
-    #else
-    MaxBlockRows = 8,
-    MaxBlockRows_ClampingMask = 0xFFFFF8,
-    #endif
-    // maximal size of the blocks fitted in L2 cache
-    MaxL2BlockSize = ei_L2_block_traits<EIGEN_TUNE_FOR_CPU_CACHE_SIZE,Scalar>::width
-  };
-
-  const bool resIsAligned = (PacketSize==1) || (((resStride%PacketSize) == 0) && (size_t(res)%16==0));
-
-  const int remainingSize = depth % PacketSize;
-  const int size = depth - remainingSize; // third dimension of the product clamped to packet boundaries
-  const int l2BlockRows = MaxL2BlockSize > rows ? rows : MaxL2BlockSize;
-  const int l2BlockCols = MaxL2BlockSize > cols ? cols : MaxL2BlockSize;
-  const int l2BlockSize = MaxL2BlockSize > size ? size : MaxL2BlockSize;
-  const int l2BlockSizeAligned = (1 + std::max(l2BlockSize,l2BlockCols)/PacketSize)*PacketSize;
-  const bool needRhsCopy = (PacketSize>1) && ((rhsStride%PacketSize!=0) || (size_t(rhs)%16!=0));
-  Scalar* EIGEN_RESTRICT block = 0;
-  const int allocBlockSize = l2BlockRows*size;
-  block = ei_aligned_stack_new(Scalar, allocBlockSize);
-  Scalar* EIGEN_RESTRICT rhsCopy
-    = ei_aligned_stack_new(Scalar, l2BlockSizeAligned*l2BlockSizeAligned);
-
-  // loops on each L2 cache friendly blocks of the result
-  for(int l2i=0; l2i<rows; l2i+=l2BlockRows)
-  {
-    const int l2blockRowEnd = std::min(l2i+l2BlockRows, rows);
-    const int l2blockRowEndBW = l2blockRowEnd & MaxBlockRows_ClampingMask;    // end of the rows aligned to bw
-    const int l2blockRemainingRows = l2blockRowEnd - l2blockRowEndBW;         // number of remaining rows
-    //const int l2blockRowEndBWPlusOne = l2blockRowEndBW + (l2blockRemainingRows?0:MaxBlockRows);
-
-    // build a cache friendly blocky matrix
-    int count = 0;
-
-    // copy l2blocksize rows of m_lhs to blocks of ps x bw
-    for(int l2k=0; l2k<size; l2k+=l2BlockSize)
-    {
-      const int l2blockSizeEnd = std::min(l2k+l2BlockSize, size);
-
-      for (int i = l2i; i<l2blockRowEndBW/*PlusOne*/; i+=MaxBlockRows)
-      {
-        // TODO merge the "if l2blockRemainingRows" using something like:
-        // const int blockRows = std::min(i+MaxBlockRows, rows) - i;
-
-        for (int k=l2k; k<l2blockSizeEnd; k+=PacketSize)
-        {
-          // TODO write these loops using meta unrolling
-          // negligible for large matrices but useful for small ones
-          if (lhsRowMajor)
-          {
-            for (int w=0; w<MaxBlockRows; ++w)
-              for (int s=0; s<PacketSize; ++s)
-                block[count++] = lhs[(i+w)*lhsStride + (k+s)];
-          }
-          else
-          {
-            for (int w=0; w<MaxBlockRows; ++w)
-              for (int s=0; s<PacketSize; ++s)
-                block[count++] = lhs[(i+w) + (k+s)*lhsStride];
-          }
-        }
-      }
-      if (l2blockRemainingRows>0)
-      {
-        for (int k=l2k; k<l2blockSizeEnd; k+=PacketSize)
-        {
-          if (lhsRowMajor)
-          {
-            for (int w=0; w<l2blockRemainingRows; ++w)
-              for (int s=0; s<PacketSize; ++s)
-                block[count++] = lhs[(l2blockRowEndBW+w)*lhsStride + (k+s)];
-          }
-          else
-          {
-            for (int w=0; w<l2blockRemainingRows; ++w)
-              for (int s=0; s<PacketSize; ++s)
-                block[count++] = lhs[(l2blockRowEndBW+w) + (k+s)*lhsStride];
-          }
-        }
-      }
-    }
-
-    for(int l2j=0; l2j<cols; l2j+=l2BlockCols)
-    {
-      int l2blockColEnd = std::min(l2j+l2BlockCols, cols);
-
-      for(int l2k=0; l2k<size; l2k+=l2BlockSize)
-      {
-        // acumulate bw rows of lhs time a single column of rhs to a bw x 1 block of res
-        int l2blockSizeEnd = std::min(l2k+l2BlockSize, size);
-
-        // if not aligned, copy the rhs block
-        if (needRhsCopy)
-          for(int l1j=l2j; l1j<l2blockColEnd; l1j+=1)
-          {
-            ei_internal_assert(l2BlockSizeAligned*(l1j-l2j)+(l2blockSizeEnd-l2k) < l2BlockSizeAligned*l2BlockSizeAligned);
-            memcpy(rhsCopy+l2BlockSizeAligned*(l1j-l2j),&(rhs[l1j*rhsStride+l2k]),(l2blockSizeEnd-l2k)*sizeof(Scalar));
-          }
-
-        // for each bw x 1 result's block
-        for(int l1i=l2i; l1i<l2blockRowEndBW; l1i+=MaxBlockRows)
-        {
-          int offsetblock = l2k * (l2blockRowEnd-l2i) + (l1i-l2i)*(l2blockSizeEnd-l2k) - l2k*MaxBlockRows;
-          const Scalar* EIGEN_RESTRICT localB = &block[offsetblock];
-          
-          for(int l1j=l2j; l1j<l2blockColEnd; l1j+=1)
-          {
-            const Scalar* EIGEN_RESTRICT rhsColumn;
-            if (needRhsCopy)
-              rhsColumn = &(rhsCopy[l2BlockSizeAligned*(l1j-l2j)-l2k]);
-            else
-              rhsColumn = &(rhs[l1j*rhsStride]);
-
-            PacketType dst[MaxBlockRows];
-            dst[3] = dst[2] = dst[1] = dst[0] = ei_pset1(Scalar(0.));
-            if (MaxBlockRows==8)
-              dst[7] = dst[6] = dst[5] = dst[4] = dst[0];
-
-            PacketType tmp;
-
-            for(int k=l2k; k<l2blockSizeEnd; k+=PacketSize)
-            {
-              tmp = ei_ploadu(&rhsColumn[k]);
-              PacketType A0, A1, A2, A3, A4, A5;
-              A0 = ei_pload(localB + k*MaxBlockRows);
-              A1 = ei_pload(localB + k*MaxBlockRows+1*PacketSize);
-              A2 = ei_pload(localB + k*MaxBlockRows+2*PacketSize);
-              A3 = ei_pload(localB + k*MaxBlockRows+3*PacketSize);
-              if (MaxBlockRows==8) A4 = ei_pload(localB + k*MaxBlockRows+4*PacketSize);
-              if (MaxBlockRows==8) A5 = ei_pload(localB + k*MaxBlockRows+5*PacketSize);
-              dst[0] = ei_pmadd(tmp, A0, dst[0]);
-              if (MaxBlockRows==8) A0 = ei_pload(localB + k*MaxBlockRows+6*PacketSize);
-              dst[1] = ei_pmadd(tmp, A1, dst[1]);
-              if (MaxBlockRows==8) A1 = ei_pload(localB + k*MaxBlockRows+7*PacketSize);
-              dst[2] = ei_pmadd(tmp, A2, dst[2]);
-              dst[3] = ei_pmadd(tmp, A3, dst[3]);
-              if (MaxBlockRows==8)
-              {
-                dst[4] = ei_pmadd(tmp, A4, dst[4]);
-                dst[5] = ei_pmadd(tmp, A5, dst[5]);
-                dst[6] = ei_pmadd(tmp, A0, dst[6]);
-                dst[7] = ei_pmadd(tmp, A1, dst[7]);
-              }
-            }
-
-            Scalar* EIGEN_RESTRICT localRes = &(res[l1i + l1j*resStride]);
-
-            if (PacketSize>1 && resIsAligned)
-            {
-              // the result is aligned: let's do packet reduction
-              ei_pstore(&(localRes[0]), ei_padd(ei_pload(&(localRes[0])), ei_preduxp(&dst[0])));
-              if (PacketSize==2)
-                ei_pstore(&(localRes[2]), ei_padd(ei_pload(&(localRes[2])), ei_preduxp(&(dst[2]))));
-              if (MaxBlockRows==8)
-              {
-                ei_pstore(&(localRes[4]), ei_padd(ei_pload(&(localRes[4])), ei_preduxp(&(dst[4]))));
-                if (PacketSize==2)
-                  ei_pstore(&(localRes[6]), ei_padd(ei_pload(&(localRes[6])), ei_preduxp(&(dst[6]))));
-              }
-            }
-            else
-            {
-              // not aligned => per coeff packet reduction
-              localRes[0] += ei_predux(dst[0]);
-              localRes[1] += ei_predux(dst[1]);
-              localRes[2] += ei_predux(dst[2]);
-              localRes[3] += ei_predux(dst[3]);
-              if (MaxBlockRows==8)
-              {
-                localRes[4] += ei_predux(dst[4]);
-                localRes[5] += ei_predux(dst[5]);
-                localRes[6] += ei_predux(dst[6]);
-                localRes[7] += ei_predux(dst[7]);
-              }
-            }
-          }
-        }
-        if (l2blockRemainingRows>0)
-        {
-          int offsetblock = l2k * (l2blockRowEnd-l2i) + (l2blockRowEndBW-l2i)*(l2blockSizeEnd-l2k) - l2k*l2blockRemainingRows;
-          const Scalar* localB = &block[offsetblock];
-
-          for(int l1j=l2j; l1j<l2blockColEnd; l1j+=1)
-          {
-            const Scalar* EIGEN_RESTRICT rhsColumn;
-            if (needRhsCopy)
-              rhsColumn = &(rhsCopy[l2BlockSizeAligned*(l1j-l2j)-l2k]);
-            else
-              rhsColumn = &(rhs[l1j*rhsStride]);
-
-            PacketType dst[MaxBlockRows];
-            dst[3] = dst[2] = dst[1] = dst[0] = ei_pset1(Scalar(0.));
-            if (MaxBlockRows==8)
-              dst[7] = dst[6] = dst[5] = dst[4] = dst[0];
-
-            // let's declare a few other temporary registers
-            PacketType tmp;
-
-            for(int k=l2k; k<l2blockSizeEnd; k+=PacketSize)
-            {
-              tmp = ei_pload(&rhsColumn[k]);
-
-                                           dst[0] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows             ])), dst[0]);
-              if (l2blockRemainingRows>=2) dst[1] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows+  PacketSize])), dst[1]);
-              if (l2blockRemainingRows>=3) dst[2] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows+2*PacketSize])), dst[2]);
-              if (l2blockRemainingRows>=4) dst[3] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows+3*PacketSize])), dst[3]);
-              if (MaxBlockRows==8)
-              {
-                if (l2blockRemainingRows>=5) dst[4] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows+4*PacketSize])), dst[4]);
-                if (l2blockRemainingRows>=6) dst[5] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows+5*PacketSize])), dst[5]);
-                if (l2blockRemainingRows>=7) dst[6] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows+6*PacketSize])), dst[6]);
-                if (l2blockRemainingRows>=8) dst[7] = ei_pmadd(tmp, ei_pload(&(localB[k*l2blockRemainingRows+7*PacketSize])), dst[7]);
-              }
-            }
-
-            Scalar* EIGEN_RESTRICT localRes = &(res[l2blockRowEndBW + l1j*resStride]);
-
-            // process the remaining rows once at a time
-                                         localRes[0] += ei_predux(dst[0]);
-            if (l2blockRemainingRows>=2) localRes[1] += ei_predux(dst[1]);
-            if (l2blockRemainingRows>=3) localRes[2] += ei_predux(dst[2]);
-            if (l2blockRemainingRows>=4) localRes[3] += ei_predux(dst[3]);
-            if (MaxBlockRows==8)
-            {
-              if (l2blockRemainingRows>=5) localRes[4] += ei_predux(dst[4]);
-              if (l2blockRemainingRows>=6) localRes[5] += ei_predux(dst[5]);
-              if (l2blockRemainingRows>=7) localRes[6] += ei_predux(dst[6]);
-              if (l2blockRemainingRows>=8) localRes[7] += ei_predux(dst[7]);
-            }
-
-          }
-        }
-      }
-    }
-  }
-  if (PacketSize>1 && remainingSize)
-  {
-    if (lhsRowMajor)
-    {
-      for (int j=0; j<cols; ++j)
-        for (int i=0; i<rows; ++i)
-        {
-          Scalar tmp = lhs[i*lhsStride+size] * rhs[j*rhsStride+size];
-          // FIXME this loop get vectorized by the compiler !
-          for (int k=1; k<remainingSize; ++k)
-            tmp += lhs[i*lhsStride+size+k] * rhs[j*rhsStride+size+k];
-          res[i+j*resStride] += tmp;
-        }
-    }
-    else
-    {
-      for (int j=0; j<cols; ++j)
-        for (int i=0; i<rows; ++i)
-        {
-          Scalar tmp = lhs[i+size*lhsStride] * rhs[j*rhsStride+size];
-          for (int k=1; k<remainingSize; ++k)
-            tmp += lhs[i+(size+k)*lhsStride] * rhs[j*rhsStride+size+k];
-          res[i+j*resStride] += tmp;
-        }
-    }
-  }
-
-  ei_aligned_stack_delete(Scalar, block, allocBlockSize);
-  ei_aligned_stack_delete(Scalar, rhsCopy, l2BlockSizeAligned*l2BlockSizeAligned);
-}
-
-#endif // EIGEN_EXTERN_INSTANTIATIONS
-
-/* Optimized col-major matrix * vector product:
- * This algorithm processes 4 columns at onces that allows to both reduce
- * the number of load/stores of the result by a factor 4 and to reduce
- * the instruction dependency. Moreover, we know that all bands have the
- * same alignment pattern.
- * TODO: since rhs gets evaluated only once, no need to evaluate it
- */
-template<typename Scalar, typename RhsType>
-static EIGEN_DONT_INLINE void ei_cache_friendly_product_colmajor_times_vector(
-  int size,
-  const Scalar* lhs, int lhsStride,
-  const RhsType& rhs,
-  Scalar* res)
-{
-  #ifdef _EIGEN_ACCUMULATE_PACKETS
-  #error _EIGEN_ACCUMULATE_PACKETS has already been defined
-  #endif
-  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) \
-    ei_pstore(&res[j], \
-      ei_padd(ei_pload(&res[j]), \
-        ei_padd( \
-          ei_padd(ei_pmul(ptmp0,EIGEN_CAT(ei_ploa , A0)(&lhs0[j])), \
-                  ei_pmul(ptmp1,EIGEN_CAT(ei_ploa , A13)(&lhs1[j]))), \
-          ei_padd(ei_pmul(ptmp2,EIGEN_CAT(ei_ploa , A2)(&lhs2[j])), \
-                  ei_pmul(ptmp3,EIGEN_CAT(ei_ploa , A13)(&lhs3[j]))) )))
-
-  typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = sizeof(Packet)/sizeof(Scalar);
-
-  enum { AllAligned = 0, EvenAligned, FirstAligned, NoneAligned };
-  const int columnsAtOnce = 4;
-  const int peels = 2;
-  const int PacketAlignedMask = PacketSize-1;
-  const int PeelAlignedMask = PacketSize*peels-1;
-
-  // How many coeffs of the result do we have to skip to be aligned.
-  // Here we assume data are at least aligned on the base scalar type that is mandatory anyway.
-  const int alignedStart = ei_alignmentOffset(res,size);
-  const int alignedSize = PacketSize>1 ? alignedStart + ((size-alignedStart) & ~PacketAlignedMask) : 0;
-  const int peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
-
-  const int alignmentStep = PacketSize>1 ? (PacketSize - lhsStride % PacketSize) & PacketAlignedMask : 0;
-  int alignmentPattern = alignmentStep==0 ? AllAligned
-                       : alignmentStep==(PacketSize/2) ? EvenAligned
-                       : FirstAligned;
-
-  // we cannot assume the first element is aligned because of sub-matrices
-  const int lhsAlignmentOffset = ei_alignmentOffset(lhs,size);
-
-  // find how many columns do we have to skip to be aligned with the result (if possible)
-  int skipColumns = 0;
-  if (PacketSize>1)
-  {
-    ei_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(Packet)==0 || size<PacketSize);
-
-    while (skipColumns<PacketSize &&
-           alignedStart != ((lhsAlignmentOffset + alignmentStep*skipColumns)%PacketSize))
-      ++skipColumns;
-    if (skipColumns==PacketSize)
-    {
-      // nothing can be aligned, no need to skip any column
-      alignmentPattern = NoneAligned;
-      skipColumns = 0;
-    }
-    else
-    {
-      skipColumns = std::min(skipColumns,rhs.size());
-      // note that the skiped columns are processed later.
-    }
-
-    ei_internal_assert((alignmentPattern==NoneAligned) || (size_t(lhs+alignedStart+lhsStride*skipColumns)%sizeof(Packet))==0);
-  }
-
-  int offset1 = (FirstAligned && alignmentStep==1?3:1);
-  int offset3 = (FirstAligned && alignmentStep==1?1:3);
-
-  int columnBound = ((rhs.size()-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns;
-  for (int i=skipColumns; i<columnBound; i+=columnsAtOnce)
-  {
-    Packet ptmp0 = ei_pset1(rhs[i]),   ptmp1 = ei_pset1(rhs[i+offset1]),
-           ptmp2 = ei_pset1(rhs[i+2]), ptmp3 = ei_pset1(rhs[i+offset3]);
-
-    // this helps a lot generating better binary code
-    const Scalar *lhs0 = lhs + i*lhsStride, *lhs1 = lhs + (i+offset1)*lhsStride,
-                 *lhs2 = lhs + (i+2)*lhsStride, *lhs3 = lhs + (i+offset3)*lhsStride;
-
-    if (PacketSize>1)
-    {
-      /* explicit vectorization */
-      // process initial unaligned coeffs
-      for (int j=0; j<alignedStart; ++j)
-        res[j] += ei_pfirst(ptmp0)*lhs0[j] + ei_pfirst(ptmp1)*lhs1[j] + ei_pfirst(ptmp2)*lhs2[j] + ei_pfirst(ptmp3)*lhs3[j];
-
-      if (alignedSize>alignedStart)
-      {
-        switch(alignmentPattern)
-        {
-          case AllAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,d,d);
-            break;
-          case EvenAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,d);
-            break;
-          case FirstAligned:
-            if(peels>1)
-            {
-              Packet A00, A01, A02, A03, A10, A11, A12, A13;
-
-              A01 = ei_pload(&lhs1[alignedStart-1]);
-              A02 = ei_pload(&lhs2[alignedStart-2]);
-              A03 = ei_pload(&lhs3[alignedStart-3]);
-
-              for (int j = alignedStart; j<peeledSize; j+=peels*PacketSize)
-              {
-                A11 = ei_pload(&lhs1[j-1+PacketSize]);  ei_palign<1>(A01,A11);
-                A12 = ei_pload(&lhs2[j-2+PacketSize]);  ei_palign<2>(A02,A12);
-                A13 = ei_pload(&lhs3[j-3+PacketSize]);  ei_palign<3>(A03,A13);
-
-                A00 = ei_pload (&lhs0[j]);
-                A10 = ei_pload (&lhs0[j+PacketSize]);
-                A00 = ei_pmadd(ptmp0, A00, ei_pload(&res[j]));
-                A10 = ei_pmadd(ptmp0, A10, ei_pload(&res[j+PacketSize]));
-
-                A00 = ei_pmadd(ptmp1, A01, A00);
-                A01 = ei_pload(&lhs1[j-1+2*PacketSize]);  ei_palign<1>(A11,A01);
-                A00 = ei_pmadd(ptmp2, A02, A00);
-                A02 = ei_pload(&lhs2[j-2+2*PacketSize]);  ei_palign<2>(A12,A02);
-                A00 = ei_pmadd(ptmp3, A03, A00);
-                ei_pstore(&res[j],A00);
-                A03 = ei_pload(&lhs3[j-3+2*PacketSize]);  ei_palign<3>(A13,A03);
-                A10 = ei_pmadd(ptmp1, A11, A10);
-                A10 = ei_pmadd(ptmp2, A12, A10);
-                A10 = ei_pmadd(ptmp3, A13, A10);
-                ei_pstore(&res[j+PacketSize],A10);
-              }
-            }
-            for (int j = peeledSize; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,du);
-            break;
-          default:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(du,du,du);
-            break;
-        }
-      }
-    } // end explicit vectorization
-
-    /* process remaining coeffs (or all if there is no explicit vectorization) */
-    for (int j=alignedSize; j<size; ++j)
-      res[j] += ei_pfirst(ptmp0)*lhs0[j] + ei_pfirst(ptmp1)*lhs1[j] + ei_pfirst(ptmp2)*lhs2[j] + ei_pfirst(ptmp3)*lhs3[j];
-  }
-
-  // process remaining first and last columns (at most columnsAtOnce-1)
-  int end = rhs.size();
-  int start = columnBound;
-  do
-  {
-    for (int i=start; i<end; ++i)
-    {
-      Packet ptmp0 = ei_pset1(rhs[i]);
-      const Scalar* lhs0 = lhs + i*lhsStride;
-
-      if (PacketSize>1)
-      {
-        /* explicit vectorization */
-        // process first unaligned result's coeffs
-        for (int j=0; j<alignedStart; ++j)
-          res[j] += ei_pfirst(ptmp0) * lhs0[j];
-
-        // process aligned result's coeffs
-        if ((size_t(lhs0+alignedStart)%sizeof(Packet))==0)
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
-            ei_pstore(&res[j], ei_pmadd(ptmp0,ei_pload(&lhs0[j]),ei_pload(&res[j])));
-        else
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
-            ei_pstore(&res[j], ei_pmadd(ptmp0,ei_ploadu(&lhs0[j]),ei_pload(&res[j])));
-      }
-
-      // process remaining scalars (or all if no explicit vectorization)
-      for (int j=alignedSize; j<size; ++j)
-        res[j] += ei_pfirst(ptmp0) * lhs0[j];
-    }
-    if (skipColumns)
-    {
-      start = 0;
-      end = skipColumns;
-      skipColumns = 0;
-    }
-    else
-      break;
-  } while(PacketSize>1);
-  #undef _EIGEN_ACCUMULATE_PACKETS
-}
-
-// TODO add peeling to mask unaligned load/stores
-template<typename Scalar, typename ResType>
-static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
-  const Scalar* lhs, int lhsStride,
-  const Scalar* rhs, int rhsSize,
-  ResType& res)
-{
-  #ifdef _EIGEN_ACCUMULATE_PACKETS
-  #error _EIGEN_ACCUMULATE_PACKETS has already been defined
-  #endif
-
-  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) {\
-    Packet b = ei_pload(&rhs[j]); \
-    ptmp0 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A0) (&lhs0[j]), ptmp0); \
-    ptmp1 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A13)(&lhs1[j]), ptmp1); \
-    ptmp2 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A2) (&lhs2[j]), ptmp2); \
-    ptmp3 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A13)(&lhs3[j]), ptmp3); }
-
-  typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = sizeof(Packet)/sizeof(Scalar);
-
-  enum { AllAligned=0, EvenAligned=1, FirstAligned=2, NoneAligned=3 };
-  const int rowsAtOnce = 4;
-  const int peels = 2;
-  const int PacketAlignedMask = PacketSize-1;
-  const int PeelAlignedMask = PacketSize*peels-1;
-  const int size = rhsSize;
-
-  // How many coeffs of the result do we have to skip to be aligned.
-  // Here we assume data are at least aligned on the base scalar type that is mandatory anyway.
-  const int alignedStart = ei_alignmentOffset(rhs, size);
-  const int alignedSize = PacketSize>1 ? alignedStart + ((size-alignedStart) & ~PacketAlignedMask) : 0;
-  const int peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
-
-  const int alignmentStep = PacketSize>1 ? (PacketSize - lhsStride % PacketSize) & PacketAlignedMask : 0;
-  int alignmentPattern = alignmentStep==0 ? AllAligned
-                       : alignmentStep==(PacketSize/2) ? EvenAligned
-                       : FirstAligned;
-
-  // we cannot assume the first element is aligned because of sub-matrices
-  const int lhsAlignmentOffset = ei_alignmentOffset(lhs,size);
-
-  // find how many rows do we have to skip to be aligned with rhs (if possible)
-  int skipRows = 0;
-  if (PacketSize>1)
-  {
-    ei_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(Packet)==0  || size<PacketSize);
-
-    while (skipRows<PacketSize &&
-           alignedStart != ((lhsAlignmentOffset + alignmentStep*skipRows)%PacketSize))
-      ++skipRows;
-    if (skipRows==PacketSize)
-    {
-      // nothing can be aligned, no need to skip any column
-      alignmentPattern = NoneAligned;
-      skipRows = 0;
-    }
-    else
-    {
-      skipRows = std::min(skipRows,res.size());
-      // note that the skiped columns are processed later.
-    }
-    ei_internal_assert((alignmentPattern==NoneAligned) || PacketSize==1
-      || (size_t(lhs+alignedStart+lhsStride*skipRows)%sizeof(Packet))==0);
-  }
-
-  int offset1 = (FirstAligned && alignmentStep==1?3:1);
-  int offset3 = (FirstAligned && alignmentStep==1?1:3);
-
-  int rowBound = ((res.size()-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows;
-  for (int i=skipRows; i<rowBound; i+=rowsAtOnce)
-  {
-    Scalar tmp0 = Scalar(0), tmp1 = Scalar(0), tmp2 = Scalar(0), tmp3 = Scalar(0);
-
-    // this helps the compiler generating good binary code
-    const Scalar *lhs0 = lhs + i*lhsStride,     *lhs1 = lhs + (i+offset1)*lhsStride,
-                 *lhs2 = lhs + (i+2)*lhsStride, *lhs3 = lhs + (i+offset3)*lhsStride;
-
-    if (PacketSize>1)
-    {
-      /* explicit vectorization */
-      Packet ptmp0 = ei_pset1(Scalar(0)), ptmp1 = ei_pset1(Scalar(0)), ptmp2 = ei_pset1(Scalar(0)), ptmp3 = ei_pset1(Scalar(0));
-
-      // process initial unaligned coeffs
-      // FIXME this loop get vectorized by the compiler !
-      for (int j=0; j<alignedStart; ++j)
-      {
-        Scalar b = rhs[j];
-        tmp0 += b*lhs0[j]; tmp1 += b*lhs1[j]; tmp2 += b*lhs2[j]; tmp3 += b*lhs3[j];
-      }
-
-      if (alignedSize>alignedStart)
-      {
-        switch(alignmentPattern)
-        {
-          case AllAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,d,d);
-            break;
-          case EvenAligned:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,d);
-            break;
-          case FirstAligned:
-            if (peels>1)
-            {
-              /* Here we proccess 4 rows with with two peeled iterations to hide
-               * tghe overhead of unaligned loads. Moreover unaligned loads are handled
-               * using special shift/move operations between the two aligned packets
-               * overlaping the desired unaligned packet. This is *much* more efficient
-               * than basic unaligned loads.
-               */
-              Packet A01, A02, A03, b, A11, A12, A13;
-              A01 = ei_pload(&lhs1[alignedStart-1]);
-              A02 = ei_pload(&lhs2[alignedStart-2]);
-              A03 = ei_pload(&lhs3[alignedStart-3]);
-
-              for (int j = alignedStart; j<peeledSize; j+=peels*PacketSize)
-              {
-                b = ei_pload(&rhs[j]);
-                A11 = ei_pload(&lhs1[j-1+PacketSize]);  ei_palign<1>(A01,A11);
-                A12 = ei_pload(&lhs2[j-2+PacketSize]);  ei_palign<2>(A02,A12);
-                A13 = ei_pload(&lhs3[j-3+PacketSize]);  ei_palign<3>(A03,A13);
-
-                ptmp0 = ei_pmadd(b, ei_pload (&lhs0[j]), ptmp0);
-                ptmp1 = ei_pmadd(b, A01, ptmp1);
-                A01 = ei_pload(&lhs1[j-1+2*PacketSize]);  ei_palign<1>(A11,A01);
-                ptmp2 = ei_pmadd(b, A02, ptmp2);
-                A02 = ei_pload(&lhs2[j-2+2*PacketSize]);  ei_palign<2>(A12,A02);
-                ptmp3 = ei_pmadd(b, A03, ptmp3);
-                A03 = ei_pload(&lhs3[j-3+2*PacketSize]);  ei_palign<3>(A13,A03);
-
-                b = ei_pload(&rhs[j+PacketSize]);
-                ptmp0 = ei_pmadd(b, ei_pload (&lhs0[j+PacketSize]), ptmp0);
-                ptmp1 = ei_pmadd(b, A11, ptmp1);
-                ptmp2 = ei_pmadd(b, A12, ptmp2);
-                ptmp3 = ei_pmadd(b, A13, ptmp3);
-              }
-            }
-            for (int j = peeledSize; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(d,du,du);
-            break;
-          default:
-            for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(du,du,du);
-            break;
-        }
-        tmp0 += ei_predux(ptmp0);
-        tmp1 += ei_predux(ptmp1);
-        tmp2 += ei_predux(ptmp2);
-        tmp3 += ei_predux(ptmp3);
-      }
-    } // end explicit vectorization
-
-    // process remaining coeffs (or all if no explicit vectorization)
-    // FIXME this loop get vectorized by the compiler !
-    for (int j=alignedSize; j<size; ++j)
-    {
-      Scalar b = rhs[j];
-      tmp0 += b*lhs0[j]; tmp1 += b*lhs1[j]; tmp2 += b*lhs2[j]; tmp3 += b*lhs3[j];
-    }
-    res[i] += tmp0; res[i+offset1] += tmp1; res[i+2] += tmp2; res[i+offset3] += tmp3;
-  }
-
-  // process remaining first and last rows (at most columnsAtOnce-1)
-  int end = res.size();
-  int start = rowBound;
-  do
-  {
-    for (int i=start; i<end; ++i)
-    {
-      Scalar tmp0 = Scalar(0);
-      Packet ptmp0 = ei_pset1(tmp0);
-      const Scalar* lhs0 = lhs + i*lhsStride;
-      // process first unaligned result's coeffs
-      // FIXME this loop get vectorized by the compiler !
-      for (int j=0; j<alignedStart; ++j)
-        tmp0 += rhs[j] * lhs0[j];
-
-      if (alignedSize>alignedStart)
-      {
-        // process aligned rhs coeffs
-        if ((size_t(lhs0+alignedStart)%sizeof(Packet))==0)
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
-            ptmp0 = ei_pmadd(ei_pload(&rhs[j]), ei_pload(&lhs0[j]), ptmp0);
-        else
-          for (int j = alignedStart;j<alignedSize;j+=PacketSize)
-            ptmp0 = ei_pmadd(ei_pload(&rhs[j]), ei_ploadu(&lhs0[j]), ptmp0);
-        tmp0 += ei_predux(ptmp0);
-      }
-
-      // process remaining scalars
-      // FIXME this loop get vectorized by the compiler !
-      for (int j=alignedSize; j<size; ++j)
-        tmp0 += rhs[j] * lhs0[j];
-      res[i] += tmp0;
-    }
-    if (skipRows)
-    {
-      start = 0;
-      end = skipRows;
-      skipRows = 0;
-    }
-    else
-      break;
-  } while(PacketSize>1);
-
-  #undef _EIGEN_ACCUMULATE_PACKETS
-}
-
-#endif // EIGEN_CACHE_FRIENDLY_PRODUCT_H

Eigen/src/Core/Coeffs.h

@@ -1,384 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_COEFFS_H
-#define EIGEN_COEFFS_H
-
-/** Short version: don't use this function, use
-  * \link operator()(int,int) const \endlink instead.
-  *
-  * Long version: this function is similar to
-  * \link operator()(int,int) const \endlink, but without the assertion.
-  * Use this for limiting the performance cost of debugging code when doing
-  * repeated coefficient access. Only use this when it is guaranteed that the
-  * parameters \a row and \a col are in range.
-  *
-  * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-  * function equivalent to \link operator()(int,int) const \endlink.
-  *
-  * \sa operator()(int,int) const, coeffRef(int,int), coeff(int) const
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::coeff(int row, int col) const
-{
-  ei_internal_assert(row >= 0 && row < rows()
-                     && col >= 0 && col < cols());
-  return derived().coeff(row, col);
-}
-
-/** \returns the coefficient at given the given row and column.
-  *
-  * \sa operator()(int,int), operator[](int) const
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::operator()(int row, int col) const
-{
-  ei_assert(row >= 0 && row < rows()
-      && col >= 0 && col < cols());
-  return derived().coeff(row, col);
-}
-
-/** Short version: don't use this function, use
-  * \link operator()(int,int) \endlink instead.
-  *
-  * Long version: this function is similar to
-  * \link operator()(int,int) \endlink, but without the assertion.
-  * Use this for limiting the performance cost of debugging code when doing
-  * repeated coefficient access. Only use this when it is guaranteed that the
-  * parameters \a row and \a col are in range.
-  *
-  * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-  * function equivalent to \link operator()(int,int) \endlink.
-  *
-  * \sa operator()(int,int), coeff(int, int) const, coeffRef(int)
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::coeffRef(int row, int col)
-{
-  ei_internal_assert(row >= 0 && row < rows()
-                     && col >= 0 && col < cols());
-  return derived().coeffRef(row, col);
-}
-
-/** \returns a reference to the coefficient at given the given row and column.
-  *
-  * \sa operator()(int,int) const, operator[](int)
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::operator()(int row, int col)
-{
-  ei_assert(row >= 0 && row < rows()
-      && col >= 0 && col < cols());
-  return derived().coeffRef(row, col);
-}
-
-/** Short version: don't use this function, use
-  * \link operator[](int) const \endlink instead.
-  *
-  * Long version: this function is similar to
-  * \link operator[](int) const \endlink, but without the assertion.
-  * Use this for limiting the performance cost of debugging code when doing
-  * repeated coefficient access. Only use this when it is guaranteed that the
-  * parameter \a index is in range.
-  *
-  * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-  * function equivalent to \link operator[](int) const \endlink.
-  *
-  * \sa operator[](int) const, coeffRef(int), coeff(int,int) const
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::coeff(int index) const
-{
-  ei_internal_assert(index >= 0 && index < size());
-  return derived().coeff(index);
-}
-
-/** \returns the coefficient at given index.
-  *
-  * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-  *
-  * \sa operator[](int), operator()(int,int) const, x() const, y() const,
-  * z() const, w() const
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::operator[](int index) const
-{
-  ei_assert(index >= 0 && index < size());
-  return derived().coeff(index);
-}
-
-/** \returns the coefficient at given index.
-  *
-  * This is synonymous to operator[](int) const.
-  *
-  * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-  *
-  * \sa operator[](int), operator()(int,int) const, x() const, y() const,
-  * z() const, w() const
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::operator()(int index) const
-{
-  ei_assert(index >= 0 && index < size());
-  return derived().coeff(index);
-}
-
-/** Short version: don't use this function, use
-  * \link operator[](int) \endlink instead.
-  *
-  * Long version: this function is similar to
-  * \link operator[](int) \endlink, but without the assertion.
-  * Use this for limiting the performance cost of debugging code when doing
-  * repeated coefficient access. Only use this when it is guaranteed that the
-  * parameters \a row and \a col are in range.
-  *
-  * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
-  * function equivalent to \link operator[](int) \endlink.
-  *
-  * \sa operator[](int), coeff(int) const, coeffRef(int,int)
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::coeffRef(int index)
-{
-  ei_internal_assert(index >= 0 && index < size());
-  return derived().coeffRef(index);
-}
-
-/** \returns a reference to the coefficient at given index.
-  *
-  * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-  *
-  * \sa operator[](int) const, operator()(int,int), x(), y(), z(), w()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::operator[](int index)
-{
-  ei_assert(index >= 0 && index < size());
-  return derived().coeffRef(index);
-}
-
-/** \returns a reference to the coefficient at given index.
-  *
-  * This is synonymous to operator[](int).
-  *
-  * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
-  *
-  * \sa operator[](int) const, operator()(int,int), x(), y(), z(), w()
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::operator()(int index)
-{
-  ei_assert(index >= 0 && index < size());
-  return derived().coeffRef(index);
-}
-
-/** equivalent to operator[](0).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::x() const { return (*this)[0]; }
-
-/** equivalent to operator[](1).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::y() const { return (*this)[1]; }
-
-/** equivalent to operator[](2).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::z() const { return (*this)[2]; }
-
-/** equivalent to operator[](3).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename ei_traits<Derived>::Scalar MatrixBase<Derived>
-  ::w() const { return (*this)[3]; }
-
-/** equivalent to operator[](0).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::x() { return (*this)[0]; }
-
-/** equivalent to operator[](1).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::y() { return (*this)[1]; }
-
-/** equivalent to operator[](2).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::z() { return (*this)[2]; }
-
-/** equivalent to operator[](3).  */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename ei_traits<Derived>::Scalar& MatrixBase<Derived>
-  ::w() { return (*this)[3]; }
-
-/** \returns the packet of coefficients starting at the given row and column. It is your responsibility
-  * to ensure that a packet really starts there. This method is only available on expressions having the
-  * PacketAccessBit.
-  *
-  * The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
-  * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-  * starting at an address which is a multiple of the packet size.
-  */
-template<typename Derived>
-template<int LoadMode>
-EIGEN_STRONG_INLINE typename ei_packet_traits<typename ei_traits<Derived>::Scalar>::type
-MatrixBase<Derived>::packet(int row, int col) const
-{
-  ei_internal_assert(row >= 0 && row < rows()
-                     && col >= 0 && col < cols());
-  return derived().template packet<LoadMode>(row,col);
-}
-
-/** Stores the given packet of coefficients, at the given row and column of this expression. It is your responsibility
-  * to ensure that a packet really starts there. This method is only available on expressions having the
-  * PacketAccessBit.
-  *
-  * The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
-  * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-  * starting at an address which is a multiple of the packet size.
-  */
-template<typename Derived>
-template<int StoreMode>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::writePacket
-(int row, int col, const typename ei_packet_traits<typename ei_traits<Derived>::Scalar>::type& x)
-{
-  ei_internal_assert(row >= 0 && row < rows()
-                     && col >= 0 && col < cols());
-  derived().template writePacket<StoreMode>(row,col,x);
-}
-
-/** \returns the packet of coefficients starting at the given index. It is your responsibility
-  * to ensure that a packet really starts there. This method is only available on expressions having the
-  * PacketAccessBit and the LinearAccessBit.
-  *
-  * The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
-  * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-  * starting at an address which is a multiple of the packet size.
-  */
-template<typename Derived>
-template<int LoadMode>
-EIGEN_STRONG_INLINE typename ei_packet_traits<typename ei_traits<Derived>::Scalar>::type
-MatrixBase<Derived>::packet(int index) const
-{
-  ei_internal_assert(index >= 0 && index < size());
-  return derived().template packet<LoadMode>(index);
-}
-
-/** Stores the given packet of coefficients, at the given index in this expression. It is your responsibility
-  * to ensure that a packet really starts there. This method is only available on expressions having the
-  * PacketAccessBit and the LinearAccessBit.
-  *
-  * The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
-  * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
-  * starting at an address which is a multiple of the packet size.
-  */
-template<typename Derived>
-template<int StoreMode>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::writePacket
-(int index, const typename ei_packet_traits<typename ei_traits<Derived>::Scalar>::type& x)
-{
-  ei_internal_assert(index >= 0 && index < size());
-  derived().template writePacket<StoreMode>(index,x);
-}
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-
-/** \internal Copies the coefficient at position (row,col) of other into *this.
-  *
-  * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-  * with usual assignments.
-  *
-  * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::copyCoeff(int row, int col, const MatrixBase<OtherDerived>& other)
-{
-  ei_internal_assert(row >= 0 && row < rows()
-                     && col >= 0 && col < cols());
-  derived().coeffRef(row, col) = other.derived().coeff(row, col);
-}
-
-/** \internal Copies the coefficient at the given index of other into *this.
-  *
-  * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-  * with usual assignments.
-  *
-  * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::copyCoeff(int index, const MatrixBase<OtherDerived>& other)
-{
-  ei_internal_assert(index >= 0 && index < size());
-  derived().coeffRef(index) = other.derived().coeff(index);
-}
-
-/** \internal Copies the packet at position (row,col) of other into *this.
-  *
-  * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-  * with usual assignments.
-  *
-  * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-  */
-template<typename Derived>
-template<typename OtherDerived, int StoreMode, int LoadMode>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::copyPacket(int row, int col, const MatrixBase<OtherDerived>& other)
-{
-  ei_internal_assert(row >= 0 && row < rows()
-                     && col >= 0 && col < cols());
-  derived().template writePacket<StoreMode>(row, col,
-    other.derived().template packet<LoadMode>(row, col));
-}
-
-/** \internal Copies the packet at the given index of other into *this.
-  *
-  * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
-  * with usual assignments.
-  *
-  * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
-  */
-template<typename Derived>
-template<typename OtherDerived, int StoreMode, int LoadMode>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::copyPacket(int index, const MatrixBase<OtherDerived>& other)
-{
-  ei_internal_assert(index >= 0 && index < size());
-  derived().template writePacket<StoreMode>(index,
-    other.derived().template packet<LoadMode>(index));
-}
-
-#endif
-
-#endif // EIGEN_COEFFS_H

Eigen/src/Core/CommaInitializer.h

@@ -1,32 +1,20 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COMMAINITIALIZER_H
 #define EIGEN_COMMAINITIALIZER_H
 
+namespace Eigen { 
+
 /** \class CommaInitializer
+  * \ingroup Core_Module
   *
   * \brief Helper class used by the comma initializer operator
   *
@@ -36,70 +24,85 @@
   *
   * \sa \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
   */
-template<typename MatrixType>
+template<typename XprType>
 struct CommaInitializer
 {
-  typedef typename ei_traits<MatrixType>::Scalar Scalar;
-  inline CommaInitializer(MatrixType& mat, const Scalar& s)
-    : m_matrix(mat), m_row(0), m_col(1), m_currentBlockRows(1)
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::Index Index;
+
+  inline CommaInitializer(XprType& xpr, const Scalar& s)
+    : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
   {
-    m_matrix.coeffRef(0,0) = s;
+    m_xpr.coeffRef(0,0) = s;
   }
 
   template<typename OtherDerived>
-  inline CommaInitializer(MatrixType& mat, const MatrixBase<OtherDerived>& other)
-    : m_matrix(mat), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
+  inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
+    : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
   {
-    m_matrix.block(0, 0, other.rows(), other.cols()) = other;
+    m_xpr.block(0, 0, other.rows(), other.cols()) = other;
+  }
+
+  /* Copy/Move constructor which transfers ownership. This is crucial in 
+   * absence of return value optimization to avoid assertions during destruction. */
+  // FIXME in C++11 mode this could be replaced by a proper RValue constructor
+  inline CommaInitializer(const CommaInitializer& o)
+  : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
+    // Mark original object as finished. In absence of R-value references we need to const_cast:
+    const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
+    const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
+    const_cast<CommaInitializer&>(o).m_currentBlockRows = 0;
   }
 
   /* inserts a scalar value in the target matrix */
   CommaInitializer& operator,(const Scalar& s)
   {
-    if (m_col==m_matrix.cols())
+    if (m_col==m_xpr.cols())
     {
       m_row+=m_currentBlockRows;
       m_col = 0;
       m_currentBlockRows = 1;
-      ei_assert(m_row<m_matrix.rows()
+      eigen_assert(m_row<m_xpr.rows()
         && "Too many rows passed to comma initializer (operator<<)");
     }
-    ei_assert(m_col<m_matrix.cols()
+    eigen_assert(m_col<m_xpr.cols()
       && "Too many coefficients passed to comma initializer (operator<<)");
-    ei_assert(m_currentBlockRows==1);
-    m_matrix.coeffRef(m_row, m_col++) = s;
+    eigen_assert(m_currentBlockRows==1);
+    m_xpr.coeffRef(m_row, m_col++) = s;
     return *this;
   }
 
   /* inserts a matrix expression in the target matrix */
   template<typename OtherDerived>
-  CommaInitializer& operator,(const MatrixBase<OtherDerived>& other)
+  CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
   {
-    if (m_col==m_matrix.cols())
+    if(other.cols()==0 || other.rows()==0)
+      return *this;
+    if (m_col==m_xpr.cols())
     {
       m_row+=m_currentBlockRows;
       m_col = 0;
       m_currentBlockRows = other.rows();
-      ei_assert(m_row+m_currentBlockRows<=m_matrix.rows()
+      eigen_assert(m_row+m_currentBlockRows<=m_xpr.rows()
         && "Too many rows passed to comma initializer (operator<<)");
     }
-    ei_assert(m_col<m_matrix.cols()
+    eigen_assert(m_col<m_xpr.cols()
       && "Too many coefficients passed to comma initializer (operator<<)");
-    ei_assert(m_currentBlockRows==other.rows());
+    eigen_assert(m_currentBlockRows==other.rows());
     if (OtherDerived::SizeAtCompileTime != Dynamic)
-      m_matrix.template block<OtherDerived::RowsAtCompileTime != Dynamic ? OtherDerived::RowsAtCompileTime : 1,
+      m_xpr.template block<OtherDerived::RowsAtCompileTime != Dynamic ? OtherDerived::RowsAtCompileTime : 1,
                               OtherDerived::ColsAtCompileTime != Dynamic ? OtherDerived::ColsAtCompileTime : 1>
                     (m_row, m_col) = other;
     else
-      m_matrix.block(m_row, m_col, other.rows(), other.cols()) = other;
+      m_xpr.block(m_row, m_col, other.rows(), other.cols()) = other;
     m_col += other.cols();
     return *this;
   }
 
   inline ~CommaInitializer()
   {
-    ei_assert((m_row+m_currentBlockRows) == m_matrix.rows()
-         && m_col == m_matrix.cols()
+    eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows()
+         && m_col == m_xpr.cols()
          && "Too few coefficients passed to comma initializer (operator<<)");
   }
 
@@ -110,12 +113,12 @@ struct CommaInitializer
     * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
     * \endcode
     */
-  inline MatrixType& finished() { return m_matrix; }
+  inline XprType& finished() { return m_xpr; }
 
-  MatrixType& m_matrix;   // target matrix
-  int m_row;              // current row id
-  int m_col;              // current col id
-  int m_currentBlockRows; // current block height
+  XprType& m_xpr;   // target expression
+  Index m_row;              // current row id
+  Index m_col;              // current col id
+  Index m_currentBlockRows; // current block height
 };
 
 /** \anchor MatrixBaseCommaInitRef
@@ -124,15 +127,15 @@ struct CommaInitializer
   * The coefficients must be provided in a row major order and exactly match
   * the size of the matrix. Otherwise an assertion is raised.
   *
-  * \addexample CommaInit \label How to easily set all the coefficients of a matrix
-  *
   * Example: \include MatrixBase_set.cpp
   * Output: \verbinclude MatrixBase_set.out
+  * 
+  * \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary order.
   *
   * \sa CommaInitializer::finished(), class CommaInitializer
   */
 template<typename Derived>
-inline CommaInitializer<Derived> MatrixBase<Derived>::operator<< (const Scalar& s)
+inline CommaInitializer<Derived> DenseBase<Derived>::operator<< (const Scalar& s)
 {
   return CommaInitializer<Derived>(*static_cast<Derived*>(this), s);
 }
@@ -141,9 +144,11 @@ inline CommaInitializer<Derived> MatrixBase<Derived>::operator<< (const Scalar&
 template<typename Derived>
 template<typename OtherDerived>
 inline CommaInitializer<Derived>
-MatrixBase<Derived>::operator<<(const MatrixBase<OtherDerived>& other)
+DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
 {
   return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_COMMAINITIALIZER_H

Eigen/src/Core/CoreInstantiations.cpp

@@ -1,47 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifdef EIGEN_EXTERN_INSTANTIATIONS
-#undef EIGEN_EXTERN_INSTANTIATIONS
-#endif
-
-#include "../../Core"
-
-namespace Eigen
-{
-
-#define EIGEN_INSTANTIATE_PRODUCT(TYPE) \
-template static void ei_cache_friendly_product<TYPE>( \
-  int _rows, int _cols, int depth, \
-  bool _lhsRowMajor, const TYPE* _lhs, int _lhsStride, \
-  bool _rhsRowMajor, const TYPE* _rhs, int _rhsStride, \
-  bool resRowMajor, TYPE* res, int resStride)
-
-EIGEN_INSTANTIATE_PRODUCT(float);
-EIGEN_INSTANTIATE_PRODUCT(double);
-EIGEN_INSTANTIATE_PRODUCT(int);
-EIGEN_INSTANTIATE_PRODUCT(std::complex<float>);
-EIGEN_INSTANTIATE_PRODUCT(std::complex<double>);
-
-}

Eigen/src/Core/CoreIterators.h

@@ -0,0 +1,61 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_COREITERATORS_H
+#define EIGEN_COREITERATORS_H
+
+namespace Eigen { 
+
+/* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
+ */
+
+/** \ingroup SparseCore_Module
+  * \class InnerIterator
+  * \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression
+  *
+  * todo
+  */
+
+// generic version for dense matrix and expressions
+template<typename Derived> class DenseBase<Derived>::InnerIterator
+{
+  protected:
+    typedef typename Derived::Scalar Scalar;
+    typedef typename Derived::Index Index;
+
+    enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit };
+  public:
+    EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, Index outer)
+      : m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.innerSize())
+    {}
+
+    EIGEN_STRONG_INLINE Scalar value() const
+    {
+      return (IsRowMajor) ? m_expression.coeff(m_outer, m_inner)
+                          : m_expression.coeff(m_inner, m_outer);
+    }
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
+
+    EIGEN_STRONG_INLINE Index index() const { return m_inner; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
+
+  protected:
+    const Derived& m_expression;
+    Index m_inner;
+    const Index m_outer;
+    const Index m_end;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_COREITERATORS_H

Eigen/src/Core/CwiseBinaryOp.h

@@ -1,156 +1,200 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_BINARY_OP_H
 #define EIGEN_CWISE_BINARY_OP_H
 
+namespace Eigen {
+
 /** \class CwiseBinaryOp
+  * \ingroup Core_Module
   *
-  * \brief Generic expression of a coefficient-wise operator between two matrices or vectors
+  * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
   *
   * \param BinaryOp template functor implementing the operator
   * \param Lhs the type of the left-hand side
   * \param Rhs the type of the right-hand side
   *
-  * This class represents an expression of a generic binary operator of two matrices or vectors.
-  * It is the return type of the operator+, operator-, and the Cwise methods, and most
-  * of the time this is the only way it is used.
+  * This class represents an expression  where a coefficient-wise binary operator is applied to two expressions.
+  * It is the return type of binary operators, by which we mean only those binary operators where
+  * both the left-hand side and the right-hand side are Eigen expressions.
+  * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp.
   *
-  * However, if you want to write a function returning such an expression, you
-  * will need to use this class.
+  * Most of the time, this is the only way that it is used, so you typically don't have to name
+  * CwiseBinaryOp types explicitly.
   *
   * \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp
   */
+
+namespace internal {
 template<typename BinaryOp, typename Lhs, typename Rhs>
-struct ei_traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
 {
+  // we must not inherit from traits<Lhs> since it has
+  // the potential to cause problems with MSVC
+  typedef typename remove_all<Lhs>::type Ancestor;
+  typedef typename traits<Ancestor>::XprKind XprKind;
+  enum {
+    RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
+    ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
+    MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
+  };
+
   // even though we require Lhs and Rhs to have the same scalar type (see CwiseBinaryOp constructor),
   // we still want to handle the case when the result type is different.
-  typedef typename ei_result_of<
+  typedef typename result_of<
                      BinaryOp(
                        typename Lhs::Scalar,
                        typename Rhs::Scalar
                      )
                    >::type Scalar;
+  typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
+                                           typename traits<Rhs>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<Lhs>::Index,
+                                         typename traits<Rhs>::Index>::type Index;
   typedef typename Lhs::Nested LhsNested;
   typedef typename Rhs::Nested RhsNested;
-  typedef typename ei_unref<LhsNested>::type _LhsNested;
-  typedef typename ei_unref<RhsNested>::type _RhsNested;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
   enum {
     LhsCoeffReadCost = _LhsNested::CoeffReadCost,
     RhsCoeffReadCost = _RhsNested::CoeffReadCost,
     LhsFlags = _LhsNested::Flags,
     RhsFlags = _RhsNested::Flags,
-    RowsAtCompileTime = Lhs::RowsAtCompileTime,
-    ColsAtCompileTime = Lhs::ColsAtCompileTime,
-    MaxRowsAtCompileTime = Lhs::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = Lhs::MaxColsAtCompileTime,
-    Flags = (int(LhsFlags) | int(RhsFlags)) & (
+    SameType = is_same<typename _LhsNested::Scalar,typename _RhsNested::Scalar>::value,
+    StorageOrdersAgree = (int(Lhs::Flags)&RowMajorBit)==(int(Rhs::Flags)&RowMajorBit),
+    Flags0 = (int(LhsFlags) | int(RhsFlags)) & (
         HereditaryBits
-      | (int(LhsFlags) & int(RhsFlags) & (LinearAccessBit | AlignedBit))
-      | (ei_functor_traits<BinaryOp>::PacketAccess && ((int(LhsFlags) & RowMajorBit)==(int(RhsFlags) & RowMajorBit))
-        ? (int(LhsFlags) & int(RhsFlags) & PacketAccessBit) : 0)),
-    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + ei_functor_traits<BinaryOp>::Cost
+      | (int(LhsFlags) & int(RhsFlags) &
+           ( AlignedBit
+           | (StorageOrdersAgree ? LinearAccessBit : 0)
+           | (functor_traits<BinaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)
+           )
+        )
+     ),
+    Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
+    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + functor_traits<BinaryOp>::Cost
   };
 };
+} // end namespace internal
+
+// we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor
+// that would take two operands of different types. If there were such an example, then this check should be
+// moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as
+// currently they take only one typename Scalar template parameter.
+// It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
+// So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
+// add together a float matrix and a double matrix.
+#define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \
+  EIGEN_STATIC_ASSERT((internal::functor_is_product_like<BINOP>::ret \
+                        ? int(internal::scalar_product_traits<LHS, RHS>::Defined) \
+                        : int(internal::is_same<LHS, RHS>::value)), \
+    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+
+template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
+class CwiseBinaryOpImpl;
 
 template<typename BinaryOp, typename Lhs, typename Rhs>
-class CwiseBinaryOp : ei_no_assignment_operator,
-  public MatrixBase<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+class CwiseBinaryOp : internal::no_assignment_operator,
+  public CwiseBinaryOpImpl<
+          BinaryOp, Lhs, Rhs,
+          typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
+                                           typename internal::traits<Rhs>::StorageKind>::ret>
 {
   public:
 
+    typedef typename CwiseBinaryOpImpl<
+        BinaryOp, Lhs, Rhs,
+        typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
+                                         typename internal::traits<Rhs>::StorageKind>::ret>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
-    typedef typename ei_traits<CwiseBinaryOp>::LhsNested LhsNested;
-    typedef typename ei_traits<CwiseBinaryOp>::RhsNested RhsNested;
 
-    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
-      : m_lhs(lhs), m_rhs(rhs), m_functor(func)
+    typedef typename internal::nested<Lhs>::type LhsNested;
+    typedef typename internal::nested<Rhs>::type RhsNested;
+    typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
+    typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
+
+    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
+      : m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
     {
-      // we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor
-      // that would take two operands of different types. If there were such an example, then this check should be
-      // moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as
-      // currently they take only one typename Scalar template parameter.
-      // It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
-      // So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
-      // add together a float matrix and a double matrix.
-      EIGEN_STATIC_ASSERT((ei_functor_allows_mixing_real_and_complex<BinaryOp>::ret
-                           ? int(ei_is_same_type<typename Lhs::RealScalar, typename Rhs::RealScalar>::ret)
-                           : int(ei_is_same_type<typename Lhs::Scalar, typename Rhs::Scalar>::ret)),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+      EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
       // require the sizes to match
       EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
-      ei_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
+      eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
     }
 
-    EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_lhs.cols(); }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const
-    {
-      return m_functor(m_lhs.coeff(row, col), m_rhs.coeff(row, col));
+    EIGEN_STRONG_INLINE Index rows() const {
+      // return the fixed size type if available to enable compile time optimizations
+      if (internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic)
+        return m_rhs.rows();
+      else
+        return m_lhs.rows();
+    }
+    EIGEN_STRONG_INLINE Index cols() const {
+      // return the fixed size type if available to enable compile time optimizations
+      if (internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic)
+        return m_rhs.cols();
+      else
+        return m_lhs.cols();
     }
 
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
-    {
-      return m_functor.packetOp(m_lhs.template packet<LoadMode>(row, col), m_rhs.template packet<LoadMode>(row, col));
-    }
-
-    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
-    {
-      return m_functor(m_lhs.coeff(index), m_rhs.coeff(index));
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int index) const
-    {
-      return m_functor.packetOp(m_lhs.template packet<LoadMode>(index), m_rhs.template packet<LoadMode>(index));
-    }
+    /** \returns the left hand side nested expression */
+    const _LhsNested& lhs() const { return m_lhs; }
+    /** \returns the right hand side nested expression */
+    const _RhsNested& rhs() const { return m_rhs; }
+    /** \returns the functor representing the binary operation */
+    const BinaryOp& functor() const { return m_functor; }
 
   protected:
-    const LhsNested m_lhs;
-    const RhsNested m_rhs;
+    LhsNested m_lhs;
+    RhsNested m_rhs;
     const BinaryOp m_functor;
 };
 
-/**\returns an expression of the difference of \c *this and \a other
-  *
-  * \note If you want to substract a given scalar from all coefficients, see Cwise::operator-().
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::operator-=(), Cwise::operator-()
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const CwiseBinaryOp<ei_scalar_difference_op<typename ei_traits<Derived>::Scalar>,
-                                 Derived, OtherDerived>
-MatrixBase<Derived>::operator-(const MatrixBase<OtherDerived> &other) const
+template<typename BinaryOp, typename Lhs, typename Rhs>
+class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
+  : public internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
 {
-  return CwiseBinaryOp<ei_scalar_difference_op<Scalar>,
-                       Derived, OtherDerived>(derived(), other.derived());
-}
+    typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
+  public:
+
+    typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
+
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
+    {
+      return derived().functor()(derived().lhs().coeff(rowId, colId),
+                                 derived().rhs().coeff(rowId, colId));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
+    {
+      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
+                                          derived().rhs().template packet<LoadMode>(rowId, colId));
+    }
+
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
+    {
+      return derived().functor()(derived().lhs().coeff(index),
+                                 derived().rhs().coeff(index));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
+    {
+      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(index),
+                                          derived().rhs().template packet<LoadMode>(index));
+    }
+};
 
 /** replaces \c *this by \c *this - \a other.
   *
@@ -161,23 +205,9 @@ template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived &
 MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
 {
-  return *this = *this - other;
-}
-
-/** \relates MatrixBase
-  *
-  * \returns an expression of the sum of \c *this and \a other
-  *
-  * \note If you want to add a given scalar to all coefficients, see Cwise::operator+().
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::operator+=(), Cwise::operator+()
-  */
-template<typename Derived>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const CwiseBinaryOp<ei_scalar_sum_op<typename ei_traits<Derived>::Scalar>, Derived, OtherDerived>
-MatrixBase<Derived>::operator+(const MatrixBase<OtherDerived> &other) const
-{
-  return CwiseBinaryOp<ei_scalar_sum_op<Scalar>, Derived, OtherDerived>(derived(), other.derived());
+  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
 }
 
 /** replaces \c *this by \c *this + \a other.
@@ -189,116 +219,11 @@ template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived &
 MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
 {
-  return *this = *this + other;
+  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
 }
 
-/** \returns an expression of the Schur product (coefficient wise product) of *this and \a other
-  *
-  * Example: \include Cwise_product.cpp
-  * Output: \verbinclude Cwise_product.out
-  *
-  * \sa class CwiseBinaryOp, operator/(), square()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_PRODUCT_RETURN_TYPE
-Cwise<ExpressionType>::operator*(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_PRODUCT_RETURN_TYPE(_expression(), other.derived());
-}
-
-/** \returns an expression of the coefficient-wise quotient of *this and \a other
-  *
-  * Example: \include Cwise_quotient.cpp
-  * Output: \verbinclude Cwise_quotient.out
-  *
-  * \sa class CwiseBinaryOp, operator*(), inverse()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)
-Cwise<ExpressionType>::operator/(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)(_expression(), other.derived());
-}
-
-/** Replaces this expression by its coefficient-wise product with \a other.
-  *
-  * Example: \include Cwise_times_equal.cpp
-  * Output: \verbinclude Cwise_times_equal.out
-  *
-  * \sa operator*(), operator/=()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline ExpressionType& Cwise<ExpressionType>::operator*=(const MatrixBase<OtherDerived> &other)
-{
-  return m_matrix.const_cast_derived() = *this * other;
-}
-
-/** Replaces this expression by its coefficient-wise quotient by \a other.
-  *
-  * Example: \include Cwise_slash_equal.cpp
-  * Output: \verbinclude Cwise_slash_equal.out
-  *
-  * \sa operator/(), operator*=()
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-inline ExpressionType& Cwise<ExpressionType>::operator/=(const MatrixBase<OtherDerived> &other)
-{
-  return m_matrix.const_cast_derived() = *this / other;
-}
-
-/** \returns an expression of the coefficient-wise min of *this and \a other
-  *
-  * Example: \include Cwise_min.cpp
-  * Output: \verbinclude Cwise_min.out
-  *
-  * \sa class CwiseBinaryOp
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)
-Cwise<ExpressionType>::min(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)(_expression(), other.derived());
-}
-
-/** \returns an expression of the coefficient-wise max of *this and \a other
-  *
-  * Example: \include Cwise_max.cpp
-  * Output: \verbinclude Cwise_max.out
-  *
-  * \sa class CwiseBinaryOp
-  */
-template<typename ExpressionType>
-template<typename OtherDerived>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_max_op)
-Cwise<ExpressionType>::max(const MatrixBase<OtherDerived> &other) const
-{
-  return EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_max_op)(_expression(), other.derived());
-}
-
-/** \returns an expression of a custom coefficient-wise operator \a func of *this and \a other
-  *
-  * The template parameter \a CustomBinaryOp is the type of the functor
-  * of the custom operator (see class CwiseBinaryOp for an example)
-  *
-  * \addexample CustomCwiseBinaryFunctors \label How to use custom coeff wise binary functors
-  *
-  * Here is an example illustrating the use of custom functors:
-  * \include class_CwiseBinaryOp.cpp
-  * Output: \verbinclude class_CwiseBinaryOp.out
-  *
-  * \sa class CwiseBinaryOp, MatrixBase::operator+, MatrixBase::operator-, Cwise::operator*, Cwise::operator/
-  */
-template<typename Derived>
-template<typename CustomBinaryOp, typename OtherDerived>
-EIGEN_STRONG_INLINE const CwiseBinaryOp<CustomBinaryOp, Derived, OtherDerived>
-MatrixBase<Derived>::binaryExpr(const MatrixBase<OtherDerived> &other, const CustomBinaryOp& func) const
-{
-  return CwiseBinaryOp<CustomBinaryOp, Derived, OtherDerived>(derived(), other.derived(), func);
-}
+} // end namespace Eigen
 
 #endif // EIGEN_CWISE_BINARY_OP_H

Eigen/src/Core/CwiseNullaryOp.h

@@ -1,106 +1,99 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_NULLARY_OP_H
 #define EIGEN_CWISE_NULLARY_OP_H
 
+namespace Eigen {
+
 /** \class CwiseNullaryOp
+  * \ingroup Core_Module
   *
   * \brief Generic expression of a matrix where all coefficients are defined by a functor
   *
   * \param NullaryOp template functor implementing the operator
+  * \param PlainObjectType the underlying plain matrix/array type
   *
   * This class represents an expression of a generic nullary operator.
-  * It is the return type of the Ones(), Zero(), Constant(), Identity() and Random() functions,
+  * It is the return type of the Ones(), Zero(), Constant(), Identity() and Random() methods,
   * and most of the time this is the only way it is used.
   *
   * However, if you want to write a function returning such an expression, you
   * will need to use this class.
   *
-  * \sa class CwiseUnaryOp, class CwiseBinaryOp, MatrixBase::NullaryExpr()
+  * \sa class CwiseUnaryOp, class CwiseBinaryOp, DenseBase::NullaryExpr()
   */
-template<typename NullaryOp, typename MatrixType>
-struct ei_traits<CwiseNullaryOp<NullaryOp, MatrixType> > : ei_traits<MatrixType>
+
+namespace internal {
+template<typename NullaryOp, typename PlainObjectType>
+struct traits<CwiseNullaryOp<NullaryOp, PlainObjectType> > : traits<PlainObjectType>
 {
   enum {
-    Flags = (ei_traits<MatrixType>::Flags
+    Flags = (traits<PlainObjectType>::Flags
       & (  HereditaryBits
-         | (ei_functor_has_linear_access<NullaryOp>::ret ? LinearAccessBit : 0)
-         | (ei_functor_traits<NullaryOp>::PacketAccess ? PacketAccessBit : 0)))
-      | (ei_functor_traits<NullaryOp>::IsRepeatable ? 0 : EvalBeforeNestingBit),
-    CoeffReadCost = ei_functor_traits<NullaryOp>::Cost
+         | (functor_has_linear_access<NullaryOp>::ret ? LinearAccessBit : 0)
+         | (functor_traits<NullaryOp>::PacketAccess ? PacketAccessBit : 0)))
+      | (functor_traits<NullaryOp>::IsRepeatable ? 0 : EvalBeforeNestingBit),
+    CoeffReadCost = functor_traits<NullaryOp>::Cost
   };
 };
+}
 
-template<typename NullaryOp, typename MatrixType>
-class CwiseNullaryOp : ei_no_assignment_operator,
-  public MatrixBase<CwiseNullaryOp<NullaryOp, MatrixType> >
+template<typename NullaryOp, typename PlainObjectType>
+class CwiseNullaryOp : internal::no_assignment_operator,
+  public internal::dense_xpr_base< CwiseNullaryOp<NullaryOp, PlainObjectType> >::type
 {
   public:
 
-    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseNullaryOp)
+    typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
 
-    CwiseNullaryOp(int rows, int cols, const NullaryOp& func = NullaryOp())
-      : m_rows(rows), m_cols(cols), m_functor(func)
+    CwiseNullaryOp(Index nbRows, Index nbCols, const NullaryOp& func = NullaryOp())
+      : m_rows(nbRows), m_cols(nbCols), m_functor(func)
     {
-      ei_assert(rows > 0
-          && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-          && cols > 0
-          && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
+      eigen_assert(nbRows >= 0
+            && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
+            &&  nbCols >= 0
+            && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols));
     }
 
-    EIGEN_STRONG_INLINE int rows() const { return m_rows.value(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_cols.value(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int rows, int cols) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
     {
-      return m_functor(rows, cols);
+      return m_functor(rowId, colId);
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int, int) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
     {
-      return m_functor.packetOp();
+      return m_functor.packetOp(rowId, colId);
     }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
     {
-      if(RowsAtCompileTime == 1)
-        return m_functor(0, index);
-      else
-        return m_functor(index, 0);
+      return m_functor(index);
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
     {
-      return m_functor.packetOp();
+      return m_functor.packetOp(index);
     }
 
+    /** \returns the functor representing the nullary operation */
+    const NullaryOp& functor() const { return m_functor; }
+
   protected:
-    const ei_int_if_dynamic<RowsAtCompileTime> m_rows;
-    const ei_int_if_dynamic<ColsAtCompileTime> m_cols;
+    const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
+    const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
     const NullaryOp m_functor;
 };
 
@@ -121,7 +114,7 @@ class CwiseNullaryOp : ei_no_assignment_operator,
 template<typename Derived>
 template<typename CustomNullaryOp>
 EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
-MatrixBase<Derived>::NullaryExpr(int rows, int cols, const CustomNullaryOp& func)
+DenseBase<Derived>::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func)
 {
   return CwiseNullaryOp<CustomNullaryOp, Derived>(rows, cols, func);
 }
@@ -144,17 +137,16 @@ MatrixBase<Derived>::NullaryExpr(int rows, int cols, const CustomNullaryOp& func
 template<typename Derived>
 template<typename CustomNullaryOp>
 EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
-MatrixBase<Derived>::NullaryExpr(int size, const CustomNullaryOp& func)
+DenseBase<Derived>::NullaryExpr(Index size, const CustomNullaryOp& func)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  ei_assert(IsVectorAtCompileTime);
   if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, Derived>(1, size, func);
   else return CwiseNullaryOp<CustomNullaryOp, Derived>(size, 1, func);
 }
 
 /** \returns an expression of a matrix defined by a custom functor \a func
   *
-  * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
+  * This variant is only for fixed-size DenseBase types. For dynamic-size types, you
   * need to use the variants taking size arguments.
   *
   * The template parameter \a CustomNullaryOp is the type of the functor.
@@ -164,18 +156,18 @@ MatrixBase<Derived>::NullaryExpr(int size, const CustomNullaryOp& func)
 template<typename Derived>
 template<typename CustomNullaryOp>
 EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
-MatrixBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
+DenseBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
 {
   return CwiseNullaryOp<CustomNullaryOp, Derived>(RowsAtCompileTime, ColsAtCompileTime, func);
 }
 
 /** \returns an expression of a constant matrix of value \a value
   *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
-  * the returned matrix. Must be compatible with this MatrixBase type.
+  * The parameters \a nbRows and \a nbCols are the number of rows and of columns of
+  * the returned matrix. Must be compatible with this DenseBase type.
   *
   * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
-  * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
+  * it is redundant to pass \a nbRows and \a nbCols as arguments, so Zero() should be used
   * instead.
   *
   * The template parameter \a CustomNullaryOp is the type of the functor.
@@ -183,16 +175,16 @@ MatrixBase<Derived>::NullaryExpr(const CustomNullaryOp& func)
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Constant(int rows, int cols, const Scalar& value)
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Constant(Index nbRows, Index nbCols, const Scalar& value)
 {
-  return NullaryExpr(rows, cols, ei_scalar_constant_op<Scalar>(value));
+  return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_constant_op<Scalar>(value));
 }
 
 /** \returns an expression of a constant matrix of value \a value
   *
   * The parameter \a size is the size of the returned vector.
-  * Must be compatible with this MatrixBase type.
+  * Must be compatible with this DenseBase type.
   *
   * \only_for_vectors
   *
@@ -205,15 +197,15 @@ MatrixBase<Derived>::Constant(int rows, int cols, const Scalar& value)
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Constant(int size, const Scalar& value)
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Constant(Index size, const Scalar& value)
 {
-  return NullaryExpr(size, ei_scalar_constant_op<Scalar>(value));
+  return DenseBase<Derived>::NullaryExpr(size, internal::scalar_constant_op<Scalar>(value));
 }
 
 /** \returns an expression of a constant matrix of value \a value
   *
-  * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you
+  * This variant is only for fixed-size DenseBase types. For dynamic-size types, you
   * need to use the variants taking size arguments.
   *
   * The template parameter \a CustomNullaryOp is the type of the functor.
@@ -221,21 +213,93 @@ MatrixBase<Derived>::Constant(int size, const Scalar& value)
   * \sa class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Constant(const Scalar& value)
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Constant(const Scalar& value)
 {
   EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, ei_scalar_constant_op<Scalar>(value));
+  return DenseBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_constant_op<Scalar>(value));
 }
 
-/** \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
+/**
+  * \brief Sets a linearly space vector.
+  *
+  * The function generates 'size' equally spaced values in the closed interval [low,high].
+  * This particular version of LinSpaced() uses sequential access, i.e. vector access is
+  * assumed to be a(0), a(1), ..., a(size). This assumption allows for better vectorization
+  * and yields faster code than the random access version.
+  *
+  * When size is set to 1, a vector of length 1 containing 'high' is returned.
+  *
+  * \only_for_vectors
+  *
+  * Example: \include DenseBase_LinSpaced_seq.cpp
+  * Output: \verbinclude DenseBase_LinSpaced_seq.out
+  *
+  * \sa setLinSpaced(Index,const Scalar&,const Scalar&), LinSpaced(Index,Scalar,Scalar), CwiseNullaryOp
+  */
 template<typename Derived>
-bool MatrixBase<Derived>::isApproxToConstant
-(const Scalar& value, RealScalar prec) const
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::SequentialLinSpacedReturnType
+DenseBase<Derived>::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high)
 {
-  for(int j = 0; j < cols(); ++j)
-    for(int i = 0; i < rows(); ++i)
-      if(!ei_isApprox(coeff(i, j), value, prec))
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
+}
+
+/**
+  * \copydoc DenseBase::LinSpaced(Sequential_t, Index, const Scalar&, const Scalar&)
+  * Special version for fixed size types which does not require the size parameter.
+  */
+template<typename Derived>
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::SequentialLinSpacedReturnType
+DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high)
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
+  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,false>(low,high,Derived::SizeAtCompileTime));
+}
+
+/**
+  * \brief Sets a linearly space vector.
+  *
+  * The function generates 'size' equally spaced values in the closed interval [low,high].
+  * When size is set to 1, a vector of length 1 containing 'high' is returned.
+  *
+  * \only_for_vectors
+  *
+  * Example: \include DenseBase_LinSpaced.cpp
+  * Output: \verbinclude DenseBase_LinSpaced.out
+  *
+  * \sa setLinSpaced(Index,const Scalar&,const Scalar&), LinSpaced(Sequential_t,Index,const Scalar&,const Scalar&,Index), CwiseNullaryOp
+  */
+template<typename Derived>
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
+DenseBase<Derived>::LinSpaced(Index size, const Scalar& low, const Scalar& high)
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return DenseBase<Derived>::NullaryExpr(size, internal::linspaced_op<Scalar,true>(low,high,size));
+}
+
+/**
+  * \copydoc DenseBase::LinSpaced(Index, const Scalar&, const Scalar&)
+  * Special version for fixed size types which does not require the size parameter.
+  */
+template<typename Derived>
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessLinSpacedReturnType
+DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
+  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar,true>(low,high,Derived::SizeAtCompileTime));
+}
+
+/** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */
+template<typename Derived>
+bool DenseBase<Derived>::isApproxToConstant
+(const Scalar& val, const RealScalar& prec) const
+{
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < rows(); ++i)
+      if(!internal::isApprox(this->coeff(i, j), val, prec))
         return false;
   return true;
 }
@@ -244,67 +308,104 @@ bool MatrixBase<Derived>::isApproxToConstant
   *
   * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
 template<typename Derived>
-bool MatrixBase<Derived>::isConstant
-(const Scalar& value, RealScalar prec) const
+bool DenseBase<Derived>::isConstant
+(const Scalar& val, const RealScalar& prec) const
 {
-  return isApproxToConstant(value, prec);
+  return isApproxToConstant(val, prec);
 }
 
-/** Alias for setConstant(): sets all coefficients in this expression to \a value.
+/** Alias for setConstant(): sets all coefficients in this expression to \a val.
   *
   * \sa setConstant(), Constant(), class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE void MatrixBase<Derived>::fill(const Scalar& value)
+EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
 {
-  setConstant(value);
+  setConstant(val);
 }
 
 /** Sets all coefficients in this expression to \a value.
   *
-  * \sa fill(), setConstant(int,const Scalar&), setConstant(int,int,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
+  * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setConstant(const Scalar& value)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
 {
-  return derived() = Constant(rows(), cols(), value);
+  return derived() = Constant(rows(), cols(), val);
 }
 
 /** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value.
   *
   * \only_for_vectors
   *
-  * Example: \include Matrix_set_int.cpp
+  * Example: \include Matrix_setConstant_int.cpp
   * Output: \verbinclude Matrix_setConstant_int.out
   *
-  * \sa MatrixBase::setConstant(const Scalar&), setConstant(int,int,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
+  * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setConstant(int size, const Scalar& value)
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
 {
   resize(size);
-  return setConstant(value);
+  return setConstant(val);
 }
 
 /** Resizes to the given size, and sets all coefficients in this expression to the given \a value.
   *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
+  * \param nbRows the new number of rows
+  * \param nbCols the new number of columns
+  * \param val the value to which all coefficients are set
   *
   * Example: \include Matrix_setConstant_int_int.cpp
   * Output: \verbinclude Matrix_setConstant_int_int.out
   *
-  * \sa MatrixBase::setConstant(const Scalar&), setConstant(int,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
+  * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setConstant(int rows, int cols, const Scalar& value)
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setConstant(Index nbRows, Index nbCols, const Scalar& val)
 {
-  resize(rows, cols);
-  return setConstant(value);
+  resize(nbRows, nbCols);
+  return setConstant(val);
 }
 
+/**
+  * \brief Sets a linearly space vector.
+  *
+  * The function generates 'size' equally spaced values in the closed interval [low,high].
+  * When size is set to 1, a vector of length 1 containing 'high' is returned.
+  *
+  * \only_for_vectors
+  *
+  * Example: \include DenseBase_setLinSpaced.cpp
+  * Output: \verbinclude DenseBase_setLinSpaced.out
+  *
+  * \sa CwiseNullaryOp
+  */
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,false>(low,high,newSize));
+}
+
+/**
+  * \brief Sets a linearly space vector.
+  *
+  * The function fill *this with equally spaced values in the closed interval [low,high].
+  * When size is set to 1, a vector of length 1 containing 'high' is returned.
+  *
+  * \only_for_vectors
+  *
+  * \sa setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
+  */
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return setLinSpaced(size(), low, high);
+}
 
 // zero:
 
@@ -317,18 +418,16 @@ Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setConstant(int row
   * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used
   * instead.
   *
-  * \addexample Zero \label How to take get a zero matrix
-  *
   * Example: \include MatrixBase_zero_int_int.cpp
   * Output: \verbinclude MatrixBase_zero_int_int.out
   *
-  * \sa Zero(), Zero(int)
+  * \sa Zero(), Zero(Index)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Zero(int rows, int cols)
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Zero(Index nbRows, Index nbCols)
 {
-  return Constant(rows, cols, Scalar(0));
+  return Constant(nbRows, nbCols, Scalar(0));
 }
 
 /** \returns an expression of a zero vector.
@@ -345,11 +444,11 @@ MatrixBase<Derived>::Zero(int rows, int cols)
   * Example: \include MatrixBase_zero_int.cpp
   * Output: \verbinclude MatrixBase_zero_int.out
   *
-  * \sa Zero(), Zero(int,int)
+  * \sa Zero(), Zero(Index,Index)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Zero(int size)
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Zero(Index size)
 {
   return Constant(size, Scalar(0));
 }
@@ -362,11 +461,11 @@ MatrixBase<Derived>::Zero(int size)
   * Example: \include MatrixBase_zero.cpp
   * Output: \verbinclude MatrixBase_zero.out
   *
-  * \sa Zero(int), Zero(int,int)
+  * \sa Zero(Index), Zero(Index,Index)
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Zero()
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Zero()
 {
   return Constant(Scalar(0));
 }
@@ -380,11 +479,11 @@ MatrixBase<Derived>::Zero()
   * \sa class CwiseNullaryOp, Zero()
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isZero(RealScalar prec) const
+bool DenseBase<Derived>::isZero(const RealScalar& prec) const
 {
-  for(int j = 0; j < cols(); ++j)
-    for(int i = 0; i < rows(); ++i)
-      if(!ei_isMuchSmallerThan(coeff(i, j), static_cast<Scalar>(1), prec))
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < rows(); ++i)
+      if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<Scalar>(1), prec))
         return false;
   return true;
 }
@@ -397,7 +496,7 @@ bool MatrixBase<Derived>::isZero(RealScalar prec) const
   * \sa class CwiseNullaryOp, Zero()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setZero()
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
 {
   return setConstant(Scalar(0));
 }
@@ -409,31 +508,31 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setZero()
   * Example: \include Matrix_setZero_int.cpp
   * Output: \verbinclude Matrix_setZero_int.out
   *
-  * \sa MatrixBase::setZero(), setZero(int,int), class CwiseNullaryOp, MatrixBase::Zero()
+  * \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero()
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setZero(int size)
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setZero(Index newSize)
 {
-  resize(size);
+  resize(newSize);
   return setConstant(Scalar(0));
 }
 
 /** Resizes to the given size, and sets all coefficients in this expression to zero.
   *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
+  * \param nbRows the new number of rows
+  * \param nbCols the new number of columns
   *
   * Example: \include Matrix_setZero_int_int.cpp
   * Output: \verbinclude Matrix_setZero_int_int.out
   *
-  * \sa MatrixBase::setZero(), setZero(int), class CwiseNullaryOp, MatrixBase::Zero()
+  * \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero()
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setZero(int rows, int cols)
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setZero(Index nbRows, Index nbCols)
 {
-  resize(rows, cols);
+  resize(nbRows, nbCols);
   return setConstant(Scalar(0));
 }
 
@@ -441,30 +540,28 @@ Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setZero(int rows, i
 
 /** \returns an expression of a matrix where all coefficients equal one.
   *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
+  * The parameters \a nbRows and \a nbCols are the number of rows and of columns of
   * the returned matrix. Must be compatible with this MatrixBase type.
   *
   * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
   * it is redundant to pass \a rows and \a cols as arguments, so Ones() should be used
   * instead.
   *
-  * \addexample One \label How to get a matrix with all coefficients equal one
-  *
   * Example: \include MatrixBase_ones_int_int.cpp
   * Output: \verbinclude MatrixBase_ones_int_int.out
   *
-  * \sa Ones(), Ones(int), isOnes(), class Ones
+  * \sa Ones(), Ones(Index), isOnes(), class Ones
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Ones(int rows, int cols)
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Ones(Index nbRows, Index nbCols)
 {
-  return Constant(rows, cols, Scalar(1));
+  return Constant(nbRows, nbCols, Scalar(1));
 }
 
 /** \returns an expression of a vector where all coefficients equal one.
   *
-  * The parameter \a size is the size of the returned vector.
+  * The parameter \a newSize is the size of the returned vector.
   * Must be compatible with this MatrixBase type.
   *
   * \only_for_vectors
@@ -476,13 +573,13 @@ MatrixBase<Derived>::Ones(int rows, int cols)
   * Example: \include MatrixBase_ones_int.cpp
   * Output: \verbinclude MatrixBase_ones_int.out
   *
-  * \sa Ones(), Ones(int,int), isOnes(), class Ones
+  * \sa Ones(), Ones(Index,Index), isOnes(), class Ones
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Ones(int size)
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Ones(Index newSize)
 {
-  return Constant(size, Scalar(1));
+  return Constant(newSize, Scalar(1));
 }
 
 /** \returns an expression of a fixed-size matrix or vector where all coefficients equal one.
@@ -493,11 +590,11 @@ MatrixBase<Derived>::Ones(int size)
   * Example: \include MatrixBase_ones.cpp
   * Output: \verbinclude MatrixBase_ones.out
   *
-  * \sa Ones(int), Ones(int,int), isOnes(), class Ones
+  * \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ConstantReturnType
-MatrixBase<Derived>::Ones()
+EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
+DenseBase<Derived>::Ones()
 {
   return Constant(Scalar(1));
 }
@@ -511,8 +608,8 @@ MatrixBase<Derived>::Ones()
   * \sa class CwiseNullaryOp, Ones()
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isOnes
-(RealScalar prec) const
+bool DenseBase<Derived>::isOnes
+(const RealScalar& prec) const
 {
   return isApproxToConstant(Scalar(1), prec);
 }
@@ -525,43 +622,43 @@ bool MatrixBase<Derived>::isOnes
   * \sa class CwiseNullaryOp, Ones()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setOnes()
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
 {
   return setConstant(Scalar(1));
 }
 
-/** Resizes to the given \a size, and sets all coefficients in this expression to one.
+/** Resizes to the given \a newSize, and sets all coefficients in this expression to one.
   *
   * \only_for_vectors
   *
   * Example: \include Matrix_setOnes_int.cpp
   * Output: \verbinclude Matrix_setOnes_int.out
   *
-  * \sa MatrixBase::setOnes(), setOnes(int,int), class CwiseNullaryOp, MatrixBase::Ones()
+  * \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones()
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setOnes(int size)
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setOnes(Index newSize)
 {
-  resize(size);
+  resize(newSize);
   return setConstant(Scalar(1));
 }
 
 /** Resizes to the given size, and sets all coefficients in this expression to one.
   *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
+  * \param nbRows the new number of rows
+  * \param nbCols the new number of columns
   *
   * Example: \include Matrix_setOnes_int_int.cpp
   * Output: \verbinclude Matrix_setOnes_int_int.out
   *
-  * \sa MatrixBase::setOnes(), setOnes(int), class CwiseNullaryOp, MatrixBase::Ones()
+  * \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones()
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setOnes(int rows, int cols)
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+PlainObjectBase<Derived>::setOnes(Index nbRows, Index nbCols)
 {
-  resize(rows, cols);
+  resize(nbRows, nbCols);
   return setConstant(Scalar(1));
 }
 
@@ -569,15 +666,13 @@ Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setOnes(int rows, i
 
 /** \returns an expression of the identity matrix (not necessarily square).
   *
-  * The parameters \a rows and \a cols are the number of rows and of columns of
+  * The parameters \a nbRows and \a nbCols are the number of rows and of columns of
   * the returned matrix. Must be compatible with this MatrixBase type.
   *
   * This variant is meant to be used for dynamic-size matrix types. For fixed-size types,
   * it is redundant to pass \a rows and \a cols as arguments, so Identity() should be used
   * instead.
   *
-  * \addexample Identity \label How to get an identity matrix
-  *
   * Example: \include MatrixBase_identity_int_int.cpp
   * Output: \verbinclude MatrixBase_identity_int_int.out
   *
@@ -585,9 +680,9 @@ Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setOnes(int rows, i
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
-MatrixBase<Derived>::Identity(int rows, int cols)
+MatrixBase<Derived>::Identity(Index nbRows, Index nbCols)
 {
-  return NullaryExpr(rows, cols, ei_scalar_identity_op<Scalar>());
+  return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_identity_op<Scalar>());
 }
 
 /** \returns an expression of the identity matrix (not necessarily square).
@@ -598,14 +693,14 @@ MatrixBase<Derived>::Identity(int rows, int cols)
   * Example: \include MatrixBase_identity.cpp
   * Output: \verbinclude MatrixBase_identity.out
   *
-  * \sa Identity(int,int), setIdentity(), isIdentity()
+  * \sa Identity(Index,Index), setIdentity(), isIdentity()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
 MatrixBase<Derived>::Identity()
 {
   EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
-  return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, ei_scalar_identity_op<Scalar>());
+  return MatrixBase<Derived>::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_identity_op<Scalar>());
 }
 
 /** \returns true if *this is approximately equal to the identity matrix
@@ -615,24 +710,24 @@ MatrixBase<Derived>::Identity()
   * Example: \include MatrixBase_isIdentity.cpp
   * Output: \verbinclude MatrixBase_isIdentity.out
   *
-  * \sa class CwiseNullaryOp, Identity(), Identity(int,int), setIdentity()
+  * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), setIdentity()
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isIdentity
-(RealScalar prec) const
+(const RealScalar& prec) const
 {
-  for(int j = 0; j < cols(); ++j)
+  for(Index j = 0; j < cols(); ++j)
   {
-    for(int i = 0; i < rows(); ++i)
+    for(Index i = 0; i < rows(); ++i)
     {
       if(i == j)
       {
-        if(!ei_isApprox(coeff(i, j), static_cast<Scalar>(1), prec))
+        if(!internal::isApprox(this->coeff(i, j), static_cast<Scalar>(1), prec))
           return false;
       }
       else
       {
-        if(!ei_isMuchSmallerThan(coeff(i, j), static_cast<RealScalar>(1), prec))
+        if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast<RealScalar>(1), prec))
           return false;
       }
     }
@@ -640,8 +735,10 @@ bool MatrixBase<Derived>::isIdentity
   return true;
 }
 
+namespace internal {
+
 template<typename Derived, bool Big = (Derived::SizeAtCompileTime>=16)>
-struct ei_setIdentity_impl
+struct setIdentity_impl
 {
   static EIGEN_STRONG_INLINE Derived& run(Derived& m)
   {
@@ -650,45 +747,47 @@ struct ei_setIdentity_impl
 };
 
 template<typename Derived>
-struct ei_setIdentity_impl<Derived, true>
+struct setIdentity_impl<Derived, true>
 {
+  typedef typename Derived::Index Index;
   static EIGEN_STRONG_INLINE Derived& run(Derived& m)
   {
     m.setZero();
-    const int size = std::min(m.rows(), m.cols());
-    for(int i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
+    const Index size = (std::min)(m.rows(), m.cols());
+    for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
     return m;
   }
 };
 
+} // end namespace internal
+
 /** Writes the identity expression (not necessarily square) into *this.
   *
   * Example: \include MatrixBase_setIdentity.cpp
   * Output: \verbinclude MatrixBase_setIdentity.out
   *
-  * \sa class CwiseNullaryOp, Identity(), Identity(int,int), isIdentity()
+  * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
 {
-  return ei_setIdentity_impl<Derived>::run(derived());
+  return internal::setIdentity_impl<Derived>::run(derived());
 }
 
-/** Resizes to the given size, and writes the identity expression (not necessarily square) into *this.
+/** \brief Resizes to the given size, and writes the identity expression (not necessarily square) into *this.
   *
-  * \param rows the new number of rows
-  * \param cols the new number of columns
+  * \param nbRows the new number of rows
+  * \param nbCols the new number of columns
   *
   * Example: \include Matrix_setIdentity_int_int.cpp
   * Output: \verbinclude Matrix_setIdentity_int_int.out
   *
   * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
-Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setIdentity(int rows, int cols)
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index nbRows, Index nbCols)
 {
-  resize(rows, cols);
+  derived().resize(nbRows, nbCols);
   return setIdentity();
 }
 
@@ -696,13 +795,13 @@ Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setIdentity(int row
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(int size, int i)
+EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return BasisReturnType(SquareMatrixType::Identity(size,size), i);
+  return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i);
 }
 
 /** \returns an expression of the i-th unit (basis) vector.
@@ -711,10 +810,10 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
   *
   * This variant is for fixed-size vector only.
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(int i)
+EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index i)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   return BasisReturnType(SquareMatrixType::Identity(),i);
@@ -724,7 +823,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitX()
@@ -734,7 +833,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitY()
@@ -744,7 +843,7 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitZ()
@@ -754,10 +853,12 @@ EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBa
   *
   * \only_for_vectors
   *
-  * \sa MatrixBase::Unit(int,int), MatrixBase::Unit(int), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
+  * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
 { return Derived::Unit(3); }
 
+} // end namespace Eigen
+
 #endif // EIGEN_CWISE_NULLARY_OP_H

Eigen/src/Core/CwiseUnaryOp.h

@@ -1,229 +1,126 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_UNARY_OP_H
 #define EIGEN_CWISE_UNARY_OP_H
 
+namespace Eigen { 
+
 /** \class CwiseUnaryOp
+  * \ingroup Core_Module
   *
-  * \brief Generic expression of a coefficient-wise unary operator of a matrix or a vector
+  * \brief Generic expression where a coefficient-wise unary operator is applied to an expression
   *
   * \param UnaryOp template functor implementing the operator
-  * \param MatrixType the type of the matrix we are applying the unary operator
+  * \param XprType the type of the expression to which we are applying the unary operator
   *
-  * This class represents an expression of a generic unary operator of a matrix or a vector.
-  * It is the return type of the unary operator-, of a matrix or a vector, and most
-  * of the time this is the only way it is used.
+  * This class represents an expression where a unary operator is applied to an expression.
+  * It is the return type of all operations taking exactly 1 input expression, regardless of the
+  * presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix
+  * is considered unary, because only the right-hand side is an expression, and its
+  * return type is a specialization of CwiseUnaryOp.
+  *
+  * Most of the time, this is the only way that it is used, so you typically don't have to name
+  * CwiseUnaryOp types explicitly.
   *
   * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp
   */
-template<typename UnaryOp, typename MatrixType>
-struct ei_traits<CwiseUnaryOp<UnaryOp, MatrixType> >
- : ei_traits<MatrixType>
+
+namespace internal {
+template<typename UnaryOp, typename XprType>
+struct traits<CwiseUnaryOp<UnaryOp, XprType> >
+ : traits<XprType>
 {
-  typedef typename ei_result_of<
-                     UnaryOp(typename MatrixType::Scalar)
+  typedef typename result_of<
+                     UnaryOp(typename XprType::Scalar)
                    >::type Scalar;
-  typedef typename MatrixType::Nested MatrixTypeNested;
-  typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef typename XprType::Nested XprTypeNested;
+  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
   enum {
-    Flags = (_MatrixTypeNested::Flags & (
+    Flags = _XprTypeNested::Flags & (
       HereditaryBits | LinearAccessBit | AlignedBit
-      | (ei_functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0))),
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost + ei_functor_traits<UnaryOp>::Cost
+      | (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
+    CoeffReadCost = _XprTypeNested::CoeffReadCost + functor_traits<UnaryOp>::Cost
   };
 };
+}
 
-template<typename UnaryOp, typename MatrixType>
-class CwiseUnaryOp : ei_no_assignment_operator,
-  public MatrixBase<CwiseUnaryOp<UnaryOp, MatrixType> >
+template<typename UnaryOp, typename XprType, typename StorageKind>
+class CwiseUnaryOpImpl;
+
+template<typename UnaryOp, typename XprType>
+class CwiseUnaryOp : internal::no_assignment_operator,
+  public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>
 {
   public:
 
+    typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
 
-    inline CwiseUnaryOp(const MatrixType& mat, const UnaryOp& func = UnaryOp())
-      : m_matrix(mat), m_functor(func) {}
+    inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
+      : m_xpr(xpr), m_functor(func) {}
 
-    EIGEN_STRONG_INLINE int rows() const { return m_matrix.rows(); }
-    EIGEN_STRONG_INLINE int cols() const { return m_matrix.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const
-    {
-      return m_functor(m_matrix.coeff(row, col));
-    }
+    /** \returns the functor representing the unary operation */
+    const UnaryOp& functor() const { return m_functor; }
 
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
-    {
-      return m_functor.packetOp(m_matrix.template packet<LoadMode>(row, col));
-    }
+    /** \returns the nested expression */
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    nestedExpression() const { return m_xpr; }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
-    {
-      return m_functor(m_matrix.coeff(index));
-    }
-
-    template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(int index) const
-    {
-      return m_functor.packetOp(m_matrix.template packet<LoadMode>(index));
-    }
+    /** \returns the nested expression */
+    typename internal::remove_all<typename XprType::Nested>::type&
+    nestedExpression() { return m_xpr.const_cast_derived(); }
 
   protected:
-    const typename MatrixType::Nested m_matrix;
+    typename XprType::Nested m_xpr;
     const UnaryOp m_functor;
 };
 
-/** \returns an expression of a custom coefficient-wise unary operator \a func of *this
-  *
-  * The template parameter \a CustomUnaryOp is the type of the functor
-  * of the custom unary operator.
-  *
-  * \addexample CustomCwiseUnaryFunctors \label How to use custom coeff wise unary functors
-  *
-  * Example:
-  * \include class_CwiseUnaryOp.cpp
-  * Output: \verbinclude class_CwiseUnaryOp.out
-  *
-  * \sa class CwiseUnaryOp, class CwiseBinarOp, MatrixBase::operator-, Cwise::abs
-  */
-template<typename Derived>
-template<typename CustomUnaryOp>
-EIGEN_STRONG_INLINE const CwiseUnaryOp<CustomUnaryOp, Derived>
-MatrixBase<Derived>::unaryExpr(const CustomUnaryOp& func) const
+// This is the generic implementation for dense storage.
+// It can be used for any expression types implementing the dense concept.
+template<typename UnaryOp, typename XprType>
+class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
+  : public internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
 {
-  return CwiseUnaryOp<CustomUnaryOp, Derived>(derived(), func);
-}
+  public:
 
-/** \returns an expression of the opposite of \c *this
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE const CwiseUnaryOp<ei_scalar_opposite_op<typename ei_traits<Derived>::Scalar>,Derived>
-MatrixBase<Derived>::operator-() const
-{
-  return derived();
-}
+    typedef CwiseUnaryOp<UnaryOp, XprType> Derived;
+    typedef typename internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
 
-/** \returns an expression of the coefficient-wise absolute value of \c *this
-  *
-  * Example: \include Cwise_abs.cpp
-  * Output: \verbinclude Cwise_abs.out
-  *
-  * \sa abs2()
-  */
-template<typename ExpressionType>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs_op)
-Cwise<ExpressionType>::abs() const
-{
-  return _expression();
-}
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(rowId, colId));
+    }
 
-/** \returns an expression of the coefficient-wise squared absolute value of \c *this
-  *
-  * Example: \include Cwise_abs2.cpp
-  * Output: \verbinclude Cwise_abs2.out
-  *
-  * \sa abs(), square()
-  */
-template<typename ExpressionType>
-EIGEN_STRONG_INLINE const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs2_op)
-Cwise<ExpressionType>::abs2() const
-{
-  return _expression();
-}
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
+    {
+      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(rowId, colId));
+    }
 
-/** \returns an expression of the complex conjugate of \c *this.
-  *
-  * \sa adjoint() */
-template<typename Derived>
-EIGEN_STRONG_INLINE typename MatrixBase<Derived>::ConjugateReturnType
-MatrixBase<Derived>::conjugate() const
-{
-  return ConjugateReturnType(derived());
-}
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(index));
+    }
 
-/** \returns an expression of the real part of \c *this.
-  *
-  * \sa imag() */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::RealReturnType
-MatrixBase<Derived>::real() const { return derived(); }
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
+    {
+      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(index));
+    }
+};
 
-/** \returns an expression of the imaginary part of \c *this.
-  *
-  * \sa real() */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ImagReturnType
-MatrixBase<Derived>::imag() const { return derived(); }
-
-/** \returns an expression of *this with the \a Scalar type casted to
-  * \a NewScalar.
-  *
-  * The template parameter \a NewScalar is the type we are casting the scalars to.
-  *
-  * \sa class CwiseUnaryOp
-  */
-template<typename Derived>
-template<typename NewType>
-EIGEN_STRONG_INLINE const CwiseUnaryOp<ei_scalar_cast_op<typename ei_traits<Derived>::Scalar, NewType>, Derived>
-MatrixBase<Derived>::cast() const
-{
-  return derived();
-}
-
-/** \relates MatrixBase */
-template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::ScalarMultipleReturnType
-MatrixBase<Derived>::operator*(const Scalar& scalar) const
-{
-  return CwiseUnaryOp<ei_scalar_multiple_op<Scalar>, Derived>
-    (derived(), ei_scalar_multiple_op<Scalar>(scalar));
-}
-
-/** \relates MatrixBase */
-template<typename Derived>
-EIGEN_STRONG_INLINE const CwiseUnaryOp<ei_scalar_quotient1_op<typename ei_traits<Derived>::Scalar>, Derived>
-MatrixBase<Derived>::operator/(const Scalar& scalar) const
-{
-  return CwiseUnaryOp<ei_scalar_quotient1_op<Scalar>, Derived>
-    (derived(), ei_scalar_quotient1_op<Scalar>(scalar));
-}
-
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-MatrixBase<Derived>::operator*=(const Scalar& other)
-{
-  return *this = *this * other;
-}
-
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-MatrixBase<Derived>::operator/=(const Scalar& other)
-{
-  return *this = *this / other;
-}
+} // end namespace Eigen
 
 #endif // EIGEN_CWISE_UNARY_OP_H

Eigen/src/Core/CwiseUnaryView.h

@@ -0,0 +1,139 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CWISE_UNARY_VIEW_H
+#define EIGEN_CWISE_UNARY_VIEW_H
+
+namespace Eigen {
+
+/** \class CwiseUnaryView
+  * \ingroup Core_Module
+  *
+  * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
+  *
+  * \param ViewOp template functor implementing the view
+  * \param MatrixType the type of the matrix we are applying the unary operator
+  *
+  * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector.
+  * It is the return type of real() and imag(), and most of the time this is the only way it is used.
+  *
+  * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
+  */
+
+namespace internal {
+template<typename ViewOp, typename MatrixType>
+struct traits<CwiseUnaryView<ViewOp, MatrixType> >
+ : traits<MatrixType>
+{
+  typedef typename result_of<
+                     ViewOp(typename traits<MatrixType>::Scalar)
+                   >::type Scalar;
+  typedef typename MatrixType::Nested MatrixTypeNested;
+  typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
+  enum {
+    Flags = (traits<_MatrixTypeNested>::Flags & (HereditaryBits | LvalueBit | LinearAccessBit | DirectAccessBit)),
+    CoeffReadCost = traits<_MatrixTypeNested>::CoeffReadCost + functor_traits<ViewOp>::Cost,
+    MatrixTypeInnerStride =  inner_stride_at_compile_time<MatrixType>::ret,
+    // need to cast the sizeof's from size_t to int explicitly, otherwise:
+    // "error: no integral type can represent all of the enumerator values
+    InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic
+                             ? int(Dynamic)
+                             : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)),
+    OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret == Dynamic
+                             ? int(Dynamic)
+                             : outer_stride_at_compile_time<MatrixType>::ret * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar))
+  };
+};
+}
+
+template<typename ViewOp, typename MatrixType, typename StorageKind>
+class CwiseUnaryViewImpl;
+
+template<typename ViewOp, typename MatrixType>
+class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
+{
+  public:
+
+    typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
+
+    inline CwiseUnaryView(const MatrixType& mat, const ViewOp& func = ViewOp())
+      : m_matrix(mat), m_functor(func) {}
+
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
+
+    EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
+
+    /** \returns the functor representing unary operation */
+    const ViewOp& functor() const { return m_functor; }
+
+    /** \returns the nested expression */
+    const typename internal::remove_all<typename MatrixType::Nested>::type&
+    nestedExpression() const { return m_matrix; }
+
+    /** \returns the nested expression */
+    typename internal::remove_all<typename MatrixType::Nested>::type&
+    nestedExpression() { return m_matrix.const_cast_derived(); }
+
+  protected:
+    // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC
+    typename internal::nested<MatrixType>::type m_matrix;
+    ViewOp m_functor;
+};
+
+template<typename ViewOp, typename MatrixType>
+class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
+  : public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
+{
+  public:
+
+    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
+    typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
+
+    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
+    
+    inline Scalar* data() { return &coeffRef(0); }
+    inline const Scalar* data() const { return &coeff(0); }
+
+    inline Index innerStride() const
+    {
+      return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
+    }
+
+    inline Index outerStride() const
+    {
+      return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
+    }
+
+    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(row, col));
+    }
+
+    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(index));
+    }
+
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
+    {
+      return derived().functor()(const_cast_derived().nestedExpression().coeffRef(row, col));
+    }
+
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
+    {
+      return derived().functor()(const_cast_derived().nestedExpression().coeffRef(index));
+    }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CWISE_UNARY_VIEW_H

Eigen/src/Core/DenseBase.h

@@ -0,0 +1,525 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_DENSEBASE_H
+#define EIGEN_DENSEBASE_H
+
+namespace Eigen {
+
+namespace internal {
+  
+// The index type defined by EIGEN_DEFAULT_DENSE_INDEX_TYPE must be a signed type.
+// This dummy function simply aims at checking that at compile time.
+static inline void check_DenseIndex_is_signed() {
+  EIGEN_STATIC_ASSERT(NumTraits<DenseIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); 
+}
+
+} // end namespace internal
+  
+/** \class DenseBase
+  * \ingroup Core_Module
+  *
+  * \brief Base class for all dense matrices, vectors, and arrays
+  *
+  * This class is the base that is inherited by all dense objects (matrix, vector, arrays,
+  * and related expression types). The common Eigen API for dense objects is contained in this class.
+  *
+  * \tparam Derived is the derived type, e.g., a matrix type or an expression.
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN.
+  *
+  * \sa \ref TopicClassHierarchy
+  */
+template<typename Derived> class DenseBase
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+  : public internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
+                                     typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>
+#else
+  : public DenseCoeffsBase<Derived>
+#endif // not EIGEN_PARSED_BY_DOXYGEN
+{
+  public:
+    using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
+                typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
+
+    class InnerIterator;
+
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+
+    /** \brief The type of indices 
+      * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
+      * \sa \ref TopicPreprocessorDirectives.
+      */
+    typedef typename internal::traits<Derived>::Index Index; 
+
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    typedef DenseCoeffsBase<Derived> Base;
+    using Base::derived;
+    using Base::const_cast_derived;
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::rowIndexByOuterInner;
+    using Base::colIndexByOuterInner;
+    using Base::coeff;
+    using Base::coeffByOuterInner;
+    using Base::packet;
+    using Base::packetByOuterInner;
+    using Base::writePacket;
+    using Base::writePacketByOuterInner;
+    using Base::coeffRef;
+    using Base::coeffRefByOuterInner;
+    using Base::copyCoeff;
+    using Base::copyCoeffByOuterInner;
+    using Base::copyPacket;
+    using Base::copyPacketByOuterInner;
+    using Base::operator();
+    using Base::operator[];
+    using Base::x;
+    using Base::y;
+    using Base::z;
+    using Base::w;
+    using Base::stride;
+    using Base::innerStride;
+    using Base::outerStride;
+    using Base::rowStride;
+    using Base::colStride;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+
+    enum {
+
+      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
+        /**< The number of rows at compile-time. This is just a copy of the value provided
+          * by the \a Derived type. If a value is not known at compile-time,
+          * it is set to the \a Dynamic constant.
+          * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */
+
+      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
+        /**< The number of columns at compile-time. This is just a copy of the value provided
+          * by the \a Derived type. If a value is not known at compile-time,
+          * it is set to the \a Dynamic constant.
+          * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */
+
+
+      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
+                                                   internal::traits<Derived>::ColsAtCompileTime>::ret),
+        /**< This is equal to the number of coefficients, i.e. the number of
+          * rows times the number of columns, or to \a Dynamic if this is not
+          * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
+
+      MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
+        /**< This value is equal to the maximum possible number of rows that this expression
+          * might have. If this expression might have an arbitrarily high number of rows,
+          * this value is set to \a Dynamic.
+          *
+          * This value is useful to know when evaluating an expression, in order to determine
+          * whether it is possible to avoid doing a dynamic memory allocation.
+          *
+          * \sa RowsAtCompileTime, MaxColsAtCompileTime, MaxSizeAtCompileTime
+          */
+
+      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
+        /**< This value is equal to the maximum possible number of columns that this expression
+          * might have. If this expression might have an arbitrarily high number of columns,
+          * this value is set to \a Dynamic.
+          *
+          * This value is useful to know when evaluating an expression, in order to determine
+          * whether it is possible to avoid doing a dynamic memory allocation.
+          *
+          * \sa ColsAtCompileTime, MaxRowsAtCompileTime, MaxSizeAtCompileTime
+          */
+
+      MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
+                                                      internal::traits<Derived>::MaxColsAtCompileTime>::ret),
+        /**< This value is equal to the maximum possible number of coefficients that this expression
+          * might have. If this expression might have an arbitrarily high number of coefficients,
+          * this value is set to \a Dynamic.
+          *
+          * This value is useful to know when evaluating an expression, in order to determine
+          * whether it is possible to avoid doing a dynamic memory allocation.
+          *
+          * \sa SizeAtCompileTime, MaxRowsAtCompileTime, MaxColsAtCompileTime
+          */
+
+      IsVectorAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime == 1
+                           || internal::traits<Derived>::MaxColsAtCompileTime == 1,
+        /**< This is set to true if either the number of rows or the number of
+          * columns is known at compile-time to be equal to 1. Indeed, in that case,
+          * we are dealing with a column-vector (if there is only one column) or with
+          * a row-vector (if there is only one row). */
+
+      Flags = internal::traits<Derived>::Flags,
+        /**< This stores expression \ref flags flags which may or may not be inherited by new expressions
+          * constructed from this one. See the \ref flags "list of flags".
+          */
+
+      IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */
+
+      InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
+                             : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
+
+      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
+        /**< This is a rough measure of how expensive it is to read one coefficient from
+          * this expression.
+          */
+
+      InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
+      OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
+    };
+
+    enum { ThisConstantIsPrivateInPlainObjectBase };
+
+    /** \returns the number of nonzero coefficients which is in practice the number
+      * of stored coefficients. */
+    inline Index nonZeros() const { return size(); }
+    /** \returns true if either the number of rows or the number of columns is equal to 1.
+      * In other words, this function returns
+      * \code rows()==1 || cols()==1 \endcode
+      * \sa rows(), cols(), IsVectorAtCompileTime. */
+
+    /** \returns the outer size.
+      *
+      * \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension
+      * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of columns for a
+      * column-major matrix, and the number of rows for a row-major matrix. */
+    Index outerSize() const
+    {
+      return IsVectorAtCompileTime ? 1
+           : int(IsRowMajor) ? this->rows() : this->cols();
+    }
+
+    /** \returns the inner size.
+      *
+      * \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension
+      * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of rows for a 
+      * column-major matrix, and the number of columns for a row-major matrix. */
+    Index innerSize() const
+    {
+      return IsVectorAtCompileTime ? this->size()
+           : int(IsRowMajor) ? this->cols() : this->rows();
+    }
+
+    /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
+      * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
+      * nothing else.
+      */
+    void resize(Index newSize)
+    {
+      EIGEN_ONLY_USED_FOR_DEBUG(newSize);
+      eigen_assert(newSize == this->size()
+                && "DenseBase::resize() does not actually allow to resize.");
+    }
+    /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
+      * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
+      * nothing else.
+      */
+    void resize(Index nbRows, Index nbCols)
+    {
+      EIGEN_ONLY_USED_FOR_DEBUG(nbRows);
+      EIGEN_ONLY_USED_FOR_DEBUG(nbCols);
+      eigen_assert(nbRows == this->rows() && nbCols == this->cols()
+                && "DenseBase::resize() does not actually allow to resize.");
+    }
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+
+    /** \internal Represents a matrix with all coefficients equal to one another*/
+    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
+    /** \internal Represents a vector with linearly spaced coefficients that allows sequential access only. */
+    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,false>,Derived> SequentialLinSpacedReturnType;
+    /** \internal Represents a vector with linearly spaced coefficients that allows random access. */
+    typedef CwiseNullaryOp<internal::linspaced_op<Scalar,true>,Derived> RandomAccessLinSpacedReturnType;
+    /** \internal the return type of MatrixBase::eigenvalues() */
+    typedef Matrix<typename NumTraits<typename internal::traits<Derived>::Scalar>::Real, internal::traits<Derived>::ColsAtCompileTime, 1> EigenvaluesReturnType;
+
+#endif // not EIGEN_PARSED_BY_DOXYGEN
+
+    /** Copies \a other into *this. \returns a reference to *this. */
+    template<typename OtherDerived>
+    Derived& operator=(const DenseBase<OtherDerived>& other);
+
+    /** Special case of the template operator=, in order to prevent the compiler
+      * from generating a default operator= (issue hit with g++ 4.1)
+      */
+    Derived& operator=(const DenseBase& other);
+
+    template<typename OtherDerived>
+    Derived& operator=(const EigenBase<OtherDerived> &other);
+
+    template<typename OtherDerived>
+    Derived& operator+=(const EigenBase<OtherDerived> &other);
+
+    template<typename OtherDerived>
+    Derived& operator-=(const EigenBase<OtherDerived> &other);
+
+    template<typename OtherDerived>
+    Derived& operator=(const ReturnByValue<OtherDerived>& func);
+
+    /** \internal Copies \a other into *this without evaluating other. \returns a reference to *this. */
+    template<typename OtherDerived>
+    Derived& lazyAssign(const DenseBase<OtherDerived>& other);
+
+    /** \internal Evaluates \a other into *this. \returns a reference to *this. */
+    template<typename OtherDerived>
+    Derived& lazyAssign(const ReturnByValue<OtherDerived>& other);
+
+    CommaInitializer<Derived> operator<< (const Scalar& s);
+
+    template<unsigned int Added,unsigned int Removed>
+    const Flagged<Derived, Added, Removed> flagged() const;
+
+    template<typename OtherDerived>
+    CommaInitializer<Derived> operator<< (const DenseBase<OtherDerived>& other);
+
+    Eigen::Transpose<Derived> transpose();
+	typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
+    ConstTransposeReturnType transpose() const;
+    void transposeInPlace();
+#ifndef EIGEN_NO_DEBUG
+  protected:
+    template<typename OtherDerived>
+    void checkTransposeAliasing(const OtherDerived& other) const;
+  public:
+#endif
+
+
+    static const ConstantReturnType
+    Constant(Index rows, Index cols, const Scalar& value);
+    static const ConstantReturnType
+    Constant(Index size, const Scalar& value);
+    static const ConstantReturnType
+    Constant(const Scalar& value);
+
+    static const SequentialLinSpacedReturnType
+    LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high);
+    static const RandomAccessLinSpacedReturnType
+    LinSpaced(Index size, const Scalar& low, const Scalar& high);
+    static const SequentialLinSpacedReturnType
+    LinSpaced(Sequential_t, const Scalar& low, const Scalar& high);
+    static const RandomAccessLinSpacedReturnType
+    LinSpaced(const Scalar& low, const Scalar& high);
+
+    template<typename CustomNullaryOp>
+    static const CwiseNullaryOp<CustomNullaryOp, Derived>
+    NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func);
+    template<typename CustomNullaryOp>
+    static const CwiseNullaryOp<CustomNullaryOp, Derived>
+    NullaryExpr(Index size, const CustomNullaryOp& func);
+    template<typename CustomNullaryOp>
+    static const CwiseNullaryOp<CustomNullaryOp, Derived>
+    NullaryExpr(const CustomNullaryOp& func);
+
+    static const ConstantReturnType Zero(Index rows, Index cols);
+    static const ConstantReturnType Zero(Index size);
+    static const ConstantReturnType Zero();
+    static const ConstantReturnType Ones(Index rows, Index cols);
+    static const ConstantReturnType Ones(Index size);
+    static const ConstantReturnType Ones();
+
+    void fill(const Scalar& value);
+    Derived& setConstant(const Scalar& value);
+    Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
+    Derived& setLinSpaced(const Scalar& low, const Scalar& high);
+    Derived& setZero();
+    Derived& setOnes();
+    Derived& setRandom();
+
+    template<typename OtherDerived>
+    bool isApprox(const DenseBase<OtherDerived>& other,
+                  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isMuchSmallerThan(const RealScalar& other,
+                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    template<typename OtherDerived>
+    bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
+                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+
+    bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    
+    inline bool hasNaN() const;
+    inline bool allFinite() const;
+
+    inline Derived& operator*=(const Scalar& other);
+    inline Derived& operator/=(const Scalar& other);
+
+    typedef typename internal::add_const_on_value_type<typename internal::eval<Derived>::type>::type EvalReturnType;
+    /** \returns the matrix or vector obtained by evaluating this expression.
+      *
+      * Notice that in the case of a plain matrix or vector (not an expression) this function just returns
+      * a const reference, in order to avoid a useless copy.
+      */
+    EIGEN_STRONG_INLINE EvalReturnType eval() const
+    {
+      // Even though MSVC does not honor strong inlining when the return type
+      // is a dynamic matrix, we desperately need strong inlining for fixed
+      // size types on MSVC.
+      return typename internal::eval<Derived>::type(derived());
+    }
+
+    /** swaps *this with the expression \a other.
+      *
+      */
+    template<typename OtherDerived>
+    void swap(const DenseBase<OtherDerived>& other,
+              int = OtherDerived::ThisConstantIsPrivateInPlainObjectBase)
+    {
+      SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
+    }
+
+    /** swaps *this with the matrix or array \a other.
+      *
+      */
+    template<typename OtherDerived>
+    void swap(PlainObjectBase<OtherDerived>& other)
+    {
+      SwapWrapper<Derived>(derived()).lazyAssign(other.derived());
+    }
+
+
+    inline const NestByValue<Derived> nestByValue() const;
+    inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
+    inline ForceAlignedAccess<Derived> forceAlignedAccess();
+    template<bool Enable> inline const typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf() const;
+    template<bool Enable> inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
+
+    Scalar sum() const;
+    Scalar mean() const;
+    Scalar trace() const;
+
+    Scalar prod() const;
+
+    typename internal::traits<Derived>::Scalar minCoeff() const;
+    typename internal::traits<Derived>::Scalar maxCoeff() const;
+
+    template<typename IndexType>
+    typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const;
+    template<typename IndexType>
+    typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const;
+    template<typename IndexType>
+    typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const;
+    template<typename IndexType>
+    typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const;
+
+    template<typename BinaryOp>
+    typename internal::result_of<BinaryOp(typename internal::traits<Derived>::Scalar)>::type
+    redux(const BinaryOp& func) const;
+
+    template<typename Visitor>
+    void visit(Visitor& func) const;
+
+    inline const WithFormat<Derived> format(const IOFormat& fmt) const;
+
+    /** \returns the unique coefficient of a 1x1 expression */
+    CoeffReturnType value() const
+    {
+      EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
+      eigen_assert(this->rows() == 1 && this->cols() == 1);
+      return derived().coeff(0,0);
+    }
+
+    bool all(void) const;
+    bool any(void) const;
+    Index count() const;
+
+    typedef VectorwiseOp<Derived, Horizontal> RowwiseReturnType;
+    typedef const VectorwiseOp<const Derived, Horizontal> ConstRowwiseReturnType;
+    typedef VectorwiseOp<Derived, Vertical> ColwiseReturnType;
+    typedef const VectorwiseOp<const Derived, Vertical> ConstColwiseReturnType;
+
+    ConstRowwiseReturnType rowwise() const;
+    RowwiseReturnType rowwise();
+    ConstColwiseReturnType colwise() const;
+    ColwiseReturnType colwise();
+
+    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index rows, Index cols);
+    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(Index size);
+    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random();
+
+    template<typename ThenDerived,typename ElseDerived>
+    const Select<Derived,ThenDerived,ElseDerived>
+    select(const DenseBase<ThenDerived>& thenMatrix,
+           const DenseBase<ElseDerived>& elseMatrix) const;
+
+    template<typename ThenDerived>
+    inline const Select<Derived,ThenDerived, typename ThenDerived::ConstantReturnType>
+    select(const DenseBase<ThenDerived>& thenMatrix, const typename ThenDerived::Scalar& elseScalar) const;
+
+    template<typename ElseDerived>
+    inline const Select<Derived, typename ElseDerived::ConstantReturnType, ElseDerived >
+    select(const typename ElseDerived::Scalar& thenScalar, const DenseBase<ElseDerived>& elseMatrix) const;
+
+    template<int p> RealScalar lpNorm() const;
+
+    template<int RowFactor, int ColFactor>
+    inline const Replicate<Derived,RowFactor,ColFactor> replicate() const;
+    
+    typedef Replicate<Derived,Dynamic,Dynamic> ReplicateReturnType;
+    inline const ReplicateReturnType replicate(Index rowFacor,Index colFactor) const;
+
+    typedef Reverse<Derived, BothDirections> ReverseReturnType;
+    typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
+    ReverseReturnType reverse();
+    ConstReverseReturnType reverse() const;
+    void reverseInPlace();
+
+#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase
+#   include "../plugins/BlockMethods.h"
+#   ifdef EIGEN_DENSEBASE_PLUGIN
+#     include EIGEN_DENSEBASE_PLUGIN
+#   endif
+#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
+
+#ifdef EIGEN2_SUPPORT
+
+    Block<Derived> corner(CornerType type, Index cRows, Index cCols);
+    const Block<Derived> corner(CornerType type, Index cRows, Index cCols) const;
+    template<int CRows, int CCols>
+    Block<Derived, CRows, CCols> corner(CornerType type);
+    template<int CRows, int CCols>
+    const Block<Derived, CRows, CCols> corner(CornerType type) const;
+
+#endif // EIGEN2_SUPPORT
+
+
+    // disable the use of evalTo for dense objects with a nice compilation error
+    template<typename Dest> inline void evalTo(Dest& ) const
+    {
+      EIGEN_STATIC_ASSERT((internal::is_same<Dest,void>::value),THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS);
+    }
+
+  protected:
+    /** Default constructor. Do nothing. */
+    DenseBase()
+    {
+      /* Just checks for self-consistency of the flags.
+       * Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down
+       */
+#ifdef EIGEN_INTERNAL_DEBUGGING
+      EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, int(IsRowMajor))
+                        && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, int(!IsRowMajor))),
+                          INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION)
+#endif
+    }
+
+  private:
+    explicit DenseBase(int);
+    DenseBase(int,int);
+    template<typename OtherDerived> explicit DenseBase(const DenseBase<OtherDerived>&);
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_DENSEBASE_H

Eigen/src/Core/DenseCoeffsBase.h

@@ -0,0 +1,754 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_DENSECOEFFSBASE_H
+#define EIGEN_DENSECOEFFSBASE_H
+
+namespace Eigen {
+
+namespace internal {
+template<typename T> struct add_const_on_value_type_if_arithmetic
+{
+  typedef typename conditional<is_arithmetic<T>::value, T, typename add_const_on_value_type<T>::type>::type type;
+};
+}
+
+/** \brief Base class providing read-only coefficient access to matrices and arrays.
+  * \ingroup Core_Module
+  * \tparam Derived Type of the derived class
+  * \tparam #ReadOnlyAccessors Constant indicating read-only access
+  *
+  * This class defines the \c operator() \c const function and friends, which can be used to read specific
+  * entries of a matrix or array.
+  * 
+  * \sa DenseCoeffsBase<Derived, WriteAccessors>, DenseCoeffsBase<Derived, DirectAccessors>,
+  *     \ref TopicClassHierarchy
+  */
+template<typename Derived>
+class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
+{
+  public:
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+
+    // Explanation for this CoeffReturnType typedef.
+    // - This is the return type of the coeff() method.
+    // - The LvalueBit means exactly that we can offer a coeffRef() method, which means exactly that we can get references
+    // to coeffs, which means exactly that we can have coeff() return a const reference (as opposed to returning a value).
+    // - The is_artihmetic check is required since "const int", "const double", etc. will cause warnings on some systems
+    // while the declaration of "const T", where T is a non arithmetic type does not. Always returning "const Scalar&" is
+    // not possible, since the underlying expressions might not offer a valid address the reference could be referring to.
+    typedef typename internal::conditional<bool(internal::traits<Derived>::Flags&LvalueBit),
+                         const Scalar&,
+                         typename internal::conditional<internal::is_arithmetic<Scalar>::value, Scalar, const Scalar>::type
+                     >::type CoeffReturnType;
+
+    typedef typename internal::add_const_on_value_type_if_arithmetic<
+                         typename internal::packet_traits<Scalar>::type
+                     >::type PacketReturnType;
+
+    typedef EigenBase<Derived> Base;
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::derived;
+
+    EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const
+    {
+      return int(Derived::RowsAtCompileTime) == 1 ? 0
+          : int(Derived::ColsAtCompileTime) == 1 ? inner
+          : int(Derived::Flags)&RowMajorBit ? outer
+          : inner;
+    }
+
+    EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const
+    {
+      return int(Derived::ColsAtCompileTime) == 1 ? 0
+          : int(Derived::RowsAtCompileTime) == 1 ? inner
+          : int(Derived::Flags)&RowMajorBit ? inner
+          : outer;
+    }
+
+    /** Short version: don't use this function, use
+      * \link operator()(Index,Index) const \endlink instead.
+      *
+      * Long version: this function is similar to
+      * \link operator()(Index,Index) const \endlink, but without the assertion.
+      * Use this for limiting the performance cost of debugging code when doing
+      * repeated coefficient access. Only use this when it is guaranteed that the
+      * parameters \a row and \a col are in range.
+      *
+      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
+      * function equivalent to \link operator()(Index,Index) const \endlink.
+      *
+      * \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const
+      */
+    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
+    {
+      eigen_internal_assert(row >= 0 && row < rows()
+                        && col >= 0 && col < cols());
+      return derived().coeff(row, col);
+    }
+
+    EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const
+    {
+      return coeff(rowIndexByOuterInner(outer, inner),
+                   colIndexByOuterInner(outer, inner));
+    }
+
+    /** \returns the coefficient at given the given row and column.
+      *
+      * \sa operator()(Index,Index), operator[](Index)
+      */
+    EIGEN_STRONG_INLINE CoeffReturnType operator()(Index row, Index col) const
+    {
+      eigen_assert(row >= 0 && row < rows()
+          && col >= 0 && col < cols());
+      return derived().coeff(row, col);
+    }
+
+    /** Short version: don't use this function, use
+      * \link operator[](Index) const \endlink instead.
+      *
+      * Long version: this function is similar to
+      * \link operator[](Index) const \endlink, but without the assertion.
+      * Use this for limiting the performance cost of debugging code when doing
+      * repeated coefficient access. Only use this when it is guaranteed that the
+      * parameter \a index is in range.
+      *
+      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
+      * function equivalent to \link operator[](Index) const \endlink.
+      *
+      * \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const
+      */
+
+    EIGEN_STRONG_INLINE CoeffReturnType
+    coeff(Index index) const
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return derived().coeff(index);
+    }
+
+
+    /** \returns the coefficient at given index.
+      *
+      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
+      *
+      * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
+      * z() const, w() const
+      */
+
+    EIGEN_STRONG_INLINE CoeffReturnType
+    operator[](Index index) const
+    {
+      #ifndef EIGEN2_SUPPORT
+      EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
+                          THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
+      #endif
+      eigen_assert(index >= 0 && index < size());
+      return derived().coeff(index);
+    }
+
+    /** \returns the coefficient at given index.
+      *
+      * This is synonymous to operator[](Index) const.
+      *
+      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
+      *
+      * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const,
+      * z() const, w() const
+      */
+
+    EIGEN_STRONG_INLINE CoeffReturnType
+    operator()(Index index) const
+    {
+      eigen_assert(index >= 0 && index < size());
+      return derived().coeff(index);
+    }
+
+    /** equivalent to operator[](0).  */
+
+    EIGEN_STRONG_INLINE CoeffReturnType
+    x() const { return (*this)[0]; }
+
+    /** equivalent to operator[](1).  */
+
+    EIGEN_STRONG_INLINE CoeffReturnType
+    y() const { return (*this)[1]; }
+
+    /** equivalent to operator[](2).  */
+
+    EIGEN_STRONG_INLINE CoeffReturnType
+    z() const { return (*this)[2]; }
+
+    /** equivalent to operator[](3).  */
+
+    EIGEN_STRONG_INLINE CoeffReturnType
+    w() const { return (*this)[3]; }
+
+    /** \internal
+      * \returns the packet of coefficients starting at the given row and column. It is your responsibility
+      * to ensure that a packet really starts there. This method is only available on expressions having the
+      * PacketAccessBit.
+      *
+      * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
+      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
+      * starting at an address which is a multiple of the packet size.
+      */
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const
+    {
+      eigen_internal_assert(row >= 0 && row < rows()
+                      && col >= 0 && col < cols());
+      return derived().template packet<LoadMode>(row,col);
+    }
+
+
+    /** \internal */
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketReturnType packetByOuterInner(Index outer, Index inner) const
+    {
+      return packet<LoadMode>(rowIndexByOuterInner(outer, inner),
+                              colIndexByOuterInner(outer, inner));
+    }
+
+    /** \internal
+      * \returns the packet of coefficients starting at the given index. It is your responsibility
+      * to ensure that a packet really starts there. This method is only available on expressions having the
+      * PacketAccessBit and the LinearAccessBit.
+      *
+      * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
+      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
+      * starting at an address which is a multiple of the packet size.
+      */
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return derived().template packet<LoadMode>(index);
+    }
+
+  protected:
+    // explanation: DenseBase is doing "using ..." on the methods from DenseCoeffsBase.
+    // But some methods are only available in the DirectAccess case.
+    // So we add dummy methods here with these names, so that "using... " doesn't fail.
+    // It's not private so that the child class DenseBase can access them, and it's not public
+    // either since it's an implementation detail, so has to be protected.
+    void coeffRef();
+    void coeffRefByOuterInner();
+    void writePacket();
+    void writePacketByOuterInner();
+    void copyCoeff();
+    void copyCoeffByOuterInner();
+    void copyPacket();
+    void copyPacketByOuterInner();
+    void stride();
+    void innerStride();
+    void outerStride();
+    void rowStride();
+    void colStride();
+};
+
+/** \brief Base class providing read/write coefficient access to matrices and arrays.
+  * \ingroup Core_Module
+  * \tparam Derived Type of the derived class
+  * \tparam #WriteAccessors Constant indicating read/write access
+  *
+  * This class defines the non-const \c operator() function and friends, which can be used to write specific
+  * entries of a matrix or array. This class inherits DenseCoeffsBase<Derived, ReadOnlyAccessors> which
+  * defines the const variant for reading specific entries.
+  * 
+  * \sa DenseCoeffsBase<Derived, DirectAccessors>, \ref TopicClassHierarchy
+  */
+template<typename Derived>
+class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
+{
+  public:
+
+    typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
+
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    using Base::coeff;
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::derived;
+    using Base::rowIndexByOuterInner;
+    using Base::colIndexByOuterInner;
+    using Base::operator[];
+    using Base::operator();
+    using Base::x;
+    using Base::y;
+    using Base::z;
+    using Base::w;
+
+    /** Short version: don't use this function, use
+      * \link operator()(Index,Index) \endlink instead.
+      *
+      * Long version: this function is similar to
+      * \link operator()(Index,Index) \endlink, but without the assertion.
+      * Use this for limiting the performance cost of debugging code when doing
+      * repeated coefficient access. Only use this when it is guaranteed that the
+      * parameters \a row and \a col are in range.
+      *
+      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
+      * function equivalent to \link operator()(Index,Index) \endlink.
+      *
+      * \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index)
+      */
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
+    {
+      eigen_internal_assert(row >= 0 && row < rows()
+                        && col >= 0 && col < cols());
+      return derived().coeffRef(row, col);
+    }
+
+    EIGEN_STRONG_INLINE Scalar&
+    coeffRefByOuterInner(Index outer, Index inner)
+    {
+      return coeffRef(rowIndexByOuterInner(outer, inner),
+                      colIndexByOuterInner(outer, inner));
+    }
+
+    /** \returns a reference to the coefficient at given the given row and column.
+      *
+      * \sa operator[](Index)
+      */
+
+    EIGEN_STRONG_INLINE Scalar&
+    operator()(Index row, Index col)
+    {
+      eigen_assert(row >= 0 && row < rows()
+          && col >= 0 && col < cols());
+      return derived().coeffRef(row, col);
+    }
+
+
+    /** Short version: don't use this function, use
+      * \link operator[](Index) \endlink instead.
+      *
+      * Long version: this function is similar to
+      * \link operator[](Index) \endlink, but without the assertion.
+      * Use this for limiting the performance cost of debugging code when doing
+      * repeated coefficient access. Only use this when it is guaranteed that the
+      * parameters \a row and \a col are in range.
+      *
+      * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this
+      * function equivalent to \link operator[](Index) \endlink.
+      *
+      * \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index)
+      */
+
+    EIGEN_STRONG_INLINE Scalar&
+    coeffRef(Index index)
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      return derived().coeffRef(index);
+    }
+
+    /** \returns a reference to the coefficient at given index.
+      *
+      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
+      *
+      * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
+      */
+
+    EIGEN_STRONG_INLINE Scalar&
+    operator[](Index index)
+    {
+      #ifndef EIGEN2_SUPPORT
+      EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime,
+                          THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD)
+      #endif
+      eigen_assert(index >= 0 && index < size());
+      return derived().coeffRef(index);
+    }
+
+    /** \returns a reference to the coefficient at given index.
+      *
+      * This is synonymous to operator[](Index).
+      *
+      * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit.
+      *
+      * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w()
+      */
+
+    EIGEN_STRONG_INLINE Scalar&
+    operator()(Index index)
+    {
+      eigen_assert(index >= 0 && index < size());
+      return derived().coeffRef(index);
+    }
+
+    /** equivalent to operator[](0).  */
+
+    EIGEN_STRONG_INLINE Scalar&
+    x() { return (*this)[0]; }
+
+    /** equivalent to operator[](1).  */
+
+    EIGEN_STRONG_INLINE Scalar&
+    y() { return (*this)[1]; }
+
+    /** equivalent to operator[](2).  */
+
+    EIGEN_STRONG_INLINE Scalar&
+    z() { return (*this)[2]; }
+
+    /** equivalent to operator[](3).  */
+
+    EIGEN_STRONG_INLINE Scalar&
+    w() { return (*this)[3]; }
+
+    /** \internal
+      * Stores the given packet of coefficients, at the given row and column of this expression. It is your responsibility
+      * to ensure that a packet really starts there. This method is only available on expressions having the
+      * PacketAccessBit.
+      *
+      * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select
+      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
+      * starting at an address which is a multiple of the packet size.
+      */
+
+    template<int StoreMode>
+    EIGEN_STRONG_INLINE void writePacket
+    (Index row, Index col, const typename internal::packet_traits<Scalar>::type& val)
+    {
+      eigen_internal_assert(row >= 0 && row < rows()
+                        && col >= 0 && col < cols());
+      derived().template writePacket<StoreMode>(row,col,val);
+    }
+
+
+    /** \internal */
+    template<int StoreMode>
+    EIGEN_STRONG_INLINE void writePacketByOuterInner
+    (Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& val)
+    {
+      writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
+                            colIndexByOuterInner(outer, inner),
+                            val);
+    }
+
+    /** \internal
+      * Stores the given packet of coefficients, at the given index in this expression. It is your responsibility
+      * to ensure that a packet really starts there. This method is only available on expressions having the
+      * PacketAccessBit and the LinearAccessBit.
+      *
+      * The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select
+      * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets
+      * starting at an address which is a multiple of the packet size.
+      */
+    template<int StoreMode>
+    EIGEN_STRONG_INLINE void writePacket
+    (Index index, const typename internal::packet_traits<Scalar>::type& val)
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      derived().template writePacket<StoreMode>(index,val);
+    }
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+
+    /** \internal Copies the coefficient at position (row,col) of other into *this.
+      *
+      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
+      * with usual assignments.
+      *
+      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
+      */
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
+    {
+      eigen_internal_assert(row >= 0 && row < rows()
+                        && col >= 0 && col < cols());
+      derived().coeffRef(row, col) = other.derived().coeff(row, col);
+    }
+
+    /** \internal Copies the coefficient at the given index of other into *this.
+      *
+      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
+      * with usual assignments.
+      *
+      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
+      */
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE void copyCoeff(Index index, const DenseBase<OtherDerived>& other)
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      derived().coeffRef(index) = other.derived().coeff(index);
+    }
+
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE void copyCoeffByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
+    {
+      const Index row = rowIndexByOuterInner(outer,inner);
+      const Index col = colIndexByOuterInner(outer,inner);
+      // derived() is important here: copyCoeff() may be reimplemented in Derived!
+      derived().copyCoeff(row, col, other);
+    }
+
+    /** \internal Copies the packet at position (row,col) of other into *this.
+      *
+      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
+      * with usual assignments.
+      *
+      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
+      */
+
+    template<typename OtherDerived, int StoreMode, int LoadMode>
+    EIGEN_STRONG_INLINE void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
+    {
+      eigen_internal_assert(row >= 0 && row < rows()
+                        && col >= 0 && col < cols());
+      derived().template writePacket<StoreMode>(row, col,
+        other.derived().template packet<LoadMode>(row, col));
+    }
+
+    /** \internal Copies the packet at the given index of other into *this.
+      *
+      * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
+      * with usual assignments.
+      *
+      * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox.
+      */
+
+    template<typename OtherDerived, int StoreMode, int LoadMode>
+    EIGEN_STRONG_INLINE void copyPacket(Index index, const DenseBase<OtherDerived>& other)
+    {
+      eigen_internal_assert(index >= 0 && index < size());
+      derived().template writePacket<StoreMode>(index,
+        other.derived().template packet<LoadMode>(index));
+    }
+
+    /** \internal */
+    template<typename OtherDerived, int StoreMode, int LoadMode>
+    EIGEN_STRONG_INLINE void copyPacketByOuterInner(Index outer, Index inner, const DenseBase<OtherDerived>& other)
+    {
+      const Index row = rowIndexByOuterInner(outer,inner);
+      const Index col = colIndexByOuterInner(outer,inner);
+      // derived() is important here: copyCoeff() may be reimplemented in Derived!
+      derived().template copyPacket< OtherDerived, StoreMode, LoadMode>(row, col, other);
+    }
+#endif
+
+};
+
+/** \brief Base class providing direct read-only coefficient access to matrices and arrays.
+  * \ingroup Core_Module
+  * \tparam Derived Type of the derived class
+  * \tparam #DirectAccessors Constant indicating direct access
+  *
+  * This class defines functions to work with strides which can be used to access entries directly. This class
+  * inherits DenseCoeffsBase<Derived, ReadOnlyAccessors> which defines functions to access entries read-only using
+  * \c operator() .
+  *
+  * \sa \ref TopicClassHierarchy
+  */
+template<typename Derived>
+class DenseCoeffsBase<Derived, DirectAccessors> : public DenseCoeffsBase<Derived, ReadOnlyAccessors>
+{
+  public:
+
+    typedef DenseCoeffsBase<Derived, ReadOnlyAccessors> Base;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::derived;
+
+    /** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
+      *
+      * \sa outerStride(), rowStride(), colStride()
+      */
+    inline Index innerStride() const
+    {
+      return derived().innerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
+      *          in a column-major matrix).
+      *
+      * \sa innerStride(), rowStride(), colStride()
+      */
+    inline Index outerStride() const
+    {
+      return derived().outerStride();
+    }
+
+    // FIXME shall we remove it ?
+    inline Index stride() const
+    {
+      return Derived::IsVectorAtCompileTime ? innerStride() : outerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive rows.
+      *
+      * \sa innerStride(), outerStride(), colStride()
+      */
+    inline Index rowStride() const
+    {
+      return Derived::IsRowMajor ? outerStride() : innerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive columns.
+      *
+      * \sa innerStride(), outerStride(), rowStride()
+      */
+    inline Index colStride() const
+    {
+      return Derived::IsRowMajor ? innerStride() : outerStride();
+    }
+};
+
+/** \brief Base class providing direct read/write coefficient access to matrices and arrays.
+  * \ingroup Core_Module
+  * \tparam Derived Type of the derived class
+  * \tparam #DirectWriteAccessors Constant indicating direct access
+  *
+  * This class defines functions to work with strides which can be used to access entries directly. This class
+  * inherits DenseCoeffsBase<Derived, WriteAccessors> which defines functions to access entries read/write using
+  * \c operator().
+  *
+  * \sa \ref TopicClassHierarchy
+  */
+template<typename Derived>
+class DenseCoeffsBase<Derived, DirectWriteAccessors>
+  : public DenseCoeffsBase<Derived, WriteAccessors>
+{
+  public:
+
+    typedef DenseCoeffsBase<Derived, WriteAccessors> Base;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::derived;
+
+    /** \returns the pointer increment between two consecutive elements within a slice in the inner direction.
+      *
+      * \sa outerStride(), rowStride(), colStride()
+      */
+    inline Index innerStride() const
+    {
+      return derived().innerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns
+      *          in a column-major matrix).
+      *
+      * \sa innerStride(), rowStride(), colStride()
+      */
+    inline Index outerStride() const
+    {
+      return derived().outerStride();
+    }
+
+    // FIXME shall we remove it ?
+    inline Index stride() const
+    {
+      return Derived::IsVectorAtCompileTime ? innerStride() : outerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive rows.
+      *
+      * \sa innerStride(), outerStride(), colStride()
+      */
+    inline Index rowStride() const
+    {
+      return Derived::IsRowMajor ? outerStride() : innerStride();
+    }
+
+    /** \returns the pointer increment between two consecutive columns.
+      *
+      * \sa innerStride(), outerStride(), rowStride()
+      */
+    inline Index colStride() const
+    {
+      return Derived::IsRowMajor ? innerStride() : outerStride();
+    }
+};
+
+namespace internal {
+
+template<typename Derived, bool JustReturnZero>
+struct first_aligned_impl
+{
+  static inline typename Derived::Index run(const Derived&)
+  { return 0; }
+};
+
+template<typename Derived>
+struct first_aligned_impl<Derived, false>
+{
+  static inline typename Derived::Index run(const Derived& m)
+  {
+    return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
+  }
+};
+
+/** \internal \returns the index of the first element of the array that is well aligned for vectorization.
+  *
+  * There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more
+  * documentation.
+  */
+template<typename Derived>
+static inline typename Derived::Index first_aligned(const Derived& m)
+{
+  return first_aligned_impl
+          <Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>
+          ::run(m);
+}
+
+template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
+struct inner_stride_at_compile_time
+{
+  enum { ret = traits<Derived>::InnerStrideAtCompileTime };
+};
+
+template<typename Derived>
+struct inner_stride_at_compile_time<Derived, false>
+{
+  enum { ret = 0 };
+};
+
+template<typename Derived, bool HasDirectAccess = has_direct_access<Derived>::ret>
+struct outer_stride_at_compile_time
+{
+  enum { ret = traits<Derived>::OuterStrideAtCompileTime };
+};
+
+template<typename Derived>
+struct outer_stride_at_compile_time<Derived, false>
+{
+  enum { ret = 0 };
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_DENSECOEFFSBASE_H

Eigen/src/Core/DenseStorage.h

@@ -0,0 +1,339 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_MATRIXSTORAGE_H
+#define EIGEN_MATRIXSTORAGE_H
+
+#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
+#else
+  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+#endif
+
+namespace Eigen {
+
+namespace internal {
+
+struct constructor_without_unaligned_array_assert {};
+
+template<typename T, int Size> void check_static_allocation_size()
+{
+  // if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit
+  #if EIGEN_STACK_ALLOCATION_LIMIT
+  EIGEN_STATIC_ASSERT(Size * sizeof(T) <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+  #endif
+}
+
+/** \internal
+  * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned:
+  * to 16 bytes boundary if the total size is a multiple of 16 bytes.
+  */
+template <typename T, int Size, int MatrixOrArrayOptions,
+          int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
+                        : (((Size*sizeof(T))%16)==0) ? 16
+                        : 0 >
+struct plain_array
+{
+  T array[Size];
+
+  plain_array() 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+};
+
+#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask)
+#elif EIGEN_GNUC_AT_LEAST(4,7) 
+  // GCC 4.7 is too aggressive in its optimizations and remove the alignement test based on the fact the array is declared to be aligned.
+  // See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900
+  // Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined:
+  template<typename PtrType>
+  EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; }
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
+    eigen_assert((reinterpret_cast<size_t>(eigen_unaligned_array_assert_workaround_gcc47(array)) & sizemask) == 0 \
+              && "this assertion is explained here: " \
+              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
+              " **** READ THIS WEB PAGE !!! ****");
+#else
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
+    eigen_assert((reinterpret_cast<size_t>(array) & sizemask) == 0 \
+              && "this assertion is explained here: " \
+              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
+              " **** READ THIS WEB PAGE !!! ****");
+#endif
+
+template <typename T, int Size, int MatrixOrArrayOptions>
+struct plain_array<T, Size, MatrixOrArrayOptions, 16>
+{
+  EIGEN_USER_ALIGN16 T array[Size];
+
+  plain_array() 
+  { 
+    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf);
+    check_static_allocation_size<T,Size>();
+  }
+
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+};
+
+template <typename T, int MatrixOrArrayOptions, int Alignment>
+struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
+{
+  EIGEN_USER_ALIGN16 T array[1];
+  plain_array() {}
+  plain_array(constructor_without_unaligned_array_assert) {}
+};
+
+} // end namespace internal
+
+/** \internal
+  *
+  * \class DenseStorage
+  * \ingroup Core_Module
+  *
+  * \brief Stores the data of a matrix
+  *
+  * This class stores the data of fixed-size, dynamic-size or mixed matrices
+  * in a way as compact as possible.
+  *
+  * \sa Matrix
+  */
+template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage;
+
+// purely fixed-size matrix
+template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage
+{
+    internal::plain_array<T,Size,_Options> m_data;
+  public:
+    inline DenseStorage() {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()) {}
+    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
+    static inline DenseIndex rows(void) {return _Rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
+};
+
+// null matrix
+template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
+{
+  public:
+    inline DenseStorage() {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
+    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void swap(DenseStorage& ) {}
+    static inline DenseIndex rows(void) {return _Rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline const T *data() const { return 0; }
+    inline T *data() { return 0; }
+};
+
+// more specializations for null matrices; these are necessary to resolve ambiguities
+template<typename T, int _Options> class DenseStorage<T, 0, Dynamic, Dynamic, _Options>
+: public DenseStorage<T, 0, 0, 0, _Options> { };
+
+template<typename T, int _Rows, int _Options> class DenseStorage<T, 0, _Rows, Dynamic, _Options>
+: public DenseStorage<T, 0, 0, 0, _Options> { };
+
+template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic, _Cols, _Options>
+: public DenseStorage<T, 0, 0, 0, _Options> { };
+
+// dynamic-size matrix with fixed-size storage
+template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_rows;
+    DenseIndex m_cols;
+  public:
+    inline DenseStorage() : m_rows(0), m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
+    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
+    inline void swap(DenseStorage& other)
+    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
+    inline DenseIndex rows() const {return m_rows;}
+    inline DenseIndex cols() const {return m_cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
+};
+
+// dynamic-size matrix with fixed-size storage and fixed width
+template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_rows;
+  public:
+    inline DenseStorage() : m_rows(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
+    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return _Cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
+};
+
+// dynamic-size matrix with fixed-size storage and fixed height
+template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_cols;
+  public:
+    inline DenseStorage() : m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
+    inline DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    inline DenseIndex rows(void) const {return _Rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+    inline void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
+};
+
+// purely dynamic matrix.
+template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
+{
+    T *m_data;
+    DenseIndex m_rows;
+    DenseIndex m_cols;
+  public:
+    inline DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+       : m_data(0), m_rows(0), m_cols(0) {}
+    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
+    inline void swap(DenseStorage& other)
+    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
+      m_rows = nbRows;
+      m_cols = nbCols;
+    }
+    void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    {
+      if(size != m_rows*m_cols)
+      {
+        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_rows = nbRows;
+      m_cols = nbCols;
+    }
+    inline const T *data() const { return m_data; }
+    inline T *data() { return m_data; }
+};
+
+// matrix with dynamic width and fixed height (so that matrix has dynamic size).
+template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
+{
+    T *m_data;
+    DenseIndex m_cols;
+  public:
+    inline DenseStorage() : m_data(0), m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
+    inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    static inline DenseIndex rows(void) {return _Rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
+      m_cols = nbCols;
+    }
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols)
+    {
+      if(size != _Rows*m_cols)
+      {
+        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_cols = nbCols;
+    }
+    inline const T *data() const { return m_data; }
+    inline T *data() { return m_data; }
+};
+
+// matrix with dynamic height and fixed width (so that matrix has dynamic size).
+template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
+{
+    T *m_data;
+    DenseIndex m_rows;
+  public:
+    inline DenseStorage() : m_data(0), m_rows(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
+    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    inline DenseIndex rows(void) const {return m_rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
+      m_rows = nbRows;
+    }
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex)
+    {
+      if(size != m_rows*_Cols)
+      {
+        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_rows = nbRows;
+    }
+    inline const T *data() const { return m_data; }
+    inline T *data() { return m_data; }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_MATRIX_H

Eigen/src/Core/Diagonal.h

@@ -0,0 +1,237 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_DIAGONAL_H
+#define EIGEN_DIAGONAL_H
+
+namespace Eigen { 
+
+/** \class Diagonal
+  * \ingroup Core_Module
+  *
+  * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
+  *
+  * \param MatrixType the type of the object in which we are taking a sub/main/super diagonal
+  * \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
+  *              A positive value means a superdiagonal, a negative value means a subdiagonal.
+  *              You can also use Dynamic so the index can be set at runtime.
+  *
+  * The matrix is not required to be square.
+  *
+  * This class represents an expression of the main diagonal, or any sub/super diagonal
+  * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the
+  * time this is the only way it is used.
+  *
+  * \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index)
+  */
+
+namespace internal {
+template<typename MatrixType, int DiagIndex>
+struct traits<Diagonal<MatrixType,DiagIndex> >
+ : traits<MatrixType>
+{
+  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef typename MatrixType::StorageKind StorageKind;
+  enum {
+    RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
+                      : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                                              MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
+    ColsAtCompileTime = 1,
+    MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
+                         : DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
+                                                                              MatrixType::MaxColsAtCompileTime)
+                         : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                                                 MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
+    MaxColsAtCompileTime = 1,
+    MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
+    Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit,
+    CoeffReadCost = _MatrixTypeNested::CoeffReadCost,
+    MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
+    InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
+    OuterStrideAtCompileTime = 0
+  };
+};
+}
+
+template<typename MatrixType, int _DiagIndex> class Diagonal
+   : public internal::dense_xpr_base< Diagonal<MatrixType,_DiagIndex> >::type
+{
+  public:
+
+    enum { DiagIndex = _DiagIndex };
+    typedef typename internal::dense_xpr_base<Diagonal>::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
+
+    inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
+
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
+
+    inline Index rows() const
+    { return m_index.value()<0 ? (std::min<Index>)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min<Index>)(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
+
+    inline Index cols() const { return 1; }
+
+    inline Index innerStride() const
+    {
+      return m_matrix.outerStride() + 1;
+    }
+
+    inline Index outerStride() const
+    {
+      return 0;
+    }
+
+    typedef typename internal::conditional<
+                       internal::is_lvalue<MatrixType>::value,
+                       Scalar,
+                       const Scalar
+                     >::type ScalarWithConstIfNotLvalue;
+
+    inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
+    inline const Scalar* data() const { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
+
+    inline Scalar& coeffRef(Index row, Index)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
+      return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
+    }
+
+    inline const Scalar& coeffRef(Index row, Index) const
+    {
+      return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
+    }
+
+    inline CoeffReturnType coeff(Index row, Index) const
+    {
+      return m_matrix.coeff(row+rowOffset(), row+colOffset());
+    }
+
+    inline Scalar& coeffRef(Index idx)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
+      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
+    }
+
+    inline const Scalar& coeffRef(Index idx) const
+    {
+      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
+    }
+
+    inline CoeffReturnType coeff(Index idx) const
+    {
+      return m_matrix.coeff(idx+rowOffset(), idx+colOffset());
+    }
+
+    const typename internal::remove_all<typename MatrixType::Nested>::type& 
+    nestedExpression() const 
+    {
+      return m_matrix;
+    }
+
+    int index() const
+    {
+      return m_index.value();
+    }
+
+  protected:
+    typename MatrixType::Nested m_matrix;
+    const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
+
+  private:
+    // some compilers may fail to optimize std::max etc in case of compile-time constants...
+    EIGEN_STRONG_INLINE Index absDiagIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); }
+    EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
+    EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
+    // triger a compile time error is someone try to call packet
+    template<int LoadMode> typename MatrixType::PacketReturnType packet(Index) const;
+    template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const;
+};
+
+/** \returns an expression of the main diagonal of the matrix \c *this
+  *
+  * \c *this is not required to be square.
+  *
+  * Example: \include MatrixBase_diagonal.cpp
+  * Output: \verbinclude MatrixBase_diagonal.out
+  *
+  * \sa class Diagonal */
+template<typename Derived>
+inline typename MatrixBase<Derived>::DiagonalReturnType
+MatrixBase<Derived>::diagonal()
+{
+  return derived();
+}
+
+/** This is the const version of diagonal(). */
+template<typename Derived>
+inline typename MatrixBase<Derived>::ConstDiagonalReturnType
+MatrixBase<Derived>::diagonal() const
+{
+  return ConstDiagonalReturnType(derived());
+}
+
+/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
+  *
+  * \c *this is not required to be square.
+  *
+  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
+  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
+  *
+  * Example: \include MatrixBase_diagonal_int.cpp
+  * Output: \verbinclude MatrixBase_diagonal_int.out
+  *
+  * \sa MatrixBase::diagonal(), class Diagonal */
+template<typename Derived>
+inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType
+MatrixBase<Derived>::diagonal(Index index)
+{
+  return DiagonalDynamicIndexReturnType(derived(), index);
+}
+
+/** This is the const version of diagonal(Index). */
+template<typename Derived>
+inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType
+MatrixBase<Derived>::diagonal(Index index) const
+{
+  return ConstDiagonalDynamicIndexReturnType(derived(), index);
+}
+
+/** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
+  *
+  * \c *this is not required to be square.
+  *
+  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
+  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
+  *
+  * Example: \include MatrixBase_diagonal_template_int.cpp
+  * Output: \verbinclude MatrixBase_diagonal_template_int.out
+  *
+  * \sa MatrixBase::diagonal(), class Diagonal */
+template<typename Derived>
+template<int Index>
+inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index>::Type
+MatrixBase<Derived>::diagonal()
+{
+  return derived();
+}
+
+/** This is the const version of diagonal<int>(). */
+template<typename Derived>
+template<int Index>
+inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index>::Type
+MatrixBase<Derived>::diagonal() const
+{
+  return derived();
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_DIAGONAL_H

Eigen/src/Core/DiagonalCoeffs.h

@@ -1,124 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_DIAGONALCOEFFS_H
-#define EIGEN_DIAGONALCOEFFS_H
-
-/** \class DiagonalCoeffs
-  *
-  * \brief Expression of the main diagonal of a matrix
-  *
-  * \param MatrixType the type of the object in which we are taking the main diagonal
-  *
-  * The matrix is not required to be square.
-  *
-  * This class represents an expression of the main diagonal of a square matrix.
-  * It is the return type of MatrixBase::diagonal() and most of the time this is
-  * the only way it is used.
-  *
-  * \sa MatrixBase::diagonal()
-  */
-template<typename MatrixType>
-struct ei_traits<DiagonalCoeffs<MatrixType> >
-{
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename ei_nested<MatrixType>::type MatrixTypeNested;
-  typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
-  enum {
-    RowsAtCompileTime = int(MatrixType::SizeAtCompileTime) == Dynamic ? Dynamic
-                      : EIGEN_ENUM_MIN(MatrixType::RowsAtCompileTime,
-                                       MatrixType::ColsAtCompileTime),
-    ColsAtCompileTime = 1,
-    MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
-                            : EIGEN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime,
-                                             MatrixType::MaxColsAtCompileTime),
-    MaxColsAtCompileTime = 1,
-    Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit),
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost
-  };
-};
-
-template<typename MatrixType> class DiagonalCoeffs
-   : public MatrixBase<DiagonalCoeffs<MatrixType> >
-{
-  public:
-
-    EIGEN_GENERIC_PUBLIC_INTERFACE(DiagonalCoeffs)
-
-    inline DiagonalCoeffs(const MatrixType& matrix) : m_matrix(matrix) {}
-
-    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(DiagonalCoeffs)
-
-    inline int rows() const { return std::min(m_matrix.rows(), m_matrix.cols()); }
-    inline int cols() const { return 1; }
-
-    inline Scalar& coeffRef(int row, int)
-    {
-      return m_matrix.const_cast_derived().coeffRef(row, row);
-    }
-
-    inline const Scalar coeff(int row, int) const
-    {
-      return m_matrix.coeff(row, row);
-    }
-
-    inline Scalar& coeffRef(int index)
-    {
-      return m_matrix.const_cast_derived().coeffRef(index, index);
-    }
-
-    inline const Scalar coeff(int index) const
-    {
-      return m_matrix.coeff(index, index);
-    }
-
-  protected:
-
-    const typename MatrixType::Nested m_matrix;
-};
-
-/** \returns an expression of the main diagonal of the matrix \c *this
-  *
-  * \c *this is not required to be square.
-  *
-  * Example: \include MatrixBase_diagonal.cpp
-  * Output: \verbinclude MatrixBase_diagonal.out
-  *
-  * \sa class DiagonalCoeffs */
-template<typename Derived>
-inline DiagonalCoeffs<Derived>
-MatrixBase<Derived>::diagonal()
-{
-  return DiagonalCoeffs<Derived>(derived());
-}
-
-/** This is the const version of diagonal(). */
-template<typename Derived>
-inline const DiagonalCoeffs<Derived>
-MatrixBase<Derived>::diagonal() const
-{
-  return DiagonalCoeffs<Derived>(derived());
-}
-
-#endif // EIGEN_DIAGONALCOEFFS_H

Eigen/src/Core/DiagonalMatrix.h

@@ -1,118 +1,286 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DIAGONALMATRIX_H
 #define EIGEN_DIAGONALMATRIX_H
 
+namespace Eigen { 
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename Derived>
+class DiagonalBase : public EigenBase<Derived>
+{
+  public:
+    typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
+    typedef typename DiagonalVectorType::Scalar Scalar;
+    typedef typename DiagonalVectorType::RealScalar RealScalar;
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
+
+    enum {
+      RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+      ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+      MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
+      MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
+      IsVectorAtCompileTime = 0,
+      Flags = 0
+    };
+
+    typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
+    typedef DenseMatrixType DenseType;
+    typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject;
+
+    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    inline Derived& derived() { return *static_cast<Derived*>(this); }
+
+    DenseMatrixType toDenseMatrix() const { return derived(); }
+    template<typename DenseDerived>
+    void evalTo(MatrixBase<DenseDerived> &other) const;
+    template<typename DenseDerived>
+    void addTo(MatrixBase<DenseDerived> &other) const
+    { other.diagonal() += diagonal(); }
+    template<typename DenseDerived>
+    void subTo(MatrixBase<DenseDerived> &other) const
+    { other.diagonal() -= diagonal(); }
+
+    inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
+    inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
+
+    inline Index rows() const { return diagonal().size(); }
+    inline Index cols() const { return diagonal().size(); }
+
+    /** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
+      */
+    template<typename MatrixDerived>
+    const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
+    operator*(const MatrixBase<MatrixDerived> &matrix) const
+    {
+      return DiagonalProduct<MatrixDerived, Derived, OnTheLeft>(matrix.derived(), derived());
+    }
+
+    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
+    inverse() const
+    {
+      return diagonal().cwiseInverse();
+    }
+    
+    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+    operator*(const Scalar& scalar) const
+    {
+      return diagonal() * scalar;
+    }
+    friend inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+    operator*(const Scalar& scalar, const DiagonalBase& other)
+    {
+      return other.diagonal() * scalar;
+    }
+    
+    #ifdef EIGEN2_SUPPORT
+    template<typename OtherDerived>
+    bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
+    {
+      return diagonal().isApprox(other.diagonal(), precision);
+    }
+    template<typename OtherDerived>
+    bool isApprox(const MatrixBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
+    {
+      return toDenseMatrix().isApprox(other, precision);
+    }
+    #endif
+};
+
+template<typename Derived>
+template<typename DenseDerived>
+void DiagonalBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
+{
+  other.setZero();
+  other.diagonal() = diagonal();
+}
+#endif
+
 /** \class DiagonalMatrix
-  * \nonstableyet 
+  * \ingroup Core_Module
+  *
+  * \brief Represents a diagonal matrix with its storage
+  *
+  * \param _Scalar the type of coefficients
+  * \param SizeAtCompileTime the dimension of the matrix, or Dynamic
+  * \param MaxSizeAtCompileTime the dimension of the matrix, or Dynamic. This parameter is optional and defaults
+  *        to SizeAtCompileTime. Most of the time, you do not need to specify it.
+  *
+  * \sa class DiagonalWrapper
+  */
+
+namespace internal {
+template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
+struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
+ : traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
+{
+  typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
+  typedef Dense StorageKind;
+  typedef DenseIndex Index;
+  enum {
+    Flags = LvalueBit
+  };
+};
+}
+template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
+class DiagonalMatrix
+  : public DiagonalBase<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
+{
+  public:
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    typedef typename internal::traits<DiagonalMatrix>::DiagonalVectorType DiagonalVectorType;
+    typedef const DiagonalMatrix& Nested;
+    typedef _Scalar Scalar;
+    typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
+    typedef typename internal::traits<DiagonalMatrix>::Index Index;
+    #endif
+
+  protected:
+
+    DiagonalVectorType m_diagonal;
+
+  public:
+
+    /** const version of diagonal(). */
+    inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
+    /** \returns a reference to the stored vector of diagonal coefficients. */
+    inline DiagonalVectorType& diagonal() { return m_diagonal; }
+
+    /** Default constructor without initialization */
+    inline DiagonalMatrix() {}
+
+    /** Constructs a diagonal matrix with given dimension  */
+    inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
+
+    /** 2D constructor. */
+    inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {}
+
+    /** 3D constructor. */
+    inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {}
+
+    /** Copy constructor. */
+    template<typename OtherDerived>
+    inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other) : m_diagonal(other.diagonal()) {}
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */
+    inline DiagonalMatrix(const DiagonalMatrix& other) : m_diagonal(other.diagonal()) {}
+    #endif
+
+    /** generic constructor from expression of the diagonal coefficients */
+    template<typename OtherDerived>
+    explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other) : m_diagonal(other)
+    {}
+
+    /** Copy operator. */
+    template<typename OtherDerived>
+    DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other)
+    {
+      m_diagonal = other.diagonal();
+      return *this;
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** This is a special case of the templated operator=. Its purpose is to
+      * prevent a default operator= from hiding the templated operator=.
+      */
+    DiagonalMatrix& operator=(const DiagonalMatrix& other)
+    {
+      m_diagonal = other.diagonal();
+      return *this;
+    }
+    #endif
+
+    /** Resizes to given size. */
+    inline void resize(Index size) { m_diagonal.resize(size); }
+    /** Sets all coefficients to zero. */
+    inline void setZero() { m_diagonal.setZero(); }
+    /** Resizes and sets all coefficients to zero. */
+    inline void setZero(Index size) { m_diagonal.setZero(size); }
+    /** Sets this matrix to be the identity matrix of the current size. */
+    inline void setIdentity() { m_diagonal.setOnes(); }
+    /** Sets this matrix to be the identity matrix of the given size. */
+    inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
+};
+
+/** \class DiagonalWrapper
+  * \ingroup Core_Module
   *
   * \brief Expression of a diagonal matrix
   *
-  * \param CoeffsVectorType the type of the vector of diagonal coefficients
+  * \param _DiagonalVectorType the type of the vector of diagonal coefficients
   *
-  * This class is an expression of a diagonal matrix with given vector of diagonal
-  * coefficients. It is the return
-  * type of MatrixBase::diagonal(const OtherDerived&) and most of the time this is
-  * the only way it is used.
+  * This class is an expression of a diagonal matrix, but not storing its own vector of diagonal coefficients,
+  * instead wrapping an existing vector expression. It is the return type of MatrixBase::asDiagonal()
+  * and most of the time this is the only way that it is used.
   *
-  * \sa MatrixBase::diagonal(const OtherDerived&)
+  * \sa class DiagonalMatrix, class DiagonalBase, MatrixBase::asDiagonal()
   */
-template<typename CoeffsVectorType>
-struct ei_traits<DiagonalMatrix<CoeffsVectorType> >
+
+namespace internal {
+template<typename _DiagonalVectorType>
+struct traits<DiagonalWrapper<_DiagonalVectorType> >
 {
-  typedef typename CoeffsVectorType::Scalar Scalar;
-  typedef typename ei_nested<CoeffsVectorType>::type CoeffsVectorTypeNested;
-  typedef typename ei_unref<CoeffsVectorTypeNested>::type _CoeffsVectorTypeNested;
+  typedef _DiagonalVectorType DiagonalVectorType;
+  typedef typename DiagonalVectorType::Scalar Scalar;
+  typedef typename DiagonalVectorType::Index Index;
+  typedef typename DiagonalVectorType::StorageKind StorageKind;
   enum {
-    RowsAtCompileTime = CoeffsVectorType::SizeAtCompileTime,
-    ColsAtCompileTime = CoeffsVectorType::SizeAtCompileTime,
-    MaxRowsAtCompileTime = CoeffsVectorType::MaxSizeAtCompileTime,
-    MaxColsAtCompileTime = CoeffsVectorType::MaxSizeAtCompileTime,
-    Flags = (_CoeffsVectorTypeNested::Flags & HereditaryBits) | Diagonal,
-    CoeffReadCost = _CoeffsVectorTypeNested::CoeffReadCost
+    RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+    ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+    MaxRowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+    MaxColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+    Flags =  traits<DiagonalVectorType>::Flags & LvalueBit
   };
 };
+}
 
-template<typename CoeffsVectorType>
-class DiagonalMatrix : ei_no_assignment_operator,
-   public MatrixBase<DiagonalMatrix<CoeffsVectorType> >
+template<typename _DiagonalVectorType>
+class DiagonalWrapper
+  : public DiagonalBase<DiagonalWrapper<_DiagonalVectorType> >, internal::no_assignment_operator
 {
   public:
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    typedef _DiagonalVectorType DiagonalVectorType;
+    typedef DiagonalWrapper Nested;
+    #endif
 
-    EIGEN_GENERIC_PUBLIC_INTERFACE(DiagonalMatrix)
+    /** Constructor from expression of diagonal coefficients to wrap. */
+    inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
 
-    // needed to evaluate a DiagonalMatrix<Xpr> to a DiagonalMatrix<NestByValue<Vector> >
-    template<typename OtherCoeffsVectorType>
-    inline DiagonalMatrix(const DiagonalMatrix<OtherCoeffsVectorType>& other) : m_coeffs(other.diagonal())
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(CoeffsVectorType);
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherCoeffsVectorType);
-      ei_assert(m_coeffs.size() > 0);
-    }
-
-    inline DiagonalMatrix(const CoeffsVectorType& coeffs) : m_coeffs(coeffs)
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(CoeffsVectorType);
-      ei_assert(coeffs.size() > 0);
-    }
-
-    inline int rows() const { return m_coeffs.size(); }
-    inline int cols() const { return m_coeffs.size(); }
-
-    inline const Scalar coeff(int row, int col) const
-    {
-      return row == col ? m_coeffs.coeff(row) : static_cast<Scalar>(0);
-    }
-
-    inline const CoeffsVectorType& diagonal() const { return m_coeffs; }
+    /** \returns a const reference to the wrapped expression of diagonal coefficients. */
+    const DiagonalVectorType& diagonal() const { return m_diagonal; }
 
   protected:
-    const typename CoeffsVectorType::Nested m_coeffs;
+    typename DiagonalVectorType::Nested m_diagonal;
 };
 
-/** \nonstableyet 
-  * \returns an expression of a diagonal matrix with *this as vector of diagonal coefficients
+/** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients
   *
   * \only_for_vectors
   *
-  * \addexample AsDiagonalExample \label How to build a diagonal matrix from a vector
-  *
   * Example: \include MatrixBase_asDiagonal.cpp
   * Output: \verbinclude MatrixBase_asDiagonal.out
   *
-  * \sa class DiagonalMatrix, isDiagonal()
+  * \sa class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal()
   **/
 template<typename Derived>
-inline const DiagonalMatrix<Derived>
+inline const DiagonalWrapper<const Derived>
 MatrixBase<Derived>::asDiagonal() const
 {
   return derived();
 }
 
-/** \nonstableyet 
-  * \returns true if *this is approximately equal to a diagonal matrix,
+/** \returns true if *this is approximately equal to a diagonal matrix,
   *          within the precision given by \a prec.
   *
   * Example: \include MatrixBase_isDiagonal.cpp
@@ -121,23 +289,25 @@ MatrixBase<Derived>::asDiagonal() const
   * \sa asDiagonal()
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isDiagonal
-(RealScalar prec) const
+bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
 {
+  using std::abs;
   if(cols() != rows()) return false;
   RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
-  for(int j = 0; j < cols(); ++j)
+  for(Index j = 0; j < cols(); ++j)
   {
-    RealScalar absOnDiagonal = ei_abs(coeff(j,j));
+    RealScalar absOnDiagonal = abs(coeff(j,j));
     if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
   }
-  for(int j = 0; j < cols(); ++j)
-    for(int i = 0; i < j; ++i)
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < j; ++i)
     {
-      if(!ei_isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false;
-      if(!ei_isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false;
+      if(!internal::isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false;
+      if(!internal::isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false;
     }
   return true;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_DIAGONALMATRIX_H

Eigen/src/Core/DiagonalProduct.h

@@ -1,130 +1,130 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DIAGONALPRODUCT_H
 #define EIGEN_DIAGONALPRODUCT_H
 
-/** \internal Specialization of ei_nested for DiagonalMatrix.
- *  Unlike ei_nested, if the argument is a DiagonalMatrix and if it must be evaluated,
- *  then it evaluated to a DiagonalMatrix having its own argument evaluated.
- */
-template<typename T, int N> struct ei_nested_diagonal : ei_nested<T,N> {};
-template<typename T, int N> struct ei_nested_diagonal<DiagonalMatrix<T>,N >
- : ei_nested<DiagonalMatrix<T>, N, DiagonalMatrix<NestByValue<typename ei_plain_matrix_type<T>::type> > >
-{};
+namespace Eigen { 
 
-// specialization of ProductReturnType
-template<typename Lhs, typename Rhs>
-struct ProductReturnType<Lhs,Rhs,DiagonalProduct>
+namespace internal {
+template<typename MatrixType, typename DiagonalType, int ProductOrder>
+struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
+ : traits<MatrixType>
 {
-  typedef typename ei_nested_diagonal<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
-  typedef typename ei_nested_diagonal<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
-
-  typedef Product<LhsNested, RhsNested, DiagonalProduct> Type;
-};
-
-template<typename LhsNested, typename RhsNested>
-struct ei_traits<Product<LhsNested, RhsNested, DiagonalProduct> >
-{
-  // clean the nested types:
-  typedef typename ei_cleantype<LhsNested>::type _LhsNested;
-  typedef typename ei_cleantype<RhsNested>::type _RhsNested;
-  typedef typename _LhsNested::Scalar Scalar;
-
+  typedef typename scalar_product_traits<typename MatrixType::Scalar, typename DiagonalType::Scalar>::ReturnType Scalar;
   enum {
-    LhsFlags = _LhsNested::Flags,
-    RhsFlags = _RhsNested::Flags,
-    RowsAtCompileTime = _LhsNested::RowsAtCompileTime,
-    ColsAtCompileTime = _RhsNested::ColsAtCompileTime,
-    MaxRowsAtCompileTime = _LhsNested::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = _RhsNested::MaxColsAtCompileTime,
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
 
-    LhsIsDiagonal = (_LhsNested::Flags&Diagonal)==Diagonal,
-    RhsIsDiagonal = (_RhsNested::Flags&Diagonal)==Diagonal,
+    _StorageOrder = MatrixType::Flags & RowMajorBit ? RowMajor : ColMajor,
+    _ScalarAccessOnDiag =  !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
+                          ||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
+    _SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
+    // FIXME currently we need same types, but in the future the next rule should be the one
+    //_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
+    _Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
+    _LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0,
 
-    CanVectorizeRhs =  (!RhsIsDiagonal) && (RhsFlags & RowMajorBit) && (RhsFlags & PacketAccessBit)
-                     && (ColsAtCompileTime % ei_packet_traits<Scalar>::size == 0),
-
-    CanVectorizeLhs =  (!LhsIsDiagonal) && (!(LhsFlags & RowMajorBit)) && (LhsFlags & PacketAccessBit)
-                     && (RowsAtCompileTime % ei_packet_traits<Scalar>::size == 0),
-
-    RemovedBits = ~((RhsFlags & RowMajorBit) && (!CanVectorizeLhs) ? 0 : RowMajorBit),
-
-    Flags = ((unsigned int)(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
-          | (((CanVectorizeLhs&&RhsIsDiagonal) || (CanVectorizeRhs&&LhsIsDiagonal)) ? PacketAccessBit : 0),
-
-    CoeffReadCost = NumTraits<Scalar>::MulCost + _LhsNested::CoeffReadCost + _RhsNested::CoeffReadCost
+    Flags = ((HereditaryBits|_LinearAccessMask|AlignedBit) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
+    CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + DiagonalType::DiagonalVectorType::CoeffReadCost
   };
 };
+}
 
-template<typename LhsNested, typename RhsNested> class Product<LhsNested, RhsNested, DiagonalProduct> : ei_no_assignment_operator,
-  public MatrixBase<Product<LhsNested, RhsNested, DiagonalProduct> >
+template<typename MatrixType, typename DiagonalType, int ProductOrder>
+class DiagonalProduct : internal::no_assignment_operator,
+                        public MatrixBase<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
 {
-    typedef typename ei_traits<Product>::_LhsNested _LhsNested;
-    typedef typename ei_traits<Product>::_RhsNested _RhsNested;
-
-    enum {
-      RhsIsDiagonal = (_RhsNested::Flags&Diagonal)==Diagonal
-    };
-
   public:
 
-    EIGEN_GENERIC_PUBLIC_INTERFACE(Product)
+    typedef MatrixBase<DiagonalProduct> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(DiagonalProduct)
 
-    template<typename Lhs, typename Rhs>
-    inline Product(const Lhs& lhs, const Rhs& rhs)
-      : m_lhs(lhs), m_rhs(rhs)
+    inline DiagonalProduct(const MatrixType& matrix, const DiagonalType& diagonal)
+      : m_matrix(matrix), m_diagonal(diagonal)
     {
-      ei_assert(lhs.cols() == rhs.rows());
+      eigen_assert(diagonal.diagonal().size() == (ProductOrder == OnTheLeft ? matrix.rows() : matrix.cols()));
     }
 
-    inline int rows() const { return m_lhs.rows(); }
-    inline int cols() const { return m_rhs.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
 
-    const Scalar coeff(int row, int col) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
     {
-      const int unique = RhsIsDiagonal ? col : row;
-      return m_lhs.coeff(row, unique) * m_rhs.coeff(unique, col);
+      return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
+    }
+    
+    EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
+    {
+      enum {
+        StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
+      };
+      return coeff(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
     }
 
     template<int LoadMode>
-    const PacketScalar packet(int row, int col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
     {
-      if (RhsIsDiagonal)
-      {
-        return ei_pmul(m_lhs.template packet<LoadMode>(row, col), ei_pset1(m_rhs.coeff(col, col)));
-      }
-      else
-      {
-        return ei_pmul(ei_pset1(m_lhs.coeff(row, row)), m_rhs.template packet<LoadMode>(row, col));
-      }
+      enum {
+        StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor
+      };
+      const Index indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col;
+      return packet_impl<LoadMode>(row,col,indexInDiagonalVector,typename internal::conditional<
+        ((int(StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
+       ||(int(StorageOrder) == ColMajor && int(ProductOrder) == OnTheRight)), internal::true_type, internal::false_type>::type());
+    }
+    
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const
+    {
+      enum {
+        StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
+      };
+      return packet<LoadMode>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
     }
 
   protected:
-    const LhsNested m_lhs;
-    const RhsNested m_rhs;
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::true_type) const
+    {
+      return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
+                     internal::pset1<PacketScalar>(m_diagonal.diagonal().coeff(id)));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::false_type) const
+    {
+      enum {
+        InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
+        DiagonalVectorPacketLoadMode = (LoadMode == Aligned && (((InnerSize%16) == 0) || (int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit)==AlignedBit) ? Aligned : Unaligned)
+      };
+      return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
+                     m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
+    }
+
+    typename MatrixType::Nested m_matrix;
+    typename DiagonalType::Nested m_diagonal;
 };
 
+/** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
+  */
+template<typename Derived>
+template<typename DiagonalDerived>
+inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
+MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
+{
+  return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), a_diagonal.derived());
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_DIAGONALPRODUCT_H

Eigen/src/Core/Dot.h

@@ -1,292 +1,131 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2006-2008, 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DOT_H
 #define EIGEN_DOT_H
 
-/***************************************************************************
-* Part 1 : the logic deciding a strategy for vectorization and unrolling
-***************************************************************************/
+namespace Eigen { 
 
-template<typename Derived1, typename Derived2>
-struct ei_dot_traits
-{
-public:
-  enum {
-    Vectorization = (int(Derived1::Flags)&int(Derived2::Flags)&ActualPacketAccessBit)
-                 && (int(Derived1::Flags)&int(Derived2::Flags)&LinearAccessBit)
-                  ? LinearVectorization
-                  : NoVectorization
-  };
+namespace internal {
 
-private:
-  typedef typename Derived1::Scalar Scalar;
-  enum {
-    PacketSize = ei_packet_traits<Scalar>::size,
-    Cost = Derived1::SizeAtCompileTime * (Derived1::CoeffReadCost + Derived2::CoeffReadCost + NumTraits<Scalar>::MulCost)
-           + (Derived1::SizeAtCompileTime-1) * NumTraits<Scalar>::AddCost,
-    UnrollingLimit = EIGEN_UNROLLING_LIMIT * (int(Vectorization) == int(NoVectorization) ? 1 : int(PacketSize))
-  };
-
-public:
-  enum {
-    Unrolling = Cost <= UnrollingLimit
-              ? CompleteUnrolling
-              : NoUnrolling
-  };
-};
-
-/***************************************************************************
-* Part 2 : unrollers
-***************************************************************************/
-
-/*** no vectorization ***/
-
-template<typename Derived1, typename Derived2, int Start, int Length>
-struct ei_dot_novec_unroller
-{
-  enum {
-    HalfLength = Length/2
-  };
-
-  typedef typename Derived1::Scalar Scalar;
-
-  inline static Scalar run(const Derived1& v1, const Derived2& v2)
-  {
-    return ei_dot_novec_unroller<Derived1, Derived2, Start, HalfLength>::run(v1, v2)
-         + ei_dot_novec_unroller<Derived1, Derived2, Start+HalfLength, Length-HalfLength>::run(v1, v2);
-  }
-};
-
-template<typename Derived1, typename Derived2, int Start>
-struct ei_dot_novec_unroller<Derived1, Derived2, Start, 1>
-{
-  typedef typename Derived1::Scalar Scalar;
-
-  inline static Scalar run(const Derived1& v1, const Derived2& v2)
-  {
-    return v1.coeff(Start) * ei_conj(v2.coeff(Start));
-  }
-};
-
-/*** vectorization ***/
-
-template<typename Derived1, typename Derived2, int Index, int Stop,
-         bool LastPacket = (Stop-Index == ei_packet_traits<typename Derived1::Scalar>::size)>
-struct ei_dot_vec_unroller
-{
-  typedef typename Derived1::Scalar Scalar;
-  typedef typename ei_packet_traits<Scalar>::type PacketScalar;
-
-  enum {
-    row1 = Derived1::RowsAtCompileTime == 1 ? 0 : Index,
-    col1 = Derived1::RowsAtCompileTime == 1 ? Index : 0,
-    row2 = Derived2::RowsAtCompileTime == 1 ? 0 : Index,
-    col2 = Derived2::RowsAtCompileTime == 1 ? Index : 0
-  };
-
-  inline static PacketScalar run(const Derived1& v1, const Derived2& v2)
-  {
-    return ei_pmadd(
-      v1.template packet<Aligned>(row1, col1),
-      v2.template packet<Aligned>(row2, col2),
-      ei_dot_vec_unroller<Derived1, Derived2, Index+ei_packet_traits<Scalar>::size, Stop>::run(v1, v2)
-    );
-  }
-};
-
-template<typename Derived1, typename Derived2, int Index, int Stop>
-struct ei_dot_vec_unroller<Derived1, Derived2, Index, Stop, true>
-{
-  enum {
-    row1 = Derived1::RowsAtCompileTime == 1 ? 0 : Index,
-    col1 = Derived1::RowsAtCompileTime == 1 ? Index : 0,
-    row2 = Derived2::RowsAtCompileTime == 1 ? 0 : Index,
-    col2 = Derived2::RowsAtCompileTime == 1 ? Index : 0,
-    alignment1 = (Derived1::Flags & AlignedBit) ? Aligned : Unaligned,
-    alignment2 = (Derived2::Flags & AlignedBit) ? Aligned : Unaligned
-  };
-
-  typedef typename Derived1::Scalar Scalar;
-  typedef typename ei_packet_traits<Scalar>::type PacketScalar;
-
-  inline static PacketScalar run(const Derived1& v1, const Derived2& v2)
-  {
-    return ei_pmul(v1.template packet<alignment1>(row1, col1), v2.template packet<alignment2>(row2, col2));
-  }
-};
-
-/***************************************************************************
-* Part 3 : implementation of all cases
-***************************************************************************/
-
-template<typename Derived1, typename Derived2,
-         int Vectorization = ei_dot_traits<Derived1, Derived2>::Vectorization,
-         int Unrolling = ei_dot_traits<Derived1, Derived2>::Unrolling
+// helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot
+// with mismatched types, the compiler emits errors about failing to instantiate cwiseProduct BEFORE
+// looking at the static assertions. Thus this is a trick to get better compile errors.
+template<typename T, typename U,
+// the NeedToTranspose condition here is taken straight from Assign.h
+         bool NeedToTranspose = T::IsVectorAtCompileTime
+                && U::IsVectorAtCompileTime
+                && ((int(T::RowsAtCompileTime) == 1 && int(U::ColsAtCompileTime) == 1)
+                      |  // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
+                         // revert to || as soon as not needed anymore.
+                    (int(T::ColsAtCompileTime) == 1 && int(U::RowsAtCompileTime) == 1))
 >
-struct ei_dot_impl;
-
-template<typename Derived1, typename Derived2>
-struct ei_dot_impl<Derived1, Derived2, NoVectorization, NoUnrolling>
+struct dot_nocheck
 {
-  typedef typename Derived1::Scalar Scalar;
-  static Scalar run(const Derived1& v1, const Derived2& v2)
+  typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
+  static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
   {
-    ei_assert(v1.size()>0 && "you are using a non initialized vector");
-    Scalar res;
-    res = v1.coeff(0) * ei_conj(v2.coeff(0));
-    for(int i = 1; i < v1.size(); ++i)
-      res += v1.coeff(i) * ei_conj(v2.coeff(i));
-    return res;
+    return a.template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct ei_dot_impl<Derived1, Derived2, NoVectorization, CompleteUnrolling>
-  : public ei_dot_novec_unroller<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
-{};
-
-template<typename Derived1, typename Derived2>
-struct ei_dot_impl<Derived1, Derived2, LinearVectorization, NoUnrolling>
+template<typename T, typename U>
+struct dot_nocheck<T, U, true>
 {
-  typedef typename Derived1::Scalar Scalar;
-  typedef typename ei_packet_traits<Scalar>::type PacketScalar;
-
-  static Scalar run(const Derived1& v1, const Derived2& v2)
+  typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
+  static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
   {
-    const int size = v1.size();
-    const int packetSize = ei_packet_traits<Scalar>::size;
-    const int alignedSize = (size/packetSize)*packetSize;
-    enum {
-      alignment1 = (Derived1::Flags & AlignedBit) ? Aligned : Unaligned,
-      alignment2 = (Derived2::Flags & AlignedBit) ? Aligned : Unaligned
-    };
-    Scalar res;
-
-    // do the vectorizable part of the sum
-    if(size >= packetSize)
-    {
-      PacketScalar packet_res = ei_pmul(
-                                  v1.template packet<alignment1>(0),
-                                  v2.template packet<alignment2>(0)
-                                );
-      for(int index = packetSize; index<alignedSize; index += packetSize)
-      {
-        packet_res = ei_pmadd(
-                       v1.template packet<alignment1>(index),
-                       v2.template packet<alignment2>(index),
-                       packet_res
-                     );
-      }
-      res = ei_predux(packet_res);
-
-      // now we must do the rest without vectorization.
-      if(alignedSize == size) return res;
-    }
-    else // too small to vectorize anything.
-         // since this is dynamic-size hence inefficient anyway for such small sizes, don't try to optimize.
-    {
-      res = Scalar(0);
-    }
-
-    // do the remainder of the vector
-    for(int index = alignedSize; index < size; ++index)
-    {
-      res += v1.coeff(index) * v2.coeff(index);
-    }
-
-    return res;
+    return a.transpose().template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct ei_dot_impl<Derived1, Derived2, LinearVectorization, CompleteUnrolling>
-{
-  typedef typename Derived1::Scalar Scalar;
-  typedef typename ei_packet_traits<Scalar>::type PacketScalar;
-  enum {
-    PacketSize = ei_packet_traits<Scalar>::size,
-    Size = Derived1::SizeAtCompileTime,
-    VectorizationSize = (Size / PacketSize) * PacketSize
-  };
-  static Scalar run(const Derived1& v1, const Derived2& v2)
-  {
-    Scalar res = ei_predux(ei_dot_vec_unroller<Derived1, Derived2, 0, VectorizationSize>::run(v1, v2));
-    if (VectorizationSize != Size)
-      res += ei_dot_novec_unroller<Derived1, Derived2, VectorizationSize, Size-VectorizationSize>::run(v1, v2);
-    return res;
-  }
-};
-
-/***************************************************************************
-* Part 4 : implementation of MatrixBase methods
-***************************************************************************/
+} // end namespace internal
 
 /** \returns the dot product of *this with other.
   *
   * \only_for_vectors
   *
   * \note If the scalar type is complex numbers, then this function returns the hermitian
-  * (sesquilinear) dot product, linear in the first variable and conjugate-linear in the
+  * (sesquilinear) dot product, conjugate-linear in the first variable and linear in the
   * second variable.
   *
   * \sa squaredNorm(), norm()
   */
 template<typename Derived>
 template<typename OtherDerived>
-typename ei_traits<Derived>::Scalar
+typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
 MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
   EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
-  EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename OtherDerived::Scalar>::ret),
-    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+  typedef internal::scalar_conj_product_op<Scalar,typename OtherDerived::Scalar> func;
+  EIGEN_CHECK_BINARY_COMPATIBILIY(func,Scalar,typename OtherDerived::Scalar);
 
-  ei_assert(size() == other.size());
+  eigen_assert(size() == other.size());
 
-  return ei_dot_impl<Derived, OtherDerived>::run(derived(), other.derived());
+  return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
 }
 
-/** \returns the squared \em l2 norm of *this, i.e., for vectors, the dot product of *this with itself.
+#ifdef EIGEN2_SUPPORT
+/** \returns the dot product of *this with other, with the Eigen2 convention that the dot product is linear in the first variable
+  * (conjugating the second variable). Of course this only makes a difference in the complex case.
+  *
+  * This method is only available in EIGEN2_SUPPORT mode.
+  *
+  * \only_for_vectors
+  *
+  * \sa dot()
+  */
+template<typename Derived>
+template<typename OtherDerived>
+typename internal::traits<Derived>::Scalar
+MatrixBase<Derived>::eigen2_dot(const MatrixBase<OtherDerived>& other) const
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
+  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
+  EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
+    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+
+  eigen_assert(size() == other.size());
+
+  return internal::dot_nocheck<OtherDerived,Derived>::run(other,*this);
+}
+#endif
+
+
+//---------- implementation of L2 norm and related functions ----------
+
+/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm.
+  * In both cases, it consists in the sum of the square of all the matrix entries.
+  * For vectors, this is also equals to the dot product of \c *this with itself.
   *
   * \sa dot(), norm()
   */
 template<typename Derived>
-inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
+EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
 {
-  return ei_real((*this).cwise().abs2().sum());
+  return numext::real((*this).cwiseAbs2().sum());
 }
 
-/** \returns the \em l2 norm of *this, i.e., for vectors, the square root of the dot product of *this with itself.
+/** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm.
+  * In both cases, it consists in the square root of the sum of the square of all the matrix entries.
+  * For vectors, this is also equals to the square root of the dot product of \c *this with itself.
   *
   * \sa dot(), squaredNorm()
   */
 template<typename Derived>
-inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
+inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
 {
-  return ei_sqrt(squaredNorm());
+  using std::sqrt;
+  return sqrt(squaredNorm());
 }
 
 /** \returns an expression of the quotient of *this by its own norm.
@@ -296,11 +135,11 @@ inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<
   * \sa norm(), normalize()
   */
 template<typename Derived>
-inline const typename MatrixBase<Derived>::PlainMatrixType
+inline const typename MatrixBase<Derived>::PlainObject
 MatrixBase<Derived>::normalized() const
 {
-  typedef typename ei_nested<Derived>::type Nested;
-  typedef typename ei_unref<Nested>::type _Nested;
+  typedef typename internal::nested<Derived>::type Nested;
+  typedef typename internal::remove_reference<Nested>::type _Nested;
   _Nested n(derived());
   return n / n.norm();
 }
@@ -317,6 +156,66 @@ inline void MatrixBase<Derived>::normalize()
   *this /= norm();
 }
 
+//---------- implementation of other norms ----------
+
+namespace internal {
+
+template<typename Derived, int p>
+struct lpNorm_selector
+{
+  typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
+  static inline RealScalar run(const MatrixBase<Derived>& m)
+  {
+    using std::pow;
+    return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
+  }
+};
+
+template<typename Derived>
+struct lpNorm_selector<Derived, 1>
+{
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  {
+    return m.cwiseAbs().sum();
+  }
+};
+
+template<typename Derived>
+struct lpNorm_selector<Derived, 2>
+{
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  {
+    return m.norm();
+  }
+};
+
+template<typename Derived>
+struct lpNorm_selector<Derived, Infinity>
+{
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  {
+    return m.cwiseAbs().maxCoeff();
+  }
+};
+
+} // end namespace internal
+
+/** \returns the \f$ \ell^p \f$ norm of *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values
+  *          of the coefficients of *this. If \a p is the special value \a Eigen::Infinity, this function returns the \f$ \ell^\infty \f$
+  *          norm, that is the maximum of the absolute values of the coefficients of *this.
+  *
+  * \sa norm()
+  */
+template<typename Derived>
+template<int p>
+inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
+MatrixBase<Derived>::lpNorm() const
+{
+  return internal::lpNorm_selector<Derived, p>::run(*this);
+}
+
+//---------- implementation of isOrthogonal / isUnitary ----------
+
 /** \returns true if *this is approximately orthogonal to \a other,
   *          within the precision given by \a prec.
   *
@@ -326,11 +225,11 @@ inline void MatrixBase<Derived>::normalize()
 template<typename Derived>
 template<typename OtherDerived>
 bool MatrixBase<Derived>::isOrthogonal
-(const MatrixBase<OtherDerived>& other, RealScalar prec) const
+(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const
 {
-  typename ei_nested<Derived,2>::type nested(derived());
-  typename ei_nested<OtherDerived,2>::type otherNested(other.derived());
-  return ei_abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
+  typename internal::nested<Derived,2>::type nested(derived());
+  typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
+  return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
 }
 
 /** \returns true if *this is approximately an unitary matrix,
@@ -345,17 +244,20 @@ bool MatrixBase<Derived>::isOrthogonal
   * Output: \verbinclude MatrixBase_isUnitary.out
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isUnitary(RealScalar prec) const
+bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const
 {
   typename Derived::Nested nested(derived());
-  for(int i = 0; i < cols(); ++i)
+  for(Index i = 0; i < cols(); ++i)
   {
-    if(!ei_isApprox(nested.col(i).squaredNorm(), static_cast<Scalar>(1), prec))
+    if(!internal::isApprox(nested.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
       return false;
-    for(int j = 0; j < i; ++j)
-      if(!ei_isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast<Scalar>(1), prec))
+    for(Index j = 0; j < i; ++j)
+      if(!internal::isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast<Scalar>(1), prec))
         return false;
   }
   return true;
 }
+
+} // end namespace Eigen
+
 #endif // EIGEN_DOT_H

Eigen/src/Core/EigenBase.h

@@ -0,0 +1,131 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_EIGENBASE_H
+#define EIGEN_EIGENBASE_H
+
+namespace Eigen {
+
+/** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
+  *
+  * In other words, an EigenBase object is an object that can be copied into a MatrixBase.
+  *
+  * Besides MatrixBase-derived classes, this also includes special matrix classes such as diagonal matrices, etc.
+  *
+  * Notice that this class is trivial, it is only used to disambiguate overloaded functions.
+  *
+  * \sa \ref TopicClassHierarchy
+  */
+template<typename Derived> struct EigenBase
+{
+//   typedef typename internal::plain_matrix_type<Derived>::type PlainObject;
+
+  typedef typename internal::traits<Derived>::StorageKind StorageKind;
+  typedef typename internal::traits<Derived>::Index Index;
+
+  /** \returns a reference to the derived object */
+  Derived& derived() { return *static_cast<Derived*>(this); }
+  /** \returns a const reference to the derived object */
+  const Derived& derived() const { return *static_cast<const Derived*>(this); }
+
+  inline Derived& const_cast_derived() const
+  { return *static_cast<Derived*>(const_cast<EigenBase*>(this)); }
+  inline const Derived& const_derived() const
+  { return *static_cast<const Derived*>(this); }
+
+  /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
+  inline Index rows() const { return derived().rows(); }
+  /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
+  inline Index cols() const { return derived().cols(); }
+  /** \returns the number of coefficients, which is rows()*cols().
+    * \sa rows(), cols(), SizeAtCompileTime. */
+  inline Index size() const { return rows() * cols(); }
+
+  /** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */
+  template<typename Dest> inline void evalTo(Dest& dst) const
+  { derived().evalTo(dst); }
+
+  /** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */
+  template<typename Dest> inline void addTo(Dest& dst) const
+  {
+    // This is the default implementation,
+    // derived class can reimplement it in a more optimized way.
+    typename Dest::PlainObject res(rows(),cols());
+    evalTo(res);
+    dst += res;
+  }
+
+  /** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */
+  template<typename Dest> inline void subTo(Dest& dst) const
+  {
+    // This is the default implementation,
+    // derived class can reimplement it in a more optimized way.
+    typename Dest::PlainObject res(rows(),cols());
+    evalTo(res);
+    dst -= res;
+  }
+
+  /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */
+  template<typename Dest> inline void applyThisOnTheRight(Dest& dst) const
+  {
+    // This is the default implementation,
+    // derived class can reimplement it in a more optimized way.
+    dst = dst * this->derived();
+  }
+
+  /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */
+  template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
+  {
+    // This is the default implementation,
+    // derived class can reimplement it in a more optimized way.
+    dst = this->derived() * dst;
+  }
+
+};
+
+/***************************************************************************
+* Implementation of matrix base methods
+***************************************************************************/
+
+/** \brief Copies the generic expression \a other into *this.
+  *
+  * \details The expression must provide a (templated) evalTo(Derived& dst) const
+  * function which does the actual job. In practice, this allows any user to write
+  * its own special matrix without having to modify MatrixBase
+  *
+  * \returns a reference to *this.
+  */
+template<typename Derived>
+template<typename OtherDerived>
+Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
+{
+  other.derived().evalTo(derived());
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
+{
+  other.derived().addTo(derived());
+  return derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
+{
+  other.derived().subTo(derived());
+  return derived();
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_EIGENBASE_H

Eigen/src/Core/Flagged.h

@@ -1,31 +1,19 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FLAGGED_H
 #define EIGEN_FLAGGED_H
 
+namespace Eigen { 
+
 /** \class Flagged
+  * \ingroup Core_Module
   *
   * \brief Expression with modified flags
   *
@@ -39,108 +27,114 @@
   *
   * \sa MatrixBase::flagged()
   */
+
+namespace internal {
 template<typename ExpressionType, unsigned int Added, unsigned int Removed>
-struct ei_traits<Flagged<ExpressionType, Added, Removed> > : ei_traits<ExpressionType>
+struct traits<Flagged<ExpressionType, Added, Removed> > : traits<ExpressionType>
 {
   enum { Flags = (ExpressionType::Flags | Added) & ~Removed };
 };
+}
 
 template<typename ExpressionType, unsigned int Added, unsigned int Removed> class Flagged
   : public MatrixBase<Flagged<ExpressionType, Added, Removed> >
 {
   public:
 
-    EIGEN_GENERIC_PUBLIC_INTERFACE(Flagged)
-    typedef typename ei_meta_if<ei_must_nest_by_value<ExpressionType>::ret,
-        ExpressionType, const ExpressionType&>::ret ExpressionTypeNested;
+    typedef MatrixBase<Flagged> Base;
+    
+    EIGEN_DENSE_PUBLIC_INTERFACE(Flagged)
+    typedef typename internal::conditional<internal::must_nest_by_value<ExpressionType>::ret,
+        ExpressionType, const ExpressionType&>::type ExpressionTypeNested;
     typedef typename ExpressionType::InnerIterator InnerIterator;
 
     inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {}
 
-    inline int rows() const { return m_matrix.rows(); }
-    inline int cols() const { return m_matrix.cols(); }
-    inline int stride() const { return m_matrix.stride(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+    inline Index outerStride() const { return m_matrix.outerStride(); }
+    inline Index innerStride() const { return m_matrix.innerStride(); }
 
-    inline const Scalar coeff(int row, int col) const
+    inline CoeffReturnType coeff(Index row, Index col) const
     {
       return m_matrix.coeff(row, col);
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline CoeffReturnType coeff(Index index) const
+    {
+      return m_matrix.coeff(index);
+    }
+    
+    inline const Scalar& coeffRef(Index row, Index col) const
     {
       return m_matrix.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const Scalar coeff(int index) const
+    inline const Scalar& coeffRef(Index index) const
     {
-      return m_matrix.coeff(index);
+      return m_matrix.const_cast_derived().coeffRef(index);
     }
 
-    inline Scalar& coeffRef(int index)
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      return m_matrix.const_cast_derived().coeffRef(row, col);
+    }
+
+    inline Scalar& coeffRef(Index index)
     {
       return m_matrix.const_cast_derived().coeffRef(index);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int row, int col) const
+    inline const PacketScalar packet(Index row, Index col) const
     {
       return m_matrix.template packet<LoadMode>(row, col);
     }
 
     template<int LoadMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
     {
       m_matrix.const_cast_derived().template writePacket<LoadMode>(row, col, x);
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(int index) const
+    inline const PacketScalar packet(Index index) const
     {
       return m_matrix.template packet<LoadMode>(index);
     }
 
     template<int LoadMode>
-    inline void writePacket(int index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& x)
     {
       m_matrix.const_cast_derived().template writePacket<LoadMode>(index, x);
     }
 
     const ExpressionType& _expression() const { return m_matrix; }
 
+    template<typename OtherDerived>
+    typename ExpressionType::PlainObject solveTriangular(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived>
+    void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
+
   protected:
     ExpressionTypeNested m_matrix;
 };
 
-/** \returns an expression of *this with added flags
+/** \returns an expression of *this with added and removed flags
   *
-  * \addexample MarkExample \label How to mark a triangular matrix as triangular
+  * This is mostly for internal use.
   *
-  * Example: \include MatrixBase_marked.cpp
-  * Output: \verbinclude MatrixBase_marked.out
-  *
-  * \sa class Flagged, extract(), part()
+  * \sa class Flagged
   */
 template<typename Derived>
-template<unsigned int Added>
-inline const Flagged<Derived, Added, 0>
-MatrixBase<Derived>::marked() const
+template<unsigned int Added,unsigned int Removed>
+inline const Flagged<Derived, Added, Removed>
+DenseBase<Derived>::flagged() const
 {
   return derived();
 }
 
-/** \returns an expression of *this with the following flags removed:
-  * EvalBeforeNestingBit and EvalBeforeAssigningBit.
-  *
-  * Example: \include MatrixBase_lazy.cpp
-  * Output: \verbinclude MatrixBase_lazy.out
-  *
-  * \sa class Flagged, marked()
-  */
-template<typename Derived>
-inline const Flagged<Derived, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit>
-MatrixBase<Derived>::lazy() const
-{
-  return derived();
-}
+} // end namespace Eigen
 
 #endif // EIGEN_FLAGGED_H

Eigen/src/Core/ForceAlignedAccess.h

@@ -0,0 +1,146 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_FORCEALIGNEDACCESS_H
+#define EIGEN_FORCEALIGNEDACCESS_H
+
+namespace Eigen {
+
+/** \class ForceAlignedAccess
+  * \ingroup Core_Module
+  *
+  * \brief Enforce aligned packet loads and stores regardless of what is requested
+  *
+  * \param ExpressionType the type of the object of which we are forcing aligned packet access
+  *
+  * This class is the return type of MatrixBase::forceAlignedAccess()
+  * and most of the time this is the only way it is used.
+  *
+  * \sa MatrixBase::forceAlignedAccess()
+  */
+
+namespace internal {
+template<typename ExpressionType>
+struct traits<ForceAlignedAccess<ExpressionType> > : public traits<ExpressionType>
+{};
+}
+
+template<typename ExpressionType> class ForceAlignedAccess
+  : public internal::dense_xpr_base< ForceAlignedAccess<ExpressionType> >::type
+{
+  public:
+
+    typedef typename internal::dense_xpr_base<ForceAlignedAccess>::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess)
+
+    inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {}
+
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
+
+    inline const CoeffReturnType coeff(Index row, Index col) const
+    {
+      return m_expression.coeff(row, col);
+    }
+
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      return m_expression.const_cast_derived().coeffRef(row, col);
+    }
+
+    inline const CoeffReturnType coeff(Index index) const
+    {
+      return m_expression.coeff(index);
+    }
+
+    inline Scalar& coeffRef(Index index)
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index row, Index col) const
+    {
+      return m_expression.template packet<Aligned>(row, col);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    {
+      m_expression.const_cast_derived().template writePacket<Aligned>(row, col, x);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index index) const
+    {
+      return m_expression.template packet<Aligned>(index);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index index, const PacketScalar& x)
+    {
+      m_expression.const_cast_derived().template writePacket<Aligned>(index, x);
+    }
+
+    operator const ExpressionType&() const { return m_expression; }
+
+  protected:
+    const ExpressionType& m_expression;
+
+  private:
+    ForceAlignedAccess& operator=(const ForceAlignedAccess&);
+};
+
+/** \returns an expression of *this with forced aligned access
+  * \sa forceAlignedAccessIf(),class ForceAlignedAccess
+  */
+template<typename Derived>
+inline const ForceAlignedAccess<Derived>
+MatrixBase<Derived>::forceAlignedAccess() const
+{
+  return ForceAlignedAccess<Derived>(derived());
+}
+
+/** \returns an expression of *this with forced aligned access
+  * \sa forceAlignedAccessIf(), class ForceAlignedAccess
+  */
+template<typename Derived>
+inline ForceAlignedAccess<Derived>
+MatrixBase<Derived>::forceAlignedAccess()
+{
+  return ForceAlignedAccess<Derived>(derived());
+}
+
+/** \returns an expression of *this with forced aligned access if \a Enable is true.
+  * \sa forceAlignedAccess(), class ForceAlignedAccess
+  */
+template<typename Derived>
+template<bool Enable>
+inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type
+MatrixBase<Derived>::forceAlignedAccessIf() const
+{
+  return derived();
+}
+
+/** \returns an expression of *this with forced aligned access if \a Enable is true.
+  * \sa forceAlignedAccess(), class ForceAlignedAccess
+  */
+template<typename Derived>
+template<bool Enable>
+inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type
+MatrixBase<Derived>::forceAlignedAccessIf()
+{
+  return derived();
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_FORCEALIGNEDACCESS_H

Eigen/src/Core/Fuzzy.h

@@ -1,32 +1,80 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FUZZY_H
 #define EIGEN_FUZZY_H
 
-#ifndef EIGEN_LEGACY_COMPARES
+namespace Eigen { 
+
+namespace internal
+{
+
+template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
+struct isApprox_selector
+{
+  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
+  {
+    using std::min;
+    typename internal::nested<Derived,2>::type nested(x);
+    typename internal::nested<OtherDerived,2>::type otherNested(y);
+    return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
+  }
+};
+
+template<typename Derived, typename OtherDerived>
+struct isApprox_selector<Derived, OtherDerived, true>
+{
+  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&)
+  {
+    return x.matrix() == y.matrix();
+  }
+};
+
+template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
+struct isMuchSmallerThan_object_selector
+{
+  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
+  {
+    return x.cwiseAbs2().sum() <= numext::abs2(prec) * y.cwiseAbs2().sum();
+  }
+};
+
+template<typename Derived, typename OtherDerived>
+struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
+{
+  static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&)
+  {
+    return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
+  }
+};
+
+template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
+struct isMuchSmallerThan_scalar_selector
+{
+  static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec)
+  {
+    return x.cwiseAbs2().sum() <= numext::abs2(prec * y);
+  }
+};
+
+template<typename Derived>
+struct isMuchSmallerThan_scalar_selector<Derived, true>
+{
+  static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&)
+  {
+    return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
+  }
+};
+
+} // end namespace internal
+
 
 /** \returns \c true if \c *this is approximately equal to \a other, within the precision
   * determined by \a prec.
@@ -40,21 +88,19 @@
   * \note Because of the multiplicativeness of this comparison, one can't use this function
   * to check whether \c *this is approximately equal to the zero matrix or vector.
   * Indeed, \c isApprox(zero) returns false unless \c *this itself is exactly the zero matrix
-  * or vector. If you want to test whether \c *this is zero, use ei_isMuchSmallerThan(const
+  * or vector. If you want to test whether \c *this is zero, use internal::isMuchSmallerThan(const
   * RealScalar&, RealScalar) instead.
   *
-  * \sa ei_isMuchSmallerThan(const RealScalar&, RealScalar) const
+  * \sa internal::isMuchSmallerThan(const RealScalar&, RealScalar) const
   */
 template<typename Derived>
 template<typename OtherDerived>
-bool MatrixBase<Derived>::isApprox(
-  const MatrixBase<OtherDerived>& other,
-  typename NumTraits<Scalar>::Real prec
+bool DenseBase<Derived>::isApprox(
+  const DenseBase<OtherDerived>& other,
+  const RealScalar& prec
 ) const
 {
-  const typename ei_nested<Derived,2>::type nested(derived());
-  const typename ei_nested<OtherDerived,2>::type otherNested(other.derived());
-  return (nested - otherNested).cwise().abs2().sum() <= prec * prec * std::min(nested.cwise().abs2().sum(), otherNested.cwise().abs2().sum());
+  return internal::isApprox_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
 }
 
 /** \returns \c true if the norm of \c *this is much smaller than \a other,
@@ -68,15 +114,15 @@ bool MatrixBase<Derived>::isApprox(
   * the value of the reference scalar \a other should come from the Hilbert-Schmidt norm
   * of a reference matrix of same dimensions.
   *
-  * \sa isApprox(), isMuchSmallerThan(const MatrixBase<OtherDerived>&, RealScalar) const
+  * \sa isApprox(), isMuchSmallerThan(const DenseBase<OtherDerived>&, RealScalar) const
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isMuchSmallerThan(
+bool DenseBase<Derived>::isMuchSmallerThan(
   const typename NumTraits<Scalar>::Real& other,
-  typename NumTraits<Scalar>::Real prec
+  const RealScalar& prec
 ) const
 {
-  return cwise().abs2().sum() <= prec * prec * other * other;
+  return internal::isMuchSmallerThan_scalar_selector<Derived>::run(derived(), other, prec);
 }
 
 /** \returns \c true if the norm of \c *this is much smaller than the norm of \a other,
@@ -91,144 +137,14 @@ bool MatrixBase<Derived>::isMuchSmallerThan(
   */
 template<typename Derived>
 template<typename OtherDerived>
-bool MatrixBase<Derived>::isMuchSmallerThan(
-  const MatrixBase<OtherDerived>& other,
-  typename NumTraits<Scalar>::Real prec
+bool DenseBase<Derived>::isMuchSmallerThan(
+  const DenseBase<OtherDerived>& other,
+  const RealScalar& prec
 ) const
 {
-  return this->cwise().abs2().sum() <= prec * prec * other.cwise().abs2().sum();
+  return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
 }
 
-#else
-
-template<typename Derived, typename OtherDerived=Derived, bool IsVector=Derived::IsVectorAtCompileTime>
-struct ei_fuzzy_selector;
-
-/** \returns \c true if \c *this is approximately equal to \a other, within the precision
-  * determined by \a prec.
-  *
-  * \note The fuzzy compares are done multiplicatively. Two vectors \f$ v \f$ and \f$ w \f$
-  * are considered to be approximately equal within precision \f$ p \f$ if
-  * \f[ \Vert v - w \Vert \leqslant p\,\min(\Vert v\Vert, \Vert w\Vert). \f]
-  * For matrices, the comparison is done on all columns.
-  *
-  * \note Because of the multiplicativeness of this comparison, one can't use this function
-  * to check whether \c *this is approximately equal to the zero matrix or vector.
-  * Indeed, \c isApprox(zero) returns false unless \c *this itself is exactly the zero matrix
-  * or vector. If you want to test whether \c *this is zero, use ei_isMuchSmallerThan(const
-  * RealScalar&, RealScalar) instead.
-  *
-  * \sa ei_isMuchSmallerThan(const RealScalar&, RealScalar) const
-  */
-template<typename Derived>
-template<typename OtherDerived>
-bool MatrixBase<Derived>::isApprox(
-  const MatrixBase<OtherDerived>& other,
-  typename NumTraits<Scalar>::Real prec
-) const
-{
-  return ei_fuzzy_selector<Derived,OtherDerived>::isApprox(derived(), other.derived(), prec);
-}
-
-/** \returns \c true if the norm of \c *this is much smaller than \a other,
-  * within the precision determined by \a prec.
-  *
-  * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is
-  * considered to be much smaller than \f$ x \f$ within precision \f$ p \f$ if
-  * \f[ \Vert v \Vert \leqslant p\,\vert x\vert. \f]
-  * For matrices, the comparison is done on all columns.
-  *
-  * \sa isApprox(), isMuchSmallerThan(const MatrixBase<OtherDerived>&, RealScalar) const
-  */
-template<typename Derived>
-bool MatrixBase<Derived>::isMuchSmallerThan(
-  const typename NumTraits<Scalar>::Real& other,
-  typename NumTraits<Scalar>::Real prec
-) const
-{
-  return ei_fuzzy_selector<Derived>::isMuchSmallerThan(derived(), other, prec);
-}
-
-/** \returns \c true if the norm of \c *this is much smaller than the norm of \a other,
-  * within the precision determined by \a prec.
-  *
-  * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is
-  * considered to be much smaller than a vector \f$ w \f$ within precision \f$ p \f$ if
-  * \f[ \Vert v \Vert \leqslant p\,\Vert w\Vert. \f]
-  * For matrices, the comparison is done on all columns.
-  *
-  * \sa isApprox(), isMuchSmallerThan(const RealScalar&, RealScalar) const
-  */
-template<typename Derived>
-template<typename OtherDerived>
-bool MatrixBase<Derived>::isMuchSmallerThan(
-  const MatrixBase<OtherDerived>& other,
-  typename NumTraits<Scalar>::Real prec
-) const
-{
-  return ei_fuzzy_selector<Derived,OtherDerived>::isMuchSmallerThan(derived(), other.derived(), prec);
-}
-
-
-template<typename Derived, typename OtherDerived>
-struct ei_fuzzy_selector<Derived,OtherDerived,true>
-{
-  typedef typename Derived::RealScalar RealScalar;
-  static bool isApprox(const Derived& self, const OtherDerived& other, RealScalar prec)
-  {
-    EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
-    ei_assert(self.size() == other.size());
-    return((self - other).squaredNorm() <= std::min(self.squaredNorm(), other.squaredNorm()) * prec * prec);
-  }
-  static bool isMuchSmallerThan(const Derived& self, const RealScalar& other, RealScalar prec)
-  {
-    return(self.squaredNorm() <= ei_abs2(other * prec));
-  }
-  static bool isMuchSmallerThan(const Derived& self, const OtherDerived& other, RealScalar prec)
-  {
-    EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
-    ei_assert(self.size() == other.size());
-    return(self.squaredNorm() <= other.squaredNorm() * prec * prec);
-  }
-};
-
-template<typename Derived, typename OtherDerived>
-struct ei_fuzzy_selector<Derived,OtherDerived,false>
-{
-  typedef typename Derived::RealScalar RealScalar;
-  static bool isApprox(const Derived& self, const OtherDerived& other, RealScalar prec)
-  {
-    EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
-    ei_assert(self.rows() == other.rows() && self.cols() == other.cols());
-    typename Derived::Nested nested(self);
-    typename OtherDerived::Nested otherNested(other);
-    for(int i = 0; i < self.cols(); ++i)
-      if((nested.col(i) - otherNested.col(i)).squaredNorm()
-          > std::min(nested.col(i).squaredNorm(), otherNested.col(i).squaredNorm()) * prec * prec)
-        return false;
-    return true;
-  }
-  static bool isMuchSmallerThan(const Derived& self, const RealScalar& other, RealScalar prec)
-  {
-    typename Derived::Nested nested(self);
-    for(int i = 0; i < self.cols(); ++i)
-      if(nested.col(i).squaredNorm() > ei_abs2(other * prec))
-        return false;
-    return true;
-  }
-  static bool isMuchSmallerThan(const Derived& self, const OtherDerived& other, RealScalar prec)
-  {
-    EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
-    ei_assert(self.rows() == other.rows() && self.cols() == other.cols());
-    typename Derived::Nested nested(self);
-    typename OtherDerived::Nested otherNested(other);
-    for(int i = 0; i < self.cols(); ++i)
-      if(nested.col(i).squaredNorm() > otherNested.col(i).squaredNorm() * prec * prec)
-        return false;
-    return true;
-  }
-};
-
-#endif
+} // end namespace Eigen
 
 #endif // EIGEN_FUZZY_H

Eigen/src/Core/GeneralProduct.h

@@ -0,0 +1,635 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_GENERAL_PRODUCT_H
+#define EIGEN_GENERAL_PRODUCT_H
+
+namespace Eigen { 
+
+/** \class GeneralProduct
+  * \ingroup Core_Module
+  *
+  * \brief Expression of the product of two general matrices or vectors
+  *
+  * \param LhsNested the type used to store the left-hand side
+  * \param RhsNested the type used to store the right-hand side
+  * \param ProductMode the type of the product
+  *
+  * This class represents an expression of the product of two general matrices.
+  * We call a general matrix, a dense matrix with full storage. For instance,
+  * This excludes triangular, selfadjoint, and sparse matrices.
+  * It is the return type of the operator* between general matrices. Its template
+  * arguments are determined automatically by ProductReturnType. Therefore,
+  * GeneralProduct should never be used direclty. To determine the result type of a
+  * function which involves a matrix product, use ProductReturnType::Type.
+  *
+  * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
+  */
+template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
+class GeneralProduct;
+
+enum {
+  Large = 2,
+  Small = 3
+};
+
+namespace internal {
+
+template<int Rows, int Cols, int Depth> struct product_type_selector;
+
+template<int Size, int MaxSize> struct product_size_category
+{
+  enum { is_large = MaxSize == Dynamic ||
+                    Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
+         value = is_large  ? Large
+               : Size == 1 ? 1
+                           : Small
+  };
+};
+
+template<typename Lhs, typename Rhs> struct product_type
+{
+  typedef typename remove_all<Lhs>::type _Lhs;
+  typedef typename remove_all<Rhs>::type _Rhs;
+  enum {
+    MaxRows  = _Lhs::MaxRowsAtCompileTime,
+    Rows  = _Lhs::RowsAtCompileTime,
+    MaxCols  = _Rhs::MaxColsAtCompileTime,
+    Cols  = _Rhs::ColsAtCompileTime,
+    MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
+                                           _Rhs::MaxRowsAtCompileTime),
+    Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
+                                        _Rhs::RowsAtCompileTime),
+    LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+  };
+
+  // the splitting into different lines of code here, introducing the _select enums and the typedef below,
+  // is to work around an internal compiler error with gcc 4.1 and 4.2.
+private:
+  enum {
+    rows_select = product_size_category<Rows,MaxRows>::value,
+    cols_select = product_size_category<Cols,MaxCols>::value,
+    depth_select = product_size_category<Depth,MaxDepth>::value
+  };
+  typedef product_type_selector<rows_select, cols_select, depth_select> selector;
+
+public:
+  enum {
+    value = selector::ret
+  };
+#ifdef EIGEN_DEBUG_PRODUCT
+  static void debug()
+  {
+      EIGEN_DEBUG_VAR(Rows);
+      EIGEN_DEBUG_VAR(Cols);
+      EIGEN_DEBUG_VAR(Depth);
+      EIGEN_DEBUG_VAR(rows_select);
+      EIGEN_DEBUG_VAR(cols_select);
+      EIGEN_DEBUG_VAR(depth_select);
+      EIGEN_DEBUG_VAR(value);
+  }
+#endif
+};
+
+
+/* The following allows to select the kind of product at compile time
+ * based on the three dimensions of the product.
+ * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
+// FIXME I'm not sure the current mapping is the ideal one.
+template<int M, int N>  struct product_type_selector<M,N,1>              { enum { ret = OuterProduct }; };
+template<int Depth>     struct product_type_selector<1,    1,    Depth>  { enum { ret = InnerProduct }; };
+template<>              struct product_type_selector<1,    1,    1>      { enum { ret = InnerProduct }; };
+template<>              struct product_type_selector<Small,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<1,    Small,Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small, Large, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
+template<>              struct product_type_selector<Large, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
+template<>              struct product_type_selector<1,    Large,Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<1,    Large,Large>  { enum { ret = GemvProduct }; };
+template<>              struct product_type_selector<1,    Small,Large>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Large,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Large,1,    Large>  { enum { ret = GemvProduct }; };
+template<>              struct product_type_selector<Small,1,    Large>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small,Small,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Small,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Small,Large,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Large,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Small,Small>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Small,Large,Small>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Large,Small>  { enum { ret = GemmProduct }; };
+
+} // end namespace internal
+
+/** \class ProductReturnType
+  * \ingroup Core_Module
+  *
+  * \brief Helper class to get the correct and optimized returned type of operator*
+  *
+  * \param Lhs the type of the left-hand side
+  * \param Rhs the type of the right-hand side
+  * \param ProductMode the type of the product (determined automatically by internal::product_mode)
+  *
+  * This class defines the typename Type representing the optimized product expression
+  * between two matrix expressions. In practice, using ProductReturnType<Lhs,Rhs>::Type
+  * is the recommended way to define the result type of a function returning an expression
+  * which involve a matrix product. The class Product should never be
+  * used directly.
+  *
+  * \sa class Product, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
+  */
+template<typename Lhs, typename Rhs, int ProductType>
+struct ProductReturnType
+{
+  // TODO use the nested type to reduce instanciations ????
+//   typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
+//   typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
+
+  typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
+};
+
+template<typename Lhs, typename Rhs>
+struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
+{
+  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
+  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
+  typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
+};
+
+template<typename Lhs, typename Rhs>
+struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
+{
+  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
+  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
+  typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
+};
+
+// this is a workaround for sun CC
+template<typename Lhs, typename Rhs>
+struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
+{};
+
+/***********************************************************************
+*  Implementation of Inner Vector Vector Product
+***********************************************************************/
+
+// FIXME : maybe the "inner product" could return a Scalar
+// instead of a 1x1 matrix ??
+// Pro: more natural for the user
+// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
+// product ends up to a row-vector times col-vector product... To tackle this use
+// case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
+
+namespace internal {
+
+template<typename Lhs, typename Rhs>
+struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
+ : traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
+{};
+
+}
+
+template<typename Lhs, typename Rhs>
+class GeneralProduct<Lhs, Rhs, InnerProduct>
+  : internal::no_assignment_operator,
+    public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
+{
+    typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
+  public:
+    GeneralProduct(const Lhs& lhs, const Rhs& rhs)
+    {
+      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
+        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+
+      Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
+    }
+
+    /** Convertion to scalar */
+    operator const typename Base::Scalar() const {
+      return Base::coeff(0,0);
+    }
+};
+
+/***********************************************************************
+*  Implementation of Outer Vector Vector Product
+***********************************************************************/
+
+namespace internal {
+
+// Column major
+template<typename ProductType, typename Dest, typename Func>
+EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const false_type&)
+{
+  typedef typename Dest::Index Index;
+  // FIXME make sure lhs is sequentially stored
+  // FIXME not very good if rhs is real and lhs complex while alpha is real too
+  const Index cols = dest.cols();
+  for (Index j=0; j<cols; ++j)
+    func(dest.col(j), prod.rhs().coeff(0,j) * prod.lhs());
+}
+
+// Row major
+template<typename ProductType, typename Dest, typename Func>
+EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const true_type&) {
+  typedef typename Dest::Index Index;
+  // FIXME make sure rhs is sequentially stored
+  // FIXME not very good if lhs is real and rhs complex while alpha is real too
+  const Index rows = dest.rows();
+  for (Index i=0; i<rows; ++i)
+    func(dest.row(i), prod.lhs().coeff(i,0) * prod.rhs());
+}
+
+template<typename Lhs, typename Rhs>
+struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
+ : traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
+{};
+
+}
+
+template<typename Lhs, typename Rhs>
+class GeneralProduct<Lhs, Rhs, OuterProduct>
+  : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
+{
+    template<typename T> struct IsRowMajor : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
+    
+  public:
+    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
+
+    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+    {
+      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
+        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+    }
+    
+    struct set  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived()  = src; } };
+    struct add  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } };
+    struct sub  { template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } };
+    struct adds {
+      Scalar m_scale;
+      adds(const Scalar& s) : m_scale(s) {}
+      template<typename Dst, typename Src> void operator()(const Dst& dst, const Src& src) const {
+        dst.const_cast_derived() += m_scale * src;
+      }
+    };
+    
+    template<typename Dest>
+    inline void evalTo(Dest& dest) const {
+      internal::outer_product_selector_run(*this, dest, set(), IsRowMajor<Dest>());
+    }
+    
+    template<typename Dest>
+    inline void addTo(Dest& dest) const {
+      internal::outer_product_selector_run(*this, dest, add(), IsRowMajor<Dest>());
+    }
+
+    template<typename Dest>
+    inline void subTo(Dest& dest) const {
+      internal::outer_product_selector_run(*this, dest, sub(), IsRowMajor<Dest>());
+    }
+
+    template<typename Dest> void scaleAndAddTo(Dest& dest, const Scalar& alpha) const
+    {
+      internal::outer_product_selector_run(*this, dest, adds(alpha), IsRowMajor<Dest>());
+    }
+};
+
+/***********************************************************************
+*  Implementation of General Matrix Vector Product
+***********************************************************************/
+
+/*  According to the shape/flags of the matrix we have to distinghish 3 different cases:
+ *   1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
+ *   2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
+ *   3 - all other cases are handled using a simple loop along the outer-storage direction.
+ *  Therefore we need a lower level meta selector.
+ *  Furthermore, if the matrix is the rhs, then the product has to be transposed.
+ */
+namespace internal {
+
+template<typename Lhs, typename Rhs>
+struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
+ : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
+{};
+
+template<int Side, int StorageOrder, bool BlasCompatible>
+struct gemv_selector;
+
+} // end namespace internal
+
+template<typename Lhs, typename Rhs>
+class GeneralProduct<Lhs, Rhs, GemvProduct>
+  : public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
+{
+  public:
+    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
+
+    typedef typename Lhs::Scalar LhsScalar;
+    typedef typename Rhs::Scalar RhsScalar;
+
+    GeneralProduct(const Lhs& a_lhs, const Rhs& a_rhs) : Base(a_lhs,a_rhs)
+    {
+//       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
+//         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+    }
+
+    enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
+    typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
+
+    template<typename Dest> void scaleAndAddTo(Dest& dst, const Scalar& alpha) const
+    {
+      eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
+      internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
+                       bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
+    }
+};
+
+namespace internal {
+
+// The vector is on the left => transposition
+template<int StorageOrder, bool BlasCompatible>
+struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
+  {
+    Transpose<Dest> destT(dest);
+    enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
+    gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
+      ::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
+        (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
+  }
+};
+
+template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
+
+template<typename Scalar,int Size,int MaxSize>
+struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
+{
+  EIGEN_STRONG_INLINE  Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
+};
+
+template<typename Scalar,int Size>
+struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
+{
+  EIGEN_STRONG_INLINE Scalar* data() { return 0; }
+};
+
+template<typename Scalar,int Size,int MaxSize>
+struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
+{
+  #if EIGEN_ALIGN_STATICALLY
+  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
+  EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
+  #else
+  // Some architectures cannot align on the stack,
+  // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
+  enum {
+    ForceAlignment  = internal::packet_traits<Scalar>::Vectorizable,
+    PacketSize      = internal::packet_traits<Scalar>::size
+  };
+  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
+  EIGEN_STRONG_INLINE Scalar* data() {
+    return ForceAlignment
+            ? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
+            : m_data.array;
+  }
+  #endif
+};
+
+template<> struct gemv_selector<OnTheRight,ColMajor,true>
+{
+  template<typename ProductType, typename Dest>
+  static inline void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
+  {
+    typedef typename ProductType::Index Index;
+    typedef typename ProductType::LhsScalar   LhsScalar;
+    typedef typename ProductType::RhsScalar   RhsScalar;
+    typedef typename ProductType::Scalar      ResScalar;
+    typedef typename ProductType::RealScalar  RealScalar;
+    typedef typename ProductType::ActualLhsType ActualLhsType;
+    typedef typename ProductType::ActualRhsType ActualRhsType;
+    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
+    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
+    typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
+
+    ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
+    ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
+                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
+
+    enum {
+      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
+      // on, the other hand it is good for the cache to pack the vector anyways...
+      EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
+      ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
+      MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
+    };
+
+    gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
+
+    bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
+    bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
+    
+    RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
+
+    ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
+                                                  evalToDest ? dest.data() : static_dest.data());
+    
+    if(!evalToDest)
+    {
+      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      int size = dest.size();
+      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      #endif
+      if(!alphaIsCompatible)
+      {
+        MappedDest(actualDestPtr, dest.size()).setZero();
+        compatibleAlpha = RhsScalar(1);
+      }
+      else
+        MappedDest(actualDestPtr, dest.size()) = dest;
+    }
+
+    general_matrix_vector_product
+      <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
+        actualLhs.rows(), actualLhs.cols(),
+        actualLhs.data(), actualLhs.outerStride(),
+        actualRhs.data(), actualRhs.innerStride(),
+        actualDestPtr, 1,
+        compatibleAlpha);
+
+    if (!evalToDest)
+    {
+      if(!alphaIsCompatible)
+        dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
+      else
+        dest = MappedDest(actualDestPtr, dest.size());
+    }
+  }
+};
+
+template<> struct gemv_selector<OnTheRight,RowMajor,true>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
+  {
+    typedef typename ProductType::LhsScalar LhsScalar;
+    typedef typename ProductType::RhsScalar RhsScalar;
+    typedef typename ProductType::Scalar    ResScalar;
+    typedef typename ProductType::Index Index;
+    typedef typename ProductType::ActualLhsType ActualLhsType;
+    typedef typename ProductType::ActualRhsType ActualRhsType;
+    typedef typename ProductType::_ActualRhsType _ActualRhsType;
+    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
+    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
+
+    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
+    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
+                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
+
+    enum {
+      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
+      // on, the other hand it is good for the cache to pack the vector anyways...
+      DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
+    };
+
+    gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
+
+    ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
+        DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
+
+    if(!DirectlyUseRhs)
+    {
+      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      int size = actualRhs.size();
+      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      #endif
+      Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
+    }
+
+    general_matrix_vector_product
+      <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
+        actualLhs.rows(), actualLhs.cols(),
+        actualLhs.data(), actualLhs.outerStride(),
+        actualRhsPtr, 1,
+        dest.data(), dest.innerStride(),
+        actualAlpha);
+  }
+};
+
+template<> struct gemv_selector<OnTheRight,ColMajor,false>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
+  {
+    typedef typename Dest::Index Index;
+    // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
+    const Index size = prod.rhs().rows();
+    for(Index k=0; k<size; ++k)
+      dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
+  }
+};
+
+template<> struct gemv_selector<OnTheRight,RowMajor,false>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha)
+  {
+    typedef typename Dest::Index Index;
+    // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
+    const Index rows = prod.rows();
+    for(Index i=0; i<rows; ++i)
+      dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
+  }
+};
+
+} // end namespace internal
+
+/***************************************************************************
+* Implementation of matrix base methods
+***************************************************************************/
+
+/** \returns the matrix product of \c *this and \a other.
+  *
+  * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
+  *
+  * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
+  */
+template<typename Derived>
+template<typename OtherDerived>
+inline const typename ProductReturnType<Derived, OtherDerived>::Type
+MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
+{
+  // A note regarding the function declaration: In MSVC, this function will sometimes
+  // not be inlined since DenseStorage is an unwindable object for dynamic
+  // matrices and product types are holding a member to store the result.
+  // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
+  enum {
+    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
+                   || OtherDerived::RowsAtCompileTime==Dynamic
+                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
+    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
+    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
+  };
+  // note to the lost user:
+  //    * for a dot product use: v1.dot(v2)
+  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
+    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
+    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
+  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
+#ifdef EIGEN_DEBUG_PRODUCT
+  internal::product_type<Derived,OtherDerived>::debug();
+#endif
+  return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+}
+
+/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
+  *
+  * The returned product will behave like any other expressions: the coefficients of the product will be
+  * computed once at a time as requested. This might be useful in some extremely rare cases when only
+  * a small and no coherent fraction of the result's coefficients have to be computed.
+  *
+  * \warning This version of the matrix product can be much much slower. So use it only if you know
+  * what you are doing and that you measured a true speed improvement.
+  *
+  * \sa operator*(const MatrixBase&)
+  */
+template<typename Derived>
+template<typename OtherDerived>
+const typename LazyProductReturnType<Derived,OtherDerived>::Type
+MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
+{
+  enum {
+    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
+                   || OtherDerived::RowsAtCompileTime==Dynamic
+                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
+    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
+    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
+  };
+  // note to the lost user:
+  //    * for a dot product use: v1.dot(v2)
+  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
+    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
+    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
+  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
+
+  return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_PRODUCT_H

Eigen/src/Core/GenericPacketMath.h

@@ -1,31 +1,20 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERIC_PACKET_MATH_H
 #define EIGEN_GENERIC_PACKET_MATH_H
 
+namespace Eigen {
+
+namespace internal {
+
 /** \internal
   * \file GenericPacketMath.h
   *
@@ -34,117 +23,328 @@
   * of generic vectorized code.
   */
 
+#ifndef EIGEN_DEBUG_ALIGNED_LOAD
+#define EIGEN_DEBUG_ALIGNED_LOAD
+#endif
+
+#ifndef EIGEN_DEBUG_UNALIGNED_LOAD
+#define EIGEN_DEBUG_UNALIGNED_LOAD
+#endif
+
+#ifndef EIGEN_DEBUG_ALIGNED_STORE
+#define EIGEN_DEBUG_ALIGNED_STORE
+#endif
+
+#ifndef EIGEN_DEBUG_UNALIGNED_STORE
+#define EIGEN_DEBUG_UNALIGNED_STORE
+#endif
+
+struct default_packet_traits
+{
+  enum {
+    HasAdd    = 1,
+    HasSub    = 1,
+    HasMul    = 1,
+    HasNegate = 1,
+    HasAbs    = 1,
+    HasAbs2   = 1,
+    HasMin    = 1,
+    HasMax    = 1,
+    HasConj   = 1,
+    HasSetLinear = 1,
+
+    HasDiv    = 0,
+    HasSqrt   = 0,
+    HasExp    = 0,
+    HasLog    = 0,
+    HasPow    = 0,
+
+    HasSin    = 0,
+    HasCos    = 0,
+    HasTan    = 0,
+    HasASin   = 0,
+    HasACos   = 0,
+    HasATan   = 0
+  };
+};
+
+template<typename T> struct packet_traits : default_packet_traits
+{
+  typedef T type;
+  enum {
+    Vectorizable = 0,
+    size = 1,
+    AlignedOnScalar = 0
+  };
+  enum {
+    HasAdd    = 0,
+    HasSub    = 0,
+    HasMul    = 0,
+    HasNegate = 0,
+    HasAbs    = 0,
+    HasAbs2   = 0,
+    HasMin    = 0,
+    HasMax    = 0,
+    HasConj   = 0,
+    HasSetLinear = 0
+  };
+};
+
 /** \internal \returns a + b (coeff-wise) */
 template<typename Packet> inline Packet
-ei_padd(const Packet& a,
+padd(const Packet& a,
         const Packet& b) { return a+b; }
 
 /** \internal \returns a - b (coeff-wise) */
 template<typename Packet> inline Packet
-ei_psub(const Packet& a,
+psub(const Packet& a,
         const Packet& b) { return a-b; }
 
+/** \internal \returns -a (coeff-wise) */
+template<typename Packet> inline Packet
+pnegate(const Packet& a) { return -a; }
+
+/** \internal \returns conj(a) (coeff-wise) */
+template<typename Packet> inline Packet
+pconj(const Packet& a) { return numext::conj(a); }
+
 /** \internal \returns a * b (coeff-wise) */
 template<typename Packet> inline Packet
-ei_pmul(const Packet& a,
+pmul(const Packet& a,
         const Packet& b) { return a*b; }
 
 /** \internal \returns a / b (coeff-wise) */
 template<typename Packet> inline Packet
-ei_pdiv(const Packet& a,
+pdiv(const Packet& a,
         const Packet& b) { return a/b; }
 
 /** \internal \returns the min of \a a and \a b  (coeff-wise) */
 template<typename Packet> inline Packet
-ei_pmin(const Packet& a,
-        const Packet& b) { return std::min(a, b); }
+pmin(const Packet& a,
+        const Packet& b) { using std::min; return (min)(a, b); }
 
 /** \internal \returns the max of \a a and \a b  (coeff-wise) */
 template<typename Packet> inline Packet
-ei_pmax(const Packet& a,
-        const Packet& b) { return std::max(a, b); }
+pmax(const Packet& a,
+        const Packet& b) { using std::max; return (max)(a, b); }
+
+/** \internal \returns the absolute value of \a a */
+template<typename Packet> inline Packet
+pabs(const Packet& a) { using std::abs; return abs(a); }
+
+/** \internal \returns the bitwise and of \a a and \a b */
+template<typename Packet> inline Packet
+pand(const Packet& a, const Packet& b) { return a & b; }
+
+/** \internal \returns the bitwise or of \a a and \a b */
+template<typename Packet> inline Packet
+por(const Packet& a, const Packet& b) { return a | b; }
+
+/** \internal \returns the bitwise xor of \a a and \a b */
+template<typename Packet> inline Packet
+pxor(const Packet& a, const Packet& b) { return a ^ b; }
+
+/** \internal \returns the bitwise andnot of \a a and \a b */
+template<typename Packet> inline Packet
+pandnot(const Packet& a, const Packet& b) { return a & (!b); }
 
 /** \internal \returns a packet version of \a *from, from must be 16 bytes aligned */
-template<typename Scalar> inline typename ei_packet_traits<Scalar>::type
-ei_pload(const Scalar* from) { return *from; }
+template<typename Packet> inline Packet
+pload(const typename unpacket_traits<Packet>::type* from) { return *from; }
 
 /** \internal \returns a packet version of \a *from, (un-aligned load) */
-template<typename Scalar> inline typename ei_packet_traits<Scalar>::type
-ei_ploadu(const Scalar* from) { return *from; }
+template<typename Packet> inline Packet
+ploadu(const typename unpacket_traits<Packet>::type* from) { return *from; }
+
+/** \internal \returns a packet with elements of \a *from duplicated.
+  * For instance, for a packet of 8 elements, 4 scalar will be read from \a *from and
+  * duplicated to form: {from[0],from[0],from[1],from[1],,from[2],from[2],,from[3],from[3]}
+  * Currently, this function is only used for scalar * complex products.
+ */
+template<typename Packet> inline Packet
+ploaddup(const typename unpacket_traits<Packet>::type* from) { return *from; }
 
 /** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
-template<typename Scalar> inline typename ei_packet_traits<Scalar>::type
-ei_pset1(const Scalar& a) { return a; }
+template<typename Packet> inline Packet
+pset1(const typename unpacket_traits<Packet>::type& a) { return a; }
+
+/** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */
+template<typename Scalar> inline typename packet_traits<Scalar>::type
+plset(const Scalar& a) { return a; }
 
 /** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */
-template<typename Scalar, typename Packet> inline void ei_pstore(Scalar* to, const Packet& from)
+template<typename Scalar, typename Packet> inline void pstore(Scalar* to, const Packet& from)
 { (*to) = from; }
 
 /** \internal copy the packet \a from to \a *to, (un-aligned store) */
-template<typename Scalar, typename Packet> inline void ei_pstoreu(Scalar* to, const Packet& from)
+template<typename Scalar, typename Packet> inline void pstoreu(Scalar* to, const Packet& from)
 { (*to) = from; }
 
+/** \internal tries to do cache prefetching of \a addr */
+template<typename Scalar> inline void prefetch(const Scalar* addr)
+{
+#if !defined(_MSC_VER)
+__builtin_prefetch(addr);
+#endif
+}
+
 /** \internal \returns the first element of a packet */
-template<typename Packet> inline typename ei_unpacket_traits<Packet>::type ei_pfirst(const Packet& a)
+template<typename Packet> inline typename unpacket_traits<Packet>::type pfirst(const Packet& a)
 { return a; }
 
 /** \internal \returns a packet where the element i contains the sum of the packet of \a vec[i] */
 template<typename Packet> inline Packet
-ei_preduxp(const Packet* vecs) { return vecs[0]; }
+preduxp(const Packet* vecs) { return vecs[0]; }
 
 /** \internal \returns the sum of the elements of \a a*/
-template<typename Packet> inline typename ei_unpacket_traits<Packet>::type ei_predux(const Packet& a)
+template<typename Packet> inline typename unpacket_traits<Packet>::type predux(const Packet& a)
 { return a; }
 
+/** \internal \returns the product of the elements of \a a*/
+template<typename Packet> inline typename unpacket_traits<Packet>::type predux_mul(const Packet& a)
+{ return a; }
+
+/** \internal \returns the min of the elements of \a a*/
+template<typename Packet> inline typename unpacket_traits<Packet>::type predux_min(const Packet& a)
+{ return a; }
+
+/** \internal \returns the max of the elements of \a a*/
+template<typename Packet> inline typename unpacket_traits<Packet>::type predux_max(const Packet& a)
+{ return a; }
+
+/** \internal \returns the reversed elements of \a a*/
+template<typename Packet> inline Packet preverse(const Packet& a)
+{ return a; }
+
+
+/** \internal \returns \a a with real and imaginary part flipped (for complex type only) */
+template<typename Packet> inline Packet pcplxflip(const Packet& a)
+{
+  // FIXME: uncomment the following in case we drop the internal imag and real functions.
+//   using std::imag;
+//   using std::real;
+  return Packet(imag(a),real(a));
+}
+
+/**************************
+* Special math functions
+***************************/
+
+/** \internal \returns the sine of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet psin(const Packet& a) { using std::sin; return sin(a); }
+
+/** \internal \returns the cosine of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pcos(const Packet& a) { using std::cos; return cos(a); }
+
+/** \internal \returns the tan of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet ptan(const Packet& a) { using std::tan; return tan(a); }
+
+/** \internal \returns the arc sine of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pasin(const Packet& a) { using std::asin; return asin(a); }
+
+/** \internal \returns the arc cosine of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pacos(const Packet& a) { using std::acos; return acos(a); }
+
+/** \internal \returns the exp of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet pexp(const Packet& a) { using std::exp; return exp(a); }
+
+/** \internal \returns the log of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet plog(const Packet& a) { using std::log; return log(a); }
+
+/** \internal \returns the square-root of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet psqrt(const Packet& a) { using std::sqrt; return sqrt(a); }
 
 /***************************************************************************
 * The following functions might not have to be overwritten for vectorized types
 ***************************************************************************/
 
+/** \internal copy a packet with constant coeficient \a a (e.g., [a,a,a,a]) to \a *to. \a to must be 16 bytes aligned */
+// NOTE: this function must really be templated on the packet type (think about different packet types for the same scalar type)
+template<typename Packet>
+inline void pstore1(typename unpacket_traits<Packet>::type* to, const typename unpacket_traits<Packet>::type& a)
+{
+  pstore(to, pset1<Packet>(a));
+}
+
 /** \internal \returns a * b + c (coeff-wise) */
 template<typename Packet> inline Packet
-ei_pmadd(const Packet&  a,
+pmadd(const Packet&  a,
          const Packet&  b,
          const Packet&  c)
-{ return ei_padd(ei_pmul(a, b),c); }
+{ return padd(pmul(a, b),c); }
 
 /** \internal \returns a packet version of \a *from.
-  * \If LoadMode equals Aligned, \a from must be 16 bytes aligned */
-template<typename Scalar, int LoadMode>
-inline typename ei_packet_traits<Scalar>::type ei_ploadt(const Scalar* from)
+  * If LoadMode equals #Aligned, \a from must be 16 bytes aligned */
+template<typename Packet, int LoadMode>
+inline Packet ploadt(const typename unpacket_traits<Packet>::type* from)
 {
   if(LoadMode == Aligned)
-    return ei_pload(from);
+    return pload<Packet>(from);
   else
-    return ei_ploadu(from);
+    return ploadu<Packet>(from);
 }
 
 /** \internal copy the packet \a from to \a *to.
-  * If StoreMode equals Aligned, \a to must be 16 bytes aligned */
+  * If StoreMode equals #Aligned, \a to must be 16 bytes aligned */
 template<typename Scalar, typename Packet, int LoadMode>
-inline void ei_pstoret(Scalar* to, const Packet& from)
+inline void pstoret(Scalar* to, const Packet& from)
 {
   if(LoadMode == Aligned)
-    ei_pstore(to, from);
+    pstore(to, from);
   else
-    ei_pstoreu(to, from);
+    pstoreu(to, from);
 }
 
-/** \internal default implementation of ei_palign() allowing partial specialization */
+/** \internal default implementation of palign() allowing partial specialization */
 template<int Offset,typename PacketType>
-struct ei_palign_impl
+struct palign_impl
 {
   // by default data are aligned, so there is nothing to be done :)
-  inline static void run(PacketType&, const PacketType&) {}
+  static inline void run(PacketType&, const PacketType&) {}
 };
 
-/** \internal update \a first using the concatenation of the \a Offset last elements
-  * of \a first and packet_size minus \a Offset first elements of \a second */
+/** \internal update \a first using the concatenation of the packet_size minus \a Offset last elements
+  * of \a first and \a Offset first elements of \a second.
+  * 
+  * This function is currently only used to optimize matrix-vector products on unligned matrices.
+  * It takes 2 packets that represent a contiguous memory array, and returns a packet starting
+  * at the position \a Offset. For instance, for packets of 4 elements, we have:
+  *  Input:
+  *  - first = {f0,f1,f2,f3}
+  *  - second = {s0,s1,s2,s3}
+  * Output: 
+  *   - if Offset==0 then {f0,f1,f2,f3}
+  *   - if Offset==1 then {f1,f2,f3,s0}
+  *   - if Offset==2 then {f2,f3,s0,s1}
+  *   - if Offset==3 then {f3,s0,s1,s3}
+  */
 template<int Offset,typename PacketType>
-inline void ei_palign(PacketType& first, const PacketType& second)
+inline void palign(PacketType& first, const PacketType& second)
 {
-  ei_palign_impl<Offset,PacketType>::run(first,second);
+  palign_impl<Offset,PacketType>::run(first,second);
 }
 
+/***************************************************************************
+* Fast complex products (GCC generates a function call which is very slow)
+***************************************************************************/
+
+template<> inline std::complex<float> pmul(const std::complex<float>& a, const std::complex<float>& b)
+{ return std::complex<float>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
+
+template<> inline std::complex<double> pmul(const std::complex<double>& a, const std::complex<double>& b)
+{ return std::complex<double>(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); }
+
+} // end namespace internal
+
+} // end namespace Eigen
+
 #endif // EIGEN_GENERIC_PACKET_MATH_H
 

Eigen/src/Core/GlobalFunctions.h

@@ -0,0 +1,92 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2010-2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_GLOBAL_FUNCTIONS_H
+#define EIGEN_GLOBAL_FUNCTIONS_H
+
+#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR) \
+  template<typename Derived> \
+  inline const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> \
+  NAME(const Eigen::ArrayBase<Derived>& x) { \
+    return x.derived(); \
+  }
+
+#define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME,FUNCTOR) \
+  \
+  template<typename Derived> \
+  struct NAME##_retval<ArrayBase<Derived> > \
+  { \
+    typedef const Eigen::CwiseUnaryOp<Eigen::internal::FUNCTOR<typename Derived::Scalar>, const Derived> type; \
+  }; \
+  template<typename Derived> \
+  struct NAME##_impl<ArrayBase<Derived> > \
+  { \
+    static inline typename NAME##_retval<ArrayBase<Derived> >::type run(const Eigen::ArrayBase<Derived>& x) \
+    { \
+      return x.derived(); \
+    } \
+  };
+
+
+namespace Eigen
+{
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag,scalar_imag_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj,scalar_conjugate_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin,scalar_sin_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos,scalar_cos_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op)
+  EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt,scalar_sqrt_op)
+  
+  template<typename Derived>
+  inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar>, const Derived>
+  pow(const Eigen::ArrayBase<Derived>& x, const typename Derived::Scalar& exponent) {
+    return x.derived().pow(exponent);
+  }
+
+  template<typename Derived>
+  inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>
+  pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<Derived>& exponents) 
+  {
+    return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>(
+      x.derived(),
+      exponents.derived()
+    );
+  }
+  
+  /**
+  * \brief Component-wise division of a scalar by array elements.
+  **/
+  template <typename Derived>
+  inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>
+    operator/(const typename Derived::Scalar& s, const Eigen::ArrayBase<Derived>& a)
+  {
+    return Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>(
+      a.derived(),
+      Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>(s)  
+    );
+  }
+
+  namespace internal
+  {
+    EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op)
+    EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(imag,scalar_imag_op)
+    EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(abs2,scalar_abs2_op)
+  }
+}
+
+// TODO: cleanly disable those functions that are not supported on Array (numext::real_ref, internal::random, internal::isApprox...)
+
+#endif // EIGEN_GLOBAL_FUNCTIONS_H

Eigen/src/Core/IO.h

@@ -1,40 +1,40 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_IO_H
 #define EIGEN_IO_H
 
-enum { Raw, AlignCols };
+namespace Eigen { 
+
+enum { DontAlignCols = 1 };
+enum { StreamPrecision = -1,
+       FullPrecision = -2 };
+
+namespace internal {
+template<typename Derived>
+std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt);
+}
 
 /** \class IOFormat
+  * \ingroup Core_Module
   *
   * \brief Stores a set of parameters controlling the way matrices are printed
   *
   * List of available parameters:
-  *  - \b precision number of digits for floating point values
-  *  - \b flags can be either Raw (default) or AlignCols which aligns all the columns
+  *  - \b precision number of digits for floating point values, or one of the special constants \c StreamPrecision and \c FullPrecision.
+  *                 The default is the special value \c StreamPrecision which means to use the
+  *                 stream's own precision setting, as set for instance using \c cout.precision(3). The other special value
+  *                 \c FullPrecision means that the number of digits will be computed to match the full precision of each floating-point
+  *                 type.
+  *  - \b flags an OR-ed combination of flags, the default value is 0, the only currently available flag is \c DontAlignCols which
+  *             allows to disable the alignment of columns, resulting in faster code.
   *  - \b coeffSeparator string printed between two coefficients of the same row
   *  - \b rowSeparator string printed between two rows
   *  - \b rowPrefix string printed at the beginning of each row
@@ -45,19 +45,18 @@ enum { Raw, AlignCols };
   * Example: \include IOFormat.cpp
   * Output: \verbinclude IOFormat.out
   *
-  * \sa MatrixBase::format(), class WithFormat
+  * \sa DenseBase::format(), class WithFormat
   */
 struct IOFormat
 {
   /** Default contructor, see class IOFormat for the meaning of the parameters */
-  IOFormat(int _precision=4, int _flags=Raw,
+  IOFormat(int _precision = StreamPrecision, int _flags = 0,
     const std::string& _coeffSeparator = " ",
     const std::string& _rowSeparator = "\n", const std::string& _rowPrefix="", const std::string& _rowSuffix="",
     const std::string& _matPrefix="", const std::string& _matSuffix="")
   : matPrefix(_matPrefix), matSuffix(_matSuffix), rowPrefix(_rowPrefix), rowSuffix(_rowSuffix), rowSeparator(_rowSeparator),
-    coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags)
+    rowSpacer(""), coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags)
   {
-    rowSpacer = "";
     int i = int(matSuffix.length())-1;
     while (i>=0 && matSuffix[i]!='\n')
     {
@@ -73,18 +72,19 @@ struct IOFormat
 };
 
 /** \class WithFormat
+  * \ingroup Core_Module
   *
   * \brief Pseudo expression providing matrix output with given format
   *
   * \param ExpressionType the type of the object on which IO stream operations are performed
   *
   * This class represents an expression with stream operators controlled by a given IOFormat.
-  * It is the return type of MatrixBase::format()
+  * It is the return type of DenseBase::format()
   * and most of the time this is the only way it is used.
   *
   * See class IOFormat for some examples.
   *
-  * \sa MatrixBase::format(), class IOFormat
+  * \sa DenseBase::format(), class IOFormat
   */
 template<typename ExpressionType>
 class WithFormat
@@ -97,7 +97,7 @@ class WithFormat
 
     friend std::ostream & operator << (std::ostream & s, const WithFormat& wf)
     {
-      return ei_print_matrix(s, wf.m_matrix.eval(), wf.m_format);
+      return internal::print_matrix(s, wf.m_matrix.eval(), wf.m_format);
     }
 
   protected:
@@ -114,41 +114,102 @@ class WithFormat
   */
 template<typename Derived>
 inline const WithFormat<Derived>
-MatrixBase<Derived>::format(const IOFormat& fmt) const
+DenseBase<Derived>::format(const IOFormat& fmt) const
 {
   return WithFormat<Derived>(derived(), fmt);
 }
 
+namespace internal {
+
+template<typename Scalar, bool IsInteger>
+struct significant_decimals_default_impl
+{
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  static inline int run()
+  {
+    using std::ceil;
+    using std::log;
+    return cast<RealScalar,int>(ceil(-log(NumTraits<RealScalar>::epsilon())/log(RealScalar(10))));
+  }
+};
+
+template<typename Scalar>
+struct significant_decimals_default_impl<Scalar, true>
+{
+  static inline int run()
+  {
+    return 0;
+  }
+};
+
+template<typename Scalar>
+struct significant_decimals_impl
+  : significant_decimals_default_impl<Scalar, NumTraits<Scalar>::IsInteger>
+{};
+
 /** \internal
   * print the matrix \a _m to the output stream \a s using the output format \a fmt */
 template<typename Derived>
-std::ostream & ei_print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt)
+std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt)
 {
-  const typename Derived::Nested m = _m;
+  if(_m.size() == 0)
+  {
+    s << fmt.matPrefix << fmt.matSuffix;
+    return s;
+  }
+  
+  typename Derived::Nested m = _m;
+  typedef typename Derived::Scalar Scalar;
+  typedef typename Derived::Index Index;
 
-  int width = 0;
-  if (fmt.flags & AlignCols)
+  Index width = 0;
+
+  std::streamsize explicit_precision;
+  if(fmt.precision == StreamPrecision)
+  {
+    explicit_precision = 0;
+  }
+  else if(fmt.precision == FullPrecision)
+  {
+    if (NumTraits<Scalar>::IsInteger)
+    {
+      explicit_precision = 0;
+    }
+    else
+    {
+      explicit_precision = significant_decimals_impl<Scalar>::run();
+    }
+  }
+  else
+  {
+    explicit_precision = fmt.precision;
+  }
+
+  std::streamsize old_precision = 0;
+  if(explicit_precision) old_precision = s.precision(explicit_precision);
+
+  bool align_cols = !(fmt.flags & DontAlignCols);
+  if(align_cols)
   {
     // compute the largest width
-    for(int j = 1; j < m.cols(); ++j)
-      for(int i = 0; i < m.rows(); ++i)
+    for(Index j = 0; j < m.cols(); ++j)
+      for(Index i = 0; i < m.rows(); ++i)
       {
         std::stringstream sstr;
-        sstr.precision(fmt.precision);
+        sstr.copyfmt(s);
         sstr << m.coeff(i,j);
-        width = std::max<int>(width, int(sstr.str().length()));
+        width = std::max<Index>(width, Index(sstr.str().length()));
       }
   }
-  s.precision(fmt.precision);
   s << fmt.matPrefix;
-  for(int i = 0; i < m.rows(); ++i)
+  for(Index i = 0; i < m.rows(); ++i)
   {
     if (i)
       s << fmt.rowSpacer;
     s << fmt.rowPrefix;
     if(width) s.width(width);
     s << m.coeff(i, 0);
-    for(int j = 1; j < m.cols(); ++j)
+    for(Index j = 1; j < m.cols(); ++j)
     {
       s << fmt.coeffSeparator;
       if (width) s.width(width);
@@ -159,26 +220,31 @@ std::ostream & ei_print_matrix(std::ostream & s, const Derived& _m, const IOForm
       s << fmt.rowSeparator;
   }
   s << fmt.matSuffix;
+  if(explicit_precision) s.precision(old_precision);
   return s;
 }
 
-/** \relates MatrixBase
+} // end namespace internal
+
+/** \relates DenseBase
   *
   * Outputs the matrix, to the given stream.
   *
-  * If you wish to print the matrix with a format different than the default, use MatrixBase::format().
+  * If you wish to print the matrix with a format different than the default, use DenseBase::format().
   *
   * It is also possible to change the default format by defining EIGEN_DEFAULT_IO_FORMAT before including Eigen headers.
   * If not defined, this will automatically be defined to Eigen::IOFormat(), that is the Eigen::IOFormat with default parameters.
   *
-  * \sa MatrixBase::format()
+  * \sa DenseBase::format()
   */
 template<typename Derived>
 std::ostream & operator <<
 (std::ostream & s,
- const MatrixBase<Derived> & m)
+ const DenseBase<Derived> & m)
 {
-  return ei_print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT);
+  return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_IO_H

Eigen/src/Core/Map.h

@@ -1,111 +1,192 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MAP_H
 #define EIGEN_MAP_H
 
+namespace Eigen { 
+
 /** \class Map
+  * \ingroup Core_Module
   *
   * \brief A matrix or vector expression mapping an existing array of data.
   *
-  * \param MatrixType the equivalent matrix type of the mapped data
-  * \param _PacketAccess allows to enforce aligned loads and stores if set to ForceAligned.
-  *                      The default is AsRequested. This parameter is internaly used by Eigen
-  *                      in expressions such as \code Map<...>(...) += other; \endcode and most
-  *                      of the time this is the only way it is used.
+  * \tparam PlainObjectType the equivalent matrix type of the mapped data
+  * \tparam MapOptions specifies whether the pointer is \c #Aligned, or \c #Unaligned.
+  *                The default is \c #Unaligned.
+  * \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout
+  *                   of an ordinary, contiguous array. This can be overridden by specifying strides.
+  *                   The type passed here must be a specialization of the Stride template, see examples below.
   *
   * This class represents a matrix or vector expression mapping an existing array of data.
   * It can be used to let Eigen interface without any overhead with non-Eigen data structures,
-  * such as plain C arrays or structures from other libraries.
+  * such as plain C arrays or structures from other libraries. By default, it assumes that the
+  * data is laid out contiguously in memory. You can however override this by explicitly specifying
+  * inner and outer strides.
   *
-  * This class is the return type of Matrix::Map() but can also be used directly.
+  * Here's an example of simply mapping a contiguous array as a \ref TopicStorageOrders "column-major" matrix:
+  * \include Map_simple.cpp
+  * Output: \verbinclude Map_simple.out
   *
-  * \sa Matrix::Map()
+  * If you need to map non-contiguous arrays, you can do so by specifying strides:
+  *
+  * Here's an example of mapping an array as a vector, specifying an inner stride, that is, the pointer
+  * increment between two consecutive coefficients. Here, we're specifying the inner stride as a compile-time
+  * fixed value.
+  * \include Map_inner_stride.cpp
+  * Output: \verbinclude Map_inner_stride.out
+  *
+  * Here's an example of mapping an array while specifying an outer stride. Here, since we're mapping
+  * as a column-major matrix, 'outer stride' means the pointer increment between two consecutive columns.
+  * Here, we're specifying the outer stride as a runtime parameter. Note that here \c OuterStride<> is
+  * a short version of \c OuterStride<Dynamic> because the default template parameter of OuterStride
+  * is  \c Dynamic
+  * \include Map_outer_stride.cpp
+  * Output: \verbinclude Map_outer_stride.out
+  *
+  * For more details and for an example of specifying both an inner and an outer stride, see class Stride.
+  *
+  * \b Tip: to change the array of data mapped by a Map object, you can use the C++
+  * placement new syntax:
+  *
+  * Example: \include Map_placement_new.cpp
+  * Output: \verbinclude Map_placement_new.out
+  *
+  * This class is the return type of PlainObjectBase::Map() but can also be used directly.
+  *
+  * \sa PlainObjectBase::Map(), \ref TopicStorageOrders
   */
-template<typename MatrixType, int _PacketAccess>
-struct ei_traits<Map<MatrixType, _PacketAccess> > : public ei_traits<MatrixType>
-{
-  enum {
-    PacketAccess = _PacketAccess,
-    Flags = ei_traits<MatrixType>::Flags & ~AlignedBit
-  };
-  typedef typename ei_meta_if<int(PacketAccess)==ForceAligned,
-                              Map<MatrixType, _PacketAccess>&,
-                              Map<MatrixType, ForceAligned> >::ret AlignedDerivedType;
-};
 
-template<typename MatrixType, int PacketAccess> class Map
-  : public MapBase<Map<MatrixType, PacketAccess> >
+namespace internal {
+template<typename PlainObjectType, int MapOptions, typename StrideType>
+struct traits<Map<PlainObjectType, MapOptions, StrideType> >
+  : public traits<PlainObjectType>
+{
+  typedef traits<PlainObjectType> TraitsBase;
+  typedef typename PlainObjectType::Index Index;
+  typedef typename PlainObjectType::Scalar Scalar;
+  enum {
+    InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
+                             ? int(PlainObjectType::InnerStrideAtCompileTime)
+                             : int(StrideType::InnerStrideAtCompileTime),
+    OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
+                             ? int(PlainObjectType::OuterStrideAtCompileTime)
+                             : int(StrideType::OuterStrideAtCompileTime),
+    HasNoInnerStride = InnerStrideAtCompileTime == 1,
+    HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0,
+    HasNoStride = HasNoInnerStride && HasNoOuterStride,
+    IsAligned = bool(EIGEN_ALIGN) && ((int(MapOptions)&Aligned)==Aligned),
+    IsDynamicSize = PlainObjectType::SizeAtCompileTime==Dynamic,
+    KeepsPacketAccess = bool(HasNoInnerStride)
+                        && ( bool(IsDynamicSize)
+                           || HasNoOuterStride
+                           || ( OuterStrideAtCompileTime!=Dynamic
+                           && ((static_cast<int>(sizeof(Scalar))*OuterStrideAtCompileTime)%16)==0 ) ),
+    Flags0 = TraitsBase::Flags & (~NestByRefBit),
+    Flags1 = IsAligned ? (int(Flags0) | AlignedBit) : (int(Flags0) & ~AlignedBit),
+    Flags2 = (bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime))
+           ? int(Flags1) : int(Flags1 & ~LinearAccessBit),
+    Flags3 = is_lvalue<PlainObjectType>::value ? int(Flags2) : (int(Flags2) & ~LvalueBit),
+    Flags = KeepsPacketAccess ? int(Flags3) : (int(Flags3) & ~PacketAccessBit)
+  };
+private:
+  enum { Options }; // Expressions don't have Options
+};
+}
+
+template<typename PlainObjectType, int MapOptions, typename StrideType> class Map
+  : public MapBase<Map<PlainObjectType, MapOptions, StrideType> >
 {
   public:
 
-    _EIGEN_GENERIC_PUBLIC_INTERFACE(Map, MapBase<Map>)
-    typedef typename ei_traits<Map>::AlignedDerivedType AlignedDerivedType;
+    typedef MapBase<Map> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Map)
 
-    inline int stride() const { return this->innerSize(); }
+    typedef typename Base::PointerType PointerType;
+#if EIGEN2_SUPPORT_STAGE <= STAGE30_FULL_EIGEN3_API
+    typedef const Scalar* PointerArgType;
+    inline PointerType cast_to_pointer_type(PointerArgType ptr) { return const_cast<PointerType>(ptr); }
+#else
+    typedef PointerType PointerArgType;
+    inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; }
+#endif
 
-    AlignedDerivedType _convertToForceAligned()
+    inline Index innerStride() const
     {
-      return Map<MatrixType,ForceAligned>(Base::m_data, Base::m_rows.value(), Base::m_cols.value());
+      return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
     }
 
-    inline Map(const Scalar* data) : Base(data) {}
-
-    inline Map(const Scalar* data, int size) : Base(data, size) {}
-
-    inline Map(const Scalar* data, int rows, int cols) : Base(data, rows, cols) {}
-
-    inline void resize(int rows, int cols)
+    inline Index outerStride() const
     {
-      EIGEN_ONLY_USED_FOR_DEBUG(rows);
-      EIGEN_ONLY_USED_FOR_DEBUG(cols);
-      ei_assert(rows == this->rows());
-      ei_assert(cols == this->cols());
+      return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
+           : IsVectorAtCompileTime ? this->size()
+           : int(Flags)&RowMajorBit ? this->cols()
+           : this->rows();
     }
 
-    inline void resize(int size)
+    /** Constructor in the fixed-size case.
+      *
+      * \param dataPtr pointer to the array to map
+      * \param a_stride optional Stride object, passing the strides.
+      */
+    inline Map(PointerArgType dataPtr, const StrideType& a_stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr)), m_stride(a_stride)
     {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(MatrixType)
-      EIGEN_ONLY_USED_FOR_DEBUG(size);
-      ei_assert(size == this->size());
+      PlainObjectType::Base::_check_template_params();
+    }
+
+    /** Constructor in the dynamic-size vector case.
+      *
+      * \param dataPtr pointer to the array to map
+      * \param a_size the size of the vector expression
+      * \param a_stride optional Stride object, passing the strides.
+      */
+    inline Map(PointerArgType dataPtr, Index a_size, const StrideType& a_stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr), a_size), m_stride(a_stride)
+    {
+      PlainObjectType::Base::_check_template_params();
+    }
+
+    /** Constructor in the dynamic-size matrix case.
+      *
+      * \param dataPtr pointer to the array to map
+      * \param nbRows the number of rows of the matrix expression
+      * \param nbCols the number of columns of the matrix expression
+      * \param a_stride optional Stride object, passing the strides.
+      */
+    inline Map(PointerArgType dataPtr, Index nbRows, Index nbCols, const StrideType& a_stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr), nbRows, nbCols), m_stride(a_stride)
+    {
+      PlainObjectType::Base::_check_template_params();
     }
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
+
+  protected:
+    StrideType m_stride;
 };
 
-/** Constructor copying an existing array of data.
-  * Only for fixed-size matrices and vectors.
-  * \param data The array of data to copy
-  *
-  * \sa Matrix::Map(const Scalar *)
-  */
-template<typename _Scalar, int _Rows, int _Cols, int _StorageOrder, int _MaxRows, int _MaxCols>
-inline Matrix<_Scalar, _Rows, _Cols, _StorageOrder, _MaxRows, _MaxCols>
-  ::Matrix(const Scalar *data)
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+inline Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
+  ::Array(const Scalar *data)
 {
-  _set_noalias(Eigen::Map<Matrix>(data));
+  this->_set_noalias(Eigen::Map<const Array>(data));
 }
 
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+inline Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
+  ::Matrix(const Scalar *data)
+{
+  this->_set_noalias(Eigen::Map<const Matrix>(data));
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_MAP_H

Eigen/src/Core/MapBase.h

@@ -1,202 +1,247 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MAPBASE_H
 #define EIGEN_MAPBASE_H
 
+#define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \
+      EIGEN_STATIC_ASSERT((int(internal::traits<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
+                          YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
+
+namespace Eigen { 
+
 /** \class MapBase
+  * \ingroup Core_Module
   *
   * \brief Base class for Map and Block expression with direct access
   *
-  * Expression classes inheriting MapBase must define the constant \c PacketAccess,
-  * and type \c AlignedDerivedType in their respective ei_traits<> specialization structure.
-  * The value of \c PacketAccess can be either:
-  *  - \b ForceAligned which enforces both aligned loads and stores
-  *  - \b AsRequested which is the default behavior
-  * The type \c AlignedDerivedType should correspond to the equivalent expression type
-  * with \c PacketAccess being \c ForceAligned.
-  *
   * \sa class Map, class Block
   */
-template<typename Derived> class MapBase
-  : public MatrixBase<Derived>
+template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
+  : public internal::dense_xpr_base<Derived>::type
 {
   public:
 
-    typedef MatrixBase<Derived> Base;
+    typedef typename internal::dense_xpr_base<Derived>::type Base;
     enum {
-      IsRowMajor = (int(ei_traits<Derived>::Flags) & RowMajorBit) ? 1 : 0,
-      PacketAccess = ei_traits<Derived>::PacketAccess,
-      RowsAtCompileTime = ei_traits<Derived>::RowsAtCompileTime,
-      ColsAtCompileTime = ei_traits<Derived>::ColsAtCompileTime,
+      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
+      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
       SizeAtCompileTime = Base::SizeAtCompileTime
     };
 
-    typedef typename ei_traits<Derived>::AlignedDerivedType AlignedDerivedType;
-    typedef typename ei_traits<Derived>::Scalar Scalar;
-    typedef typename Base::PacketScalar PacketScalar;
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename internal::conditional<
+                         bool(internal::is_lvalue<Derived>::value),
+                         Scalar *,
+                         const Scalar *>::type
+                     PointerType;
+
     using Base::derived;
+//    using Base::RowsAtCompileTime;
+//    using Base::ColsAtCompileTime;
+//    using Base::SizeAtCompileTime;
+    using Base::MaxRowsAtCompileTime;
+    using Base::MaxColsAtCompileTime;
+    using Base::MaxSizeAtCompileTime;
+    using Base::IsVectorAtCompileTime;
+    using Base::Flags;
+    using Base::IsRowMajor;
 
-    inline int rows() const { return m_rows.value(); }
-    inline int cols() const { return m_cols.value(); }
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::coeff;
+    using Base::coeffRef;
+    using Base::lazyAssign;
+    using Base::eval;
 
-    inline int stride() const { return derived().stride(); }
+    using Base::innerStride;
+    using Base::outerStride;
+    using Base::rowStride;
+    using Base::colStride;
+
+    // bug 217 - compile error on ICC 11.1
+    using Base::operator=;
+
+    typedef typename Base::CoeffReturnType CoeffReturnType;
+
+    inline Index rows() const { return m_rows.value(); }
+    inline Index cols() const { return m_cols.value(); }
+
+    /** Returns a pointer to the first coefficient of the matrix or vector.
+      *
+      * \note When addressing this data, make sure to honor the strides returned by innerStride() and outerStride().
+      *
+      * \sa innerStride(), outerStride()
+      */
     inline const Scalar* data() const { return m_data; }
 
-    template<bool IsForceAligned,typename Dummy> struct force_aligned_impl {
-      AlignedDerivedType static run(MapBase& a) { return a.derived(); }
-    };
-
-    template<typename Dummy> struct force_aligned_impl<false,Dummy> {
-      AlignedDerivedType static run(MapBase& a) { return a.derived()._convertToForceAligned(); }
-    };
-
-    /** \returns an expression equivalent to \c *this but having the \c PacketAccess constant
-      * set to \c ForceAligned. Must be reimplemented by the derived class. */
-    AlignedDerivedType forceAligned()
+    inline const Scalar& coeff(Index rowId, Index colId) const
     {
-      return force_aligned_impl<int(PacketAccess)==int(ForceAligned),Derived>::run(*this);
+      return m_data[colId * colStride() + rowId * rowStride()];
     }
 
-    inline const Scalar& coeff(int row, int col) const
+    inline const Scalar& coeff(Index index) const
     {
-      if(IsRowMajor)
-        return m_data[col + row * stride()];
-      else // column-major
-        return m_data[row + col * stride()];
+      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
+      return m_data[index * innerStride()];
     }
 
-    inline Scalar& coeffRef(int row, int col)
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
-      if(IsRowMajor)
-        return const_cast<Scalar*>(m_data)[col + row * stride()];
-      else // column-major
-        return const_cast<Scalar*>(m_data)[row + col * stride()];
+      return this->m_data[colId * colStride() + rowId * rowStride()];
     }
 
-    inline const Scalar coeff(int index) const
+    inline const Scalar& coeffRef(Index index) const
     {
-      ei_assert(Derived::IsVectorAtCompileTime || (ei_traits<Derived>::Flags & LinearAccessBit));
-      if ( ((RowsAtCompileTime == 1) == IsRowMajor) )
-        return m_data[index];
-      else
-        return m_data[index*stride()];
-    }
-
-    inline Scalar& coeffRef(int index)
-    {
-      ei_assert(Derived::IsVectorAtCompileTime || (ei_traits<Derived>::Flags & LinearAccessBit));
-      if ( ((RowsAtCompileTime == 1) == IsRowMajor) )
-        return const_cast<Scalar*>(m_data)[index];
-      else
-        return const_cast<Scalar*>(m_data)[index*stride()];
+      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
+      return this->m_data[index * innerStride()];
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(int row, int col) const
+    inline PacketScalar packet(Index rowId, Index colId) const
     {
-      return ei_ploadt<Scalar, int(PacketAccess) == ForceAligned ? Aligned : LoadMode>
-               (m_data + (IsRowMajor ? col + row * stride()
-                                     : row + col * stride()));
+      return internal::ploadt<PacketScalar, LoadMode>
+               (m_data + (colId * colStride() + rowId * rowStride()));
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(int index) const
+    inline PacketScalar packet(Index index) const
     {
-      return ei_ploadt<Scalar, int(PacketAccess) == ForceAligned ? Aligned : LoadMode>(m_data + index);
+      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
+      return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
     }
 
-    template<int StoreMode>
-    inline void writePacket(int row, int col, const PacketScalar& x)
-    {
-      ei_pstoret<Scalar, PacketScalar, int(PacketAccess) == ForceAligned ? Aligned : StoreMode>
-               (const_cast<Scalar*>(m_data) + (IsRowMajor ? col + row * stride()
-                                                          : row + col * stride()), x);
-    }
-
-    template<int StoreMode>
-    inline void writePacket(int index, const PacketScalar& x)
-    {
-      ei_pstoret<Scalar, PacketScalar, int(PacketAccess) == ForceAligned ? Aligned : StoreMode>
-        (const_cast<Scalar*>(m_data) + index, x);
-    }
-
-    inline MapBase(const Scalar* data) : m_data(data), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
+    inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
     {
       EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
+      checkSanity();
     }
 
-    inline MapBase(const Scalar* data, int size)
-            : m_data(data),
-              m_rows(RowsAtCompileTime == Dynamic ? size : RowsAtCompileTime),
-              m_cols(ColsAtCompileTime == Dynamic ? size : ColsAtCompileTime)
+    inline MapBase(PointerType dataPtr, Index vecSize)
+            : m_data(dataPtr),
+              m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)),
+              m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime))
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-      ei_assert(size > 0 || data == 0);
-      ei_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
+      eigen_assert(vecSize >= 0);
+      eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize);
+      checkSanity();
     }
 
-    inline MapBase(const Scalar* data, int rows, int cols)
-            : m_data(data), m_rows(rows), m_cols(cols)
+    inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols)
+            : m_data(dataPtr), m_rows(nbRows), m_cols(nbCols)
     {
-      ei_assert( (data == 0)
-              || (   rows > 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-                  && cols > 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
+      eigen_assert( (dataPtr == 0)
+              || (   nbRows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
+                  && nbCols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols)));
+      checkSanity();
     }
 
+  protected:
+
+    void checkSanity() const
+    {
+      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(internal::traits<Derived>::Flags&PacketAccessBit,
+                                        internal::inner_stride_at_compile_time<Derived>::ret==1),
+                          PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
+      eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::Flags&AlignedBit, (size_t(m_data) % 16) == 0)
+                   && "input pointer is not aligned on a 16 byte boundary");
+    }
+
+    PointerType m_data;
+    const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
+    const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
+};
+
+template<typename Derived> class MapBase<Derived, WriteAccessors>
+  : public MapBase<Derived, ReadOnlyAccessors>
+{
+    typedef MapBase<Derived, ReadOnlyAccessors> ReadOnlyMapBase;
+  public:
+
+    typedef MapBase<Derived, ReadOnlyAccessors> Base;
+
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::PacketScalar PacketScalar;
+    typedef typename Base::Index Index;
+    typedef typename Base::PointerType PointerType;
+
+    using Base::derived;
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::coeff;
+    using Base::coeffRef;
+
+    using Base::innerStride;
+    using Base::outerStride;
+    using Base::rowStride;
+    using Base::colStride;
+
+    typedef typename internal::conditional<
+                    internal::is_lvalue<Derived>::value,
+                    Scalar,
+                    const Scalar
+                  >::type ScalarWithConstIfNotLvalue;
+
+    inline const Scalar* data() const { return this->m_data; }
+    inline ScalarWithConstIfNotLvalue* data() { return this->m_data; } // no const-cast here so non-const-correct code will give a compile error
+
+    inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col)
+    {
+      return this->m_data[col * colStride() + row * rowStride()];
+    }
+
+    inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
+    {
+      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
+      return this->m_data[index * innerStride()];
+    }
+
+    template<int StoreMode>
+    inline void writePacket(Index row, Index col, const PacketScalar& val)
+    {
+      internal::pstoret<Scalar, PacketScalar, StoreMode>
+               (this->m_data + (col * colStride() + row * rowStride()), val);
+    }
+
+    template<int StoreMode>
+    inline void writePacket(Index index, const PacketScalar& val)
+    {
+      EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
+      internal::pstoret<Scalar, PacketScalar, StoreMode>
+                (this->m_data + index * innerStride(), val);
+    }
+
+    explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
+    inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
+    inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {}
+
     Derived& operator=(const MapBase& other)
     {
-      return Base::operator=(other);
+      ReadOnlyMapBase::Base::operator=(other);
+      return derived();
     }
 
-    template<typename OtherDerived>
-    Derived& operator=(const MatrixBase<OtherDerived>& other)
-    {
-      return Base::operator=(other);
-    }
-    
-    using Base::operator*=;
-
-    template<typename OtherDerived>
-    Derived& operator+=(const MatrixBase<OtherDerived>& other)
-    { return derived() = forceAligned() + other; }
-
-    template<typename OtherDerived>
-    Derived& operator-=(const MatrixBase<OtherDerived>& other)
-    { return derived() = forceAligned() - other; }
-
-    Derived& operator*=(const Scalar& other)
-    { return derived() = forceAligned() * other; }
-
-    Derived& operator/=(const Scalar& other)
-    { return derived() = forceAligned() / other; }
-
-  protected:
-    const Scalar* EIGEN_RESTRICT m_data;
-    const ei_int_if_dynamic<RowsAtCompileTime> m_rows;
-    const ei_int_if_dynamic<ColsAtCompileTime> m_cols;
+    // In theory we could simply refer to Base:Base::operator=, but MSVC does not like Base::Base,
+    // see bugs 821 and 920.
+    using ReadOnlyMapBase::Base::operator=;
 };
 
+#undef EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS
+
+} // end namespace Eigen
+
 #endif // EIGEN_MAPBASE_H