bump version number

: fix warnings with recent gcc(4.3.3)

.clang-format

@@ -1,19 +0,0 @@
----
-BasedOnStyle: Google
-ColumnLimit:  120
----
-Language:     Cpp
-BasedOnStyle: Google
-ColumnLimit:  120
-StatementMacros:
-  - EIGEN_STATIC_ASSERT
-  - EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
-  - EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
-SortIncludes: false
-AttributeMacros:
-- EIGEN_STRONG_INLINE
-- EIGEN_ALWAYS_INLINE
-- EIGEN_DEVICE_FUNC
-- EIGEN_DONT_INLINE
-- EIGEN_DEPRECATED
-- EIGEN_UNUSED

.git-blame-ignore-revs

@@ -1,4 +0,0 @@
-# First major clang-format MR (https://gitlab.com/libeigen/eigen/-/merge_requests/1429).
-f38e16c193d489c278c189bc06b448a94adb45fb
-# Formatting of tests, examples, benchmarks, et cetera (https://gitlab.com/libeigen/eigen/-/merge_requests/1432).
-46e9cdb7fea25d7f7aef4332b9c3ead3857e213d

.gitattributes

@@ -1,3 +0,0 @@
-*.sh                         eol=lf
-debug/msvc/*.dat             eol=crlf
-debug/msvc/*.natvis          eol=crlf

.gitignore

@@ -1,41 +0,0 @@
-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
-*.patch
-a
-a.*
-lapack/testing
-lapack/reference
-.*project
-.settings
-Makefile
-!ci/build.gitlab-ci.yml
-!scripts/buildtests.in
-!Eigen/Core
-!Eigen/src/Core

.gitlab-ci.yml

@@ -1,34 +0,0 @@
-# This file is part of Eigen, a lightweight C++ template library
-# for linear algebra.
-#
-# Copyright (C) 2023, The Eigen Authors
-#
-# 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/.
-
-stages:
-  - checkformat
-  - build
-  - test
-  - deploy
-
-variables:
-  # CMake build directory.
-  EIGEN_CI_BUILDDIR: .build
-  # Specify the CMake build target.
-  EIGEN_CI_BUILD_TARGET: ""
-  # If a test regex is specified, that will be selected.
-  # Otherwise, we will try a label if specified.
-  EIGEN_CI_CTEST_REGEX: ""
-  EIGEN_CI_CTEST_LABEL: ""
-  EIGEN_CI_CTEST_ARGS: ""
-
-include:
-  - "/ci/checkformat.gitlab-ci.yml"
-  - "/ci/common.gitlab-ci.yml"
-  - "/ci/build.linux.gitlab-ci.yml"
-  - "/ci/build.windows.gitlab-ci.yml"
-  - "/ci/test.linux.gitlab-ci.yml"
-  - "/ci/test.windows.gitlab-ci.yml"
-  - "/ci/deploy.gitlab-ci.yml"

.gitlab/issue_templates/Bug Report.md

@@ -1,69 +0,0 @@
-<!--
-Please read this!
-
-Before opening a new issue, make sure to search for keywords in the issues
-filtered by "bug::confirmed" or "bug::unconfirmed" and "bugzilla" label:
-
-- https://gitlab.com/libeigen/eigen/-/issues?scope=all&utf8=%E2%9C%93&state=opened&label_name[]=bug%3A%3Aconfirmed
-- https://gitlab.com/libeigen/eigen/-/issues?scope=all&utf8=%E2%9C%93&state=opened&label_name[]=bug%3A%3Aunconfirmed
-- https://gitlab.com/libeigen/eigen/-/issues?scope=all&utf8=%E2%9C%93&state=opened&label_name[]=bugzilla
-
-and verify the issue you're about to submit isn't a duplicate. -->
-
-### Summary
-<!-- Summarize the bug encountered concisely. -->
-
-### Environment
-<!-- Please provide your development environment here -->
-- **Operating System** : Windows/Linux
-- **Architecture** : x64/Arm64/PowerPC ...
-- **Eigen Version** : 3.3.9
-- **Compiler Version** : Gcc7.0
-- **Compile Flags** : -O3 -march=native
-- **Vector Extension** : SSE/AVX/NEON ...
-
-### Minimal Example
-<!-- If possible, please create a minimal example here that exhibits the problematic behavior.
-You can also link to [godbolt](https://godbolt.org). But please note that you need to click 
-the "Share" button in the top right-hand corner of the godbolt page where you reproduce the sample 
-code to get the share link instead of in your browser address bar. 
-
-You can read [the guidelines on stackoverflow](https://stackoverflow.com/help/minimal-reproducible-example)
-on how to create a good minimal example. -->
-
-```cpp
-//show your code here
-```
-
-### Steps to reproduce
-<!-- Describe how one can reproduce the issue - this is very important. Please use an ordered list. -->
-
-1. first step
-2. second step
-3. ... 
-
-### What is the current *bug* behavior?
-<!-- Describe what actually happens. -->
-
-### What is the expected *correct* behavior?
-<!-- Describe what you should see instead. -->
-
-### Relevant logs
-<!-- Add relevant code snippets or program output within blocks marked by " ``` " -->
-
-<!-- OPTIONAL: remove this section if you are not reporting a compilation warning issue.-->
-### Warning Messages
-<!-- Show us the warning messages you got! -->
-
-<!-- OPTIONAL: remove this section if you are not reporting a performance issue. -->
-### Benchmark scripts and results
-<!-- Please share any benchmark scripts - either standalone, or using [Google Benchmark](https://github.com/google/benchmark). -->
-
-### Anything else that might help
-<!-- It will be better to provide us more information to help narrow down the cause. 
-Including but not limited to the following: 
-- lines of code that might help us diagnose the problem. 
-- potential ways to address the issue.
-- last known working/first broken version (release number or commit hash). --> 
-
-- [ ] Have a plan to fix this issue.

.gitlab/issue_templates/Feature Request.md

@@ -1,7 +0,0 @@
-### Describe the feature you would like to be implemented.
-
-### Would such a feature be useful for other users? Why?
-
-### Any hints on how to implement the requested feature?
-
-### Additional resources

.gitlab/merge_request_templates/Merge Request Template.md

@@ -1,26 +0,0 @@
-<!-- 
-Thanks for contributing a merge request! Please name and fully describe your MR as you would for a commit message.
-If the MR fixes an issue, please include "Fixes #issue" in the commit message and the MR description.
-
-In addition, we recommend that first-time contributors read our [contribution guidelines](https://eigen.tuxfamily.org/index.php?title=Contributing_to_Eigen) and [git page](https://eigen.tuxfamily.org/index.php?title=Git), which will help you submit a more standardized MR.
-
-Before submitting the MR, you also need to complete the following checks:
-- Make one PR per feature/bugfix (don't mix multiple changes into one PR). Avoid committing unrelated changes.
-- Rebase before committing
-- For code changes, run the test suite (at least the tests that are likely affected by the change).
-  See our [test guidelines](https://eigen.tuxfamily.org/index.php?title=Tests).
-- If possible, add a test (both for bug-fixes as well as new features)
-- Make sure new features are documented
-
-Note that we are a team of volunteers; we appreciate your patience during the review process.
-
-Again, thanks for contributing! -->
-
-### Reference issue
-<!-- You can link to a specific issue using the gitlab syntax #<issue number>  -->
-
-### What does this implement/fix?
-<!--Please explain your changes.-->
-
-### Additional information
-<!--Any additional information you think is important.-->

.krazy

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

CMakeLists.txt

@@ -1,806 +1,102 @@
-cmake_minimum_required(VERSION 3.10.0)
+project(Eigen)
+set(EIGEN_VERSION_NUMBER "2.0.2")
 
-#==============================================================================
-# CMake Policy issues.
-#==============================================================================
-# Allow overriding options in a parent project via `set` before including Eigen.
-if (POLICY CMP0077)
-  cmake_policy (SET CMP0077 NEW)
-endif (POLICY CMP0077)
+#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)
 
-# NOTE Remove setting the policy once the minimum required CMake version is
-# increased to at least 3.15. Retain enabling the export to package registry.
-if (POLICY CMP0090)
-  # The export command does not populate package registry by default
-  cmake_policy (SET CMP0090 NEW)
-  # Unless otherwise specified, always export to package registry to ensure
-  # backwards compatibility.
-  if (NOT DEFINED CMAKE_EXPORT_PACKAGE_REGISTRY)
-    set (CMAKE_EXPORT_PACKAGE_REGISTRY ON)
-  endif (NOT DEFINED CMAKE_EXPORT_PACKAGE_REGISTRY)
-endif (POLICY CMP0090)
+#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}")
 
-# Disable warning about find_package(CUDA).
-# CUDA language support is lacking for clang as the CUDA compiler
-# until at least cmake version 3.18.  Even then, there seems to be
-# issues on Windows+Ninja in passing build flags.  Continue using
-# the "old" way for now.
-if (POLICY CMP0146)
-  cmake_policy(SET CMP0146 OLD)
-endif ()
+if(EIGEN_SVN_REVISION)
+  set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER} (SVN revision ${EIGEN_SVN_REVISION})")
+else(EIGEN_SVN_REVISION)
+  set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER}")
+endif(EIGEN_SVN_REVISION)
 
-# Normalize DESTINATION paths
-if (POLICY CMP0177)
-  cmake_policy(SET CMP0177 NEW)
-endif ()
+cmake_minimum_required(VERSION 2.6.2)
 
-#==============================================================================
-# CMake Project.
-#==============================================================================
-
-project(Eigen3)
-
-# Remove this block after bumping CMake to v3.21.0
-# PROJECT_IS_TOP_LEVEL is defined then by default
-if(CMAKE_VERSION VERSION_LESS 3.21.0)
-  if(CMAKE_SOURCE_DIR STREQUAL CMAKE_CURRENT_SOURCE_DIR)
-    set(PROJECT_IS_TOP_LEVEL ON)
-  else()
-    set(PROJECT_IS_TOP_LEVEL OFF)
-  endif()
-endif()
-
-#==============================================================================
-# Build ON/OFF Settings.
-#==============================================================================
-# Determine if we should build tests.
-include(CMakeDependentOption)
-cmake_dependent_option(BUILD_TESTING "Enable creation of tests." ON "PROJECT_IS_TOP_LEVEL" OFF)
-option(EIGEN_BUILD_TESTING "Enable creation of Eigen tests." ${BUILD_TESTING})
-option(EIGEN_LEAVE_TEST_IN_ALL_TARGET "Leaves tests in the all target, needed by ctest for automatic building." OFF)
-
-# Determine if we should build BLAS/LAPACK implementations.
-option(EIGEN_BUILD_BLAS "Toggles the building of the Eigen Blas library" ${PROJECT_IS_TOP_LEVEL})
-option(EIGEN_BUILD_LAPACK "Toggles the building of the included Eigen LAPACK library" ${PROJECT_IS_TOP_LEVEL})
-if (EIGEN_BUILD_BLAS OR EIGEN_BUILD_LAPACK)
-  # BLAS and LAPACK currently need a fortran compiler.
-  include(CMakeDetermineFortranCompiler)
-  if (NOT CMAKE_Fortran_COMPILER)
-    set(EIGEN_BUILD_BLAS OFF)
-    set(EIGEN_BUILD_LAPACK OFF)
-  else()
-    # Determine if we should build shared libraries for BLAS/LAPACK on this platform.
-    get_cmake_property(EIGEN_BUILD_SHARED_LIBS TARGET_SUPPORTS_SHARED_LIBS)
-  endif()
-endif()
+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)
-option(EIGEN_BUILD_SPBENCH "Build sparse benchmark suite" OFF)
-# Avoid building docs if included from another project.
-# Building documentation requires creating and running executables on the host
-# platform.  We shouldn't do this if cross-compiling.
-if (PROJECT_IS_TOP_LEVEL AND NOT CMAKE_CROSSCOMPILING)
-  set(EIGEN_BUILD_DOC_DEFAULT ON)
-endif()
-option(EIGEN_BUILD_DOC "Enable creation of Eigen documentation" ${EIGEN_BUILD_DOC_DEFAULT})
 
-option(EIGEN_BUILD_DEMOS "Toggles the building of the Eigen demos" ${PROJECT_IS_TOP_LEVEL})
+if(EIGEN_BUILD_LIB)
+  option(EIGEN_TEST_LIB "Build the unit tests using the library (disable -pedantic)" OFF)
+endif(EIGEN_BUILD_LIB)
 
-# Disable pkgconfig only for native Windows builds
-if(NOT WIN32 OR NOT CMAKE_HOST_SYSTEM_NAME MATCHES Windows)
-  option(EIGEN_BUILD_PKGCONFIG "Build pkg-config .pc file for Eigen" ${PROJECT_IS_TOP_LEVEL})
-endif()
-option(EIGEN_BUILD_CMAKE_PACKAGE "Enables the creation of EigenConfig.cmake and related files" ${PROJECT_IS_TOP_LEVEL})
+set(CMAKE_INCLUDE_CURRENT_DIR ON)
 
-if (EIGEN_BUILD_TESTING OR EIGEN_BUILD_BLAS OR EIGEN_BUILD_LAPACK OR EIGEN_BUILT_BTL OR EIGEN_BUILD_BTL OR EIGEN_BUILD_SPBENCH OR EIGEN_BUILD_DOC OR EIGEN_BUILD_DEMOS)
-  set(EIGEN_IS_BUILDING_ ON)
-endif()
-
-#==============================================================================
-# Version Info.
-#==============================================================================
-
-# If version information is not provided, automatically parse the version number
-# from header files.
-file(READ "${PROJECT_SOURCE_DIR}/Eigen/Version" _eigen_version_header)
-if (NOT DEFINED EIGEN_WORLD_VERSION)
-  string(REGEX MATCH "define[ \t]+EIGEN_WORLD_VERSION[ \t]+([0-9]+)" _eigen_world_version_match "${_eigen_version_header}")
-  set(EIGEN_WORLD_VERSION "${CMAKE_MATCH_1}")
-endif()
-if (NOT DEFINED EIGEN_MAJOR_VERSION)
-  string(REGEX MATCH "define[ \t]+EIGEN_MAJOR_VERSION[ \t]+([0-9]+)" _eigen_major_version_match "${_eigen_version_header}")
-  set(EIGEN_MAJOR_VERSION "${CMAKE_MATCH_1}")
-endif()
-if (NOT DEFINED EIGEN_MINOR_VERSION)
-  string(REGEX MATCH "define[ \t]+EIGEN_MINOR_VERSION[ \t]+([0-9]+)" _eigen_minor_version_match "${_eigen_version_header}")
-  set(EIGEN_MINOR_VERSION "${CMAKE_MATCH_1}")
-endif()
-if (NOT DEFINED EIGEN_PATCH_VERSION)
-  string(REGEX MATCH "define[ \t]+EIGEN_PATCH_VERSION[ \t]+([0-9]+)" _eigen_patch_version_match "${_eigen_version_header}")
-  set(EIGEN_PATCH_VERSION "${CMAKE_MATCH_1}")
-endif()
-if (NOT DEFINED EIGEN_PRERELEASE_VERSION)
-  set(EIGEN_PRERELEASE_VERSION "dev")
-endif()
-
-# If we are in a git repo, extract a changeset.
-if(IS_DIRECTORY ${CMAKE_SOURCE_DIR}/.git)
-  # if the git program is absent or this will leave the EIGEN_GIT_REVNUM string empty,
-  # but won't stop CMake.
-  execute_process(COMMAND git ls-remote -q ${CMAKE_SOURCE_DIR} HEAD OUTPUT_VARIABLE EIGEN_GIT_OUTPUT)
-endif()
-
-# extract the git rev number from the git output...
-if(EIGEN_GIT_OUTPUT)
-  string(REGEX MATCH "^([0-9;a-f]+).*" EIGEN_GIT_CHANGESET_MATCH "${EIGEN_GIT_OUTPUT}")
-  set(EIGEN_GIT_REVNUM "${CMAKE_MATCH_1}")
-endif()
-
-if (NOT DEFINED EIGEN_BUILD_VERSION AND DEFINED EIGEN_GIT_REVNUM)
-  string(SUBSTRING "${EIGEN_GIT_REVNUM}" 0 8 EIGEN_BUILD_VERSION)
-else()
-  set(EIGEN_BUILD_VERSION "")
-endif()
-
-# The EIGEN_VERSION_NUMBER must be of the form <major.minor.patch>.
-# The EIGEN_VERSION_STRING can contain the preprelease/build strings.
-set(EIGEN_VERSION_NUMBER "${EIGEN_MAJOR_VERSION}.${EIGEN_MINOR_VERSION}.${EIGEN_PATCH_VERSION}")
-set(EIGEN_VERSION_STRING "${EIGEN_VERSION_NUMBER}")
-if (NOT "x${EIGEN_PRERELEASE_VERSION}" STREQUAL "x")
-  set(EIGEN_VERSION_STRING "${EIGEN_VERSION_STRING}-${EIGEN_PRERELEASE_VERSION}")
-endif()
-if (NOT "x${EIGEN_BUILD_VERSION}" STREQUAL "x")
-  set(EIGEN_VERSION_STRING "${EIGEN_VERSION_STRING}+${EIGEN_BUILD_VERSION}")
-endif()
-
-
-# Generate version file.
-configure_file("${CMAKE_CURRENT_SOURCE_DIR}/cmake/Version.in"
-               "${CMAKE_CURRENT_BINARY_DIR}/include/Eigen/Version")
-
-#==============================================================================
-# Install Path Configuration.
-#==============================================================================
-
-# Unconditionally allow install of targets to support nested dependency
-# installations.
-#
-# Note: projects that depend on Eigen should _probably_ exclude installing
-# Eigen by default (e.g. by using EXCLUDE_FROM_ALL when using
-# FetchContent_Declare or add_subdirectory) to avoid overwriting a previous
-# installation.
-
-include(GNUInstallDirs)
-# Backward compatibility support for EIGEN_INCLUDE_INSTALL_DIR
-if(EIGEN_INCLUDE_INSTALL_DIR)
-  message(WARNING "EIGEN_INCLUDE_INSTALL_DIR is deprecated. Use INCLUDE_INSTALL_DIR instead.")
-endif()
-
-if(EIGEN_INCLUDE_INSTALL_DIR AND NOT INCLUDE_INSTALL_DIR)
-  set(INCLUDE_INSTALL_DIR ${EIGEN_INCLUDE_INSTALL_DIR}
-      CACHE PATH "The directory relative to CMAKE_INSTALL_PREFIX where Eigen header files are installed")
-else()
-  set(INCLUDE_INSTALL_DIR
-      "${CMAKE_INSTALL_INCLUDEDIR}/eigen3"
-      CACHE PATH "The directory relative to CMAKE_INSTALL_PREFIX where Eigen header files are installed"
-      )
-endif()
-set(CMAKEPACKAGE_INSTALL_DIR
-    "${CMAKE_INSTALL_DATADIR}/eigen3/cmake"
-    CACHE PATH "The directory relative to CMAKE_INSTALL_PREFIX where Eigen3Config.cmake is installed"
-    )
-set(PKGCONFIG_INSTALL_DIR
-    "${CMAKE_INSTALL_DATADIR}/pkgconfig"
-    CACHE PATH "The directory relative to CMAKE_INSTALL_PREFIX where eigen3.pc is installed"
-    )
-
-foreach(var INCLUDE_INSTALL_DIR CMAKEPACKAGE_INSTALL_DIR PKGCONFIG_INSTALL_DIR)
-  # If an absolute path is specified, make it relative to "{CMAKE_INSTALL_PREFIX}".
-  if(IS_ABSOLUTE "${${var}}")
-    file(RELATIVE_PATH "${var}" "${CMAKE_INSTALL_PREFIX}" "${${var}}")
-  endif()
-endforeach()
-
-#==============================================================================
-# Eigen Library.
-#==============================================================================
-
-# Alias Eigen_*_DIR to Eigen3_*_DIR:
-set(Eigen_SOURCE_DIR ${Eigen3_SOURCE_DIR})
-set(Eigen_BINARY_DIR ${Eigen3_BINARY_DIR})
-
-# Imported target support
-add_library (eigen INTERFACE)
-add_library (Eigen3::Eigen ALIAS eigen)
-target_include_directories (eigen INTERFACE
-  $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
-  $<INSTALL_INTERFACE:${INCLUDE_INSTALL_DIR}>
-)
-
-# Eigen requires at least C++14
-target_compile_features (eigen INTERFACE cxx_std_14)
-
-# Export as title case Eigen
-set_target_properties (eigen PROPERTIES EXPORT_NAME Eigen)
-
-#==============================================================================
-# Install Rule Configuration.
-#==============================================================================
-
-install(FILES
-  signature_of_eigen3_matrix_library
-  DESTINATION ${INCLUDE_INSTALL_DIR} COMPONENT Devel
-  )
-
-if(EIGEN_BUILD_PKGCONFIG)
-    configure_file(eigen3.pc.in eigen3.pc @ONLY)
-    install(FILES ${CMAKE_CURRENT_BINARY_DIR}/eigen3.pc
-        DESTINATION ${PKGCONFIG_INSTALL_DIR})
-endif()
-
-install(DIRECTORY Eigen DESTINATION ${INCLUDE_INSTALL_DIR} COMPONENT Devel)
-# Replace the "Version" header file with the generated one.
-install(FILES ${CMAKE_CURRENT_BINARY_DIR}/include/Eigen/Version
-    DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/ COMPONENT Devel)
-
-install(TARGETS eigen EXPORT Eigen3Targets)
-
-if(EIGEN_BUILD_CMAKE_PACKAGE)
-  include (CMakePackageConfigHelpers)
-  configure_package_config_file (
-    ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3Config.cmake.in
-    ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
-    INSTALL_DESTINATION ${CMAKEPACKAGE_INSTALL_DIR}
-    NO_SET_AND_CHECK_MACRO # Eigen does not provide legacy style defines
-    NO_CHECK_REQUIRED_COMPONENTS_MACRO # Eigen does not provide components
-  )
-
-  set(CVF_VERSION "${EIGEN_VERSION_NUMBER}")
-  configure_file("${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3ConfigVersion.cmake.in"
-                 "Eigen3ConfigVersion.cmake"
-                 @ONLY)
-
-  # The Eigen target will be located in the Eigen3 namespace. Other CMake
-  # targets can refer to it using Eigen3::Eigen.
-  export (TARGETS eigen NAMESPACE Eigen3:: FILE Eigen3Targets.cmake)
-  # Export Eigen3 package to CMake registry such that it can be easily found by
-  # CMake even if it has not been installed to a standard directory.
-  export (PACKAGE Eigen3)
-
-  install (EXPORT Eigen3Targets NAMESPACE Eigen3:: DESTINATION ${CMAKEPACKAGE_INSTALL_DIR})
-
-  install (FILES ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
-                ${CMAKE_CURRENT_BINARY_DIR}/Eigen3ConfigVersion.cmake
-          DESTINATION ${CMAKEPACKAGE_INSTALL_DIR})
-
-  # Add uninstall target
-  if(NOT TARGET uninstall AND PROJECT_IS_TOP_LEVEL)
-    add_custom_target ( uninstall
-        COMMAND ${CMAKE_COMMAND} -P ${CMAKE_CURRENT_SOURCE_DIR}/cmake/EigenUninstall.cmake)
-  endif()
-endif()
-
-#==============================================================================
-# General Build Configuration.
-#==============================================================================
-
-# Avoid setting the standard in a parent if unset.
-if(PROJECT_IS_TOP_LEVEL)
-  set(CMAKE_CXX_STANDARD 14 CACHE STRING "Default C++ standard")
-  set(CMAKE_CXX_STANDARD_REQUIRED ON CACHE BOOL "Require C++ standard")
-  set(CMAKE_CXX_EXTENSIONS OFF CACHE BOOL "Allow C++ extensions")
-endif()
-
-# Guard against in-source builds
-if(${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 (PROJECT_IS_TOP_LEVEL AND NOT CMAKE_BUILD_TYPE)
-  set(CMAKE_BUILD_TYPE "Release")
-endif()
-
-# Only try to figure out how to link the math library if we are building something.
-# Otherwise, let the parent project deal with dependencies.
-if (EIGEN_IS_BUILDING_)
-  # Use Eigen's cmake files.
-  set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
-
-  set(CMAKE_INCLUDE_CURRENT_DIR OFF)
-
-  find_package(StandardMathLibrary)
-  set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "")
-  if(NOT STANDARD_MATH_LIBRARY_FOUND)
-    message(FATAL_ERROR
-      "Can't link to the standard math library. Please report to the Eigen developers, telling them about your platform.")
-  else()
-    if(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO)
-      set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "${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: ${EIGEN_STANDARD_LIBRARIES_TO_LINK_TO}")
-  else()
-    message(STATUS "Standard libraries to link to explicitly: none")
-  endif()
-
-  # Default tests/examples/libraries to row-major.
-  option(EIGEN_DEFAULT_TO_ROW_MAJOR "Use row-major as default matrix storage order" OFF)
-  if(EIGEN_DEFAULT_TO_ROW_MAJOR)
-    add_definitions("-DEIGEN_DEFAULT_TO_ROW_MAJOR")
-  endif()
-endif()
-
-#==============================================================================
-# Test Configuration.
-#==============================================================================
-
-if (EIGEN_BUILD_TESTING)
-  function(ei_maybe_separate_arguments variable mode args)
-    # Use separate_arguments if the input is a single string containing a space.
-    # Otherwise, if it is already a list or doesn't have a space, just propagate
-    # the original value.  This is to better support multi-argument lists.
-    list(LENGTH args list_length)
-    if (${list_length} EQUAL 1)
-      string(FIND "${args}" " " has_space)
-      if (${has_space} GREATER -1)
-        separate_arguments(args ${mode} "${args}")
-      endif()
-    endif()
-    set(${variable} ${args} PARENT_SCOPE)
-  endfunction(ei_maybe_separate_arguments)
-
-  include(CheckCXXCompilerFlag)
-  macro(ei_add_cxx_compiler_flag FLAG)
-    string(REGEX REPLACE "-" "" SFLAG1 ${FLAG})
-    string(REGEX REPLACE "\\+" "p" SFLAG ${SFLAG1})
-    check_cxx_compiler_flag(${FLAG} COMPILER_SUPPORT_${SFLAG})
-    if(COMPILER_SUPPORT_${SFLAG})
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ${FLAG}")
-    endif()
-  endmacro()
-
-  set(EIGEN_TEST_CUSTOM_LINKER_FLAGS  "" CACHE STRING "Additional linker flags when linking unit tests.")
-  set(EIGEN_TEST_CUSTOM_CXX_FLAGS     "" CACHE STRING "Additional compiler flags when compiling unit tests.")
-  # Convert space-separated arguments into CMake lists for downstream consumption.
-  ei_maybe_separate_arguments(EIGEN_TEST_CUSTOM_LINKER_FLAGS NATIVE_COMMAND "${EIGEN_TEST_CUSTOM_LINKER_FLAGS}")
-  ei_maybe_separate_arguments(EIGEN_TEST_CUSTOM_CXX_FLAGS NATIVE_COMMAND "${EIGEN_TEST_CUSTOM_CXX_FLAGS}")
-
-  option(EIGEN_SPLIT_LARGE_TESTS "Split large tests into smaller executables" ON)
-  set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320")
-
-  # Flags for tests.
-  if(NOT MSVC)
-    # We assume that other compilers are partly compatible with GNUCC
-
-    # clang outputs some warnings for unknown 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("-Wshorten-64-to-32")
-    ei_add_cxx_compiler_flag("-Wlogical-op")
-    ei_add_cxx_compiler_flag("-Wenum-conversion")
-    ei_add_cxx_compiler_flag("-Wc++11-extensions")
-    ei_add_cxx_compiler_flag("-Wdouble-promotion")
-    # ei_add_cxx_compiler_flag("-Wconversion")
-    ei_add_cxx_compiler_flag("-Wshadow")
-    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-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")                   # disable ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
-
-    # Clang emits warnings about unused flag.
-    if (NOT CMAKE_CXX_COMPILER_ID MATCHES "Clang")
-      ei_add_cxx_compiler_flag("-fno-check-new")
-    endif()
-
-
-    if(ANDROID_NDK)
-      ei_add_cxx_compiler_flag("-pie")
-      ei_add_cxx_compiler_flag("-fPIE")
-    endif()
-
-    set(CMAKE_REQUIRED_FLAGS "")
+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_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF)
     if(EIGEN_TEST_SSE2)
       set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -msse2")
-      message(STATUS "Enabling SSE2 in tests/examples")
-    endif()
+      message("Enabling SSE2 in tests/examples")
+    endif(EIGEN_TEST_SSE2)
 
     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()
+      message("Enabling SSE3 in tests/examples")
+    endif(EIGEN_TEST_SSE3)
 
     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()
+      message("Enabling SSSE3 in tests/examples")
+    endif(EIGEN_TEST_SSSE3)
 
-    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_AVX "Enable/Disable AVX in tests/examples" OFF)
-    if(EIGEN_TEST_AVX)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx")
-      message(STATUS "Enabling AVX in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_FMA "Enable/Disable FMA in tests/examples" OFF)
-    if(EIGEN_TEST_FMA AND NOT EIGEN_TEST_NEON)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfma")
-      message(STATUS "Enabling FMA in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_AVX2 "Enable/Disable AVX2 in tests/examples" OFF)
-    if(EIGEN_TEST_AVX2)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx2 -mfma")
-      message(STATUS "Enabling AVX2 in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_AVX512 "Enable/Disable AVX512 in tests/examples" OFF)
-    if(EIGEN_TEST_AVX512)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx512f -mfma")
-      message(STATUS "Enabling AVX512 in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_AVX512DQ "Enable/Disable AVX512DQ in tests/examples" OFF)
-    if(EIGEN_TEST_AVX512DQ)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx512dq -mfma")
-      message(STATUS "Enabling AVX512DQ in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_AVX512FP16 "Enable/Disable AVX512-FP16 in tests/examples" OFF)
-    if(EIGEN_TEST_AVX512FP16)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx512f -mfma -mavx512vl -mavx512fp16")
-    message(STATUS "Enabling AVX512-FP16 in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_F16C "Enable/Disable F16C in tests/examples" OFF)
-    if(EIGEN_TEST_F16C)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mf16c")
-      message(STATUS "Enabling F16C in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_ALTIVEC "Enable/Disable AltiVec in tests/examples" OFF)
+    option(EIGEN_TEST_ALTIVEC "Enable/Disable altivec in tests/examples" OFF)
     if(EIGEN_TEST_ALTIVEC)
       set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -maltivec -mabi=altivec")
-      message(STATUS "Enabling AltiVec in tests/examples")
-    endif()
+      message("Enabling AltiVec in tests/examples")
+    endif(EIGEN_TEST_ALTIVEC)
 
-    option(EIGEN_TEST_VSX "Enable/Disable VSX in tests/examples" OFF)
-    if(EIGEN_TEST_VSX)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -m64 -mvsx")
-      message(STATUS "Enabling VSX in tests/examples")
-    endif()
+  endif(CMAKE_SYSTEM_NAME MATCHES Linux)
+endif(CMAKE_COMPILER_IS_GNUCXX)
 
-    option(EIGEN_TEST_MSA "Enable/Disable MSA in tests/examples" OFF)
-    if(EIGEN_TEST_MSA)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mmsa")
-      message(STATUS "Enabling MSA in tests/examples")
-    endif()
+if(MSVC)
+  set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} ")
 
-   option(EIGEN_TEST_LSX "Enable/Disable LSX in tests/examples" OFF)
-   if(EIGEN_TEST_LSX)
-     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mlsx")
-     message(STATUS "Enabling LSX in tests/examples")
-   endif()
+  option(EIGEN_TEST_SSE2 "Enable/Disable SSE2 in tests/examples" OFF)
+  if(EIGEN_TEST_SSE2)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:SSE2")
+    message("Enabling SSE2 in tests/examples")
+  endif(EIGEN_TEST_SSE2)
+endif(MSVC)
 
-    option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF)
-    if(EIGEN_TEST_NEON)
-      if(EIGEN_TEST_FMA)
-        set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon-vfpv4")
-      else()
-        set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon")
-      endif()
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfloat-abi=hard")
-      message(STATUS "Enabling NEON in tests/examples")
-    endif()
+option(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION "Disable explicit vectorization in tests/examples" OFF)
+if(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
+  add_definitions(-DEIGEN_DONT_VECTORIZE=1)
+  message("Disabling vectorization in tests/examples")
+endif(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
 
-    option(EIGEN_TEST_NEON64 "Enable/Disable Neon in tests/examples" OFF)
-    if(EIGEN_TEST_NEON64)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
-      message(STATUS "Enabling NEON in tests/examples")
-    endif()
+include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
 
-    option(EIGEN_TEST_Z13 "Enable/Disable S390X(zEC13) ZVECTOR in tests/examples" OFF)
-    if(EIGEN_TEST_Z13)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -march=z13 -mzvector")
-      message(STATUS "Enabling S390X(zEC13) ZVECTOR in tests/examples")
-    endif()
+add_subdirectory(Eigen)
 
-    option(EIGEN_TEST_Z14 "Enable/Disable S390X(zEC14) ZVECTOR in tests/examples" OFF)
-    if(EIGEN_TEST_Z14)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -march=z14 -mzvector")
-      message(STATUS "Enabling S390X(zEC13) ZVECTOR in tests/examples")
-    endif()
+if(EIGEN_BUILD_TESTS)
+  include(CTest)
+  add_subdirectory(test)
+endif(EIGEN_BUILD_TESTS)
 
-    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()
+add_subdirectory(doc)
 
-  else()
-    # 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 deactivate selectively)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /EHsc /wd4127 /wd4505 /wd4714")
+if(EIGEN_BUILD_DEMOS)
+  add_subdirectory(demos)
+endif(EIGEN_BUILD_DEMOS)
 
-    # 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 "${CMAKE_CXX_FLAGS} /arch:SSE2")
-      endif()
-      message(STATUS "Enabling SSE2 in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_AVX "Enable/Disable AVX in tests/examples" OFF)
-    if(EIGEN_TEST_AVX)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX")
-      message(STATUS "Enabling AVX in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_FMA "Enable/Disable FMA/AVX2 in tests/examples" OFF)
-    option(EIGEN_TEST_AVX2 "Enable/Disable FMA/AVX2 in tests/examples" OFF)
-    if((EIGEN_TEST_FMA AND NOT EIGEN_TEST_NEON) OR EIGEN_TEST_AVX2)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX2")
-      message(STATUS "Enabling FMA/AVX2 in tests/examples")
-    endif()
-
-    option(EIGEN_TEST_AVX512 "Enable/Disable AVX512 in tests/examples" OFF)
-    option(EIGEN_TEST_AVX512DQ "Enable/Disable AVX512DQ in tests/examples" OFF)
-    if(EIGEN_TEST_AVX512 OR EIGEN_TEST_AVX512DQ)
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /arch:AVX512")
-      message(STATUS "Enabling AVX512 in tests/examples")
-    endif()
-
-  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(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_NO_EXCEPTIONS "Disables C++ exceptions" OFF)
-  if(EIGEN_TEST_NO_EXCEPTIONS)
-    ei_add_cxx_compiler_flag("-fno-exceptions")
-    message(STATUS "Disabling exceptions in tests/examples")
-  endif()
-
-  set(EIGEN_CUDA_CXX_FLAGS "" CACHE STRING "Additional flags to pass to the cuda compiler.")
-  set(EIGEN_CUDA_COMPUTE_ARCH 30 CACHE STRING "The CUDA compute architecture(s) to target when compiling CUDA code")
-
-  option(EIGEN_TEST_SYCL "Add Sycl support." OFF)
-  if(EIGEN_TEST_SYCL)
-    option(EIGEN_SYCL_DPCPP "Use the DPCPP Sycl implementation (DPCPP is default SYCL-Compiler)." ON)
-    option(EIGEN_SYCL_TRISYCL "Use the triSYCL Sycl implementation." OFF)
-    option(EIGEN_SYCL_ComputeCpp "Use the ComputeCPP Sycl implementation." OFF)
-
-    # Building options
-    # https://developer.codeplay.com/products/computecpp/ce/2.11.0/guides/eigen-overview/options-for-building-eigen-sycl
-    option(EIGEN_SYCL_USE_DEFAULT_SELECTOR "Use sycl default selector to select the preferred device." OFF)
-    option(EIGEN_SYCL_NO_LOCAL_MEM "Build for devices without dedicated shared memory." OFF)
-    option(EIGEN_SYCL_LOCAL_MEM "Allow the use of local memory (enabled by default)." ON)
-    option(EIGEN_SYCL_LOCAL_THREAD_DIM0 "Set work group size for dimension 0." 16)
-    option(EIGEN_SYCL_LOCAL_THREAD_DIM1 "Set work group size for dimension 1." 16)
-    option(EIGEN_SYCL_ASYNC_EXECUTION "Allow asynchronous execution (enabled by default)." ON)
-    option(EIGEN_SYCL_DISABLE_SKINNY "Disable optimization for tall/skinny matrices." OFF)
-    option(EIGEN_SYCL_DISABLE_DOUBLE_BUFFER "Disable double buffer." OFF)
-    option(EIGEN_SYCL_DISABLE_SCALAR "Disable scalar contraction." OFF)
-    option(EIGEN_SYCL_DISABLE_GEMV "Disable GEMV and create a single kernel to calculate contraction instead." OFF)
-
-    set(EIGEN_SYCL ON)
-    set(CMAKE_CXX_STANDARD 17)
-    set(CMAKE_CXX_FLAGS  "${CMAKE_CXX_FLAGS} -Wno-deprecated-declarations -Wno-shorten-64-to-32 -Wno-cast-align")
-    set(CMAKE_CXX_FLAGS  "${CMAKE_CXX_FLAGS} -Wno-deprecated-copy-with-user-provided-copy -Wno-unused-variable")
-    set (CMAKE_MODULE_PATH "${CMAKE_ROOT}/Modules" "cmake/Modules/" "${CMAKE_MODULE_PATH}")
-    find_package(Threads REQUIRED)
-    if(EIGEN_SYCL_TRISYCL)
-      message(STATUS "Using triSYCL")
-      include(FindTriSYCL)
-    elseif(EIGEN_SYCL_ComputeCpp)
-      message(STATUS "Using ComputeCPP SYCL")
-      include(FindComputeCpp)
-      set(COMPUTECPP_DRIVER_DEFAULT_VALUE OFF)
-      if (NOT MSVC)
-        set(COMPUTECPP_DRIVER_DEFAULT_VALUE ON)
-      endif()
-      option(COMPUTECPP_USE_COMPILER_DRIVER
-              "Use ComputeCpp driver instead of a 2 steps compilation"
-              ${COMPUTECPP_DRIVER_DEFAULT_VALUE}
-              )
-    else() #Default SYCL compiler is DPCPP (EIGEN_SYCL_DPCPP)
-      set(DPCPP_SYCL_TARGET "spir64" CACHE STRING "Default target for Intel CPU/GPU")
-      message(STATUS "Using DPCPP")
-      find_package(DPCPP)
-      add_definitions(-DSYCL_COMPILER_IS_DPCPP)
-    endif(EIGEN_SYCL_TRISYCL)
-    if(EIGEN_DONT_VECTORIZE_SYCL)
-      message(STATUS "Disabling SYCL vectorization in tests/examples")
-      # When disabling SYCL vectorization, also disable Eigen default vectorization
-      add_definitions(-DEIGEN_DONT_VECTORIZE=1)
-      add_definitions(-DEIGEN_DONT_VECTORIZE_SYCL=1)
-    endif()
-  endif()
-
-  include(EigenConfigureTesting)
-
-  if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
-    # CTest automatic test building relies on the "all" target.
-    add_subdirectory(test)
-    add_subdirectory(failtest)
-  else()
-    add_subdirectory(test EXCLUDE_FROM_ALL)
-    add_subdirectory(failtest EXCLUDE_FROM_ALL)
-  endif()
-
-  ei_testing_print_summary()
-
-  if (EIGEN_SPLIT_TESTSUITE)
-    ei_split_testsuite("${EIGEN_SPLIT_TESTSUITE}")
-  endif()
-endif(EIGEN_BUILD_TESTING)
-
-#==============================================================================
-# Other Build Configurations.
-#==============================================================================
-add_subdirectory(unsupported)
-
-if(EIGEN_BUILD_BLAS)
-  add_subdirectory(blas)
-endif()
-
-if (EIGEN_BUILD_LAPACK)
-  add_subdirectory(lapack)
-endif()
-
-if(EIGEN_BUILD_DOC)
-  add_subdirectory(doc EXCLUDE_FROM_ALL)
-endif()
-
-# TODO: consider also replacing EIGEN_BUILD_BTL by a custom target "make btl"?
 if(EIGEN_BUILD_BTL)
-  add_subdirectory(bench/btl EXCLUDE_FROM_ALL)
-endif()
-
-if(NOT WIN32 AND EIGEN_BUILD_SPBENCH)
-  add_subdirectory(bench/spbench EXCLUDE_FROM_ALL)
-endif()
-
-if (EIGEN_BUILD_DEMOS)
-  add_subdirectory(demos EXCLUDE_FROM_ALL)
-endif()
-
-if (PROJECT_IS_TOP_LEVEL)
-  # must be after test and unsupported, for configuring buildtests.in
-  add_subdirectory(scripts EXCLUDE_FROM_ALL)
-  configure_file(scripts/cdashtesting.cmake.in cdashtesting.cmake @ONLY)
-endif()
-
-#==============================================================================
-# Summary.
-#==============================================================================
-
-if(PROJECT_IS_TOP_LEVEL)
-  string(TOLOWER "${CMAKE_GENERATOR}" cmake_generator_tolower)
-  if(cmake_generator_tolower MATCHES "makefile")
-    message(STATUS "Available targets (use: make TARGET):")
-  else()
-    message(STATUS "Available targets (use: cmake --build . --target TARGET):")
-  endif()
-  message(STATUS "------------+--------------------------------------------------------------")
-  message(STATUS "Target      |   Description")
-  message(STATUS "------------+--------------------------------------------------------------")
-  message(STATUS "install     | Install Eigen. Headers will be installed to:")
-  message(STATUS "            |     <CMAKE_INSTALL_PREFIX>/<INCLUDE_INSTALL_DIR>")
-  message(STATUS "            |   Using the following values:")
-  message(STATUS "            |     CMAKE_INSTALL_PREFIX: ${CMAKE_INSTALL_PREFIX}")
-  message(STATUS "            |     INCLUDE_INSTALL_DIR:  ${INCLUDE_INSTALL_DIR}")
-  message(STATUS "            |   Change the install location of Eigen headers using:")
-  message(STATUS "            |     cmake . -DCMAKE_INSTALL_PREFIX=yourprefix")
-  message(STATUS "            |   Or:")
-  message(STATUS "            |     cmake . -DINCLUDE_INSTALL_DIR=yourdir")
-  message(STATUS "uninstall   | Remove files installed by the install target")
-  if (EIGEN_BUILD_DOC)
-    message(STATUS "doc         | Generate the API documentation, requires Doxygen & LaTeX")
-    message(STATUS "install-doc | Install the API documentation")
-  endif()
-  if(EIGEN_BUILD_TESTING)
-    message(STATUS "check       | Build and run the unit-tests. Read this page:")
-    message(STATUS "            |   http://eigen.tuxfamily.org/index.php?title=Tests")
-  endif()
-  if (EIGEN_BUILD_BLAS)
-    message(STATUS "blas        | Build BLAS library (not the same thing as Eigen)")
-  endif()
-  if (EIGEN_BUILD_LAPACK)
-    message(STATUS "lapack      | Build LAPACK subset library (not the same thing as Eigen)")
-  endif()
-  message(STATUS "------------+--------------------------------------------------------------")
-  message(STATUS "")
-endif()
-
-message(STATUS "")
-message(STATUS "Configured Eigen ${EIGEN_VERSION_STRING}")
-message(STATUS "")
+  add_subdirectory(bench/btl)
+endif(EIGEN_BUILD_BTL)

COPYING

@@ -0,0 +1,674 @@
+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
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+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. Limitation of Liability.
+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM 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 PROGRAM (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 PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state 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 program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: 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 3 of the License, or
+    (at your option) any later version.
+
+    This program 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 General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+    <program>  Copyright (C) <year>  <name of author>
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License.  Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<http://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library.  If this is what you want to do, use the GNU Lesser General
+Public License instead of this License.  But first, please read
+<http://www.gnu.org/philosophy/why-not-lgpl.html>.

COPYING.APACHE

@@ -1,203 +0,0 @@
-/*
-                                 Apache License
-                           Version 2.0, January 2004
-                        http://www.apache.org/licenses/
-
-   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
-
-   1. Definitions.
-
-      "License" shall mean the terms and conditions for use, reproduction,
-      and distribution as defined by Sections 1 through 9 of this document.
-
-      "Licensor" shall mean the copyright owner or entity authorized by
-      the copyright owner that is granting the License.
-
-      "Legal Entity" shall mean the union of the acting entity and all
-      other entities that control, are controlled by, or are under common
-      control with that entity. For the purposes of this definition,
-      "control" means (i) the power, direct or indirect, to cause the
-      direction or management of such entity, whether by contract or
-      otherwise, or (ii) ownership of fifty percent (50%) or more of the
-      outstanding shares, or (iii) beneficial ownership of such entity.
-
-      "You" (or "Your") shall mean an individual or Legal Entity
-      exercising permissions granted by this License.
-
-      "Source" form shall mean the preferred form for making modifications,
-      including but not limited to software source code, documentation
-      source, and configuration files.
-
-      "Object" form shall mean any form resulting from mechanical
-      transformation or translation of a Source form, including but
-      not limited to compiled object code, generated documentation,
-      and conversions to other media types.
-
-      "Work" shall mean the work of authorship, whether in Source or
-      Object form, made available under the License, as indicated by a
-      copyright notice that is included in or attached to the work
-      (an example is provided in the Appendix below).
-
-      "Derivative Works" shall mean any work, whether in Source or Object
-      form, that is based on (or derived from) the Work and for which the
-      editorial revisions, annotations, elaborations, or other modifications
-      represent, as a whole, an original work of authorship. For the purposes
-      of this License, Derivative Works shall not include works that remain
-      separable from, or merely link (or bind by name) to the interfaces of,
-      the Work and Derivative Works thereof.
-
-      "Contribution" shall mean any work of authorship, including
-      the original version of the Work and any modifications or additions
-      to that Work or Derivative Works thereof, that is intentionally
-      submitted to Licensor for inclusion in the Work by the copyright owner
-      or by an individual or Legal Entity authorized to submit on behalf of
-      the copyright owner. For the purposes of this definition, "submitted"
-      means any form of electronic, verbal, or written communication sent
-      to the Licensor or its representatives, including but not limited to
-      communication on electronic mailing lists, source code control systems,
-      and issue tracking systems that are managed by, or on behalf of, the
-      Licensor for the purpose of discussing and improving the Work, but
-      excluding communication that is conspicuously marked or otherwise
-      designated in writing by the copyright owner as "Not a Contribution."
-
-      "Contributor" shall mean Licensor and any individual or Legal Entity
-      on behalf of whom a Contribution has been received by Licensor and
-      subsequently incorporated within the Work.
-
-   2. Grant of Copyright License. Subject to the terms and conditions of
-      this License, each Contributor hereby grants to You a perpetual,
-      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
-      copyright license to reproduce, prepare Derivative Works of,
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-      Work and such Derivative Works in Source or Object form.
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-      worldwide, non-exclusive, no-charge, royalty-free, irrevocable
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-      where such license applies only to those patent claims licensable
-      by such Contributor that are necessarily infringed by their
-      Contribution(s) alone or by combination of their Contribution(s)
-      with the Work to which such Contribution(s) was submitted. If You
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-      cross-claim or counterclaim in a lawsuit) alleging that the Work
-      or a Contribution incorporated within the Work constitutes direct
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-          Derivative Works a copy of this License; and
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-          of the NOTICE file are for informational purposes only and
-          do not modify the License. You may add Your own attribution
-          notices within Derivative Works that You distribute, alongside
-          or as an addendum to the NOTICE text from the Work, provided
-          that such additional attribution notices cannot be construed
-          as modifying the License.
-
-      You may add Your own copyright statement to Your modifications and
-      may provide additional or different license terms and conditions
-      for use, reproduction, or distribution of Your modifications, or
-      for any such Derivative Works as a whole, provided Your use,
-      reproduction, and distribution of the Work otherwise complies with
-      the conditions stated in this License.
-
-   5. Submission of Contributions. Unless You explicitly state otherwise,
-      any Contribution intentionally submitted for inclusion in the Work
-      by You to the Licensor shall be under the terms and conditions of
-      this License, without any additional terms or conditions.
-      Notwithstanding the above, nothing herein shall supersede or modify
-      the terms of any separate license agreement you may have executed
-      with Licensor regarding such Contributions.
-
-   6. Trademarks. This License does not grant permission to use the trade
-      names, trademarks, service marks, or product names of the Licensor,
-      except as required for reasonable and customary use in describing the
-      origin of the Work and reproducing the content of the NOTICE file.
-
-   7. Disclaimer of Warranty. Unless required by applicable law or
-      agreed to in writing, Licensor provides the Work (and each
-      Contributor provides its Contributions) on an "AS IS" BASIS,
-      WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
-      implied, including, without limitation, any warranties or conditions
-      of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
-      PARTICULAR PURPOSE. You are solely responsible for determining the
-      appropriateness of using or redistributing the Work and assume any
-      risks associated with Your exercise of permissions under this License.
-
-   8. Limitation of Liability. In no event and under no legal theory,
-      whether in tort (including negligence), contract, or otherwise,
-      unless required by applicable law (such as deliberate and grossly
-      negligent acts) or agreed to in writing, shall any Contributor be
-      liable to You for damages, including any direct, indirect, special,
-      incidental, or consequential damages of any character arising as a
-      result of this License or out of the use or inability to use the
-      Work (including but not limited to damages for loss of goodwill,
-      work stoppage, computer failure or malfunction, or any and all
-      other commercial damages or losses), even if such Contributor
-      has been advised of the possibility of such damages.
-
-   9. Accepting Warranty or Additional Liability. While redistributing
-      the Work or Derivative Works thereof, You may choose to offer,
-      and charge a fee for, acceptance of support, warranty, indemnity,
-      or other liability obligations and/or rights consistent with this
-      License. However, in accepting such obligations, You may act only
-      on Your own behalf and on Your sole responsibility, not on behalf
-      of any other Contributor, and only if You agree to indemnify,
-      defend, and hold each Contributor harmless for any liability
-      incurred by, or claims asserted against, such Contributor by reason
-      of your accepting any such warranty or additional liability.
-
-   END OF TERMS AND CONDITIONS
-
-   APPENDIX: How to apply the Apache License to your work.
-
-      To apply the Apache License to your work, attach the following
-      boilerplate notice, with the fields enclosed by brackets "[]"
-      replaced with your own identifying information. (Don't include
-      the brackets!)  The text should be enclosed in the appropriate
-      comment syntax for the file format. We also recommend that a
-      file or class name and description of purpose be included on the
-      same "printed page" as the copyright notice for easier
-      identification within third-party archives.
-
-   Copyright [yyyy] [name of copyright owner]
-
-   Licensed under the Apache License, Version 2.0 (the "License");
-   you may not use this file except in compliance with the License.
-   You may obtain a copy of the License at
-
-       http://www.apache.org/licenses/LICENSE-2.0
-
-   Unless required by applicable law or agreed to in writing, software
-   distributed under the License is distributed on an "AS IS" BASIS,
-   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-   See the License for the specific language governing permissions and
-   limitations under the License.
-*/

COPYING.BSD

@@ -1,26 +0,0 @@
-/*
- 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.
-*/

COPYING.LESSER

@@ -0,0 +1,165 @@
+		   GNU LESSER GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+
+  This version of the GNU Lesser General Public License incorporates
+the terms and conditions of version 3 of the GNU General Public
+License, supplemented by the additional permissions listed below.
+
+  0. Additional Definitions. 
+
+  As used herein, "this License" refers to version 3 of the GNU Lesser
+General Public License, and the "GNU GPL" refers to version 3 of the GNU
+General Public License.
+
+  "The Library" refers to a covered work governed by this License,
+other than an Application or a Combined Work as defined below.
+
+  An "Application" is any work that makes use of an interface provided
+by the Library, but which is not otherwise based on the Library.
+Defining a subclass of a class defined by the Library is deemed a mode
+of using an interface provided by the Library.
+
+  A "Combined Work" is a work produced by combining or linking an
+Application with the Library.  The particular version of the Library
+with which the Combined Work was made is also called the "Linked
+Version".
+
+  The "Minimal Corresponding Source" for a Combined Work means the
+Corresponding Source for the Combined Work, excluding any source code
+for portions of the Combined Work that, considered in isolation, are
+based on the Application, and not on the Linked Version.
+
+  The "Corresponding Application Code" for a Combined Work means the
+object code and/or source code for the Application, including any data
+and utility programs needed for reproducing the Combined Work from the
+Application, but excluding the System Libraries of the Combined Work.
+
+  1. Exception to Section 3 of the GNU GPL.
+
+  You may convey a covered work under sections 3 and 4 of this License
+without being bound by section 3 of the GNU GPL.
+
+  2. Conveying Modified Versions.
+
+  If you modify a copy of the Library, and, in your modifications, a
+facility refers to a function or data to be supplied by an Application
+that uses the facility (other than as an argument passed when the
+facility is invoked), then you may convey a copy of the modified
+version:
+
+   a) under this License, provided that you make a good faith effort to
+   ensure that, in the event an Application does not supply the
+   function or data, the facility still operates, and performs
+   whatever part of its purpose remains meaningful, or
+
+   b) under the GNU GPL, with none of the additional permissions of
+   this License applicable to that copy.
+
+  3. Object Code Incorporating Material from Library Header Files.
+
+  The object code form of an Application may incorporate material from
+a header file that is part of the Library.  You may convey such object
+code under terms of your choice, provided that, if the incorporated
+material is not limited to numerical parameters, data structure
+layouts and accessors, or small macros, inline functions and templates
+(ten or fewer lines in length), you do both of the following:
+
+   a) Give prominent notice with each copy of the object code that the
+   Library is used in it and that the Library and its use are
+   covered by this License.
+
+   b) Accompany the object code with a copy of the GNU GPL and this license
+   document.
+
+  4. Combined Works.
+
+  You may convey a Combined Work under terms of your choice that,
+taken together, effectively do not restrict modification of the
+portions of the Library contained in the Combined Work and reverse
+engineering for debugging such modifications, if you also do each of
+the following:
+
+   a) Give prominent notice with each copy of the Combined Work that
+   the Library is used in it and that the Library and its use are
+   covered by this License.
+
+   b) Accompany the Combined Work with a copy of the GNU GPL and this license
+   document.
+
+   c) For a Combined Work that displays copyright notices during
+   execution, include the copyright notice for the Library among
+   these notices, as well as a reference directing the user to the
+   copies of the GNU GPL and this license document.
+
+   d) Do one of the following:
+
+       0) Convey the Minimal Corresponding Source under the terms of this
+       License, and the Corresponding Application Code in a form
+       suitable for, and under terms that permit, the user to
+       recombine or relink the Application with a modified version of
+       the Linked Version to produce a modified Combined Work, in the
+       manner specified by section 6 of the GNU GPL for conveying
+       Corresponding Source.
+
+       1) Use a suitable shared library mechanism for linking with the
+       Library.  A suitable mechanism is one that (a) uses at run time
+       a copy of the Library already present on the user's computer
+       system, and (b) will operate properly with a modified version
+       of the Library that is interface-compatible with the Linked
+       Version. 
+
+   e) Provide Installation Information, but only if you would otherwise
+   be required to provide such information under section 6 of the
+   GNU GPL, and only to the extent that such information is
+   necessary to install and execute a modified version of the
+   Combined Work produced by recombining or relinking the
+   Application with a modified version of the Linked Version. (If
+   you use option 4d0, the Installation Information must accompany
+   the Minimal Corresponding Source and Corresponding Application
+   Code. If you use option 4d1, you must provide the Installation
+   Information in the manner specified by section 6 of the GNU GPL
+   for conveying Corresponding Source.)
+
+  5. Combined Libraries.
+
+  You may place library facilities that are a work based on the
+Library side by side in a single library together with other library
+facilities that are not Applications and are not covered by this
+License, and convey such a combined library under terms of your
+choice, if you do both of the following:
+
+   a) Accompany the combined library with a copy of the same work based
+   on the Library, uncombined with any other library facilities,
+   conveyed under the terms of this License.
+
+   b) Give prominent notice with the combined library that part of it
+   is a work based on the Library, and explaining where to find the
+   accompanying uncombined form of the same work.
+
+  6. Revised Versions of the GNU Lesser General Public License.
+
+  The Free Software Foundation may publish revised and/or new versions
+of the GNU Lesser General Public License from time to time. Such new
+versions will be similar in spirit to the present version, but may
+differ in detail to address new problems or concerns.
+
+  Each version is given a distinguishing version number. If the
+Library as you received it specifies that a certain numbered version
+of the GNU Lesser General Public License "or any later version"
+applies to it, you have the option of following the terms and
+conditions either of that published version or of any later version
+published by the Free Software Foundation. If the Library as you
+received it does not specify a version number of the GNU Lesser
+General Public License, you may choose any version of the GNU Lesser
+General Public License ever published by the Free Software Foundation.
+
+  If the Library as you received it specifies that a proxy can decide
+whether future versions of the GNU Lesser General Public License shall
+apply, that proxy's public statement of acceptance of any version is
+permanent authorization for you to choose that version for the
+Library.

COPYING.MINPACK

@@ -1,51 +0,0 @@
-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

@@ -1,373 +0,0 @@
-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 https://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

@@ -1,6 +0,0 @@
-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 other MPL2-compatible licenses,
-whence the other COPYING.* files here.

CTestConfig.cmake

@@ -2,16 +2,12 @@
 ## Then modify the CMakeLists.txt file in the root directory of your
 ## project to incorporate the testing dashboard.
 ## # The following are required to uses Dart and the Cdash dashboard
-##   enable_testing()
-##   include(CTest)
+##   ENABLE_TESTING()
+##   INCLUDE(Dart)
 set(CTEST_PROJECT_NAME "Eigen")
-set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
+set(CTEST_NIGHTLY_START_TIME "05:00:00 UTC")
 
 set(CTEST_DROP_METHOD "http")
-set(CTEST_DROP_SITE "my.cdash.org")
-set(CTEST_DROP_LOCATION "/submit.php?project=Eigen")
+set(CTEST_DROP_SITE "www.cdash.org")
+set(CTEST_DROP_LOCATION "/CDashPublic/submit.php?project=Eigen")
 set(CTEST_DROP_SITE_CDASH TRUE)
-#set(CTEST_PROJECT_SUBPROJECTS
-#Official
-#Unsupported
-#)

CTestCustom.cmake.in

@@ -1,4 +0,0 @@
-
-set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "2000")
-set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS   "2000")
-list(APPEND CTEST_CUSTOM_ERROR_EXCEPTION    @EIGEN_CTEST_ERROR_EXCEPTION@)

Doxyfile

@@ -0,0 +1,281 @@
+# 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/AccelerateSupport

@@ -1,52 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_ACCELERATESUPPORT_MODULE_H
-#define EIGEN_ACCELERATESUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \ingroup Support_modules
- * \defgroup AccelerateSupport_Module AccelerateSupport module
- *
- * This module provides an interface to the Apple Accelerate library.
- * It provides the seven following main factorization classes:
- * - class AccelerateLLT: a Cholesky (LL^T) factorization.
- * - class AccelerateLDLT: the default LDL^T factorization.
- * - class AccelerateLDLTUnpivoted: a Cholesky-like LDL^T factorization with only 1x1 pivots and no pivoting
- * - class AccelerateLDLTSBK: an LDL^T factorization with Supernode Bunch-Kaufman and static pivoting
- * - class AccelerateLDLTTPP: an LDL^T factorization with full threshold partial pivoting
- * - class AccelerateQR: a QR factorization
- * - class AccelerateCholeskyAtA: a QR factorization without storing Q (equivalent to A^TA = R^T R)
- *
- * \code
- * #include <Eigen/AccelerateSupport>
- * \endcode
- *
- * In order to use this module, the Accelerate headers must be accessible from
- * the include paths, and your binary must be linked to the Accelerate framework.
- * The Accelerate library is only available on Apple hardware.
- *
- * Note that many of the algorithms can be influenced by the UpLo template
- * argument. All matrices are assumed to be symmetric. For example, the following
- * creates an LDLT factorization where your matrix is symmetric (implicit) and
- * uses the lower triangle:
- *
- * \code
- * AccelerateLDLT<SparseMatrix<float>, Lower> ldlt;
- * \endcode
- */
-
-// IWYU pragma: begin_exports
-#include "src/AccelerateSupport/AccelerateSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_ACCELERATESUPPORT_MODULE_H

Eigen/Array

@@ -0,0 +1,39 @@
+#ifndef EIGEN_ARRAY_MODULE_H
+#define EIGEN_ARRAY_MODULE_H
+
+#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"
+
+#endif // EIGEN_ARRAY_MODULE_H

Eigen/CMakeLists.txt

@@ -0,0 +1,34 @@
+set(Eigen_HEADERS Core LU Cholesky QR Geometry Sparse Array SVD LeastSquares QtAlignedMalloc StdVector)
+
+if(EIGEN_BUILD_LIB)
+    set(Eigen_SRCS
+      src/Core/CoreInstantiations.cpp
+      src/Cholesky/CholeskyInstantiations.cpp
+      src/QR/QrInstantiations.cpp
+    )
+
+    add_library(Eigen2 SHARED ${Eigen_SRCS})
+
+    install(TARGETS Eigen2
+            RUNTIME DESTINATION bin
+            LIBRARY DESTINATION lib
+            ARCHIVE DESTINATION lib)
+endif(EIGEN_BUILD_LIB)
+
+if(CMAKE_COMPILER_IS_GNUCXX)
+    set(CMAKE_CXX_FLAGS "${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)
+
+install(FILES
+  ${Eigen_HEADERS}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen
+  )
+
+add_subdirectory(src)

Eigen/Cholesky

@@ -1,43 +1,65 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_CHOLESKY_MODULE_H
 #define EIGEN_CHOLESKY_MODULE_H
 
 #include "Core"
-#include "Jacobi"
 
-#include "src/Core/util/DisableStupidWarnings.h"
+#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 {
 
 /** \defgroup Cholesky_Module Cholesky module
- *
- *
- *
- * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
- * Those decompositions are also accessible via the following methods:
- *  - MatrixBase::llt()
- *  - MatrixBase::ldlt()
- *  - SelfAdjointView::llt()
- *  - SelfAdjointView::ldlt()
- *
- * \code
- * #include <Eigen/Cholesky>
- * \endcode
- */
+  *
+  * \nonstableyet
+  *
+  * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
+  * Those decompositions are accessible via the following MatrixBase methods:
+  *  - MatrixBase::llt(),
+  *  - MatrixBase::ldlt()
+  *
+  * \code
+  * #include <Eigen/Cholesky>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
+#include "src/Array/CwiseOperators.h"
+#include "src/Array/Functors.h"
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
-#ifdef EIGEN_USE_LAPACKE
-#include "src/misc/lapacke_helpers.h"
-#include "src/Cholesky/LLT_LAPACKE.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
 #endif
-// IWYU pragma: end_exports
 
-#include "src/Core/util/ReenableStupidWarnings.h"
+#include "src/Core/util/EnableMSVCWarnings.h"
 
-#endif  // EIGEN_CHOLESKY_MODULE_H
+#endif // EIGEN_CHOLESKY_MODULE_H

Eigen/CholmodSupport

@@ -1,48 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_MODULE_H
-#define EIGEN_CHOLMODSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#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.suitesparse.com">suitesparse</a> package. It provides the two following main factorization classes:
- * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
- * - class CholmodDecomposition: 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.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/CholmodSupport/CholmodSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_CHOLMODSUPPORT_MODULE_H

Eigen/Core

@@ -1,446 +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>
-// 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
 
-#ifndef EIGEN_CORE_MODULE_H
-#define EIGEN_CORE_MODULE_H
+// first thing Eigen does: prevent MSVC from committing suicide
+#include "src/Core/util/DisableMSVCWarnings.h"
 
-// Eigen version information.
-#include "Version"
-
-// first thing Eigen does: stop the compiler from reporting useless warnings.
-#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 compiler/OS/arch detections and define most defaults.
-#include "src/Core/util/Macros.h"
-
-// This detects SSE/AVX/NEON/etc. and configure alignment settings
-#include "src/Core/util/ConfigureVectorization.h"
-
-// We need cuda_runtime.h/hip_runtime.h to ensure that
-// the EIGEN_USING_STD macro works properly on the device side
-#if defined(EIGEN_CUDACC)
-#include <cuda_runtime.h>
-#elif defined(EIGEN_HIPCC)
-#include <hip/hip_runtime.h>
+#ifdef _MSC_VER
+  #include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
+  #if (_MSC_VER >= 1500) // 2008 or later
+    // Remember that usage of defined() in a #define is undefined by the standard.
+    // 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
 
-#ifdef EIGEN_EXCEPTIONS
-#include <new>
+#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
 
-// Disable the ipa-cp-clone optimization flag with MinGW 6.x or older (enabled by default with -O3)
-// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
-#if EIGEN_COMP_MINGW && EIGEN_GNUC_STRICT_LESS_THAN(6, 0, 0)
-#pragma GCC optimize("-fno-ipa-cp-clone")
+// 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
 
-// Prevent ICC from specializing std::complex operators that silently fail
-// on device. This allows us to use our own device-compatible specializations
-// instead.
-#if EIGEN_COMP_ICC && defined(EIGEN_GPU_COMPILE_PHASE) && !defined(_OVERRIDE_COMPLEX_SPECIALIZATION_)
-#define _OVERRIDE_COMPLEX_SPECIALIZATION_ 1
-#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 defined(EIGEN_HAS_CUDA_FP16) || defined(EIGEN_HAS_HIP_FP16)
-#define EIGEN_HAS_GPU_FP16
+#ifndef EIGEN_DONT_VECTORIZE
+  #if defined (EIGEN_SSE2_BUT_NOT_OLD_GCC) || defined(EIGEN_SSE2_ON_MSVC_2008_OR_LATER)
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_SSE
+    #include <emmintrin.h>
+    #include <xmmintrin.h>
+    #ifdef __SSE3__
+      #include <pmmintrin.h>
+    #endif
+    #ifdef __SSSE3__
+      #include <tmmintrin.h>
+    #endif
+  #elif defined __ALTIVEC__
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_ALTIVEC
+    #include <altivec.h>
+    // We need to #undef all these ugly tokens defined in <altivec.h>
+    // => use __vector instead of vector
+    #undef bool
+    #undef vector
+    #undef pixel
+  #endif
 #endif
 
-#if defined(EIGEN_HAS_CUDA_BF16) || defined(EIGEN_HAS_HIP_BF16)
-#define EIGEN_HAS_GPU_BF16
-#endif
-
-#if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
-#define EIGEN_HAS_OPENMP
-#endif
-
-#ifdef EIGEN_HAS_OPENMP
-#include <atomic>
-#include <omp.h>
-#endif
-
-// MSVC for windows mobile does not have the errno.h file
-#if !(EIGEN_COMP_MSVC && EIGEN_OS_WINCE) && !EIGEN_COMP_ARM
-#define EIGEN_HAS_ERRNO
-#endif
-
-#ifdef EIGEN_HAS_ERRNO
-#include <cerrno>
-#endif
-#include <cstddef>
 #include <cstdlib>
 #include <cmath>
+#include <complex>
+#include <cassert>
 #include <functional>
-#ifndef EIGEN_NO_IO
-#include <sstream>
-#include <iosfwd>
-#endif
+#include <iostream>
 #include <cstring>
 #include <string>
 #include <limits>
-#include <climits>  // for CHAR_BIT
-// for min/max:
-#include <algorithm>
 
-#include <array>
-#include <memory>
-#include <vector>
-
-// for std::is_nothrow_move_assignable
-#include <type_traits>
-
-// for std::this_thread::yield().
-#if !defined(EIGEN_USE_BLAS) && (defined(EIGEN_HAS_OPENMP) || defined(EIGEN_GEMM_THREADPOOL))
-#include <thread>
+#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(EIGEN_NO_EXCEPTIONS)
+  #define EIGEN_EXCEPTIONS
 #endif
 
-// for std::bit_cast()
-#if defined(__cpp_lib_bit_cast) && __cpp_lib_bit_cast >= 201806L
-#include <bit>
+#ifdef EIGEN_EXCEPTIONS
+  #include <new>
 #endif
 
-// for outputting debug info
-#ifdef EIGEN_DEBUG_ASSIGN
-#include <iostream>
-#endif
-
-// required for __cpuid, needs to be included after cmath
-// also required for _BitScanReverse on Windows on ARM
-#if EIGEN_COMP_MSVC && (EIGEN_ARCH_i386_OR_x86_64 || EIGEN_ARCH_ARM64) && !EIGEN_OS_WINCE
-#include <intrin.h>
-#endif
-
-#if defined(EIGEN_USE_SYCL)
-#undef min
-#undef max
-#undef isnan
-#undef isinf
-#undef isfinite
-#include <CL/sycl.hpp>
-#include <map>
-#include <thread>
-#include <utility>
-#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM0
-#define EIGEN_SYCL_LOCAL_THREAD_DIM0 16
-#endif
-#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM1
-#define EIGEN_SYCL_LOCAL_THREAD_DIM1 16
-#endif
-#endif
-
-#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS || defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API || \
-    defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS || defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API ||  \
-    defined EIGEN2_SUPPORT
-// This will generate an error message:
-#error Eigen2-support is only available up to version 3.2. Please go to "http://eigen.tuxfamily.org/index.php?title=Eigen2" for further information
+// 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.
 #endif
 
 namespace Eigen {
 
-// we use size_t frequently and we'll never remember to prepend it with std:: every time just to
-// ensure QNX/QCC support
-using std::size_t;
-// gcc 4.6.0 wants std:: for ptrdiff_t
-using std::ptrdiff_t;
-
-}  // namespace Eigen
-
 /** \defgroup Core_Module Core module
- * This is the main module of Eigen providing dense matrix and vector support
- * (both fixed and dynamic size) with all the features corresponding to a BLAS library
- * and much more...
- *
- * \code
- * #include <Eigen/Core>
- * \endcode
- */
+  * This is the main module of Eigen providing dense matrix and vector support
+  * (both fixed and dynamic size) with all the features corresponding to a BLAS library
+  * and much more...
+  *
+  * \code
+  * #include <Eigen/Core>
+  * \endcode
+  */
 
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#endif
-
-// IWYU pragma: begin_exports
+#include "src/Core/util/Macros.h"
 #include "src/Core/util/Constants.h"
-#include "src/Core/util/Meta.h"
-#include "src/Core/util/Assert.h"
 #include "src/Core/util/ForwardDeclarations.h"
-#include "src/Core/util/StaticAssert.h"
+#include "src/Core/util/Meta.h"
 #include "src/Core/util/XprHelper.h"
+#include "src/Core/util/StaticAssert.h"
 #include "src/Core/util/Memory.h"
-#include "src/Core/util/IntegralConstant.h"
-#include "src/Core/util/Serializer.h"
-#include "src/Core/util/SymbolicIndex.h"
-#include "src/Core/util/EmulateArray.h"
-#include "src/Core/util/MoreMeta.h"
 
 #include "src/Core/NumTraits.h"
 #include "src/Core/MathFunctions.h"
-#include "src/Core/RandomImpl.h"
 #include "src/Core/GenericPacketMath.h"
-#include "src/Core/MathFunctionsImpl.h"
-#include "src/Core/arch/Default/ConjHelper.h"
-// Generic half float support
-#include "src/Core/arch/Default/Half.h"
-#include "src/Core/arch/Default/BFloat16.h"
-#include "src/Core/arch/Default/GenericPacketMathFunctionsFwd.h"
 
-#if defined EIGEN_VECTORIZE_AVX512
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/AVX/PacketMath.h"
-#include "src/Core/arch/AVX/Reductions.h"
-#include "src/Core/arch/AVX512/PacketMath.h"
-#include "src/Core/arch/AVX512/Reductions.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/PacketMathFP16.h"
-#endif
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/AVX/TypeCasting.h"
-#include "src/Core/arch/AVX512/TypeCasting.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/TypeCastingFP16.h"
-#endif
-#include "src/Core/arch/SSE/Complex.h"
-#include "src/Core/arch/AVX/Complex.h"
-#include "src/Core/arch/AVX512/Complex.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/AVX/MathFunctions.h"
-#include "src/Core/arch/AVX512/MathFunctions.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/MathFunctionsFP16.h"
-#endif
-#include "src/Core/arch/AVX512/TrsmKernel.h"
-#elif defined EIGEN_VECTORIZE_AVX
-// Use AVX for floats and doubles, SSE for integers
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/SSE/Complex.h"
-#include "src/Core/arch/AVX/PacketMath.h"
-#include "src/Core/arch/AVX/Reductions.h"
-#include "src/Core/arch/AVX/TypeCasting.h"
-#include "src/Core/arch/AVX/Complex.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/AVX/MathFunctions.h"
-#elif defined EIGEN_VECTORIZE_SSE
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/SSE/Complex.h"
+#if defined EIGEN_VECTORIZE_SSE
+  #include "src/Core/arch/SSE/PacketMath.h"
+#elif defined EIGEN_VECTORIZE_ALTIVEC
+  #include "src/Core/arch/AltiVec/PacketMath.h"
 #endif
 
-#if defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
-#include "src/Core/arch/AltiVec/PacketMath.h"
-#include "src/Core/arch/AltiVec/TypeCasting.h"
-#include "src/Core/arch/AltiVec/MathFunctions.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/TypeCasting.h"
-#include "src/Core/arch/NEON/MathFunctions.h"
-#include "src/Core/arch/NEON/Complex.h"
-#elif defined EIGEN_VECTORIZE_LSX
-#include "src/Core/arch/LSX/PacketMath.h"
-#include "src/Core/arch/LSX/TypeCasting.h"
-#include "src/Core/arch/LSX/MathFunctions.h"
-#include "src/Core/arch/LSX/Complex.h"
-#elif defined EIGEN_VECTORIZE_SVE
-#include "src/Core/arch/SVE/PacketMath.h"
-#include "src/Core/arch/SVE/TypeCasting.h"
-#include "src/Core/arch/SVE/MathFunctions.h"
-#elif defined EIGEN_VECTORIZE_ZVECTOR
-#include "src/Core/arch/ZVector/PacketMath.h"
-#include "src/Core/arch/ZVector/MathFunctions.h"
-#include "src/Core/arch/ZVector/Complex.h"
-#elif defined EIGEN_VECTORIZE_MSA
-#include "src/Core/arch/MSA/PacketMath.h"
-#include "src/Core/arch/MSA/MathFunctions.h"
-#include "src/Core/arch/MSA/Complex.h"
-#elif defined EIGEN_VECTORIZE_HVX
-#include "src/Core/arch/HVX/PacketMath.h"
+#ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+#define EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD 16
 #endif
 
-#if defined EIGEN_VECTORIZE_GPU
-#include "src/Core/arch/GPU/PacketMath.h"
-#include "src/Core/arch/GPU/MathFunctions.h"
-#include "src/Core/arch/GPU/TypeCasting.h"
-#endif
-
-#if defined(EIGEN_USE_SYCL)
-#include "src/Core/arch/SYCL/InteropHeaders.h"
-#if !defined(EIGEN_DONT_VECTORIZE_SYCL)
-#include "src/Core/arch/SYCL/PacketMath.h"
-#include "src/Core/arch/SYCL/MathFunctions.h"
-#include "src/Core/arch/SYCL/TypeCasting.h"
-#endif
-#endif
-
-#include "src/Core/arch/Default/Settings.h"
-// This file provides generic implementations valid for scalar as well
-#include "src/Core/arch/Default/GenericPacketMathFunctions.h"
-
-#include "src/Core/functors/TernaryFunctors.h"
-#include "src/Core/functors/BinaryFunctors.h"
-#include "src/Core/functors/UnaryFunctors.h"
-#include "src/Core/functors/NullaryFunctors.h"
-#include "src/Core/functors/StlFunctors.h"
-#include "src/Core/functors/AssignmentFunctors.h"
-
-// Specialized functors for GPU.
-#ifdef EIGEN_GPUCC
-#include "src/Core/arch/GPU/Complex.h"
-#endif
-
-// Specializations of vectorized activation functions for NEON.
-#ifdef EIGEN_VECTORIZE_NEON
-#include "src/Core/arch/NEON/UnaryFunctors.h"
-#endif
-
-#include "src/Core/util/IndexedViewHelper.h"
-#include "src/Core/util/ReshapedHelper.h"
-#include "src/Core/ArithmeticSequence.h"
-#ifndef EIGEN_NO_IO
-#include "src/Core/IO.h"
-#endif
-#include "src/Core/DenseCoeffsBase.h"
-#include "src/Core/DenseBase.h"
+#include "src/Core/Functors.h"
 #include "src/Core/MatrixBase.h"
-#include "src/Core/EigenBase.h"
+#include "src/Core/Coeffs.h"
 
-#include "src/Core/Product.h"
-#include "src/Core/CoreEvaluators.h"
-#include "src/Core/AssignEvaluator.h"
-#include "src/Core/RealView.h"
-#include "src/Core/Assign.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/ArrayBase.h"
-#include "src/Core/util/BlasUtil.h"
-#include "src/Core/DenseStorage.h"
+#include "src/Core/MatrixStorage.h"
 #include "src/Core/NestByValue.h"
-
-// #include "src/Core/ForceAlignedAccess.h"
-
-#include "src/Core/ReturnByValue.h"
-#include "src/Core/NoAlias.h"
-#include "src/Core/PlainObjectBase.h"
+#include "src/Core/Flagged.h"
 #include "src/Core/Matrix.h"
-#include "src/Core/Array.h"
-#include "src/Core/Fill.h"
-#include "src/Core/CwiseTernaryOp.h"
+#include "src/Core/Cwise.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/InnerProduct.h"
 #include "src/Core/Dot.h"
-#include "src/Core/StableNorm.h"
-#include "src/Core/Stride.h"
+#include "src/Core/Product.h"
+#include "src/Core/DiagonalProduct.h"
+#include "src/Core/SolveTriangular.h"
 #include "src/Core/MapBase.h"
 #include "src/Core/Map.h"
-#include "src/Core/Ref.h"
 #include "src/Core/Block.h"
-#include "src/Core/VectorBlock.h"
-#include "src/Core/IndexedView.h"
-#include "src/Core/Reshaped.h"
+#include "src/Core/Minor.h"
 #include "src/Core/Transpose.h"
 #include "src/Core/DiagonalMatrix.h"
-#include "src/Core/Diagonal.h"
-#include "src/Core/DiagonalProduct.h"
-#include "src/Core/SkewSymmetricMatrix3.h"
+#include "src/Core/DiagonalCoeffs.h"
+#include "src/Core/Sum.h"
 #include "src/Core/Redux.h"
 #include "src/Core/Visitor.h"
-#include "src/Core/FindCoeff.h"
 #include "src/Core/Fuzzy.h"
+#include "src/Core/IO.h"
 #include "src/Core/Swap.h"
 #include "src/Core/CommaInitializer.h"
-#include "src/Core/GeneralProduct.h"
-#include "src/Core/Solve.h"
-#include "src/Core/Inverse.h"
-#include "src/Core/SolverBase.h"
-#include "src/Core/PermutationMatrix.h"
-#include "src/Core/Transpositions.h"
-#include "src/Core/TriangularMatrix.h"
-#include "src/Core/SelfAdjointView.h"
-#include "src/Core/products/GeneralBlockPanelKernel.h"
-#include "src/Core/DeviceWrapper.h"
-#ifdef EIGEN_GEMM_THREADPOOL
-#include "ThreadPool"
-#endif
-#include "src/Core/products/Parallelizer.h"
-#include "src/Core/ProductEvaluators.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"
-#include "src/Core/ConditionEstimator.h"
+#include "src/Core/Part.h"
+#include "src/Core/CacheFriendlyProduct.h"
 
-#if defined(EIGEN_VECTORIZE_VSX)
-#include "src/Core/arch/AltiVec/MatrixProduct.h"
-#elif defined EIGEN_VECTORIZE_NEON
-#include "src/Core/arch/NEON/GeneralBlockPanelKernel.h"
-#elif defined EIGEN_VECTORIZE_LSX
-#include "src/Core/arch/LSX/GeneralBlockPanelKernel.h"
-#endif
+} // namespace Eigen
 
-#if defined(EIGEN_VECTORIZE_AVX512)
-#include "src/Core/arch/AVX512/GemmKernel.h"
-#endif
+#include "src/Core/util/EnableMSVCWarnings.h"
 
-#include "src/Core/Select.h"
-#include "src/Core/VectorwiseOp.h"
-#include "src/Core/PartialReduxEvaluator.h"
-#include "src/Core/Random.h"
-#include "src/Core/Replicate.h"
-#include "src/Core/Reverse.h"
-#include "src/Core/ArrayWrapper.h"
-#include "src/Core/StlIterators.h"
-
-#ifdef EIGEN_USE_BLAS
-#include "src/Core/products/GeneralMatrixMatrix_BLAS.h"
-#include "src/Core/products/GeneralMatrixVector_BLAS.h"
-#include "src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h"
-#include "src/Core/products/SelfadjointMatrixMatrix_BLAS.h"
-#include "src/Core/products/SelfadjointMatrixVector_BLAS.h"
-#include "src/Core/products/TriangularMatrixMatrix_BLAS.h"
-#include "src/Core/products/TriangularMatrixVector_BLAS.h"
-#include "src/Core/products/TriangularSolverMatrix_BLAS.h"
-#endif  // EIGEN_USE_BLAS
-
-#ifdef EIGEN_USE_MKL_VML
-#include "src/Core/Assign_MKL.h"
-#endif
-
-#include "src/Core/GlobalFunctions.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_CORE_MODULE_H
+#endif // EIGEN_CORE_H

Eigen/Dense

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

Eigen/Eigen

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

Eigen/Eigenvalues

@@ -1,63 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_EIGENVALUES_MODULE_H
-#define EIGEN_EIGENVALUES_MODULE_H
-
-#include "Core"
-
-#include "Cholesky"
-#include "Jacobi"
-#include "Householder"
-#include "LU"
-#include "Geometry"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \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/misc/RealSvd2x2.h"
-
-// IWYU pragma: begin_exports
-#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
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#include "src/Eigenvalues/RealSchur_LAPACKE.h"
-#include "src/Eigenvalues/ComplexSchur_LAPACKE.h"
-#include "src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h"
-#endif
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_EIGENVALUES_MODULE_H

Eigen/Geometry

@@ -1,59 +1,51 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_GEOMETRY_MODULE_H
 #define EIGEN_GEOMETRY_MODULE_H
 
 #include "Core"
 
-#include "SVD"
-#include "LU"
+#include "src/Core/util/DisableMSVCWarnings.h"
+
+#include "Array"
 #include <limits>
 
-#include "src/Core/util/DisableStupidWarnings.h"
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+
+namespace Eigen {
 
 /** \defgroup Geometry_Module Geometry module
- *
- * This module provides support for:
- *  - fixed-size homogeneous transformations
- *  - translation, scaling, 2D and 3D rotations
- *  - \link Quaternion quaternions \endlink
- *  - cross products (\ref MatrixBase::cross(), \ref MatrixBase::cross3())
- *  - orthogonal vector generation (MatrixBase::unitOrthogonal)
- *  - some linear components: \link ParametrizedLine parametrized-lines \endlink and \link Hyperplane hyperplanes \endlink
- *  - \link AlignedBox axis aligned bounding boxes \endlink
- *  - \link umeyama() least-square transformation fitting \endlink
- * \code
- * #include <Eigen/Geometry>
- * \endcode
- */
+  *
+  * \nonstableyet
+  *
+  * This module provides support for:
+  *  - fixed-size homogeneous transformations
+  *  - translation, scaling, 2D and 3D rotations
+  *  - quaternions
+  *  - \ref MatrixBase::cross() "cross product"
+  *  - \ref MatrixBase::unitOrthogonal() "orthognal vector generation"
+  *  - some linear components: parametrized-lines and hyperplanes
+  *
+  * \code
+  * #include <Eigen/Geometry>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
 #include "src/Geometry/OrthoMethods.h"
-#include "src/Geometry/EulerAngles.h"
-#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/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"
-#include "src/Geometry/Umeyama.h"
 
-// Use the SSE optimized version whenever possible.
-#if (defined EIGEN_VECTORIZE_SSE) || (defined EIGEN_VECTORIZE_NEON)
-#include "src/Geometry/arch/Geometry_SIMD.h"
-#endif
-// IWYU pragma: end_exports
+} // namespace Eigen
 
-#include "src/Core/util/ReenableStupidWarnings.h"
+#include "src/Core/util/EnableMSVCWarnings.h"
 
-#endif  // EIGEN_GEOMETRY_MODULE_H
+#endif // EIGEN_GEOMETRY_MODULE_H

Eigen/Householder

@@ -1,31 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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
- */
-
-// IWYU pragma: begin_exports
-#include "src/Householder/Householder.h"
-#include "src/Householder/HouseholderSequence.h"
-#include "src/Householder/BlockHouseholder.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_HOUSEHOLDER_MODULE_H

Eigen/IterativeLinearSolvers

@@ -1,52 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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,
-  *  - LeastSquaresConjugateGradient for rectangular least-square problems,
-  *  - 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.
-  *  - IncompleteLUT - incomplete LU factorization with dual thresholding
-  *
-  * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport,
-  UmfPackSupport, SuperLUSupport, AccelerateSupport.
-  *
-    \code
-    #include <Eigen/IterativeLinearSolvers>
-    \endcode
-  */
-
-// IWYU pragma: begin_exports
-#include "src/IterativeLinearSolvers/SolveWithGuess.h"
-#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
-#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
-#include "src/IterativeLinearSolvers/ConjugateGradient.h"
-#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h"
-#include "src/IterativeLinearSolvers/BiCGSTAB.h"
-#include "src/IterativeLinearSolvers/IncompleteLUT.h"
-#include "src/IterativeLinearSolvers/IncompleteCholesky.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H

Eigen/Jacobi

@@ -1,33 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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().
- */
-
-// IWYU pragma: begin_exports
-#include "src/Jacobi/Jacobi.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_JACOBI_MODULE_H

Eigen/KLUSupport

@@ -1,43 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_KLUSUPPORT_MODULE_H
-#define EIGEN_KLUSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-#include <btf.h>
-#include <klu.h>
-}
-
-/** \ingroup Support_modules
- * \defgroup KLUSupport_Module KLUSupport module
- *
- * This module provides an interface to the KLU library which is part of the <a
- * href="http://www.suitesparse.com">suitesparse</a> package. It provides the following factorization class:
- * - class KLU: a sparse LU factorization, well-suited for circuit simulation.
- *
- * \code
- * #include <Eigen/KLUSupport>
- * \endcode
- *
- * In order to use this module, the klu and btf headers must be accessible from the include paths, and your binary must
- * be linked to the klu library and its dependencies. The dependencies depend on how umfpack has been compiled. For a
- * cmake based project, you can use our FindKLU.cmake module to help you in this task.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/KLUSupport/KLUSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_KLUSUPPORT_MODULE_H

Eigen/LU

@@ -1,46 +1,29 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_LU_MODULE_H
 #define EIGEN_LU_MODULE_H
 
 #include "Core"
 
-#include "src/Core/util/DisableStupidWarnings.h"
+#include "src/Core/util/DisableMSVCWarnings.h"
+
+namespace Eigen {
 
 /** \defgroup LU_Module LU module
- * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
- * This module defines the following MatrixBase methods:
- *  - MatrixBase::inverse()
- *  - MatrixBase::determinant()
- *
- * \code
- * #include <Eigen/LU>
- * \endcode
- */
+  * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
+  * This module defines the following MatrixBase methods:
+  *  - MatrixBase::inverse()
+  *  - MatrixBase::determinant()
+  *
+  * \code
+  * #include <Eigen/LU>
+  * \endcode
+  */
 
-#include "src/misc/Kernel.h"
-#include "src/misc/Image.h"
-
-// IWYU pragma: begin_exports
-#include "src/LU/FullPivLU.h"
-#include "src/LU/PartialPivLU.h"
-#ifdef EIGEN_USE_LAPACKE
-#include "src/misc/lapacke_helpers.h"
-#include "src/LU/PartialPivLU_LAPACKE.h"
-#endif
+#include "src/LU/LU.h"
 #include "src/LU/Determinant.h"
-#include "src/LU/InverseImpl.h"
+#include "src/LU/Inverse.h"
 
-#if defined EIGEN_VECTORIZE_SSE || defined EIGEN_VECTORIZE_NEON
-#include "src/LU/arch/InverseSize4.h"
-#endif
-// IWYU pragma: end_exports
+} // namespace Eigen
 
-#include "src/Core/util/ReenableStupidWarnings.h"
+#include "src/Core/util/EnableMSVCWarnings.h"
 
-#endif  // EIGEN_LU_MODULE_H
+#endif // EIGEN_LU_MODULE_H

Eigen/LeastSquares

@@ -0,0 +1,27 @@
+#ifndef EIGEN_REGRESSION_MODULE_H
+#define EIGEN_REGRESSION_MODULE_H
+
+#include "Core"
+
+#include "src/Core/util/DisableMSVCWarnings.h"
+
+#include "QR"
+#include "Geometry"
+
+namespace Eigen {
+
+/** \defgroup LeastSquares_Module LeastSquares module
+  * This module provides linear regression and related features.
+  *
+  * \code
+  * #include <Eigen/LeastSquares>
+  * \endcode
+  */
+
+#include "src/LeastSquares/LeastSquares.h"
+
+} // namespace Eigen
+
+#include "src/Core/util/EnableMSVCWarnings.h"
+
+#endif // EIGEN_REGRESSION_MODULE_H

Eigen/MetisSupport

@@ -1,35 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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
- */
-
-// IWYU pragma: begin_exports
-#include "src/MetisSupport/MetisSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_METISSUPPORT_MODULE_H

Eigen/OrderingMethods

@@ -1,73 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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 least 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
- */
-
-// IWYU pragma: begin_exports
-#include "src/OrderingMethods/Amd.h"
-#include "src/OrderingMethods/Ordering.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_ORDERINGMETHODS_MODULE_H

Eigen/PaStiXSupport

@@ -1,51 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_PASTIXSUPPORT_MODULE_H
-#define EIGEN_PASTIXSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.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. This wrapper resuires PaStiX version 5.x compiled without MPI
- * support. 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.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/PaStiXSupport/PaStiXSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_PASTIXSUPPORT_MODULE_H

Eigen/PardisoSupport

@@ -1,38 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_PARDISOSUPPORT_MODULE_H
-#define EIGEN_PARDISOSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include <mkl_pardiso.h>
-
-/** \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.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/PardisoSupport/PardisoSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_PARDISOSUPPORT_MODULE_H

Eigen/QR

@@ -1,48 +1,73 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_QR_MODULE_H
 #define EIGEN_QR_MODULE_H
 
 #include "Core"
 
-#include "Cholesky"
-#include "Jacobi"
-#include "Householder"
+#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 {
 
 /** \defgroup QR_Module QR module
- *
- *
- *
- * This module provides various QR decompositions
- * This module also provides some MatrixBase methods, including:
- *  - MatrixBase::householderQr()
- *  - MatrixBase::colPivHouseholderQr()
- *  - MatrixBase::fullPivHouseholderQr()
- *
- * \code
- * #include <Eigen/QR>
- * \endcode
- */
+  *
+  * \nonstableyet
+  *
+  * This module mainly provides QR decomposition and an eigen value solver.
+  * This module also provides some MatrixBase methods, including:
+  *  - MatrixBase::qr(),
+  *  - MatrixBase::eigenvalues(),
+  *  - MatrixBase::operatorNorm()
+  *
+  * \code
+  * #include <Eigen/QR>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
-#include "src/QR/HouseholderQR.h"
-#include "src/QR/FullPivHouseholderQR.h"
-#include "src/QR/ColPivHouseholderQR.h"
-#include "src/QR/CompleteOrthogonalDecomposition.h"
-#ifdef EIGEN_USE_LAPACKE
-#include "src/misc/lapacke_helpers.h"
-#include "src/QR/HouseholderQR_LAPACKE.h"
-#include "src/QR/ColPivHouseholderQR_LAPACKE.h"
-#endif
-// IWYU pragma: end_exports
+#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/Core/util/ReenableStupidWarnings.h"
+// 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>
 
-#endif  // EIGEN_QR_MODULE_H
+// removed because it does not support complex yet
+//  PREFIX template class EigenSolver<MATRIXTYPE>
+
+// 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"
+
+#endif // EIGEN_QR_MODULE_H

Eigen/QtAlignedMalloc

@@ -1,9 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_QTMALLOC_MODULE_H
 #define EIGEN_QTMALLOC_MODULE_H
@@ -12,21 +6,24 @@
 
 #if (!EIGEN_MALLOC_ALREADY_ALIGNED)
 
-#include "src/Core/util/DisableStupidWarnings.h"
+inline void *qMalloc(size_t size)
+{
+  return Eigen::ei_aligned_malloc(size);
+}
 
-void *qMalloc(std::size_t size) { return Eigen::internal::aligned_malloc(size); }
+inline void qFree(void *ptr)
+{
+  Eigen::ei_aligned_free(ptr);
+}
 
-void qFree(void *ptr) { Eigen::internal::aligned_free(ptr); }
-
-void *qRealloc(void *ptr, std::size_t size) {
-  void *newPtr = Eigen::internal::aligned_malloc(size);
-  std::memcpy(newPtr, ptr, size);
-  Eigen::internal::aligned_free(ptr);
+inline void *qRealloc(void *ptr, size_t size)
+{
+  void* newPtr = Eigen::ei_aligned_malloc(size);
+  memcpy(newPtr, ptr, size);
+  Eigen::ei_aligned_free(ptr);
   return newPtr;
 }
 
-#include "src/Core/util/ReenableStupidWarnings.h"
-
 #endif
 
-#endif  // EIGEN_QTMALLOC_MODULE_H
+#endif // EIGEN_QTMALLOC_MODULE_H

Eigen/SPQRSupport

@@ -1,41 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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.suitesparse.com">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 "CholmodSupport"
-
-// IWYU pragma: begin_exports
-#include "src/SPQRSupport/SuiteSparseQRSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif

Eigen/SVD

@@ -1,56 +1,29 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_SVD_MODULE_H
 #define EIGEN_SVD_MODULE_H
 
-#include "QR"
-#include "Householder"
-#include "Jacobi"
+#include "Core"
 
-#include "src/Core/util/DisableStupidWarnings.h"
+#include "src/Core/util/DisableMSVCWarnings.h"
+
+namespace Eigen {
 
 /** \defgroup SVD_Module SVD module
- *
- *
- *
- * This module provides SVD decomposition for matrices (both real and complex).
- * Two decomposition algorithms are provided:
- *  - JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very
- * slow for larger ones.
- *  - BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast
- * for large problems. These decompositions are accessible via the respective classes and following MatrixBase methods:
- *  - MatrixBase::jacobiSvd()
- *  - MatrixBase::bdcSvd()
- *
- * \code
- * #include <Eigen/SVD>
- * \endcode
- */
+  *
+  * \nonstableyet
+  *
+  * This module provides SVD decomposition for (currently) real matrices.
+  * This decomposition is accessible via the following MatrixBase method:
+  *  - MatrixBase::svd()
+  *
+  * \code
+  * #include <Eigen/SVD>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
-#include "src/misc/RealSvd2x2.h"
-#include "src/SVD/UpperBidiagonalization.h"
-#include "src/SVD/SVDBase.h"
-#include "src/SVD/JacobiSVD.h"
-#include "src/SVD/BDCSVD.h"
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#ifndef EIGEN_USE_LAPACKE_STRICT
-#include "src/SVD/JacobiSVD_LAPACKE.h"
-#endif
-#include "src/SVD/BDCSVD_LAPACKE.h"
-#endif
-// IWYU pragma: end_exports
+#include "src/SVD/SVD.h"
 
-#include "src/Core/util/ReenableStupidWarnings.h"
+} // namespace Eigen
 
-#endif  // EIGEN_SVD_MODULE_H
+#include "src/Core/util/EnableMSVCWarnings.h"
+
+#endif // EIGEN_SVD_MODULE_H

Eigen/Sparse

@@ -1,33 +1,130 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_SPARSE_MODULE_H
 #define EIGEN_SPARSE_MODULE_H
 
-/** \defgroup Sparse_Module Sparse meta-module
+#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
   *
-  * Meta-module including all related modules:
-  * - \ref SparseCore_Module
-  * - \ref OrderingMethods_Module
-  * - \ref SparseCholesky_Module
-  * - \ref SparseLU_Module
-  * - \ref SparseQR_Module
-  * - \ref IterativeLinearSolvers_Module
+  * \nonstableyet
   *
-    \code
-    #include <Eigen/Sparse>
-    \endcode
+  * See the \ref TutorialSparse "Sparse tutorial"
+  *
+  * \code
+  * #include <Eigen/QR>
+  * \endcode
   */
 
-#include "SparseCore"
-#include "OrderingMethods"
-#include "SparseCholesky"
-#include "SparseLU"
-#include "SparseQR"
-#include "IterativeLinearSolvers"
+#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"
 
-#endif  // EIGEN_SPARSE_MODULE_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"
+
+#endif // EIGEN_SPARSE_MODULE_H

Eigen/SparseCholesky

@@ -1,40 +0,0 @@
-// 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
- */
-
-// IWYU pragma: begin_exports
-#include "src/SparseCholesky/SimplicialCholesky.h"
-#include "src/SparseCholesky/SimplicialCholesky_impl.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_SPARSECHOLESKY_MODULE_H

Eigen/SparseCore

@@ -1,70 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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>
-#include <numeric>
-
-/**
- * \defgroup SparseCore_Module SparseCore module
- *
- * This module provides a sparse matrix representation, and basic associated matrix manipulations
- * and operations.
- *
- * See the \ref TutorialSparse "Sparse tutorial"
- *
- * \code
- * #include <Eigen/SparseCore>
- * \endcode
- *
- * This module depends on: Core.
- */
-
-// IWYU pragma: begin_exports
-#include "src/SparseCore/SparseUtil.h"
-#include "src/SparseCore/SparseMatrixBase.h"
-#include "src/SparseCore/SparseAssign.h"
-#include "src/SparseCore/CompressedStorage.h"
-#include "src/SparseCore/AmbiVector.h"
-#include "src/SparseCore/SparseCompressedBase.h"
-#include "src/SparseCore/SparseMatrix.h"
-#include "src/SparseCore/SparseMap.h"
-#include "src/SparseCore/SparseVector.h"
-#include "src/SparseCore/SparseRef.h"
-#include "src/SparseCore/SparseCwiseUnaryOp.h"
-#include "src/SparseCore/SparseCwiseBinaryOp.h"
-#include "src/SparseCore/SparseTranspose.h"
-#include "src/SparseCore/SparseBlock.h"
-#include "src/SparseCore/SparseDot.h"
-#include "src/SparseCore/SparseRedux.h"
-#include "src/SparseCore/SparseView.h"
-#include "src/SparseCore/SparseDiagonalProduct.h"
-#include "src/SparseCore/ConservativeSparseSparseProduct.h"
-#include "src/SparseCore/SparseSparseProductWithPruning.h"
-#include "src/SparseCore/SparseProduct.h"
-#include "src/SparseCore/SparseDenseProduct.h"
-#include "src/SparseCore/SparseSelfAdjointView.h"
-#include "src/SparseCore/SparseTriangularView.h"
-#include "src/SparseCore/TriangularSolver.h"
-#include "src/SparseCore/SparsePermutation.h"
-#include "src/SparseCore/SparseFuzzy.h"
-#include "src/SparseCore/SparseSolverBase.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_SPARSECORE_MODULE_H

Eigen/SparseLU

@@ -1,50 +0,0 @@
-// 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.
- */
-
-// Ordering interface
-#include "OrderingMethods"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-// IWYU pragma: begin_exports
-#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"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_SPARSELU_MODULE_H

Eigen/SparseQR

@@ -1,38 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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
- *
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/SparseCore/SparseColEtree.h"
-#include "src/SparseQR/SparseQR.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif

Eigen/StdDeque

@@ -1,30 +0,0 @@
-// 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 EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \
-    (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
-
-#define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)
-
-#else
-
-// IWYU pragma: begin_exports
-#include "src/StlSupport/StdDeque.h"
-// IWYU pragma: end_exports
-
-#endif
-
-#endif  // EIGEN_STDDEQUE_MODULE_H

Eigen/StdList

@@ -1,29 +0,0 @@
-// 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 EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \
-    (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
-
-#define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)
-
-#else
-
-// IWYU pragma: begin_exports
-#include "src/StlSupport/StdList.h"
-// IWYU pragma: end_exports
-
-#endif
-
-#endif  // EIGEN_STDLIST_MODULE_H

Eigen/StdVector

@@ -1,30 +1,133 @@
-// 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
 
-#include "Core"
-#include <vector>
+#if defined(_GLIBCXX_VECTOR) || defined(_VECTOR_)
+#error you must include Eigen/StdVector before std::vector
+#endif                                                    
 
-#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \
-    (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
+#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
 
-#define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)
+#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; }
+  };
 
 #else
 
-// IWYU pragma: begin_exports
-#include "src/StlSupport/StdVector.h"
-// IWYU pragma: end_exports
+  #define _EIGEN_WORKAROUND_MSVC_STD_VECTOR(T) T
 
 #endif
 
-#endif  // EIGEN_STDVECTOR_MODULE_H
+}
+
+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

@@ -1,70 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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 This wrapper requires at least versions 4.0 of SuperLU. The 3.x versions are not supported.
- *
- * \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.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/SuperLUSupport/SuperLUSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_SUPERLUSUPPORT_MODULE_H

Eigen/ThreadPool

@@ -1,80 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@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_THREADPOOL_MODULE_H
-#define EIGEN_THREADPOOL_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup ThreadPool_Module ThreadPool Module
- *
- * This module provides 2 threadpool implementations
- *  - a simple reference implementation
- *  - a faster non blocking implementation
- *
- * \code
- * #include <Eigen/ThreadPool>
- * \endcode
- */
-
-#include <cstddef>
-#include <cstring>
-#include <time.h>
-
-#include <vector>
-#include <atomic>
-#include <condition_variable>
-#include <deque>
-#include <mutex>
-#include <thread>
-#include <functional>
-#include <memory>
-#include <utility>
-
-// There are non-parenthesized calls to "max" in the  <unordered_map> header,
-// which trigger a check in test/main.h causing compilation to fail.
-// We work around the check here by removing the check for max in
-// the case where we have to emulate thread_local.
-#ifdef max
-#undef max
-#endif
-#include <unordered_map>
-
-#include "src/Core/util/Meta.h"
-#include "src/Core/util/MaxSizeVector.h"
-
-#ifndef EIGEN_MUTEX
-#define EIGEN_MUTEX std::mutex
-#endif
-#ifndef EIGEN_MUTEX_LOCK
-#define EIGEN_MUTEX_LOCK std::unique_lock<std::mutex>
-#endif
-#ifndef EIGEN_CONDVAR
-#define EIGEN_CONDVAR std::condition_variable
-#endif
-
-// IWYU pragma: begin_exports
-#include "src/ThreadPool/ThreadLocal.h"
-#include "src/ThreadPool/ThreadYield.h"
-#include "src/ThreadPool/ThreadCancel.h"
-#include "src/ThreadPool/EventCount.h"
-#include "src/ThreadPool/RunQueue.h"
-#include "src/ThreadPool/ThreadPoolInterface.h"
-#include "src/ThreadPool/ThreadEnvironment.h"
-#include "src/ThreadPool/Barrier.h"
-#include "src/ThreadPool/NonBlockingThreadPool.h"
-#include "src/ThreadPool/CoreThreadPoolDevice.h"
-#include "src/ThreadPool/ForkJoin.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_CXX11_THREADPOOL_MODULE_H

Eigen/UmfPackSupport

@@ -1,42 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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_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.suitesparse.com">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.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/UmfPackSupport/UmfPackSupport.h"
-// IWYU pragma: endexports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_UMFPACKSUPPORT_MODULE_H

Eigen/Version

@@ -1,14 +0,0 @@
-#ifndef EIGEN_VERSION_H
-#define EIGEN_VERSION_H
-
-// The "WORLD" version will forever remain "3" for the "Eigen3" library.
-#define EIGEN_WORLD_VERSION 3
-// As of Eigen3 5.0.0, we have moved to Semantic Versioning (semver.org).
-#define EIGEN_MAJOR_VERSION 5
-#define EIGEN_MINOR_VERSION 0
-#define EIGEN_PATCH_VERSION 0
-#define EIGEN_PRERELEASE_VERSION ""
-#define EIGEN_BUILD_VERSION ""
-#define EIGEN_VERSION_STRING "5.0.0"
-
-#endif  // EIGEN_VERSION_H

Eigen/src/AccelerateSupport/AccelerateSupport.h

@@ -1,423 +0,0 @@
-#ifndef EIGEN_ACCELERATESUPPORT_H
-#define EIGEN_ACCELERATESUPPORT_H
-
-#include <Accelerate/Accelerate.h>
-
-#include <Eigen/Sparse>
-
-namespace Eigen {
-
-template <typename MatrixType_, int UpLo_, SparseFactorization_t Solver_, bool EnforceSquare_>
-class AccelerateImpl;
-
-/** \ingroup AccelerateSupport_Module
- * \typedef AccelerateLLT
- * \brief A direct Cholesky (LLT) factorization and solver based on Accelerate
- *
- * \warning Only single and double precision real scalar types are supported by Accelerate
- *
- * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<>
- * \tparam UpLo_ additional information about the matrix structure. Default is Lower.
- *
- * \sa \ref TutorialSparseSolverConcept, class AccelerateLLT
- */
-template <typename MatrixType, int UpLo = Lower>
-using AccelerateLLT = AccelerateImpl<MatrixType, UpLo | Symmetric, SparseFactorizationCholesky, true>;
-
-/** \ingroup AccelerateSupport_Module
- * \typedef AccelerateLDLT
- * \brief The default Cholesky (LDLT) factorization and solver based on Accelerate
- *
- * \warning Only single and double precision real scalar types are supported by Accelerate
- *
- * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<>
- * \tparam UpLo_ additional information about the matrix structure. Default is Lower.
- *
- * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLT
- */
-template <typename MatrixType, int UpLo = Lower>
-using AccelerateLDLT = AccelerateImpl<MatrixType, UpLo | Symmetric, SparseFactorizationLDLT, true>;
-
-/** \ingroup AccelerateSupport_Module
- * \typedef AccelerateLDLTUnpivoted
- * \brief A direct Cholesky-like LDL^T factorization and solver based on Accelerate with only 1x1 pivots and no pivoting
- *
- * \warning Only single and double precision real scalar types are supported by Accelerate
- *
- * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<>
- * \tparam UpLo_ additional information about the matrix structure. Default is Lower.
- *
- * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLTUnpivoted
- */
-template <typename MatrixType, int UpLo = Lower>
-using AccelerateLDLTUnpivoted = AccelerateImpl<MatrixType, UpLo | Symmetric, SparseFactorizationLDLTUnpivoted, true>;
-
-/** \ingroup AccelerateSupport_Module
- * \typedef AccelerateLDLTSBK
- * \brief A direct Cholesky (LDLT) factorization and solver based on Accelerate with Supernode Bunch-Kaufman and static
- * pivoting
- *
- * \warning Only single and double precision real scalar types are supported by Accelerate
- *
- * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<>
- * \tparam UpLo_ additional information about the matrix structure. Default is Lower.
- *
- * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLTSBK
- */
-template <typename MatrixType, int UpLo = Lower>
-using AccelerateLDLTSBK = AccelerateImpl<MatrixType, UpLo | Symmetric, SparseFactorizationLDLTSBK, true>;
-
-/** \ingroup AccelerateSupport_Module
- * \typedef AccelerateLDLTTPP
- * \brief A direct Cholesky (LDLT) factorization and solver based on Accelerate with full threshold partial pivoting
- *
- * \warning Only single and double precision real scalar types are supported by Accelerate
- *
- * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<>
- * \tparam UpLo_ additional information about the matrix structure. Default is Lower.
- *
- * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLTTPP
- */
-template <typename MatrixType, int UpLo = Lower>
-using AccelerateLDLTTPP = AccelerateImpl<MatrixType, UpLo | Symmetric, SparseFactorizationLDLTTPP, true>;
-
-/** \ingroup AccelerateSupport_Module
- * \typedef AccelerateQR
- * \brief A QR factorization and solver based on Accelerate
- *
- * \warning Only single and double precision real scalar types are supported by Accelerate
- *
- * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<>
- *
- * \sa \ref TutorialSparseSolverConcept, class AccelerateQR
- */
-template <typename MatrixType>
-using AccelerateQR = AccelerateImpl<MatrixType, 0, SparseFactorizationQR, false>;
-
-/** \ingroup AccelerateSupport_Module
- * \typedef AccelerateCholeskyAtA
- * \brief A QR factorization and solver based on Accelerate without storing Q (equivalent to A^TA = R^T R)
- *
- * \warning Only single and double precision real scalar types are supported by Accelerate
- *
- * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<>
- *
- * \sa \ref TutorialSparseSolverConcept, class AccelerateCholeskyAtA
- */
-template <typename MatrixType>
-using AccelerateCholeskyAtA = AccelerateImpl<MatrixType, 0, SparseFactorizationCholeskyAtA, false>;
-
-namespace internal {
-template <typename T>
-struct AccelFactorizationDeleter {
-  void operator()(T* sym) {
-    if (sym) {
-      SparseCleanup(*sym);
-      delete sym;
-      sym = nullptr;
-    }
-  }
-};
-
-template <typename DenseVecT, typename DenseMatT, typename SparseMatT, typename NumFactT>
-struct SparseTypesTraitBase {
-  typedef DenseVecT AccelDenseVector;
-  typedef DenseMatT AccelDenseMatrix;
-  typedef SparseMatT AccelSparseMatrix;
-
-  typedef SparseOpaqueSymbolicFactorization SymbolicFactorization;
-  typedef NumFactT NumericFactorization;
-
-  typedef AccelFactorizationDeleter<SymbolicFactorization> SymbolicFactorizationDeleter;
-  typedef AccelFactorizationDeleter<NumericFactorization> NumericFactorizationDeleter;
-};
-
-template <typename Scalar>
-struct SparseTypesTrait {};
-
-template <>
-struct SparseTypesTrait<double> : SparseTypesTraitBase<DenseVector_Double, DenseMatrix_Double, SparseMatrix_Double,
-                                                       SparseOpaqueFactorization_Double> {};
-
-template <>
-struct SparseTypesTrait<float>
-    : SparseTypesTraitBase<DenseVector_Float, DenseMatrix_Float, SparseMatrix_Float, SparseOpaqueFactorization_Float> {
-};
-
-}  // end namespace internal
-
-template <typename MatrixType_, int UpLo_, SparseFactorization_t Solver_, bool EnforceSquare_>
-class AccelerateImpl : public SparseSolverBase<AccelerateImpl<MatrixType_, UpLo_, Solver_, EnforceSquare_> > {
- protected:
-  using Base = SparseSolverBase<AccelerateImpl>;
-  using Base::derived;
-  using Base::m_isInitialized;
-
- public:
-  using Base::_solve_impl;
-
-  typedef MatrixType_ MatrixType;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::StorageIndex StorageIndex;
-  enum { ColsAtCompileTime = Dynamic, MaxColsAtCompileTime = Dynamic };
-  enum { UpLo = UpLo_ };
-
-  using AccelDenseVector = typename internal::SparseTypesTrait<Scalar>::AccelDenseVector;
-  using AccelDenseMatrix = typename internal::SparseTypesTrait<Scalar>::AccelDenseMatrix;
-  using AccelSparseMatrix = typename internal::SparseTypesTrait<Scalar>::AccelSparseMatrix;
-  using SymbolicFactorization = typename internal::SparseTypesTrait<Scalar>::SymbolicFactorization;
-  using NumericFactorization = typename internal::SparseTypesTrait<Scalar>::NumericFactorization;
-  using SymbolicFactorizationDeleter = typename internal::SparseTypesTrait<Scalar>::SymbolicFactorizationDeleter;
-  using NumericFactorizationDeleter = typename internal::SparseTypesTrait<Scalar>::NumericFactorizationDeleter;
-
-  AccelerateImpl() {
-    m_isInitialized = false;
-
-    auto check_flag_set = [](int value, int flag) { return ((value & flag) == flag); };
-
-    if (check_flag_set(UpLo_, Symmetric)) {
-      m_sparseKind = SparseSymmetric;
-      m_triType = (UpLo_ & Lower) ? SparseLowerTriangle : SparseUpperTriangle;
-    } else if (check_flag_set(UpLo_, UnitLower)) {
-      m_sparseKind = SparseUnitTriangular;
-      m_triType = SparseLowerTriangle;
-    } else if (check_flag_set(UpLo_, UnitUpper)) {
-      m_sparseKind = SparseUnitTriangular;
-      m_triType = SparseUpperTriangle;
-    } else if (check_flag_set(UpLo_, StrictlyLower)) {
-      m_sparseKind = SparseTriangular;
-      m_triType = SparseLowerTriangle;
-    } else if (check_flag_set(UpLo_, StrictlyUpper)) {
-      m_sparseKind = SparseTriangular;
-      m_triType = SparseUpperTriangle;
-    } else if (check_flag_set(UpLo_, Lower)) {
-      m_sparseKind = SparseTriangular;
-      m_triType = SparseLowerTriangle;
-    } else if (check_flag_set(UpLo_, Upper)) {
-      m_sparseKind = SparseTriangular;
-      m_triType = SparseUpperTriangle;
-    } else {
-      m_sparseKind = SparseOrdinary;
-      m_triType = (UpLo_ & Lower) ? SparseLowerTriangle : SparseUpperTriangle;
-    }
-
-    m_order = SparseOrderDefault;
-  }
-
-  explicit AccelerateImpl(const MatrixType& matrix) : AccelerateImpl() { compute(matrix); }
-
-  ~AccelerateImpl() {}
-
-  inline Index cols() const { return m_nCols; }
-  inline Index rows() const { return m_nRows; }
-
-  ComputationInfo info() const {
-    eigen_assert(m_isInitialized && "Decomposition is not initialized.");
-    return m_info;
-  }
-
-  void analyzePattern(const MatrixType& matrix);
-
-  void factorize(const MatrixType& matrix);
-
-  void compute(const MatrixType& matrix);
-
-  template <typename Rhs, typename Dest>
-  void _solve_impl(const MatrixBase<Rhs>& b, MatrixBase<Dest>& dest) const;
-
-  /** Sets the ordering algorithm to use. */
-  void setOrder(SparseOrder_t order) { m_order = order; }
-
- private:
-  template <typename T>
-  void buildAccelSparseMatrix(const SparseMatrix<T>& a, AccelSparseMatrix& A, std::vector<long>& columnStarts) {
-    const Index nColumnsStarts = a.cols() + 1;
-
-    columnStarts.resize(nColumnsStarts);
-
-    for (Index i = 0; i < nColumnsStarts; i++) columnStarts[i] = a.outerIndexPtr()[i];
-
-    SparseAttributes_t attributes{};
-    attributes.transpose = false;
-    attributes.triangle = m_triType;
-    attributes.kind = m_sparseKind;
-
-    SparseMatrixStructure structure{};
-    structure.attributes = attributes;
-    structure.rowCount = static_cast<int>(a.rows());
-    structure.columnCount = static_cast<int>(a.cols());
-    structure.blockSize = 1;
-    structure.columnStarts = columnStarts.data();
-    structure.rowIndices = const_cast<int*>(a.innerIndexPtr());
-
-    A.structure = structure;
-    A.data = const_cast<T*>(a.valuePtr());
-  }
-
-  void doAnalysis(AccelSparseMatrix& A) {
-    m_numericFactorization.reset(nullptr);
-
-    SparseSymbolicFactorOptions opts{};
-    opts.control = SparseDefaultControl;
-    opts.orderMethod = m_order;
-    opts.order = nullptr;
-    opts.ignoreRowsAndColumns = nullptr;
-    opts.malloc = malloc;
-    opts.free = free;
-    opts.reportError = nullptr;
-
-    m_symbolicFactorization.reset(new SymbolicFactorization(SparseFactor(Solver_, A.structure, opts)));
-
-    SparseStatus_t status = m_symbolicFactorization->status;
-
-    updateInfoStatus(status);
-
-    if (status != SparseStatusOK) m_symbolicFactorization.reset(nullptr);
-  }
-
-  void doFactorization(AccelSparseMatrix& A) {
-    SparseStatus_t status = SparseStatusReleased;
-
-    if (m_symbolicFactorization) {
-      m_numericFactorization.reset(new NumericFactorization(SparseFactor(*m_symbolicFactorization, A)));
-
-      status = m_numericFactorization->status;
-
-      if (status != SparseStatusOK) m_numericFactorization.reset(nullptr);
-    }
-
-    updateInfoStatus(status);
-  }
-
- protected:
-  void updateInfoStatus(SparseStatus_t status) const {
-    switch (status) {
-      case SparseStatusOK:
-        m_info = Success;
-        break;
-      case SparseFactorizationFailed:
-      case SparseMatrixIsSingular:
-        m_info = NumericalIssue;
-        break;
-      case SparseInternalError:
-      case SparseParameterError:
-      case SparseStatusReleased:
-      default:
-        m_info = InvalidInput;
-        break;
-    }
-  }
-
-  mutable ComputationInfo m_info;
-  Index m_nRows, m_nCols;
-  std::unique_ptr<SymbolicFactorization, SymbolicFactorizationDeleter> m_symbolicFactorization;
-  std::unique_ptr<NumericFactorization, NumericFactorizationDeleter> m_numericFactorization;
-  SparseKind_t m_sparseKind;
-  SparseTriangle_t m_triType;
-  SparseOrder_t m_order;
-};
-
-/** Computes the symbolic and numeric decomposition of matrix \a a */
-template <typename MatrixType_, int UpLo_, SparseFactorization_t Solver_, bool EnforceSquare_>
-void AccelerateImpl<MatrixType_, UpLo_, Solver_, EnforceSquare_>::compute(const MatrixType& a) {
-  if (EnforceSquare_) eigen_assert(a.rows() == a.cols());
-
-  m_nRows = a.rows();
-  m_nCols = a.cols();
-
-  AccelSparseMatrix A{};
-  std::vector<long> columnStarts;
-
-  buildAccelSparseMatrix(a, A, columnStarts);
-
-  doAnalysis(A);
-
-  if (m_symbolicFactorization) doFactorization(A);
-
-  m_isInitialized = true;
-}
-
-/** Performs a symbolic decomposition on the sparsity pattern of matrix \a a.
- *
- * This function is particularly useful when solving for several problems having the same structure.
- *
- * \sa factorize()
- */
-template <typename MatrixType_, int UpLo_, SparseFactorization_t Solver_, bool EnforceSquare_>
-void AccelerateImpl<MatrixType_, UpLo_, Solver_, EnforceSquare_>::analyzePattern(const MatrixType& a) {
-  if (EnforceSquare_) eigen_assert(a.rows() == a.cols());
-
-  m_nRows = a.rows();
-  m_nCols = a.cols();
-
-  AccelSparseMatrix A{};
-  std::vector<long> columnStarts;
-
-  buildAccelSparseMatrix(a, A, columnStarts);
-
-  doAnalysis(A);
-
-  m_isInitialized = true;
-}
-
-/** Performs a numeric decomposition of matrix \a a.
- *
- * The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been
- * performed.
- *
- * \sa analyzePattern()
- */
-template <typename MatrixType_, int UpLo_, SparseFactorization_t Solver_, bool EnforceSquare_>
-void AccelerateImpl<MatrixType_, UpLo_, Solver_, EnforceSquare_>::factorize(const MatrixType& a) {
-  eigen_assert(m_symbolicFactorization && "You must first call analyzePattern()");
-  eigen_assert(m_nRows == a.rows() && m_nCols == a.cols());
-
-  if (EnforceSquare_) eigen_assert(a.rows() == a.cols());
-
-  AccelSparseMatrix A{};
-  std::vector<long> columnStarts;
-
-  buildAccelSparseMatrix(a, A, columnStarts);
-
-  doFactorization(A);
-}
-
-template <typename MatrixType_, int UpLo_, SparseFactorization_t Solver_, bool EnforceSquare_>
-template <typename Rhs, typename Dest>
-void AccelerateImpl<MatrixType_, UpLo_, Solver_, EnforceSquare_>::_solve_impl(const MatrixBase<Rhs>& b,
-                                                                              MatrixBase<Dest>& x) const {
-  if (!m_numericFactorization) {
-    m_info = InvalidInput;
-    return;
-  }
-
-  eigen_assert(m_nRows == b.rows());
-  eigen_assert(((b.cols() == 1) || b.outerStride() == b.rows()));
-
-  SparseStatus_t status = SparseStatusOK;
-
-  Scalar* b_ptr = const_cast<Scalar*>(b.derived().data());
-  Scalar* x_ptr = const_cast<Scalar*>(x.derived().data());
-
-  AccelDenseMatrix xmat{};
-  xmat.attributes = SparseAttributes_t();
-  xmat.columnCount = static_cast<int>(x.cols());
-  xmat.rowCount = static_cast<int>(x.rows());
-  xmat.columnStride = xmat.rowCount;
-  xmat.data = x_ptr;
-
-  AccelDenseMatrix bmat{};
-  bmat.attributes = SparseAttributes_t();
-  bmat.columnCount = static_cast<int>(b.cols());
-  bmat.rowCount = static_cast<int>(b.rows());
-  bmat.columnStride = bmat.rowCount;
-  bmat.data = b_ptr;
-
-  SparseSolve(*m_numericFactorization, bmat, xmat);
-
-  updateInfoStatus(status);
-}
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_ACCELERATESUPPORT_H

Eigen/src/AccelerateSupport/InternalHeaderCheck.h

@@ -1,3 +0,0 @@
-#ifndef EIGEN_ACCELERATESUPPORT_MODULE_H
-#error "Please include Eigen/AccelerateSupport instead of including headers inside the src directory directly."
-#endif

Eigen/src/Array/BooleanRedux.h

@@ -0,0 +1,145 @@
+// 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

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

Eigen/src/Array/CwiseOperators.h

@@ -0,0 +1,453 @@
+// 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

@@ -0,0 +1,305 @@
+// 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

@@ -0,0 +1,80 @@
+// 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

@@ -0,0 +1,342 @@
+// 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

@@ -0,0 +1,156 @@
+// 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

@@ -0,0 +1,159 @@
+// 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

@@ -0,0 +1,9 @@
+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)

Eigen/src/Cholesky/CMakeLists.txt

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

Eigen/src/Cholesky/CholeskyInstantiations.cpp

@@ -0,0 +1,35 @@
+// 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_EXTERN_INSTANTIATIONS
+#define EIGEN_EXTERN_INSTANTIATIONS
+#endif
+#include "../../Core"
+#undef EIGEN_EXTERN_INSTANTIATIONS
+
+#include "../../Cholesky"
+
+namespace Eigen {
+  EIGEN_CHOLESKY_MODULE_INSTANTIATE();
+}

Eigen/src/Cholesky/InternalHeaderCheck.h

@@ -1,3 +0,0 @@
-#ifndef EIGEN_CHOLESKY_MODULE_H
-#error "Please include Eigen/Cholesky instead of including headers inside the src directory directly."
-#endif

Eigen/src/Cholesky/LDLT.h

@@ -1,649 +1,198 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
+// for linear algebra. Eigen itself is part of the KDE project.
 //
-// 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 >
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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/.
+// 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_LDLT_H
 #define EIGEN_LDLT_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+/** \ingroup cholesky_Module
+  *
+  * \class LDLT
+  *
+  * \brief Robust Cholesky decomposition of a matrix and associated features
+  *
+  * \param MatrixType the type of the matrix of which we are computing the LDL^T Cholesky decomposition
+  *
+  * 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.
+  *
+  * Compared to a standard Cholesky decomposition, avoiding the square roots allows for faster and more
+  * stable 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.
+  *
+  * \sa MatrixBase::ldlt(), class LLT
+  */
+template<typename MatrixType> class LDLT
+{
+  public:
 
-namespace Eigen {
-
-namespace internal {
-template <typename MatrixType_, int UpLo_>
-struct traits<LDLT<MatrixType_, UpLo_> > : traits<MatrixType_> {
-  typedef MatrixXpr XprKind;
-  typedef SolverStorage StorageKind;
-  typedef int StorageIndex;
-  enum { Flags = 0 };
-};
-
-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 };
-}  // namespace internal
-
-/** \ingroup Cholesky_Module
- *
- * \class LDLT
- *
- * \brief Robust Cholesky decomposition of a matrix with pivoting
- *
- * \tparam MatrixType_ the type of the matrix of which to compute the LDL^T Cholesky decomposition
- * \tparam UpLo_ the triangular part that will be used for the decomposition: Lower (default) or Upper.
- *             The other triangular part won't be read.
- *
- * 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.
- *
- * The decomposition uses pivoting to ensure stability, so that D will have
- * zeros in the bottom right rank(A) - n submatrix. Avoiding the square root
- * on D also stabilizes the computation.
- *
- * 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.
- *
- * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
- *
- * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt(), class LLT
- */
-template <typename MatrixType_, int UpLo_>
-class LDLT : public SolverBase<LDLT<MatrixType_, UpLo_> > {
- public:
-  typedef MatrixType_ MatrixType;
-  typedef SolverBase<LDLT> Base;
-  friend class SolverBase<LDLT>;
-
-  EIGEN_GENERIC_PUBLIC_INTERFACE(LDLT)
-  enum {
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    UpLo = UpLo_
-  };
-  typedef Matrix<Scalar, RowsAtCompileTime, 1, 0, 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()
-   */
-  explicit 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)
-   */
-  template <typename InputType>
-  explicit LDLT(const EigenBase<InputType>& matrix)
-      : m_matrix(matrix.rows(), matrix.cols()),
-        m_transpositions(matrix.rows()),
-        m_temporary(matrix.rows()),
-        m_sign(internal::ZeroSign),
-        m_isInitialized(false) {
-    compute(matrix.derived());
-  }
-
-  /** \brief Constructs a LDLT factorization from a given matrix
-   *
-   * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c
-   * MatrixType is a Eigen::Ref.
-   *
-   * \sa LDLT(const EigenBase&)
-   */
-  template <typename InputType>
-  explicit LDLT(EigenBase<InputType>& matrix)
-      : m_matrix(matrix.derived()),
-        m_transpositions(matrix.rows()),
-        m_temporary(matrix.rows()),
-        m_sign(internal::ZeroSign),
-        m_isInitialized(false) {
-    compute(matrix.derived());
-  }
-
-  /** 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 Diagonal<const MatrixType> vectorD() const {
-    eigen_assert(m_isInitialized && "LDLT is not initialized.");
-    return m_matrix.diagonal();
-  }
-
-  /** \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;
-  }
-
-  /** \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;
-  }
-
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-  /** \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$ if \f$ A \f$ is singular.
-   *
-   * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt()
-   */
-  template <typename Rhs>
-  inline const Solve<LDLT, Rhs> solve(const MatrixBase<Rhs>& b) const;
-#endif
-
-  template <typename Derived>
-  bool solveInPlace(MatrixBase<Derived>& bAndX) const;
-
-  template <typename InputType>
-  LDLT& compute(const EigenBase<InputType>& matrix);
-
-  /** \returns an estimate of the reciprocal condition number of the matrix of
-   *  which \c *this is the LDLT decomposition.
-   */
-  RealScalar rcond() const {
-    eigen_assert(m_isInitialized && "LDLT is not initialized.");
-    return internal::rcond_estimate_helper(m_l1_norm, *this);
-  }
-
-  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;
-
-  /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix
-   * is self-adjoint.
-   *
-   * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as:
-   * \code x = decomposition.adjoint().solve(b) \endcode
-   */
-  const LDLT& adjoint() const { return *this; }
-
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_matrix.rows(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_matrix.cols(); }
-
-  /** \brief Reports whether previous computation was successful.
-   *
-   * \returns \c Success if computation was successful,
-   *          \c NumericalIssue if the factorization failed because of a zero pivot.
-   */
-  ComputationInfo info() const {
-    eigen_assert(m_isInitialized && "LDLT is not initialized.");
-    return m_info;
-  }
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  template <typename RhsType, typename DstType>
-  void _solve_impl(const RhsType& rhs, DstType& dst) const;
-
-  template <bool Conjugate, typename RhsType, typename DstType>
-  void _solve_impl_transposed(const RhsType& rhs, DstType& dst) const;
-#endif
-
- protected:
-  EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
-
-  /** \internal
-   * 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;
-  RealScalar m_l1_norm;
-  TranspositionType m_transpositions;
-  TmpMatrixType m_temporary;
-  internal::SignMatrix m_sign;
-  bool m_isInitialized;
-  ComputationInfo m_info;
-};
-
-namespace internal {
-
-template <int UpLo>
-struct ldlt_inplace;
-
-template <>
-struct ldlt_inplace<Lower> {
-  template <typename MatrixType, typename TranspositionType, typename Workspace>
-  static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) {
-    using std::abs;
     typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename TranspositionType::StorageIndex IndexType;
-    eigen_assert(mat.rows() == mat.cols());
-    const Index size = mat.rows();
-    bool found_zero_pivot = false;
-    bool ret = true;
+    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
 
-    if (size <= 1) {
-      transpositions.setIdentity();
-      if (size == 0)
-        sign = ZeroSign;
-      else if (numext::real(mat.coeff(0, 0)) > static_cast<RealScalar>(0))
-        sign = PositiveSemiDef;
-      else if (numext::real(mat.coeff(0, 0)) < static_cast<RealScalar>(0))
-        sign = NegativeSemiDef;
-      else
-        sign = ZeroSign;
-      return true;
+    LDLT(const MatrixType& matrix)
+      : m_matrix(matrix.rows(), matrix.cols())
+    {
+      compute(matrix);
     }
 
-    for (Index k = 0; k < size; ++k) {
-      // 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;
+    /** \returns the lower triangular matrix L */
+    inline Part<MatrixType, UnitLowerTriangular> matrixL(void) const { return m_matrix; }
 
-      transpositions.coeffRef(k) = IndexType(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 (Index 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));
-      }
+    /** \returns the coefficients of the diagonal matrix D */
+    inline DiagonalCoeffs<MatrixType> vectorD(void) const { return m_matrix.diagonal(); }
 
-      // 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);
+    /** \returns true if the matrix is positive definite */
+    inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
 
-      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);
-      }
+    template<typename RhsDerived, typename ResDerived>
+    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
 
-      // 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, since LDLT is not rank-revealing
-      // we should only make sure that we do not introduce INF or NaN values.
-      // Remark that LAPACK also uses 0 as the cutoff value.
-      RealScalar realAkk = numext::real(mat.coeffRef(k, k));
-      bool pivot_is_valid = (abs(realAkk) > RealScalar(0));
+    template<typename Derived>
+    bool solveInPlace(MatrixBase<Derived> &bAndX) const;
 
-      if (k == 0 && !pivot_is_valid) {
-        // The entire diagonal is zero, there is nothing more to do
-        // except filling the transpositions, and checking whether the matrix is zero.
-        sign = ZeroSign;
-        for (Index j = 0; j < size; ++j) {
-          transpositions.coeffRef(j) = IndexType(j);
-          ret = ret && (mat.col(j).tail(size - j - 1).array() == Scalar(0)).all();
-        }
-        return ret;
-      }
+    void compute(const MatrixType& matrix);
 
-      if ((rs > 0) && pivot_is_valid)
-        A21 /= realAkk;
-      else if (rs > 0)
-        ret = ret && (A21.array() == Scalar(0)).all();
+  protected:
+    /** \internal
+      * 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;
 
-      if (found_zero_pivot && pivot_is_valid)
-        ret = false;  // factorization failed
-      else if (!pivot_is_valid)
-        found_zero_pivot = true;
+    bool m_isPositiveDefinite;
+};
 
-      if (sign == PositiveSemiDef) {
-        if (realAkk < static_cast<RealScalar>(0)) sign = Indefinite;
-      } else if (sign == NegativeSemiDef) {
-        if (realAkk > static_cast<RealScalar>(0)) sign = Indefinite;
-      } else if (sign == ZeroSign) {
-        if (realAkk > static_cast<RealScalar>(0))
-          sign = PositiveSemiDef;
-        else if (realAkk < static_cast<RealScalar>(0))
-          sign = NegativeSemiDef;
-      }
+/** 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)
+{
+  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)
+  {
+    m_matrix = a;
+    return;
+  }
+
+  // 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)
+    {
+      m_isPositiveDefinite = false;
+      return;
     }
 
-    return ret;
-  }
+    int endSize = size-j-1;
+    if (endSize>0)
+    {
+      _temporary.end(endSize) = ( m_matrix.block(j+1,0, endSize, j)
+                                  * m_matrix.col(j).start(j).conjugate() ).lazy();
 
-  // 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;
+      m_matrix.row(j).end(endSize) = a.row(j).end(endSize).conjugate()
+                                   - _temporary.end(endSize).transpose();
 
-    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 (!numext::is_exactly_zero(gamma)) mat.col(j).tail(rs) += (sigma * numext::conj(wj) / gamma) * w.tail(rs);
+      m_matrix.col(j).end(endSize) = m_matrix.row(j).end(endSize) / tmp;
     }
-    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> {
-  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 MatrixL(m); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(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 MatrixL(m.adjoint()); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
-};
-
-}  // end namespace internal
-
-/** Compute / recompute the LDLT decomposition A = L D L^* = U^* D U of \a matrix
- */
-template <typename MatrixType, int UpLo_>
-template <typename InputType>
-LDLT<MatrixType, UpLo_>& LDLT<MatrixType, UpLo_>::compute(const EigenBase<InputType>& a) {
-  eigen_assert(a.rows() == a.cols());
-  const Index size = a.rows();
-
-  m_matrix = a.derived();
-
-  // Compute matrix L1 norm = max abs column sum.
-  m_l1_norm = RealScalar(0);
-  // TODO move this code to SelfAdjointView
-  for (Index col = 0; col < size; ++col) {
-    RealScalar abs_col_sum;
-    if (UpLo_ == Lower)
-      abs_col_sum =
-          m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
-    else
-      abs_col_sum =
-          m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>();
-    if (abs_col_sum > m_l1_norm) m_l1_norm = abs_col_sum;
-  }
-
-  m_transpositions.resize(size);
-  m_isInitialized = false;
-  m_temporary.resize(size);
-  m_sign = internal::ZeroSign;
-
-  m_info = internal::ldlt_inplace<UpLo>::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success
-                                                                                                    : NumericalIssue;
-
-  m_isInitialized = true;
-  return *this;
 }
 
-/** 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 LDLT<MatrixType, UpLo_>::RealScalar& sigma) {
-  typedef typename TranspositionType::StorageIndex IndexType;
-  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) = IndexType(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;
+/** 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
+{
+  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);
 }
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-template <typename MatrixType_, int UpLo_>
-template <typename RhsType, typename DstType>
-void LDLT<MatrixType_, UpLo_>::_solve_impl(const RhsType& rhs, DstType& dst) const {
-  _solve_impl_transposed<true>(rhs, dst);
-}
-
-template <typename MatrixType_, int UpLo_>
-template <bool Conjugate, typename RhsType, typename DstType>
-void LDLT<MatrixType_, UpLo_>::_solve_impl_transposed(const RhsType& rhs, DstType& dst) const {
-  // dst = P b
-  dst = m_transpositions * rhs;
-
-  // dst = L^-1 (P b)
-  // dst = L^-*T (P b)
-  matrixL().template conjugateIf<!Conjugate>().solveInPlace(dst);
-
-  // dst = D^-* (L^-1 P b)
-  // dst = D^-1 (L^-*T P b)
-  // more precisely, use pseudo-inverse of D (see bug 241)
-  using std::abs;
-  const typename Diagonal<const MatrixType>::RealReturnType vecD(vectorD());
-  // In some previous versions, tolerance was set to the max of 1/highest (or rather numeric_limits::min())
-  // and the maximal diagonal entry * epsilon as motivated by LAPACK's xGELSS:
-  // RealScalar tolerance = numext::maxi(vecD.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 leads to numerical issues in some cases. Moreover, Lapack's
-  // xSYTRS routines use 0 for the tolerance. Using numeric_limits::min() gives us more robustness to denormals.
-  RealScalar tolerance = (std::numeric_limits<RealScalar>::min)();
-  for (Index i = 0; i < vecD.size(); ++i) {
-    if (abs(vecD(i)) > tolerance)
-      dst.row(i) /= vecD(i);
-    else
-      dst.row(i).setZero();
-  }
-
-  // dst = L^-* (D^-* L^-1 P b)
-  // dst = L^-T (D^-1 L^-*T P b)
-  matrixL().transpose().template conjugateIf<Conjugate>().solveInPlace(dst);
-
-  // dst = P^T (L^-* D^-* L^-1 P b) = A^-1 b
-  // dst = P^-T (L^-T D^-1 L^-*T P b) = A^-1 b
-  dst = m_transpositions.transpose() * dst;
-}
-#endif
-
-/** \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, int UpLo_>
-template <typename Derived>
-bool LDLT<MatrixType, UpLo_>::solveInPlace(MatrixBase<Derived>& bAndX) const {
-  eigen_assert(m_isInitialized && "LDLT is not initialized.");
-  eigen_assert(m_matrix.rows() == bAndX.rows());
-
-  bAndX = this->solve(bAndX);
-
+/** This is the \em in-place version of solve().
+  *
+  * \param bAndX represents both the right-hand side matrix b and result x.
+  *
+  * 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 Derived>
+bool LDLT<MatrixType>::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);
   return true;
 }
 
-/** \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 {
-  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
- * \sa MatrixBase::ldlt()
- */
-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);
+  * \returns the Cholesky decomposition without square root of \c *this
+  */
+template<typename Derived>
+inline const LDLT<typename MatrixBase<Derived>::PlainMatrixType>
+MatrixBase<Derived>::ldlt() const
+{
+  return derived();
 }
 
-/** \cholesky_module
- * \returns the Cholesky decomposition with full pivoting without square root of \c *this
- * \sa SelfAdjointView::ldlt()
- */
-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
+#endif // EIGEN_LDLT_H

Eigen/src/Cholesky/LLT.h

@@ -1,514 +1,186 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
+// for linear algebra. Eigen itself is part of the KDE project.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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/.
+// 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_LLT_H
 #define EIGEN_LLT_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+/** \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
+  *
+  * 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.
+  *
+  * While the Cholesky decomposition is particularly useful to solve selfadjoint problems like  D^*D x = b,
+  * for that purpose, we recommend the Cholesky decomposition without square root which is more stable
+  * 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.
+  *
+  * \sa MatrixBase::llt(), class LDLT
+  */
+template<typename MatrixType> class LLT
+{
+  private:
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
 
-namespace Eigen {
+    enum {
+      PacketSize = ei_packet_traits<Scalar>::size,
+      AlignmentMask = int(PacketSize)-1
+    };
 
-namespace internal {
+  public:
 
-template <typename MatrixType_, int UpLo_>
-struct traits<LLT<MatrixType_, UpLo_> > : traits<MatrixType_> {
-  typedef MatrixXpr XprKind;
-  typedef SolverStorage StorageKind;
-  typedef int StorageIndex;
-  enum { Flags = 0 };
-};
-
-template <typename MatrixType, int UpLo>
-struct LLT_Traits;
-}  // namespace internal
-
-/** \ingroup Cholesky_Module
- *
- * \class LLT
- *
- * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
- *
- * \tparam MatrixType_ the type of the matrix of which we are computing the LL^T Cholesky decomposition
- * \tparam UpLo_ the triangular part that will be used for the decomposition: 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.
- *
- * While the Cholesky decomposition is particularly useful to solve selfadjoint problems like  D^*D x = b,
- * for that purpose, we recommend the Cholesky decomposition without square root which is more stable
- * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other
- * situations like generalised eigen problems with hermitian matrices.
- *
- * 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
- *
- * \b Performance: for best performance, it is recommended to use a column-major storage format
- * with the Lower triangular part (the default), or, equivalently, a row-major storage format
- * with the Upper triangular part. Otherwise, you might get a 20% slowdown for the full factorization
- * step, and rank-updates can be up to 3 times slower.
- *
- * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
- *
- * Note that during the decomposition, only the lower (or upper, as defined by UpLo_) triangular part of A is
- * considered. Therefore, the strict lower part does not have to store correct values.
- *
- * \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT
- */
-template <typename MatrixType_, int UpLo_>
-class LLT : public SolverBase<LLT<MatrixType_, UpLo_> > {
- public:
-  typedef MatrixType_ MatrixType;
-  typedef SolverBase<LLT> Base;
-  friend class SolverBase<LLT>;
-
-  EIGEN_GENERIC_PUBLIC_INTERFACE(LLT)
-  enum { MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime };
-
-  enum { PacketSize = internal::packet_traits<Scalar>::size, AlignmentMask = int(PacketSize) - 1, UpLo = UpLo_ };
-
-  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()
-   */
-  explicit LLT(Index size) : m_matrix(size, size), m_isInitialized(false) {}
-
-  template <typename InputType>
-  explicit LLT(const EigenBase<InputType>& matrix) : m_matrix(matrix.rows(), matrix.cols()), m_isInitialized(false) {
-    compute(matrix.derived());
-  }
-
-  /** \brief Constructs a LLT factorization from a given matrix
-   *
-   * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when
-   * \c MatrixType is a Eigen::Ref.
-   *
-   * \sa LLT(const EigenBase&)
-   */
-  template <typename InputType>
-  explicit LLT(EigenBase<InputType>& matrix) : m_matrix(matrix.derived()), m_isInitialized(false) {
-    compute(matrix.derived());
-  }
-
-  /** \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 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);
-  }
-
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-  /** \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(), SelfAdjointView::llt()
-   */
-  template <typename Rhs>
-  inline const Solve<LLT, Rhs> solve(const MatrixBase<Rhs>& b) const;
-#endif
-
-  template <typename Derived>
-  void solveInPlace(const MatrixBase<Derived>& bAndX) const;
-
-  template <typename InputType>
-  LLT& compute(const EigenBase<InputType>& matrix);
-
-  /** \returns an estimate of the reciprocal condition number of the matrix of
-   *  which \c *this is the Cholesky decomposition.
-   */
-  RealScalar rcond() const {
-    eigen_assert(m_isInitialized && "LLT is not initialized.");
-    eigen_assert(m_info == Success && "LLT failed because matrix appears to be negative");
-    return internal::rcond_estimate_helper(m_l1_norm, *this);
-  }
-
-  /** \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 successful,
-   *          \c NumericalIssue if the matrix.appears not to be positive definite.
-   */
-  ComputationInfo info() const {
-    eigen_assert(m_isInitialized && "LLT is not initialized.");
-    return m_info;
-  }
-
-  /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix
-   * is self-adjoint.
-   *
-   * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as:
-   * \code x = decomposition.adjoint().solve(b) \endcode
-   */
-  const LLT& adjoint() const noexcept { return *this; }
-
-  constexpr Index rows() const noexcept { return m_matrix.rows(); }
-  constexpr Index cols() const noexcept { return m_matrix.cols(); }
-
-  template <typename VectorType>
-  LLT& rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  template <typename RhsType, typename DstType>
-  void _solve_impl(const RhsType& rhs, DstType& dst) const;
-
-  template <bool Conjugate, typename RhsType, typename DstType>
-  void _solve_impl_transposed(const RhsType& rhs, DstType& dst) const;
-#endif
-
- protected:
-  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;
-  RealScalar m_l1_norm;
-  bool m_isInitialized;
-  ComputationInfo m_info;
-};
-
-namespace internal {
-
-template <typename Scalar, int UpLo>
-struct llt_inplace;
-
-template <typename MatrixType, typename VectorType>
-static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec,
-                                   const typename MatrixType::RealScalar& sigma) {
-  using std::sqrt;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::ColXpr ColXpr;
-  typedef internal::remove_all_t<ColXpr> ColXprCleaned;
-  typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
-  typedef Matrix<Scalar, Dynamic, 1> TempVectorType;
-  typedef typename TempVectorType::SegmentReturnType TempVecSegment;
-
-  Index n = mat.cols();
-  eigen_assert(mat.rows() == n && vec.size() == n);
-
-  TempVectorType temp;
-
-  if (sigma > 0) {
-    // 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) {
-      JacobiRotation<Scalar> g;
-      g.makeGivens(mat(i, i), -temp(i), &mat(i, i));
-
-      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);
-      }
+    LLT(const MatrixType& matrix)
+      : m_matrix(matrix.rows(), matrix.cols())
+    {
+      compute(matrix);
     }
-  } 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;
+    /** \returns the lower triangular matrix L */
+    inline Part<MatrixType, LowerTriangular> matrixL(void) const { return m_matrix; }
 
-      // Update the terms of L
-      Index rs = n - j - 1;
-      if (rs) {
-        temp.tail(rs) -= (wj / Ljj) * mat.col(j).tail(rs);
-        if (!numext::is_exactly_zero(gamma))
-          mat.col(j).tail(rs) =
-              (nLjj / Ljj) * mat.col(j).tail(rs) + (nLjj * sigma * numext::conj(wj) / gamma) * temp.tail(rs);
-      }
-    }
-  }
-  return -1;
-}
+    /** \returns true if the matrix is positive definite */
+    inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
 
-template <typename Scalar>
-struct llt_inplace<Scalar, Lower> {
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  template <typename MatrixType>
-  static Index unblocked(MatrixType& mat) {
-    using std::sqrt;
+    template<typename RhsDerived, typename ResDerived>
+    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
 
-    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
+    template<typename Derived>
+    bool solveInPlace(MatrixBase<Derived> &bAndX) const;
 
-      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);
+    void compute(const MatrixType& matrix);
 
-      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 /= x;
-    }
-    return -1;
-  }
-
-  template <typename MatrixType>
-  static Index blocked(MatrixType& m) {
-    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,
-                                                         typename NumTraits<RealScalar>::Literal(-1));  // bottleneck
-    }
-    return -1;
-  }
-
-  template <typename MatrixType, typename VectorType>
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) {
-    return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
-  }
+  protected:
+    /** \internal
+      * Used to compute and store L
+      * The strict upper part is not used and even not initialized.
+      */
+    MatrixType m_matrix;
+    bool m_isPositiveDefinite;
 };
 
-template <typename Scalar>
-struct llt_inplace<Scalar, Upper> {
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-
-  template <typename MatrixType>
-  static EIGEN_STRONG_INLINE Index unblocked(MatrixType& mat) {
-    Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::unblocked(matt);
-  }
-  template <typename MatrixType>
-  static EIGEN_STRONG_INLINE Index blocked(MatrixType& mat) {
-    Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::blocked(matt);
-  }
-  template <typename MatrixType, typename VectorType>
-  static 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 MatrixL(m); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(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 MatrixL(m.adjoint()); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(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_>
-template <typename InputType>
-LLT<MatrixType, UpLo_>& LLT<MatrixType, UpLo_>::compute(const EigenBase<InputType>& a) {
-  eigen_assert(a.rows() == a.cols());
-  const Index size = a.rows();
+  */
+template<typename MatrixType>
+void LLT<MatrixType>::compute(const MatrixType& a)
+{
+  assert(a.rows()==a.cols());
+  const int size = a.rows();
   m_matrix.resize(size, size);
-  if (!internal::is_same_dense(m_matrix, a.derived())) m_matrix = a.derived();
+  const RealScalar eps = ei_sqrt(precision<Scalar>());
 
-  // Compute matrix L1 norm = max abs column sum.
-  m_l1_norm = RealScalar(0);
-  // TODO move this code to SelfAdjointView
-  for (Index col = 0; col < size; ++col) {
-    RealScalar abs_col_sum;
-    if (UpLo_ == Lower)
-      abs_col_sum =
-          m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
-    else
-      abs_col_sum =
-          m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>();
-    if (abs_col_sum > m_l1_norm) m_l1_norm = abs_col_sum;
+  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)
+  {
+    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))))
+    {
+      m_isPositiveDefinite = false;
+      return;
+    }
+    m_matrix.coeffRef(j,j) = x = ei_sqrt(x);
+
+    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;
+    }
   }
-
-  m_isInitialized = true;
-  bool ok = Traits::inplace_decomposition(m_matrix);
-  m_info = ok ? Success : NumericalIssue;
-
-  return *this;
 }
 
-/** 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;
+/** 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
+{
+  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);
 }
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-template <typename MatrixType_, int UpLo_>
-template <typename RhsType, typename DstType>
-void LLT<MatrixType_, UpLo_>::_solve_impl(const RhsType& rhs, DstType& dst) const {
-  _solve_impl_transposed<true>(rhs, dst);
-}
-
-template <typename MatrixType_, int UpLo_>
-template <bool Conjugate, typename RhsType, typename DstType>
-void LLT<MatrixType_, UpLo_>::_solve_impl_transposed(const RhsType& rhs, DstType& dst) const {
-  dst = rhs;
-
-  matrixL().template conjugateIf<!Conjugate>().solveInPlace(dst);
-  matrixU().template conjugateIf<!Conjugate>().solveInPlace(dst);
-}
-#endif
-
-/** \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.
- *
- * This version avoids a copy when the right hand side matrix b is not needed anymore.
- *
- * \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
- * This function will const_cast it, so constness isn't honored here.
- *
- * \sa LLT::solve(), MatrixBase::llt()
- */
-template <typename MatrixType, int UpLo_>
-template <typename Derived>
-void LLT<MatrixType, UpLo_>::solveInPlace(const MatrixBase<Derived>& bAndX) const {
-  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();
+/** This is the \em in-place version of solve().
+  *
+  * \param bAndX represents both the right-hand side matrix b and result x.
+  *
+  * 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 Derived>
+bool LLT<MatrixType>::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;
 }
 
 /** \cholesky_module
- * \returns the LLT decomposition of \c *this
- * \sa SelfAdjointView::llt()
- */
-template <typename Derived>
-inline const LLT<typename MatrixBase<Derived>::PlainObject> MatrixBase<Derived>::llt() const {
-  return LLT<PlainObject>(derived());
+  * \returns the LLT decomposition of \c *this
+  */
+template<typename Derived>
+inline const LLT<typename MatrixBase<Derived>::PlainMatrixType>
+MatrixBase<Derived>::llt() const
+{
+  return LLT<PlainMatrixType>(derived());
 }
 
-/** \cholesky_module
- * \returns the LLT decomposition of \c *this
- * \sa SelfAdjointView::llt()
- */
-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
+#endif // EIGEN_LLT_H

Eigen/src/Cholesky/LLT_LAPACKE.h

@@ -1,124 +0,0 @@
-/*
- 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 LAPACKe
- *     LLt decomposition based on LAPACKE_?potrf function.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_LLT_LAPACKE_H
-#define EIGEN_LLT_LAPACKE_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-namespace lapacke_helpers {
-// -------------------------------------------------------------------------------------------------------------------
-//        Dispatch for rank update handling upper and lower parts
-// -------------------------------------------------------------------------------------------------------------------
-
-template <UpLoType Mode>
-struct rank_update {};
-
-template <>
-struct rank_update<Lower> {
-  template <typename MatrixType, typename VectorType>
-  static Index run(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) {
-    return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
-  }
-};
-
-template <>
-struct rank_update<Upper> {
-  template <typename MatrixType, typename VectorType>
-  static Index run(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) {
-    Transpose<MatrixType> matt(mat);
-    return Eigen::internal::llt_rank_update_lower(matt, vec.conjugate(), sigma);
-  }
-};
-
-// -------------------------------------------------------------------------------------------------------------------
-//        Generic lapacke llt implementation that hands of to the dispatches
-// -------------------------------------------------------------------------------------------------------------------
-
-template <typename Scalar, UpLoType Mode>
-struct lapacke_llt {
-  EIGEN_STATIC_ASSERT(((Mode == Lower) || (Mode == Upper)), MODE_MUST_BE_UPPER_OR_LOWER)
-  template <typename MatrixType>
-  static Index blocked(MatrixType &m) {
-    eigen_assert(m.rows() == m.cols());
-    if (m.rows() == 0) {
-      return -1;
-    }
-    /* Set up parameters for ?potrf */
-    lapack_int size = to_lapack(m.rows());
-    lapack_int matrix_order = lapack_storage_of(m);
-    constexpr char uplo = Mode == Upper ? 'U' : 'L';
-    Scalar *a = &(m.coeffRef(0, 0));
-    lapack_int lda = to_lapack(m.outerStride());
-
-    lapack_int info = potrf(matrix_order, uplo, size, to_lapack(a), lda);
-    info = (info == 0) ? -1 : info > 0 ? info - 1 : size;
-    return info;
-  }
-
-  template <typename MatrixType, typename VectorType>
-  static Index rankUpdate(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) {
-    return rank_update<Mode>::run(mat, vec, sigma);
-  }
-};
-}  // namespace lapacke_helpers
-// end namespace lapacke_helpers
-
-/*
- * Here, we just put the generic implementation from lapacke_llt into a full specialization of the llt_inplace
- * type. By being a full specialization, the versions defined here thus get precedence over the generic implementation
- * in LLT.h for double, float and complex double, complex float types.
- */
-
-#define EIGEN_LAPACKE_LLT(EIGTYPE)                                                             \
-  template <>                                                                                  \
-  struct llt_inplace<EIGTYPE, Lower> : public lapacke_helpers::lapacke_llt<EIGTYPE, Lower> {}; \
-  template <>                                                                                  \
-  struct llt_inplace<EIGTYPE, Upper> : public lapacke_helpers::lapacke_llt<EIGTYPE, Upper> {};
-
-EIGEN_LAPACKE_LLT(double)
-EIGEN_LAPACKE_LLT(float)
-EIGEN_LAPACKE_LLT(std::complex<double>)
-EIGEN_LAPACKE_LLT(std::complex<float>)
-
-#undef EIGEN_LAPACKE_LLT
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_LLT_LAPACKE_H

Eigen/src/CholmodSupport/CholmodSupport.h

@@ -1,738 +0,0 @@
-// 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Scalar>
-struct cholmod_configure_matrix;
-
-template <>
-struct cholmod_configure_matrix<double> {
-  template <typename CholmodType>
-  static void run(CholmodType& mat) {
-    mat.xtype = CHOLMOD_REAL;
-    mat.dtype = CHOLMOD_DOUBLE;
-  }
-};
-
-template <>
-struct cholmod_configure_matrix<std::complex<double> > {
-  template <typename CholmodType>
-  static void run(CholmodType& mat) {
-    mat.xtype = CHOLMOD_COMPLEX;
-    mat.dtype = CHOLMOD_DOUBLE;
-  }
-};
-
-// Other scalar types are not yet supported by Cholmod
-// template<> struct cholmod_configure_matrix<float> {
-//   template<typename CholmodType>
-//   static void run(CholmodType& mat) {
-//     mat.xtype = CHOLMOD_REAL;
-//     mat.dtype = CHOLMOD_SINGLE;
-//   }
-// };
-//
-// template<> struct cholmod_configure_matrix<std::complex<float> > {
-//   template<typename CholmodType>
-//   static void run(CholmodType& mat) {
-//     mat.xtype = CHOLMOD_COMPLEX;
-//     mat.dtype = CHOLMOD_SINGLE;
-//   }
-// };
-
-}  // 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 StorageIndex_>
-cholmod_sparse viewAsCholmod(Ref<SparseMatrix<Scalar_, Options_, StorageIndex_> > 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<StorageIndex_, int>::value) {
-    res.itype = CHOLMOD_INT;
-  } else if (internal::is_same<StorageIndex_, SuiteSparse_long>::value) {
-    res.itype = CHOLMOD_LONG;
-  } else {
-    eigen_assert(false && "Index type not supported yet");
-  }
-
-  // setup res.xtype
-  internal::cholmod_configure_matrix<Scalar_>::run(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(Ref<SparseMatrix<Scalar_, Options_, Index_> >(mat.const_cast_derived()));
-  return res;
-}
-
-template <typename Scalar_, int Options_, typename Index_>
-const cholmod_sparse viewAsCholmod(const SparseVector<Scalar_, Options_, Index_>& mat) {
-  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<Scalar_, Options_, Index_> >(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<const SparseMatrix<Scalar_, Options_, Index_>, UpLo>& mat) {
-  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<Scalar_, Options_, Index_> >(mat.matrix().const_cast_derived()));
-
-  if (UpLo == Upper) res.stype = 1;
-  if (UpLo == Lower) res.stype = -1;
-  // swap stype for rowmajor matrices (only works for real matrices)
-  EIGEN_STATIC_ASSERT((Options_ & RowMajorBit) == 0 || NumTraits<Scalar_>::IsComplex == 0,
-                      THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
-  if (Options_ & RowMajorBit) 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>::run(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, typename StorageIndex>
-Map<const SparseMatrix<Scalar, ColMajor, StorageIndex> > viewAsEigen(cholmod_sparse& cm) {
-  return Map<const SparseMatrix<Scalar, ColMajor, StorageIndex> >(
-      cm.nrow, cm.ncol, static_cast<StorageIndex*>(cm.p)[cm.ncol], static_cast<StorageIndex*>(cm.p),
-      static_cast<StorageIndex*>(cm.i), static_cast<Scalar*>(cm.x));
-}
-
-/** Returns a view of the Cholmod sparse matrix factor \a cm as an Eigen sparse matrix.
- * The data are not copied but shared. */
-template <typename Scalar, typename StorageIndex>
-Map<const SparseMatrix<Scalar, ColMajor, StorageIndex> > viewAsEigen(cholmod_factor& cm) {
-  return Map<const SparseMatrix<Scalar, ColMajor, StorageIndex> >(
-      cm.n, cm.n, static_cast<StorageIndex*>(cm.p)[cm.n], static_cast<StorageIndex*>(cm.p),
-      static_cast<StorageIndex*>(cm.i), static_cast<Scalar*>(cm.x));
-}
-
-namespace internal {
-
-// template specializations for int and long that call the correct cholmod method
-
-#define EIGEN_CHOLMOD_SPECIALIZE0(ret, name)                        \
-  template <typename StorageIndex_>                                 \
-  inline ret cm_##name(cholmod_common& Common) {                    \
-    return cholmod_##name(&Common);                                 \
-  }                                                                 \
-  template <>                                                       \
-  inline ret cm_##name<SuiteSparse_long>(cholmod_common & Common) { \
-    return cholmod_l_##name(&Common);                               \
-  }
-
-#define EIGEN_CHOLMOD_SPECIALIZE1(ret, name, t1, a1)                         \
-  template <typename StorageIndex_>                                          \
-  inline ret cm_##name(t1& a1, cholmod_common& Common) {                     \
-    return cholmod_##name(&a1, &Common);                                     \
-  }                                                                          \
-  template <>                                                                \
-  inline ret cm_##name<SuiteSparse_long>(t1 & a1, cholmod_common & Common) { \
-    return cholmod_l_##name(&a1, &Common);                                   \
-  }
-
-EIGEN_CHOLMOD_SPECIALIZE0(int, start)
-EIGEN_CHOLMOD_SPECIALIZE0(int, finish)
-
-EIGEN_CHOLMOD_SPECIALIZE1(int, free_factor, cholmod_factor*, L)
-EIGEN_CHOLMOD_SPECIALIZE1(int, free_dense, cholmod_dense*, X)
-EIGEN_CHOLMOD_SPECIALIZE1(int, free_sparse, cholmod_sparse*, A)
-
-EIGEN_CHOLMOD_SPECIALIZE1(cholmod_factor*, analyze, cholmod_sparse, A)
-EIGEN_CHOLMOD_SPECIALIZE1(cholmod_sparse*, factor_to_sparse, cholmod_factor, L)
-
-template <typename StorageIndex_>
-inline cholmod_dense* cm_solve(int sys, cholmod_factor& L, cholmod_dense& B, cholmod_common& Common) {
-  return cholmod_solve(sys, &L, &B, &Common);
-}
-template <>
-inline cholmod_dense* cm_solve<SuiteSparse_long>(int sys, cholmod_factor& L, cholmod_dense& B, cholmod_common& Common) {
-  return cholmod_l_solve(sys, &L, &B, &Common);
-}
-
-template <typename StorageIndex_>
-inline cholmod_sparse* cm_spsolve(int sys, cholmod_factor& L, cholmod_sparse& B, cholmod_common& Common) {
-  return cholmod_spsolve(sys, &L, &B, &Common);
-}
-template <>
-inline cholmod_sparse* cm_spsolve<SuiteSparse_long>(int sys, cholmod_factor& L, cholmod_sparse& B,
-                                                    cholmod_common& Common) {
-  return cholmod_l_spsolve(sys, &L, &B, &Common);
-}
-
-template <typename StorageIndex_>
-inline int cm_factorize_p(cholmod_sparse* A, double beta[2], StorageIndex_* fset, std::size_t fsize, cholmod_factor* L,
-                          cholmod_common& Common) {
-  return cholmod_factorize_p(A, beta, fset, fsize, L, &Common);
-}
-template <>
-inline int cm_factorize_p<SuiteSparse_long>(cholmod_sparse* A, double beta[2], SuiteSparse_long* fset,
-                                            std::size_t fsize, cholmod_factor* L, cholmod_common& Common) {
-  return cholmod_l_factorize_p(A, beta, fset, fsize, L, &Common);
-}
-
-#undef EIGEN_CHOLMOD_SPECIALIZE0
-#undef EIGEN_CHOLMOD_SPECIALIZE1
-
-}  // namespace internal
-
-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 : public SparseSolverBase<Derived> {
- protected:
-  typedef SparseSolverBase<Derived> Base;
-  using Base::derived;
-  using Base::m_isInitialized;
-
- public:
-  typedef MatrixType_ MatrixType;
-  enum { UpLo = UpLo_ };
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef MatrixType CholMatrixType;
-  typedef typename MatrixType::StorageIndex StorageIndex;
-  enum { ColsAtCompileTime = MatrixType::ColsAtCompileTime, MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime };
-
- public:
-  CholmodBase() : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false) {
-    EIGEN_STATIC_ASSERT((internal::is_same<double, RealScalar>::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY);
-    m_shiftOffset[0] = m_shiftOffset[1] = 0.0;
-    internal::cm_start<StorageIndex>(m_cholmod);
-  }
-
-  explicit CholmodBase(const MatrixType& matrix)
-      : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false) {
-    EIGEN_STATIC_ASSERT((internal::is_same<double, RealScalar>::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY);
-    m_shiftOffset[0] = m_shiftOffset[1] = 0.0;
-    internal::cm_start<StorageIndex>(m_cholmod);
-    compute(matrix);
-  }
-
-  ~CholmodBase() {
-    if (m_cholmodFactor) internal::cm_free_factor<StorageIndex>(m_cholmodFactor, m_cholmod);
-    internal::cm_finish<StorageIndex>(m_cholmod);
-  }
-
-  inline StorageIndex cols() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
-  inline StorageIndex rows() const { return internal::convert_index<StorageIndex, Index>(m_cholmodFactor->n); }
-
-  /** \brief Reports whether previous computation was successful.
-   *
-   * \returns \c Success if computation was successful,
-   *          \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();
-  }
-
-  /** 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) {
-      internal::cm_free_factor<StorageIndex>(m_cholmodFactor, m_cholmod);
-      m_cholmodFactor = 0;
-    }
-    cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
-    m_cholmodFactor = internal::cm_analyze<StorageIndex>(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>());
-    internal::cm_factorize_p<StorageIndex>(&A, m_shiftOffset, 0, 0, m_cholmodFactor, m_cholmod);
-
-    // If the factorization failed, either the input matrix was zero (so m_cholmodFactor == nullptr), or minor is the
-    // column at which it failed. On success minor == n.
-    this->m_info =
-        (m_cholmodFactor != nullptr && 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_impl(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());
-
-    // Cholmod needs column-major storage without inner-stride, which corresponds to the default behavior of Ref.
-    Ref<const Matrix<typename Rhs::Scalar, Dynamic, Dynamic, ColMajor> > b_ref(b.derived());
-
-    cholmod_dense b_cd = viewAsCholmod(b_ref);
-    cholmod_dense* x_cd = internal::cm_solve<StorageIndex>(CHOLMOD_A, *m_cholmodFactor, b_cd, m_cholmod);
-    if (!x_cd) {
-      this->m_info = NumericalIssue;
-      return;
-    }
-    // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
-    // NOTE Actually, the copy can be avoided by calling cholmod_solve2 instead of cholmod_solve
-    dest = Matrix<Scalar, Dest::RowsAtCompileTime, Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),
-                                                                                 b.rows(), b.cols());
-    internal::cm_free_dense<StorageIndex>(x_cd, m_cholmod);
-  }
-
-  /** \internal */
-  template <typename RhsDerived, typename DestDerived>
-  void _solve_impl(const SparseMatrixBase<RhsDerived>& b, SparseMatrixBase<DestDerived>& 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
-    Ref<SparseMatrix<typename RhsDerived::Scalar, ColMajor, typename RhsDerived::StorageIndex> > b_ref(
-        b.const_cast_derived());
-    cholmod_sparse b_cs = viewAsCholmod(b_ref);
-    cholmod_sparse* x_cs = internal::cm_spsolve<StorageIndex>(CHOLMOD_A, *m_cholmodFactor, b_cs, m_cholmod);
-    if (!x_cs) {
-      this->m_info = NumericalIssue;
-      return;
-    }
-    // TODO optimize this copy by swapping when possible (be careful with alignment, etc.)
-    // NOTE cholmod_spsolve in fact just calls the dense solver for blocks of 4 columns at a time (similar to Eigen's
-    // sparse solver)
-    dest.derived() = viewAsEigen<typename DestDerived::Scalar, typename DestDerived::StorageIndex>(*x_cs);
-    internal::cm_free_sparse<StorageIndex>(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] = double(offset);
-    return derived();
-  }
-
-  /** \returns the determinant of the underlying matrix from the current factorization */
-  Scalar determinant() const {
-    using std::exp;
-    return exp(logDeterminant());
-  }
-
-  /** \returns the log determinant of the underlying matrix from the current factorization */
-  Scalar logDeterminant() const {
-    using numext::real;
-    using std::log;
-    eigen_assert(m_factorizationIsOk &&
-                 "The decomposition is not in a valid state for solving, you must first call either compute() or "
-                 "symbolic()/numeric()");
-
-    RealScalar logDet = 0;
-    Scalar* x = static_cast<Scalar*>(m_cholmodFactor->x);
-    if (m_cholmodFactor->is_super) {
-      // Supernodal factorization stored as a packed list of dense column-major blocks,
-      // as described by the following structure:
-
-      // super[k] == index of the first column of the j-th super node
-      StorageIndex* super = static_cast<StorageIndex*>(m_cholmodFactor->super);
-      // pi[k] == offset to the description of row indices
-      StorageIndex* pi = static_cast<StorageIndex*>(m_cholmodFactor->pi);
-      // px[k] == offset to the respective dense block
-      StorageIndex* px = static_cast<StorageIndex*>(m_cholmodFactor->px);
-
-      Index nb_super_nodes = m_cholmodFactor->nsuper;
-      for (Index k = 0; k < nb_super_nodes; ++k) {
-        StorageIndex ncols = super[k + 1] - super[k];
-        StorageIndex nrows = pi[k + 1] - pi[k];
-
-        Map<const Array<Scalar, 1, Dynamic>, 0, InnerStride<> > sk(x + px[k], ncols, InnerStride<>(nrows + 1));
-        logDet += sk.real().log().sum();
-      }
-    } else {
-      // Simplicial factorization stored as standard CSC matrix.
-      StorageIndex* p = static_cast<StorageIndex*>(m_cholmodFactor->p);
-      Index size = m_cholmodFactor->n;
-      for (Index k = 0; k < size; ++k) logDet += log(real(x[p[k]]));
-    }
-    if (m_cholmodFactor->is_ll) logDet *= 2.0;
-    return logDet;
-  }
-
-  template <typename Stream>
-  void dumpMemory(Stream& /*s*/) {}
-
- protected:
-  mutable cholmod_common m_cholmod;
-  cholmod_factor* m_cholmodFactor;
-  double m_shiftOffset[2];
-  mutable ComputationInfo m_info;
-  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.
- *
- * \implsparsesolverconcept
- *
- * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non
- * compressed.
- *
- * \warning Only double precision real and complex scalar types are supported by Cholmod.
- *
- * \sa \ref TutorialSparseSolverConcept, 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;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::StorageIndex StorageIndex;
-  typedef TriangularView<const MatrixType, Eigen::Lower> MatrixL;
-  typedef TriangularView<const typename MatrixType::AdjointReturnType, Eigen::Upper> MatrixU;
-
-  CholmodSimplicialLLT() : Base() { init(); }
-
-  CholmodSimplicialLLT(const MatrixType& matrix) : Base() {
-    init();
-    this->compute(matrix);
-  }
-
-  ~CholmodSimplicialLLT() {}
-
-  /** \returns an expression of the factor L */
-  inline MatrixL matrixL() const { return viewAsEigen<Scalar, StorageIndex>(*Base::m_cholmodFactor); }
-
-  /** \returns an expression of the factor U (= L^*) */
-  inline MatrixU matrixU() const { return matrixL().adjoint(); }
-
- 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.
- *
- * \implsparsesolverconcept
- *
- * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non
- * compressed.
- *
- * \warning Only double precision real and complex scalar types are supported by Cholmod.
- *
- * \sa \ref TutorialSparseSolverConcept, 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;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::StorageIndex StorageIndex;
-  typedef Matrix<Scalar, Dynamic, 1> VectorType;
-  typedef TriangularView<const MatrixType, Eigen::UnitLower> MatrixL;
-  typedef TriangularView<const typename MatrixType::AdjointReturnType, Eigen::UnitUpper> MatrixU;
-
-  CholmodSimplicialLDLT() : Base() { init(); }
-
-  CholmodSimplicialLDLT(const MatrixType& matrix) : Base() {
-    init();
-    this->compute(matrix);
-  }
-
-  ~CholmodSimplicialLDLT() {}
-
-  /** \returns a vector expression of the diagonal D */
-  inline VectorType vectorD() const {
-    auto cholmodL = viewAsEigen<Scalar, StorageIndex>(*Base::m_cholmodFactor);
-
-    VectorType D{cholmodL.rows()};
-
-    for (Index k = 0; k < cholmodL.outerSize(); ++k) {
-      typename decltype(cholmodL)::InnerIterator it{cholmodL, k};
-      D(k) = it.value();
-    }
-
-    return D;
-  }
-
-  /** \returns an expression of the factor L */
-  inline MatrixL matrixL() const { return viewAsEigen<Scalar, StorageIndex>(*Base::m_cholmodFactor); }
-
-  /** \returns an expression of the factor U (= L^*) */
-  inline MatrixU matrixU() const { return matrixL().adjoint(); }
-
- 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.
- *
- * \implsparsesolverconcept
- *
- * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non
- * compressed.
- *
- * \warning Only double precision real and complex scalar types are supported by Cholmod.
- *
- * \sa \ref TutorialSparseSolverConcept
- */
-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;
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::StorageIndex StorageIndex;
-
-  CholmodSupernodalLLT() : Base() { init(); }
-
-  CholmodSupernodalLLT(const MatrixType& matrix) : Base() {
-    init();
-    this->compute(matrix);
-  }
-
-  ~CholmodSupernodalLLT() {}
-
-  /** \returns an expression of the factor L */
-  inline MatrixType matrixL() const {
-    // Convert Cholmod factor's supernodal storage format to Eigen's CSC storage format
-    cholmod_sparse* cholmodL = internal::cm_factor_to_sparse(*Base::m_cholmodFactor, m_cholmod);
-    MatrixType L = viewAsEigen<Scalar, StorageIndex>(*cholmodL);
-    internal::cm_free_sparse<StorageIndex>(cholmodL, m_cholmod);
-
-    return L;
-  }
-
-  /** \returns an expression of the factor U (= L^*) */
-  inline MatrixType matrixU() const { return matrixL().adjoint(); }
-
- 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.
- *
- * \implsparsesolverconcept
- *
- * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non
- * compressed.
- *
- * \warning Only double precision real and complex scalar types are supported by Cholmod.
- *
- * \sa \ref TutorialSparseSolverConcept
- */
-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();
-    this->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;
-  }
-};
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_CHOLMODSUPPORT_H

Eigen/src/CholmodSupport/InternalHeaderCheck.h

@@ -1,3 +0,0 @@
-#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H
-#error "Please include Eigen/CholmodSupport instead of including headers inside the src directory directly."
-#endif

Eigen/src/Core/ArithmeticSequence.h

@@ -1,239 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2017 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_ARITHMETIC_SEQUENCE_H
-#define EIGEN_ARITHMETIC_SEQUENCE_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-// Helper to cleanup the type of the increment:
-template <typename T>
-struct cleanup_seq_incr {
-  typedef typename cleanup_index_type<T, DynamicIndex>::type type;
-};
-
-}  // namespace internal
-
-//--------------------------------------------------------------------------------
-// seq(first,last,incr) and seqN(first,size,incr)
-//--------------------------------------------------------------------------------
-
-template <typename FirstType = Index, typename SizeType = Index, typename IncrType = internal::FixedInt<1> >
-class ArithmeticSequence;
-
-template <typename FirstType, typename SizeType, typename IncrType>
-ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                   typename internal::cleanup_index_type<SizeType>::type,
-                   typename internal::cleanup_seq_incr<IncrType>::type>
-seqN(FirstType first, SizeType size, IncrType incr);
-
-/** \class ArithmeticSequence
- * \ingroup Core_Module
- *
- * This class represents an arithmetic progression \f$ a_0, a_1, a_2, ..., a_{n-1}\f$ defined by
- * its \em first value \f$ a_0 \f$, its \em size (aka length) \em n, and the \em increment (aka stride)
- * that is equal to \f$ a_{i+1}-a_{i}\f$ for any \em i.
- *
- * It is internally used as the return type of the Eigen::seq and Eigen::seqN functions, and as the input arguments
- * of DenseBase::operator()(const RowIndices&, const ColIndices&), and most of the time this is the
- * only way it is used.
- *
- * \tparam FirstType type of the first element, usually an Index,
- *                   but internally it can be a symbolic expression
- * \tparam SizeType type representing the size of the sequence, usually an Index
- *                  or a compile time integral constant. Internally, it can also be a symbolic expression
- * \tparam IncrType type of the increment, can be a runtime Index, or a compile time integral constant (default is
- * compile-time 1)
- *
- * \sa Eigen::seq, Eigen::seqN, DenseBase::operator()(const RowIndices&, const ColIndices&), class IndexedView
- */
-template <typename FirstType, typename SizeType, typename IncrType>
-class ArithmeticSequence {
- public:
-  constexpr ArithmeticSequence() = default;
-  constexpr ArithmeticSequence(FirstType first, SizeType size) : m_first(first), m_size(size) {}
-  constexpr ArithmeticSequence(FirstType first, SizeType size, IncrType incr)
-      : m_first(first), m_size(size), m_incr(incr) {}
-
-  enum {
-    // SizeAtCompileTime = internal::get_fixed_value<SizeType>::value,
-    IncrAtCompileTime = internal::get_fixed_value<IncrType, DynamicIndex>::value
-  };
-
-  /** \returns the size, i.e., number of elements, of the sequence */
-  constexpr Index size() const { return m_size; }
-
-  /** \returns the first element \f$ a_0 \f$ in the sequence */
-  constexpr Index first() const { return m_first; }
-
-  /** \returns the value \f$ a_i \f$ at index \a i in the sequence. */
-  constexpr Index operator[](Index i) const { return m_first + i * m_incr; }
-
-  constexpr const FirstType& firstObject() const { return m_first; }
-  constexpr const SizeType& sizeObject() const { return m_size; }
-  constexpr const IncrType& incrObject() const { return m_incr; }
-
- protected:
-  FirstType m_first;
-  SizeType m_size;
-  IncrType m_incr;
-
- public:
-  constexpr auto reverse() const -> decltype(Eigen::seqN(m_first + (m_size + fix<-1>()) * m_incr, m_size, -m_incr)) {
-    return seqN(m_first + (m_size + fix<-1>()) * m_incr, m_size, -m_incr);
-  }
-};
-
-/** \returns an ArithmeticSequence starting at \a first, of length \a size, and increment \a incr
- *
- * \sa seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) */
-template <typename FirstType, typename SizeType, typename IncrType>
-ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                   typename internal::cleanup_index_type<SizeType>::type,
-                   typename internal::cleanup_seq_incr<IncrType>::type>
-seqN(FirstType first, SizeType size, IncrType incr) {
-  return ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                            typename internal::cleanup_index_type<SizeType>::type,
-                            typename internal::cleanup_seq_incr<IncrType>::type>(first, size, incr);
-}
-
-/** \returns an ArithmeticSequence starting at \a first, of length \a size, and unit increment
- *
- * \sa seqN(FirstType,SizeType,IncrType), seq(FirstType,LastType) */
-template <typename FirstType, typename SizeType>
-ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                   typename internal::cleanup_index_type<SizeType>::type>
-seqN(FirstType first, SizeType size) {
-  return ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                            typename internal::cleanup_index_type<SizeType>::type>(first, size);
-}
-
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-
-/** \returns an ArithmeticSequence starting at \a f, up (or down) to \a l, and with positive (or negative) increment \a
- * incr
- *
- * It is essentially an alias to:
- * \code
- * seqN(f, (l-f+incr)/incr, incr);
- * \endcode
- *
- * \sa seqN(FirstType,SizeType,IncrType), seq(FirstType,LastType)
- */
-template <typename FirstType, typename LastType, typename IncrType>
-auto seq(FirstType f, LastType l, IncrType incr);
-
-/** \returns an ArithmeticSequence starting at \a f, up (or down) to \a l, and unit increment
- *
- * It is essentially an alias to:
- * \code
- * seqN(f,l-f+1);
- * \endcode
- *
- * \sa seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType)
- */
-template <typename FirstType, typename LastType>
-auto seq(FirstType f, LastType l);
-
-#else  // EIGEN_PARSED_BY_DOXYGEN
-
-template <typename FirstType, typename LastType>
-auto seq(FirstType f, LastType l)
-    -> decltype(seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-                     (typename internal::cleanup_index_type<LastType>::type(l) -
-                      typename internal::cleanup_index_type<FirstType>::type(f) + fix<1>()))) {
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-              (typename internal::cleanup_index_type<LastType>::type(l) -
-               typename internal::cleanup_index_type<FirstType>::type(f) + fix<1>()));
-}
-
-template <typename FirstType, typename LastType, typename IncrType>
-auto seq(FirstType f, LastType l, IncrType incr)
-    -> decltype(seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-                     (typename internal::cleanup_index_type<LastType>::type(l) -
-                      typename internal::cleanup_index_type<FirstType>::type(f) +
-                      typename internal::cleanup_seq_incr<IncrType>::type(incr)) /
-                         typename internal::cleanup_seq_incr<IncrType>::type(incr),
-                     typename internal::cleanup_seq_incr<IncrType>::type(incr))) {
-  typedef typename internal::cleanup_seq_incr<IncrType>::type CleanedIncrType;
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-              (typename internal::cleanup_index_type<LastType>::type(l) -
-               typename internal::cleanup_index_type<FirstType>::type(f) + CleanedIncrType(incr)) /
-                  CleanedIncrType(incr),
-              CleanedIncrType(incr));
-}
-
-#endif  // EIGEN_PARSED_BY_DOXYGEN
-
-namespace placeholders {
-
-/** \cpp11
- * \returns a symbolic ArithmeticSequence representing the last \a size elements with increment \a incr.
- *
- * It is a shortcut for: \code seqN(last-(size-fix<1>)*incr, size, incr) \endcode
- *
- * \sa lastN(SizeType), seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) */
-template <typename SizeType, typename IncrType>
-auto lastN(SizeType size, IncrType incr)
-    -> decltype(seqN(Eigen::placeholders::last - (size - fix<1>()) * incr, size, incr)) {
-  return seqN(Eigen::placeholders::last - (size - fix<1>()) * incr, size, incr);
-}
-
-/** \cpp11
- * \returns a symbolic ArithmeticSequence representing the last \a size elements with a unit increment.
- *
- *  It is a shortcut for: \code seq(last+fix<1>-size, last) \endcode
- *
- * \sa lastN(SizeType,IncrType, seqN(FirstType,SizeType), seq(FirstType,LastType) */
-template <typename SizeType>
-auto lastN(SizeType size) -> decltype(seqN(Eigen::placeholders::last + fix<1>() - size, size)) {
-  return seqN(Eigen::placeholders::last + fix<1>() - size, size);
-}
-
-}  // namespace placeholders
-
-/** \namespace Eigen::indexing
-  * \ingroup Core_Module
-  *
-  * The sole purpose of this namespace is to be able to import all functions
-  * and symbols that are expected to be used within operator() for indexing
-  * and slicing. If you already imported the whole Eigen namespace:
-  * \code using namespace Eigen; \endcode
-  * then you are already all set. Otherwise, if you don't want/cannot import
-  * the whole Eigen namespace, the following line:
-  * \code using namespace Eigen::indexing; \endcode
-  * is equivalent to:
-  * \code
-  using Eigen::fix;
-  using Eigen::seq;
-  using Eigen::seqN;
-  using Eigen::placeholders::all;
-  using Eigen::placeholders::last;
-  using Eigen::placeholders::lastN;  // c++11 only
-  using Eigen::placeholders::lastp1;
-  \endcode
-  */
-namespace indexing {
-using Eigen::fix;
-using Eigen::seq;
-using Eigen::seqN;
-using Eigen::placeholders::all;
-using Eigen::placeholders::last;
-using Eigen::placeholders::lastN;
-using Eigen::placeholders::lastp1;
-}  // namespace indexing
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_ARITHMETIC_SEQUENCE_H

Eigen/src/Core/Array.h

@@ -1,376 +0,0 @@
-// 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-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;
-};
-}  // namespace internal
-
-/** \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.
- *
- * See documentation of class Matrix for detailed information on the template parameters
- * storage layout.
- *
- * This class can be extended with the help of the plugin mechanism described on the page
- * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
- *
- * \sa \blank \ref TutorialArrayClass, \ref TopicClassHierarchy
- */
-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_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived>& other) {
-    return Base::operator=(other);
-  }
-
-  /** Set all the entries to \a value.
-   * \sa DenseBase::setConstant(), DenseBase::fill()
-   */
-  /* This overload is needed because 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=.
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const Scalar& value) {
-    Base::setConstant(value);
-    return *this;
-  }
-
-  /** 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_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const DenseBase<OtherDerived>& other) {
-    return Base::_set(other);
-  }
-
-  /**
-   * \brief Assigns arrays to each other.
-   *
-   * \note This is a special case of the templated operator=. Its purpose is
-   * to prevent a default operator= from hiding the templated operator=.
-   *
-   * \callgraph
-   */
-  EIGEN_DEVICE_FUNC 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)
-   */
-#ifdef EIGEN_INITIALIZE_COEFFS
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array() : Base() { EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
-#else
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array() = default;
-#endif
-  /** \brief Move constructor */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(Array&&) = default;
-  EIGEN_DEVICE_FUNC Array& operator=(Array&& other) noexcept(std::is_nothrow_move_assignable<Scalar>::value) {
-    Base::operator=(std::move(other));
-    return *this;
-  }
-
-  /** \brief Construct a row of column vector with fixed size from an arbitrary number of coefficients.
-   *
-   * \only_for_vectors
-   *
-   * This constructor is for 1D array or vectors with more than 4 coefficients.
-   *
-   * \warning To construct a column (resp. row) vector of fixed length, the number of values passed to this
-   * constructor must match the the fixed number of rows (resp. columns) of \c *this.
-   *
-   *
-   * Example: \include Array_variadic_ctor_cxx11.cpp
-   * Output: \verbinclude Array_variadic_ctor_cxx11.out
-   *
-   * \sa Array(const std::initializer_list<std::initializer_list<Scalar>>&)
-   * \sa Array(const Scalar&), Array(const Scalar&,const Scalar&)
-   */
-  template <typename... ArgTypes>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3,
-                                              const ArgTypes&... args)
-      : Base(a0, a1, a2, a3, args...) {}
-
-  /** \brief Constructs an array and initializes it from the coefficients given as initializer-lists grouped by row.
-   * \cpp11
-   *
-   * In the general case, the constructor takes a list of rows, each row being represented as a list of coefficients:
-   *
-   * Example: \include Array_initializer_list_23_cxx11.cpp
-   * Output: \verbinclude Array_initializer_list_23_cxx11.out
-   *
-   * Each of the inner initializer lists must contain the exact same number of elements, otherwise an assertion is
-   * triggered.
-   *
-   * In the case of a compile-time column 1D array, implicit transposition from a single row is allowed.
-   * Therefore <code> Array<int,Dynamic,1>{{1,2,3,4,5}}</code> is legal and the more verbose syntax
-   * <code>Array<int,Dynamic,1>{{1},{2},{3},{4},{5}}</code> can be avoided:
-   *
-   * Example: \include Array_initializer_list_vector_cxx11.cpp
-   * Output: \verbinclude Array_initializer_list_vector_cxx11.out
-   *
-   * In the case of fixed-sized arrays, the initializer list sizes must exactly match the array sizes,
-   * and implicit transposition is allowed for compile-time 1D arrays only.
-   *
-   * \sa  Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(
-      const std::initializer_list<std::initializer_list<Scalar>>& list)
-      : Base(list) {}
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  template <typename T>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array(const T& x) {
-    Base::template _init1<T>(x);
-  }
-
-  template <typename T0, typename T1>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1) {
-    this->template _init2<T0, T1>(val0, val1);
-  }
-
-#else
-  /** \brief Constructs a fixed-sized array initialized with coefficients starting at \a data */
-  EIGEN_DEVICE_FUNC explicit Array(const Scalar* data);
-  /** 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 Array() instead.
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array(Index dim);
-  /** constructs an initialized 1x1 Array with the given coefficient
-   * \sa const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args */
-  Array(const Scalar& value);
-  /** constructs an uninitialized array with \a rows rows and \a cols columns.
-   *
-   * This is useful for dynamic-size arrays. For fixed-size arrays,
-   * it is redundant to pass these parameters, so one should use the default constructor
-   * Array() instead. */
-  Array(Index rows, Index cols);
-  /** constructs an initialized 2D vector with given coefficients
-   * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args) */
-  Array(const Scalar& val0, const Scalar& val1);
-#endif  // end EIGEN_PARSED_BY_DOXYGEN
-
-  /** constructs an initialized 3D vector with given coefficients
-   * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2) {
-    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
-   * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2,
-                                              const Scalar& val3) {
-    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;
-  }
-
-  /** Copy constructor */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(const Array&) = default;
-
- private:
-  struct PrivateType {};
-
- public:
-  /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(
-      const EigenBase<OtherDerived>& other,
-      std::enable_if_t<internal::is_convertible<typename OtherDerived::Scalar, Scalar>::value, PrivateType> =
-          PrivateType())
-      : Base(other.derived()) {}
-
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return 1; }
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { 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.
- *
- * With \cpp11, template alias are also defined for common sizes.
- * They follow the same pattern as above except that the scalar type suffix is replaced by a
- * template parameter, i.e.:
- *   - `ArrayRowsCols<Type>` where `Rows` and `Cols` can be \c 2,\c 3,\c 4, or \c X for fixed or dynamic size.
- *   - `ArraySize<Type>` where `Size` can be \c 2,\c 3,\c 4 or \c X for fixed or dynamic size 1D arrays.
- *
- * \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_FIXED_TYPEDEFS
-
-#define EIGEN_MAKE_ARRAY_TYPEDEFS(Size, SizeSuffix)              \
-  /** \ingroup arraytypedefs */                                  \
-  /** \brief \cpp11 */                                           \
-  template <typename Type>                                       \
-  using Array##SizeSuffix##SizeSuffix = Array<Type, Size, Size>; \
-  /** \ingroup arraytypedefs */                                  \
-  /** \brief \cpp11 */                                           \
-  template <typename Type>                                       \
-  using Array##SizeSuffix = Array<Type, Size, 1>;
-
-#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Size)        \
-  /** \ingroup arraytypedefs */                      \
-  /** \brief \cpp11 */                               \
-  template <typename Type>                           \
-  using Array##Size##X = Array<Type, Size, Dynamic>; \
-  /** \ingroup arraytypedefs */                      \
-  /** \brief \cpp11 */                               \
-  template <typename Type>                           \
-  using Array##X##Size = Array<Type, Dynamic, Size>;
-
-EIGEN_MAKE_ARRAY_TYPEDEFS(2, 2)
-EIGEN_MAKE_ARRAY_TYPEDEFS(3, 3)
-EIGEN_MAKE_ARRAY_TYPEDEFS(4, 4)
-EIGEN_MAKE_ARRAY_TYPEDEFS(Dynamic, X)
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(2)
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(3)
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(4)
-
-#undef EIGEN_MAKE_ARRAY_TYPEDEFS
-#undef EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS
-
-#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

@@ -1,213 +0,0 @@
-// 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.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 dimensional 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 TopicCustomizing_Plugins 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;
-
-  typedef typename internal::traits<Derived>::StorageKind StorageKind;
-  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::ColsAtCompileTime;
-  using Base::Flags;
-  using Base::IsVectorAtCompileTime;
-  using Base::MaxColsAtCompileTime;
-  using Base::MaxRowsAtCompileTime;
-  using Base::MaxSizeAtCompileTime;
-  using Base::RowsAtCompileTime;
-  using Base::SizeAtCompileTime;
-
-  using Base::coeff;
-  using Base::coeffRef;
-  using Base::cols;
-  using Base::const_cast_derived;
-  using Base::derived;
-  using Base::lazyAssign;
-  using Base::rows;
-  using Base::size;
-  using Base::operator-;
-  using Base::operator=;
-  using Base::operator+=;
-  using Base::operator-=;
-  using Base::operator*=;
-  using Base::operator/=;
-
-  typedef typename Base::CoeffReturnType CoeffReturnType;
-
-  typedef typename Base::PlainObject PlainObject;
-
-  /** \internal Represents a matrix with all coefficients equal to one another*/
-  typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> ConstantReturnType;
-#endif  // not EIGEN_PARSED_BY_DOXYGEN
-
-#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase
-#define EIGEN_DOC_UNARY_ADDONS(X, Y)
-#include "../plugins/MatrixCwiseUnaryOps.inc"
-#include "../plugins/ArrayCwiseUnaryOps.inc"
-#include "../plugins/CommonCwiseBinaryOps.inc"
-#include "../plugins/MatrixCwiseBinaryOps.inc"
-#include "../plugins/ArrayCwiseBinaryOps.inc"
-#ifdef EIGEN_ARRAYBASE_PLUGIN
-#include EIGEN_ARRAYBASE_PLUGIN
-#endif
-#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
-#undef EIGEN_DOC_UNARY_ADDONS
-
-  /** Special case of the template operator=, in order to prevent the compiler
-   * from generating a default operator= (issue hit with g++ 4.1)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const ArrayBase& other) {
-    internal::call_assignment(derived(), other.derived());
-    return derived();
-  }
-
-  /** Set all the entries to \a value.
-   * \sa DenseBase::setConstant(), DenseBase::fill() */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const Scalar& value) {
-    Base::setConstant(value);
-    return derived();
-  }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const Scalar& other) {
-    internal::call_assignment(this->derived(), PlainObject::Constant(rows(), cols(), other),
-                              internal::add_assign_op<Scalar, Scalar>());
-    return derived();
-  }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const Scalar& other) {
-    internal::call_assignment(this->derived(), PlainObject::Constant(rows(), cols(), other),
-                              internal::sub_assign_op<Scalar, Scalar>());
-    return derived();
-  }
-
-  /** replaces \c *this by \c *this + \a other.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
-
-  /** replaces \c *this by \c *this - \a other.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
-
-  /** replaces \c *this by \c *this * \a other coefficient wise.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
-
-  /** replaces \c *this by \c *this / \a other coefficient wise.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::div_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
-
- public:
-  EIGEN_DEVICE_FUNC ArrayBase<Derived>& array() { return *this; }
-  EIGEN_DEVICE_FUNC const ArrayBase<Derived>& array() const { return *this; }
-
-  /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
-   * \sa MatrixBase::array() */
-  EIGEN_DEVICE_FUNC MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); }
-  EIGEN_DEVICE_FUNC const MatrixWrapper<const Derived> matrix() const {
-    return MatrixWrapper<const Derived>(derived());
-  }
-
-  //     template<typename Dest>
-  //     inline void evalTo(Dest& dst) const { dst = matrix(); }
-
- protected:
-  EIGEN_DEFAULT_COPY_CONSTRUCTOR(ArrayBase)
-  EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(ArrayBase)
-
- 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;
-  }
-};
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_ARRAYBASE_H

Eigen/src/Core/ArrayWrapper.h

@@ -1,165 +0,0 @@
-// 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.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<remove_all_t<typename ExpressionType::Nested> > {
-  typedef ArrayXpr XprKind;
-  // Let's remove NestByRefBit
-  enum {
-    Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
-    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
-    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
-  };
-};
-}  // namespace internal
-
-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 internal::remove_all_t<ExpressionType> NestedExpression;
-
-  typedef std::conditional_t<internal::is_lvalue<ExpressionType>::value, Scalar, const Scalar>
-      ScalarWithConstIfNotLvalue;
-
-  typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
-
-  using Base::coeffRef;
-
-  EIGEN_DEVICE_FUNC explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
-
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); }
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); }
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); }
-
-  EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-  EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); }
-
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
-    return m_expression.coeffRef(rowId, colId);
-  }
-
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
-
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC inline void evalTo(Dest& dst) const {
-    dst = m_expression;
-  }
-
-  EIGEN_DEVICE_FUNC const internal::remove_all_t<NestedExpressionType>& nestedExpression() const {
-    return m_expression;
-  }
-
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index)  */
-  EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); }
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index,Index)*/
-  EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); }
-
- 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<remove_all_t<typename ExpressionType::Nested> > {
-  typedef MatrixXpr XprKind;
-  // Let's remove NestByRefBit
-  enum {
-    Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
-    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
-    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
-  };
-};
-}  // namespace internal
-
-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 internal::remove_all_t<ExpressionType> NestedExpression;
-
-  typedef std::conditional_t<internal::is_lvalue<ExpressionType>::value, Scalar, const Scalar>
-      ScalarWithConstIfNotLvalue;
-
-  typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
-
-  using Base::coeffRef;
-
-  EIGEN_DEVICE_FUNC explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
-
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); }
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); }
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); }
-
-  EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-  EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); }
-
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
-    return m_expression.derived().coeffRef(rowId, colId);
-  }
-
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
-
-  EIGEN_DEVICE_FUNC const internal::remove_all_t<NestedExpressionType>& nestedExpression() const {
-    return m_expression;
-  }
-
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index)  */
-  EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); }
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index,Index)*/
-  EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); }
-
- protected:
-  NestedExpressionType m_expression;
-};
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_ARRAYWRAPPER_H

Eigen/src/Core/Assign.h

@@ -1,80 +1,445 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
+// for linear algebra. Eigen itself is part of the KDE project.
 //
 // Copyright (C) 2007 Michael Olbrich <michael.olbrich@gmx.net>
-// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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/.
+// 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_ASSIGN_H
 #define EIGEN_ASSIGN_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+/***************************************************************************
+* Part 1 : the logic deciding a strategy for vectorization and unrolling
+***************************************************************************/
 
-namespace Eigen {
+template <typename Derived, typename OtherDerived>
+struct ei_assign_traits
+{
+public:
+  enum {
+    DstIsAligned = Derived::Flags & AlignedBit,
+    SrcIsAligned = OtherDerived::Flags & AlignedBit,
+    SrcAlignment = DstIsAligned && SrcIsAligned ? Aligned : Unaligned
+  };
 
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::lazyAssign(const DenseBase<OtherDerived>& other) {
-  enum { SameType = internal::is_same<typename Derived::Scalar, typename OtherDerived::Scalar>::value };
+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
+  };
 
-  EIGEN_STATIC_ASSERT_LVALUE(Derived)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived, OtherDerived)
-  EIGEN_STATIC_ASSERT(
-      SameType,
-      YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+  enum {
+    MightVectorize = (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit)
+                  && ((int(Derived::Flags)&RowMajorBit)==(int(OtherDerived::Flags)&RowMajorBit)),
+    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 */
+  };
 
-  eigen_assert(rows() == other.rows() && cols() == other.cols());
-  internal::call_assignment_no_alias(derived(), other.derived());
+public:
+  enum {
+    Vectorization = int(MayInnerVectorize)  ? int(InnerVectorization)
+                  : int(MayLinearVectorize) ? int(LinearVectorization)
+                  : int(MaySliceVectorize)  ? int(SliceVectorization)
+                                            : int(NoVectorization)
+  };
 
+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)
+  };
+
+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) )
+              : int(NoUnrolling)
+  };
+};
+
+/***************************************************************************
+* Part 2 : meta-unrollers
+***************************************************************************/
+
+/***********************
+*** No vectorization ***
+***********************/
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct ei_assign_novec_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)
+  {
+    dst.copyCoeff(row, col, src);
+    ei_assign_novec_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>
+{
+  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) {}
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct ei_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
+  };
+
+  EIGEN_STRONG_INLINE static 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);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct ei_assign_innervec_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_innervec_InnerUnrolling
+{
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int row_or_col)
+  {
+    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);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct ei_assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
+};
+
+/***************************************************************************
+* Part 3 : implementation of all cases
+***************************************************************************/
+
+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;
+
+/***********************
+*** No vectorization ***
+***********************/
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, NoVectorization, NoUnrolling>
+{
+  inline static 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);
+      }
+  }
+};
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, NoVectorization, CompleteUnrolling>
+{
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  {
+    ei_assign_novec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+      ::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, NoVectorization, InnerUnrolling>
+{
+  EIGEN_STRONG_INLINE static 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);
+  }
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, InnerVectorization, NoUnrolling>
+{
+  inline static 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);
+      }
+  }
+};
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, InnerVectorization, CompleteUnrolling>
+{
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  {
+    ei_assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+      ::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, InnerVectorization, InnerUnrolling>
+{
+  EIGEN_STRONG_INLINE static 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);
+  }
+};
+
+/***************************
+*** Linear vectorization ***
+***************************/
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, LinearVectorization, NoUnrolling>
+{
+  inline static void run(Derived1 &dst, const Derived2 &src)
+  {
+    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)
+      dst.copyCoeff(index, src);
+  }
+};
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, LinearVectorization, CompleteUnrolling>
+{
+  EIGEN_STRONG_INLINE static 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;
+
+    ei_assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
+    ei_assign_novec_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
+  }
+};
+
+/**************************
+*** Slice vectorization ***
+***************************/
+
+template<typename Derived1, typename Derived2>
+struct ei_assign_impl<Derived1, Derived2, SliceVectorization, NoUnrolling>
+{
+  inline static 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)
+    {
+      const int 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);
+      }
+
+      // 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);
+      }
+
+      // 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);
+      }
+
+      alignedStart = std::min<int>((alignedStart+alignedStep)%packetSize, innerSize);
+    }
+  }
+};
+
+/***************************************************************************
+* Part 4 : implementation of MatrixBase methods
+***************************************************************************/
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>
+  ::lazyAssign(const MatrixBase<OtherDerived>& other)
+{
+  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());
   return derived();
 }
 
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
+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;
+
+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()); }
+};
+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()); }
+};
+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()); }
+};
+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()); }
+};
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>
+  ::operator=(const MatrixBase<OtherDerived>& other)
+{
+  return ei_assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
 }
 
-template <typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(
-    const ReturnByValue<OtherDerived>& other) {
-  other.derived().evalTo(derived());
-  return derived();
-}
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_ASSIGN_H
+#endif // EIGEN_ASSIGN_H

Eigen/src/Core/Assign_MKL.h

@@ -1,183 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
- Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
-
- 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Dst, typename Src>
-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 = 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
-  };
-
- public:
-  enum { EnableVml = MightEnableVml && LargeEnough, Traversal = MightLinearize ? LinearTraversal : DefaultTraversal };
-};
-
-#define EIGEN_PP_EXPAND(ARG) ARG
-#if !defined(EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
-#define EIGEN_VMLMODE_EXPAND_xLA , VML_HA
-#else
-#define EIGEN_VMLMODE_EXPAND_xLA , VML_LA
-#endif
-
-#define EIGEN_VMLMODE_EXPAND_x_
-
-#define EIGEN_VMLMODE_PREFIX_xLA vm
-#define EIGEN_VMLMODE_PREFIX_x_ v
-#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_x, VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                      \
-  template <typename DstXprType, typename SrcXprNested>                                                    \
-  struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>,              \
-                    assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense,                                          \
-                    std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> {            \
-    typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType;                       \
-    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
-      resize_if_allowed(dst, src, func);                                                                   \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                  \
-      if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == (int)LinearTraversal) {                \
-        VMLOP(dst.size(), (const VMLTYPE *)src.nestedExpression().data(),                                  \
-              (VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                     \
-      } else {                                                                                             \
-        const Index outerSize = dst.outerSize();                                                           \
-        for (Index outer = 0; outer < outerSize; ++outer) {                                                \
-          const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer, 0))         \
-                                                    : &(src.nestedExpression().coeffRef(0, outer));        \
-          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer));     \
-          VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr,                                                 \
-                (VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                      \
-        }                                                                                                  \
-      }                                                                                                    \
-    }                                                                                                      \
-  };
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)                                                \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), s##VMLOP), float, float, VMLMODE) \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), d##VMLOP), double, double, VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)                                   \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), c##VMLOP), scomplex, \
-                                   MKL_Complex8, VMLMODE)                                                 \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), z##VMLOP), dcomplex, \
-                                   MKL_Complex16, VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)  \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA)
-// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,   Abs,    _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _)
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(cbrt, Cbrt, _)
-
-#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                        \
-  template <typename DstXprType, typename SrcXprNested, typename Plain>                                    \
-  struct Assignment<DstXprType,                                                                            \
-                    CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested,               \
-                                  const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>>,   \
-                    assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense,                                          \
-                    std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> {            \
-    typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested,                       \
-                          const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>>            \
-        SrcXprType;                                                                                        \
-    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
-      resize_if_allowed(dst, src, func);                                                                   \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                  \
-      VMLTYPE exponent = reinterpret_cast<const VMLTYPE &>(src.rhs().functor().m_other);                   \
-      if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == LinearTraversal) {                     \
-        VMLOP(dst.size(), (const VMLTYPE *)src.lhs().data(), exponent,                                     \
-              (VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                     \
-      } else {                                                                                             \
-        const Index outerSize = dst.outerSize();                                                           \
-        for (Index outer = 0; outer < outerSize; ++outer) {                                                \
-          const EIGENTYPE *src_ptr =                                                                       \
-              src.IsRowMajor ? &(src.lhs().coeffRef(outer, 0)) : &(src.lhs().coeffRef(0, outer));          \
-          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer));     \
-          VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, exponent,                                       \
-                (VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                      \
-        }                                                                                                  \
-      }                                                                                                    \
-    }                                                                                                      \
-  };
-
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_ASSIGN_VML_H

Eigen/src/Core/BandMatrix.h

@@ -1,338 +0,0 @@
-// 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.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::StorageIndex StorageIndex;
-  typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
-  typedef EigenBase<Derived> Base;
-
- protected:
-  enum {
-    DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic,
-    SizeAtCompileTime = min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime)
-  };
-
- public:
-  using Base::cols;
-  using Base::derived;
-  using Base::rows;
-
-  /** \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((int(Options) & int(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 =
-          (int(Options) & int(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 ? min_size_prefer_dynamic(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
-                                 : min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
-    };
-    typedef Block<CoefficientsType, 1, DiagonalSize> BuildType;
-    typedef std::conditional_t<Conjugate, CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, BuildType>, BuildType>
-        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
- *
- * \tparam Scalar_ Numeric type, i.e. float, double, int
- * \tparam Rows_ Number of rows, or \b Dynamic
- * \tparam Cols_ Number of columns, or \b Dynamic
- * \tparam Supers_ Number of super diagonal
- * \tparam Subs_ Number of sub diagonal
- * \tparam 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 Eigen::Index StorageIndex;
-  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, int(Options) & int(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>::StorageIndex StorageIndex;
-  typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
-
-  explicit 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 */
-  constexpr Index rows() const { return m_rows.value(); }
-
-  /** \returns the number of rows */
-  constexpr Index cols() const { return m_coeffs.cols(); }
-
-  /** \returns the number of super diagonals */
-  constexpr Index supers() const { return m_supers.value(); }
-
-  /** \returns the number of sub diagonals */
-  constexpr 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_::StorageIndex StorageIndex;
-  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>::StorageIndex StorageIndex;
-
-  explicit 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);
-    // eigen_assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
-  }
-
-  /** \returns the number of columns */
-  constexpr Index rows() const { return m_rows.value(); }
-
-  /** \returns the number of rows */
-  constexpr Index cols() const { return m_coeffs.cols(); }
-
-  /** \returns the number of super diagonals */
-  constexpr Index supers() const { return m_supers.value(); }
-
-  /** \returns the number of sub diagonals */
-  constexpr 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
- *
- * \tparam Scalar Numeric type, i.e. float, double, int
- * \tparam Size Number of rows and cols, or \b Dynamic
- * \tparam 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::StorageIndex StorageIndex;
-
- public:
-  explicit 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:
-};
-
-struct BandShape {};
-
-template <typename Scalar_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct evaluator_traits<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> >
-    : public evaluator_traits_base<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> > {
-  typedef BandShape Shape;
-};
-
-template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct evaluator_traits<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> >
-    : public evaluator_traits_base<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> > {
-  typedef BandShape Shape;
-};
-
-template <>
-struct AssignmentKind<DenseShape, BandShape> {
-  typedef EigenBase2EigenBase Kind;
-};
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_BANDMATRIX_H

Eigen/src/Core/CMakeLists.txt

@@ -0,0 +1,9 @@
+FILE(GLOB Eigen_Core_SRCS "*.h")
+
+INSTALL(FILES
+  ${Eigen_Core_SRCS}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core
+  )
+
+ADD_SUBDIRECTORY(util)
+ADD_SUBDIRECTORY(arch)

Eigen/src/Core/CacheFriendlyProduct.h

@@ -0,0 +1,753 @@
+// 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

@@ -0,0 +1,384 @@
+// 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

@@ -1,149 +1,149 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
+// for linear algebra. Eigen itself is part of the KDE project.
 //
-// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2006-2008 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/.
+// 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_COMMAINITIALIZER_H
 #define EIGEN_COMMAINITIALIZER_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
 /** \class CommaInitializer
- * \ingroup Core_Module
- *
- * \brief Helper class used by the comma initializer operator
- *
- * This class is internally used to implement the comma initializer feature. It is
- * the return type of MatrixBase::operator<<, and most of the time this is the only
- * way it is used.
- *
- * \sa \blank \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
- */
-template <typename XprType>
-struct CommaInitializer {
-  typedef typename XprType::Scalar Scalar;
-
-  EIGEN_DEVICE_FUNC inline CommaInitializer(XprType& xpr, const Scalar& s)
-      : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1) {
-    eigen_assert(m_xpr.rows() > 0 && m_xpr.cols() > 0 && "Cannot comma-initialize a 0x0 matrix (operator<<)");
-    m_xpr.coeffRef(0, 0) = s;
+  *
+  * \brief Helper class used by the comma initializer operator
+  *
+  * This class is internally used to implement the comma initializer feature. It is
+  * the return type of MatrixBase::operator<<, and most of the time this is the only
+  * way it is used.
+  *
+  * \sa \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
+  */
+template<typename MatrixType>
+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)
+  {
+    m_matrix.coeffRef(0,0) = s;
   }
 
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
-      : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows()) {
-    eigen_assert(m_xpr.rows() >= other.rows() && m_xpr.cols() >= other.cols() &&
-                 "Cannot comma-initialize a 0x0 matrix (operator<<)");
-    m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>(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
-  EIGEN_DEVICE_FUNC 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;
+  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())
+  {
+    m_matrix.block(0, 0, other.rows(), other.cols()) = other;
   }
 
   /* inserts a scalar value in the target matrix */
-  EIGEN_DEVICE_FUNC CommaInitializer &operator,(const Scalar& s) {
-    if (m_col == m_xpr.cols()) {
-      m_row += m_currentBlockRows;
+  CommaInitializer& operator,(const Scalar& s)
+  {
+    if (m_col==m_matrix.cols())
+    {
+      m_row+=m_currentBlockRows;
       m_col = 0;
       m_currentBlockRows = 1;
-      eigen_assert(m_row < m_xpr.rows() && "Too many rows passed to comma initializer (operator<<)");
+      ei_assert(m_row<m_matrix.rows()
+        && "Too many rows passed to comma initializer (operator<<)");
     }
-    eigen_assert(m_col < m_xpr.cols() && "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows == 1);
-    m_xpr.coeffRef(m_row, m_col++) = s;
+    ei_assert(m_col<m_matrix.cols()
+      && "Too many coefficients passed to comma initializer (operator<<)");
+    ei_assert(m_currentBlockRows==1);
+    m_matrix.coeffRef(m_row, m_col++) = s;
     return *this;
   }
 
   /* inserts a matrix expression in the target matrix */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC CommaInitializer &operator,(const DenseBase<OtherDerived>& other) {
-    if (m_col == m_xpr.cols() && (other.cols() != 0 || other.rows() != m_currentBlockRows)) {
-      m_row += m_currentBlockRows;
+  template<typename OtherDerived>
+  CommaInitializer& operator,(const MatrixBase<OtherDerived>& other)
+  {
+    if (m_col==m_matrix.cols())
+    {
+      m_row+=m_currentBlockRows;
       m_col = 0;
       m_currentBlockRows = other.rows();
-      eigen_assert(m_row + m_currentBlockRows <= m_xpr.rows() &&
-                   "Too many rows passed to comma initializer (operator<<)");
+      ei_assert(m_row+m_currentBlockRows<=m_matrix.rows()
+        && "Too many rows passed to comma initializer (operator<<)");
     }
-    eigen_assert((m_col + other.cols() <= m_xpr.cols()) &&
-                 "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows == other.rows());
-    m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>(m_row, m_col, other.rows(),
-                                                                                           other.cols()) = other;
+    ei_assert(m_col<m_matrix.cols()
+      && "Too many coefficients passed to comma initializer (operator<<)");
+    ei_assert(m_currentBlockRows==other.rows());
+    if (OtherDerived::SizeAtCompileTime != Dynamic)
+      m_matrix.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_col += other.cols();
     return *this;
   }
 
-  EIGEN_DEVICE_FUNC inline ~CommaInitializer()
-#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS
-      noexcept(false)  // Eigen::eigen_assert_exception
-#endif
+  inline ~CommaInitializer()
   {
-    finished();
+    ei_assert((m_row+m_currentBlockRows) == m_matrix.rows()
+         && m_col == m_matrix.cols()
+         && "Too few coefficients passed to comma initializer (operator<<)");
   }
 
   /** \returns the built matrix once all its coefficients have been set.
-   * Calling finished is 100% optional. Its purpose is to write expressions
-   * like this:
-   * \code
-   * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
-   * \endcode
-   */
-  EIGEN_DEVICE_FUNC inline XprType& finished() {
-    eigen_assert(((m_row + m_currentBlockRows) == m_xpr.rows() || m_xpr.cols() == 0) && m_col == m_xpr.cols() &&
-                 "Too few coefficients passed to comma initializer (operator<<)");
-    return m_xpr;
-  }
+    * Calling finished is 100% optional. Its purpose is to write expressions
+    * like this:
+    * \code
+    * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
+    * \endcode
+    */
+  inline MatrixType& finished() { return m_matrix; }
 
-  XprType& m_xpr;            // target expression
-  Index m_row;               // current row id
-  Index m_col;               // current col id
-  Index m_currentBlockRows;  // current block height
+  MatrixType& m_matrix;   // target matrix
+  int m_row;              // current row id
+  int m_col;              // current col id
+  int m_currentBlockRows; // current block height
 };
 
 /** \anchor MatrixBaseCommaInitRef
- * Convenient operator to set the coefficients of a matrix.
- *
- * The coefficients must be provided in a row major order and exactly match
- * the size of the matrix. Otherwise an assertion is raised.
- *
- * 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>
-EIGEN_DEVICE_FUNC inline CommaInitializer<Derived> DenseBase<Derived>::operator<<(const Scalar& s) {
+  * Convenient operator to set the coefficients of a matrix.
+  *
+  * 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
+  *
+  * \sa CommaInitializer::finished(), class CommaInitializer
+  */
+template<typename Derived>
+inline CommaInitializer<Derived> MatrixBase<Derived>::operator<< (const Scalar& s)
+{
   return CommaInitializer<Derived>(*static_cast<Derived*>(this), s);
 }
 
 /** \sa operator<<(const Scalar&) */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC inline CommaInitializer<Derived> DenseBase<Derived>::operator<<(
-    const DenseBase<OtherDerived>& other) {
-  return CommaInitializer<Derived>(*static_cast<Derived*>(this), other);
+template<typename Derived>
+template<typename OtherDerived>
+inline CommaInitializer<Derived>
+MatrixBase<Derived>::operator<<(const MatrixBase<OtherDerived>& other)
+{
+  return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
 }
 
-}  // end namespace Eigen
-
-#endif  // EIGEN_COMMAINITIALIZER_H
+#endif // EIGEN_COMMAINITIALIZER_H

Eigen/src/Core/ConditionEstimator.h

@@ -1,173 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2016 Rasmus Munk Larsen (rmlarsen@google.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_CONDITIONESTIMATOR_H
-#define EIGEN_CONDITIONESTIMATOR_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Vector, typename RealVector, bool IsComplex>
-struct rcond_compute_sign {
-  static inline Vector run(const Vector& v) {
-    const RealVector v_abs = v.cwiseAbs();
-    return (v_abs.array() == static_cast<typename Vector::RealScalar>(0))
-        .select(Vector::Ones(v.size()), v.cwiseQuotient(v_abs));
-  }
-};
-
-// Partial specialization to avoid elementwise division for real vectors.
-template <typename Vector>
-struct rcond_compute_sign<Vector, Vector, false> {
-  static inline Vector run(const Vector& v) {
-    return (v.array() < static_cast<typename Vector::RealScalar>(0))
-        .select(-Vector::Ones(v.size()), Vector::Ones(v.size()));
-  }
-};
-
-/**
- * \returns an estimate of ||inv(matrix)||_1 given a decomposition of
- * \a matrix that implements .solve() and .adjoint().solve() methods.
- *
- * This function implements Algorithms 4.1 and 5.1 from
- *   http://www.maths.manchester.ac.uk/~higham/narep/narep135.pdf
- * which also forms the basis for the condition number estimators in
- * LAPACK. Since at most 10 calls to the solve method of dec are
- * performed, the total cost is O(dims^2), as opposed to O(dims^3)
- * needed to compute the inverse matrix explicitly.
- *
- * The most common usage is in estimating the condition number
- * ||matrix||_1 * ||inv(matrix)||_1. The first term ||matrix||_1 can be
- * computed directly in O(n^2) operations.
- *
- * Supports the following decompositions: FullPivLU, PartialPivLU, LDLT, and
- * LLT.
- *
- * \sa FullPivLU, PartialPivLU, LDLT, LLT.
- */
-template <typename Decomposition>
-typename Decomposition::RealScalar rcond_invmatrix_L1_norm_estimate(const Decomposition& dec) {
-  typedef typename Decomposition::MatrixType MatrixType;
-  typedef typename Decomposition::Scalar Scalar;
-  typedef typename Decomposition::RealScalar RealScalar;
-  typedef typename internal::plain_col_type<MatrixType>::type Vector;
-  typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVector;
-  const bool is_complex = (NumTraits<Scalar>::IsComplex != 0);
-
-  eigen_assert(dec.rows() == dec.cols());
-  const Index n = dec.rows();
-  if (n == 0) return 0;
-
-    // Disable Index to float conversion warning
-#ifdef __INTEL_COMPILER
-#pragma warning push
-#pragma warning(disable : 2259)
-#endif
-  Vector v = dec.solve(Vector::Ones(n) / Scalar(n));
-#ifdef __INTEL_COMPILER
-#pragma warning pop
-#endif
-
-  // lower_bound is a lower bound on
-  //   ||inv(matrix)||_1  = sup_v ||inv(matrix) v||_1 / ||v||_1
-  // and is the objective maximized by the ("super-") gradient ascent
-  // algorithm below.
-  RealScalar lower_bound = v.template lpNorm<1>();
-  if (n == 1) return lower_bound;
-
-  // Gradient ascent algorithm follows: We know that the optimum is achieved at
-  // one of the simplices v = e_i, so in each iteration we follow a
-  // super-gradient to move towards the optimal one.
-  RealScalar old_lower_bound = lower_bound;
-  Vector sign_vector(n);
-  Vector old_sign_vector;
-  Index v_max_abs_index = -1;
-  Index old_v_max_abs_index = v_max_abs_index;
-  for (int k = 0; k < 4; ++k) {
-    sign_vector = internal::rcond_compute_sign<Vector, RealVector, is_complex>::run(v);
-    if (k > 0 && !is_complex && sign_vector == old_sign_vector) {
-      // Break if the solution stagnated.
-      break;
-    }
-    // v_max_abs_index = argmax |real( inv(matrix)^T * sign_vector )|
-    v = dec.adjoint().solve(sign_vector);
-    v.real().cwiseAbs().maxCoeff(&v_max_abs_index);
-    if (v_max_abs_index == old_v_max_abs_index) {
-      // Break if the solution stagnated.
-      break;
-    }
-    // Move to the new simplex e_j, where j = v_max_abs_index.
-    v = dec.solve(Vector::Unit(n, v_max_abs_index));  // v = inv(matrix) * e_j.
-    lower_bound = v.template lpNorm<1>();
-    if (lower_bound <= old_lower_bound) {
-      // Break if the gradient step did not increase the lower_bound.
-      break;
-    }
-    if (!is_complex) {
-      old_sign_vector = sign_vector;
-    }
-    old_v_max_abs_index = v_max_abs_index;
-    old_lower_bound = lower_bound;
-  }
-  // The following calculates an independent estimate of ||matrix||_1 by
-  // multiplying matrix by a vector with entries of slowly increasing
-  // magnitude and alternating sign:
-  //   v_i = (-1)^{i} (1 + (i / (dim-1))), i = 0,...,dim-1.
-  // This improvement to Hager's algorithm above is due to Higham. It was
-  // added to make the algorithm more robust in certain corner cases where
-  // large elements in the matrix might otherwise escape detection due to
-  // exact cancellation (especially when op and op_adjoint correspond to a
-  // sequence of backsubstitutions and permutations), which could cause
-  // Hager's algorithm to vastly underestimate ||matrix||_1.
-  Scalar alternating_sign(RealScalar(1));
-  for (Index i = 0; i < n; ++i) {
-    // The static_cast is needed when Scalar is a complex and RealScalar implements expression templates
-    v[i] = alternating_sign * static_cast<RealScalar>(RealScalar(1) + (RealScalar(i) / (RealScalar(n - 1))));
-    alternating_sign = -alternating_sign;
-  }
-  v = dec.solve(v);
-  const RealScalar alternate_lower_bound = (2 * v.template lpNorm<1>()) / (3 * RealScalar(n));
-  return numext::maxi(lower_bound, alternate_lower_bound);
-}
-
-/** \brief Reciprocal condition number estimator.
- *
- * Computing a decomposition of a dense matrix takes O(n^3) operations, while
- * this method estimates the condition number quickly and reliably in O(n^2)
- * operations.
- *
- * \returns an estimate of the reciprocal condition number
- * (1 / (||matrix||_1 * ||inv(matrix)||_1)) of matrix, given ||matrix||_1 and
- * its decomposition. Supports the following decompositions: FullPivLU,
- * PartialPivLU, LDLT, and LLT.
- *
- * \sa FullPivLU, PartialPivLU, LDLT, LLT.
- */
-template <typename Decomposition>
-typename Decomposition::RealScalar rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm,
-                                                         const Decomposition& dec) {
-  typedef typename Decomposition::RealScalar RealScalar;
-  eigen_assert(dec.rows() == dec.cols());
-  if (dec.rows() == 0) return NumTraits<RealScalar>::infinity();
-  if (numext::is_exactly_zero(matrix_norm)) return RealScalar(0);
-  if (dec.rows() == 1) return RealScalar(1);
-  const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec);
-  return (numext::is_exactly_zero(inverse_matrix_norm) ? RealScalar(0)
-                                                       : (RealScalar(1) / inverse_matrix_norm) / matrix_norm);
-}
-
-}  // namespace internal
-
-}  // namespace Eigen
-
-#endif

Eigen/src/Core/CoreInstantiations.cpp

@@ -0,0 +1,47 @@
+// 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

@@ -1,141 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-/* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
- */
-
-namespace internal {
-
-template <typename XprType, typename EvaluatorKind>
-class inner_iterator_selector;
-
-}
-
-/** \class InnerIterator
- * \brief An InnerIterator allows to loop over the element of any matrix expression.
- *
- * \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is
- * constructed.
- *
- * TODO: add a usage example
- */
-template <typename XprType>
-class InnerIterator {
- protected:
-  typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
-  typedef internal::evaluator<XprType> EvaluatorType;
-  typedef typename internal::traits<XprType>::Scalar Scalar;
-
- public:
-  /** Construct an iterator over the \a outerId -th row or column of \a xpr */
-  InnerIterator(const XprType &xpr, const Index &outerId) : m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize()) {}
-
-  /// \returns the value of the current coefficient.
-  EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
-  /** Increment the iterator \c *this to the next non-zero coefficient.
-   * Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
-   */
-  EIGEN_STRONG_INLINE InnerIterator &operator++() {
-    m_iter.operator++();
-    return *this;
-  }
-  EIGEN_STRONG_INLINE InnerIterator &operator+=(Index i) {
-    m_iter.operator+=(i);
-    return *this;
-  }
-  EIGEN_STRONG_INLINE InnerIterator operator+(Index i) {
-    InnerIterator result(*this);
-    result += i;
-    return result;
-  }
-
-  /// \returns the column or row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
-  /// \returns the row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
-  /// \returns the column index of the current coefficient.
-  EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
-  /// \returns \c true if the iterator \c *this still references a valid coefficient.
-  EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
-
- protected:
-  EvaluatorType m_eval;
-  IteratorType m_iter;
-
- private:
-  // If you get here, then you're not using the right InnerIterator type, e.g.:
-  //   SparseMatrix<double,RowMajor> A;
-  //   SparseMatrix<double>::InnerIterator it(A,0);
-  template <typename T>
-  InnerIterator(const EigenBase<T> &, Index outer);
-};
-
-namespace internal {
-
-// Generic inner iterator implementation for dense objects
-template <typename XprType>
-class inner_iterator_selector<XprType, IndexBased> {
- protected:
-  typedef evaluator<XprType> EvaluatorType;
-  typedef typename traits<XprType>::Scalar Scalar;
-  enum { IsRowMajor = (XprType::Flags & RowMajorBit) == RowMajorBit };
-
- public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
-      : m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize) {}
-
-  EIGEN_STRONG_INLINE Scalar value() const {
-    return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner) : m_eval.coeff(m_inner, m_outer);
-  }
-
-  EIGEN_STRONG_INLINE inner_iterator_selector &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 EvaluatorType &m_eval;
-  Index m_inner;
-  const Index m_outer;
-  const Index m_end;
-};
-
-// For iterator-based evaluator, inner-iterator is already implemented as
-// evaluator<>::InnerIterator
-template <typename XprType>
-class inner_iterator_selector<XprType, IteratorBased> : public evaluator<XprType>::InnerIterator {
- protected:
-  typedef typename evaluator<XprType>::InnerIterator Base;
-  typedef evaluator<XprType> EvaluatorType;
-
- public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId,
-                                              const Index & /*innerSize*/)
-      : Base(eval, outerId) {}
-};
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_COREITERATORS_H

Eigen/src/Core/Cwise.h

@@ -0,0 +1,211 @@
+// 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) 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_CWISE_H
+#define EIGEN_CWISE_H
+
+/** \internal
+  * convenient macro to defined the return type of a cwise binary operation */
+#define EIGEN_CWISE_BINOP_RETURN_TYPE(OP) \
+    CwiseBinaryOp<OP<typename ei_traits<ExpressionType>::Scalar>, ExpressionType, OtherDerived>
+
+#define EIGEN_CWISE_PRODUCT_RETURN_TYPE \
+    CwiseBinaryOp< \
+      ei_scalar_product_op< \
+        typename ei_scalar_product_traits< \
+          typename ei_traits<ExpressionType>::Scalar, \
+          typename ei_traits<OtherDerived>::Scalar \
+        >::ReturnType \
+      >, \
+      ExpressionType, \
+      OtherDerived \
+    >
+
+/** \internal
+  * convenient macro to defined the return type of a cwise unary operation */
+#define EIGEN_CWISE_UNOP_RETURN_TYPE(OP) \
+    CwiseUnaryOp<OP<typename ei_traits<ExpressionType>::Scalar>, ExpressionType>
+
+/** \internal
+  * convenient macro to defined the return type of a cwise comparison to a scalar */
+#define EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(OP) \
+    CwiseBinaryOp<OP<typename ei_traits<ExpressionType>::Scalar>, ExpressionType, \
+        NestByValue<typename ExpressionType::ConstantReturnType> >
+
+/** \class Cwise
+  *
+  * \brief Pseudo expression providing additional coefficient-wise operations
+  *
+  * \param ExpressionType the type of the object on which to do coefficient-wise operations
+  *
+  * This class represents an expression with additional coefficient-wise features.
+  * It is the return type of MatrixBase::cwise()
+  * and most of the time this is the only way it is used.
+  *
+  * Note that some methods are defined in the \ref Array module.
+  *
+  * Example: \include MatrixBase_cwise_const.cpp
+  * Output: \verbinclude MatrixBase_cwise_const.out
+  *
+  * \sa MatrixBase::cwise() const, MatrixBase::cwise()
+  */
+template<typename ExpressionType> class Cwise
+{
+  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;
+    typedef CwiseUnaryOp<ei_scalar_add_op<Scalar>, ExpressionType> ScalarAddReturnType;
+
+    inline Cwise(const ExpressionType& matrix) : m_matrix(matrix) {}
+
+    /** \internal */
+    inline const ExpressionType& _expression() const { return m_matrix; }
+
+    template<typename OtherDerived>
+    const EIGEN_CWISE_PRODUCT_RETURN_TYPE
+    operator*(const MatrixBase<OtherDerived> &other) const;
+
+    template<typename OtherDerived>
+    const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)
+    operator/(const MatrixBase<OtherDerived> &other) const;
+
+    template<typename OtherDerived>
+    const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)
+    min(const MatrixBase<OtherDerived> &other) const;
+
+    template<typename OtherDerived>
+    const EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_max_op)
+    max(const MatrixBase<OtherDerived> &other) const;
+
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs_op)      abs() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs2_op)     abs2() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_square_op)   square() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_cube_op)     cube() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_inverse_op)  inverse() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_sqrt_op)     sqrt() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_exp_op)      exp() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_log_op)      log() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_cos_op)      cos() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_sin_op)      sin() const;
+    const EIGEN_CWISE_UNOP_RETURN_TYPE(ei_scalar_pow_op)      pow(const Scalar& exponent) const;
+
+    const ScalarAddReturnType
+    operator+(const Scalar& scalar) const;
+
+    /** \relates Cwise */
+    friend const ScalarAddReturnType
+    operator+(const Scalar& scalar, const Cwise& mat)
+    { return mat + scalar; }
+
+    ExpressionType& operator+=(const Scalar& scalar);
+
+    const ScalarAddReturnType
+    operator-(const Scalar& scalar) const;
+
+    ExpressionType& operator-=(const Scalar& scalar);
+
+    template<typename OtherDerived>
+    inline ExpressionType& operator*=(const MatrixBase<OtherDerived> &other);
+
+    template<typename OtherDerived>
+    inline ExpressionType& operator/=(const MatrixBase<OtherDerived> &other);
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)
+    operator<(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)
+    operator<=(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)
+    operator>(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)
+    operator>=(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)
+    operator==(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)
+    operator!=(const MatrixBase<OtherDerived>& other) const;
+
+    // comparisons to a scalar value
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)
+    operator<(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)
+    operator<=(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)
+    operator>(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)
+    operator>=(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)
+    operator==(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)
+    operator!=(Scalar s) const;
+
+    // allow to extend Cwise outside Eigen
+    #ifdef EIGEN_CWISE_PLUGIN
+    #include EIGEN_CWISE_PLUGIN
+    #endif
+
+  protected:
+    ExpressionTypeNested m_matrix;
+};
+
+/** \returns a Cwise wrapper of *this providing additional coefficient-wise operations
+  *
+  * Example: \include MatrixBase_cwise_const.cpp
+  * Output: \verbinclude MatrixBase_cwise_const.out
+  *
+  * \sa class Cwise, cwise()
+  */
+template<typename Derived>
+inline const Cwise<Derived>
+MatrixBase<Derived>::cwise() const
+{
+  return derived();
+}
+
+/** \returns a Cwise wrapper of *this providing additional coefficient-wise operations
+  *
+  * Example: \include MatrixBase_cwise.cpp
+  * Output: \verbinclude MatrixBase_cwise.out
+  *
+  * \sa class Cwise, cwise() const
+  */
+template<typename Derived>
+inline Cwise<Derived>
+MatrixBase<Derived>::cwise()
+{
+  return derived();
+}
+
+#endif // EIGEN_CWISE_H

Eigen/src/Core/CwiseBinaryOp.h

@@ -1,166 +1,304 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
+// for linear algebra. Eigen itself is part of the KDE project.
 //
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2006-2008 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/.
+// 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_CWISE_BINARY_OP_H
 #define EIGEN_CWISE_BINARY_OP_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-template <typename BinaryOp, typename Lhs, typename 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 remove_all_t<Lhs> Ancestor;
-  typedef typename traits<Ancestor>::XprKind XprKind;
-  enum {
-    RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
-    ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
-    MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
-  };
-
+/** \class CwiseBinaryOp
+  *
+  * \brief Generic expression of a coefficient-wise operator between two matrices or vectors
+  *
+  * \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.
+  *
+  * However, if you want to write a function returning such an expression, you
+  * will need to use this class.
+  *
+  * \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp
+  */
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct ei_traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
   // 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 result_of<BinaryOp(const typename Lhs::Scalar&, const typename Rhs::Scalar&)>::type Scalar;
-  typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind,
-                                              BinaryOp>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<Lhs>::StorageIndex, typename traits<Rhs>::StorageIndex>::type
-      StorageIndex;
+  typedef typename ei_result_of<
+                     BinaryOp(
+                       typename Lhs::Scalar,
+                       typename Rhs::Scalar
+                     )
+                   >::type Scalar;
   typedef typename Lhs::Nested LhsNested;
   typedef typename Rhs::Nested RhsNested;
-  typedef std::remove_reference_t<LhsNested> LhsNested_;
-  typedef std::remove_reference_t<RhsNested> RhsNested_;
+  typedef typename ei_unref<LhsNested>::type _LhsNested;
+  typedef typename ei_unref<RhsNested>::type _RhsNested;
   enum {
-    Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind,
-                                        LhsNested_::Flags & RowMajorBit, RhsNested_::Flags & RowMajorBit>::value
+    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)) & (
+        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
   };
 };
-}  // end namespace internal
 
-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> >
+{
+  public:
 
-/** \class CwiseBinaryOp
- * \ingroup Core_Module
- *
- * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
- *
- * \tparam BinaryOp template functor implementing the operator
- * \tparam LhsType the type of the left-hand side
- * \tparam RhsType the type of the right-hand side
- *
- * 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.
- *
- * 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
- */
-template <typename BinaryOp, typename LhsType, typename RhsType>
-class CwiseBinaryOp : public CwiseBinaryOpImpl<BinaryOp, LhsType, RhsType,
-                                               typename internal::cwise_promote_storage_type<
-                                                   typename internal::traits<LhsType>::StorageKind,
-                                                   typename internal::traits<RhsType>::StorageKind, BinaryOp>::ret>,
-                      internal::no_assignment_operator {
- public:
-  typedef internal::remove_all_t<BinaryOp> Functor;
-  typedef internal::remove_all_t<LhsType> Lhs;
-  typedef internal::remove_all_t<RhsType> Rhs;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
+    typedef typename ei_traits<CwiseBinaryOp>::LhsNested LhsNested;
+    typedef typename ei_traits<CwiseBinaryOp>::RhsNested RhsNested;
 
-  typedef typename CwiseBinaryOpImpl<
-      BinaryOp, LhsType, RhsType,
-      typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
-                                                    typename internal::traits<Rhs>::StorageKind, BinaryOp>::ret>::Base
-      Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
+    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
+      : m_lhs(lhs), m_rhs(rhs), 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)
+      // require the sizes to match
+      EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
+      ei_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
+    }
 
-  EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp, typename Lhs::Scalar, typename Rhs::Scalar)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
+    EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); }
+    EIGEN_STRONG_INLINE int cols() const { return m_lhs.cols(); }
 
-  typedef typename internal::ref_selector<LhsType>::type LhsNested;
-  typedef typename internal::ref_selector<RhsType>::type RhsNested;
-  typedef std::remove_reference_t<LhsNested> LhsNested_;
-  typedef std::remove_reference_t<RhsNested> RhsNested_;
+    EIGEN_STRONG_INLINE const Scalar coeff(int row, int col) const
+    {
+      return m_functor(m_lhs.coeff(row, col), m_rhs.coeff(row, col));
+    }
 
-#if EIGEN_COMP_MSVC
-  // Required for Visual Studio or the Copy constructor will probably not get inlined!
-  EIGEN_STRONG_INLINE CwiseBinaryOp(const CwiseBinaryOp<BinaryOp, LhsType, RhsType>&) = default;
-#endif
+    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_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs,
-                                                      const BinaryOp& func = BinaryOp())
-      : m_lhs(aLhs), m_rhs(aRhs), m_functor(func) {
-    eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
-  }
+    EIGEN_STRONG_INLINE const Scalar coeff(int index) const
+    {
+      return m_functor(m_lhs.coeff(index), m_rhs.coeff(index));
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept {
-    // return the fixed size type if available to enable compile time optimizations
-    return internal::traits<internal::remove_all_t<LhsNested>>::RowsAtCompileTime == Dynamic ? m_rhs.rows()
-                                                                                             : m_lhs.rows();
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept {
-    // return the fixed size type if available to enable compile time optimizations
-    return internal::traits<internal::remove_all_t<LhsNested>>::ColsAtCompileTime == Dynamic ? m_rhs.cols()
-                                                                                             : m_lhs.cols();
-  }
+    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 */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const LhsNested_& lhs() const { return m_lhs; }
-  /** \returns the right hand side nested expression */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const RhsNested_& rhs() const { return m_rhs; }
-  /** \returns the functor representing the binary operation */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const BinaryOp& functor() const { return m_functor; }
-
- protected:
-  LhsNested m_lhs;
-  RhsNested m_rhs;
-  const BinaryOp m_functor;
+  protected:
+    const LhsNested m_lhs;
+    const RhsNested m_rhs;
+    const BinaryOp m_functor;
 };
 
-// Generic API dispatcher
-template <typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
-class CwiseBinaryOpImpl : public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs>>::type {
- public:
-  typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs>>::type Base;
-};
+/**\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
+{
+  return CwiseBinaryOp<ei_scalar_difference_op<Scalar>,
+                       Derived, OtherDerived>(derived(), other.derived());
+}
 
 /** replaces \c *this by \c *this - \a other.
- *
- * \returns a reference to \c *this
- */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived>& other) {
-  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>());
-  return derived();
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+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());
 }
 
 /** replaces \c *this by \c *this + \a other.
- *
- * \returns a reference to \c *this
- */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other) {
-  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar, typename OtherDerived::Scalar>());
-  return derived();
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
+{
+  return *this = *this + other;
 }
 
-}  // end namespace Eigen
+/** \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());
+}
 
-#endif  // EIGEN_CWISE_BINARY_OP_H
+/** \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);
+}
+
+#endif // EIGEN_CWISE_BINARY_OP_H

Eigen/src/Core/CwiseTernaryOp.h

@@ -1,171 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2016 Eugene Brevdo <ebrevdo@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_CWISE_TERNARY_OP_H
-#define EIGEN_CWISE_TERNARY_OP_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
-struct traits<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>> {
-  // we must not inherit from traits<Arg1> since it has
-  // the potential to cause problems with MSVC
-  typedef remove_all_t<Arg1> 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 Arg1, Arg2, and Arg3 to have the same scalar type
-  // (see CwiseTernaryOp constructor),
-  // we still want to handle the case when the result type is different.
-  typedef typename result_of<TernaryOp(const typename Arg1::Scalar&, const typename Arg2::Scalar&,
-                                       const typename Arg3::Scalar&)>::type Scalar;
-
-  typedef typename internal::traits<Arg1>::StorageKind StorageKind;
-  typedef typename internal::traits<Arg1>::StorageIndex StorageIndex;
-
-  typedef typename Arg1::Nested Arg1Nested;
-  typedef typename Arg2::Nested Arg2Nested;
-  typedef typename Arg3::Nested Arg3Nested;
-  typedef std::remove_reference_t<Arg1Nested> Arg1Nested_;
-  typedef std::remove_reference_t<Arg2Nested> Arg2Nested_;
-  typedef std::remove_reference_t<Arg3Nested> Arg3Nested_;
-  enum { Flags = Arg1Nested_::Flags & RowMajorBit };
-};
-}  // end namespace internal
-
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3, typename StorageKind>
-class CwiseTernaryOpImpl;
-
-/** \class CwiseTernaryOp
- * \ingroup Core_Module
- *
- * \brief Generic expression where a coefficient-wise ternary operator is
- * applied to two expressions
- *
- * \tparam TernaryOp template functor implementing the operator
- * \tparam Arg1Type the type of the first argument
- * \tparam Arg2Type the type of the second argument
- * \tparam Arg3Type the type of the third argument
- *
- * This class represents an expression where a coefficient-wise ternary
- * operator is applied to three expressions.
- * It is the return type of ternary operators, by which we mean only those
- * ternary operators where
- * all three arguments are Eigen expressions.
- * For example, the return type of betainc(matrix1, matrix2, matrix3) is a
- * CwiseTernaryOp.
- *
- * Most of the time, this is the only way that it is used, so you typically
- * don't have to name
- * CwiseTernaryOp types explicitly.
- *
- * \sa MatrixBase::ternaryExpr(const MatrixBase<Argument2> &, const
- * MatrixBase<Argument3> &, const CustomTernaryOp &) const, class CwiseBinaryOp,
- * class CwiseUnaryOp, class CwiseNullaryOp
- */
-template <typename TernaryOp, typename Arg1Type, typename Arg2Type, typename Arg3Type>
-class CwiseTernaryOp : public CwiseTernaryOpImpl<TernaryOp, Arg1Type, Arg2Type, Arg3Type,
-                                                 typename internal::traits<Arg1Type>::StorageKind>,
-                       internal::no_assignment_operator {
- public:
-  typedef internal::remove_all_t<Arg1Type> Arg1;
-  typedef internal::remove_all_t<Arg2Type> Arg2;
-  typedef internal::remove_all_t<Arg3Type> Arg3;
-
-  // require the sizes to match
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg2)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg3)
-
-  // The index types should match
-  EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
-                                         typename internal::traits<Arg2Type>::StorageKind>::value),
-                      STORAGE_KIND_MUST_MATCH)
-  EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
-                                         typename internal::traits<Arg3Type>::StorageKind>::value),
-                      STORAGE_KIND_MUST_MATCH)
-
-  typedef typename CwiseTernaryOpImpl<TernaryOp, Arg1Type, Arg2Type, Arg3Type,
-                                      typename internal::traits<Arg1Type>::StorageKind>::Base Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseTernaryOp)
-
-  typedef typename internal::ref_selector<Arg1Type>::type Arg1Nested;
-  typedef typename internal::ref_selector<Arg2Type>::type Arg2Nested;
-  typedef typename internal::ref_selector<Arg3Type>::type Arg3Nested;
-  typedef std::remove_reference_t<Arg1Nested> Arg1Nested_;
-  typedef std::remove_reference_t<Arg2Nested> Arg2Nested_;
-  typedef std::remove_reference_t<Arg3Nested> Arg3Nested_;
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseTernaryOp(const Arg1& a1, const Arg2& a2, const Arg3& a3,
-                                                       const TernaryOp& func = TernaryOp())
-      : m_arg1(a1), m_arg2(a2), m_arg3(a3), m_functor(func) {
-    eigen_assert(a1.rows() == a2.rows() && a1.cols() == a2.cols() && a1.rows() == a3.rows() && a1.cols() == a3.cols());
-  }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
-        internal::traits<internal::remove_all_t<Arg2Nested>>::RowsAtCompileTime == Dynamic)
-      return m_arg3.rows();
-    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
-             internal::traits<internal::remove_all_t<Arg3Nested>>::RowsAtCompileTime == Dynamic)
-      return m_arg2.rows();
-    else
-      return m_arg1.rows();
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
-        internal::traits<internal::remove_all_t<Arg2Nested>>::ColsAtCompileTime == Dynamic)
-      return m_arg3.cols();
-    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
-             internal::traits<internal::remove_all_t<Arg3Nested>>::ColsAtCompileTime == Dynamic)
-      return m_arg2.cols();
-    else
-      return m_arg1.cols();
-  }
-
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC const Arg1Nested_& arg1() const { return m_arg1; }
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC const Arg2Nested_& arg2() const { return m_arg2; }
-  /** \returns the third argument nested expression */
-  EIGEN_DEVICE_FUNC const Arg3Nested_& arg3() const { return m_arg3; }
-  /** \returns the functor representing the ternary operation */
-  EIGEN_DEVICE_FUNC const TernaryOp& functor() const { return m_functor; }
-
- protected:
-  Arg1Nested m_arg1;
-  Arg2Nested m_arg2;
-  Arg3Nested m_arg3;
-  const TernaryOp m_functor;
-};
-
-// Generic API dispatcher
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3, typename StorageKind>
-class CwiseTernaryOpImpl : public internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type {
- public:
-  typedef typename internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type Base;
-};
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_CWISE_TERNARY_OP_H

Eigen/src/Core/CwiseUnaryOp.h

@@ -1,91 +1,229 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
+// for linear algebra. Eigen itself is part of the KDE project.
 //
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2006-2008 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/.
+// 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_CWISE_UNARY_OP_H
 #define EIGEN_CWISE_UNARY_OP_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-template <typename UnaryOp, typename XprType>
-struct traits<CwiseUnaryOp<UnaryOp, XprType> > : traits<XprType> {
-  typedef typename result_of<UnaryOp(const typename XprType::Scalar&)>::type Scalar;
-  typedef typename XprType::Nested XprTypeNested;
-  typedef std::remove_reference_t<XprTypeNested> XprTypeNested_;
-  enum { Flags = XprTypeNested_::Flags & RowMajorBit };
-};
-}  // namespace internal
-
-template <typename UnaryOp, typename XprType, typename StorageKind>
-class CwiseUnaryOpImpl;
-
 /** \class CwiseUnaryOp
- * \ingroup Core_Module
- *
- * \brief Generic expression where a coefficient-wise unary operator is applied to an expression
- *
- * \tparam UnaryOp template functor implementing the operator
- * \tparam XprType the type of the expression to which we are applying the unary operator
- *
- * 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 XprType>
-class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>,
-                     internal::no_assignment_operator {
- public:
-  typedef typename CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>::Base Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
-  typedef typename internal::ref_selector<XprType>::type XprTypeNested;
-  typedef internal::remove_all_t<XprType> NestedExpression;
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
-      : m_xpr(xpr), m_functor(func) {}
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_xpr.rows(); }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_xpr.cols(); }
-
-  /** \returns the functor representing the unary operation */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const UnaryOp& functor() const { return m_functor; }
-
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression() const {
-    return m_xpr;
-  }
-
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE internal::remove_all_t<XprTypeNested>& nestedExpression() { return m_xpr; }
-
- protected:
-  XprTypeNested m_xpr;
-  const UnaryOp m_functor;
+  *
+  * \brief Generic expression of a coefficient-wise unary operator of a matrix or a vector
+  *
+  * \param UnaryOp template functor implementing the operator
+  * \param MatrixType the type of the matrix 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.
+  *
+  * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp
+  */
+template<typename UnaryOp, typename MatrixType>
+struct ei_traits<CwiseUnaryOp<UnaryOp, MatrixType> >
+ : ei_traits<MatrixType>
+{
+  typedef typename ei_result_of<
+                     UnaryOp(typename MatrixType::Scalar)
+                   >::type Scalar;
+  typedef typename MatrixType::Nested MatrixTypeNested;
+  typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
+  enum {
+    Flags = (_MatrixTypeNested::Flags & (
+      HereditaryBits | LinearAccessBit | AlignedBit
+      | (ei_functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0))),
+    CoeffReadCost = _MatrixTypeNested::CoeffReadCost + ei_functor_traits<UnaryOp>::Cost
+  };
 };
 
-// Generic API dispatcher
-template <typename UnaryOp, typename XprType, typename StorageKind>
-class CwiseUnaryOpImpl : public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type {
- public:
-  typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
+template<typename UnaryOp, typename MatrixType>
+class CwiseUnaryOp : ei_no_assignment_operator,
+  public MatrixBase<CwiseUnaryOp<UnaryOp, MatrixType> >
+{
+  public:
+
+    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
+
+    inline CwiseUnaryOp(const MatrixType& mat, const UnaryOp& func = UnaryOp())
+      : m_matrix(mat), 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 const Scalar coeff(int row, int col) const
+    {
+      return m_functor(m_matrix.coeff(row, col));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(int row, int col) const
+    {
+      return m_functor.packetOp(m_matrix.template packet<LoadMode>(row, col));
+    }
+
+    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));
+    }
+
+  protected:
+    const typename MatrixType::Nested m_matrix;
+    const UnaryOp m_functor;
 };
 
-}  // end namespace Eigen
+/** \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
+{
+  return CwiseUnaryOp<CustomUnaryOp, Derived>(derived(), func);
+}
 
-#endif  // EIGEN_CWISE_UNARY_OP_H
+/** \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();
+}
+
+/** \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();
+}
+
+/** \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();
+}
+
+/** \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());
+}
+
+/** \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(); }
+
+/** \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;
+}
+
+#endif // EIGEN_CWISE_UNARY_OP_H

Eigen/src/Core/CwiseUnaryView.h

@@ -1,167 +0,0 @@
-// 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-template <typename ViewOp, typename MatrixType, typename StrideType>
-struct traits<CwiseUnaryView<ViewOp, MatrixType, StrideType> > : traits<MatrixType> {
-  typedef typename result_of<ViewOp(typename traits<MatrixType>::Scalar&)>::type1 ScalarRef;
-  static_assert(std::is_reference<ScalarRef>::value, "Views must return a reference type.");
-  typedef remove_all_t<ScalarRef> Scalar;
-  typedef typename MatrixType::Nested MatrixTypeNested;
-  typedef remove_all_t<MatrixTypeNested> MatrixTypeNested_;
-  enum {
-    FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags =
-        traits<MatrixTypeNested_>::Flags &
-        (RowMajorBit | FlagsLvalueBit | DirectAccessBit),  // FIXME DirectAccessBit should not be handled by expressions
-    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 =
-        StrideType::InnerStrideAtCompileTime == 0
-            ? (MatrixTypeInnerStride == Dynamic
-                   ? int(Dynamic)
-                   : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)))
-            : int(StrideType::InnerStrideAtCompileTime),
-
-    OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
-                                   ? (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)))
-                                   : int(StrideType::OuterStrideAtCompileTime)
-  };
-};
-
-// Generic API dispatcher
-template <typename ViewOp, typename XprType, typename StrideType, typename StorageKind,
-          bool Mutable = !std::is_const<XprType>::value>
-class CwiseUnaryViewImpl : public generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type {
- public:
-  typedef typename generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type Base;
-};
-
-template <typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false>
-    : public dense_xpr_base<CwiseUnaryView<ViewOp, MatrixType, StrideType> >::type {
- public:
-  typedef CwiseUnaryView<ViewOp, MatrixType, StrideType> Derived;
-  typedef typename dense_xpr_base<CwiseUnaryView<ViewOp, MatrixType, StrideType> >::type Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
-
-  EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeffRef(0)); }
-
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const {
-    return StrideType::InnerStrideAtCompileTime != 0 ? int(StrideType::InnerStrideAtCompileTime)
-                                                     : derived().nestedExpression().innerStride() *
-                                                           sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar);
-  }
-
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const {
-    return StrideType::OuterStrideAtCompileTime != 0 ? int(StrideType::OuterStrideAtCompileTime)
-                                                     : derived().nestedExpression().outerStride() *
-                                                           sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar);
-  }
-
- protected:
-  EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl)
-
-  // Allow const access to coeffRef for the case of direct access being enabled.
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const {
-    return internal::evaluator<Derived>(derived()).coeffRef(index);
-  }
-
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const {
-    return internal::evaluator<Derived>(derived()).coeffRef(row, col);
-  }
-};
-
-template <typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, true>
-    : public CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false> {
- public:
-  typedef CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false> Base;
-  typedef CwiseUnaryView<ViewOp, MatrixType, StrideType> Derived;
-  EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
-
-  using Base::data;
-  EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) {
-    return internal::evaluator<Derived>(derived()).coeffRef(row, col);
-  }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
-    return internal::evaluator<Derived>(derived()).coeffRef(index);
-  }
-
- protected:
-  EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl)
-};
-
-}  // namespace internal
-
-/** \class CwiseUnaryView
- * \ingroup Core_Module
- *
- * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
- *
- * \tparam ViewOp template functor implementing the view
- * \tparam 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
- */
-template <typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryView : public internal::CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType,
-                                                           typename internal::traits<MatrixType>::StorageKind> {
- public:
-  typedef typename internal::CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType,
-                                                typename internal::traits<MatrixType>::StorageKind>::Base Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
-  typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
-  typedef internal::remove_all_t<MatrixType> NestedExpression;
-
-  explicit EIGEN_DEVICE_FUNC inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp())
-      : m_matrix(mat), m_functor(func) {}
-
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_matrix.rows(); }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_matrix.cols(); }
-
-  /** \returns the functor representing unary operation */
-  EIGEN_DEVICE_FUNC const ViewOp& functor() const { return m_functor; }
-
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC const internal::remove_all_t<MatrixTypeNested>& nestedExpression() const { return m_matrix; }
-
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC std::remove_reference_t<MatrixTypeNested>& nestedExpression() { return m_matrix; }
-
- protected:
-  MatrixTypeNested m_matrix;
-  ViewOp m_functor;
-};
-
-}  // namespace Eigen
-
-#endif  // EIGEN_CWISE_UNARY_VIEW_H

Eigen/src/Core/DenseBase.h

@@ -1,673 +0,0 @@
-// 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
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-// The index type defined by EIGEN_DEFAULT_DENSE_INDEX_TYPE must be a signed type.
-EIGEN_STATIC_ASSERT(NumTraits<DenseIndex>::IsSigned, THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE)
-
-/** \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 TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN.
- *
- * \sa \blank \ref TopicClassHierarchy
- */
-template <typename Derived>
-class DenseBase
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-    : public DenseCoeffsBase<Derived, internal::accessors_level<Derived>::value>
-#else
-    : public DenseCoeffsBase<Derived, DirectWriteAccessors>
-#endif  // not EIGEN_PARSED_BY_DOXYGEN
-{
- public:
-  /** Inner iterator type to iterate over the coefficients of a row or column.
-   * \sa class InnerIterator
-   */
-  typedef Eigen::InnerIterator<Derived> InnerIterator;
-
-  typedef typename internal::traits<Derived>::StorageKind StorageKind;
-
-  /**
-   * \brief The type used to store indices
-   * \details This typedef is relevant for types that store multiple indices such as
-   *          PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index
-   * \sa \blank \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase.
-   */
-  typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
-
-  /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc. */
-  typedef typename internal::traits<Derived>::Scalar Scalar;
-
-  /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex<float>, etc.
-   *
-   * It is an alias for the Scalar type */
-  typedef Scalar value_type;
-
-  typedef typename NumTraits<Scalar>::Real RealScalar;
-  typedef DenseCoeffsBase<Derived, internal::accessors_level<Derived>::value> Base;
-
-  using Base::coeff;
-  using Base::coeffByOuterInner;
-  using Base::colIndexByOuterInner;
-  using Base::cols;
-  using Base::const_cast_derived;
-  using Base::derived;
-  using Base::rowIndexByOuterInner;
-  using Base::rows;
-  using Base::size;
-  using Base::operator();
-  using Base::operator[];
-  using Base::colStride;
-  using Base::innerStride;
-  using Base::outerStride;
-  using Base::rowStride;
-  using Base::stride;
-  using Base::w;
-  using Base::x;
-  using Base::y;
-  using Base::z;
-  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_of_xpr_at_compile_time<Derived>::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),
-    /**< 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>::RowsAtCompileTime == 1 || internal::traits<Derived>::ColsAtCompileTime == 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). */
-
-    NumDimensions = int(MaxSizeAtCompileTime) == 1 ? 0
-                    : bool(IsVectorAtCompileTime)  ? 1
-                                                   : 2,
-    /**< This value is equal to Tensor::NumDimensions, i.e. 0 for scalars, 1 for vectors,
-     * and 2 for matrices.
-     */
-
-    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),
-
-    InnerStrideAtCompileTime = internal::inner_stride_at_compile_time<Derived>::ret,
-    OuterStrideAtCompileTime = internal::outer_stride_at_compile_time<Derived>::ret
-  };
-
-  typedef typename internal::find_best_packet<Scalar, SizeAtCompileTime>::type PacketScalar;
-
-  enum { IsPlainObjectBase = 0 };
-
-  /** The plain matrix type corresponding to this expression.
-   * \sa PlainObject */
-  typedef Matrix<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>
-      PlainMatrix;
-
-  /** The plain array type corresponding to this expression.
-   * \sa 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>
-      PlainArray;
-
-  /** \brief The plain matrix or array type corresponding to this expression.
-   *
-   * This 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 std::conditional_t<internal::is_same<typename internal::traits<Derived>::XprKind, MatrixXpr>::value,
-                             PlainMatrix, PlainArray>
-      PlainObject;
-
-  /** \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. */
-  EIGEN_DEVICE_FUNC constexpr 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. */
-  EIGEN_DEVICE_FUNC constexpr 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.
-   */
-  EIGEN_DEVICE_FUNC 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.
-   */
-  EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) {
-    EIGEN_ONLY_USED_FOR_DEBUG(rows);
-    EIGEN_ONLY_USED_FOR_DEBUG(cols);
-    eigen_assert(rows == this->rows() && cols == 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>, PlainObject> ConstantReturnType;
-  /** \internal Represents a matrix with all coefficients equal to zero*/
-  typedef CwiseNullaryOp<internal::scalar_zero_op<Scalar>, PlainObject> ZeroReturnType;
-  /** \internal \deprecated Represents a vector with linearly spaced coefficients that allows sequential access only. */
-  EIGEN_DEPRECATED typedef CwiseNullaryOp<internal::linspaced_op<Scalar>, PlainObject> SequentialLinSpacedReturnType;
-  /** \internal Represents a vector with linearly spaced coefficients that allows random access. */
-  typedef CwiseNullaryOp<internal::linspaced_op<Scalar>, PlainObject> RandomAccessLinSpacedReturnType;
-  /** \internal Represents a vector with equally spaced coefficients that allows random access. */
-  typedef CwiseNullaryOp<internal::equalspaced_op<Scalar>, PlainObject> RandomAccessEqualSpacedReturnType;
-  /** \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>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const DenseBase& other);
-
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC Derived& operator=(const EigenBase<OtherDerived>& other);
-
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC Derived& operator+=(const EigenBase<OtherDerived>& other);
-
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC Derived& operator-=(const EigenBase<OtherDerived>& other);
-
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC Derived& operator=(const ReturnByValue<OtherDerived>& func);
-
-  /** \internal
-   * Copies \a other into *this without evaluating other. \returns a reference to *this. */
-  template <typename OtherDerived>
-  /** \deprecated */
-  EIGEN_DEPRECATED EIGEN_DEVICE_FUNC Derived& lazyAssign(const DenseBase<OtherDerived>& other);
-
-  EIGEN_DEVICE_FUNC CommaInitializer<Derived> operator<<(const Scalar& s);
-
-  template <unsigned int Added, unsigned int Removed>
-  /** \deprecated it now returns \c *this */
-  EIGEN_DEPRECATED const Derived& flagged() const {
-    return derived();
-  }
-
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC CommaInitializer<Derived> operator<<(const DenseBase<OtherDerived>& other);
-
-  typedef Transpose<Derived> TransposeReturnType;
-  EIGEN_DEVICE_FUNC TransposeReturnType transpose();
-  typedef Transpose<const Derived> ConstTransposeReturnType;
-  EIGEN_DEVICE_FUNC const ConstTransposeReturnType transpose() const;
-  EIGEN_DEVICE_FUNC void transposeInPlace();
-
-  EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(Index rows, Index cols, const Scalar& value);
-  EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(Index size, const Scalar& value);
-  EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(const Scalar& value);
-
-  EIGEN_DEPRECATED_WITH_REASON("The method may result in accuracy loss. Use .EqualSpaced() instead.")
-  EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Sequential_t, Index size, const Scalar& low,
-                                                                           const Scalar& high);
-  EIGEN_DEPRECATED_WITH_REASON("The method may result in accuracy loss. Use .EqualSpaced() instead.")
-  EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Sequential_t, const Scalar& low,
-                                                                           const Scalar& high);
-
-  EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Index size, const Scalar& low,
-                                                                           const Scalar& high);
-  EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(const Scalar& low, const Scalar& high);
-
-  EIGEN_DEVICE_FUNC static const RandomAccessEqualSpacedReturnType EqualSpaced(Index size, const Scalar& low,
-                                                                               const Scalar& step);
-  EIGEN_DEVICE_FUNC static const RandomAccessEqualSpacedReturnType EqualSpaced(const Scalar& low, const Scalar& step);
-
-  template <typename CustomNullaryOp>
-  EIGEN_DEVICE_FUNC static const CwiseNullaryOp<CustomNullaryOp, PlainObject> NullaryExpr(Index rows, Index cols,
-                                                                                          const CustomNullaryOp& func);
-  template <typename CustomNullaryOp>
-  EIGEN_DEVICE_FUNC static const CwiseNullaryOp<CustomNullaryOp, PlainObject> NullaryExpr(Index size,
-                                                                                          const CustomNullaryOp& func);
-  template <typename CustomNullaryOp>
-  EIGEN_DEVICE_FUNC static const CwiseNullaryOp<CustomNullaryOp, PlainObject> NullaryExpr(const CustomNullaryOp& func);
-
-  EIGEN_DEVICE_FUNC static const ZeroReturnType Zero(Index rows, Index cols);
-  EIGEN_DEVICE_FUNC static const ZeroReturnType Zero(Index size);
-  EIGEN_DEVICE_FUNC static const ZeroReturnType Zero();
-  EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index rows, Index cols);
-  EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index size);
-  EIGEN_DEVICE_FUNC static const ConstantReturnType Ones();
-
-  EIGEN_DEVICE_FUNC void fill(const Scalar& value);
-  EIGEN_DEVICE_FUNC Derived& setConstant(const Scalar& value);
-  EIGEN_DEVICE_FUNC Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high);
-  EIGEN_DEVICE_FUNC Derived& setLinSpaced(const Scalar& low, const Scalar& high);
-  EIGEN_DEVICE_FUNC Derived& setEqualSpaced(Index size, const Scalar& low, const Scalar& step);
-  EIGEN_DEVICE_FUNC Derived& setEqualSpaced(const Scalar& low, const Scalar& step);
-  EIGEN_DEVICE_FUNC Derived& setZero();
-  EIGEN_DEVICE_FUNC Derived& setOnes();
-  EIGEN_DEVICE_FUNC Derived& setRandom();
-
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC bool isApprox(const DenseBase<OtherDerived>& other,
-                                  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-  EIGEN_DEVICE_FUNC bool isMuchSmallerThan(const RealScalar& other,
-                                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
-                                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-
-  EIGEN_DEVICE_FUNC bool isApproxToConstant(const Scalar& value,
-                                            const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-  EIGEN_DEVICE_FUNC bool isConstant(const Scalar& value,
-                                    const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-  EIGEN_DEVICE_FUNC bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-  EIGEN_DEVICE_FUNC bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
-
-  EIGEN_DEVICE_FUNC inline bool hasNaN() const;
-  EIGEN_DEVICE_FUNC inline bool allFinite() const;
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const Scalar& other);
-  template <bool Enable = !internal::is_same<Scalar, RealScalar>::value, typename = std::enable_if_t<Enable>>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const RealScalar& other);
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const Scalar& other);
-  template <bool Enable = !internal::is_same<Scalar, RealScalar>::value, typename = std::enable_if_t<Enable>>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const RealScalar& other);
-
-  typedef internal::add_const_on_value_type_t<typename internal::eval<Derived>::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.
-   *
-   * \warning Be careful with eval() and the auto C++ keyword, as detailed in this \link TopicPitfalls_auto_keyword page
-   * \endlink.
-   */
-  EIGEN_DEVICE_FUNC 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>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(const DenseBase<OtherDerived>& other) {
-    EIGEN_STATIC_ASSERT(!OtherDerived::IsPlainObjectBase, THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY);
-    eigen_assert(rows() == other.rows() && cols() == other.cols());
-    call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op<Scalar>());
-  }
-
-  /** swaps *this with the matrix or array \a other.
-   *
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(PlainObjectBase<OtherDerived>& other) {
-    eigen_assert(rows() == other.rows() && cols() == other.cols());
-    call_assignment(derived(), other.derived(), internal::swap_assign_op<Scalar>());
-  }
-
-  EIGEN_DEVICE_FUNC inline const NestByValue<Derived> nestByValue() const;
-  EIGEN_DEVICE_FUNC inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
-  EIGEN_DEVICE_FUNC inline ForceAlignedAccess<Derived> forceAlignedAccess();
-  template <bool Enable>
-  EIGEN_DEVICE_FUNC inline const std::conditional_t<Enable, ForceAlignedAccess<Derived>, Derived&>
-  forceAlignedAccessIf() const;
-  template <bool Enable>
-  EIGEN_DEVICE_FUNC inline std::conditional_t<Enable, ForceAlignedAccess<Derived>, Derived&> forceAlignedAccessIf();
-
-  EIGEN_DEVICE_FUNC Scalar sum() const;
-  EIGEN_DEVICE_FUNC Scalar mean() const;
-  EIGEN_DEVICE_FUNC Scalar trace() const;
-
-  EIGEN_DEVICE_FUNC Scalar prod() const;
-
-  template <int NaNPropagation>
-  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff() const;
-  template <int NaNPropagation>
-  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff() const;
-
-  // By default, the fastest version with undefined NaN propagation semantics is
-  // used.
-  // TODO(rmlarsen): Replace with default template argument when we move to
-  // c++11 or beyond.
-  EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar minCoeff() const {
-    return minCoeff<PropagateFast>();
-  }
-  EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar maxCoeff() const {
-    return maxCoeff<PropagateFast>();
-  }
-
-  template <int NaNPropagation, typename IndexType>
-  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const;
-  template <int NaNPropagation, typename IndexType>
-  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const;
-  template <int NaNPropagation, typename IndexType>
-  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const;
-  template <int NaNPropagation, typename IndexType>
-  EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const;
-
-  // TODO(rmlarsen): Replace these methods with a default template argument.
-  template <typename IndexType>
-  EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar minCoeff(IndexType* row, IndexType* col) const {
-    return minCoeff<PropagateFast>(row, col);
-  }
-  template <typename IndexType>
-  EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar maxCoeff(IndexType* row, IndexType* col) const {
-    return maxCoeff<PropagateFast>(row, col);
-  }
-  template <typename IndexType>
-  EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar minCoeff(IndexType* index) const {
-    return minCoeff<PropagateFast>(index);
-  }
-  template <typename IndexType>
-  EIGEN_DEVICE_FUNC inline typename internal::traits<Derived>::Scalar maxCoeff(IndexType* index) const {
-    return maxCoeff<PropagateFast>(index);
-  }
-
-  template <typename BinaryOp>
-  EIGEN_DEVICE_FUNC Scalar redux(const BinaryOp& func) const;
-
-  template <typename Visitor>
-  EIGEN_DEVICE_FUNC void visit(Visitor& func) const;
-
-  /** \returns a WithFormat proxy object allowing to print a matrix the with given
-   * format \a fmt.
-   *
-   * See class IOFormat for some examples.
-   *
-   * \sa class IOFormat, class WithFormat
-   */
-  inline const WithFormat<Derived> format(const IOFormat& fmt) const { return WithFormat<Derived>(derived(), fmt); }
-
-  /** \returns the unique coefficient of a 1x1 expression */
-  EIGEN_DEVICE_FUNC CoeffReturnType value() const {
-    EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) eigen_assert(this->rows() == 1 && this->cols() == 1);
-    return derived().coeff(0, 0);
-  }
-
-  EIGEN_DEVICE_FUNC bool all() const;
-  EIGEN_DEVICE_FUNC bool any() const;
-  EIGEN_DEVICE_FUNC 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;
-
-  /** \returns a VectorwiseOp wrapper of *this for broadcasting and partial reductions
-   *
-   * Example: \include MatrixBase_rowwise.cpp
-   * Output: \verbinclude MatrixBase_rowwise.out
-   *
-   * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
-   */
-  // Code moved here due to a CUDA compiler bug
-  EIGEN_DEVICE_FUNC inline ConstRowwiseReturnType rowwise() const { return ConstRowwiseReturnType(derived()); }
-  EIGEN_DEVICE_FUNC RowwiseReturnType rowwise();
-
-  /** \returns a VectorwiseOp wrapper of *this broadcasting and partial reductions
-   *
-   * Example: \include MatrixBase_colwise.cpp
-   * Output: \verbinclude MatrixBase_colwise.out
-   *
-   * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
-   */
-  EIGEN_DEVICE_FUNC inline ConstColwiseReturnType colwise() const { return ConstColwiseReturnType(derived()); }
-  EIGEN_DEVICE_FUNC ColwiseReturnType colwise();
-
-  typedef CwiseNullaryOp<internal::scalar_random_op<Scalar>, PlainObject> RandomReturnType;
-  static const RandomReturnType Random(Index rows, Index cols);
-  static const RandomReturnType Random(Index size);
-  static const RandomReturnType Random();
-
-  template <typename ThenDerived, typename ElseDerived>
-  inline EIGEN_DEVICE_FUNC
-      CwiseTernaryOp<internal::scalar_boolean_select_op<typename DenseBase<ThenDerived>::Scalar,
-                                                        typename DenseBase<ElseDerived>::Scalar, Scalar>,
-                     ThenDerived, ElseDerived, Derived>
-      select(const DenseBase<ThenDerived>& thenMatrix, const DenseBase<ElseDerived>& elseMatrix) const;
-
-  template <typename ThenDerived>
-  inline EIGEN_DEVICE_FUNC
-      CwiseTernaryOp<internal::scalar_boolean_select_op<typename DenseBase<ThenDerived>::Scalar,
-                                                        typename DenseBase<ThenDerived>::Scalar, Scalar>,
-                     ThenDerived, typename DenseBase<ThenDerived>::ConstantReturnType, Derived>
-      select(const DenseBase<ThenDerived>& thenMatrix, const typename DenseBase<ThenDerived>::Scalar& elseScalar) const;
-
-  template <typename ElseDerived>
-  inline EIGEN_DEVICE_FUNC
-      CwiseTernaryOp<internal::scalar_boolean_select_op<typename DenseBase<ElseDerived>::Scalar,
-                                                        typename DenseBase<ElseDerived>::Scalar, Scalar>,
-                     typename DenseBase<ElseDerived>::ConstantReturnType, ElseDerived, Derived>
-      select(const typename DenseBase<ElseDerived>::Scalar& thenScalar, const DenseBase<ElseDerived>& elseMatrix) const;
-
-  template <int p>
-  RealScalar lpNorm() const;
-
-  template <int RowFactor, int ColFactor>
-  EIGEN_DEVICE_FUNC const Replicate<Derived, RowFactor, ColFactor> replicate() const;
-  /**
-   * \return an expression of the replication of \c *this
-   *
-   * Example: \include MatrixBase_replicate_int_int.cpp
-   * Output: \verbinclude MatrixBase_replicate_int_int.out
-   *
-   * \sa VectorwiseOp::replicate(), DenseBase::replicate<int,int>(), class Replicate
-   */
-  // Code moved here due to a CUDA compiler bug
-  EIGEN_DEVICE_FUNC const Replicate<Derived, Dynamic, Dynamic> replicate(Index rowFactor, Index colFactor) const {
-    return Replicate<Derived, Dynamic, Dynamic>(derived(), rowFactor, colFactor);
-  }
-
-  typedef Reverse<Derived, BothDirections> ReverseReturnType;
-  typedef const Reverse<const Derived, BothDirections> ConstReverseReturnType;
-  EIGEN_DEVICE_FUNC ReverseReturnType reverse();
-  /** This is the const version of reverse(). */
-  // Code moved here due to a CUDA compiler bug
-  EIGEN_DEVICE_FUNC ConstReverseReturnType reverse() const { return ConstReverseReturnType(derived()); }
-  EIGEN_DEVICE_FUNC void reverseInPlace();
-
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-  /** STL-like <a href="https://en.cppreference.com/w/cpp/named_req/RandomAccessIterator">RandomAccessIterator</a>
-   * iterator type as returned by the begin() and end() methods.
-   */
-  typedef random_access_iterator_type iterator;
-  /** This is the const version of iterator (aka read-only) */
-  typedef random_access_iterator_type const_iterator;
-#else
-  typedef std::conditional_t<(Flags & DirectAccessBit) == DirectAccessBit,
-                             internal::pointer_based_stl_iterator<Derived>,
-                             internal::generic_randaccess_stl_iterator<Derived> >
-      iterator_type;
-
-  typedef std::conditional_t<(Flags & DirectAccessBit) == DirectAccessBit,
-                             internal::pointer_based_stl_iterator<const Derived>,
-                             internal::generic_randaccess_stl_iterator<const Derived> >
-      const_iterator_type;
-
-  // Stl-style iterators are supported only for vectors.
-
-  typedef std::conditional_t<IsVectorAtCompileTime, iterator_type, void> iterator;
-
-  typedef std::conditional_t<IsVectorAtCompileTime, const_iterator_type, void> const_iterator;
-#endif
-
-  inline iterator begin();
-  inline const_iterator begin() const;
-  inline const_iterator cbegin() const;
-  inline iterator end();
-  inline const_iterator end() const;
-  inline const_iterator cend() const;
-
-  using RealViewReturnType = std::conditional_t<NumTraits<Scalar>::IsComplex, RealView<Derived>, Derived&>;
-  using ConstRealViewReturnType =
-      std::conditional_t<NumTraits<Scalar>::IsComplex, RealView<const Derived>, const Derived&>;
-
-  EIGEN_DEVICE_FUNC RealViewReturnType realView();
-  EIGEN_DEVICE_FUNC ConstRealViewReturnType realView() const;
-
-#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase
-#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
-#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND)
-#define EIGEN_DOC_UNARY_ADDONS(X, Y)
-#include "../plugins/CommonCwiseUnaryOps.inc"
-#include "../plugins/BlockMethods.inc"
-#include "../plugins/IndexedViewMethods.inc"
-#include "../plugins/ReshapedMethods.inc"
-#ifdef EIGEN_DENSEBASE_PLUGIN
-#include EIGEN_DENSEBASE_PLUGIN
-#endif
-#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
-#undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL
-#undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF
-#undef EIGEN_DOC_UNARY_ADDONS
-
-  // disable the use of evalTo for dense objects with a nice compilation error
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC 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:
-  EIGEN_DEFAULT_COPY_CONSTRUCTOR(DenseBase)
-  /** Default constructor. Do nothing. */
-#ifdef EIGEN_INTERNAL_DEBUGGING
-  EIGEN_DEVICE_FUNC constexpr DenseBase() {
-    /* Just checks for self-consistency of the flags.
-     * Only do it when debugging Eigen, as this borders on paranoia and could slow compilation down
-     */
-    EIGEN_STATIC_ASSERT(
-        (internal::check_implication(MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1, int(IsRowMajor)) &&
-         internal::check_implication(MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1, int(!IsRowMajor))),
-        INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION)
-  }
-#else
-  EIGEN_DEVICE_FUNC constexpr DenseBase() = default;
-#endif
-
- private:
-  EIGEN_DEVICE_FUNC explicit DenseBase(int);
-  EIGEN_DEVICE_FUNC DenseBase(int, int);
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC explicit DenseBase(const DenseBase<OtherDerived>&);
-};
-
-/** Free-function swap.
- */
-template <typename DerivedA, typename DerivedB>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    // Use forwarding references to capture all combinations of cv-qualified l+r-value cases.
-    std::enable_if_t<std::is_base_of<DenseBase<std::decay_t<DerivedA>>, std::decay_t<DerivedA>>::value &&
-                         std::is_base_of<DenseBase<std::decay_t<DerivedB>>, std::decay_t<DerivedB>>::value,
-                     void>
-    swap(DerivedA&& a, DerivedB&& b) {
-  a.swap(b);
-}
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_DENSEBASE_H