ADD: added other eigen lib

libs/eigen/.clang-format

@@ -0,0 +1,12 @@
+---
+Language:     Cpp
+BasedOnStyle: Google
+ColumnLimit:  120
+SortIncludes: false
+AttributeMacros:
+- EIGEN_STRONG_INLINE
+- EIGEN_ALWAYS_INLINE
+- EIGEN_DEVICE_FUNC
+- EIGEN_DONT_INLINE
+- EIGEN_DEPRECATED
+- EIGEN_UNUSED

libs/eigen/CMakeLists.txt

@@ -1,8 +1,35 @@
 # cmake_minimum_require must be the first command of the file
-cmake_minimum_required(VERSION 3.5.0)
+cmake_minimum_required(VERSION 3.10.0)
+
+# 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)
 
 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 TRUE)
+  else()
+    set(PROJECT_IS_TOP_LEVEL FALSE)
+  endif()
+endif()
+
+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")
+
 # guard against in-source builds
 
 if(${CMAKE_SOURCE_DIR} STREQUAL ${CMAKE_BINARY_DIR})
@@ -61,10 +88,6 @@ include(CMakeDependentOption)
 
 set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
 
-
-option(EIGEN_TEST_CXX11 "Enable testing with C++11 and C++11 features (e.g. Tensor module)." OFF)
-
-
 macro(ei_add_cxx_compiler_flag FLAG)
   string(REGEX REPLACE "-" "" SFLAG1 ${FLAG})
   string(REGEX REPLACE "\\+" "p" SFLAG ${SFLAG1})
@@ -74,20 +97,6 @@ macro(ei_add_cxx_compiler_flag FLAG)
   endif()
 endmacro()
 
-check_cxx_compiler_flag("-std=c++11" EIGEN_COMPILER_SUPPORT_CPP11)
-
-if(EIGEN_TEST_CXX11)
-  set(CMAKE_CXX_STANDARD 11)
-  set(CMAKE_CXX_EXTENSIONS OFF)
-  if(EIGEN_COMPILER_SUPPORT_CPP11)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c++11")
-  endif()
-else()
-  #set(CMAKE_CXX_STANDARD 03)
-  #set(CMAKE_CXX_EXTENSIONS OFF)
-  ei_add_cxx_compiler_flag("-std=c++03")
-endif()
-
 # Determine if we should build shared libraries on this platform.
 get_cmake_property(EIGEN_BUILD_SHARED_LIBS TARGET_SUPPORTS_SHARED_LIBS)
 
@@ -100,6 +109,8 @@ find_package(StandardMathLibrary)
 
 set(EIGEN_TEST_CUSTOM_LINKER_FLAGS  "" CACHE STRING "Additional linker flags when linking unit tests.")
 set(EIGEN_TEST_CUSTOM_CXX_FLAGS     "" CACHE STRING "Additional compiler flags when compiling unit tests.")
+# convert space separated argument into CMake lists for downstream consumption
+separate_arguments(EIGEN_TEST_CUSTOM_CXX_FLAGS NATIVE_COMMAND ${EIGEN_TEST_CUSTOM_CXX_FLAGS})
 
 set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "")
 
@@ -109,13 +120,11 @@ if(NOT STANDARD_MATH_LIBRARY_FOUND)
     "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)
@@ -125,6 +134,7 @@ else()
 endif()
 
 option(EIGEN_BUILD_BTL "Build benchmark suite" OFF)
+option(EIGEN_BUILD_SPBENCH "Build sparse benchmark suite" OFF)
 
 # Disable pkgconfig only for native Windows builds
 if(NOT WIN32 OR NOT CMAKE_HOST_SYSTEM_NAME MATCHES Windows)
@@ -183,18 +193,6 @@ if(NOT MSVC)
   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
 
-
-  # The -ansi flag must be added last, otherwise it is also used as a linker flag by check_cxx_compiler_flag making it fails
-  # Moreover we should not set both -strict-ansi and -ansi
-  check_cxx_compiler_flag("-strict-ansi" COMPILER_SUPPORT_STRICTANSI)
-  ei_add_cxx_compiler_flag("-Qunused-arguments")        # disable clang warning: argument unused during compilation: '-ansi'
-
-  if(COMPILER_SUPPORT_STRICTANSI)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -strict-ansi")
-  else()
-    ei_add_cxx_compiler_flag("-ansi")
-  endif()
-
   if(ANDROID_NDK)
     ei_add_cxx_compiler_flag("-pie")
     ei_add_cxx_compiler_flag("-fPIE")
@@ -253,21 +251,21 @@ if(NOT MSVC)
   option(EIGEN_TEST_AVX512 "Enable/Disable AVX512 in tests/examples" OFF)
   if(EIGEN_TEST_AVX512)
     set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx512f -mfma")
-    if (NOT "${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fabi-version=6")
-    endif()
     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 "${CMAKE_CXX_FLAGS} -mavx512dq")
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mavx512dq -mfma")
-    if (NOT "${CMAKE_CXX_COMPILER_ID}" STREQUAL "Clang")
-      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fabi-version=6")
-    endif()
     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")
@@ -369,11 +367,19 @@ else()
   endif()
 
   option(EIGEN_TEST_FMA "Enable/Disable FMA/AVX2 in tests/examples" OFF)
-  if(EIGEN_TEST_FMA AND NOT EIGEN_TEST_NEON)
+  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()
 
 option(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION "Disable explicit vectorization in tests/examples" OFF)
@@ -416,7 +422,8 @@ if(EIGEN_TEST_NO_EXCEPTIONS)
   message(STATUS "Disabling exceptions in tests/examples")
 endif()
 
-set(EIGEN_CUDA_COMPUTE_ARCH 30 CACHE STRING "The CUDA compute architecture level to target when compiling CUDA code")
+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")
 
 include_directories(${CMAKE_CURRENT_SOURCE_DIR})
 
@@ -450,17 +457,6 @@ foreach(var INCLUDE_INSTALL_DIR CMAKEPACKAGE_INSTALL_DIR PKGCONFIG_INSTALL_DIR)
   endif()
 endforeach()
 
-# similar to set_target_properties but append the property instead of overwriting it
-macro(ei_add_target_property target prop value)
-
-  get_target_property(previous ${target} ${prop})
-  # if the property wasn't previously set, ${previous} is now "previous-NOTFOUND" which cmake allows catching with plain if()
-  if(NOT previous)
-    set(previous "")
-  endif()
-  set_target_properties(${target} PROPERTIES ${prop} "${previous} ${value}")
-endmacro()
-
 install(FILES
   signature_of_eigen3_matrix_library
   DESTINATION ${INCLUDE_INSTALL_DIR} COMPONENT Devel
@@ -482,8 +478,9 @@ if(EIGEN_BUILD_DOC)
 endif()
 
 
-option(BUILD_TESTING "Enable creation of Eigen tests." ON)
+cmake_dependent_option(BUILD_TESTING "Enable creation of tests." ON "PROJECT_IS_TOP_LEVEL" OFF)
-if(BUILD_TESTING)
+option(EIGEN_BUILD_TESTING "Enable creation of Eigen tests." ${BUILD_TESTING})
+if(EIGEN_BUILD_TESTING)
   include(EigenConfigureTesting)
 
   if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
@@ -495,6 +492,9 @@ if(BUILD_TESTING)
   add_subdirectory(failtest)
 endif()
 
+include(CMakeDetermineFortranCompiler)
+option(EIGEN_BUILD_BLAS "Toggles the building of the Eigen Blas library" ${CMAKE_Fortran_COMPILER})
+option(EIGEN_BUILD_LAPACK "Toggles the building of the included Eigen LAPACK library" ${CMAKE_Fortran_COMPILER})
 if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
   add_subdirectory(blas)
   add_subdirectory(lapack)
@@ -545,13 +545,30 @@ if(EIGEN_BUILD_BTL)
   add_subdirectory(bench/btl EXCLUDE_FROM_ALL)
 endif()
 
-if(NOT WIN32)
+find_package(CLANG_FORMAT 9 EXACT)
+if(CLANG_FORMAT_FOUND)
+set(FORMAT_SOURCES)
+list(APPEND FORMAT_SUBDIRS blas bench demos "doc" Eigen include lapack scripts share unsupported test failtest)
+foreach(DIR ${FORMAT_SUBDIRS})
+    set(ABS_DIR ${CMAKE_CURRENT_SOURCE_DIR}/${DIR})
+    file(GLOB_RECURSE ${DIR}_SOURCES ${ABS_DIR}/*.cc ${ABS_DIR}/*.h ${ABS_DIR}/*.cpp ${ABS_DIR}/*.hpp ${ABS_DIR}/*.c)
+    list(APPEND FORMAT_SOURCES ${${DIR}_SOURCES})
+  endforeach()
+    file(GLOB FORMAT_SOURCES_WITHOUTENDING LIST_DIRECTORIES false ${CMAKE_CURRENT_SOURCE_DIR}/Eigen/* ${CMAKE_CURRENT_SOURCE_DIR}/Eigen/CXX11/* ${CMAKE_CURRENT_SOURCE_DIR}/unsupported/Eigen/* ${CMAKE_CURRENT_SOURCE_DIR}/unsupported/Eigen/CXX11/*)
+    list(FILTER FORMAT_SOURCES_WITHOUTENDING EXCLUDE REGEX ".*.txt$")
+    list (APPEND FORMAT_SOURCES ${FORMAT_SOURCES_WITHOUTENDING})
+    add_custom_target(format
+    COMMAND ${CLANG_FORMAT_EXECUTABLE} -i -style=file ${FORMAT_SOURCES}
+    DEPENDS ${FORMAT_SOURCES})
+endif()
+
+if(NOT WIN32 AND EIGEN_BUILD_SPBENCH)
   add_subdirectory(bench/spbench EXCLUDE_FROM_ALL)
 endif()
 
 configure_file(scripts/cdashtesting.cmake.in cdashtesting.cmake @ONLY)
 
-if(BUILD_TESTING)
+if(EIGEN_BUILD_TESTING)
   ei_testing_print_summary()
 endif()
 
@@ -559,6 +576,7 @@ message(STATUS "")
 message(STATUS "Configured Eigen ${EIGEN_VERSION_NUMBER}")
 message(STATUS "")
 
+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):")
@@ -578,30 +596,29 @@ message(STATUS "         |     cmake . -DCMAKE_INSTALL_PREFIX=yourprefix")
   message(STATUS "         |   Or:")
   message(STATUS "         |     cmake . -DINCLUDE_INSTALL_DIR=yourdir")
   message(STATUS "doc      | Generate the API documentation, requires Doxygen & LaTeX")
-if(BUILD_TESTING)
+  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(CLANG_FORMAT_FOUND)
+    message(STATUS "format   | Formats the source code according to .clang-format file")
+  endif()
   message(STATUS "blas     | Build BLAS library (not the same thing as Eigen)")
   message(STATUS "uninstall| Remove files installed by the install target")
   message(STATUS "---------+--------------------------------------------------------------")
   message(STATUS "")
-
+endif()
 
 set ( EIGEN_VERSION_STRING ${EIGEN_VERSION_NUMBER} )
 set ( EIGEN_VERSION_MAJOR  ${EIGEN_WORLD_VERSION} )
 set ( EIGEN_VERSION_MINOR  ${EIGEN_MAJOR_VERSION} )
 set ( EIGEN_VERSION_PATCH  ${EIGEN_MINOR_VERSION} )
-set ( EIGEN_DEFINITIONS "")
-set ( EIGEN_INCLUDE_DIR "${CMAKE_INSTALL_PREFIX}/${INCLUDE_INSTALL_DIR}" )
-set ( EIGEN_ROOT_DIR ${CMAKE_INSTALL_PREFIX} )
 
 include (CMakePackageConfigHelpers)
 
 # Imported target support
 add_library (eigen INTERFACE)
 add_library (Eigen3::Eigen ALIAS eigen)
-target_compile_definitions (eigen INTERFACE ${EIGEN_DEFINITIONS})
 target_include_directories (eigen INTERFACE
   $<BUILD_INTERFACE:${CMAKE_CURRENT_SOURCE_DIR}>
   $<INSTALL_INTERFACE:${INCLUDE_INSTALL_DIR}>
@@ -612,13 +629,19 @@ set_target_properties (eigen PROPERTIES EXPORT_NAME Eigen)
 
 install (TARGETS eigen EXPORT Eigen3Targets)
 
+option(EIGEN_BUILD_CMAKE_PACKAGE "Enables the creation of EigenConfig.cmake and related files" ON)
+if(EIGEN_BUILD_CMAKE_PACKAGE)
 configure_package_config_file (
   ${CMAKE_CURRENT_SOURCE_DIR}/cmake/Eigen3Config.cmake.in
   ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
-  PATH_VARS EIGEN_INCLUDE_DIR EIGEN_ROOT_DIR
   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
 )
+
+# NOTE Remove the first code path once the minimum required CMake version is
+# bumped to 3.14 or above.
+if (CMAKE_VERSION VERSION_LESS 3.14)
   # Remove CMAKE_SIZEOF_VOID_P from Eigen3ConfigVersion.cmake since Eigen does
   # not depend on architecture specific settings or libraries. More
   # specifically, an Eigen3Config.cmake generated from a 64 bit target can be
@@ -629,6 +652,12 @@ write_basic_package_version_file (Eigen3ConfigVersion.cmake
                                     VERSION ${EIGEN_VERSION_NUMBER}
                                     COMPATIBILITY SameMajorVersion)
   set (CMAKE_SIZEOF_VOID_P ${_Eigen3_CMAKE_SIZEOF_VOID_P})
+else (CMAKE_VERSION VERSION_LESS 3.14)
+  write_basic_package_version_file (Eigen3ConfigVersion.cmake
+                                    VERSION ${EIGEN_VERSION_NUMBER}
+                                    COMPATIBILITY SameMajorVersion
+                                    ARCH_INDEPENDENT)
+endif (CMAKE_VERSION VERSION_LESS 3.14)
 
 # The Eigen target will be located in the Eigen3 namespace. Other CMake
 # targets can refer to it using Eigen3::Eigen.
@@ -639,14 +668,16 @@ export (PACKAGE Eigen3)
 
 install (EXPORT Eigen3Targets NAMESPACE Eigen3:: DESTINATION ${CMAKEPACKAGE_INSTALL_DIR})
 
-install ( FILES ${CMAKE_CURRENT_SOURCE_DIR}/cmake/UseEigen3.cmake
+install (FILES ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
-                ${CMAKE_CURRENT_BINARY_DIR}/Eigen3Config.cmake
                ${CMAKE_CURRENT_BINARY_DIR}/Eigen3ConfigVersion.cmake
          DESTINATION ${CMAKEPACKAGE_INSTALL_DIR})
 
 # Add uninstall target
+if(NOT TARGET uninstall)
   add_custom_target ( uninstall
       COMMAND ${CMAKE_COMMAND} -P ${CMAKE_CURRENT_SOURCE_DIR}/cmake/EigenUninstall.cmake)
+endif()
+endif()
 
 if (EIGEN_SPLIT_TESTSUITE)
   ei_split_testsuite("${EIGEN_SPLIT_TESTSUITE}")

libs/eigen/COPYING.GPL

@@ -1,674 +0,0 @@
-                    GNU 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.
-
-                            Preamble
-
-  The GNU General Public License is a free, copyleft license for
-software and other kinds of works.
-
-  The licenses for most software and other practical works are designed
-to take away your freedom to share and change the works.  By contrast,
-the GNU General Public License is intended to guarantee your freedom to
-share and change all versions of a program--to make sure it remains free
-software for all its users.  We, the Free Software Foundation, use the
-GNU General Public License for most of our software; it applies also to
-any other work released this way by its authors.  You can apply it to
-your programs, too.
-
-  When we speak of free software, we are referring to freedom, not
-price.  Our General Public Licenses are designed to make sure that you
-have the freedom to distribute copies of free software (and charge for
-them if you wish), that you receive source code or can get it if you
-want it, that you can change the software or use pieces of it in new
-free programs, and that you know you can do these things.
-
-  To protect your rights, we need to prevent others from denying you
-these rights or asking you to surrender the rights.  Therefore, you have
-certain responsibilities if you distribute copies of the software, or if
-you modify it: responsibilities to respect the freedom of others.
-
-  For example, if you distribute copies of such a program, whether
-gratis or for a fee, you must pass on to the recipients the same
-freedoms that you received.  You must make sure that they, too, receive
-or can get the source code.  And you must show them these terms so they
-know their rights.
-
-  Developers that use the GNU GPL protect your rights with two steps:
-(1) assert copyright on the software, and (2) offer you this License
-giving you legal permission to copy, distribute and/or modify it.
-
-  For the developers' and authors' protection, the GPL clearly explains
-that there is no warranty for this free software.  For both users' and
-authors' sake, the GPL requires that modified versions be marked as
-changed, so that their problems will not be attributed erroneously to
-authors of previous versions.
-
-  Some devices are designed to deny users access to install or run
-modified versions of the software inside them, although the manufacturer
-can do so.  This is fundamentally incompatible with the aim of
-protecting users' freedom to change the software.  The systematic
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-States should not allow patents to restrict development and use of
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-avoid the special danger that patents applied to a free program could
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-patents cannot be used to render the program non-free.
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-modification follow.
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libs/eigen/COPYING.MPL2

@@ -357,7 +357,7 @@ Exhibit A - Source Code Form License Notice
 
   This Source Code Form is subject to the terms of the Mozilla Public
   License, v. 2.0. If a copy of the MPL was not distributed with this
-  file, You can obtain one at http://mozilla.org/MPL/2.0/.
+  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

libs/eigen/Eigen/AccelerateSupport

@@ -0,0 +1,50 @@
+// 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
+  */
+
+#include "src/AccelerateSupport/AccelerateSupport.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_ACCELERATESUPPORT_MODULE_H

libs/eigen/Eigen/Cholesky

@@ -32,11 +32,7 @@
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
 #ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
+#include "src/misc/lapacke_helpers.h"
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
 #include "src/Cholesky/LLT_LAPACKE.h"
 #endif
 

libs/eigen/Eigen/CholmodSupport

@@ -22,7 +22,7 @@ extern "C" {
   * 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 CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
+  * - 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

libs/eigen/Eigen/Core

@@ -8,8 +8,8 @@
 // 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
+#ifndef EIGEN_CORE_MODULE_H
-#define EIGEN_CORE_H
+#define EIGEN_CORE_MODULE_H
 
 // first thing Eigen does: stop the compiler from reporting useless warnings.
 #include "src/Core/util/DisableStupidWarnings.h"
@@ -36,7 +36,7 @@
 
 // Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3)
 // See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
-#if EIGEN_COMP_MINGW && EIGEN_GNUC_AT_LEAST(4,6) && EIGEN_GNUC_AT_MOST(5,5)
+#if EIGEN_COMP_MINGW && EIGEN_GNUC_AT_MOST(5,5)
   #pragma GCC optimize ("-fno-ipa-cp-clone")
 #endif
 
@@ -67,6 +67,7 @@
 #endif
 
 #ifdef EIGEN_HAS_OPENMP
+#include <atomic>
 #include <omp.h>
 #endif
 
@@ -83,8 +84,8 @@
 #include <cmath>
 #include <cassert>
 #include <functional>
-#include <sstream>
 #ifndef EIGEN_NO_IO
+  #include <sstream>
   #include <iosfwd>
 #endif
 #include <cstring>
@@ -94,14 +95,10 @@
 // for min/max:
 #include <algorithm>
 
-#if EIGEN_HAS_CXX11
 #include <array>
-#endif
 
 // for std::is_nothrow_move_assignable
-#ifdef EIGEN_INCLUDE_TYPE_TRAITS
 #include <type_traits>
-#endif
 
 // for outputting debug info
 #ifdef EIGEN_DEBUG_ASSIGN
@@ -109,7 +106,8 @@
 #endif
 
 // required for __cpuid, needs to be included after cmath
-#if EIGEN_COMP_MSVC && EIGEN_ARCH_i386_OR_x86_64 && !EIGEN_OS_WINCE
+// 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
 
@@ -165,6 +163,7 @@ using std::ptrdiff_t;
 #include "src/Core/util/XprHelper.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/NumTraits.h"
@@ -179,6 +178,9 @@ using std::ptrdiff_t;
 #include "src/Core/arch/Default/GenericPacketMathFunctionsFwd.h"
 
 #if defined EIGEN_VECTORIZE_AVX512
+  #if defined EIGEN_VECTORIZE_AVX512FP16
+    #include "src/Core/arch/AVX512/PacketMathFP16.h"
+  #endif
   #include "src/Core/arch/SSE/PacketMath.h"
   #include "src/Core/arch/SSE/TypeCasting.h"
   #include "src/Core/arch/SSE/Complex.h"
@@ -191,6 +193,7 @@ using std::ptrdiff_t;
   #include "src/Core/arch/SSE/MathFunctions.h"
   #include "src/Core/arch/AVX/MathFunctions.h"
   #include "src/Core/arch/AVX512/MathFunctions.h"
+  #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"
@@ -256,10 +259,14 @@ using std::ptrdiff_t;
 #include "src/Core/functors/StlFunctors.h"
 #include "src/Core/functors/AssignmentFunctors.h"
 
-// Specialized functors to enable the processing of complex numbers
+// Specialized functors for GPU.
-// on CUDA devices
+#ifdef EIGEN_GPUCC
-#ifdef EIGEN_CUDACC
+#include "src/Core/arch/GPU/Complex.h"
-#include "src/Core/arch/CUDA/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"
@@ -314,6 +321,7 @@ using std::ptrdiff_t;
 #include "src/Core/DiagonalMatrix.h"
 #include "src/Core/Diagonal.h"
 #include "src/Core/DiagonalProduct.h"
+#include "src/Core/SkewSymmetricMatrix3.h"
 #include "src/Core/Redux.h"
 #include "src/Core/Visitor.h"
 #include "src/Core/Fuzzy.h"
@@ -346,12 +354,16 @@ using std::ptrdiff_t;
 #include "src/Core/CoreIterators.h"
 #include "src/Core/ConditionEstimator.h"
 
-#if defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
+#if defined(EIGEN_VECTORIZE_VSX)
   #include "src/Core/arch/AltiVec/MatrixProduct.h"
 #elif defined EIGEN_VECTORIZE_NEON
   #include "src/Core/arch/NEON/GeneralBlockPanelKernel.h"
 #endif
 
+#if defined(EIGEN_VECTORIZE_AVX512)
+  #include "src/Core/arch/AVX512/GemmKernel.h"
+#endif
+
 #include "src/Core/BooleanRedux.h"
 #include "src/Core/Select.h"
 #include "src/Core/VectorwiseOp.h"
@@ -381,4 +393,4 @@ using std::ptrdiff_t;
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif // EIGEN_CORE_H
+#endif // EIGEN_CORE_MODULE_H

libs/eigen/Eigen/IterativeLinearSolvers

@@ -27,7 +27,7 @@
   *  - 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.
+  * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport, AccelerateSupport.
   *
     \code
     #include <Eigen/IterativeLinearSolvers>

libs/eigen/Eigen/LU

@@ -28,11 +28,7 @@
 #include "src/LU/FullPivLU.h"
 #include "src/LU/PartialPivLU.h"
 #ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
+#include "src/misc/lapacke_helpers.h"
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
 #include "src/LU/PartialPivLU_LAPACKE.h"
 #endif
 #include "src/LU/Determinant.h"

libs/eigen/Eigen/QR

@@ -36,11 +36,7 @@
 #include "src/QR/ColPivHouseholderQR.h"
 #include "src/QR/CompleteOrthogonalDecomposition.h"
 #ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
+#include "src/misc/lapacke_helpers.h"
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
 #include "src/QR/HouseholderQR_LAPACKE.h"
 #include "src/QR/ColPivHouseholderQR_LAPACKE.h"
 #endif

libs/eigen/Eigen/SPQRSupport

@@ -28,7 +28,7 @@
   *
   */
 
-#include "src/CholmodSupport/CholmodSupport.h"
+#include "Eigen/CholmodSupport"
 #include "src/SPQRSupport/SuiteSparseQRSupport.h"
 
 #endif

libs/eigen/Eigen/SVD

@@ -36,14 +36,17 @@
 #include "src/SVD/SVDBase.h"
 #include "src/SVD/JacobiSVD.h"
 #include "src/SVD/BDCSVD.h"
-#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
+#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
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 

libs/eigen/Eigen/SparseCore

@@ -41,7 +41,6 @@
 #include "src/SparseCore/SparseCompressedBase.h"
 #include "src/SparseCore/SparseMatrix.h"
 #include "src/SparseCore/SparseMap.h"
-#include "src/SparseCore/MappedSparseMatrix.h"
 #include "src/SparseCore/SparseVector.h"
 #include "src/SparseCore/SparseRef.h"
 #include "src/SparseCore/SparseCwiseUnaryOp.h"

libs/eigen/Eigen/src/AccelerateSupport/AccelerateSupport.h

@@ -0,0 +1,421 @@
+#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
+  * \class 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
+  * \class 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
+  * \class 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
+  * \class 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
+  * \class 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
+  * \class 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
+  * \class 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

libs/eigen/Eigen/src/AccelerateSupport/InternalHeaderCheck.h

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

libs/eigen/Eigen/src/Cholesky/InternalHeaderCheck.h

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

libs/eigen/Eigen/src/Cholesky/LDLT.h

@@ -13,11 +13,13 @@
 #ifndef EIGEN_LDLT_H
 #define EIGEN_LDLT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
-  template<typename _MatrixType, int _UpLo> struct traits<LDLT<_MatrixType, _UpLo> >
+  template<typename MatrixType_, int UpLo_> struct traits<LDLT<MatrixType_, UpLo_> >
-   : traits<_MatrixType>
+   : traits<MatrixType_>
   {
     typedef MatrixXpr XprKind;
     typedef SolverStorage StorageKind;
@@ -37,8 +39,8 @@ namespace internal {
   *
   * \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 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 decompositon: Lower (default) or Upper.
+  * \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
@@ -56,11 +58,11 @@ namespace internal {
   *
   * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt(), class LLT
   */
-template<typename _MatrixType, int _UpLo> class LDLT
+template<typename MatrixType_, int UpLo_> class LDLT
-        : public SolverBase<LDLT<_MatrixType, _UpLo> >
+        : public SolverBase<LDLT<MatrixType_, UpLo_> >
 {
   public:
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
     typedef SolverBase<LDLT> Base;
     friend class SolverBase<LDLT>;
 
@@ -68,7 +70,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
     enum {
       MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-      UpLo = _UpLo
+      UpLo = UpLo_
     };
     typedef Matrix<Scalar, RowsAtCompileTime, 1, 0, MaxRowsAtCompileTime, 1> TmpMatrixType;
 
@@ -244,7 +246,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
       * 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; };
+    const LDLT& adjoint() const { return *this; }
 
     EIGEN_DEVICE_FUNC inline EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_matrix.rows(); }
     EIGEN_DEVICE_FUNC inline EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_matrix.cols(); }
@@ -270,10 +272,7 @@ template<typename _MatrixType, int _UpLo> class LDLT
 
   protected:
 
-    static void check_template_parameters()
+    EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
-    {
-      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
-    }
 
     /** \internal
       * Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U.
@@ -441,7 +440,7 @@ template<> struct ldlt_inplace<Lower>
       // Update the terms of L
       Index rs = size-j-1;
       w.tail(rs) -= wj * mat.col(j).tail(rs);
-      if(gamma != 0)
+      if(!numext::is_exactly_zero(gamma))
         mat.col(j).tail(rs) += (sigma*numext::conj(wj)/gamma)*w.tail(rs);
     }
     return true;
@@ -494,12 +493,10 @@ template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
 
 /** Compute / recompute the LDLT decomposition A = L D L^* = U^* D U of \a matrix
   */
-template<typename MatrixType, int _UpLo>
+template<typename MatrixType, int UpLo_>
 template<typename InputType>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>& a)
+LDLT<MatrixType,UpLo_>& LDLT<MatrixType,UpLo_>::compute(const EigenBase<InputType>& a)
 {
-  check_template_parameters();
-
   eigen_assert(a.rows()==a.cols());
   const Index size = a.rows();
 
@@ -510,7 +507,7 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const EigenBase<InputTyp
   // TODO move this code to SelfAdjointView
   for (Index col = 0; col < size; ++col) {
     RealScalar abs_col_sum;
-    if (_UpLo == Lower)
+    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>();
@@ -534,9 +531,9 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const EigenBase<InputTyp
  * \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 MatrixType, int UpLo_>
 template<typename Derived>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w, const typename LDLT<MatrixType,_UpLo>::RealScalar& sigma)
+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();
@@ -562,16 +559,16 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Deri
 }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-template<typename _MatrixType, int _UpLo>
+template<typename MatrixType_, int UpLo_>
 template<typename RhsType, typename DstType>
-void LDLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
+void LDLT<MatrixType_,UpLo_>::_solve_impl(const RhsType &rhs, DstType &dst) const
 {
   _solve_impl_transposed<true>(rhs, dst);
 }
 
-template<typename _MatrixType,int _UpLo>
+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
+void LDLT<MatrixType_,UpLo_>::_solve_impl_transposed(const RhsType &rhs, DstType &dst) const
 {
   // dst = P b
   dst = m_transpositions * rhs;
@@ -624,9 +621,9 @@ void LDLT<_MatrixType,_UpLo>::_solve_impl_transposed(const RhsType &rhs, DstType
   *
   * \sa LDLT::solve(), MatrixBase::ldlt()
   */
-template<typename MatrixType,int _UpLo>
+template<typename MatrixType,int UpLo_>
 template<typename Derived>
-bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
+bool LDLT<MatrixType,UpLo_>::solveInPlace(MatrixBase<Derived> &bAndX) const
 {
   eigen_assert(m_isInitialized && "LDLT is not initialized.");
   eigen_assert(m_matrix.rows() == bAndX.rows());
@@ -639,8 +636,8 @@ bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
 /** \returns the matrix represented by the decomposition,
  * i.e., it returns the product: P^T L D L^* P.
  * This function is provided for debug purpose. */
-template<typename MatrixType, int _UpLo>
+template<typename MatrixType, int UpLo_>
-MatrixType LDLT<MatrixType,_UpLo>::reconstructedMatrix() const
+MatrixType LDLT<MatrixType,UpLo_>::reconstructedMatrix() const
 {
   eigen_assert(m_isInitialized && "LDLT is not initialized.");
   const Index size = m_matrix.rows();

libs/eigen/Eigen/src/Cholesky/LLT.h

@@ -10,12 +10,14 @@
 #ifndef EIGEN_LLT_H
 #define EIGEN_LLT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal{
 
-template<typename _MatrixType, int _UpLo> struct traits<LLT<_MatrixType, _UpLo> >
+template<typename MatrixType_, int UpLo_> struct traits<LLT<MatrixType_, UpLo_> >
- : traits<_MatrixType>
+ : traits<MatrixType_>
 {
   typedef MatrixXpr XprKind;
   typedef SolverStorage StorageKind;
@@ -32,8 +34,8 @@ template<typename MatrixType, int UpLo> struct LLT_Traits;
   *
   * \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 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 decompositon: Lower (default) or Upper.
+  * \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
@@ -58,16 +60,16 @@ template<typename MatrixType, int UpLo> struct LLT_Traits;
   *
   * 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.
+  * 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
+template<typename MatrixType_, int UpLo_> class LLT
-        : public SolverBase<LLT<_MatrixType, _UpLo> >
+        : public SolverBase<LLT<MatrixType_, UpLo_> >
 {
   public:
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
     typedef SolverBase<LLT> Base;
     friend class SolverBase<LLT>;
 
@@ -79,7 +81,7 @@ template<typename _MatrixType, int _UpLo> class LLT
     enum {
       PacketSize = internal::packet_traits<Scalar>::size,
       AlignmentMask = int(PacketSize)-1,
-      UpLo = _UpLo
+      UpLo = UpLo_
     };
 
     typedef internal::LLT_Traits<MatrixType,UpLo> Traits;
@@ -199,7 +201,7 @@ template<typename _MatrixType, int _UpLo> class LLT
       * 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 EIGEN_NOEXCEPT { return *this; };
+    const LLT& adjoint() const EIGEN_NOEXCEPT { return *this; }
 
     inline EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_matrix.rows(); }
     inline EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_matrix.cols(); }
@@ -217,10 +219,7 @@ template<typename _MatrixType, int _UpLo> class LLT
 
   protected:
 
-    static void check_template_parameters()
+    EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
-    {
-      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
-    }
 
     /** \internal
       * Used to compute and store L
@@ -243,7 +242,7 @@ static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
   typedef typename MatrixType::ColXpr ColXpr;
-  typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
+  typedef internal::remove_all_t<ColXpr> ColXprCleaned;
   typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
   typedef Matrix<Scalar,Dynamic,1> TempVectorType;
   typedef typename TempVectorType::SegmentReturnType TempVecSegment;
@@ -298,7 +297,7 @@ static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const
       if(rs)
       {
         temp.tail(rs) -= (wj/Ljj) * mat.col(j).tail(rs);
-        if(gamma != 0)
+        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);
       }
     }
@@ -427,12 +426,10 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
   * Example: \include TutorialLinAlgComputeTwice.cpp
   * Output: \verbinclude TutorialLinAlgComputeTwice.out
   */
-template<typename MatrixType, int _UpLo>
+template<typename MatrixType, int UpLo_>
 template<typename InputType>
-LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>& a)
+LLT<MatrixType,UpLo_>& LLT<MatrixType,UpLo_>::compute(const EigenBase<InputType>& a)
 {
-  check_template_parameters();
-
   eigen_assert(a.rows()==a.cols());
   const Index size = a.rows();
   m_matrix.resize(size, size);
@@ -444,7 +441,7 @@ LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>
   // TODO move this code to SelfAdjointView
   for (Index col = 0; col < size; ++col) {
     RealScalar abs_col_sum;
-    if (_UpLo == Lower)
+    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>();
@@ -464,9 +461,9 @@ LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const EigenBase<InputType>
   * 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 MatrixType_, int UpLo_>
 template<typename VectorType>
-LLT<_MatrixType,_UpLo> & LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma)
+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());
@@ -480,16 +477,16 @@ LLT<_MatrixType,_UpLo> & LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v,
 }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-template<typename _MatrixType,int _UpLo>
+template<typename MatrixType_,int UpLo_>
 template<typename RhsType, typename DstType>
-void LLT<_MatrixType,_UpLo>::_solve_impl(const RhsType &rhs, DstType &dst) const
+void LLT<MatrixType_,UpLo_>::_solve_impl(const RhsType &rhs, DstType &dst) const
 {
   _solve_impl_transposed<true>(rhs, dst);
 }
 
-template<typename _MatrixType,int _UpLo>
+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
+void LLT<MatrixType_,UpLo_>::_solve_impl_transposed(const RhsType &rhs, DstType &dst) const
 {
     dst = rhs;
 
@@ -511,9 +508,9 @@ void LLT<_MatrixType,_UpLo>::_solve_impl_transposed(const RhsType &rhs, DstType
   *
   * \sa LLT::solve(), MatrixBase::llt()
   */
-template<typename MatrixType, int _UpLo>
+template<typename MatrixType, int UpLo_>
 template<typename Derived>
-void LLT<MatrixType,_UpLo>::solveInPlace(const MatrixBase<Derived> &bAndX) const
+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());
@@ -524,8 +521,8 @@ void LLT<MatrixType,_UpLo>::solveInPlace(const MatrixBase<Derived> &bAndX) const
 /** \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>
+template<typename MatrixType, int UpLo_>
-MatrixType LLT<MatrixType,_UpLo>::reconstructedMatrix() const
+MatrixType LLT<MatrixType,UpLo_>::reconstructedMatrix() const
 {
   eigen_assert(m_isInitialized && "LLT is not initialized.");
   return matrixL() * matrixL().adjoint().toDenseMatrix();

libs/eigen/Eigen/src/Cholesky/LLT_LAPACKE.h

@@ -33,64 +33,86 @@
 #ifndef EIGEN_LLT_LAPACKE_H
 #define EIGEN_LLT_LAPACKE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
-template<typename Scalar> struct lapacke_llt;
+namespace lapacke_helpers {
+  // -------------------------------------------------------------------------------------------------------------------
+  //        Dispatch for rank update handling upper and lower parts
+  // -------------------------------------------------------------------------------------------------------------------
 
-#define EIGEN_LAPACKE_LLT(EIGTYPE, BLASTYPE, LAPACKE_PREFIX) \
+  template<UpLoType Mode>
-template<> struct lapacke_llt<EIGTYPE> \
+  struct rank_update {};
-{ \
+
-  template<typename MatrixType> \
+  template<>
-  static inline Index potrf(MatrixType& m, char uplo) \
+  struct rank_update<Lower> {
-  { \
+      template<typename MatrixType, typename VectorType>
-    lapack_int matrix_order; \
+      static Index run(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) {
-    lapack_int size, lda, info, StorageOrder; \
+        return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
-    EIGTYPE* a; \
+      }
-    eigen_assert(m.rows()==m.cols()); \
-    /* Set up parameters for ?potrf */ \
-    size = convert_index<lapack_int>(m.rows()); \
-    StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \
-    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
-    a = &(m.coeffRef(0,0)); \
-    lda = convert_index<lapack_int>(m.outerStride()); \
-\
-    info = LAPACKE_##LAPACKE_PREFIX##potrf( matrix_order, uplo, size, (BLASTYPE*)a, lda ); \
-    info = (info==0) ? -1 : info>0 ? info-1 : size; \
-    return info; \
-  } \
-}; \
-template<> struct llt_inplace<EIGTYPE, Lower> \
-{ \
-  template<typename MatrixType> \
-  static Index blocked(MatrixType& m) \
-  { \
-    return lapacke_llt<EIGTYPE>::potrf(m, 'L'); \
-  } \
-  template<typename MatrixType, typename VectorType> \
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
-  { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
-}; \
-template<> struct llt_inplace<EIGTYPE, Upper> \
-{ \
-  template<typename MatrixType> \
-  static Index blocked(MatrixType& m) \
-  { \
-    return lapacke_llt<EIGTYPE>::potrf(m, 'U'); \
-  } \
-  template<typename MatrixType, typename VectorType> \
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
-  { \
-    Transpose<MatrixType> matt(mat); \
-    return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \
-  } \
   };
 
-EIGEN_LAPACKE_LLT(double, double, d)
+  template<>
-EIGEN_LAPACKE_LLT(float, float, s)
+  struct rank_update<Upper> {
-EIGEN_LAPACKE_LLT(dcomplex, lapack_complex_double, z)
+      template<typename MatrixType, typename VectorType>
-EIGEN_LAPACKE_LLT(scomplex, lapack_complex_float, c)
+      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 {
+    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);
+      Scalar* a = &(m.coeffRef(0,0));
+      lapack_int lda = to_lapack(m.outerStride());
+
+      lapack_int info = potrf(matrix_order, translate_mode<Mode>, 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);
+    }
+  };
+}
+// 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
 

libs/eigen/Eigen/src/CholmodSupport/CholmodSupport.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_CHOLMODSUPPORT_H
 #define EIGEN_CHOLMODSUPPORT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -54,8 +56,8 @@ template<> struct cholmod_configure_matrix<std::complex<double> > {
 /** 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>
+template<typename Scalar_, int Options_, typename StorageIndex_>
-cholmod_sparse viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_StorageIndex> > mat)
+cholmod_sparse viewAsCholmod(Ref<SparseMatrix<Scalar_,Options_,StorageIndex_> > mat)
 {
   cholmod_sparse res;
   res.nzmax   = mat.nonZeros();
@@ -80,11 +82,11 @@ cholmod_sparse viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_StorageIndex> >
   res.dtype   = 0;
   res.stype   = -1;
 
-  if (internal::is_same<_StorageIndex,int>::value)
+  if (internal::is_same<StorageIndex_,int>::value)
   {
     res.itype = CHOLMOD_INT;
   }
-  else if (internal::is_same<_StorageIndex,SuiteSparse_long>::value)
+  else if (internal::is_same<StorageIndex_,SuiteSparse_long>::value)
   {
     res.itype = CHOLMOD_LONG;
   }
@@ -94,39 +96,39 @@ cholmod_sparse viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_StorageIndex> >
   }
 
   // setup res.xtype
-  internal::cholmod_configure_matrix<_Scalar>::run(res);
+  internal::cholmod_configure_matrix<Scalar_>::run(res);
 
   res.stype = 0;
 
   return res;
 }
 
-template<typename _Scalar, int _Options, typename _Index>
+template<typename Scalar_, int Options_, typename Index_>
-const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>& mat)
+const cholmod_sparse viewAsCholmod(const SparseMatrix<Scalar_,Options_,Index_>& mat)
 {
-  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.const_cast_derived()));
+  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<Scalar_,Options_,Index_> >(mat.const_cast_derived()));
   return res;
 }
 
-template<typename _Scalar, int _Options, typename _Index>
+template<typename Scalar_, int Options_, typename Index_>
-const cholmod_sparse viewAsCholmod(const SparseVector<_Scalar,_Options,_Index>& mat)
+const cholmod_sparse viewAsCholmod(const SparseVector<Scalar_,Options_,Index_>& mat)
 {
-  cholmod_sparse res = viewAsCholmod(Ref<SparseMatrix<_Scalar,_Options,_Index> >(mat.const_cast_derived()));
+  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>
+template<typename Scalar_, int Options_, typename Index_, unsigned int UpLo>
-cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<const SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
+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()));
+  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);
+  EIGEN_STATIC_ASSERT((Options_ & RowMajorBit) == 0 || NumTraits<Scalar_>::IsComplex == 0, THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
-  if(_Options & RowMajorBit) res.stype *=-1;
+  if(Options_ & RowMajorBit) res.stype *=-1;
 
   return res;
 }
@@ -155,9 +157,9 @@ cholmod_dense viewAsCholmod(MatrixBase<Derived>& mat)
 /** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
   * The data are not copied but shared. */
 template<typename Scalar, int Flags, typename StorageIndex>
-MappedSparseMatrix<Scalar,Flags,StorageIndex> viewAsEigen(cholmod_sparse& cm)
+Map<SparseMatrix<Scalar,Flags,StorageIndex> > viewAsEigen(cholmod_sparse& cm)
 {
-  return MappedSparseMatrix<Scalar,Flags,StorageIndex>
+  return Map<SparseMatrix<Scalar,Flags,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) );
 }
@@ -167,11 +169,11 @@ 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<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<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)
@@ -183,14 +185,14 @@ EIGEN_CHOLMOD_SPECIALIZE1(int, free_sparse, cholmod_sparse*, A)
 
 EIGEN_CHOLMOD_SPECIALIZE1(cholmod_factor*, analyze, cholmod_sparse, A)
 
-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<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<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>
+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); }
+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); }
 
@@ -210,7 +212,7 @@ enum CholmodMode {
   * \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>
+template<typename MatrixType_, int UpLo_, typename Derived>
 class CholmodBase : public SparseSolverBase<Derived>
 {
   protected:
@@ -218,8 +220,8 @@ class CholmodBase : public SparseSolverBase<Derived>
     using Base::derived;
     using Base::m_isInitialized;
   public:
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
-    enum { UpLo = _UpLo };
+    enum { UpLo = UpLo_ };
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
     typedef MatrixType CholMatrixType;
@@ -436,7 +438,7 @@ class CholmodBase : public SparseSolverBase<Derived>
       if (m_cholmodFactor->is_ll)
         logDet *= 2.0;
       return logDet;
-    };
+    }
 
     template<typename Stream>
     void dumpMemory(Stream& /*s*/)
@@ -461,8 +463,8 @@ class CholmodBase : public SparseSolverBase<Derived>
   * 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 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
+  * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
   *
   * \implsparsesolverconcept
@@ -473,15 +475,15 @@ class CholmodBase : public SparseSolverBase<Derived>
   *
   * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLLT
   */
-template<typename _MatrixType, int _UpLo = Lower>
+template<typename MatrixType_, int UpLo_ = Lower>
-class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> >
+class CholmodSimplicialLLT : public CholmodBase<MatrixType_, UpLo_, CholmodSimplicialLLT<MatrixType_, UpLo_> >
 {
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base;
+    typedef CholmodBase<MatrixType_, UpLo_, CholmodSimplicialLLT> Base;
     using Base::m_cholmod;
 
   public:
 
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
 
     CholmodSimplicialLLT() : Base() { init(); }
 
@@ -512,8 +514,8 @@ class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimpl
   * 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 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
+  * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
   *
   * \implsparsesolverconcept
@@ -524,15 +526,15 @@ class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimpl
   *
   * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLDLT
   */
-template<typename _MatrixType, int _UpLo = Lower>
+template<typename MatrixType_, int UpLo_ = Lower>
-class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> >
+class CholmodSimplicialLDLT : public CholmodBase<MatrixType_, UpLo_, CholmodSimplicialLDLT<MatrixType_, UpLo_> >
 {
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base;
+    typedef CholmodBase<MatrixType_, UpLo_, CholmodSimplicialLDLT> Base;
     using Base::m_cholmod;
 
   public:
 
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
 
     CholmodSimplicialLDLT() : Base() { init(); }
 
@@ -561,8 +563,8 @@ class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimp
   * 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 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
+  * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
   *
   * \implsparsesolverconcept
@@ -573,15 +575,15 @@ class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimp
   *
   * \sa \ref TutorialSparseSolverConcept
   */
-template<typename _MatrixType, int _UpLo = Lower>
+template<typename MatrixType_, int UpLo_ = Lower>
-class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> >
+class CholmodSupernodalLLT : public CholmodBase<MatrixType_, UpLo_, CholmodSupernodalLLT<MatrixType_, UpLo_> >
 {
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base;
+    typedef CholmodBase<MatrixType_, UpLo_, CholmodSupernodalLLT> Base;
     using Base::m_cholmod;
 
   public:
 
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
 
     CholmodSupernodalLLT() : Base() { init(); }
 
@@ -612,8 +614,8 @@ class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSuper
   * 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 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
+  * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower
   *               or Upper. Default is Lower.
   *
   * \implsparsesolverconcept
@@ -624,15 +626,15 @@ class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSuper
   *
   * \sa \ref TutorialSparseSolverConcept
   */
-template<typename _MatrixType, int _UpLo = Lower>
+template<typename MatrixType_, int UpLo_ = Lower>
-class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> >
+class CholmodDecomposition : public CholmodBase<MatrixType_, UpLo_, CholmodDecomposition<MatrixType_, UpLo_> >
 {
-    typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base;
+    typedef CholmodBase<MatrixType_, UpLo_, CholmodDecomposition> Base;
     using Base::m_cholmod;
 
   public:
 
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
 
     CholmodDecomposition() : Base() { init(); }
 

libs/eigen/Eigen/src/CholmodSupport/InternalHeaderCheck.h

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

libs/eigen/Eigen/src/Core/ArithmeticSequence.h

@@ -10,69 +10,18 @@
 #ifndef EIGEN_ARITHMETIC_SEQUENCE_H
 #define EIGEN_ARITHMETIC_SEQUENCE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
-#if (!EIGEN_HAS_CXX11) || !((!EIGEN_COMP_GNUC) || EIGEN_COMP_GNUC>=48)
-template<typename T> struct aseq_negate {};
-
-template<> struct aseq_negate<Index> {
-  typedef Index type;
-};
-
-template<int N> struct aseq_negate<FixedInt<N> > {
-  typedef FixedInt<-N> type;
-};
-
-// Compilation error in the following case:
-template<> struct aseq_negate<FixedInt<DynamicIndex> > {};
-
-template<typename FirstType,typename SizeType,typename IncrType,
-         bool FirstIsSymbolic=symbolic::is_symbolic<FirstType>::value,
-         bool SizeIsSymbolic =symbolic::is_symbolic<SizeType>::value>
-struct aseq_reverse_first_type {
-  typedef Index type;
-};
-
-template<typename FirstType,typename SizeType,typename IncrType>
-struct aseq_reverse_first_type<FirstType,SizeType,IncrType,true,true> {
-  typedef symbolic::AddExpr<FirstType,
-                            symbolic::ProductExpr<symbolic::AddExpr<SizeType,symbolic::ValueExpr<FixedInt<-1> > >,
-                                                  symbolic::ValueExpr<IncrType> >
-                           > type;
-};
-
-template<typename SizeType,typename IncrType,typename EnableIf = void>
-struct aseq_reverse_first_type_aux {
-  typedef Index type;
-};
-
-template<typename SizeType,typename IncrType>
-struct aseq_reverse_first_type_aux<SizeType,IncrType,typename internal::enable_if<bool((SizeType::value+IncrType::value)|0x1)>::type> {
-  typedef FixedInt<(SizeType::value-1)*IncrType::value> type;
-};
-
-template<typename FirstType,typename SizeType,typename IncrType>
-struct aseq_reverse_first_type<FirstType,SizeType,IncrType,true,false> {
-  typedef typename aseq_reverse_first_type_aux<SizeType,IncrType>::type Aux;
-  typedef symbolic::AddExpr<FirstType,symbolic::ValueExpr<Aux> > type;
-};
-
-template<typename FirstType,typename SizeType,typename IncrType>
-struct aseq_reverse_first_type<FirstType,SizeType,IncrType,false,true> {
-  typedef symbolic::AddExpr<symbolic::ProductExpr<symbolic::AddExpr<SizeType,symbolic::ValueExpr<FixedInt<-1> > >,
-                                                  symbolic::ValueExpr<IncrType> >,
-                            symbolic::ValueExpr<> > type;
-};
-#endif
-
 // 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)
@@ -137,21 +86,9 @@ protected:
   IncrType  m_incr;
 
 public:
-
-#if EIGEN_HAS_CXX11 && ((!EIGEN_COMP_GNUC) || EIGEN_COMP_GNUC>=48)
   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);
   }
-#else
-protected:
-  typedef typename internal::aseq_negate<IncrType>::type ReverseIncrType;
-  typedef typename internal::aseq_reverse_first_type<FirstType,SizeType,IncrType>::type ReverseFirstType;
-public:
-  ArithmeticSequence<ReverseFirstType,SizeType,ReverseIncrType>
-  reverse() const {
-    return seqN(m_first+(m_size+fix<-1>())*m_incr,m_size,-m_incr);
-  }
-#endif
 };
 
 /** \returns an ArithmeticSequence starting at \a first, of length \a size, and increment \a incr
@@ -200,7 +137,6 @@ auto seq(FirstType f, LastType l);
 
 #else // EIGEN_PARSED_BY_DOXYGEN
 
-#if EIGEN_HAS_CXX11
 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)
@@ -226,101 +162,11 @@ auto seq(FirstType f, LastType l, IncrType incr)
               CleanedIncrType(incr));
 }
 
-#else // EIGEN_HAS_CXX11
-
-template<typename FirstType,typename LastType>
-typename internal::enable_if<!(symbolic::is_symbolic<FirstType>::value || symbolic::is_symbolic<LastType>::value),
-                             ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,Index> >::type
-seq(FirstType f, LastType l)
-{
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-              Index((typename internal::cleanup_index_type<LastType>::type(l)-typename internal::cleanup_index_type<FirstType>::type(f)+fix<1>())));
-}
-
-template<typename FirstTypeDerived,typename LastType>
-typename internal::enable_if<!symbolic::is_symbolic<LastType>::value,
-    ArithmeticSequence<FirstTypeDerived, symbolic::AddExpr<symbolic::AddExpr<symbolic::NegateExpr<FirstTypeDerived>,symbolic::ValueExpr<> >,
-                                                            symbolic::ValueExpr<internal::FixedInt<1> > > > >::type
-seq(const symbolic::BaseExpr<FirstTypeDerived> &f, LastType l)
-{
-  return seqN(f.derived(),(typename internal::cleanup_index_type<LastType>::type(l)-f.derived()+fix<1>()));
-}
-
-template<typename FirstType,typename LastTypeDerived>
-typename internal::enable_if<!symbolic::is_symbolic<FirstType>::value,
-    ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                        symbolic::AddExpr<symbolic::AddExpr<LastTypeDerived,symbolic::ValueExpr<> >,
-                                          symbolic::ValueExpr<internal::FixedInt<1> > > > >::type
-seq(FirstType f, const symbolic::BaseExpr<LastTypeDerived> &l)
-{
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),(l.derived()-typename internal::cleanup_index_type<FirstType>::type(f)+fix<1>()));
-}
-
-template<typename FirstTypeDerived,typename LastTypeDerived>
-ArithmeticSequence<FirstTypeDerived,
-                    symbolic::AddExpr<symbolic::AddExpr<LastTypeDerived,symbolic::NegateExpr<FirstTypeDerived> >,symbolic::ValueExpr<internal::FixedInt<1> > > >
-seq(const symbolic::BaseExpr<FirstTypeDerived> &f, const symbolic::BaseExpr<LastTypeDerived> &l)
-{
-  return seqN(f.derived(),(l.derived()-f.derived()+fix<1>()));
-}
-
-
-template<typename FirstType,typename LastType, typename IncrType>
-typename internal::enable_if<!(symbolic::is_symbolic<FirstType>::value || symbolic::is_symbolic<LastType>::value),
-    ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,Index,typename internal::cleanup_seq_incr<IncrType>::type> >::type
-seq(FirstType f, LastType l, IncrType incr)
-{
-  typedef typename internal::cleanup_seq_incr<IncrType>::type CleanedIncrType;
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-              Index((typename internal::cleanup_index_type<LastType>::type(l)-typename internal::cleanup_index_type<FirstType>::type(f)+CleanedIncrType(incr))/CleanedIncrType(incr)), incr);
-}
-
-template<typename FirstTypeDerived,typename LastType, typename IncrType>
-typename internal::enable_if<!symbolic::is_symbolic<LastType>::value,
-    ArithmeticSequence<FirstTypeDerived,
-                        symbolic::QuotientExpr<symbolic::AddExpr<symbolic::AddExpr<symbolic::NegateExpr<FirstTypeDerived>,
-                                                                                   symbolic::ValueExpr<> >,
-                                                                 symbolic::ValueExpr<typename internal::cleanup_seq_incr<IncrType>::type> >,
-                                              symbolic::ValueExpr<typename internal::cleanup_seq_incr<IncrType>::type> >,
-                        typename internal::cleanup_seq_incr<IncrType>::type> >::type
-seq(const symbolic::BaseExpr<FirstTypeDerived> &f, LastType l, IncrType incr)
-{
-  typedef typename internal::cleanup_seq_incr<IncrType>::type CleanedIncrType;
-  return seqN(f.derived(),(typename internal::cleanup_index_type<LastType>::type(l)-f.derived()+CleanedIncrType(incr))/CleanedIncrType(incr), incr);
-}
-
-template<typename FirstType,typename LastTypeDerived, typename IncrType>
-typename internal::enable_if<!symbolic::is_symbolic<FirstType>::value,
-    ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                        symbolic::QuotientExpr<symbolic::AddExpr<symbolic::AddExpr<LastTypeDerived,symbolic::ValueExpr<> >,
-                                                                 symbolic::ValueExpr<typename internal::cleanup_seq_incr<IncrType>::type> >,
-                                               symbolic::ValueExpr<typename internal::cleanup_seq_incr<IncrType>::type> >,
-                        typename internal::cleanup_seq_incr<IncrType>::type> >::type
-seq(FirstType f, const symbolic::BaseExpr<LastTypeDerived> &l, IncrType incr)
-{
-  typedef typename internal::cleanup_seq_incr<IncrType>::type CleanedIncrType;
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-              (l.derived()-typename internal::cleanup_index_type<FirstType>::type(f)+CleanedIncrType(incr))/CleanedIncrType(incr), incr);
-}
-
-template<typename FirstTypeDerived,typename LastTypeDerived, typename IncrType>
-ArithmeticSequence<FirstTypeDerived,
-                    symbolic::QuotientExpr<symbolic::AddExpr<symbolic::AddExpr<LastTypeDerived,
-                                                                               symbolic::NegateExpr<FirstTypeDerived> >,
-                                                             symbolic::ValueExpr<typename internal::cleanup_seq_incr<IncrType>::type> >,
-                                          symbolic::ValueExpr<typename internal::cleanup_seq_incr<IncrType>::type> >,
-                    typename internal::cleanup_seq_incr<IncrType>::type>
-seq(const symbolic::BaseExpr<FirstTypeDerived> &f, const symbolic::BaseExpr<LastTypeDerived> &l, IncrType incr)
-{
-  typedef typename internal::cleanup_seq_incr<IncrType>::type CleanedIncrType;
-  return seqN(f.derived(),(l.derived()-f.derived()+CleanedIncrType(incr))/CleanedIncrType(incr), incr);
-}
-#endif // EIGEN_HAS_CXX11
 
 #endif // EIGEN_PARSED_BY_DOXYGEN
 
+namespace placeholders {
 
-#if EIGEN_HAS_CXX11 || defined(EIGEN_PARSED_BY_DOXYGEN)
 /** \cpp11
   * \returns a symbolic ArithmeticSequence representing the last \a size elements with increment \a incr.
   *
@@ -329,9 +175,9 @@ seq(const symbolic::BaseExpr<FirstTypeDerived> &f, const symbolic::BaseExpr<Last
   * \sa lastN(SizeType), seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) */
 template<typename SizeType,typename IncrType>
 auto lastN(SizeType size, IncrType incr)
--> decltype(seqN(Eigen::last-(size-fix<1>())*incr, size, incr))
+-> decltype(seqN(Eigen::placeholders::last-(size-fix<1>())*incr, size, incr))
 {
-  return seqN(Eigen::last-(size-fix<1>())*incr, size, incr);
+  return seqN(Eigen::placeholders::last-(size-fix<1>())*incr, size, incr);
 }
 
 /** \cpp11
@@ -342,18 +188,19 @@ auto lastN(SizeType size, IncrType incr)
   * \sa lastN(SizeType,IncrType, seqN(FirstType,SizeType), seq(FirstType,LastType) */
 template<typename SizeType>
 auto lastN(SizeType size)
--> decltype(seqN(Eigen::last+fix<1>()-size, size))
+-> decltype(seqN(Eigen::placeholders::last+fix<1>()-size, size))
 {
-  return seqN(Eigen::last+fix<1>()-size, size);
+  return seqN(Eigen::placeholders::last+fix<1>()-size, size);
 }
-#endif
+
+}  // namespace placeholders
 
 namespace internal {
 
 // Convert a symbolic span into a usable one (i.e., remove last/end "keywords")
 template<typename T>
 struct make_size_type {
-  typedef typename internal::conditional<symbolic::is_symbolic<T>::value, Index, T>::type type;
+  typedef std::conditional_t<symbolic::is_symbolic<T>::value, Index, T> type;
 };
 
 template<typename FirstType,typename SizeType,typename IncrType,int XprSize>
@@ -387,25 +234,23 @@ struct get_compile_time_incr<ArithmeticSequence<FirstType,SizeType,IncrType> > {
   * \code using namespace Eigen::indexing; \endcode
   * is equivalent to:
   * \code
-  using Eigen::all;
+  using Eigen::fix;
   using Eigen::seq;
   using Eigen::seqN;
-  using Eigen::lastN; // c++11 only
+  using Eigen::placeholders::all;
-  using Eigen::last;
+  using Eigen::placeholders::last;
-  using Eigen::lastp1;
+  using Eigen::placeholders::lastN;  // c++11 only
-  using Eigen::fix;
+  using Eigen::placeholders::lastp1;
   \endcode
   */
 namespace indexing {
-  using Eigen::all;
+  using Eigen::fix;
   using Eigen::seq;
   using Eigen::seqN;
-  #if EIGEN_HAS_CXX11
+  using Eigen::placeholders::all;
-  using Eigen::lastN;
+  using Eigen::placeholders::last;
-  #endif
+  using Eigen::placeholders::lastN;
-  using Eigen::last;
+  using Eigen::placeholders::lastp1;
-  using Eigen::lastp1;
-  using Eigen::fix;
 }
 
 } // end namespace Eigen

libs/eigen/Eigen/src/Core/Array.h

@@ -10,14 +10,16 @@
 #ifndef EIGEN_ARRAY_H
 #define EIGEN_ARRAY_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+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> >
+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;
+  typedef ArrayBase<Array<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> > XprBase;
 };
 }
 
@@ -41,16 +43,16 @@ struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : tra
   *
   * \sa \blank \ref TutorialArrayClass, \ref TopicClassHierarchy
   */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+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 PlainObjectBase<Array<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> >
 {
   public:
 
     typedef PlainObjectBase<Array> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Array)
 
-    enum { Options = _Options };
+    enum { Options = Options_ };
     typedef typename Base::PlainObject PlainObject;
 
   protected:
@@ -131,7 +133,6 @@ class Array
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array() : Base()
     {
-      Base::_check_template_params();
       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
@@ -142,17 +143,14 @@ class Array
     Array(internal::constructor_without_unaligned_array_assert)
       : Base(internal::constructor_without_unaligned_array_assert())
     {
-      Base::_check_template_params();
       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 #endif
 
-#if EIGEN_HAS_RVALUE_REFERENCES
     EIGEN_DEVICE_FUNC
     Array(Array&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_constructible<Scalar>::value)
       : Base(std::move(other))
     {
-      Base::_check_template_params();
     }
     EIGEN_DEVICE_FUNC
     Array& operator=(Array&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_assignable<Scalar>::value)
@@ -160,9 +158,7 @@ class Array
       Base::operator=(std::move(other));
       return *this;
     }
-#endif
 
-    #if EIGEN_HAS_CXX11
     /** \copydoc PlainObjectBase(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
      *
      * Example: \include Array_variadic_ctor_cxx11.cpp
@@ -197,16 +193,15 @@ class Array
       *
       * \sa  Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
       */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(
-    EIGEN_STRONG_INLINE Array(const std::initializer_list<std::initializer_list<Scalar>>& list) : Base(list) {}
+        const std::initializer_list<std::initializer_list<Scalar>>& list)
-    #endif // end EIGEN_HAS_CXX11
+        : Base(list) {}
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename T>
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE explicit Array(const T& x)
     {
-      Base::_check_template_params();
       Base::template _init1<T>(x);
     }
 
@@ -214,7 +209,6 @@ class Array
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
     {
-      Base::_check_template_params();
       this->template _init2<T0,T1>(val0, val1);
     }
 
@@ -249,7 +243,6 @@ class Array
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
     {
-      Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
       m_storage.data()[0] = val0;
       m_storage.data()[1] = val1;
@@ -261,7 +254,6 @@ class Array
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
     {
-      Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
       m_storage.data()[0] = val0;
       m_storage.data()[1] = val1;
@@ -283,8 +275,8 @@ class Array
     template<typename OtherDerived>
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other,
-                              typename internal::enable_if<internal::is_convertible<typename OtherDerived::Scalar,Scalar>::value,
+                              std::enable_if_t<internal::is_convertible<typename OtherDerived::Scalar,Scalar>::value,
-                                                           PrivateType>::type = PrivateType())
+                                               PrivateType> = PrivateType())
       : Base(other.derived())
     { }
 
@@ -359,8 +351,6 @@ EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
 #undef EIGEN_MAKE_ARRAY_TYPEDEFS
 #undef EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS
 
-#if EIGEN_HAS_CXX11
-
 #define EIGEN_MAKE_ARRAY_TYPEDEFS(Size, SizeSuffix)               \
 /** \ingroup arraytypedefs */                                     \
 /** \brief \cpp11 */                                              \
@@ -392,8 +382,6 @@ EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(4)
 #undef EIGEN_MAKE_ARRAY_TYPEDEFS
 #undef EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS
 
-#endif // EIGEN_HAS_CXX11
-
 #define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
 using Eigen::Matrix##SizeSuffix##TypeSuffix; \
 using Eigen::Vector##SizeSuffix##TypeSuffix; \

libs/eigen/Eigen/src/Core/ArrayBase.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_ARRAYBASE_H
 #define EIGEN_ARRAYBASE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 template<typename ExpressionType> class MatrixWrapper;
@@ -21,7 +23,7 @@ template<typename ExpressionType> class MatrixWrapper;
   *
   * An array is similar to a dense vector or matrix. While matrices are mathematical
   * objects with well defined linear algebra operators, an array is just a collection
-  * of scalar values arranged in a one or two dimensionnal fashion. As the main consequence,
+  * 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

libs/eigen/Eigen/src/Core/ArrayWrapper.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_ARRAYWRAPPER_H
 #define EIGEN_ARRAYWRAPPER_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class ArrayWrapper
@@ -26,12 +28,12 @@ namespace Eigen {
 namespace internal {
 template<typename ExpressionType>
 struct traits<ArrayWrapper<ExpressionType> >
-  : public traits<typename remove_all<typename ExpressionType::Nested>::type >
+  : public traits<remove_all_t<typename ExpressionType::Nested> >
 {
   typedef ArrayXpr XprKind;
   // Let's remove NestByRefBit
   enum {
-    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
     LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
     Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
   };
@@ -45,13 +47,13 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     typedef ArrayBase<ArrayWrapper> Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
-    typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
+    typedef internal::remove_all_t<ExpressionType> NestedExpression;
 
-    typedef typename internal::conditional<
+    typedef std::conditional_t<
                        internal::is_lvalue<ExpressionType>::value,
                        Scalar,
                        const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
+                     > ScalarWithConstIfNotLvalue;
 
     typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
 
@@ -91,7 +93,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     inline void evalTo(Dest& dst) const { dst = m_expression; }
 
     EIGEN_DEVICE_FUNC
-    const typename internal::remove_all<NestedExpressionType>::type&
+    const internal::remove_all_t<NestedExpressionType>&
     nestedExpression() const
     {
       return m_expression;
@@ -124,12 +126,12 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
 namespace internal {
 template<typename ExpressionType>
 struct traits<MatrixWrapper<ExpressionType> >
- : public traits<typename remove_all<typename ExpressionType::Nested>::type >
+ : public traits<remove_all_t<typename ExpressionType::Nested> >
 {
   typedef MatrixXpr XprKind;
   // Let's remove NestByRefBit
   enum {
-    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
     LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
     Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
   };
@@ -143,13 +145,13 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
-    typedef typename internal::remove_all<ExpressionType>::type NestedExpression;
+    typedef internal::remove_all_t<ExpressionType> NestedExpression;
 
-    typedef typename internal::conditional<
+    typedef std::conditional_t<
               internal::is_lvalue<ExpressionType>::value,
               Scalar,
               const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
+            > ScalarWithConstIfNotLvalue;
 
     typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
 
@@ -185,7 +187,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     }
 
     EIGEN_DEVICE_FUNC
-    const typename internal::remove_all<NestedExpressionType>::type&
+    const internal::remove_all_t<NestedExpressionType>&
     nestedExpression() const
     {
       return m_expression;

libs/eigen/Eigen/src/Core/Assign.h

@@ -12,6 +12,8 @@
 #ifndef EIGEN_ASSIGN_H
 #define EIGEN_ASSIGN_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 template<typename Derived>

libs/eigen/Eigen/src/Core/AssignEvaluator.h

@@ -12,6 +12,8 @@
 #ifndef EIGEN_ASSIGN_EVALUATOR_H
 #define EIGEN_ASSIGN_EVALUATOR_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 // This implementation is based on Assign.h
@@ -40,7 +42,7 @@ public:
     DstAlignment = DstEvaluator::Alignment,
     SrcAlignment = SrcEvaluator::Alignment,
     DstHasDirectAccess = (DstFlags & DirectAccessBit) == DirectAccessBit,
-    JointAlignment = EIGEN_PLAIN_ENUM_MIN(DstAlignment,SrcAlignment)
+    JointAlignment = plain_enum_min(DstAlignment, SrcAlignment)
   };
 
 private:
@@ -51,8 +53,8 @@ private:
     InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
               : int(DstFlags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
               : int(Dst::MaxRowsAtCompileTime),
-    RestrictedInnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(InnerSize,MaxPacketSize),
+    RestrictedInnerSize = min_size_prefer_fixed(InnerSize, MaxPacketSize),
-    RestrictedLinearSize = EIGEN_SIZE_MIN_PREFER_FIXED(Dst::SizeAtCompileTime,MaxPacketSize),
+    RestrictedLinearSize = min_size_prefer_fixed(Dst::SizeAtCompileTime, MaxPacketSize),
     OuterStride = int(outer_stride_at_compile_time<Dst>::ret),
     MaxSizeAtCompileTime = Dst::SizeAtCompileTime
   };
@@ -111,7 +113,7 @@ public:
               || int(Traversal) == SliceVectorizedTraversal
   };
 
-  typedef typename conditional<int(Traversal)==LinearVectorizedTraversal, LinearPacketType, InnerPacketType>::type PacketType;
+  typedef std::conditional_t<int(Traversal)==LinearVectorizedTraversal, LinearPacketType, InnerPacketType> PacketType;
 
 private:
   enum {
@@ -216,7 +218,7 @@ struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
 template<typename Kernel, int Stop>
 struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling<Kernel, Stop, Stop>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel&) { }
 };
 
 template<typename Kernel, int Index_, int Stop>
@@ -285,7 +287,7 @@ struct copy_using_evaluator_innervec_CompleteUnrolling
 template<typename Kernel, int Stop>
 struct copy_using_evaluator_innervec_CompleteUnrolling<Kernel, Stop, Stop>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&) { }
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel&) { }
 };
 
 template<typename Kernel, int Index_, int Stop, int SrcAlignment, int DstAlignment>
@@ -325,10 +327,9 @@ struct dense_assignment_loop;
 template<typename Kernel, int Unrolling>
 struct dense_assignment_loop<Kernel, AllAtOnceTraversal, Unrolling>
 {
-  EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE run(Kernel& /*kernel*/)
+  EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE EIGEN_CONSTEXPR run(Kernel& /*kernel*/)
   {
-    typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
+    EIGEN_STATIC_ASSERT(int(Kernel::DstEvaluatorType::XprType::SizeAtCompileTime) == 0,
-    EIGEN_STATIC_ASSERT(int(DstXprType::SizeAtCompileTime) == 0,
       EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT)
   }
 };
@@ -386,7 +387,7 @@ struct unaligned_dense_assignment_loop
 {
   // if IsAligned = true, then do nothing
   template <typename Kernel>
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel&, Index, Index) {}
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel&, Index, Index) {}
 };
 
 template <>
@@ -402,7 +403,7 @@ struct unaligned_dense_assignment_loop<false>
                                     Index end)
 #else
   template <typename Kernel>
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel,
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel,
                                       Index start,
                                       Index end)
 #endif
@@ -415,7 +416,7 @@ struct unaligned_dense_assignment_loop<false>
 template<typename Kernel>
 struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel)
   {
     const Index size = kernel.size();
     typedef typename Kernel::Scalar Scalar;
@@ -443,7 +444,7 @@ struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, NoUnrolling>
 template<typename Kernel>
 struct dense_assignment_loop<Kernel, LinearVectorizedTraversal, CompleteUnrolling>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel)
   {
     typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
     typedef typename Kernel::PacketType PacketType;
@@ -469,7 +470,7 @@ struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, NoUnrolling>
     SrcAlignment = Kernel::AssignmentTraits::SrcAlignment,
     DstAlignment = Kernel::AssignmentTraits::DstAlignment
   };
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel)
   {
     const Index innerSize = kernel.innerSize();
     const Index outerSize = kernel.outerSize();
@@ -511,7 +512,7 @@ struct dense_assignment_loop<Kernel, InnerVectorizedTraversal, InnerUnrolling>
 template<typename Kernel>
 struct dense_assignment_loop<Kernel, LinearTraversal, NoUnrolling>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel)
   {
     const Index size = kernel.size();
     for(Index i = 0; i < size; ++i)
@@ -522,7 +523,7 @@ struct dense_assignment_loop<Kernel, LinearTraversal, NoUnrolling>
 template<typename Kernel>
 struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel)
   {
     typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
     copy_using_evaluator_LinearTraversal_CompleteUnrolling<Kernel, 0, DstXprType::SizeAtCompileTime>::run(kernel);
@@ -536,7 +537,7 @@ struct dense_assignment_loop<Kernel, LinearTraversal, CompleteUnrolling>
 template<typename Kernel>
 struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel)
   {
     typedef typename Kernel::Scalar Scalar;
     typedef typename Kernel::PacketType PacketType;
@@ -584,7 +585,7 @@ struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, NoUnrolling>
 template<typename Kernel>
 struct dense_assignment_loop<Kernel, SliceVectorizedTraversal, InnerUnrolling>
 {
-  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel &kernel)
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void run(Kernel &kernel)
   {
     typedef typename Kernel::DstEvaluatorType::XprType DstXprType;
     typedef typename Kernel::PacketType PacketType;
@@ -766,7 +767,7 @@ void resize_if_allowed(DstXprType &dst, const SrcXprType& src, const internal::a
 }
 
 template<typename DstXprType, typename SrcXprType, typename Functor>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src, const Functor &func)
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src, const Functor &func)
 {
   typedef evaluator<DstXprType> DstEvaluatorType;
   typedef evaluator<SrcXprType> SrcEvaluatorType;
@@ -844,8 +845,8 @@ void call_assignment(const Dst& dst, const Src& src)
 
 // Deal with "assume-aliasing"
 template<typename Dst, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
-void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if< evaluator_assume_aliasing<Src>::value, void*>::type = 0)
+void call_assignment(Dst& dst, const Src& src, const Func& func, std::enable_if_t< evaluator_assume_aliasing<Src>::value, void*> = 0)
 {
   typename plain_matrix_type<Src>::type tmp(src);
   call_assignment_no_alias(dst, tmp, func);
@@ -853,7 +854,7 @@ void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable
 
 template<typename Dst, typename Src, typename Func>
 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable_if<!evaluator_assume_aliasing<Src>::value, void*>::type = 0)
+void call_assignment(Dst& dst, const Src& src, const Func& func, std::enable_if_t<!evaluator_assume_aliasing<Src>::value, void*> = 0)
 {
   call_assignment_no_alias(dst, src, func);
 }
@@ -861,7 +862,7 @@ void call_assignment(Dst& dst, const Src& src, const Func& func, typename enable
 // by-pass "assume-aliasing"
 // When there is no aliasing, we require that 'dst' has been properly resized
 template<typename Dst, template <typename> class StorageBase, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
 void call_assignment(NoAlias<Dst,StorageBase>& dst, const Src& src, const Func& func)
 {
   call_assignment_no_alias(dst.expression(), src, func);
@@ -869,7 +870,7 @@ void call_assignment(NoAlias<Dst,StorageBase>& dst, const Src& src, const Func&
 
 
 template<typename Dst, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
 void call_assignment_no_alias(Dst& dst, const Src& src, const Func& func)
 {
   enum {
@@ -878,8 +879,8 @@ void call_assignment_no_alias(Dst& dst, const Src& src, const Func& func)
                       ) && int(Dst::SizeAtCompileTime) != 1
   };
 
-  typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst>::type ActualDstTypeCleaned;
+  typedef std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst> ActualDstTypeCleaned;
-  typedef typename internal::conditional<NeedToTranspose, Transpose<Dst>, Dst&>::type ActualDstType;
+  typedef std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst&> ActualDstType;
   ActualDstType actualDst(dst);
 
   // TODO check whether this is the right place to perform these checks:
@@ -911,14 +912,14 @@ void call_restricted_packet_assignment_no_alias(Dst& dst, const Src& src, const
 }
 
 template<typename Dst, typename Src>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
 void call_assignment_no_alias(Dst& dst, const Src& src)
 {
   call_assignment_no_alias(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());
 }
 
 template<typename Dst, typename Src, typename Func>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
 void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src, const Func& func)
 {
   // TODO check whether this is the right place to perform these checks:
@@ -929,7 +930,7 @@ void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src, const Func&
   Assignment<Dst,Src,Func>::run(dst, src, func);
 }
 template<typename Dst, typename Src>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
 void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src)
 {
   call_assignment_no_alias_no_transpose(dst, src, internal::assign_op<typename Dst::Scalar,typename Src::Scalar>());

libs/eigen/Eigen/src/Core/Assign_MKL.h

@@ -34,6 +34,8 @@
 #ifndef EIGEN_ASSIGN_VML_H
 #define EIGEN_ASSIGN_VML_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
@@ -82,7 +84,7 @@ class vml_assign_traits
 #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, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> {              \
+                   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);                                                                                        \
@@ -142,7 +144,7 @@ EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil,  Ceil,   _)
   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, typename enable_if<vml_assign_traits<DstXprType,SrcXprNested>::EnableVml>::type> {            \
+                   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) {                     \

libs/eigen/Eigen/src/Core/BandMatrix.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_BANDMATRIX_H
 #define EIGEN_BANDMATRIX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -41,7 +43,7 @@ class BandMatrixBase : public EigenBase<Derived>
       DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic))
                             ? 1 + Supers + Subs
                             : Dynamic,
-      SizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime)
+      SizeAtCompileTime = min_size_prefer_dynamic(RowsAtCompileTime,ColsAtCompileTime)
     };
 
   public:
@@ -96,13 +98,13 @@ class BandMatrixBase : public EigenBase<Derived>
         DiagonalSize = (RowsAtCompileTime==Dynamic || ColsAtCompileTime==Dynamic)
                      ? Dynamic
                      : (ActualIndex<0
-                     ? EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
+                     ? min_size_prefer_dynamic(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
-                     : EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
+                     : min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
       };
       typedef Block<CoefficientsType,1, DiagonalSize> BuildType;
-      typedef typename internal::conditional<Conjugate,
+      typedef std::conditional_t<Conjugate,
                  CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>,BuildType >,
-                 BuildType>::type Type;
+                 BuildType> Type;
     };
 
     /** \returns a vector expression of the \a N -th sub or super diagonal */
@@ -161,12 +163,12 @@ class BandMatrixBase : public EigenBase<Derived>
   *
   * \brief Represents a rectangular matrix with a banded storage
   *
-  * \tparam _Scalar Numeric type, i.e. float, double, int
+  * \tparam Scalar_ Numeric type, i.e. float, double, int
-  * \tparam _Rows Number of rows, or \b Dynamic
+  * \tparam Rows_ Number of rows, or \b Dynamic
-  * \tparam _Cols Number of columns, or \b Dynamic
+  * \tparam Cols_ Number of columns, or \b Dynamic
-  * \tparam _Supers Number of super diagonal
+  * \tparam Supers_ Number of super diagonal
-  * \tparam _Subs Number of sub diagonal
+  * \tparam Subs_ Number of sub diagonal
-  * \tparam _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
+  * \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.
@@ -174,29 +176,29 @@ class BandMatrixBase : public EigenBase<Derived>
   * \sa class TridiagonalMatrix
   */
 
-template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
+template<typename Scalar_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
+struct traits<BandMatrix<Scalar_,Rows_,Cols_,Supers_,Subs_,Options_> >
 {
-  typedef _Scalar Scalar;
+  typedef Scalar_ Scalar;
   typedef Dense StorageKind;
   typedef Eigen::Index StorageIndex;
   enum {
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
-    RowsAtCompileTime = _Rows,
+    RowsAtCompileTime = Rows_,
-    ColsAtCompileTime = _Cols,
+    ColsAtCompileTime = Cols_,
-    MaxRowsAtCompileTime = _Rows,
+    MaxRowsAtCompileTime = Rows_,
-    MaxColsAtCompileTime = _Cols,
+    MaxColsAtCompileTime = Cols_,
     Flags = LvalueBit,
-    Supers = _Supers,
+    Supers = Supers_,
-    Subs = _Subs,
+    Subs = Subs_,
-    Options = _Options,
+    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>
+template<typename Scalar_, int Rows, int Cols, int Supers, int Subs, int Options>
-class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Subs,Options> >
+class BandMatrix : public BandMatrixBase<BandMatrix<Scalar_,Rows,Cols,Supers,Subs,Options> >
 {
   public:
 
@@ -233,32 +235,32 @@ class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Sub
     internal::variable_if_dynamic<Index, Subs>   m_subs;
 };
 
-template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+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>
+template<typename CoefficientsType_,int Rows_, int Cols_, int Supers_, int Subs_,int Options_>
-struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+struct traits<BandMatrixWrapper<CoefficientsType_,Rows_,Cols_,Supers_,Subs_,Options_> >
 {
-  typedef typename _CoefficientsType::Scalar Scalar;
+  typedef typename CoefficientsType_::Scalar Scalar;
-  typedef typename _CoefficientsType::StorageKind StorageKind;
+  typedef typename CoefficientsType_::StorageKind StorageKind;
-  typedef typename _CoefficientsType::StorageIndex StorageIndex;
+  typedef typename CoefficientsType_::StorageIndex StorageIndex;
   enum {
-    CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
+    CoeffReadCost = internal::traits<CoefficientsType_>::CoeffReadCost,
-    RowsAtCompileTime = _Rows,
+    RowsAtCompileTime = Rows_,
-    ColsAtCompileTime = _Cols,
+    ColsAtCompileTime = Cols_,
-    MaxRowsAtCompileTime = _Rows,
+    MaxRowsAtCompileTime = Rows_,
-    MaxColsAtCompileTime = _Cols,
+    MaxColsAtCompileTime = Cols_,
     Flags = LvalueBit,
-    Supers = _Supers,
+    Supers = Supers_,
-    Subs = _Subs,
+    Subs = Subs_,
-    Options = _Options,
+    Options = Options_,
     DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
   };
-  typedef _CoefficientsType CoefficientsType;
+  typedef CoefficientsType_ CoefficientsType;
 };
 
-template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+template<typename CoefficientsType_,int Rows_, int Cols_, int Supers_, int Subs_,int Options_>
-class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<CoefficientsType_,Rows_,Cols_,Supers_,Subs_,Options_> >
 {
   public:
 
@@ -266,12 +268,12 @@ class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsT
     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)
+    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);
-      //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
+      // eigen_assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
     }
 
     /** \returns the number of columns */
@@ -291,9 +293,9 @@ class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsT
   protected:
 
     const CoefficientsType& m_coeffs;
-    internal::variable_if_dynamic<Index, _Rows>   m_rows;
+    internal::variable_if_dynamic<Index, Rows_>   m_rows;
-    internal::variable_if_dynamic<Index, _Supers> m_supers;
+    internal::variable_if_dynamic<Index, Supers_> m_supers;
-    internal::variable_if_dynamic<Index, _Subs>   m_subs;
+    internal::variable_if_dynamic<Index, Subs_>   m_subs;
 };
 
 /**
@@ -330,16 +332,16 @@ class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint
 
 struct BandShape {};
 
-template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
+template<typename Scalar_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct evaluator_traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
+struct evaluator_traits<BandMatrix<Scalar_,Rows_,Cols_,Supers_,Subs_,Options_> >
-  : public evaluator_traits_base<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>
+template<typename CoefficientsType_,int Rows_, int Cols_, int Supers_, int Subs_,int Options_>
-struct evaluator_traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+struct evaluator_traits<BandMatrixWrapper<CoefficientsType_,Rows_,Cols_,Supers_,Subs_,Options_> >
-  : public evaluator_traits_base<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+  : public evaluator_traits_base<BandMatrixWrapper<CoefficientsType_,Rows_,Cols_,Supers_,Subs_,Options_> >
 {
   typedef BandShape Shape;
 };

libs/eigen/Eigen/src/Core/Block.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_BLOCK_H
 #define EIGEN_BLOCK_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -21,7 +23,7 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprTyp
   typedef typename traits<XprType>::StorageKind StorageKind;
   typedef typename traits<XprType>::XprKind XprKind;
   typedef typename ref_selector<XprType>::type XprTypeNested;
-  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  typedef std::remove_reference_t<XprTypeNested> XprTypeNested_;
   enum{
     MatrixRows = traits<XprType>::RowsAtCompileTime,
     MatrixCols = traits<XprType>::ColsAtCompileTime,
@@ -110,7 +112,7 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class
     EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
 
-    typedef typename internal::remove_all<XprType>::type NestedExpression;
+    typedef internal::remove_all_t<XprType> NestedExpression;
 
     /** Column or Row constructor
       */
@@ -260,19 +262,19 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(Index rowId, Index colId) const
+    EIGEN_DEVICE_FUNC inline PacketScalar packet(Index rowId, Index colId) const
     {
       return m_xpr.template packet<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
     template<int LoadMode>
-    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
+    EIGEN_DEVICE_FUNC inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
     {
       m_xpr.template writePacket<Unaligned>(rowId + m_startRow.value(), colId + m_startCol.value(), val);
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(Index index) const
+    EIGEN_DEVICE_FUNC inline PacketScalar packet(Index index) const
     {
       return m_xpr.template packet<Unaligned>
               (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
@@ -280,7 +282,7 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
     }
 
     template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& val)
+    EIGEN_DEVICE_FUNC inline void writePacket(Index index, const PacketScalar& val)
     {
       m_xpr.template writePacket<Unaligned>
          (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
@@ -295,7 +297,7 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
     #endif
 
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const typename internal::remove_all<XprTypeNested>::type& nestedExpression() const
+    const internal::remove_all_t<XprTypeNested>& nestedExpression() const
     {
       return m_xpr;
     }
@@ -378,7 +380,7 @@ class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
     }
 
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const typename internal::remove_all<XprTypeNested>::type& nestedExpression() const EIGEN_NOEXCEPT
+    const internal::remove_all_t<XprTypeNested>& nestedExpression() const EIGEN_NOEXCEPT
     {
       return m_xpr;
     }

libs/eigen/Eigen/src/Core/BooleanRedux.h

@@ -10,58 +10,62 @@
 #ifndef EIGEN_ALLANDANY_H
 #define EIGEN_ALLANDANY_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
-template<typename Derived, int UnrollCount, int Rows>
+template<typename Derived, int UnrollCount, int InnerSize>
 struct all_unroller
 {
   enum {
-    col = (UnrollCount-1) / Rows,
+    IsRowMajor = (int(Derived::Flags) & int(RowMajor)),
-    row = (UnrollCount-1) % Rows
+    i = (UnrollCount-1) / InnerSize,
+    j = (UnrollCount-1) % InnerSize
   };
 
   EIGEN_DEVICE_FUNC static inline bool run(const Derived &mat)
   {
-    return all_unroller<Derived, UnrollCount-1, Rows>::run(mat) && mat.coeff(row, col);
+    return all_unroller<Derived, UnrollCount-1, InnerSize>::run(mat) && mat.coeff(IsRowMajor ? i : j, IsRowMajor ? j : i);
   }
 };
 
-template<typename Derived, int Rows>
+template<typename Derived, int InnerSize>
-struct all_unroller<Derived, 0, Rows>
+struct all_unroller<Derived, 0, InnerSize>
 {
   EIGEN_DEVICE_FUNC static inline bool run(const Derived &/*mat*/) { return true; }
 };
 
-template<typename Derived, int Rows>
+template<typename Derived, int InnerSize>
-struct all_unroller<Derived, Dynamic, Rows>
+struct all_unroller<Derived, Dynamic, InnerSize>
 {
   EIGEN_DEVICE_FUNC static inline bool run(const Derived &) { return false; }
 };
 
-template<typename Derived, int UnrollCount, int Rows>
+template<typename Derived, int UnrollCount, int InnerSize>
 struct any_unroller
 {
   enum {
-    col = (UnrollCount-1) / Rows,
+    IsRowMajor = (int(Derived::Flags) & int(RowMajor)),
-    row = (UnrollCount-1) % Rows
+    i = (UnrollCount-1) / InnerSize,
+    j = (UnrollCount-1) % InnerSize
   };
 
   EIGEN_DEVICE_FUNC static inline bool run(const Derived &mat)
   {
-    return any_unroller<Derived, UnrollCount-1, Rows>::run(mat) || mat.coeff(row, col);
+    return any_unroller<Derived, UnrollCount-1, InnerSize>::run(mat) || mat.coeff(IsRowMajor ? i : j, IsRowMajor ? j : i);
   }
 };
 
-template<typename Derived, int Rows>
+template<typename Derived, int InnerSize>
-struct any_unroller<Derived, 0, Rows>
+struct any_unroller<Derived, 0, InnerSize>
 {
   EIGEN_DEVICE_FUNC static inline bool run(const Derived & /*mat*/) { return false; }
 };
 
-template<typename Derived, int Rows>
+template<typename Derived, int InnerSize>
-struct any_unroller<Derived, Dynamic, Rows>
+struct any_unroller<Derived, Dynamic, InnerSize>
 {
   EIGEN_DEVICE_FUNC static inline bool run(const Derived &) { return false; }
 };
@@ -81,16 +85,16 @@ EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::all() const
   typedef internal::evaluator<Derived> Evaluator;
   enum {
     unroll = SizeAtCompileTime != Dynamic
-          && SizeAtCompileTime * (int(Evaluator::CoeffReadCost) + int(NumTraits<Scalar>::AddCost)) <= EIGEN_UNROLLING_LIMIT
+          && SizeAtCompileTime * (int(Evaluator::CoeffReadCost) + int(NumTraits<Scalar>::AddCost)) <= EIGEN_UNROLLING_LIMIT,
   };
   Evaluator evaluator(derived());
   if(unroll)
-    return internal::all_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic, internal::traits<Derived>::RowsAtCompileTime>::run(evaluator);
+    return internal::all_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic, InnerSizeAtCompileTime>::run(evaluator);
   else
   {
-    for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < derived().outerSize(); ++i)
-      for(Index i = 0; i < rows(); ++i)
+      for(Index j = 0; j < derived().innerSize(); ++j)
-        if (!evaluator.coeff(i, j)) return false;
+        if (!evaluator.coeff(IsRowMajor ? i : j, IsRowMajor ? j : i)) return false;
     return true;
   }
 }
@@ -105,16 +109,16 @@ EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::any() const
   typedef internal::evaluator<Derived> Evaluator;
   enum {
     unroll = SizeAtCompileTime != Dynamic
-          && SizeAtCompileTime * (int(Evaluator::CoeffReadCost) + int(NumTraits<Scalar>::AddCost)) <= EIGEN_UNROLLING_LIMIT
+          && SizeAtCompileTime * (int(Evaluator::CoeffReadCost) + int(NumTraits<Scalar>::AddCost)) <= EIGEN_UNROLLING_LIMIT,
   };
   Evaluator evaluator(derived());
   if(unroll)
-    return internal::any_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic, internal::traits<Derived>::RowsAtCompileTime>::run(evaluator);
+    return internal::any_unroller<Evaluator, unroll ? int(SizeAtCompileTime) : Dynamic, InnerSizeAtCompileTime>::run(evaluator);
   else
   {
-    for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < derived().outerSize(); ++i)
-      for(Index i = 0; i < rows(); ++i)
+      for(Index j = 0; j < derived().innerSize(); ++j)
-        if (evaluator.coeff(i, j)) return true;
+        if (evaluator.coeff(IsRowMajor ? i : j, IsRowMajor ? j : i)) return true;
     return false;
   }
 }
@@ -134,7 +138,7 @@ EIGEN_DEVICE_FUNC inline Eigen::Index DenseBase<Derived>::count() const
   * \sa allFinite()
   */
 template<typename Derived>
-inline bool DenseBase<Derived>::hasNaN() const
+EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::hasNaN() const
 {
 #if EIGEN_COMP_MSVC || (defined __FAST_MATH__)
   return derived().array().isNaN().any();
@@ -148,7 +152,7 @@ inline bool DenseBase<Derived>::hasNaN() const
   * \sa hasNaN()
   */
 template<typename Derived>
-inline bool DenseBase<Derived>::allFinite() const
+EIGEN_DEVICE_FUNC inline bool DenseBase<Derived>::allFinite() const
 {
 #if EIGEN_COMP_MSVC || (defined __FAST_MATH__)
   return derived().array().isFinite().all();

libs/eigen/Eigen/src/Core/CommaInitializer.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_COMMAINITIALIZER_H
 #define EIGEN_COMMAINITIALIZER_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 /** \class CommaInitializer
@@ -45,7 +47,7 @@ struct CommaInitializer
   {
     eigen_assert(m_xpr.rows() >= other.rows() && m_xpr.cols() >= other.cols()
       && "Cannot comma-initialize a 0x0 matrix (operator<<)");
-    m_xpr.block(0, 0, other.rows(), other.cols()) = other;
+    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 

libs/eigen/Eigen/src/Core/ConditionEstimator.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_CONDITIONESTIMATOR_H
 #define EIGEN_CONDITIONESTIMATOR_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -161,10 +163,10 @@ rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm, const Deco
   typedef typename Decomposition::RealScalar RealScalar;
   eigen_assert(dec.rows() == dec.cols());
   if (dec.rows() == 0)                        return NumTraits<RealScalar>::infinity();
-  if (matrix_norm == RealScalar(0)) return RealScalar(0);
+  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 (inverse_matrix_norm == RealScalar(0) ? RealScalar(0)
+  return (numext::is_exactly_zero(inverse_matrix_norm) ? RealScalar(0)
                                                        : (RealScalar(1) / inverse_matrix_norm) / matrix_norm);
 }
 

libs/eigen/Eigen/src/Core/CoreEvaluators.h

@@ -13,6 +13,8 @@
 #ifndef EIGEN_COREEVALUATORS_H
 #define EIGEN_COREEVALUATORS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -498,7 +500,7 @@ struct evaluator<CwiseNullaryOp<NullaryOp,PlainObjectType> >
   : evaluator_base<CwiseNullaryOp<NullaryOp,PlainObjectType> >
 {
   typedef CwiseNullaryOp<NullaryOp,PlainObjectType> XprType;
-  typedef typename internal::remove_all<PlainObjectType>::type PlainObjectTypeCleaned;
+  typedef internal::remove_all_t<PlainObjectType> PlainObjectTypeCleaned;
 
   enum {
     CoeffReadCost = internal::functor_traits<NullaryOp>::Cost,
@@ -655,8 +657,8 @@ struct ternary_evaluator<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>, IndexBased
         )
      ),
     Flags = (Flags0 & ~RowMajorBit) | (Arg1Flags & RowMajorBit),
-    Alignment = EIGEN_PLAIN_ENUM_MIN(
+    Alignment = plain_enum_min(
-        EIGEN_PLAIN_ENUM_MIN(evaluator<Arg1>::Alignment, evaluator<Arg2>::Alignment),
+            plain_enum_min(evaluator<Arg1>::Alignment, evaluator<Arg2>::Alignment),
             evaluator<Arg3>::Alignment)
   };
 
@@ -751,7 +753,7 @@ struct binary_evaluator<CwiseBinaryOp<BinaryOp, Lhs, Rhs>, IndexBased, IndexBase
         )
      ),
     Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
-    Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<Lhs>::Alignment,evaluator<Rhs>::Alignment)
+    Alignment = plain_enum_min(evaluator<Lhs>::Alignment, evaluator<Rhs>::Alignment)
   };
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -810,11 +812,11 @@ protected:
 
 // -------------------- CwiseUnaryView --------------------
 
-template<typename UnaryOp, typename ArgType>
+template<typename UnaryOp, typename ArgType, typename StrideType>
-struct unary_evaluator<CwiseUnaryView<UnaryOp, ArgType>, IndexBased>
+struct unary_evaluator<CwiseUnaryView<UnaryOp, ArgType, StrideType>, IndexBased>
-  : evaluator_base<CwiseUnaryView<UnaryOp, ArgType> >
+  : evaluator_base<CwiseUnaryView<UnaryOp, ArgType, StrideType> >
 {
-  typedef CwiseUnaryView<UnaryOp, ArgType> XprType;
+  typedef CwiseUnaryView<UnaryOp, ArgType, StrideType> XprType;
 
   enum {
     CoeffReadCost = int(evaluator<ArgType>::CoeffReadCost) + int(functor_traits<UnaryOp>::Cost),
@@ -900,7 +902,8 @@ struct mapbase_evaluator : evaluator_base<Derived>
       m_innerStride(map.innerStride()),
       m_outerStride(map.outerStride())
   {
-    EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(evaluator<Derived>::Flags&PacketAccessBit, internal::inner_stride_at_compile_time<Derived>::ret==1),
+    EIGEN_STATIC_ASSERT(check_implication((evaluator<Derived>::Flags & PacketAccessBit) != 0,
+                                          internal::inner_stride_at_compile_time<Derived>::ret == 1),
                         PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
     EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost);
   }
@@ -1072,7 +1075,7 @@ struct evaluator<Block<ArgType, BlockRows, BlockCols, InnerPanel> >
     Alignment0 = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic)
                              && (OuterStrideAtCompileTime!=0)
                              && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0)) ? int(PacketAlignment) : 0,
-    Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<ArgType>::Alignment, Alignment0)
+    Alignment = plain_enum_min(evaluator<ArgType>::Alignment, Alignment0)
   };
   typedef block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel> block_evaluator_type;
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -1222,8 +1225,8 @@ struct block_evaluator<ArgType, BlockRows, BlockCols, InnerPanel, /* HasDirectAc
   explicit block_evaluator(const XprType& block)
     : mapbase_evaluator<XprType, typename XprType::PlainObject>(block)
   {
-    // TODO: for the 3.3 release, this should be turned to an internal assertion, but let's keep it as is for the beta lifetime
+    eigen_internal_assert((internal::is_constant_evaluated() || (internal::UIntPtr(block.data()) % plain_enum_max(1,evaluator<XprType>::Alignment)) == 0) \
-    eigen_assert(((internal::UIntPtr(block.data()) % EIGEN_PLAIN_ENUM_MAX(1,evaluator<XprType>::Alignment)) == 0) && "data is not aligned");
+      && "data is not aligned");
   }
 };
 
@@ -1239,12 +1242,12 @@ struct evaluator<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
   typedef Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> XprType;
   enum {
     CoeffReadCost = evaluator<ConditionMatrixType>::CoeffReadCost
-                  + EIGEN_PLAIN_ENUM_MAX(evaluator<ThenMatrixType>::CoeffReadCost,
+                  + plain_enum_max(evaluator<ThenMatrixType>::CoeffReadCost,
                                              evaluator<ElseMatrixType>::CoeffReadCost),
 
     Flags = (unsigned int)evaluator<ThenMatrixType>::Flags & evaluator<ElseMatrixType>::Flags & HereditaryBits,
 
-    Alignment = EIGEN_PLAIN_ENUM_MIN(evaluator<ThenMatrixType>::Alignment, evaluator<ElseMatrixType>::Alignment)
+    Alignment = plain_enum_min(evaluator<ThenMatrixType>::Alignment, evaluator<ElseMatrixType>::Alignment)
   };
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -1295,7 +1298,7 @@ struct unary_evaluator<Replicate<ArgType, RowFactor, ColFactor> >
     Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor
   };
   typedef typename internal::nested_eval<ArgType,Factor>::type ArgTypeNested;
-  typedef typename internal::remove_all<ArgTypeNested>::type ArgTypeNestedCleaned;
+  typedef internal::remove_all_t<ArgTypeNested> ArgTypeNestedCleaned;
 
   enum {
     CoeffReadCost = evaluator<ArgTypeNestedCleaned>::CoeffReadCost,
@@ -1379,7 +1382,7 @@ template<typename XprType>
 struct evaluator_wrapper_base
   : evaluator_base<XprType>
 {
-  typedef typename remove_all<typename XprType::NestedExpressionType>::type ArgType;
+  typedef remove_all_t<typename XprType::NestedExpressionType> ArgType;
   enum {
     CoeffReadCost = evaluator<ArgType>::CoeffReadCost,
     Flags = evaluator<ArgType>::Flags,
@@ -1720,14 +1723,14 @@ struct evaluator<EvalToTemp<ArgType> >
   EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
     : m_result(xpr.arg())
   {
-    ::new (static_cast<Base*>(this)) Base(m_result);
+    internal::construct_at<Base>(this, m_result);
   }
 
   // This constructor is used when nesting an EvalTo evaluator in another evaluator
   EIGEN_DEVICE_FUNC evaluator(const ArgType& arg)
     : m_result(arg)
   {
-    ::new (static_cast<Base*>(this)) Base(m_result);
+    internal::construct_at<Base>(this, m_result);
   }
 
 protected:

libs/eigen/Eigen/src/Core/CoreIterators.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_COREITERATORS_H
 #define EIGEN_COREITERATORS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 /* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core

libs/eigen/Eigen/src/Core/CwiseBinaryOp.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_CWISE_BINARY_OP_H
 #define EIGEN_CWISE_BINARY_OP_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -19,7 +21,7 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
 {
   // we must not inherit from traits<Lhs> since it has
   // the potential to cause problems with MSVC
-  typedef typename remove_all<Lhs>::type Ancestor;
+  typedef remove_all_t<Lhs> Ancestor;
   typedef typename traits<Ancestor>::XprKind XprKind;
   enum {
     RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
@@ -43,10 +45,10 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
                                       typename traits<Rhs>::StorageIndex>::type StorageIndex;
   typedef typename Lhs::Nested LhsNested;
   typedef typename Rhs::Nested RhsNested;
-  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef std::remove_reference_t<LhsNested> LhsNested_;
-  typedef typename remove_reference<RhsNested>::type _RhsNested;
+  typedef std::remove_reference_t<RhsNested> RhsNested_;
   enum {
-    Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind,typename traits<Rhs>::StorageKind,_LhsNested::Flags & RowMajorBit,_RhsNested::Flags & RowMajorBit>::value
+    Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind,typename traits<Rhs>::StorageKind,LhsNested_::Flags & RowMajorBit,RhsNested_::Flags & RowMajorBit>::value
   };
 };
 } // end namespace internal
@@ -84,9 +86,9 @@ class CwiseBinaryOp :
 {
   public:
 
-    typedef typename internal::remove_all<BinaryOp>::type Functor;
+    typedef internal::remove_all_t<BinaryOp> Functor;
-    typedef typename internal::remove_all<LhsType>::type Lhs;
+    typedef internal::remove_all_t<LhsType> Lhs;
-    typedef typename internal::remove_all<RhsType>::type Rhs;
+    typedef internal::remove_all_t<RhsType> Rhs;
 
     typedef typename CwiseBinaryOpImpl<
         BinaryOp, LhsType, RhsType,
@@ -95,12 +97,15 @@ class CwiseBinaryOp :
                                                       BinaryOp>::ret>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
 
+    EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar)
+    EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
+
     typedef typename internal::ref_selector<LhsType>::type LhsNested;
     typedef typename internal::ref_selector<RhsType>::type RhsNested;
-    typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
+    typedef std::remove_reference_t<LhsNested> LhsNested_;
-    typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
+    typedef std::remove_reference_t<RhsNested> RhsNested_;
 
-#if EIGEN_COMP_MSVC && EIGEN_HAS_CXX11
+#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;
@@ -110,29 +115,26 @@ class CwiseBinaryOp :
     CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
       : m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
     {
-      EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
-      // require the sizes to match
-      EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
       eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
     }
 
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
     Index rows() const EIGEN_NOEXCEPT {
       // return the fixed size type if available to enable compile time optimizations
-      return internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic ? m_rhs.rows() : m_lhs.rows();
+      return internal::traits<internal::remove_all_t<LhsNested>>::RowsAtCompileTime==Dynamic ? m_rhs.rows() : m_lhs.rows();
     }
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR
     Index cols() const EIGEN_NOEXCEPT {
       // return the fixed size type if available to enable compile time optimizations
-      return internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic ? m_rhs.cols() : m_lhs.cols();
+      return internal::traits<internal::remove_all_t<LhsNested>>::ColsAtCompileTime==Dynamic ? m_rhs.cols() : m_lhs.cols();
     }
 
     /** \returns the left hand side nested expression */
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const _LhsNested& lhs() const { return m_lhs; }
+    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; }
+    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; }

libs/eigen/Eigen/src/Core/CwiseNullaryOp.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_CWISE_NULLARY_OP_H
 #define EIGEN_CWISE_NULLARY_OP_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -304,6 +306,20 @@ DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
   return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op<Scalar>(low,high,Derived::SizeAtCompileTime));
 }
 
+template <typename Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessEqualSpacedReturnType
+DenseBase<Derived>::EqualSpaced(Index size, const Scalar& low, const Scalar& step) {
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return DenseBase<Derived>::NullaryExpr(size, internal::equalspaced_op<Scalar>(low, step));
+}
+
+template <typename Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase<Derived>::RandomAccessEqualSpacedReturnType
+DenseBase<Derived>::EqualSpaced(const Scalar& low, const Scalar& step) {
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return DenseBase<Derived>::NullaryExpr(Derived::SizeAtCompileTime, internal::equalspaced_op<Scalar>(low, step));
+}
+
 /** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */
 template<typename Derived>
 EIGEN_DEVICE_FUNC bool DenseBase<Derived>::isApproxToConstant
@@ -453,6 +469,19 @@ EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(
   return setLinSpaced(size(), low, high);
 }
 
+template <typename Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setEqualSpaced(Index newSize, const Scalar& low,
+                                                                                  const Scalar& step) {
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return derived() = Derived::NullaryExpr(newSize, internal::equalspaced_op<Scalar>(low, step));
+}
+template <typename Derived>
+EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setEqualSpaced(const Scalar& low,
+                                                                                  const Scalar& step) {
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  return setEqualSpaced(size(), low, step);
+}
+
 // zero:
 
 /** \returns an expression of a zero matrix.

libs/eigen/Eigen/src/Core/CwiseTernaryOp.h

@@ -12,6 +12,8 @@
 #ifndef EIGEN_CWISE_TERNARY_OP_H
 #define EIGEN_CWISE_TERNARY_OP_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -19,7 +21,7 @@ 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 typename remove_all<Arg1>::type Ancestor;
+  typedef remove_all_t<Arg1> Ancestor;
   typedef typename traits<Ancestor>::XprKind XprKind;
   enum {
     RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
@@ -41,10 +43,10 @@ struct traits<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3> > {
   typedef typename Arg1::Nested Arg1Nested;
   typedef typename Arg2::Nested Arg2Nested;
   typedef typename Arg3::Nested Arg3Nested;
-  typedef typename remove_reference<Arg1Nested>::type _Arg1Nested;
+  typedef std::remove_reference_t<Arg1Nested> Arg1Nested_;
-  typedef typename remove_reference<Arg2Nested>::type _Arg2Nested;
+  typedef std::remove_reference_t<Arg2Nested> Arg2Nested_;
-  typedef typename remove_reference<Arg3Nested>::type _Arg3Nested;
+  typedef std::remove_reference_t<Arg3Nested> Arg3Nested_;
-  enum { Flags = _Arg1Nested::Flags & RowMajorBit };
+  enum { Flags = Arg1Nested_::Flags & RowMajorBit };
 };
 }  // end namespace internal
 
@@ -87,27 +89,10 @@ class CwiseTernaryOp : public CwiseTernaryOpImpl<
                        internal::no_assignment_operator
 {
  public:
-  typedef typename internal::remove_all<Arg1Type>::type Arg1;
+  typedef internal::remove_all_t<Arg1Type> Arg1;
-  typedef typename internal::remove_all<Arg2Type>::type Arg2;
+  typedef internal::remove_all_t<Arg2Type> Arg2;
-  typedef typename internal::remove_all<Arg3Type>::type Arg3;
+  typedef internal::remove_all_t<Arg3Type> Arg3;
 
-  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 typename internal::remove_reference<Arg1Nested>::type _Arg1Nested;
-  typedef typename internal::remove_reference<Arg2Nested>::type _Arg2Nested;
-  typedef typename internal::remove_reference<Arg3Nested>::type _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) {
   // require the sizes to match
   EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg2)
   EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg3)
@@ -122,6 +107,23 @@ class CwiseTernaryOp : public CwiseTernaryOpImpl<
                        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());
   }
@@ -130,14 +132,14 @@ class CwiseTernaryOp : public CwiseTernaryOpImpl<
   EIGEN_STRONG_INLINE Index rows() const {
     // return the fixed size type if available to enable compile time
     // optimizations
-    if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+    if (internal::traits<internal::remove_all_t<Arg1Nested>>::
                 RowsAtCompileTime == Dynamic &&
-        internal::traits<typename internal::remove_all<Arg2Nested>::type>::
+        internal::traits<internal::remove_all_t<Arg2Nested>>::
                 RowsAtCompileTime == Dynamic)
       return m_arg3.rows();
-    else if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::
                      RowsAtCompileTime == Dynamic &&
-             internal::traits<typename internal::remove_all<Arg3Nested>::type>::
+             internal::traits<internal::remove_all_t<Arg3Nested>>::
                      RowsAtCompileTime == Dynamic)
       return m_arg2.rows();
     else
@@ -147,14 +149,14 @@ class CwiseTernaryOp : public CwiseTernaryOpImpl<
   EIGEN_STRONG_INLINE Index cols() const {
     // return the fixed size type if available to enable compile time
     // optimizations
-    if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+    if (internal::traits<internal::remove_all_t<Arg1Nested>>::
                 ColsAtCompileTime == Dynamic &&
-        internal::traits<typename internal::remove_all<Arg2Nested>::type>::
+        internal::traits<internal::remove_all_t<Arg2Nested>>::
                 ColsAtCompileTime == Dynamic)
       return m_arg3.cols();
-    else if (internal::traits<typename internal::remove_all<Arg1Nested>::type>::
+    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::
                      ColsAtCompileTime == Dynamic &&
-             internal::traits<typename internal::remove_all<Arg3Nested>::type>::
+             internal::traits<internal::remove_all_t<Arg3Nested>>::
                      ColsAtCompileTime == Dynamic)
       return m_arg2.cols();
     else
@@ -163,13 +165,13 @@ class CwiseTernaryOp : public CwiseTernaryOpImpl<
 
   /** \returns the first argument nested expression */
   EIGEN_DEVICE_FUNC
-  const _Arg1Nested& arg1() const { return m_arg1; }
+  const Arg1Nested_& arg1() const { return m_arg1; }
   /** \returns the first argument nested expression */
   EIGEN_DEVICE_FUNC
-  const _Arg2Nested& arg2() const { return m_arg2; }
+  const Arg2Nested_& arg2() const { return m_arg2; }
   /** \returns the third argument nested expression */
   EIGEN_DEVICE_FUNC
-  const _Arg3Nested& arg3() const { return m_arg3; }
+  const Arg3Nested_& arg3() const { return m_arg3; }
   /** \returns the functor representing the ternary operation */
   EIGEN_DEVICE_FUNC
   const TernaryOp& functor() const { return m_functor; }

libs/eigen/Eigen/src/Core/CwiseUnaryOp.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_CWISE_UNARY_OP_H
 #define EIGEN_CWISE_UNARY_OP_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -22,9 +24,9 @@ struct traits<CwiseUnaryOp<UnaryOp, XprType> >
                      UnaryOp(const typename XprType::Scalar&)
                    >::type Scalar;
   typedef typename XprType::Nested XprTypeNested;
-  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  typedef std::remove_reference_t<XprTypeNested> XprTypeNested_;
   enum {
-    Flags = _XprTypeNested::Flags & RowMajorBit
+    Flags = XprTypeNested_::Flags & RowMajorBit
   };
 };
 }
@@ -59,7 +61,7 @@ class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal
     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 typename internal::remove_all<XprType>::type NestedExpression;
+    typedef internal::remove_all_t<XprType> NestedExpression;
 
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     explicit CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
@@ -76,12 +78,12 @@ class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal
 
     /** \returns the nested expression */
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const typename internal::remove_all<XprTypeNested>::type&
+    const internal::remove_all_t<XprTypeNested>&
     nestedExpression() const { return m_xpr; }
 
     /** \returns the nested expression */
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    typename internal::remove_all<XprTypeNested>::type&
+    internal::remove_all_t<XprTypeNested>&
     nestedExpression() { return m_xpr; }
 
   protected:

libs/eigen/Eigen/src/Core/CwiseUnaryView.h

@@ -10,35 +10,42 @@
 #ifndef EIGEN_CWISE_UNARY_VIEW_H
 #define EIGEN_CWISE_UNARY_VIEW_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
-template<typename ViewOp, typename MatrixType>
+template<typename ViewOp, typename MatrixType, typename StrideType>
-struct traits<CwiseUnaryView<ViewOp, MatrixType> >
+struct traits<CwiseUnaryView<ViewOp, MatrixType, StrideType> >
  : traits<MatrixType>
 {
   typedef typename result_of<
                      ViewOp(const typename traits<MatrixType>::Scalar&)
                    >::type Scalar;
   typedef typename MatrixType::Nested MatrixTypeNested;
-  typedef typename remove_all<MatrixTypeNested>::type _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
+    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 = MatrixTypeInnerStride == Dynamic
+    InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0
+                             ? (MatrixTypeInnerStride == Dynamic
                                ? int(Dynamic)
-                             : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)),
+                               : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)))
-    OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret == Dynamic
+                             : 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))
+                               : outer_stride_at_compile_time<MatrixType>::ret * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)))
+                             : int(StrideType::OuterStrideAtCompileTime)
   };
 };
 }
 
-template<typename ViewOp, typename MatrixType, typename StorageKind>
+template<typename ViewOp, typename MatrixType, typename StrideType, typename StorageKind>
 class CwiseUnaryViewImpl;
 
 /** \class CwiseUnaryView
@@ -54,15 +61,15 @@ class CwiseUnaryViewImpl;
   *
   * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
   */
-template<typename ViewOp, typename MatrixType>
+template<typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
+class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, typename internal::traits<MatrixType>::StorageKind>
 {
   public:
 
-    typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
+    typedef typename 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 typename internal::remove_all<MatrixType>::type NestedExpression;
+    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) {}
@@ -78,11 +85,11 @@ class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename in
     EIGEN_DEVICE_FUNC const ViewOp& functor() const { return m_functor; }
 
     /** \returns the nested expression */
-    EIGEN_DEVICE_FUNC const typename internal::remove_all<MatrixTypeNested>::type&
+    EIGEN_DEVICE_FUNC const internal::remove_all_t<MatrixTypeNested>&
     nestedExpression() const { return m_matrix; }
 
     /** \returns the nested expression */
-    EIGEN_DEVICE_FUNC typename internal::remove_reference<MatrixTypeNested>::type&
+    EIGEN_DEVICE_FUNC std::remove_reference_t<MatrixTypeNested>&
     nestedExpression() { return m_matrix; }
 
   protected:
@@ -91,22 +98,22 @@ class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename in
 };
 
 // Generic API dispatcher
-template<typename ViewOp, typename XprType, typename StorageKind>
+template<typename ViewOp, typename XprType, typename StrideType, typename StorageKind>
 class CwiseUnaryViewImpl
-  : public internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type
+  : public internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type
 {
 public:
-  typedef typename internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType> >::type Base;
+  typedef typename internal::generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type Base;
 };
 
-template<typename ViewOp, typename MatrixType>
+template<typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
+class CwiseUnaryViewImpl<ViewOp,MatrixType,StrideType,Dense>
-  : public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
+  : public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType, StrideType> >::type
 {
   public:
 
-    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
+    typedef CwiseUnaryView<ViewOp, MatrixType,StrideType> Derived;
-    typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
+    typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType,StrideType> >::type Base;
 
     EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
@@ -116,12 +123,16 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
 
     EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR inline Index innerStride() const
     {
-      return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
+      return StrideType::InnerStrideAtCompileTime != 0
+             ? int(StrideType::InnerStrideAtCompileTime)
+             : derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
     }
 
     EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR inline Index outerStride() const
     {
-      return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
+      return StrideType::OuterStrideAtCompileTime != 0
+             ? int(StrideType::OuterStrideAtCompileTime)
+             : derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
     }
   protected:
     EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl)

libs/eigen/Eigen/src/Core/DenseBase.h

@@ -11,17 +11,12 @@
 #ifndef EIGEN_DENSEBASE_H
 #define EIGEN_DENSEBASE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
-namespace internal {
-
 // The index type defined by EIGEN_DEFAULT_DENSE_INDEX_TYPE must be a signed type.
-// This dummy function simply aims at checking that at compile time.
-static inline void check_DenseIndex_is_signed() {
 EIGEN_STATIC_ASSERT(NumTraits<DenseIndex>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE)
-}
-
-} // end namespace internal
 
 /** \class DenseBase
   * \ingroup Core_Module
@@ -110,8 +105,7 @@ template<typename Derived> class DenseBase
           * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */
 
 
-      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
+      SizeAtCompileTime = (internal::size_of_xpr_at_compile_time<Derived>::ret),
-                                                   internal::traits<Derived>::ColsAtCompileTime>::ret),
         /**< This is equal to the number of coefficients, i.e. the number of
           * rows times the number of columns, or to \a Dynamic if this is not
           * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
@@ -138,8 +132,8 @@ template<typename Derived> class DenseBase
           * \sa ColsAtCompileTime, MaxRowsAtCompileTime, MaxSizeAtCompileTime
           */
 
-      MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
+      MaxSizeAtCompileTime = internal::size_at_compile_time(internal::traits<Derived>::MaxRowsAtCompileTime,
-                                                      internal::traits<Derived>::MaxColsAtCompileTime>::ret),
+                                                            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.
@@ -206,13 +200,8 @@ template<typename Derived> class DenseBase
       * 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 typename internal::conditional<internal::is_same<typename internal::traits<Derived>::XprKind,MatrixXpr >::value,
+    typedef std::conditional_t<internal::is_same<typename internal::traits<Derived>::XprKind,MatrixXpr >::value,
-                                 PlainMatrix, PlainArray>::type PlainObject;
+                                 PlainMatrix, PlainArray> PlainObject;
-
-    /** \returns the number of nonzero coefficients which is in practice the number
-      * of stored coefficients. */
-    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
-    inline Index nonZeros() const { return size(); }
 
     /** \returns the outer size.
       *
@@ -269,6 +258,8 @@ template<typename Derived> class DenseBase
     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;
 
@@ -324,9 +315,9 @@ template<typename Derived> class DenseBase
     typedef Transpose<Derived> TransposeReturnType;
     EIGEN_DEVICE_FUNC
     TransposeReturnType transpose();
-    typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
+    typedef Transpose<const Derived> ConstTransposeReturnType;
     EIGEN_DEVICE_FUNC
-    ConstTransposeReturnType transpose() const;
+    const ConstTransposeReturnType transpose() const;
     EIGEN_DEVICE_FUNC
     void transposeInPlace();
 
@@ -347,6 +338,11 @@ template<typename Derived> class DenseBase
     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);
@@ -368,6 +364,8 @@ template<typename Derived> class DenseBase
     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();
@@ -387,15 +385,15 @@ template<typename Derived> class DenseBase
     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;
 
-    inline bool hasNaN() const;
+    EIGEN_DEVICE_FUNC inline bool hasNaN() const;
-    inline bool allFinite() const;
+    EIGEN_DEVICE_FUNC inline bool allFinite() const;
 
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator*=(const Scalar& other);
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Derived& operator/=(const Scalar& other);
 
-    typedef typename internal::add_const_on_value_type<typename internal::eval<Derived>::type>::type EvalReturnType;
+    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
@@ -439,9 +437,9 @@ template<typename Derived> class DenseBase
     EIGEN_DEVICE_FUNC inline const ForceAlignedAccess<Derived> forceAlignedAccess() const;
     EIGEN_DEVICE_FUNC inline ForceAlignedAccess<Derived> forceAlignedAccess();
     template<bool Enable> EIGEN_DEVICE_FUNC
-    inline const typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf() const;
+    inline const std::conditional_t<Enable,ForceAlignedAccess<Derived>,Derived&> forceAlignedAccessIf() const;
     template<bool Enable> EIGEN_DEVICE_FUNC
-    inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type forceAlignedAccessIf();
+    inline std::conditional_t<Enable,ForceAlignedAccess<Derived>,Derived&> forceAlignedAccessIf();
 
     EIGEN_DEVICE_FUNC Scalar sum() const;
     EIGEN_DEVICE_FUNC Scalar mean() const;
@@ -621,27 +619,21 @@ template<typename Derived> class DenseBase
     /** This is the const version of iterator (aka read-only) */
     typedef random_access_iterator_type const_iterator;
     #else
-    typedef typename internal::conditional< (Flags&DirectAccessBit)==DirectAccessBit,
+    typedef std::conditional_t< (Flags&DirectAccessBit)==DirectAccessBit,
                                      internal::pointer_based_stl_iterator<Derived>,
                                      internal::generic_randaccess_stl_iterator<Derived>
-                                          >::type iterator_type;
+                                   > iterator_type;
 
-    typedef typename internal::conditional< (Flags&DirectAccessBit)==DirectAccessBit,
+    typedef std::conditional_t< (Flags&DirectAccessBit)==DirectAccessBit,
                                      internal::pointer_based_stl_iterator<const Derived>,
                                      internal::generic_randaccess_stl_iterator<const Derived>
-                                          >::type const_iterator_type;
+                                   > const_iterator_type;
 
     // Stl-style iterators are supported only for vectors.
 
-    typedef typename internal::conditional< IsVectorAtCompileTime,
+    typedef std::conditional_t<IsVectorAtCompileTime, iterator_type, void> iterator;
-                                            iterator_type,
-                                            void
-                                          >::type iterator;
 
-    typedef typename internal::conditional< IsVectorAtCompileTime,
+    typedef std::conditional_t<IsVectorAtCompileTime, const_iterator_type, void> const_iterator;
-                                            const_iterator_type,
-                                            void
-                                          >::type const_iterator;
     #endif
 
     inline iterator begin();
@@ -678,14 +670,13 @@ template<typename Derived> class DenseBase
   protected:
     EIGEN_DEFAULT_COPY_CONSTRUCTOR(DenseBase)
     /** Default constructor. Do nothing. */
-    EIGEN_DEVICE_FUNC DenseBase()
+    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
        */
 #ifdef EIGEN_INTERNAL_DEBUGGING
-      EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, int(IsRowMajor))
+      EIGEN_STATIC_ASSERT((internal::check_implication(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, int(IsRowMajor))
-                        && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, int(!IsRowMajor))),
+                        && internal::check_implication(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, int(!IsRowMajor))),
                           INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION)
 #endif
     }

libs/eigen/Eigen/src/Core/DenseCoeffsBase.h

@@ -10,12 +10,14 @@
 #ifndef EIGEN_DENSECOEFFSBASE_H
 #define EIGEN_DENSECOEFFSBASE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 template<typename T> struct add_const_on_value_type_if_arithmetic
 {
-  typedef typename conditional<is_arithmetic<T>::value, T, typename add_const_on_value_type<T>::type>::type type;
+  typedef std::conditional_t<is_arithmetic<T>::value, T, add_const_on_value_type_t<T>> type;
 };
 }
 
@@ -43,13 +45,13 @@ class DenseCoeffsBase<Derived,ReadOnlyAccessors> : public EigenBase<Derived>
     // - This is the return type of the coeff() method.
     // - The LvalueBit means exactly that we can offer a coeffRef() method, which means exactly that we can get references
     // to coeffs, which means exactly that we can have coeff() return a const reference (as opposed to returning a value).
-    // - The is_artihmetic check is required since "const int", "const double", etc. will cause warnings on some systems
+    // - The is_arithmetic check is required since "const int", "const double", etc. will cause warnings on some systems
     // while the declaration of "const T", where T is a non arithmetic type does not. Always returning "const Scalar&" is
     // not possible, since the underlying expressions might not offer a valid address the reference could be referring to.
-    typedef typename internal::conditional<bool(internal::traits<Derived>::Flags&LvalueBit),
+    typedef std::conditional_t<bool(internal::traits<Derived>::Flags&LvalueBit),
                 const Scalar&,
-                         typename internal::conditional<internal::is_arithmetic<Scalar>::value, Scalar, const Scalar>::type
+                std::conditional_t<internal::is_arithmetic<Scalar>::value, Scalar, const Scalar>
-                     >::type CoeffReturnType;
+            > CoeffReturnType;
 
     typedef typename internal::add_const_on_value_type_if_arithmetic<
                          typename internal::packet_traits<Scalar>::type

libs/eigen/Eigen/src/Core/DenseStorage.h

@@ -18,6 +18,8 @@
   #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X)
 #endif
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -25,9 +27,7 @@ namespace internal {
 struct constructor_without_unaligned_array_assert {};
 
 template <typename T, int Size>
-EIGEN_DEVICE_FUNC
+EIGEN_DEVICE_FUNC constexpr void check_static_allocation_size() {
-void check_static_allocation_size()
-{
 // if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit
 #if EIGEN_STACK_ALLOCATION_LIMIT
   EIGEN_STATIC_ASSERT(Size * sizeof(T) <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
@@ -45,35 +45,30 @@ struct plain_array
 {
   T array[Size];
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array() { check_static_allocation_size<T, Size>(); }
-  plain_array()
-  {
-    check_static_allocation_size<T,Size>();
-  }
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array(constructor_without_unaligned_array_assert) {
-  plain_array(constructor_without_unaligned_array_assert)
-  {
     check_static_allocation_size<T, Size>();
   }
 };
 
 #if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
   #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask)
-#elif EIGEN_GNUC_AT_LEAST(4,7)
+#elif EIGEN_COMP_GNUC
   // GCC 4.7 is too aggressive in its optimizations and remove the alignment test based on the fact the array is declared to be aligned.
   // See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900
   // Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined:
   template<typename PtrType>
   EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; }
   #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
-    eigen_assert((internal::UIntPtr(eigen_unaligned_array_assert_workaround_gcc47(array)) & (sizemask)) == 0 \
+    eigen_assert((internal::is_constant_evaluated() \
+                || (internal::UIntPtr(eigen_unaligned_array_assert_workaround_gcc47(array)) & (sizemask)) == 0) \
               && "this assertion is explained here: " \
               "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
               " **** READ THIS WEB PAGE !!! ****");
 #else
   #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
-    eigen_assert((internal::UIntPtr(array) & (sizemask)) == 0 \
+    eigen_assert((internal::is_constant_evaluated() || (internal::UIntPtr(array) & (sizemask)) == 0) \
               && "this assertion is explained here: " \
               "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
               " **** READ THIS WEB PAGE !!! ****");
@@ -84,16 +79,12 @@ struct plain_array<T, Size, MatrixOrArrayOptions, 8>
 {
   EIGEN_ALIGN_TO_BOUNDARY(8) T array[Size];
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array() {
-  plain_array()
-  {
     EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(7);
     check_static_allocation_size<T,Size>();
   }
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array(constructor_without_unaligned_array_assert) {
-  plain_array(constructor_without_unaligned_array_assert)
-  {
     check_static_allocation_size<T, Size>();
   }
 };
@@ -103,16 +94,12 @@ struct plain_array<T, Size, MatrixOrArrayOptions, 16>
 {
   EIGEN_ALIGN_TO_BOUNDARY(16) T array[Size];
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array() {
-  plain_array()
-  {
     EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(15);
     check_static_allocation_size<T,Size>();
   }
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array(constructor_without_unaligned_array_assert) {
-  plain_array(constructor_without_unaligned_array_assert)
-  {
     check_static_allocation_size<T, Size>();
   }
 };
@@ -122,16 +109,12 @@ struct plain_array<T, Size, MatrixOrArrayOptions, 32>
 {
   EIGEN_ALIGN_TO_BOUNDARY(32) T array[Size];
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array() {
-  plain_array()
-  {
     EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(31);
     check_static_allocation_size<T,Size>();
   }
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array(constructor_without_unaligned_array_assert) {
-  plain_array(constructor_without_unaligned_array_assert)
-  {
     check_static_allocation_size<T, Size>();
   }
 };
@@ -141,16 +124,12 @@ struct plain_array<T, Size, MatrixOrArrayOptions, 64>
 {
   EIGEN_ALIGN_TO_BOUNDARY(64) T array[Size];
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array() {
-  plain_array()
-  {
     EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(63);
     check_static_allocation_size<T,Size>();
   }
 
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC constexpr plain_array(constructor_without_unaligned_array_assert) {
-  plain_array(constructor_without_unaligned_array_assert)
-  {
     check_static_allocation_size<T, Size>();
   }
 };
@@ -159,8 +138,8 @@ template <typename T, int MatrixOrArrayOptions, int Alignment>
 struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
 {
   T array[1];
-  EIGEN_DEVICE_FUNC plain_array() {}
+  EIGEN_DEVICE_FUNC constexpr plain_array() {}
-  EIGEN_DEVICE_FUNC plain_array(constructor_without_unaligned_array_assert) {}
+  EIGEN_DEVICE_FUNC constexpr plain_array(constructor_without_unaligned_array_assert) {}
 };
 
 struct plain_array_helper {
@@ -201,57 +180,32 @@ struct plain_array_helper {
   *
   * \sa Matrix
   */
-template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage;
+template<typename T, int Size, int Rows_, int Cols_, int Options_> class DenseStorage;
 
 // purely fixed-size matrix
-template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage
+template<typename T, int Size, int Rows_, int Cols_, int Options_> class DenseStorage
 {
-    internal::plain_array<T,Size,_Options> m_data;
+    internal::plain_array<T,Size,Options_> m_data;
   public:
-    EIGEN_DEVICE_FUNC DenseStorage() {
+    constexpr EIGEN_DEVICE_FUNC DenseStorage() {
       EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
     }
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert)
-    explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()) {}
-#if !EIGEN_HAS_CXX11 || defined(EIGEN_DENSE_STORAGE_CTOR_PLUGIN)
+#if defined(EIGEN_DENSE_STORAGE_CTOR_PLUGIN)
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC constexpr
     DenseStorage(const DenseStorage& other) : m_data(other.m_data) {
       EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
     }
 #else
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage&) = default;
+    EIGEN_DEVICE_FUNC constexpr DenseStorage(const DenseStorage&) = default;
 #endif
-#if !EIGEN_HAS_CXX11
+    EIGEN_DEVICE_FUNC constexpr DenseStorage& operator=(const DenseStorage&) = default;
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC constexpr DenseStorage(DenseStorage&&) = default;
-    DenseStorage& operator=(const DenseStorage& other)
+    EIGEN_DEVICE_FUNC constexpr DenseStorage& operator=(DenseStorage&&) = default;
-    {
+    EIGEN_DEVICE_FUNC constexpr DenseStorage(Index size, Index rows, Index cols) {
-      if (this != &other) m_data = other.m_data;
-      return *this;
-    }
-#else
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage&) = default;
-#endif
-#if EIGEN_HAS_RVALUE_REFERENCES
-#if !EIGEN_HAS_CXX11
-    EIGEN_DEVICE_FUNC DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
-      : m_data(std::move(other.m_data))
-    {
-    }
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(DenseStorage&& other) EIGEN_NOEXCEPT
-    {
-      if (this != &other)
-        m_data = std::move(other.m_data);
-      return *this;
-    }
-#else
-    EIGEN_DEVICE_FUNC DenseStorage(DenseStorage&&) = default;
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(DenseStorage&&) = default;
-#endif
-#endif
-    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) {
       EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      eigen_internal_assert(size==rows*cols && rows==_Rows && cols==_Cols);
+      eigen_internal_assert(size == rows * cols && rows == Rows_ && cols == Cols_);
       EIGEN_UNUSED_VARIABLE(size);
       EIGEN_UNUSED_VARIABLE(rows);
       EIGEN_UNUSED_VARIABLE(cols);
@@ -259,55 +213,146 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
     EIGEN_DEVICE_FUNC void swap(DenseStorage& other) {
       numext::swap(m_data, other.m_data);
     }
-    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index rows(void) EIGEN_NOEXCEPT {return _Rows;}
+    EIGEN_DEVICE_FUNC static constexpr Index rows(void) EIGEN_NOEXCEPT { return Rows_; }
-    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index cols(void) EIGEN_NOEXCEPT {return _Cols;}
+    EIGEN_DEVICE_FUNC static constexpr Index cols(void) EIGEN_NOEXCEPT { return Cols_; }
-    EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index, Index, Index) {}
-    EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC constexpr void resize(Index, Index, Index) {}
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
+    EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
 };
 
 // null matrix
-template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
+template<typename T, int Rows_, int Cols_, int Options_>
+class DenseStorage<T, 0, Rows_, Cols_, Options_>
 {
   public:
-    EIGEN_DEVICE_FUNC DenseStorage() {}
+    static_assert(Rows_ * Cols_ == 0, "The fixed number of rows times columns must equal the storage size.");
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) {}
+    EIGEN_DEVICE_FUNC constexpr DenseStorage() {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage&) {}
+    EIGEN_DEVICE_FUNC explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert) {}
-    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage&) { return *this; }
+    EIGEN_DEVICE_FUNC constexpr DenseStorage(const DenseStorage&) {}
-    EIGEN_DEVICE_FUNC DenseStorage(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC constexpr DenseStorage& operator=(const DenseStorage&) { return *this; }
-    EIGEN_DEVICE_FUNC void swap(DenseStorage& ) {}
+    EIGEN_DEVICE_FUNC constexpr DenseStorage(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index rows(void) EIGEN_NOEXCEPT {return _Rows;}
+    EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage& ) {}
-    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index cols(void) EIGEN_NOEXCEPT {return _Cols;}
+    EIGEN_DEVICE_FUNC static constexpr Index rows(void) EIGEN_NOEXCEPT {return Rows_;}
-    EIGEN_DEVICE_FUNC void conservativeResize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC static constexpr Index cols(void) EIGEN_NOEXCEPT {return Cols_;}
-    EIGEN_DEVICE_FUNC void resize(Index,Index,Index) {}
+    EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC const T *data() const { return 0; }
+    EIGEN_DEVICE_FUNC constexpr void resize(Index,Index,Index) {}
-    EIGEN_DEVICE_FUNC T *data() { return 0; }
+    EIGEN_DEVICE_FUNC constexpr const T *data() const { return 0; }
+    EIGEN_DEVICE_FUNC constexpr T *data() { return 0; }
 };
 
 // more specializations for null matrices; these are necessary to resolve ambiguities
-template<typename T, int _Options> class DenseStorage<T, 0, Dynamic, Dynamic, _Options>
+template<typename T, int Options_>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
+class DenseStorage<T, 0, Dynamic, Dynamic, Options_> {
-
-template<typename T, int _Rows, int _Options> class DenseStorage<T, 0, _Rows, Dynamic, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
-template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic, _Cols, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
-// dynamic-size matrix with fixed-size storage
-template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
-{
-    internal::plain_array<T,Size,_Options> m_data;
     Index m_rows;
     Index m_cols;
   public:
     EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : DenseStorage() {}
-      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_rows(other.m_rows), m_cols(other.m_cols) {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) {
-      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(other.m_rows), m_cols(other.m_cols)
+      m_rows = other.m_rows;
+      m_cols = other.m_cols;
+      return *this;
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index cols) : m_rows(rows), m_cols(cols) {
+      eigen_assert(m_rows * m_cols == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) {
+      numext::swap(m_rows,other.m_rows);
+      numext::swap(m_cols,other.m_cols);
+    }
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT {return m_rows;}
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT {return m_cols;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index cols) {
+      m_rows = rows;
+      m_cols = cols;
+      eigen_assert(m_rows * m_cols == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index cols) {
+      m_rows = rows;
+      m_cols = cols;
+      eigen_assert(m_rows * m_cols == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC const T *data() const { return nullptr; }
+    EIGEN_DEVICE_FUNC T *data() { return nullptr; }
+};
+
+template<typename T, int Rows_, int Options_>
+class DenseStorage<T, 0, Rows_, Dynamic, Options_> {
+    Index m_cols;
+  public:
+    EIGEN_DEVICE_FUNC DenseStorage() : m_cols(0) {}
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : DenseStorage() {}
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_cols(other.m_cols) {}
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) {
+      m_cols = other.m_cols;
+      return *this;
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(Index, Index, Index cols) : m_cols(cols) {
+      eigen_assert(Rows_ * m_cols == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) {
+      numext::swap(m_cols, other.m_cols);
+    }
+    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index rows(void) EIGEN_NOEXCEPT {return Rows_;}
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index cols(void) const EIGEN_NOEXCEPT {return m_cols;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index, Index cols) {
+      m_cols = cols;
+      eigen_assert(Rows_ * m_cols == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC void resize(Index, Index, Index cols) {
+      m_cols = cols;
+      eigen_assert(Rows_ * m_cols == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC const T *data() const { return nullptr; }
+    EIGEN_DEVICE_FUNC T *data() { return nullptr; }
+};
+
+template<typename T, int Cols_, int Options_>
+class DenseStorage<T, 0, Dynamic, Cols_, Options_> {
+    Index m_rows;
+  public:
+    EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0) {}
+    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : DenseStorage() {}
+    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) : m_rows(other.m_rows) {}
+    EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other) {
+      m_rows = other.m_rows;
+      return *this;
+    }
+    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index) : m_rows(rows) {
+      eigen_assert(m_rows * Cols_ == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC void swap(DenseStorage& other) {
+      numext::swap(m_rows, other.m_rows);
+    }
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index rows(void) const EIGEN_NOEXCEPT {return m_rows;}
+    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index cols(void) EIGEN_NOEXCEPT {return Cols_;}
+    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index) {
+      m_rows = rows;
+      eigen_assert(m_rows * Cols_ == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index) {
+      m_rows = rows;
+      eigen_assert(m_rows * Cols_ == 0 && "The number of rows times columns must equal the storage size.");
+    }
+    EIGEN_DEVICE_FUNC const T *data() const { return nullptr; }
+    EIGEN_DEVICE_FUNC T *data() { return nullptr; }
+};
+
+// dynamic-size matrix with fixed-size storage
+template<typename T, int Size, int Options_>
+class DenseStorage<T, Size, Dynamic, Dynamic, Options_>
 {
+    internal::plain_array<T,Size,Options_> m_data;
+    Index m_rows;
+    Index m_cols;
+  public:
+   EIGEN_DEVICE_FUNC constexpr DenseStorage() : m_data(), m_rows(0), m_cols(0) {}
+   EIGEN_DEVICE_FUNC explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert)
+       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
+   EIGEN_DEVICE_FUNC constexpr DenseStorage(const DenseStorage& other)
+       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(other.m_rows), m_cols(other.m_cols) {
     internal::plain_array_helper::copy(other.m_data, m_rows * m_cols, m_data);
    }
     EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
@@ -320,34 +365,40 @@ template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic
       }
       return *this;
     }
-    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index cols) : m_rows(rows), m_cols(cols) {}
+    EIGEN_DEVICE_FUNC constexpr DenseStorage(Index, Index rows, Index cols) : m_rows(rows), m_cols(cols) {}
     EIGEN_DEVICE_FUNC void swap(DenseStorage& other)
     {
       internal::plain_array_helper::swap(m_data, m_rows * m_cols, other.m_data, other.m_rows * other.m_cols);
       numext::swap(m_rows,other.m_rows);
       numext::swap(m_cols,other.m_cols);
     }
-    EIGEN_DEVICE_FUNC Index rows() const {return m_rows;}
+    EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_rows; }
-    EIGEN_DEVICE_FUNC Index cols() const {return m_cols;}
+    EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_cols; }
-    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
+    EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index, Index rows, Index cols) {
-    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index cols) { m_rows = rows; m_cols = cols; }
+      m_rows = rows;
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+      m_cols = cols;
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
+    }
+    EIGEN_DEVICE_FUNC constexpr void resize(Index, Index rows, Index cols) {
+      m_rows = rows;
+      m_cols = cols;
+    }
+    EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
 };
 
 // dynamic-size matrix with fixed-size storage and fixed width
-template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
+template<typename T, int Size, int Cols_, int Options_>
+class DenseStorage<T, Size, Dynamic, Cols_, Options_>
 {
-    internal::plain_array<T,Size,_Options> m_data;
+    internal::plain_array<T,Size,Options_> m_data;
     Index m_rows;
   public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_rows(0) {}
+   EIGEN_DEVICE_FUNC constexpr DenseStorage() : m_rows(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
+   EIGEN_DEVICE_FUNC explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert)
        : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
+   EIGEN_DEVICE_FUNC constexpr DenseStorage(const DenseStorage& other)
-      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(other.m_rows)
+       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(other.m_rows) {
-    {
+      internal::plain_array_helper::copy(other.m_data, m_rows * Cols_, m_data);
-      internal::plain_array_helper::copy(other.m_data, m_rows * _Cols, m_data);
    }
 
     EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
@@ -355,78 +406,80 @@ template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Si
       if (this != &other)
       {
         m_rows = other.m_rows;
-        internal::plain_array_helper::copy(other.m_data, m_rows * _Cols, m_data);
+        internal::plain_array_helper::copy(other.m_data, m_rows * Cols_, m_data);
       }
       return *this;
     }
-    EIGEN_DEVICE_FUNC DenseStorage(Index, Index rows, Index) : m_rows(rows) {}
+    EIGEN_DEVICE_FUNC constexpr DenseStorage(Index, Index rows, Index) : m_rows(rows) {}
     EIGEN_DEVICE_FUNC void swap(DenseStorage& other)
     { 
-      internal::plain_array_helper::swap(m_data, m_rows * _Cols, other.m_data, other.m_rows * _Cols);
+      internal::plain_array_helper::swap(m_data, m_rows * Cols_, other.m_data, other.m_rows * Cols_);
       numext::swap(m_rows, other.m_rows);
     }
-    EIGEN_DEVICE_FUNC Index rows(void) const EIGEN_NOEXCEPT {return m_rows;}
+    EIGEN_DEVICE_FUNC constexpr Index rows(void) const EIGEN_NOEXCEPT { return m_rows; }
-    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index cols(void) const EIGEN_NOEXCEPT {return _Cols;}
+    EIGEN_DEVICE_FUNC constexpr Index cols(void) const EIGEN_NOEXCEPT { return Cols_; }
-    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index rows, Index) { m_rows = rows; }
+    EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index, Index rows, Index) { m_rows = rows; }
-    EIGEN_DEVICE_FUNC void resize(Index, Index rows, Index) { m_rows = rows; }
+    EIGEN_DEVICE_FUNC constexpr void resize(Index, Index rows, Index) { m_rows = rows; }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
+    EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
 };
 
 // dynamic-size matrix with fixed-size storage and fixed height
-template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
+template<typename T, int Size, int Rows_, int Options_>
+class DenseStorage<T, Size, Rows_, Dynamic, Options_>
 {
-    internal::plain_array<T,Size,_Options> m_data;
+    internal::plain_array<T,Size,Options_> m_data;
     Index m_cols;
   public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_cols(0) {}
+   EIGEN_DEVICE_FUNC constexpr DenseStorage() : m_cols(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
+   EIGEN_DEVICE_FUNC explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert)
        : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other) 
+   EIGEN_DEVICE_FUNC constexpr DenseStorage(const DenseStorage& other)
-      : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(other.m_cols)
+       : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(other.m_cols) {
-    {
+      internal::plain_array_helper::copy(other.m_data, Rows_ * m_cols, m_data);
-      internal::plain_array_helper::copy(other.m_data, _Rows * m_cols, m_data);
    }
     EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
     {
       if (this != &other)
       {
         m_cols = other.m_cols;
-        internal::plain_array_helper::copy(other.m_data, _Rows * m_cols, m_data);
+        internal::plain_array_helper::copy(other.m_data, Rows_ * m_cols, m_data);
       }
       return *this;
     }
     EIGEN_DEVICE_FUNC DenseStorage(Index, Index, Index cols) : m_cols(cols) {}
     EIGEN_DEVICE_FUNC void swap(DenseStorage& other) {
-      internal::plain_array_helper::swap(m_data, _Rows * m_cols, other.m_data, _Rows * other.m_cols);
+      internal::plain_array_helper::swap(m_data, Rows_ * m_cols, other.m_data, Rows_ * other.m_cols);
       numext::swap(m_cols, other.m_cols);
     }
-    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index rows(void) const EIGEN_NOEXCEPT {return _Rows;}
+    EIGEN_DEVICE_FUNC constexpr Index rows(void) const EIGEN_NOEXCEPT { return Rows_; }
-    EIGEN_DEVICE_FUNC Index cols(void) const EIGEN_NOEXCEPT {return m_cols;}
+    EIGEN_DEVICE_FUNC constexpr Index cols(void) const EIGEN_NOEXCEPT { return m_cols; }
-    EIGEN_DEVICE_FUNC void conservativeResize(Index, Index, Index cols) { m_cols = cols; }
+    EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index, Index, Index cols) { m_cols = cols; }
-    EIGEN_DEVICE_FUNC void resize(Index, Index, Index cols) { m_cols = cols; }
+    EIGEN_DEVICE_FUNC constexpr void resize(Index, Index, Index cols) { m_cols = cols; }
-    EIGEN_DEVICE_FUNC const T *data() const { return m_data.array; }
+    EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
-    EIGEN_DEVICE_FUNC T *data() { return m_data.array; }
+    EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
 };
 
 // purely dynamic matrix.
-template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
+template<typename T, int Options_>
+class DenseStorage<T, Dynamic, Dynamic, Dynamic, Options_>
 {
     T *m_data;
     Index m_rows;
     Index m_cols;
   public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
+   EIGEN_DEVICE_FUNC constexpr DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC explicit DenseStorage(internal::constructor_without_unaligned_array_assert)
+   EIGEN_DEVICE_FUNC explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert)
        : m_data(0), m_rows(0), m_cols(0) {}
    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols)
+       : m_data(internal::conditional_aligned_new_auto<T, (Options_ & DontAlign) == 0>(size)),
-    {
+         m_rows(rows),
+         m_cols(cols) {
       EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
       eigen_internal_assert(size==rows*cols && rows>=0 && cols >=0);
    }
     EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*other.m_cols))
+      : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(other.m_rows*other.m_cols))
       , m_rows(other.m_rows)
       , m_cols(other.m_cols)
     {
@@ -442,7 +495,6 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
       }
       return *this;
     }
-#if EIGEN_HAS_RVALUE_REFERENCES
     EIGEN_DEVICE_FUNC
     DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
       : m_data(std::move(other.m_data))
@@ -461,8 +513,7 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
       numext::swap(m_cols, other.m_cols);
       return *this;
     }
-#endif
+    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, m_rows*m_cols); }
-    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
     EIGEN_DEVICE_FUNC void swap(DenseStorage& other)
     {
       numext::swap(m_data,other.m_data);
@@ -473,7 +524,7 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
     EIGEN_DEVICE_FUNC Index cols(void) const EIGEN_NOEXCEPT {return m_cols;}
     void conservativeResize(Index size, Index rows, Index cols)
     {
-      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(Options_&DontAlign)==0>(m_data, size, m_rows*m_cols);
       m_rows = rows;
       m_cols = cols;
     }
@@ -481,9 +532,9 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
     {
       if(size != m_rows*m_cols)
       {
-        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols);
+        internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, m_rows*m_cols);
         if (size>0) // >0 and not simply !=0 to let the compiler knows that size cannot be negative
-          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+          m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size);
         else
           m_data = 0;
         EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
@@ -496,25 +547,25 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
 };
 
 // matrix with dynamic width and fixed height (so that matrix has dynamic size).
-template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
+template<typename T, int Rows_, int Options_>
-{
+class DenseStorage<T, Dynamic, Rows_, Dynamic, Options_> {
     T *m_data;
     Index m_cols;
   public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_cols(0) {}
+   EIGEN_DEVICE_FUNC constexpr DenseStorage() : m_data(0), m_cols(0) {}
-    explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
+   explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
+   EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols)
-    {
+       : m_data(internal::conditional_aligned_new_auto<T, (Options_ & DontAlign) == 0>(size)), m_cols(cols) {
       EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      eigen_internal_assert(size==rows*cols && rows==_Rows && cols >=0);
+      eigen_internal_assert(size==rows*cols && rows==Rows_ && cols >=0);
       EIGEN_UNUSED_VARIABLE(rows);
    }
     EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(_Rows*other.m_cols))
+      : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(Rows_*other.m_cols))
       , m_cols(other.m_cols)
     {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_cols*_Rows)
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_cols*Rows_)
-      internal::smart_copy(other.m_data, other.m_data+_Rows*m_cols, m_data);
+      internal::smart_copy(other.m_data, other.m_data+Rows_*m_cols, m_data);
     }
     EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
     {
@@ -525,7 +576,6 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
       }
       return *this;
     }
-#if EIGEN_HAS_RVALUE_REFERENCES
     EIGEN_DEVICE_FUNC
     DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
       : m_data(std::move(other.m_data))
@@ -541,26 +591,25 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
       numext::swap(m_cols, other.m_cols);
       return *this;
     }
-#endif
+    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, Rows_*m_cols); }
-    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
     EIGEN_DEVICE_FUNC void swap(DenseStorage& other) {
       numext::swap(m_data,other.m_data);
       numext::swap(m_cols,other.m_cols);
     }
-    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index rows(void) EIGEN_NOEXCEPT {return _Rows;}
+    EIGEN_DEVICE_FUNC static constexpr Index rows(void) EIGEN_NOEXCEPT { return Rows_; }
     EIGEN_DEVICE_FUNC Index cols(void) const EIGEN_NOEXCEPT {return m_cols;}
     EIGEN_DEVICE_FUNC void conservativeResize(Index size, Index, Index cols)
     {
-      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(Options_&DontAlign)==0>(m_data, size, Rows_*m_cols);
       m_cols = cols;
     }
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index, Index cols)
     {
-      if(size != _Rows*m_cols)
+      if(size != Rows_*m_cols)
       {
-        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols);
+        internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, Rows_*m_cols);
         if (size>0) // >0 and not simply !=0 to let the compiler knows that size cannot be negative
-          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+          m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size);
         else
           m_data = 0;
         EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
@@ -572,25 +621,26 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
 };
 
 // matrix with dynamic height and fixed width (so that matrix has dynamic size).
-template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
+template<typename T, int Cols_, int Options_>
+class DenseStorage<T, Dynamic, Dynamic, Cols_, Options_>
 {
     T *m_data;
     Index m_rows;
   public:
-    EIGEN_DEVICE_FUNC DenseStorage() : m_data(0), m_rows(0) {}
+   EIGEN_DEVICE_FUNC constexpr DenseStorage() : m_data(0), m_rows(0) {}
-    explicit DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
+   explicit constexpr DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
-    EIGEN_DEVICE_FUNC DenseStorage(Index size, Index rows, Index cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
+   EIGEN_DEVICE_FUNC constexpr DenseStorage(Index size, Index rows, Index cols)
-    {
+       : m_data(internal::conditional_aligned_new_auto<T, (Options_ & DontAlign) == 0>(size)), m_rows(rows) {
       EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-      eigen_internal_assert(size==rows*cols && rows>=0 && cols == _Cols);
+      eigen_internal_assert(size==rows*cols && rows>=0 && cols == Cols_);
       EIGEN_UNUSED_VARIABLE(cols);
    }
     EIGEN_DEVICE_FUNC DenseStorage(const DenseStorage& other)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(other.m_rows*_Cols))
+      : m_data(internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(other.m_rows*Cols_))
       , m_rows(other.m_rows)
     {
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*_Cols)
+      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = m_rows*Cols_)
-      internal::smart_copy(other.m_data, other.m_data+other.m_rows*_Cols, m_data);
+      internal::smart_copy(other.m_data, other.m_data+other.m_rows*Cols_, m_data);
     }
     EIGEN_DEVICE_FUNC DenseStorage& operator=(const DenseStorage& other)
     {
@@ -601,7 +651,6 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
       }
       return *this;
     }
-#if EIGEN_HAS_RVALUE_REFERENCES
     EIGEN_DEVICE_FUNC
     DenseStorage(DenseStorage&& other) EIGEN_NOEXCEPT
       : m_data(std::move(other.m_data))
@@ -617,26 +666,25 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
       numext::swap(m_rows, other.m_rows);
       return *this;
     }
-#endif
+    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, Cols_*m_rows); }
-    EIGEN_DEVICE_FUNC ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
     EIGEN_DEVICE_FUNC void swap(DenseStorage& other) {
       numext::swap(m_data,other.m_data);
       numext::swap(m_rows,other.m_rows);
     }
     EIGEN_DEVICE_FUNC Index rows(void) const EIGEN_NOEXCEPT {return m_rows;}
-    EIGEN_DEVICE_FUNC static EIGEN_CONSTEXPR Index cols(void) {return _Cols;}
+    EIGEN_DEVICE_FUNC static constexpr Index cols(void) { return Cols_; }
     void conservativeResize(Index size, Index rows, Index)
     {
-      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(Options_&DontAlign)==0>(m_data, size, m_rows*Cols_);
       m_rows = rows;
     }
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index size, Index rows, Index)
     {
-      if(size != m_rows*_Cols)
+      if(size != m_rows*Cols_)
       {
-        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows);
+        internal::conditional_aligned_delete_auto<T,(Options_&DontAlign)==0>(m_data, Cols_*m_rows);
         if (size>0) // >0 and not simply !=0 to let the compiler knows that size cannot be negative
-          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+          m_data = internal::conditional_aligned_new_auto<T,(Options_&DontAlign)==0>(size);
         else
           m_data = 0;
         EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})

libs/eigen/Eigen/src/Core/Diagonal.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_DIAGONAL_H
 #define EIGEN_DIAGONAL_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class Diagonal
@@ -18,8 +20,8 @@ namespace Eigen {
   *
   * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
   *
-  * \param MatrixType the type of the object in which we are taking a sub/main/super diagonal
+  * \tparam MatrixType the type of the object in which we are taking a sub/main/super diagonal
-  * \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
+  * \tparam DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
   *              A positive value means a superdiagonal, a negative value means a subdiagonal.
   *              You can also use DynamicIndex so the index can be set at runtime.
   *
@@ -38,21 +40,21 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
  : traits<MatrixType>
 {
   typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef std::remove_reference_t<MatrixTypeNested> MatrixTypeNested_;
   typedef typename MatrixType::StorageKind StorageKind;
   enum {
     RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
-                      : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                      : (plain_enum_min(MatrixType::RowsAtCompileTime - plain_enum_max(-DiagIndex, 0),
-                                              MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
+                                        MatrixType::ColsAtCompileTime - plain_enum_max( DiagIndex, 0))),
     ColsAtCompileTime = 1,
     MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
-                         : DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
+                         : DiagIndex == DynamicIndex ? min_size_prefer_fixed(MatrixType::MaxRowsAtCompileTime,
                                                                              MatrixType::MaxColsAtCompileTime)
-                         : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                         : (plain_enum_min(MatrixType::MaxRowsAtCompileTime - plain_enum_max(-DiagIndex, 0),
-                                                 MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
+                                           MatrixType::MaxColsAtCompileTime - plain_enum_max( DiagIndex, 0))),
     MaxColsAtCompileTime = 1,
     MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags = (unsigned int)_MatrixTypeNested::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions
+    Flags = (unsigned int)MatrixTypeNested_::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions
     MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
     InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
     OuterStrideAtCompileTime = 0
@@ -60,12 +62,12 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
 };
 }
 
-template<typename MatrixType, int _DiagIndex> class Diagonal
+template<typename MatrixType, int DiagIndex_> class Diagonal
-   : public internal::dense_xpr_base< Diagonal<MatrixType,_DiagIndex> >::type
+   : public internal::dense_xpr_base< Diagonal<MatrixType,DiagIndex_> >::type
 {
   public:
 
-    enum { DiagIndex = _DiagIndex };
+    enum { DiagIndex = DiagIndex_ };
     typedef typename internal::dense_xpr_base<Diagonal>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
 
@@ -95,11 +97,11 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
     EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
     inline Index outerStride() const EIGEN_NOEXCEPT { return 0; }
 
-    typedef typename internal::conditional<
+    typedef std::conditional_t<
               internal::is_lvalue<MatrixType>::value,
               Scalar,
               const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
+            > ScalarWithConstIfNotLvalue;
 
     EIGEN_DEVICE_FUNC
     inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
@@ -145,7 +147,7 @@ template<typename MatrixType, int _DiagIndex> class Diagonal
     }
 
     EIGEN_DEVICE_FUNC
-    inline const typename internal::remove_all<typename MatrixType::Nested>::type&
+    inline const internal::remove_all_t<typename MatrixType::Nested>&
     nestedExpression() const
     {
       return m_matrix;
@@ -191,7 +193,8 @@ MatrixBase<Derived>::diagonal()
 
 /** This is the const version of diagonal(). */
 template<typename Derived>
-EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::ConstDiagonalReturnType
+EIGEN_DEVICE_FUNC inline
+const typename MatrixBase<Derived>::ConstDiagonalReturnType
 MatrixBase<Derived>::diagonal() const
 {
   return ConstDiagonalReturnType(derived());
@@ -209,18 +212,18 @@ MatrixBase<Derived>::diagonal() const
   *
   * \sa MatrixBase::diagonal(), class Diagonal */
 template<typename Derived>
-EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType
+EIGEN_DEVICE_FUNC inline Diagonal<Derived, DynamicIndex>
 MatrixBase<Derived>::diagonal(Index index)
 {
-  return DiagonalDynamicIndexReturnType(derived(), index);
+  return Diagonal<Derived, DynamicIndex>(derived(), index);
 }
 
 /** This is the const version of diagonal(Index). */
 template<typename Derived>
-EIGEN_DEVICE_FUNC inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType
+EIGEN_DEVICE_FUNC inline const Diagonal<const Derived, DynamicIndex>
 MatrixBase<Derived>::diagonal(Index index) const
 {
-  return ConstDiagonalDynamicIndexReturnType(derived(), index);
+  return Diagonal<const Derived, DynamicIndex>(derived(), index);
 }
 
 /** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
@@ -237,20 +240,20 @@ MatrixBase<Derived>::diagonal(Index index) const
 template<typename Derived>
 template<int Index_>
 EIGEN_DEVICE_FUNC
-inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index_>::Type
+inline Diagonal<Derived, Index_>
 MatrixBase<Derived>::diagonal()
 {
-  return typename DiagonalIndexReturnType<Index_>::Type(derived());
+  return Diagonal<Derived, Index_>(derived());
 }
 
 /** This is the const version of diagonal<int>(). */
 template<typename Derived>
 template<int Index_>
 EIGEN_DEVICE_FUNC
-inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index_>::Type
+inline const Diagonal<const Derived, Index_>
 MatrixBase<Derived>::diagonal() const
 {
-  return typename ConstDiagonalIndexReturnType<Index_>::Type(derived());
+  return  Diagonal<const Derived, Index_>(derived());
 }
 
 } // end namespace Eigen

libs/eigen/Eigen/src/Core/DiagonalMatrix.h

@@ -11,9 +11,23 @@
 #ifndef EIGEN_DIAGONALMATRIX_H
 #define EIGEN_DIAGONALMATRIX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
+/** \class DiagonalBase
+ * \ingroup Core_Module
+ *
+ * \brief Base class for diagonal matrices and expressions
+ *
+ * This is the base class that is inherited by diagonal matrix and related expression
+ * types, which internally use a vector for storing the diagonal entries. Diagonal
+ * types always represent square matrices.
+ *
+ * \tparam Derived is the derived type, a DiagonalMatrix or DiagonalWrapper.
+ *
+ * \sa class DiagonalMatrix, class DiagonalWrapper
+ */
 template<typename Derived>
 class DiagonalBase : public EigenBase<Derived>
 {
@@ -37,24 +51,35 @@ class DiagonalBase : public EigenBase<Derived>
     typedef DenseMatrixType DenseType;
     typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject;
 
+    /** \returns a reference to the derived object. */
     EIGEN_DEVICE_FUNC
     inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    /** \returns a const reference to the derived object. */
     EIGEN_DEVICE_FUNC
     inline Derived& derived() { return *static_cast<Derived*>(this); }
 
+    /**
+     * Constructs a dense matrix from \c *this. Note, this directly returns a dense matrix type,
+     * not an expression.
+     * \returns A dense matrix, with its diagonal entries set from the the derived object. */
     EIGEN_DEVICE_FUNC
     DenseMatrixType toDenseMatrix() const { return derived(); }
 
+    /** \returns a reference to the derived object's vector of diagonal coefficients. */
     EIGEN_DEVICE_FUNC
     inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
+    /** \returns a const reference to the derived object's vector of diagonal coefficients. */
     EIGEN_DEVICE_FUNC
     inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
 
-    EIGEN_DEVICE_FUNC
+    /** \returns the number of rows. */
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR 
     inline Index rows() const { return diagonal().size(); }
-    EIGEN_DEVICE_FUNC
+    /** \returns the number of columns. */
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR 
     inline Index cols() const { return diagonal().size(); }
 
+    /** \returns the diagonal matrix product of \c *this by the dense matrix, \a matrix */
     template<typename MatrixDerived>
     EIGEN_DEVICE_FUNC
     const Product<Derived,MatrixDerived,LazyProduct>
@@ -63,88 +88,99 @@ class DiagonalBase : public EigenBase<Derived>
       return Product<Derived, MatrixDerived, LazyProduct>(derived(),matrix.derived());
     }
 
-    typedef DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> > InverseReturnType;
+    template <typename OtherDerived>
-    EIGEN_DEVICE_FUNC
+    using DiagonalProductReturnType = DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
-    inline const InverseReturnType
+        DiagonalVectorType, typename OtherDerived::DiagonalVectorType, product)>;
-    inverse() const
+
-    {
+    /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a other */
-      return InverseReturnType(diagonal().cwiseInverse());
+    template <typename OtherDerived>
+    EIGEN_DEVICE_FUNC const DiagonalProductReturnType<OtherDerived> operator*(
+        const DiagonalBase<OtherDerived>& other) const {
+      return diagonal().cwiseProduct(other.diagonal()).asDiagonal();
     }
 
+    using DiagonalInverseReturnType =
+        DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType>>;
+
+    /** \returns the inverse \c *this. Computed as the coefficient-wise inverse of the diagonal. */
     EIGEN_DEVICE_FUNC
-    inline const DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType,Scalar,product) >
+    inline const DiagonalInverseReturnType inverse() const { return diagonal().cwiseInverse().asDiagonal(); }
-    operator*(const Scalar& scalar) const
+
-    {
+    using DiagonalScaleReturnType =
-      return DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType,Scalar,product) >(diagonal() * scalar);
+        DiagonalWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(DiagonalVectorType, Scalar, product)>;
+
+    /** \returns the product of \c *this by the scalar \a scalar */
+    EIGEN_DEVICE_FUNC
+    inline const DiagonalScaleReturnType operator*(const Scalar& scalar) const {
+      return (diagonal() * scalar).asDiagonal();
     }
+
+    using ScaleDiagonalReturnType =
+        DiagonalWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar, DiagonalVectorType, product)>;
+
+    /** \returns the product of a scalar and the diagonal matrix \a other */
     EIGEN_DEVICE_FUNC
-    friend inline const DiagonalWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,DiagonalVectorType,product) >
+    friend inline const ScaleDiagonalReturnType operator*(const Scalar& scalar, const DiagonalBase& other) {
-    operator*(const Scalar& scalar, const DiagonalBase& other)
+      return (scalar * other.diagonal()).asDiagonal();
-    {
-      return DiagonalWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar,DiagonalVectorType,product) >(scalar * other.diagonal());
     }
 
     template <typename OtherDerived>
-    EIGEN_DEVICE_FUNC
+    using DiagonalSumReturnType = DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
-    #ifdef EIGEN_PARSED_BY_DOXYGEN
+        DiagonalVectorType, typename OtherDerived::DiagonalVectorType, sum)>;
-    inline unspecified_expression_type
+
-    #else
+    /** \returns the sum of \c *this and the diagonal matrix \a other */
-    inline const DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(DiagonalVectorType,typename OtherDerived::DiagonalVectorType,sum) >
+    template <typename OtherDerived>
-    #endif
+    EIGEN_DEVICE_FUNC inline const DiagonalSumReturnType<OtherDerived> operator+(
-    operator+(const DiagonalBase<OtherDerived>& other) const
+        const DiagonalBase<OtherDerived>& other) const {
-    {
       return (diagonal() + other.diagonal()).asDiagonal();
     }
 
     template <typename OtherDerived>
-    EIGEN_DEVICE_FUNC
+    using DiagonalDifferenceReturnType = DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
-    #ifdef EIGEN_PARSED_BY_DOXYGEN
+        DiagonalVectorType, typename OtherDerived::DiagonalVectorType, difference)>;
-    inline unspecified_expression_type
+
-    #else
+    /** \returns the difference of \c *this and the diagonal matrix \a other */
-    inline const DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(DiagonalVectorType,typename OtherDerived::DiagonalVectorType,difference) >
+    template <typename OtherDerived>
-    #endif
+    EIGEN_DEVICE_FUNC inline const DiagonalDifferenceReturnType<OtherDerived> operator-(
-    operator-(const DiagonalBase<OtherDerived>& other) const
+        const DiagonalBase<OtherDerived>& other) const {
-    {
       return (diagonal() - other.diagonal()).asDiagonal();
     }
 };
 
-#endif
-
 /** \class DiagonalMatrix
  * \ingroup Core_Module
  *
  * \brief Represents a diagonal matrix with its storage
  *
-  * \param _Scalar the type of coefficients
+ * \tparam Scalar_ the type of coefficients
-  * \param SizeAtCompileTime the dimension of the matrix, or Dynamic
+ * \tparam SizeAtCompileTime the dimension of the matrix, or Dynamic
-  * \param MaxSizeAtCompileTime the dimension of the matrix, or Dynamic. This parameter is optional and defaults
+ * \tparam MaxSizeAtCompileTime the dimension of the matrix, or Dynamic. This parameter is optional and defaults
  *        to SizeAtCompileTime. Most of the time, you do not need to specify it.
  *
-  * \sa class DiagonalWrapper
+ * \sa class DiagonalBase, class DiagonalWrapper
  */
 
 namespace internal {
-template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
+template<typename Scalar_, int SizeAtCompileTime, int MaxSizeAtCompileTime>
-struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
+struct traits<DiagonalMatrix<Scalar_,SizeAtCompileTime,MaxSizeAtCompileTime> >
- : traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
+ : traits<Matrix<Scalar_,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
 {
-  typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
+  typedef Matrix<Scalar_,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
   typedef DiagonalShape StorageKind;
   enum {
-    Flags = LvalueBit | NoPreferredStorageOrderBit
+    Flags = LvalueBit | NoPreferredStorageOrderBit | NestByRefBit
   };
 };
 }
-template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
+template<typename Scalar_, int SizeAtCompileTime, int MaxSizeAtCompileTime>
 class DiagonalMatrix
-  : public DiagonalBase<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
+  : public DiagonalBase<DiagonalMatrix<Scalar_,SizeAtCompileTime,MaxSizeAtCompileTime> >
 {
   public:
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     typedef typename internal::traits<DiagonalMatrix>::DiagonalVectorType DiagonalVectorType;
     typedef const DiagonalMatrix& Nested;
-    typedef _Scalar Scalar;
+    typedef Scalar_ Scalar;
     typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
     typedef typename internal::traits<DiagonalMatrix>::StorageIndex StorageIndex;
     #endif
@@ -178,10 +214,7 @@ class DiagonalMatrix
     EIGEN_DEVICE_FUNC
     inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {}
 
-    #if EIGEN_HAS_CXX11
+    /** \brief Construct a diagonal matrix with fixed size from an arbitrary number of coefficients.
-    /** \brief Construct a diagonal matrix with fixed size from an arbitrary number of coefficients. \cpp11
-      * 
-      * There exists C++98 anologue constructors for fixed-size diagonal matrices having 2 or 3 coefficients.
       * 
       * \warning To construct a diagonal matrix of fixed size, the number of values passed to this 
       * constructor must match the fixed dimension of \c *this.
@@ -200,7 +233,10 @@ class DiagonalMatrix
     EIGEN_DEVICE_FUNC
     explicit EIGEN_STRONG_INLINE DiagonalMatrix(const std::initializer_list<std::initializer_list<Scalar>>& list)
       : m_diagonal(list) {}
-    #endif  // EIGEN_HAS_CXX11
+
+    /** \brief Constructs a DiagonalMatrix from an r-value diagonal vector type */
+    EIGEN_DEVICE_FUNC
+    explicit inline DiagonalMatrix(DiagonalVectorType&& diag) : m_diagonal(std::move(diag)) {}
 
     /** Copy constructor. */
     template<typename OtherDerived>
@@ -239,6 +275,22 @@ class DiagonalMatrix
     }
     #endif
 
+    typedef DiagonalWrapper<const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, DiagonalVectorType>>
+        InitializeReturnType;
+
+    /** Initializes a diagonal matrix of size SizeAtCompileTime with coefficients set to zero */
+    EIGEN_DEVICE_FUNC
+    static const InitializeReturnType Zero() { return DiagonalVectorType::Zero().asDiagonal(); }
+    /** Initializes a diagonal matrix of size dim with coefficients set to zero */
+    EIGEN_DEVICE_FUNC
+    static const InitializeReturnType Zero(Index size) { return DiagonalVectorType::Zero(size).asDiagonal(); }
+    /** Initializes a identity matrix of size SizeAtCompileTime */
+    EIGEN_DEVICE_FUNC
+    static const InitializeReturnType Identity() { return DiagonalVectorType::Ones().asDiagonal(); }
+    /** Initializes a identity matrix of size dim */
+    EIGEN_DEVICE_FUNC
+    static const InitializeReturnType Identity(Index size) { return DiagonalVectorType::Ones(size).asDiagonal(); }
+
     /** Resizes to given size. */
     EIGEN_DEVICE_FUNC
     inline void resize(Index size) { m_diagonal.resize(size); }
@@ -261,7 +313,7 @@ class DiagonalMatrix
   *
   * \brief Expression of a diagonal matrix
   *
-  * \param _DiagonalVectorType the type of the vector of diagonal coefficients
+  * \tparam DiagonalVectorType_ the type of the vector of diagonal coefficients
   *
   * This class is an expression of a diagonal matrix, but not storing its own vector of diagonal coefficients,
   * instead wrapping an existing vector expression. It is the return type of MatrixBase::asDiagonal()
@@ -271,10 +323,10 @@ class DiagonalMatrix
   */
 
 namespace internal {
-template<typename _DiagonalVectorType>
+template<typename DiagonalVectorType_>
-struct traits<DiagonalWrapper<_DiagonalVectorType> >
+struct traits<DiagonalWrapper<DiagonalVectorType_> >
 {
-  typedef _DiagonalVectorType DiagonalVectorType;
+  typedef DiagonalVectorType_ DiagonalVectorType;
   typedef typename DiagonalVectorType::Scalar Scalar;
   typedef typename DiagonalVectorType::StorageIndex StorageIndex;
   typedef DiagonalShape StorageKind;
@@ -289,13 +341,13 @@ struct traits<DiagonalWrapper<_DiagonalVectorType> >
 };
 }
 
-template<typename _DiagonalVectorType>
+template<typename DiagonalVectorType_>
 class DiagonalWrapper
-  : public DiagonalBase<DiagonalWrapper<_DiagonalVectorType> >, internal::no_assignment_operator
+  : public DiagonalBase<DiagonalWrapper<DiagonalVectorType_> >, internal::no_assignment_operator
 {
   public:
     #ifndef EIGEN_PARSED_BY_DOXYGEN
-    typedef _DiagonalVectorType DiagonalVectorType;
+    typedef DiagonalVectorType_ DiagonalVectorType;
     typedef DiagonalWrapper Nested;
     #endif
 

libs/eigen/Eigen/src/Core/DiagonalProduct.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_DIAGONALPRODUCT_H
 #define EIGEN_DIAGONALPRODUCT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.

libs/eigen/Eigen/src/Core/Dot.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_DOT_H
 #define EIGEN_DOT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
@@ -18,14 +20,9 @@ namespace internal {
 // with mismatched types, the compiler emits errors about failing to instantiate cwiseProduct BEFORE
 // looking at the static assertions. Thus this is a trick to get better compile errors.
 template<typename T, typename U,
-// the NeedToTranspose condition here is taken straight from Assign.h
+         bool NeedToTranspose = T::IsVectorAtCompileTime && U::IsVectorAtCompileTime &&
-         bool NeedToTranspose = T::IsVectorAtCompileTime
+                ((int(T::RowsAtCompileTime) == 1 && int(U::ColsAtCompileTime) == 1) ||
-                && U::IsVectorAtCompileTime
+                 (int(T::ColsAtCompileTime) == 1 && int(U::RowsAtCompileTime) == 1))>
-                && ((int(T::RowsAtCompileTime) == 1 && int(U::ColsAtCompileTime) == 1)
-                      |  // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
-                         // revert to || as soon as not needed anymore.
-                    (int(T::ColsAtCompileTime) == 1 && int(U::RowsAtCompileTime) == 1))
->
 struct dot_nocheck
 {
   typedef scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> conj_prod;
@@ -123,8 +120,8 @@ template<typename Derived>
 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
 MatrixBase<Derived>::normalized() const
 {
-  typedef typename internal::nested_eval<Derived,2>::type _Nested;
+  typedef typename internal::nested_eval<Derived,2>::type Nested_;
-  _Nested n(derived());
+  Nested_ n(derived());
   RealScalar z = n.squaredNorm();
   // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
   if(z>RealScalar(0))
@@ -166,8 +163,8 @@ template<typename Derived>
 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::PlainObject
 MatrixBase<Derived>::stableNormalized() const
 {
-  typedef typename internal::nested_eval<Derived,3>::type _Nested;
+  typedef typename internal::nested_eval<Derived,3>::type Nested_;
-  _Nested n(derived());
+  Nested_ n(derived());
   RealScalar w = n.cwiseAbs().maxCoeff();
   RealScalar z = (n/w).squaredNorm();
   if(z>RealScalar(0))

libs/eigen/Eigen/src/Core/EigenBase.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_EIGENBASE_H
 #define EIGEN_EIGENBASE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class EigenBase

libs/eigen/Eigen/src/Core/ForceAlignedAccess.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_FORCEALIGNEDACCESS_H
 #define EIGEN_FORCEALIGNEDACCESS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class ForceAlignedAccess
@@ -128,7 +130,7 @@ MatrixBase<Derived>::forceAlignedAccess()
   */
 template<typename Derived>
 template<bool Enable>
-inline typename internal::add_const_on_value_type<typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type>::type
+inline add_const_on_value_type_t<std::conditional_t<Enable,ForceAlignedAccess<Derived>,Derived&>>
 MatrixBase<Derived>::forceAlignedAccessIf() const
 {
   return derived();  // FIXME This should not work but apparently is never used
@@ -139,7 +141,7 @@ MatrixBase<Derived>::forceAlignedAccessIf() const
   */
 template<typename Derived>
 template<bool Enable>
-inline typename internal::conditional<Enable,ForceAlignedAccess<Derived>,Derived&>::type
+inline std::conditional_t<Enable,ForceAlignedAccess<Derived>,Derived&>
 MatrixBase<Derived>::forceAlignedAccessIf()
 {
   return derived();  // FIXME This should not work but apparently is never used

libs/eigen/Eigen/src/Core/Fuzzy.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_FUZZY_H
 #define EIGEN_FUZZY_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal

libs/eigen/Eigen/src/Core/GeneralProduct.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_GENERAL_PRODUCT_H
 #define EIGEN_GENERAL_PRODUCT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 enum {
@@ -50,17 +52,17 @@ template<int Size, int MaxSize> struct product_size_category
 
 template<typename Lhs, typename Rhs> struct product_type
 {
-  typedef typename remove_all<Lhs>::type _Lhs;
+  typedef remove_all_t<Lhs> Lhs_;
-  typedef typename remove_all<Rhs>::type _Rhs;
+  typedef remove_all_t<Rhs> Rhs_;
   enum {
-    MaxRows = traits<_Lhs>::MaxRowsAtCompileTime,
+    MaxRows = traits<Lhs_>::MaxRowsAtCompileTime,
-    Rows    = traits<_Lhs>::RowsAtCompileTime,
+    Rows    = traits<Lhs_>::RowsAtCompileTime,
-    MaxCols = traits<_Rhs>::MaxColsAtCompileTime,
+    MaxCols = traits<Rhs_>::MaxColsAtCompileTime,
-    Cols    = traits<_Rhs>::ColsAtCompileTime,
+    Cols    = traits<Rhs_>::ColsAtCompileTime,
-    MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::MaxColsAtCompileTime,
+    MaxDepth = min_size_prefer_fixed(traits<Lhs_>::MaxColsAtCompileTime,
-                                           traits<_Rhs>::MaxRowsAtCompileTime),
+                                     traits<Rhs_>::MaxRowsAtCompileTime),
-    Depth = EIGEN_SIZE_MIN_PREFER_FIXED(traits<_Lhs>::ColsAtCompileTime,
+    Depth = min_size_prefer_fixed(traits<Lhs_>::ColsAtCompileTime,
-                                        traits<_Rhs>::RowsAtCompileTime)
+                                  traits<Rhs_>::RowsAtCompileTime)
   };
 
   // the splitting into different lines of code here, introducing the _select enums and the typedef below,
@@ -180,12 +182,13 @@ struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
     PacketSize      = internal::packet_traits<Scalar>::size
   };
   #if EIGEN_MAX_STATIC_ALIGN_BYTES!=0
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0,EIGEN_PLAIN_ENUM_MIN(AlignedMax,PacketSize)> m_data;
+  internal::plain_array<Scalar, internal::min_size_prefer_fixed(Size, MaxSize), 0,
+                        internal::plain_enum_min(AlignedMax, PacketSize)> m_data;
   EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
   #else
   // Some architectures cannot align on the stack,
   // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?EIGEN_MAX_ALIGN_BYTES:0),0> m_data;
+  internal::plain_array<Scalar, internal::min_size_prefer_fixed(Size, MaxSize)+(ForceAlignment?EIGEN_MAX_ALIGN_BYTES:0),0> m_data;
   EIGEN_STRONG_INLINE Scalar* data() {
     return ForceAlignment
             ? reinterpret_cast<Scalar*>((internal::UIntPtr(m_data.array) & ~(std::size_t(EIGEN_MAX_ALIGN_BYTES-1))) + EIGEN_MAX_ALIGN_BYTES)
@@ -216,14 +219,13 @@ template<> struct gemv_dense_selector<OnTheRight,ColMajor,true>
     typedef typename Lhs::Scalar   LhsScalar;
     typedef typename Rhs::Scalar   RhsScalar;
     typedef typename Dest::Scalar  ResScalar;
-    typedef typename Dest::RealScalar  RealScalar;
     
     typedef internal::blas_traits<Lhs> LhsBlasTraits;
     typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
     typedef internal::blas_traits<Rhs> RhsBlasTraits;
     typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
   
-    typedef Map<Matrix<ResScalar,Dynamic,1>, EIGEN_PLAIN_ENUM_MIN(AlignedMax,internal::packet_traits<ResScalar>::size)> MappedDest;
+    typedef Map<Matrix<ResScalar,Dynamic,1>, plain_enum_min(AlignedMax, internal::packet_traits<ResScalar>::size)> MappedDest;
 
     ActualLhsType actualLhs = LhsBlasTraits::extract(lhs);
     ActualRhsType actualRhs = RhsBlasTraits::extract(rhs);
@@ -231,7 +233,7 @@ template<> struct gemv_dense_selector<OnTheRight,ColMajor,true>
     ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs);
 
     // make sure Dest is a compile-time vector type (bug 1166)
-    typedef typename conditional<Dest::IsVectorAtCompileTime, Dest, typename Dest::ColXpr>::type ActualDest;
+    typedef std::conditional_t<Dest::IsVectorAtCompileTime, Dest, typename Dest::ColXpr> ActualDest;
 
     enum {
       // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
@@ -261,7 +263,7 @@ template<> struct gemv_dense_selector<OnTheRight,ColMajor,true>
     {
       gemv_static_vector_if<ResScalar,ActualDest::SizeAtCompileTime,ActualDest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
 
-      const bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0));
+      const bool alphaIsCompatible = (!ComplexByReal) || (numext::is_exactly_zero(numext::imag(actualAlpha)));
       const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
 
       ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
@@ -314,10 +316,10 @@ template<> struct gemv_dense_selector<OnTheRight,RowMajor,true>
     typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType;
     typedef internal::blas_traits<Rhs> RhsBlasTraits;
     typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType;
-    typedef typename internal::remove_all<ActualRhsType>::type ActualRhsTypeCleaned;
+    typedef internal::remove_all_t<ActualRhsType> ActualRhsTypeCleaned;
 
-    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(lhs);
+    std::add_const_t<ActualLhsType> actualLhs = LhsBlasTraits::extract(lhs);
-    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(rhs);
+    std::add_const_t<ActualRhsType> actualRhs = RhsBlasTraits::extract(rhs);
 
     ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs);
 

libs/eigen/Eigen/src/Core/GenericPacketMath.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_GENERIC_PACKET_MATH_H
 #define EIGEN_GENERIC_PACKET_MATH_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -57,12 +59,14 @@ struct default_packet_traits
     HasMax       = 1,
     HasConj      = 1,
     HasSetLinear = 1,
+    HasSign      = 1,
     HasBlend     = 0,
     // This flag is used to indicate whether packet comparison is supported.
     // pcmp_eq, pcmp_lt and pcmp_le should be defined for it to be true.
     HasCmp       = 0,
 
     HasDiv    = 0,
+    HasReciprocal = 0,
     HasSqrt   = 0,
     HasRsqrt  = 0,
     HasExp    = 0,
@@ -98,8 +102,7 @@ struct default_packet_traits
     HasRound  = 0,
     HasRint   = 0,
     HasFloor  = 0,
-    HasCeil   = 0,
+    HasCeil   = 0
-    HasSign   = 0
   };
 };
 
@@ -160,7 +163,7 @@ struct eigen_packet_wrapper
 {
   EIGEN_ALWAYS_INLINE operator T&() { return m_val; }
   EIGEN_ALWAYS_INLINE operator const T&() const { return m_val; }
-  EIGEN_ALWAYS_INLINE eigen_packet_wrapper() {}
+  EIGEN_ALWAYS_INLINE eigen_packet_wrapper() = default;
   EIGEN_ALWAYS_INLINE eigen_packet_wrapper(const T &v) : m_val(v) {}
   EIGEN_ALWAYS_INLINE eigen_packet_wrapper& operator=(const T &v) {
     m_val = v;
@@ -176,7 +179,7 @@ struct eigen_packet_wrapper
  */
 template<typename Packet>
 struct is_scalar {
-  typedef typename unpacket_traits<Packet>::type Scalar;
+  using Scalar = typename unpacket_traits<Packet>::type;
   enum {
     value = internal::is_same<Packet, Scalar>::value
   };
@@ -217,6 +220,15 @@ padd(const Packet& a, const Packet& b) { return a+b; }
 template<> EIGEN_DEVICE_FUNC inline bool
 padd(const bool& a, const bool& b) { return a || b; }
 
+/** \internal \returns a packet version of \a *from, (un-aligned masked add)
+ * There is no generic implementation. We only have implementations for specialized
+ * cases. Generic case should not be called.
+ */
+template<typename Packet> EIGEN_DEVICE_FUNC inline
+std::enable_if_t<unpacket_traits<Packet>::masked_fpops_available, Packet>
+padd(const Packet& a, const Packet& b, typename unpacket_traits<Packet>::mask_t umask);
+
+
 /** \internal \returns a - b (coeff-wise) */
 template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 psub(const Packet& a, const Packet& b) { return a-b; }
@@ -259,7 +271,7 @@ struct ptrue_impl {
 // have another option, since the scalar type requires initialization.
 template<typename T>
 struct ptrue_impl<T, 
-    typename internal::enable_if<is_scalar<T>::value && NumTraits<T>::RequireInitialization>::type > {
+    std::enable_if_t<is_scalar<T>::value && NumTraits<T>::RequireInitialization> > {
   static EIGEN_DEVICE_FUNC inline T run(const T& /*a*/){
     return T(1);
   }
@@ -285,7 +297,7 @@ struct pzero_impl {
 // for zero may not consist of all-zero bits.
 template<typename T>
 struct pzero_impl<T,
-    typename internal::enable_if<is_scalar<T>::value>::type> {
+    std::enable_if_t<is_scalar<T>::value>> {
   static EIGEN_DEVICE_FUNC inline T run(const T& /*a*/) {
     return T(0);
   }
@@ -398,8 +410,8 @@ struct bitwise_helper : public bytewise_bitwise_helper<T> {};
 // For integers or non-trivial scalars, use binary operators.
 template<typename T>
 struct bitwise_helper<T,
-  typename internal::enable_if<
+  typename std::enable_if_t<
-    is_scalar<T>::value && (NumTraits<T>::IsInteger || NumTraits<T>::RequireInitialization)>::type
+    is_scalar<T>::value && (NumTraits<T>::IsInteger || NumTraits<T>::RequireInitialization)>
   > : public operator_bitwise_helper<T> {};
 
 /** \internal \returns the bitwise and of \a a and \a b */
@@ -441,7 +453,7 @@ struct pselect_impl {
 // For scalars, use ternary select.
 template<typename Packet>
 struct pselect_impl<Packet, 
-    typename internal::enable_if<is_scalar<Packet>::value>::type > {
+    std::enable_if_t<is_scalar<Packet>::value> > {
   static EIGEN_DEVICE_FUNC inline Packet run(const Packet& mask, const Packet& a, const Packet& b) {
     return numext::equal_strict(mask, Packet(0)) ? b : a;
   }
@@ -551,13 +563,13 @@ template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 parg(const Packet& a) { using numext::arg; return arg(a); }
 
 
-/** \internal \returns \a a logically shifted by N bits to the right */
+/** \internal \returns \a a arithmetically shifted by N bits to the right */
 template<int N> EIGEN_DEVICE_FUNC inline int
 parithmetic_shift_right(const int& a) { return a >> N; }
 template<int N> EIGEN_DEVICE_FUNC inline long int
 parithmetic_shift_right(const long int& a) { return a >> N; }
 
-/** \internal \returns \a a arithmetically shifted by N bits to the right */
+/** \internal \returns \a a logically shifted by N bits to the right */
 template<int N> EIGEN_DEVICE_FUNC inline int
 plogical_shift_right(const int& a) { return static_cast<int>(static_cast<unsigned int>(a) >> N); }
 template<int N> EIGEN_DEVICE_FUNC inline long int
@@ -594,20 +606,52 @@ pldexp(const Packet &a, const Packet &exponent) {
 template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pabsdiff(const Packet& a, const Packet& b) { return pselect(pcmp_lt(a, b), psub(b, a), psub(a, b)); }
 
-/** \internal \returns a packet version of \a *from, from must be 16 bytes aligned */
+/** \internal \returns a packet version of \a *from, from must be properly aligned */
 template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 pload(const typename unpacket_traits<Packet>::type* from) { return *from; }
 
+/** \internal \returns n elements of a packet version of \a *from, from must be properly aligned
+  * offset indicates the starting element in which to load and
+  * offset + n <= unpacket_traits::size
+  * All elements before offset and after the last element loaded will initialized with zero */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+pload_partial(const typename unpacket_traits<Packet>::type* from, const Index n, const Index offset = 0)
+{
+  const Index packet_size = unpacket_traits<Packet>::size;
+  eigen_assert(n + offset <= packet_size && "number of elements plus offset will read past end of packet");
+  typedef typename unpacket_traits<Packet>::type Scalar;
+  EIGEN_ALIGN_MAX Scalar elements[packet_size] = { Scalar(0) };
+  for (Index i = offset; i < numext::mini(n+offset,packet_size); i++) {
+    elements[i] = from[i-offset];
+  }
+  return pload<Packet>(elements);
+}
+
 /** \internal \returns a packet version of \a *from, (un-aligned load) */
 template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
 ploadu(const typename unpacket_traits<Packet>::type* from) { return *from; }
 
+/** \internal \returns n elements of a packet version of \a *from, (un-aligned load)
+  * All elements after the last element loaded will initialized with zero */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+ploadu_partial(const typename unpacket_traits<Packet>::type* from, const Index n)
+{
+  const Index packet_size = unpacket_traits<Packet>::size;
+  eigen_assert(n <= packet_size && "number of elements will read past end of packet");
+  typedef typename unpacket_traits<Packet>::type Scalar;
+  EIGEN_ALIGN_MAX Scalar elements[packet_size] = { Scalar(0) };
+  for (Index i = 0; i < numext::mini(n,packet_size); i++) {
+    elements[i] = from[i];
+  }
+  return pload<Packet>(elements);
+}
+
 /** \internal \returns a packet version of \a *from, (un-aligned masked load)
  * There is no generic implementation. We only have implementations for specialized
  * cases. Generic case should not be called.
  */
 template<typename Packet> EIGEN_DEVICE_FUNC inline
-typename enable_if<unpacket_traits<Packet>::masked_load_available, Packet>::type
+std::enable_if_t<unpacket_traits<Packet>::masked_load_available, Packet>
 ploadu(const typename unpacket_traits<Packet>::type* from, typename unpacket_traits<Packet>::mask_t umask);
 
 /** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */
@@ -692,29 +736,75 @@ peven_mask(const Packet& /*a*/) {
 }
 
 
-/** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */
+/** \internal copy the packet \a from to \a *to, \a to must be properly aligned */
 template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore(Scalar* to, const Packet& from)
 { (*to) = from; }
 
+/** \internal copy n elements of the packet \a from to \a *to, \a to must be properly aligned
+ * offset indicates the starting element in which to store and
+ * offset + n <= unpacket_traits::size */
+template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstore_partial(Scalar* to, const Packet& from, const Index n, const Index offset = 0)
+{
+  const Index packet_size = unpacket_traits<Packet>::size;
+  eigen_assert(n + offset <= packet_size && "number of elements plus offset will write past end of packet");
+  EIGEN_ALIGN_MAX Scalar elements[packet_size];
+  pstore<Scalar>(elements, from);
+  for (Index i = 0; i < numext::mini(n,packet_size-offset); i++) {
+    to[i] = elements[i + offset];
+  }
+}
+
 /** \internal copy the packet \a from to \a *to, (un-aligned store) */
 template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from)
 {  (*to) = from; }
 
+/** \internal copy n elements of the packet \a from to \a *to, (un-aligned store) */
+template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pstoreu_partial(Scalar* to, const Packet& from, const Index n)
+{
+  const Index packet_size = unpacket_traits<Packet>::size;
+  eigen_assert(n <= packet_size && "number of elements will write past end of packet");
+  EIGEN_ALIGN_MAX Scalar elements[packet_size];
+  pstore<Scalar>(elements, from);
+  for (Index i = 0; i < numext::mini(n,packet_size); i++) {
+    to[i] = elements[i];
+  }
+}
+
 /** \internal copy the packet \a from to \a *to, (un-aligned store with a mask)
  * There is no generic implementation. We only have implementations for specialized
  * cases. Generic case should not be called.
  */
 template<typename Scalar, typename Packet>
 EIGEN_DEVICE_FUNC inline
-typename enable_if<unpacket_traits<Packet>::masked_store_available, void>::type
+std::enable_if_t<unpacket_traits<Packet>::masked_store_available, void>
 pstoreu(Scalar* to, const Packet& from, typename unpacket_traits<Packet>::mask_t umask);
 
 template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, Index /*stride*/)
 { return ploadu<Packet>(from); }
 
+template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline Packet pgather_partial(const Scalar* from, Index stride, const Index n)
+{
+  const Index packet_size = unpacket_traits<Packet>::size;
+  EIGEN_ALIGN_MAX Scalar elements[packet_size] = { Scalar(0) };
+  for (Index i = 0; i < numext::mini(n,packet_size); i++) {
+    elements[i] = from[i*stride];
+  }
+  return pload<Packet>(elements);
+}
+
 template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, Index /*stride*/)
 { pstore(to, from); }
 
+template<typename Scalar, typename Packet> EIGEN_DEVICE_FUNC inline void pscatter_partial(Scalar* to, const Packet& from, Index stride, const Index n)
+{
+  const Index packet_size = unpacket_traits<Packet>::size;
+  EIGEN_ALIGN_MAX Scalar elements[packet_size];
+  pstore<Scalar>(elements, from);
+  for (Index i = 0; i < numext::mini(n,packet_size); i++) {
+    to[i*stride] = elements[i];
+  }
+}
+
 /** \internal tries to do cache prefetching of \a addr */
 template<typename Scalar> EIGEN_DEVICE_FUNC inline void prefetch(const Scalar* addr)
 {
@@ -814,13 +904,6 @@ Packet plog2(const Packet& a) {
 template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet psqrt(const Packet& a) { return numext::sqrt(a); }
 
-/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */
-template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet prsqrt(const Packet& a) {
-  typedef typename internal::unpacket_traits<Packet>::type Scalar;
-  return pdiv(pset1<Packet>(Scalar(1)), psqrt(a));
-}
-
 /** \internal \returns the rounded value of \a a (coeff-wise) */
 template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet pround(const Packet& a) { using numext::round; return round(a); }
@@ -838,6 +921,24 @@ Packet print(const Packet& a) { using numext::rint; return rint(a); }
 template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet pceil(const Packet& a) { using numext::ceil; return ceil(a); }
 
+template<typename Packet, typename EnableIf = void>
+struct psign_impl {
+  static EIGEN_DEVICE_FUNC inline Packet run(const Packet& a) {
+    return numext::sign(a);
+  }
+};
+
+/** \internal \returns the sign of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
+psign(const Packet& a) {
+  return psign_impl<Packet>::run(a);
+}
+
+template<> EIGEN_DEVICE_FUNC inline bool
+psign(const bool& a) {
+  return a;
+}
+
 /** \internal \returns the first element of a packet */
 template<typename Packet>
 EIGEN_DEVICE_FUNC inline typename unpacket_traits<Packet>::type
@@ -849,7 +950,7 @@ pfirst(const Packet& a)
   * For packet-size smaller or equal to 4, this boils down to a noop.
   */
 template<typename Packet>
-EIGEN_DEVICE_FUNC inline typename conditional<(unpacket_traits<Packet>::size%8)==0,typename unpacket_traits<Packet>::half,Packet>::type
+EIGEN_DEVICE_FUNC inline std::conditional_t<(unpacket_traits<Packet>::size%8)==0,typename unpacket_traits<Packet>::half,Packet>
 predux_half_dowto4(const Packet& a)
 { return a; }
 
@@ -943,6 +1044,35 @@ template<typename Packet> EIGEN_DEVICE_FUNC inline bool predux_any(const Packet&
 * The following functions might not have to be overwritten for vectorized types
 ***************************************************************************/
 
+// FMA instructions.
+/** \internal \returns a * b + c (coeff-wise) */
+template <typename Packet>
+EIGEN_DEVICE_FUNC inline Packet pmadd(const Packet& a, const Packet& b,
+                                      const Packet& c) {
+  return padd(pmul(a, b), c);
+}
+
+/** \internal \returns a * b - c (coeff-wise) */
+template <typename Packet>
+EIGEN_DEVICE_FUNC inline Packet pmsub(const Packet& a, const Packet& b,
+                                      const Packet& c) {
+  return psub(pmul(a, b), c);
+}
+
+/** \internal \returns -(a * b) + c (coeff-wise) */
+template <typename Packet>
+EIGEN_DEVICE_FUNC inline Packet pnmadd(const Packet& a, const Packet& b,
+                                       const Packet& c) {
+  return padd(pnegate(pmul(a, b)), c);
+}
+
+/** \internal \returns -(a * b) - c (coeff-wise) */
+template <typename Packet>
+EIGEN_DEVICE_FUNC inline Packet pnmsub(const Packet& a, const Packet& b,
+                                       const Packet& c) {
+  return psub(pnegate(pmul(a, b)), c);
+}
+
 /** \internal copy a packet with constant coefficient \a a (e.g., [a,a,a,a]) to \a *to. \a to must be 16 bytes aligned */
 // NOTE: this function must really be templated on the packet type (think about different packet types for the same scalar type)
 template<typename Packet>
@@ -951,13 +1081,6 @@ inline void pstore1(typename unpacket_traits<Packet>::type* to, const typename u
   pstore(to, pset1<Packet>(a));
 }
 
-/** \internal \returns a * b + c (coeff-wise) */
-template<typename Packet> EIGEN_DEVICE_FUNC inline Packet
-pmadd(const Packet&  a,
-         const Packet&  b,
-         const Packet&  c)
-{ return padd(pmul(a, b),c); }
-
 /** \internal \returns a packet version of \a *from.
   * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
 template<typename Packet, int Alignment>
@@ -969,6 +1092,17 @@ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt(const typename unpacket_trai
     return ploadu<Packet>(from);
 }
 
+/** \internal \returns n elements of a packet version of \a *from.
+  * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
+template<typename Packet, int Alignment>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt_partial(const typename unpacket_traits<Packet>::type* from, const Index n, const Index offset = 0)
+{
+  if(Alignment >= unpacket_traits<Packet>::alignment)
+    return pload_partial<Packet>(from, n, offset);
+  else
+    return ploadu_partial<Packet>(from, n);
+}
+
 /** \internal copy the packet \a from to \a *to.
   * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
 template<typename Scalar, typename Packet, int Alignment>
@@ -980,6 +1114,17 @@ EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& fro
     pstoreu(to, from);
 }
 
+/** \internal copy n elements of the packet \a from to \a *to.
+  * The pointer \a from must be aligned on a \a Alignment bytes boundary. */
+template<typename Scalar, typename Packet, int Alignment>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret_partial(Scalar* to, const Packet& from, const Index n, const Index offset = 0)
+{
+  if(Alignment >= unpacket_traits<Packet>::alignment)
+    pstore_partial(to, from, n, offset);
+  else
+    pstoreu_partial(to, from, n);
+}
+
 /** \internal \returns a packet version of \a *from.
   * Unlike ploadt, ploadt_ro takes advantage of the read-only memory path on the
   * hardware if available to speedup the loading of data that won't be modified
@@ -1033,6 +1178,47 @@ pblend(const Selector<unpacket_traits<Packet>::size>& ifPacket, const Packet& th
   return ifPacket.select[0] ? thenPacket : elsePacket;
 }
 
+/** \internal \returns 1 / a (coeff-wise) */
+template <typename Packet>
+EIGEN_DEVICE_FUNC inline Packet preciprocal(const Packet& a) {
+  using Scalar = typename unpacket_traits<Packet>::type;
+  return pdiv(pset1<Packet>(Scalar(1)), a);
+}
+
+/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */
+template<typename Packet> EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
+Packet prsqrt(const Packet& a) {
+  return preciprocal<Packet>(psqrt(a));
+}
+
+template <typename Packet, bool IsScalar = is_scalar<Packet>::value,
+    bool IsInteger = NumTraits<typename unpacket_traits<Packet>::type>::IsInteger>
+    struct psignbit_impl;
+template <typename Packet, bool IsInteger>
+struct psignbit_impl<Packet, true, IsInteger> {
+     EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Packet run(const Packet& a) { return numext::signbit(a); }
+};
+template <typename Packet>
+struct psignbit_impl<Packet, false, false> {
+    // generic implementation if not specialized in PacketMath.h
+    // slower than arithmetic shift
+    typedef typename unpacket_traits<Packet>::type Scalar;
+    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static Packet run(const Packet& a) {
+        const Packet cst_pos_one = pset1<Packet>(Scalar(1));
+        const Packet cst_neg_one = pset1<Packet>(Scalar(-1));
+        return pcmp_eq(por(pand(a, cst_neg_one), cst_pos_one), cst_neg_one);
+    }
+};
+template <typename Packet>
+struct psignbit_impl<Packet, false, true> {
+    // generic implementation for integer packets
+    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Packet run(const Packet& a) { return pcmp_lt(a, pzero(a)); }
+};
+/** \internal \returns the sign bit of \a a as a bitmask*/
+template <typename Packet>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE constexpr Packet
+psignbit(const Packet& a) { return psignbit_impl<Packet>::run(a); }
+
 } // end namespace internal
 
 } // end namespace Eigen

libs/eigen/Eigen/src/Core/GlobalFunctions.h

@@ -51,6 +51,8 @@
     } \
   };
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen
 {
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op,real part,\sa ArrayBase::real)
@@ -66,11 +68,9 @@ namespace Eigen
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sinh,scalar_sinh_op,hyperbolic sine,\sa ArrayBase::sinh)
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cosh,scalar_cosh_op,hyperbolic cosine,\sa ArrayBase::cosh)
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tanh,scalar_tanh_op,hyperbolic tangent,\sa ArrayBase::tanh)
-#if EIGEN_HAS_CXX11_MATH
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asinh,scalar_asinh_op,inverse hyperbolic sine,\sa ArrayBase::asinh)
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acosh,scalar_acosh_op,inverse hyperbolic cosine,\sa ArrayBase::acosh)
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atanh,scalar_atanh_op,inverse hyperbolic tangent,\sa ArrayBase::atanh)
-#endif
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(logistic,scalar_logistic_op,logistic function,\sa ArrayBase::logistic)
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(lgamma,scalar_lgamma_op,natural logarithm of the gamma function,\sa ArrayBase::lgamma)
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(digamma,scalar_digamma_op,derivative of lgamma,\sa ArrayBase::digamma)
@@ -99,9 +99,16 @@ namespace Eigen
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isfinite,scalar_isfinite_op,finite value test,\sa Eigen::isinf DOXCOMMA Eigen::isnan DOXCOMMA ArrayBase::isfinite)
   EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sign,scalar_sign_op,sign (or 0),\sa ArrayBase::sign)
 
+  template <typename Derived, typename ScalarExponent>
+  using GlobalUnaryPowReturnType = std::enable_if_t<
+      !internal::is_arithmetic<typename NumTraits<Derived>::Real>::value &&
+          internal::is_arithmetic<typename NumTraits<ScalarExponent>::Real>::value,
+      CwiseUnaryOp<internal::scalar_unary_pow_op<typename Derived::Scalar, ScalarExponent>, const Derived> >;
+
   /** \returns an expression of the coefficient-wise power of \a x to the given constant \a exponent.
    *
-    * \tparam ScalarExponent is the scalar type of \a exponent. It must be compatible with the scalar type of the given expression (\c Derived::Scalar).
+   * \tparam ScalarExponent is the scalar type of \a exponent. It must be compatible with the scalar type of the given
+   * expression (\c Derived::Scalar).
    *
    * \sa ArrayBase::pow()
    *
@@ -109,21 +116,14 @@ namespace Eigen
    */
 #ifdef EIGEN_PARSED_BY_DOXYGEN
   template <typename Derived, typename ScalarExponent>
-  inline const CwiseBinaryOp<internal::scalar_pow_op<Derived::Scalar,ScalarExponent>,Derived,Constant<ScalarExponent> >
+  EIGEN_DEVICE_FUNC inline const GlobalUnaryPowReturnType<Derived, ScalarExponent> pow(
-  pow(const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent);
+      const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent);
 #else
   template <typename Derived, typename ScalarExponent>
-  EIGEN_DEVICE_FUNC inline
+  EIGEN_DEVICE_FUNC inline const GlobalUnaryPowReturnType<Derived, ScalarExponent> pow(
-  EIGEN_MSVC10_WORKAROUND_BINARYOP_RETURN_TYPE(
+      const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent) {
-    const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,typename internal::promote_scalar_arg<typename Derived::Scalar
+    return GlobalUnaryPowReturnType<Derived, ScalarExponent>(
-                                                 EIGEN_COMMA ScalarExponent EIGEN_COMMA
+        x.derived(), internal::scalar_unary_pow_op<typename Derived::Scalar, ScalarExponent>(exponent));
-                                                 EIGEN_SCALAR_BINARY_SUPPORTED(pow,typename Derived::Scalar,ScalarExponent)>::type,pow))
-  pow(const Eigen::ArrayBase<Derived>& x, const ScalarExponent& exponent)
-  {
-    typedef typename internal::promote_scalar_arg<typename Derived::Scalar,ScalarExponent,
-                                                  EIGEN_SCALAR_BINARY_SUPPORTED(pow,typename Derived::Scalar,ScalarExponent)>::type PromotedExponent;
-    return EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(Derived,PromotedExponent,pow)(x.derived(),
-           typename internal::plain_constant_type<Derived,PromotedExponent>::type(x.derived().rows(), x.derived().cols(), internal::scalar_constant_op<PromotedExponent>(exponent)));
   }
 #endif
 
@@ -168,10 +168,9 @@ namespace Eigen
 #else
   template <typename Scalar, typename Derived>
   EIGEN_DEVICE_FUNC inline
-  EIGEN_MSVC10_WORKAROUND_BINARYOP_RETURN_TYPE(
     const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(typename internal::promote_scalar_arg<typename Derived::Scalar
                                                  EIGEN_COMMA Scalar EIGEN_COMMA
-                                                 EIGEN_SCALAR_BINARY_SUPPORTED(pow,Scalar,typename Derived::Scalar)>::type,Derived,pow))
+                                                 EIGEN_SCALAR_BINARY_SUPPORTED(pow,Scalar,typename Derived::Scalar)>::type,Derived,pow)
   pow(const Scalar& x, const Eigen::ArrayBase<Derived>& exponents) {
     typedef typename internal::promote_scalar_arg<typename Derived::Scalar,Scalar,
                                                   EIGEN_SCALAR_BINARY_SUPPORTED(pow,Scalar,typename Derived::Scalar)>::type PromotedScalar;
@@ -180,6 +179,25 @@ namespace Eigen
   }
 #endif
 
+  /** \returns an expression of the coefficient-wise atan2(\a x, \a y). \a x and \a y must be of the same type.
+    *
+    * This function computes the coefficient-wise atan2().
+    *
+    * \sa ArrayBase::atan2()
+    *
+    * \relates ArrayBase
+    */
+  template <typename LhsDerived, typename RhsDerived>
+  inline const std::enable_if_t<
+      std::is_same<typename LhsDerived::Scalar, typename RhsDerived::Scalar>::value,
+      Eigen::CwiseBinaryOp<Eigen::internal::scalar_atan2_op<typename LhsDerived::Scalar, typename RhsDerived::Scalar>, const LhsDerived, const RhsDerived>
+      >
+  atan2(const Eigen::ArrayBase<LhsDerived>& x, const Eigen::ArrayBase<RhsDerived>& exponents) {
+    return Eigen::CwiseBinaryOp<Eigen::internal::scalar_atan2_op<typename LhsDerived::Scalar, typename RhsDerived::Scalar>, const LhsDerived, const RhsDerived>(
+      x.derived(),
+      exponents.derived()
+    );
+  }
 
   namespace internal
   {

libs/eigen/Eigen/src/Core/IO.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_IO_H
 #define EIGEN_IO_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 enum { DontAlignCols = 1 };
@@ -131,7 +133,6 @@ template<typename Derived>
 std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt)
 {
   using internal::is_same;
-  using internal::conditional;
 
   if(_m.size() == 0)
   {
@@ -141,22 +142,21 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
   
   typename Derived::Nested m = _m;
   typedef typename Derived::Scalar Scalar;
-  typedef typename
+  typedef std::conditional_t<
-      conditional<
           is_same<Scalar, char>::value ||
             is_same<Scalar, unsigned char>::value ||
             is_same<Scalar, numext::int8_t>::value ||
             is_same<Scalar, numext::uint8_t>::value,
           int,
-          typename conditional<
+          std::conditional_t<
               is_same<Scalar, std::complex<char> >::value ||
                 is_same<Scalar, std::complex<unsigned char> >::value ||
                 is_same<Scalar, std::complex<numext::int8_t> >::value ||
                 is_same<Scalar, std::complex<numext::uint8_t> >::value,
               std::complex<int>,
               const Scalar&
-            >::type
+            >
-        >::type PrintType;
+        > PrintType;
 
   Index width = 0;
 

libs/eigen/Eigen/src/Core/IndexedView.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_INDEXED_VIEW_H
 #define EIGEN_INDEXED_VIEW_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -21,8 +23,8 @@ struct traits<IndexedView<XprType, RowIndices, ColIndices> >
   enum {
     RowsAtCompileTime = int(array_size<RowIndices>::value),
     ColsAtCompileTime = int(array_size<ColIndices>::value),
-    MaxRowsAtCompileTime = RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime) : Dynamic,
+    MaxRowsAtCompileTime = RowsAtCompileTime,
-    MaxColsAtCompileTime = ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime) : Dynamic,
+    MaxColsAtCompileTime = ColsAtCompileTime,
 
     XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
     IsRowMajor = (MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
@@ -40,10 +42,10 @@ struct traits<IndexedView<XprType, RowIndices, ColIndices> >
 
     InnerSize = XprTypeIsRowMajor ? ColsAtCompileTime : RowsAtCompileTime,
     IsBlockAlike = InnerIncr==1 && OuterIncr==1,
-    IsInnerPannel = HasSameStorageOrderAsXprType && is_same<AllRange<InnerSize>,typename conditional<XprTypeIsRowMajor,ColIndices,RowIndices>::type>::value,
+    IsInnerPannel = HasSameStorageOrderAsXprType && is_same<AllRange<InnerSize>,std::conditional_t<XprTypeIsRowMajor,ColIndices,RowIndices>>::value,
 
-    InnerStrideAtCompileTime = InnerIncr<0 || InnerIncr==DynamicIndex || XprInnerStride==Dynamic ? Dynamic : XprInnerStride * InnerIncr,
+    InnerStrideAtCompileTime = InnerIncr<0 || InnerIncr==DynamicIndex || XprInnerStride==Dynamic || InnerIncr==UndefinedIncr ? Dynamic : XprInnerStride * InnerIncr,
-    OuterStrideAtCompileTime = OuterIncr<0 || OuterIncr==DynamicIndex || XprOuterstride==Dynamic ? Dynamic : XprOuterstride * OuterIncr,
+    OuterStrideAtCompileTime = OuterIncr<0 || OuterIncr==DynamicIndex || XprOuterstride==Dynamic || OuterIncr==UndefinedIncr ? Dynamic : XprOuterstride * OuterIncr,
 
     ReturnAsScalar = is_same<RowIndices,SingleRange>::value && is_same<ColIndices,SingleRange>::value,
     ReturnAsBlock = (!ReturnAsScalar) && IsBlockAlike,
@@ -96,7 +98,7 @@ class IndexedViewImpl;
   *  - decltype(ArrayXi::LinSpaced(...))
   *  - Any view/expressions of the previous types
   *  - Eigen::ArithmeticSequence
-  *  - Eigen::internal::AllRange      (helper for Eigen::all)
+  *  - Eigen::internal::AllRange     (helper for Eigen::placeholders::all)
   *  - Eigen::internal::SingleRange  (helper for single index)
   *  - etc.
   *
@@ -114,7 +116,7 @@ public:
   EIGEN_INHERIT_ASSIGNMENT_OPERATORS(IndexedView)
 
   typedef typename internal::ref_selector<XprType>::non_const_type MatrixTypeNested;
-  typedef typename internal::remove_all<XprType>::type NestedExpression;
+  typedef internal::remove_all_t<XprType> NestedExpression;
 
   template<typename T0, typename T1>
   IndexedView(XprType& xpr, const T0& rowIndices, const T1& colIndices)
@@ -122,17 +124,17 @@ public:
   {}
 
   /** \returns number of rows */
-  Index rows() const { return internal::size(m_rowIndices); }
+  Index rows() const { return internal::index_list_size(m_rowIndices); }
 
   /** \returns number of columns */
-  Index cols() const { return internal::size(m_colIndices); }
+  Index cols() const { return internal::index_list_size(m_colIndices); }
 
   /** \returns the nested expression */
-  const typename internal::remove_all<XprType>::type&
+  const internal::remove_all_t<XprType>&
   nestedExpression() const { return m_xpr; }
 
   /** \returns the nested expression */
-  typename internal::remove_reference<XprType>::type&
+  std::remove_reference_t<XprType>&
   nestedExpression() { return m_xpr; }
 
   /** \returns a const reference to the object storing/generating the row indices */
@@ -189,12 +191,16 @@ struct unary_evaluator<IndexedView<ArgType, RowIndices, ColIndices>, IndexBased>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
   CoeffReturnType coeff(Index row, Index col) const
   {
+    eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows()
+                 && m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols());
     return m_argImpl.coeff(m_xpr.rowIndices()[row], m_xpr.colIndices()[col]);
   }
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
   Scalar& coeffRef(Index row, Index col)
   {
+    eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows()
+                 && m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols());
     return m_argImpl.coeffRef(m_xpr.rowIndices()[row], m_xpr.colIndices()[col]);
   }
 
@@ -204,6 +210,8 @@ struct unary_evaluator<IndexedView<ArgType, RowIndices, ColIndices>, IndexBased>
     EIGEN_STATIC_ASSERT_LVALUE(XprType)
     Index row = XprType::RowsAtCompileTime == 1 ? 0 : index;
     Index col = XprType::RowsAtCompileTime == 1 ? index : 0;
+    eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows()
+                 && m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols());
     return m_argImpl.coeffRef( m_xpr.rowIndices()[row], m_xpr.colIndices()[col]);
   }
 
@@ -212,6 +220,8 @@ struct unary_evaluator<IndexedView<ArgType, RowIndices, ColIndices>, IndexBased>
   {
     Index row = XprType::RowsAtCompileTime == 1 ? 0 : index;
     Index col = XprType::RowsAtCompileTime == 1 ? index : 0;
+    eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows()
+                 && m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols());
     return m_argImpl.coeffRef( m_xpr.rowIndices()[row], m_xpr.colIndices()[col]);
   }
 
@@ -220,6 +230,8 @@ struct unary_evaluator<IndexedView<ArgType, RowIndices, ColIndices>, IndexBased>
   {
     Index row = XprType::RowsAtCompileTime == 1 ? 0 : index;
     Index col = XprType::RowsAtCompileTime == 1 ? index : 0;
+    eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows()
+                 && m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols());
     return m_argImpl.coeff( m_xpr.rowIndices()[row], m_xpr.colIndices()[col]);
   }
 

libs/eigen/Eigen/src/Core/InternalHeaderCheck.h

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

libs/eigen/Eigen/src/Core/Inverse.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_INVERSE_H
 #define EIGEN_INVERSE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 template<typename XprType,typename StorageKind> class InverseImpl;
@@ -46,9 +48,9 @@ public:
   typedef typename XprType::StorageIndex StorageIndex;
   typedef typename XprType::Scalar                            Scalar;
   typedef typename internal::ref_selector<XprType>::type      XprTypeNested;
-  typedef typename internal::remove_all<XprTypeNested>::type  XprTypeNestedCleaned;
+  typedef internal::remove_all_t<XprTypeNested>  XprTypeNestedCleaned;
   typedef typename internal::ref_selector<Inverse>::type Nested;
-  typedef typename internal::remove_all<XprType>::type NestedExpression;
+  typedef internal::remove_all_t<XprType> NestedExpression;
 
   explicit EIGEN_DEVICE_FUNC Inverse(const XprType &xpr)
     : m_xpr(xpr)
@@ -102,7 +104,7 @@ struct unary_evaluator<Inverse<ArgType> >
   unary_evaluator(const InverseType& inv_xpr)
     : m_result(inv_xpr.rows(), inv_xpr.cols())
   {
-    ::new (static_cast<Base*>(this)) Base(m_result);
+    internal::construct_at<Base>(this, m_result);
     internal::call_assignment_no_alias(m_result, inv_xpr);
   }
 

libs/eigen/Eigen/src/Core/Map.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_MAP_H
 #define EIGEN_MAP_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -129,7 +131,6 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
     explicit inline Map(PointerArgType dataPtr, const StrideType& stride = StrideType())
       : Base(cast_to_pointer_type(dataPtr)), m_stride(stride)
     {
-      PlainObjectType::Base::_check_template_params();
     }
 
     /** Constructor in the dynamic-size vector case.
@@ -142,7 +143,6 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
     inline Map(PointerArgType dataPtr, Index size, const StrideType& stride = StrideType())
       : Base(cast_to_pointer_type(dataPtr), size), m_stride(stride)
     {
-      PlainObjectType::Base::_check_template_params();
     }
 
     /** Constructor in the dynamic-size matrix case.
@@ -156,7 +156,6 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
     inline Map(PointerArgType dataPtr, Index rows, Index cols, const StrideType& stride = StrideType())
       : Base(cast_to_pointer_type(dataPtr), rows, cols), m_stride(stride)
     {
-      PlainObjectType::Base::_check_template_params();
     }
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)

libs/eigen/Eigen/src/Core/MapBase.h

@@ -15,6 +15,8 @@
       EIGEN_STATIC_ASSERT((int(internal::evaluator<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
                           YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \ingroup Core_Module
@@ -51,10 +53,10 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
     typedef typename internal::traits<Derived>::Scalar Scalar;
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename NumTraits<Scalar>::Real RealScalar;
-    typedef typename internal::conditional<
+    typedef std::conditional_t<
                 bool(internal::is_lvalue<Derived>::value),
                 Scalar *,
-                         const Scalar *>::type
+                const Scalar *>
             PointerType;
 
     using Base::derived;
@@ -189,7 +191,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
 
     template<typename T>
     EIGEN_DEVICE_FUNC
-    void checkSanity(typename internal::enable_if<(internal::traits<T>::Alignment>0),void*>::type = 0) const
+    void checkSanity(std::enable_if_t<(internal::traits<T>::Alignment>0),void*> = 0) const
     {
 #if EIGEN_MAX_ALIGN_BYTES>0
       // innerStride() is not set yet when this function is called, so we optimistically assume the lowest plausible value:
@@ -202,7 +204,7 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
 
     template<typename T>
     EIGEN_DEVICE_FUNC
-    void checkSanity(typename internal::enable_if<internal::traits<T>::Alignment==0,void*>::type = 0) const
+    void checkSanity(std::enable_if_t<internal::traits<T>::Alignment==0,void*> = 0) const
     {}
 
     PointerType m_data;
@@ -245,11 +247,11 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
     using Base::rowStride;
     using Base::colStride;
 
-    typedef typename internal::conditional<
+    typedef std::conditional_t<
                     internal::is_lvalue<Derived>::value,
                     Scalar,
                     const Scalar
-                  >::type ScalarWithConstIfNotLvalue;
+                  > ScalarWithConstIfNotLvalue;
 
     EIGEN_DEVICE_FUNC
     inline const Scalar* data() const { return this->m_data; }

libs/eigen/Eigen/src/Core/MathFunctions.h

@@ -17,16 +17,9 @@
 #define EIGEN_LOG2E 1.442695040888963407359924681001892137426645954152985934135449406931109219L
 #define EIGEN_LN2   0.693147180559945309417232121458176568075500134360255254120680009493393621L
 
-namespace Eigen {
+#include "./InternalHeaderCheck.h"
 
-// On WINCE, std::abs is defined for int only, so let's defined our own overloads:
+namespace Eigen {
-// This issue has been confirmed with MSVC 2008 only, but the issue might exist for more recent versions too.
-#if EIGEN_OS_WINCE && EIGEN_COMP_MSVC && EIGEN_COMP_MSVC<=1500
-long        abs(long        x) { return (labs(x));  }
-double      abs(double      x) { return (fabs(x));  }
-float       abs(float       x) { return (fabsf(x)); }
-long double abs(long double x) { return (fabsl(x)); }
-#endif
 
 namespace internal {
 
@@ -236,6 +229,63 @@ struct imag_ref_retval
   typedef typename NumTraits<Scalar>::Real & type;
 };
 
+
+/****************************************************************************
+* Implementation of sign                                                 *
+****************************************************************************/
+template<typename Scalar, bool IsComplex = (NumTraits<Scalar>::IsComplex!=0),
+    bool IsInteger = (NumTraits<Scalar>::IsInteger!=0)>
+struct sign_impl
+{
+  EIGEN_DEVICE_FUNC
+  static inline Scalar run(const Scalar& a)
+  {
+    return Scalar( (a>Scalar(0)) - (a<Scalar(0)) );
+  }
+};
+
+template<typename Scalar>
+struct sign_impl<Scalar, false, false>
+{
+  EIGEN_DEVICE_FUNC
+  static inline Scalar run(const Scalar& a)
+  {
+    return (std::isnan)(a) ? a : Scalar( (a>Scalar(0)) - (a<Scalar(0)) );
+  }
+};
+
+template<typename Scalar, bool IsInteger>
+struct sign_impl<Scalar, true, IsInteger>
+{
+  EIGEN_DEVICE_FUNC
+  static inline Scalar run(const Scalar& a)
+  {
+    using real_type = typename NumTraits<Scalar>::Real;
+    real_type aa = std::abs(a);
+    if (aa==real_type(0))
+      return Scalar(0);
+    aa = real_type(1)/aa;
+    return Scalar(a.real()*aa, a.imag()*aa );
+  }
+};
+
+// The sign function for bool is the identity.
+template<>
+struct sign_impl<bool, false, true>
+{
+  EIGEN_DEVICE_FUNC
+  static inline bool run(const bool& a)
+  {
+    return a;
+  }
+};
+
+template<typename Scalar>
+struct sign_retval
+{
+  typedef Scalar type;
+};
+
 /****************************************************************************
 * Implementation of conj                                                 *
 ****************************************************************************/
@@ -441,9 +491,9 @@ struct cast_impl
 // generating warnings on clang.  Here we explicitly cast the real component.
 template<typename OldType, typename NewType>
 struct cast_impl<OldType, NewType,
-  typename internal::enable_if<
+  typename std::enable_if_t<
     !NumTraits<OldType>::IsComplex && NumTraits<NewType>::IsComplex
-  >::type>
+  >>
 {
   EIGEN_DEVICE_FUNC
   static inline NewType run(const OldType& x)
@@ -469,57 +519,16 @@ inline NewType cast(const OldType& x)
 template<typename Scalar>
 struct round_impl
 {
+  EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
+
   EIGEN_DEVICE_FUNC
   static inline Scalar run(const Scalar& x)
   {
-    EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
-#if EIGEN_HAS_CXX11_MATH
     EIGEN_USING_STD(round);
-#endif
     return Scalar(round(x));
   }
 };
 
-#if !EIGEN_HAS_CXX11_MATH
-#if EIGEN_HAS_C99_MATH
-// Use ::roundf for float.
-template<>
-struct round_impl<float> {
-  EIGEN_DEVICE_FUNC
-  static inline float run(const float& x)
-  {
-    return ::roundf(x);
-  }
-};
-#else
-template<typename Scalar>
-struct round_using_floor_ceil_impl
-{
-  EIGEN_DEVICE_FUNC
-  static inline Scalar run(const Scalar& x)
-  {
-    EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
-    // Without C99 round/roundf, resort to floor/ceil.
-    EIGEN_USING_STD(floor);
-    EIGEN_USING_STD(ceil);
-    // If not enough precision to resolve a decimal at all, return the input.
-    // Otherwise, adding 0.5 can trigger an increment by 1.
-    const Scalar limit = Scalar(1ull << (NumTraits<Scalar>::digits() - 1));
-    if (x >= limit || x <= -limit) {
-      return x;
-    }
-    return (x > Scalar(0)) ? Scalar(floor(x + Scalar(0.5))) : Scalar(ceil(x - Scalar(0.5)));
-  }
-};
-
-template<>
-struct round_impl<float> : round_using_floor_ceil_impl<float> {};
-
-template<>
-struct round_impl<double> : round_using_floor_ceil_impl<double> {};
-#endif // EIGEN_HAS_C99_MATH
-#endif // !EIGEN_HAS_CXX11_MATH
-
 template<typename Scalar>
 struct round_retval
 {
@@ -532,36 +541,16 @@ struct round_retval
 
 template<typename Scalar>
 struct rint_impl {
+  EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
+
   EIGEN_DEVICE_FUNC
   static inline Scalar run(const Scalar& x)
   {
-    EIGEN_STATIC_ASSERT((!NumTraits<Scalar>::IsComplex), NUMERIC_TYPE_MUST_BE_REAL)
-#if EIGEN_HAS_CXX11_MATH
     EIGEN_USING_STD(rint);
-#endif
     return rint(x);
   }
 };
 
-#if !EIGEN_HAS_CXX11_MATH
-template<>
-struct rint_impl<double> {
-  EIGEN_DEVICE_FUNC
-  static inline double run(const double& x)
-  {
-    return ::rint(x);
-  }
-};
-template<>
-struct rint_impl<float> {
-  EIGEN_DEVICE_FUNC
-  static inline float run(const float& x)
-  {
-    return ::rintf(x);
-  }
-};
-#endif
-
 template<typename Scalar>
 struct rint_retval
 {
@@ -574,7 +563,7 @@ struct rint_retval
 
 // Visual Studio 2017 has a bug where arg(float) returns 0 for negative inputs.
 // This seems to be fixed in VS 2019.
-#if EIGEN_HAS_CXX11_MATH && (!EIGEN_COMP_MSVC || EIGEN_COMP_MSVC >= 1920)
+#if (!EIGEN_COMP_MSVC || EIGEN_COMP_MSVC >= 1920)
 // std::arg is only defined for types of std::complex, or integer types or float/double/long double
 template<typename Scalar,
           bool HasStdImpl = NumTraits<Scalar>::IsComplex || is_integral<Scalar>::value
@@ -675,11 +664,7 @@ struct expm1_impl {
   EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x)
   {
     EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
-    #if EIGEN_HAS_CXX11_MATH
     using std::expm1;
-    #else
-    using std_fallback::expm1;
-    #endif
     return expm1(x);
   }
 };
@@ -736,14 +721,11 @@ namespace std_fallback {
 
 template<typename Scalar>
 struct log1p_impl {
+  EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
+
   EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x)
   {
-    EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
-    #if EIGEN_HAS_CXX11_MATH
     using std::log1p;
-    #else
-    using std_fallback::log1p;
-    #endif
     return log1p(x);
   }
 };
@@ -751,9 +733,10 @@ struct log1p_impl {
 // Specialization for complex types that are not supported by std::log1p.
 template <typename RealScalar>
 struct log1p_impl<std::complex<RealScalar> > {
+  EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar)
+
   EIGEN_DEVICE_FUNC static inline std::complex<RealScalar> run(
       const std::complex<RealScalar>& x) {
-    EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar)
     return std_fallback::log1p(x);
   }
 };
@@ -893,7 +876,7 @@ struct random_default_impl<Scalar, false, true>
     // ScalarX is the widest of ScalarU and unsigned int.
     // We'll deal only with ScalarX and unsigned int below thus avoiding signed
     // types and arithmetic and signed overflows (which are undefined behavior).
-    typedef typename conditional<(ScalarU(-1) > unsigned(-1)), ScalarU, unsigned>::type ScalarX;
+    typedef std::conditional_t<(ScalarU(-1) > unsigned(-1)), ScalarU, unsigned> ScalarX;
     // The following difference doesn't overflow, provided our integer types are two's
     // complement and have the same number of padding bits in signed and unsigned variants.
     // This is the case in most modern implementations of C++.
@@ -918,8 +901,8 @@ struct random_default_impl<Scalar, false, true>
 #else
     enum { rand_bits = meta_floor_log2<(unsigned int)(RAND_MAX)+1>::value,
            scalar_bits = sizeof(Scalar) * CHAR_BIT,
-           shift = EIGEN_PLAIN_ENUM_MAX(0, int(rand_bits) - int(scalar_bits)),
+           shift = plain_enum_max(0, int(rand_bits) - int(scalar_bits)),
-           offset = NumTraits<Scalar>::IsSigned ? (1 << (EIGEN_PLAIN_ENUM_MIN(rand_bits,scalar_bits)-1)) : 0
+           offset = NumTraits<Scalar>::IsSigned ? (1 << (plain_enum_min(rand_bits, scalar_bits)-1)) : 0
     };
     return Scalar((std::rand() >> shift) - offset);
 #endif
@@ -956,7 +939,7 @@ inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random()
 // Implementation of is* functions
 
 // std::is* do not work with fast-math and gcc, std::is* are available on MSVC 2013 and newer, as well as in clang.
-#if (EIGEN_HAS_CXX11_MATH && !(EIGEN_COMP_GNUC_STRICT && __FINITE_MATH_ONLY__)) || (EIGEN_COMP_MSVC>=1800) || (EIGEN_COMP_CLANG)
+#if (!(EIGEN_COMP_GNUC_STRICT && __FINITE_MATH_ONLY__)) || (EIGEN_COMP_MSVC) || (EIGEN_COMP_CLANG)
 #define EIGEN_USE_STD_FPCLASSIFY 1
 #else
 #define EIGEN_USE_STD_FPCLASSIFY 0
@@ -964,22 +947,22 @@ inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random()
 
 template<typename T>
 EIGEN_DEVICE_FUNC
-typename internal::enable_if<internal::is_integral<T>::value,bool>::type
+std::enable_if_t<internal::is_integral<T>::value,bool>
 isnan_impl(const T&) { return false; }
 
 template<typename T>
 EIGEN_DEVICE_FUNC
-typename internal::enable_if<internal::is_integral<T>::value,bool>::type
+std::enable_if_t<internal::is_integral<T>::value,bool>
 isinf_impl(const T&) { return false; }
 
 template<typename T>
 EIGEN_DEVICE_FUNC
-typename internal::enable_if<internal::is_integral<T>::value,bool>::type
+std::enable_if_t<internal::is_integral<T>::value,bool>
 isfinite_impl(const T&) { return true; }
 
 template<typename T>
 EIGEN_DEVICE_FUNC
-typename internal::enable_if<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>::type
+std::enable_if_t<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>
 isfinite_impl(const T& x)
 {
   #if defined(EIGEN_GPU_COMPILE_PHASE)
@@ -994,7 +977,7 @@ isfinite_impl(const T& x)
 
 template<typename T>
 EIGEN_DEVICE_FUNC
-typename internal::enable_if<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>::type
+std::enable_if_t<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>
 isinf_impl(const T& x)
 {
   #if defined(EIGEN_GPU_COMPILE_PHASE)
@@ -1009,7 +992,7 @@ isinf_impl(const T& x)
 
 template<typename T>
 EIGEN_DEVICE_FUNC
-typename internal::enable_if<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>::type
+std::enable_if_t<(!internal::is_integral<T>::value)&&(!NumTraits<T>::IsComplex),bool>
 isnan_impl(const T& x)
 {
   #if defined(EIGEN_GPU_COMPILE_PHASE)
@@ -1042,7 +1025,7 @@ EIGEN_DEVICE_FUNC inline bool isinf_impl(const float& x)       { return isinf_ms
 
 #elif (defined __FINITE_MATH_ONLY__ && __FINITE_MATH_ONLY__ && EIGEN_COMP_GNUC)
 
-#if EIGEN_GNUC_AT_LEAST(5,0)
+#if EIGEN_COMP_GNUC
   #define EIGEN_TMP_NOOPT_ATTRIB EIGEN_DEVICE_FUNC inline __attribute__((optimize("no-finite-math-only")))
 #else
   // NOTE the inline qualifier and noinline attribute are both needed: the former is to avoid linking issue (duplicate symbol),
@@ -1234,7 +1217,7 @@ inline EIGEN_MATHFUNC_RETVAL(real, Scalar) real(const Scalar& x)
 
 template<typename Scalar>
 EIGEN_DEVICE_FUNC
-inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) >::type real_ref(const Scalar& x)
+inline internal::add_const_on_value_type_t< EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) > real_ref(const Scalar& x)
 {
   return internal::real_ref_impl<Scalar>::run(x);
 }
@@ -1262,7 +1245,7 @@ inline EIGEN_MATHFUNC_RETVAL(arg, Scalar) arg(const Scalar& x)
 
 template<typename Scalar>
 EIGEN_DEVICE_FUNC
-inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) >::type imag_ref(const Scalar& x)
+inline internal::add_const_on_value_type_t< EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) > imag_ref(const Scalar& x)
 {
   return internal::imag_ref_impl<Scalar>::run(x);
 }
@@ -1281,6 +1264,13 @@ inline EIGEN_MATHFUNC_RETVAL(conj, Scalar) conj(const Scalar& x)
   return EIGEN_MATHFUNC_IMPL(conj, Scalar)::run(x);
 }
 
+template<typename Scalar>
+EIGEN_DEVICE_FUNC
+inline EIGEN_MATHFUNC_RETVAL(sign, Scalar) sign(const Scalar& x)
+{
+  return EIGEN_MATHFUNC_IMPL(sign, Scalar)::run(x);
+}
+
 template<typename Scalar>
 EIGEN_DEVICE_FUNC
 inline EIGEN_MATHFUNC_RETVAL(abs2, Scalar) abs2(const Scalar& x)
@@ -1505,7 +1495,7 @@ double log(const double &x) { return ::log(x); }
 
 template<typename T>
 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
-typename internal::enable_if<NumTraits<T>::IsSigned || NumTraits<T>::IsComplex,typename NumTraits<T>::Real>::type
+std::enable_if_t<NumTraits<T>::IsSigned || NumTraits<T>::IsComplex,typename NumTraits<T>::Real>
 abs(const T &x) {
   EIGEN_USING_STD(abs);
   return abs(x);
@@ -1513,7 +1503,7 @@ abs(const T &x) {
 
 template<typename T>
 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
-typename internal::enable_if<!(NumTraits<T>::IsSigned || NumTraits<T>::IsComplex),typename NumTraits<T>::Real>::type
+std::enable_if_t<!(NumTraits<T>::IsSigned || NumTraits<T>::IsComplex),typename NumTraits<T>::Real>
 abs(const T &x) {
   return x;
 }
@@ -1541,6 +1531,37 @@ double abs(const std::complex<double>& x) {
 }
 #endif
 
+template <typename Scalar, bool IsInteger = NumTraits<Scalar>::IsInteger, bool IsSigned = NumTraits<Scalar>::IsSigned>
+struct signbit_impl;
+template <typename Scalar>
+struct signbit_impl<Scalar, false, true> {
+  static constexpr size_t Size = sizeof(Scalar);
+  static constexpr size_t Shift = (CHAR_BIT * Size) - 1;
+  using intSize_t = typename get_integer_by_size<Size>::signed_type;
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static Scalar run(const Scalar& x) {
+    intSize_t a = bit_cast<intSize_t, Scalar>(x);
+    a = a >> Shift;
+    Scalar result = bit_cast<Scalar, intSize_t>(a);
+    return result;
+  }
+};
+template <typename Scalar>
+struct signbit_impl<Scalar, true, true> {
+  static constexpr size_t Size = sizeof(Scalar);
+  static constexpr size_t Shift = (CHAR_BIT * Size) - 1;
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Scalar run(const Scalar& x) { return x >> Shift; }
+};
+template <typename Scalar>
+struct signbit_impl<Scalar, true, false> {
+  EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Scalar run(const Scalar&  ) {
+    return Scalar(0);
+  }
+};
+template <typename Scalar>
+EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Scalar signbit(const Scalar& x) {
+  return signbit_impl<Scalar>::run(x);
+}
+
 template<typename T>
 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
 T exp(const T &x) {
@@ -1659,14 +1680,12 @@ T acos(const T &x) {
   return acos(x);
 }
 
-#if EIGEN_HAS_CXX11_MATH
 template<typename T>
 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
 T acosh(const T &x) {
   EIGEN_USING_STD(acosh);
   return static_cast<T>(acosh(x));
 }
-#endif
 
 #if defined(SYCL_DEVICE_ONLY)
 SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(acos, acos)
@@ -1688,14 +1707,12 @@ T asin(const T &x) {
   return asin(x);
 }
 
-#if EIGEN_HAS_CXX11_MATH
 template<typename T>
 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
 T asinh(const T &x) {
   EIGEN_USING_STD(asinh);
   return static_cast<T>(asinh(x));
 }
-#endif
 
 #if defined(SYCL_DEVICE_ONLY)
 SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(asin, asin)
@@ -1717,14 +1734,12 @@ T atan(const T &x) {
   return static_cast<T>(atan(x));
 }
 
-#if EIGEN_HAS_CXX11_MATH
 template<typename T>
 EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
 T atanh(const T &x) {
   EIGEN_USING_STD(atanh);
   return static_cast<T>(atanh(x));
 }
-#endif
 
 #if defined(SYCL_DEVICE_ONLY)
 SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(atan, atan)
@@ -2006,9 +2021,10 @@ namespace internal {
 // Specialization for complex types that are not supported by std::expm1.
 template <typename RealScalar>
 struct expm1_impl<std::complex<RealScalar> > {
+  EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar)
+
   EIGEN_DEVICE_FUNC static inline std::complex<RealScalar> run(
       const std::complex<RealScalar>& x) {
-    EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar)
     RealScalar xr = x.real();
     RealScalar xi = x.imag();
     // expm1(z) = exp(z) - 1

libs/eigen/Eigen/src/Core/MathFunctionsImpl.h

@@ -11,17 +11,152 @@
 #ifndef EIGEN_MATHFUNCTIONSIMPL_H
 #define EIGEN_MATHFUNCTIONSIMPL_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
+/** \internal Fast reciprocal using Newton-Raphson's method.
+
+ Preconditions:
+   1. The starting guess provided in approx_a_recip must have at least half
+      the leading mantissa bits in the correct result, such that a single
+      Newton-Raphson step is sufficient to get within 1-2 ulps of the currect
+      result.
+   2. If a is zero, approx_a_recip must be infinite with the same sign as a.
+   3. If a is infinite, approx_a_recip must be zero with the same sign as a.
+
+   If the preconditions are satisfied, which they are for for the _*_rcp_ps
+   instructions on x86, the result has a maximum relative error of 2 ulps,
+   and correctly handles reciprocals of zero, infinity, and NaN.
+*/
+template <typename Packet, int Steps>
+struct generic_reciprocal_newton_step {
+  static_assert(Steps > 0, "Steps must be at least 1.");
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE  Packet
+  run(const Packet& a, const Packet& approx_a_recip) {
+    using Scalar = typename unpacket_traits<Packet>::type;
+    const Packet two = pset1<Packet>(Scalar(2));
+    // Refine the approximation using one Newton-Raphson step:
+    //   x_{i} = x_{i-1} * (2 - a * x_{i-1})
+     const Packet x =
+         generic_reciprocal_newton_step<Packet,Steps - 1>::run(a, approx_a_recip);
+     const Packet tmp = pnmadd(a, x, two);
+     // If tmp is NaN, it means that a is either +/-0 or +/-Inf.
+     // In this case return the approximation directly.
+     const Packet is_not_nan = pcmp_eq(tmp, tmp);
+     return pselect(is_not_nan, pmul(x, tmp), x);
+  }
+};
+
+template<typename Packet>
+struct generic_reciprocal_newton_step<Packet, 0> {
+   EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Packet
+   run(const Packet& /*unused*/, const Packet& approx_rsqrt) {
+    return approx_rsqrt;
+  }
+};
+
+
+/** \internal Fast reciprocal sqrt using Newton-Raphson's method.
+
+ Preconditions:
+   1. The starting guess provided in approx_a_recip must have at least half
+      the leading mantissa bits in the correct result, such that a single
+      Newton-Raphson step is sufficient to get within 1-2 ulps of the currect
+      result.
+   2. If a is zero, approx_a_recip must be infinite with the same sign as a.
+   3. If a is infinite, approx_a_recip must be zero with the same sign as a.
+
+   If the preconditions are satisfied, which they are for for the _*_rcp_ps
+   instructions on x86, the result has a maximum relative error of 2 ulps,
+   and correctly handles zero, infinity, and NaN. Positive denormals are
+   treated as zero.
+*/
+template <typename Packet, int Steps>
+struct generic_rsqrt_newton_step {
+  static_assert(Steps > 0, "Steps must be at least 1.");
+
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE  Packet
+  run(const Packet& a, const Packet& approx_rsqrt) {
+    using Scalar = typename unpacket_traits<Packet>::type;
+    const Packet one_point_five = pset1<Packet>(Scalar(1.5));
+    const Packet minus_half = pset1<Packet>(Scalar(-0.5));
+    
+    // Refine the approximation using one Newton-Raphson step:
+    //   x_{n+1} = x_n * (1.5 + (-0.5 * x_n) * (a * x_n)).
+    // The approximation is expressed this way to avoid over/under-flows.  
+    Packet x_newton  = pmul(approx_rsqrt, pmadd(pmul(minus_half, approx_rsqrt), pmul(a, approx_rsqrt), one_point_five));
+    for (int step = 1; step < Steps; ++step) {
+      x_newton  = pmul(x_newton, pmadd(pmul(minus_half, x_newton), pmul(a, x_newton), one_point_five));
+    }
+    
+    // If approx_rsqrt is 0 or +/-inf, we should return it as is.  Note:
+    // on intel, approx_rsqrt can be inf for small denormal values.
+    const Packet return_approx = por(pcmp_eq(approx_rsqrt, pzero(a)),
+                                     pcmp_eq(pabs(approx_rsqrt), pset1<Packet>(NumTraits<Scalar>::infinity())));
+    return pselect(return_approx, approx_rsqrt, x_newton);
+  }
+};
+
+template<typename Packet>
+struct generic_rsqrt_newton_step<Packet, 0> {
+   EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Packet
+   run(const Packet& /*unused*/, const Packet& approx_rsqrt) {
+    return approx_rsqrt;
+  }
+};
+
+
+/** \internal Fast sqrt using Newton-Raphson's method.
+
+ Preconditions:
+   1. The starting guess for the reciprocal sqrt provided in approx_rsqrt must
+      have at least half the leading mantissa bits in the correct result, such
+      that a single Newton-Raphson step is sufficient to get within 1-2 ulps of
+      the currect result.
+   2. If a is zero, approx_rsqrt must be infinite.
+   3. If a is infinite, approx_rsqrt must be zero.
+
+   If the preconditions are satisfied, which they are for for the _*_rsqrt_ps
+   instructions on x86, the result has a maximum relative error of 2 ulps,
+   and correctly handles zero and infinity, and NaN. Positive denormal inputs
+   are treated as zero.
+*/
+template <typename Packet, int Steps=1>
+struct generic_sqrt_newton_step {
+  static_assert(Steps > 0, "Steps must be at least 1.");
+
+  EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE  Packet
+  run(const Packet& a, const Packet& approx_rsqrt) {
+    using Scalar = typename unpacket_traits<Packet>::type;
+    const Packet one_point_five = pset1<Packet>(Scalar(1.5));
+    const Packet minus_half = pset1<Packet>(Scalar(-0.5));
+    // If a is inf or zero, return a directly.
+    const Packet inf_mask = pcmp_eq(a, pset1<Packet>(NumTraits<Scalar>::infinity()));
+    const Packet return_a = por(pcmp_eq(a, pzero(a)), inf_mask);
+    // Do a single step of Newton's iteration for reciprocal square root:
+    //   x_{n+1} = x_n * (1.5 + (-0.5 * x_n) * (a * x_n))).
+    // The Newton's step is computed this way to avoid over/under-flows.
+    Packet rsqrt = pmul(approx_rsqrt, pmadd(pmul(minus_half, approx_rsqrt), pmul(a, approx_rsqrt), one_point_five));
+    for (int step = 1; step < Steps; ++step) {
+      rsqrt = pmul(rsqrt, pmadd(pmul(minus_half, rsqrt), pmul(a, rsqrt), one_point_five));
+    }
+
+    // Return sqrt(x) = x * rsqrt(x) for non-zero finite positive arguments.
+    // Return a itself for 0 or +inf, NaN for negative arguments.
+    return pselect(return_a, a, pmul(a, rsqrt));
+  }
+};
+
 /** \internal \returns the hyperbolic tan of \a a (coeff-wise)
     Doesn't do anything fancy, just a 13/6-degree rational interpolant which
     is accurate up to a couple of ulps in the (approximate) range [-8, 8],
     outside of which tanh(x) = +/-1 in single precision. The input is clamped
     to the range [-c, c]. The value c is chosen as the smallest value where
     the approximation evaluates to exactly 1. In the reange [-0.0004, 0.0004]
-    the approxmation tanh(x) ~= x is used for better accuracy as x tends to zero.
+    the approximation tanh(x) ~= x is used for better accuracy as x tends to zero.
 
     This implementation works on both scalars and packets.
 */
@@ -88,7 +223,7 @@ RealScalar positive_real_hypot(const RealScalar& x, const RealScalar& y)
   EIGEN_USING_STD(sqrt);
   RealScalar p, qp;
   p = numext::maxi(x,y);
-  if(p==RealScalar(0)) return RealScalar(0);
+  if(numext::is_exactly_zero(p)) return RealScalar(0);
   qp = numext::mini(y,x) / p;
   return p * sqrt(RealScalar(1) + qp*qp);
 }
@@ -138,7 +273,7 @@ EIGEN_DEVICE_FUNC std::complex<T> complex_sqrt(const std::complex<T>& z) {
 
   return
     (numext::isinf)(y) ? std::complex<T>(NumTraits<T>::infinity(), y)
-      : x == zero ? std::complex<T>(w, y < zero ? -w : w)
+      : numext::is_exactly_zero(x) ? std::complex<T>(w, y < zero ? -w : w)
                                    : x > zero ? std::complex<T>(w, y / (2 * w))
       : std::complex<T>(numext::abs(y) / (2 * w), y < zero ? -w : w );
 }
@@ -177,9 +312,9 @@ EIGEN_DEVICE_FUNC std::complex<T> complex_rsqrt(const std::complex<T>& z) {
   const T woz = w / abs_z;
   // Corner cases consistent with 1/sqrt(z) on gcc/clang.
   return
-    abs_z == zero ? std::complex<T>(NumTraits<T>::infinity(), NumTraits<T>::quiet_NaN())
+          numext::is_exactly_zero(abs_z) ? std::complex<T>(NumTraits<T>::infinity(), NumTraits<T>::quiet_NaN())
                                          : ((numext::isinf)(x) || (numext::isinf)(y)) ? std::complex<T>(zero, zero)
-      : x == zero ? std::complex<T>(woz, y < zero ? woz : -woz)
+      : numext::is_exactly_zero(x) ? std::complex<T>(woz, y < zero ? woz : -woz)
                                    : x > zero ? std::complex<T>(woz, -y / (2 * w * abs_z))
       : std::complex<T>(numext::abs(y) / (2 * w * abs_z), y < zero ? woz : -woz );
 }

libs/eigen/Eigen/src/Core/Matrix.h

@@ -11,37 +11,39 @@
 #ifndef EIGEN_MATRIX_H
 #define EIGEN_MATRIX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+template<typename Scalar_, int Rows_, int Cols_, int Options_, int MaxRows_, int MaxCols_>
-struct traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+struct traits<Matrix<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> >
 {
 private:
-  enum { size = internal::size_at_compile_time<_Rows,_Cols>::ret };
+  constexpr static int size = internal::size_at_compile_time(Rows_,Cols_);
-  typedef typename find_best_packet<_Scalar,size>::type PacketScalar;
+  typedef typename find_best_packet<Scalar_,size>::type PacketScalar;
   enum {
-      row_major_bit = _Options&RowMajor ? RowMajorBit : 0,
+      row_major_bit = Options_&RowMajor ? RowMajorBit : 0,
-      is_dynamic_size_storage = _MaxRows==Dynamic || _MaxCols==Dynamic,
+      is_dynamic_size_storage = MaxRows_==Dynamic || MaxCols_==Dynamic,
-      max_size = is_dynamic_size_storage ? Dynamic : _MaxRows*_MaxCols,
+      max_size = is_dynamic_size_storage ? Dynamic : MaxRows_*MaxCols_,
-      default_alignment = compute_default_alignment<_Scalar,max_size>::value,
+      default_alignment = compute_default_alignment<Scalar_,max_size>::value,
-      actual_alignment = ((_Options&DontAlign)==0) ? default_alignment : 0,
+      actual_alignment = ((Options_&DontAlign)==0) ? default_alignment : 0,
       required_alignment = unpacket_traits<PacketScalar>::alignment,
-      packet_access_bit = (packet_traits<_Scalar>::Vectorizable && (EIGEN_UNALIGNED_VECTORIZE || (actual_alignment>=required_alignment))) ? PacketAccessBit : 0
+      packet_access_bit = (packet_traits<Scalar_>::Vectorizable && (EIGEN_UNALIGNED_VECTORIZE || (actual_alignment>=required_alignment))) ? PacketAccessBit : 0
     };
 
 public:
-  typedef _Scalar Scalar;
+  typedef Scalar_ Scalar;
   typedef Dense StorageKind;
   typedef Eigen::Index StorageIndex;
   typedef MatrixXpr XprKind;
   enum {
-    RowsAtCompileTime = _Rows,
+    RowsAtCompileTime = Rows_,
-    ColsAtCompileTime = _Cols,
+    ColsAtCompileTime = Cols_,
-    MaxRowsAtCompileTime = _MaxRows,
+    MaxRowsAtCompileTime = MaxRows_,
-    MaxColsAtCompileTime = _MaxCols,
+    MaxColsAtCompileTime = MaxCols_,
-    Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
+    Flags = compute_matrix_flags(Options_),
-    Options = _Options,
+    Options = Options_,
     InnerStrideAtCompileTime = 1,
     OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime,
 
@@ -63,18 +65,18 @@ public:
   * The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note").
   *
   * The first three template parameters are required:
-  * \tparam _Scalar Numeric type, e.g. float, double, int or std::complex<float>.
+  * \tparam Scalar_ Numeric type, e.g. float, double, int or std::complex<float>.
   *                 User defined scalar types are supported as well (see \ref user_defined_scalars "here").
-  * \tparam _Rows Number of rows, or \b Dynamic
+  * \tparam Rows_ Number of rows, or \b Dynamic
-  * \tparam _Cols Number of columns, or \b Dynamic
+  * \tparam Cols_ Number of columns, or \b Dynamic
   *
   * The remaining template parameters are optional -- in most cases you don't have to worry about them.
-  * \tparam _Options A combination of either \b #RowMajor or \b #ColMajor, and of either
+  * \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of either
   *                 \b #AutoAlign or \b #DontAlign.
   *                 The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required
   *                 for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size.
-  * \tparam _MaxRows Maximum number of rows. Defaults to \a _Rows (\ref maxrows "note").
+  * \tparam MaxRows_ Maximum number of rows. Defaults to \a Rows_ (\ref maxrows "note").
-  * \tparam _MaxCols Maximum number of columns. Defaults to \a _Cols (\ref maxrows "note").
+  * \tparam MaxCols_ Maximum number of columns. Defaults to \a Cols_ (\ref maxrows "note").
   *
   * Eigen provides a number of typedefs covering the usual cases. Here are some examples:
   *
@@ -128,12 +130,12 @@ public:
   * Note that \em dense matrices, be they Fixed-size or Dynamic-size, <em>do not</em> expand dynamically in the sense of a std::map.
   * If you want this behavior, see the Sparse module.</dd>
   *
-  * <dt><b>\anchor maxrows _MaxRows and _MaxCols:</b></dt>
+  * <dt><b>\anchor maxrows MaxRows_ and MaxCols_:</b></dt>
   * <dd>In most cases, one just leaves these parameters to the default values.
   * These parameters mean the maximum size of rows and columns that the matrix may have. They are useful in cases
   * when the exact numbers of rows and columns are not known are compile-time, but it is known at compile-time that they cannot
-  * exceed a certain value. This happens when taking dynamic-size blocks inside fixed-size matrices: in this case _MaxRows and _MaxCols
+  * exceed a certain value. This happens when taking dynamic-size blocks inside fixed-size matrices: in this case MaxRows_ and MaxCols_
-  * are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.</dd>
+  * are the dimensions of the original matrix, while Rows_ and Cols_ are Dynamic.</dd>
   * </dl>
   *
   * <i><b>ABI and storage layout</b></i>
@@ -174,9 +176,9 @@ public:
   * \ref TopicStorageOrders
   */
 
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+template<typename Scalar_, int Rows_, int Cols_, int Options_, int MaxRows_, int MaxCols_>
 class Matrix
-  : public PlainObjectBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+  : public PlainObjectBase<Matrix<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> >
 {
   public:
 
@@ -185,7 +187,7 @@ class Matrix
       */
     typedef PlainObjectBase<Matrix> Base;
 
-    enum { Options = _Options };
+    enum { Options = Options_ };
 
     EIGEN_DENSE_PUBLIC_INTERFACE(Matrix)
 
@@ -258,7 +260,6 @@ class Matrix
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Matrix() : Base()
     {
-      Base::_check_template_params();
       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
@@ -266,24 +267,18 @@ class Matrix
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     explicit Matrix(internal::constructor_without_unaligned_array_assert)
       : Base(internal::constructor_without_unaligned_array_assert())
-    { Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
+    { EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
 
-#if EIGEN_HAS_RVALUE_REFERENCES
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Matrix(Matrix&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_constructible<Scalar>::value)
-      : Base(std::move(other))
+      : Base(std::move(other)) {}
-    {
-      Base::_check_template_params();
-    }
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Matrix& operator=(Matrix&& other) EIGEN_NOEXCEPT_IF(std::is_nothrow_move_assignable<Scalar>::value)
     {
       Base::operator=(std::move(other));
       return *this;
     }
-#endif
 
-#if EIGEN_HAS_CXX11
     /** \copydoc PlainObjectBase(const Scalar&, const Scalar&, const Scalar&,  const Scalar&, const ArgTypes&... args)
      *
      * Example: \include Matrix_variadic_ctor_cxx11.cpp
@@ -317,9 +312,9 @@ class Matrix
       *
       * \sa Matrix(const Scalar& a0, const Scalar& a1, const Scalar& a2,  const Scalar& a3, const ArgTypes&... args)
       */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC explicit constexpr EIGEN_STRONG_INLINE Matrix(
-    explicit EIGEN_STRONG_INLINE Matrix(const std::initializer_list<std::initializer_list<Scalar>>& list) : Base(list) {}
+        const std::initializer_list<std::initializer_list<Scalar>>& list)
-#endif // end EIGEN_HAS_CXX11
+        : Base(list) {}
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 
@@ -328,7 +323,6 @@ class Matrix
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     explicit Matrix(const T& x)
     {
-      Base::_check_template_params();
       Base::template _init1<T>(x);
     }
 
@@ -336,7 +330,6 @@ class Matrix
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Matrix(const T0& x, const T1& y)
     {
-      Base::_check_template_params();
       Base::template _init2<T0,T1>(x, y);
     }
 
@@ -388,7 +381,6 @@ class Matrix
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z)
     {
-      Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 3)
       m_storage.data()[0] = x;
       m_storage.data()[1] = y;
@@ -400,7 +392,6 @@ class Matrix
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
     {
-      Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 4)
       m_storage.data()[0] = x;
       m_storage.data()[1] = y;
@@ -480,16 +471,21 @@ class Matrix
 
 #define EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix)   \
 /** \ingroup matrixtypedefs */                                    \
+/** \brief `Size`&times;`Size` matrix of type `Type`. */          \
 typedef Matrix<Type, Size, Size> Matrix##SizeSuffix##TypeSuffix;  \
 /** \ingroup matrixtypedefs */                                    \
+/** \brief `Size`&times;`1` vector of type `Type`. */             \
 typedef Matrix<Type, Size, 1>    Vector##SizeSuffix##TypeSuffix;  \
 /** \ingroup matrixtypedefs */                                    \
+/** \brief `1`&times;`Size` vector of type `Type`. */             \
 typedef Matrix<Type, 1, Size>    RowVector##SizeSuffix##TypeSuffix;
 
 #define EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, Size)         \
 /** \ingroup matrixtypedefs */                                    \
+/** \brief `Size`&times;`Dynamic` matrix of type `Type`. */       \
 typedef Matrix<Type, Size, Dynamic> Matrix##Size##X##TypeSuffix;  \
 /** \ingroup matrixtypedefs */                                    \
+/** \brief `Dynamic`&times;`Size` matrix of type `Type`. */       \
 typedef Matrix<Type, Dynamic, Size> Matrix##X##Size##TypeSuffix;
 
 #define EIGEN_MAKE_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \
@@ -511,29 +507,27 @@ EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
 #undef EIGEN_MAKE_TYPEDEFS
 #undef EIGEN_MAKE_FIXED_TYPEDEFS
 
-#if EIGEN_HAS_CXX11
-
 #define EIGEN_MAKE_TYPEDEFS(Size, SizeSuffix)                        \
 /** \ingroup matrixtypedefs */                                       \
-/** \brief \cpp11 */                                              \
+/** \brief \cpp11 `Size`&times;`Size` matrix of type `Type`.*/       \
 template <typename Type>                                             \
 using Matrix##SizeSuffix = Matrix<Type, Size, Size>;                 \
 /** \ingroup matrixtypedefs */                                       \
-/** \brief \cpp11 */                                              \
+/** \brief \cpp11 `Size`&times;`1` vector of type `Type`.*/          \
 template <typename Type>                                             \
 using Vector##SizeSuffix = Matrix<Type, Size, 1>;                    \
 /** \ingroup matrixtypedefs */                                       \
-/** \brief \cpp11 */                                              \
+/** \brief \cpp11 `1`&times;`Size` vector of type `Type`.*/          \
 template <typename Type>                                             \
 using RowVector##SizeSuffix = Matrix<Type, 1, Size>;
 
 #define EIGEN_MAKE_FIXED_TYPEDEFS(Size)                            \
 /** \ingroup matrixtypedefs */                                     \
-/** \brief \cpp11 */                                              \
+/** \brief \cpp11 `Size`&times;`Dynamic` matrix of type `Type` */  \
 template <typename Type>                                           \
 using Matrix##Size##X = Matrix<Type, Size, Dynamic>;               \
 /** \ingroup matrixtypedefs */                                     \
-/** \brief \cpp11 */                                              \
+/** \brief \cpp11 `Dynamic`&times;`Size` matrix of type `Type`. */ \
 template <typename Type>                                           \
 using Matrix##X##Size = Matrix<Type, Dynamic, Size>;
 
@@ -546,20 +540,18 @@ EIGEN_MAKE_FIXED_TYPEDEFS(3)
 EIGEN_MAKE_FIXED_TYPEDEFS(4)
 
 /** \ingroup matrixtypedefs
-  * \brief \cpp11 */
+  * \brief \cpp11 `Size`&times;`1` vector of type `Type`. */
 template <typename Type, int Size>
 using Vector = Matrix<Type, Size, 1>;
 
 /** \ingroup matrixtypedefs
-  * \brief \cpp11 */
+  * \brief \cpp11 `1`&times;`Size` vector of type `Type`. */
 template <typename Type, int Size>
 using RowVector = Matrix<Type, 1, Size>;
 
 #undef EIGEN_MAKE_TYPEDEFS
 #undef EIGEN_MAKE_FIXED_TYPEDEFS
 
-#endif // EIGEN_HAS_CXX11
-
 } // end namespace Eigen
 
 #endif // EIGEN_MATRIX_H

libs/eigen/Eigen/src/Core/MatrixBase.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_MATRIXBASE_H
 #define EIGEN_MATRIXBASE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class MatrixBase
@@ -92,8 +94,8 @@ template<typename Derived> class MatrixBase
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** type of the equivalent square matrix */
-    typedef Matrix<Scalar,EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime),
+    typedef Matrix<Scalar, internal::max_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime),
-                          EIGEN_SIZE_MAX(RowsAtCompileTime,ColsAtCompileTime)> SquareMatrixType;
+                           internal::max_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime)> SquareMatrixType;
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
     /** \returns the size of the main diagonal, which is min(rows(),cols()).
@@ -107,10 +109,10 @@ template<typename Derived> class MatrixBase
     /** \internal Represents a matrix with all coefficients equal to one another*/
     typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,PlainObject> ConstantReturnType;
     /** \internal the return type of MatrixBase::adjoint() */
-    typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
+    typedef std::conditional_t<NumTraits<Scalar>::IsComplex,
                CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, ConstTransposeReturnType>,
                ConstTransposeReturnType
-                     >::type AdjointReturnType;
+            > AdjointReturnType;
     /** \internal Return type of eigenvalues() */
     typedef Matrix<std::complex<RealScalar>, internal::traits<Derived>::ColsAtCompileTime, 1, ColMajor> EigenvaluesReturnType;
     /** \internal the return type of identity */
@@ -184,6 +186,11 @@ template<typename Derived> class MatrixBase
     const Product<Derived, DiagonalDerived, LazyProduct>
     operator*(const DiagonalBase<DiagonalDerived> &diagonal) const;
 
+    template<typename SkewDerived>
+    EIGEN_DEVICE_FUNC
+    const Product<Derived, SkewDerived, LazyProduct>
+    operator*(const SkewSymmetricBase<SkewDerived> &skew) const;
+
     template<typename OtherDerived>
     EIGEN_DEVICE_FUNC
     typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
@@ -206,28 +213,22 @@ template<typename Derived> class MatrixBase
     EIGEN_DEVICE_FUNC
     DiagonalReturnType diagonal();
 
-    typedef typename internal::add_const<Diagonal<const Derived> >::type ConstDiagonalReturnType;
+    typedef Diagonal<const Derived> ConstDiagonalReturnType;
     EIGEN_DEVICE_FUNC
-    ConstDiagonalReturnType diagonal() const;
+    const ConstDiagonalReturnType diagonal() const;
-
-    template<int Index> struct DiagonalIndexReturnType { typedef Diagonal<Derived,Index> Type; };
-    template<int Index> struct ConstDiagonalIndexReturnType { typedef const Diagonal<const Derived,Index> Type; };
 
     template<int Index>
     EIGEN_DEVICE_FUNC
-    typename DiagonalIndexReturnType<Index>::Type diagonal();
+    Diagonal<Derived, Index> diagonal();
 
     template<int Index>
     EIGEN_DEVICE_FUNC
-    typename ConstDiagonalIndexReturnType<Index>::Type diagonal() const;
+    const Diagonal<const Derived, Index> diagonal() const;
-
-    typedef Diagonal<Derived,DynamicIndex> DiagonalDynamicIndexReturnType;
-    typedef typename internal::add_const<Diagonal<const Derived,DynamicIndex> >::type ConstDiagonalDynamicIndexReturnType;
 
     EIGEN_DEVICE_FUNC
-    DiagonalDynamicIndexReturnType diagonal(Index index);
+    Diagonal<Derived, DynamicIndex> diagonal(Index index);
     EIGEN_DEVICE_FUNC
-    ConstDiagonalDynamicIndexReturnType diagonal(Index index) const;
+    const Diagonal<const Derived, DynamicIndex> diagonal(Index index) const;
 
     template<unsigned int Mode> struct TriangularViewReturnType { typedef TriangularView<Derived, Mode> Type; };
     template<unsigned int Mode> struct ConstTriangularViewReturnType { typedef const TriangularView<const Derived, Mode> Type; };
@@ -263,6 +264,8 @@ template<typename Derived> class MatrixBase
     EIGEN_DEVICE_FUNC
     const DiagonalWrapper<const Derived> asDiagonal() const;
     const PermutationWrapper<const Derived> asPermutation() const;
+    EIGEN_DEVICE_FUNC
+    const SkewSymmetricWrapper<const Derived> asSkewSymmetric() const;
 
     EIGEN_DEVICE_FUNC
     Derived& setIdentity();
@@ -277,6 +280,8 @@ template<typename Derived> class MatrixBase
     bool isUpperTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
     bool isLowerTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
+    bool isSkewSymmetric(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+
     template<typename OtherDerived>
     bool isOrthogonal(const MatrixBase<OtherDerived>& other,
                       const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
@@ -368,25 +373,23 @@ template<typename Derived> class MatrixBase
 
 /////////// SVD module ///////////
 
-    inline JacobiSVD<PlainObject> jacobiSvd(unsigned int computationOptions = 0) const;
+    template<int Options = 0>
-    inline BDCSVD<PlainObject>    bdcSvd(unsigned int computationOptions = 0) const;
+    inline JacobiSVD<PlainObject, Options> jacobiSvd() const;
+    template<int Options = 0>
+    EIGEN_DEPRECATED
+    inline JacobiSVD<PlainObject, Options> jacobiSvd(unsigned int computationOptions) const;
+
+    template<int Options = 0>
+    inline BDCSVD<PlainObject, Options> bdcSvd() const;
+    template<int Options = 0>
+    EIGEN_DEPRECATED
+    inline BDCSVD<PlainObject, Options> bdcSvd(unsigned int computationOptions) const;
 
 /////////// Geometry module ///////////
 
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    /// \internal helper struct to form the return type of the cross product
-    template<typename OtherDerived> struct cross_product_return_type {
-      typedef typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType Scalar;
-      typedef Matrix<Scalar,MatrixBase::RowsAtCompileTime,MatrixBase::ColsAtCompileTime> type;
-    };
-    #endif // EIGEN_PARSED_BY_DOXYGEN
     template<typename OtherDerived>
     EIGEN_DEVICE_FUNC
-#ifndef EIGEN_PARSED_BY_DOXYGEN
+    inline typename internal::cross_impl<Derived, OtherDerived>::return_type
-    inline typename cross_product_return_type<OtherDerived>::type
-#else
-    inline PlainObject
-#endif
     cross(const MatrixBase<OtherDerived>& other) const;
 
     template<typename OtherDerived>
@@ -468,11 +471,9 @@ template<typename Derived> class MatrixBase
     const MatrixFunctionReturnValue<Derived> matrixFunction(StemFunction f) const;
     EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, cosh, hyperbolic cosine)
     EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, sinh, hyperbolic sine)
-#if EIGEN_HAS_CXX11_MATH
     EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, atanh, inverse hyperbolic cosine)
     EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, acosh, inverse hyperbolic cosine)
     EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, asinh, inverse hyperbolic sine)
-#endif
     EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, cos, cosine)
     EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, sin, sine)
     EIGEN_MATRIX_FUNCTION(MatrixSquareRootReturnValue, sqrt, square root)

libs/eigen/Eigen/src/Core/NestByValue.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_NESTBYVALUE_H
 #define EIGEN_NESTBYVALUE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -41,6 +43,8 @@ template<typename ExpressionType> class NestByValue
   public:
 
     typedef typename internal::dense_xpr_base<NestByValue>::type Base;
+    static constexpr bool HasDirectAccess = internal::has_direct_access<ExpressionType>::ret;
+    
     EIGEN_DENSE_PUBLIC_INTERFACE(NestByValue)
 
     EIGEN_DEVICE_FUNC explicit inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {}
@@ -52,6 +56,18 @@ template<typename ExpressionType> class NestByValue
 
     EIGEN_DEVICE_FUNC const ExpressionType& nestedExpression() const { return m_expression; }
 
+    EIGEN_DEVICE_FUNC typename std::enable_if<HasDirectAccess, const Scalar*>::type data() const {
+      return m_expression.data();
+    }
+    
+    EIGEN_DEVICE_FUNC typename std::enable_if<HasDirectAccess, Index>::type innerStride() const {
+      return m_expression.innerStride();
+    }
+    
+    EIGEN_DEVICE_FUNC typename std::enable_if<HasDirectAccess, Index>::type outerStride() const {
+      return m_expression.outerStride();
+    }
+
   protected:
     const ExpressionType m_expression;
 };

libs/eigen/Eigen/src/Core/NoAlias.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_NOALIAS_H
 #define EIGEN_NOALIAS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class NoAlias

libs/eigen/Eigen/src/Core/NumTraits.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_NUMTRAITS_H
 #define EIGEN_NUMTRAITS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -61,10 +63,10 @@ struct default_digits_impl<T,false,false> // Floating point
 {
   EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
   static int run() {
-    using std::log;
+    using std::log2;
     using std::ceil;
     typedef typename NumTraits<T>::Real Real;
-    return int(ceil(-log(NumTraits<Real>::epsilon())/log(static_cast<Real>(2))));
+    return int(ceil(-log2(NumTraits<Real>::epsilon())));
   }
 };
 
@@ -83,17 +85,17 @@ namespace numext {
 // TODO: Replace by std::bit_cast (available in C++20)
 template <typename Tgt, typename Src>
 EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Tgt bit_cast(const Src& src) {
-#if EIGEN_HAS_TYPE_TRAITS
   // The behaviour of memcpy is not specified for non-trivially copyable types
   EIGEN_STATIC_ASSERT(std::is_trivially_copyable<Src>::value, THIS_TYPE_IS_NOT_SUPPORTED);
   EIGEN_STATIC_ASSERT(std::is_trivially_copyable<Tgt>::value && std::is_default_constructible<Tgt>::value,
                       THIS_TYPE_IS_NOT_SUPPORTED);
-#endif
-
   EIGEN_STATIC_ASSERT(sizeof(Src) == sizeof(Tgt), THIS_TYPE_IS_NOT_SUPPORTED);
+
   Tgt tgt;
+  // Load src into registers first. This allows the memcpy to be elided by CUDA.
+  const Src staged = src;
   EIGEN_USING_STD(memcpy)
-  memcpy(&tgt, &src, sizeof(Tgt));
+  memcpy(static_cast<void*>(&tgt),static_cast<const void*>(&staged), sizeof(Tgt));
   return tgt;
 }
 }  // namespace numext
@@ -162,11 +164,7 @@ template<typename T> struct GenericNumTraits
   };
 
   typedef T Real;
-  typedef typename internal::conditional<
+  typedef std::conditional_t<IsInteger, std::conditional_t<sizeof(T)<=2, float, double>, T> NonInteger;
-                     IsInteger,
-                     typename internal::conditional<sizeof(T)<=2, float, double>::type,
-                     T
-                   >::type NonInteger;
   typedef T Nested;
   typedef T Literal;
 
@@ -252,15 +250,15 @@ template<> struct NumTraits<long double>
   static inline long double dummy_precision() { return 1e-15l; }
 };
 
-template<typename _Real> struct NumTraits<std::complex<_Real> >
+template<typename Real_> struct NumTraits<std::complex<Real_> >
-  : GenericNumTraits<std::complex<_Real> >
+  : GenericNumTraits<std::complex<Real_> >
 {
-  typedef _Real Real;
+  typedef Real_ Real;
-  typedef typename NumTraits<_Real>::Literal Literal;
+  typedef typename NumTraits<Real_>::Literal Literal;
   enum {
     IsComplex = 1,
-    RequireInitialization = NumTraits<_Real>::RequireInitialization,
+    RequireInitialization = NumTraits<Real_>::RequireInitialization,
-    ReadCost = 2 * NumTraits<_Real>::ReadCost,
+    ReadCost = 2 * NumTraits<Real_>::ReadCost,
     AddCost = 2 * NumTraits<Real>::AddCost,
     MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost
   };

libs/eigen/Eigen/src/Core/PartialReduxEvaluator.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_PARTIALREDUX_H
 #define EIGEN_PARTIALREDUX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
@@ -29,7 +31,7 @@ namespace internal {
 *    some (optional) processing of the outcome, e.g., division by n for mean.
 *
 * For the vectorized path let's observe that the packet-size and outer-unrolling
-* are both decided by the assignement logic. So all we have to do is to decide
+* are both decided by the assignment logic. So all we have to do is to decide
 * on the inner unrolling.
 *
 * For the unrolling, we can reuse "internal::redux_vec_unroller" from Redux.h,
@@ -54,12 +56,17 @@ struct packetwise_redux_traits
 /* Value to be returned when size==0 , by default let's return 0 */
 template<typename PacketType,typename Func>
 EIGEN_DEVICE_FUNC
-PacketType packetwise_redux_empty_value(const Func& ) { return pset1<PacketType>(0); }
+PacketType packetwise_redux_empty_value(const Func& ) {
+  const typename unpacket_traits<PacketType>::type zero(0);
+  return pset1<PacketType>(zero);
+}
 
 /* For products the default is 1 */
 template<typename PacketType,typename Scalar>
 EIGEN_DEVICE_FUNC
-PacketType packetwise_redux_empty_value(const scalar_product_op<Scalar,Scalar>& ) { return pset1<PacketType>(1); }
+PacketType packetwise_redux_empty_value(const scalar_product_op<Scalar,Scalar>& ) {
+  return pset1<PacketType>(Scalar(1));
+}
 
 /* Perform the actual reduction */
 template<typename Func, typename Evaluator,
@@ -134,8 +141,8 @@ struct evaluator<PartialReduxExpr<ArgType, MemberOp, Direction> >
 {
   typedef PartialReduxExpr<ArgType, MemberOp, Direction> XprType;
   typedef typename internal::nested_eval<ArgType,1>::type ArgTypeNested;
-  typedef typename internal::add_const_on_value_type<ArgTypeNested>::type ConstArgTypeNested;
+  typedef add_const_on_value_type_t<ArgTypeNested> ConstArgTypeNested;
-  typedef typename internal::remove_all<ArgTypeNested>::type ArgTypeNestedCleaned;
+  typedef internal::remove_all_t<ArgTypeNested> ArgTypeNestedCleaned;
   typedef typename ArgType::Scalar InputScalar;
   typedef typename XprType::Scalar Scalar;
   enum {
@@ -147,16 +154,16 @@ struct evaluator<PartialReduxExpr<ArgType, MemberOp, Direction> >
                   : TraversalSize==0 ? 1
                   : int(TraversalSize) * int(evaluator<ArgType>::CoeffReadCost) + int(CostOpType::value),
     
-    _ArgFlags = evaluator<ArgType>::Flags,
+    ArgFlags_ = evaluator<ArgType>::Flags,
 
-    _Vectorizable =  bool(int(_ArgFlags)&PacketAccessBit)
+    Vectorizable_ =  bool(int(ArgFlags_)&PacketAccessBit)
                   && bool(MemberOp::Vectorizable)
-                  && (Direction==int(Vertical) ? bool(_ArgFlags&RowMajorBit) : (_ArgFlags&RowMajorBit)==0)
+                  && (Direction==int(Vertical) ? bool(ArgFlags_&RowMajorBit) : (ArgFlags_&RowMajorBit)==0)
                   && (TraversalSize!=0),
                   
     Flags = (traits<XprType>::Flags&RowMajorBit)
           | (evaluator<ArgType>::Flags&(HereditaryBits&(~RowMajorBit)))
-          | (_Vectorizable ? PacketAccessBit : 0)
+          | (Vectorizable_ ? PacketAccessBit : 0)
           | LinearAccessBit,
     
     Alignment = 0 // FIXME this will need to be improved once PartialReduxExpr is vectorized

libs/eigen/Eigen/src/Core/PermutationMatrix.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_PERMUTATIONMATRIX_H
 #define EIGEN_PERMUTATIONMATRIX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
@@ -269,13 +271,13 @@ class PermutationBase : public EigenBase<Derived>
 };
 
 namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_>
-struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
+struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, StorageIndex_> >
- : traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
+ : traits<Matrix<StorageIndex_,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
 {
   typedef PermutationStorage StorageKind;
-  typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
+  typedef Matrix<StorageIndex_, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
-  typedef _StorageIndex StorageIndex;
+  typedef StorageIndex_ StorageIndex;
   typedef void Scalar;
 };
 }
@@ -287,14 +289,14 @@ struct traits<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _Storag
   *
   * \tparam SizeAtCompileTime the number of rows/cols, or Dynamic
   * \tparam MaxSizeAtCompileTime the maximum number of rows/cols, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it.
-  * \tparam _StorageIndex the integer type of the indices
+  * \tparam StorageIndex_ the integer type of the indices
   *
   * This class represents a permutation matrix, internally stored as a vector of integers.
   *
   * \sa class PermutationBase, class PermutationWrapper, class DiagonalMatrix
   */
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_>
-class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex> >
+class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, StorageIndex_> >
 {
     typedef PermutationBase<PermutationMatrix> Base;
     typedef internal::traits<PermutationMatrix> Traits;
@@ -389,20 +391,20 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
 
 
 namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_, int PacketAccess_>
-struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
+struct traits<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, StorageIndex_>,PacketAccess_> >
- : traits<Matrix<_StorageIndex,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
+ : traits<Matrix<StorageIndex_,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
 {
   typedef PermutationStorage StorageKind;
-  typedef Map<const Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, _PacketAccess> IndicesType;
+  typedef Map<const Matrix<StorageIndex_, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1>, PacketAccess_> IndicesType;
-  typedef _StorageIndex StorageIndex;
+  typedef StorageIndex_ StorageIndex;
   typedef void Scalar;
 };
 }
 
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_, int PacketAccess_>
-class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess>
+class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, StorageIndex_>,PacketAccess_>
-  : public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageIndex>,_PacketAccess> >
+  : public PermutationBase<Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, StorageIndex_>,PacketAccess_> >
 {
     typedef PermutationBase<Map> Base;
     typedef internal::traits<Map> Traits;
@@ -452,18 +454,18 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, _StorageInd
     IndicesType m_indices;
 };
 
-template<typename _IndicesType> class TranspositionsWrapper;
+template<typename IndicesType_> class TranspositionsWrapper;
 namespace internal {
-template<typename _IndicesType>
+template<typename IndicesType_>
-struct traits<PermutationWrapper<_IndicesType> >
+struct traits<PermutationWrapper<IndicesType_> >
 {
   typedef PermutationStorage StorageKind;
   typedef void Scalar;
-  typedef typename _IndicesType::Scalar StorageIndex;
+  typedef typename IndicesType_::Scalar StorageIndex;
-  typedef _IndicesType IndicesType;
+  typedef IndicesType_ IndicesType;
   enum {
-    RowsAtCompileTime = _IndicesType::SizeAtCompileTime,
+    RowsAtCompileTime = IndicesType_::SizeAtCompileTime,
-    ColsAtCompileTime = _IndicesType::SizeAtCompileTime,
+    ColsAtCompileTime = IndicesType_::SizeAtCompileTime,
     MaxRowsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
     MaxColsAtCompileTime = IndicesType::MaxSizeAtCompileTime,
     Flags = 0
@@ -476,14 +478,14 @@ struct traits<PermutationWrapper<_IndicesType> >
   *
   * \brief Class to view a vector of integers as a permutation matrix
   *
-  * \tparam _IndicesType the type of the vector of integer (can be any compatible expression)
+  * \tparam IndicesType_ the type of the vector of integer (can be any compatible expression)
   *
   * This class allows to view any vector expression of integers as a permutation matrix.
   *
   * \sa class PermutationBase, class PermutationMatrix
   */
-template<typename _IndicesType>
+template<typename IndicesType_>
-class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesType> >
+class PermutationWrapper : public PermutationBase<PermutationWrapper<IndicesType_> >
 {
     typedef PermutationBase<PermutationWrapper> Base;
     typedef internal::traits<PermutationWrapper> Traits;
@@ -498,7 +500,7 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
     {}
 
     /** const version of indices(). */
-    const typename internal::remove_all<typename IndicesType::Nested>::type&
+    const internal::remove_all_t<typename IndicesType::Nested>&
     indices() const { return m_indices; }
 
   protected:

libs/eigen/Eigen/src/Core/PlainObjectBase.h

@@ -22,23 +22,20 @@
 # define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
 #endif
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
 template<int MaxSizeAtCompileTime> struct check_rows_cols_for_overflow {
   template <typename Index>
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE constexpr void run(Index, Index) {}
-  static EIGEN_ALWAYS_INLINE void run(Index, Index)
-  {
-  }
 };
 
 template<> struct check_rows_cols_for_overflow<Dynamic> {
   template <typename Index>
-  EIGEN_DEVICE_FUNC
+  EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE constexpr void run(Index rows, Index cols) {
-  static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols)
-  {
     // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
     // we assume Index is signed
     Index max_index = (std::size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
@@ -64,18 +61,18 @@ namespace doxygen {
 // This is a workaround to doxygen not being able to understand the inheritance logic
 // when it is hidden by the dense_xpr_base helper struct.
 // Moreover, doxygen fails to include members that are not documented in the declaration body of
-// MatrixBase if we inherits MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >,
+// MatrixBase if we inherits MatrixBase<Matrix<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> >,
 // this is why we simply inherits MatrixBase, though this does not make sense.
 
 /** This class is just a workaround for Doxygen and it does not not actually exist. */
 template<typename Derived> struct dense_xpr_base_dispatcher;
 /** This class is just a workaround for Doxygen and it does not not actually exist. */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+template<typename Scalar_, int Rows_, int Cols_, int Options_, int MaxRows_, int MaxCols_>
-struct dense_xpr_base_dispatcher<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+struct dense_xpr_base_dispatcher<Matrix<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> >
     : public MatrixBase {};
 /** This class is just a workaround for Doxygen and it does not not actually exist. */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+template<typename Scalar_, int Rows_, int Cols_, int Options_, int MaxRows_, int MaxCols_>
-struct dense_xpr_base_dispatcher<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+struct dense_xpr_base_dispatcher<Array<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_> >
     : public ArrayBase {};
 
 } // namespace doxygen
@@ -134,6 +131,16 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     enum { NeedsToAlign = (SizeAtCompileTime != Dynamic) && (internal::traits<Derived>::Alignment>0) };
     EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
 
+    EIGEN_STATIC_ASSERT(internal::check_implication(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (int(Options)&RowMajor)==RowMajor), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT(internal::check_implication(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (int(Options)&RowMajor)==0), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT((RowsAtCompileTime == Dynamic) || (RowsAtCompileTime >= 0), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT((ColsAtCompileTime == Dynamic) || (ColsAtCompileTime >= 0), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT((MaxRowsAtCompileTime == Dynamic) || (MaxRowsAtCompileTime >= 0), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT((MaxColsAtCompileTime == Dynamic) || (MaxColsAtCompileTime >= 0), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT((MaxRowsAtCompileTime == RowsAtCompileTime || RowsAtCompileTime==Dynamic), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT((MaxColsAtCompileTime == ColsAtCompileTime || ColsAtCompileTime==Dynamic), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    EIGEN_STATIC_ASSERT(((Options & (DontAlign|RowMajor)) == Options), INVALID_MATRIX_TEMPLATE_PARAMETERS)
+
     EIGEN_DEVICE_FUNC
     Base& base() { return *static_cast<Base*>(this); }
     EIGEN_DEVICE_FUNC
@@ -148,9 +155,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts.
       *
       * See DenseCoeffsBase<Derived,ReadOnlyAccessors>::coeff(Index) const for details. */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const Scalar& coeff(Index rowId, Index colId) const {
-    EIGEN_STRONG_INLINE const Scalar& coeff(Index rowId, Index colId) const
-    {
       if (Flags & RowMajorBit)
         return m_storage.data()[colId + rowId * m_storage.cols()];
       else  // column-major
@@ -171,9 +176,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts.
       *
       * See DenseCoeffsBase<Derived,WriteAccessors>::coeffRef(Index,Index) const for details. */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index rowId, Index colId) {
-    EIGEN_STRONG_INLINE Scalar& coeffRef(Index rowId, Index colId)
-    {
       if (Flags & RowMajorBit)
         return m_storage.data()[colId + rowId * m_storage.cols()];
       else  // column-major
@@ -184,17 +187,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts.
       *
       * See DenseCoeffsBase<Derived,WriteAccessors>::coeffRef(Index) const for details. */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index index) { return m_storage.data()[index]; }
-    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
-    {
-      return m_storage.data()[index];
-    }
 
     /** This is the const version of coeffRef(Index,Index) which is thus synonym of coeff(Index,Index).
       * It is provided for convenience. */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const Scalar& coeffRef(Index rowId, Index colId) const {
-    EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const
-    {
       if (Flags & RowMajorBit)
         return m_storage.data()[colId + rowId * m_storage.cols()];
       else  // column-major
@@ -203,9 +200,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 
     /** This is the const version of coeffRef(Index) which is thus synonym of coeff(Index).
       * It is provided for convenience. */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const Scalar& coeffRef(Index index) const {
-    EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const
-    {
       return m_storage.data()[index];
     }
 
@@ -267,13 +262,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
       */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index rows, Index cols) {
-    EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
+      eigen_assert(internal::check_implication(RowsAtCompileTime!=Dynamic, rows==RowsAtCompileTime)
-    {
+                   && internal::check_implication(ColsAtCompileTime!=Dynamic, cols==ColsAtCompileTime)
-      eigen_assert(   EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,rows==RowsAtCompileTime)
+                   && internal::check_implication(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic, rows<=MaxRowsAtCompileTime)
-                   && EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,cols==ColsAtCompileTime)
+                   && internal::check_implication(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic, cols<=MaxColsAtCompileTime)
-                   && EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,rows<=MaxRowsAtCompileTime)
-                   && EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,cols<=MaxColsAtCompileTime)
                    && rows>=0 && cols>=0 && "Invalid sizes when resizing a matrix or array.");
       internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(rows, cols);
       #ifdef EIGEN_INITIALIZE_COEFFS
@@ -297,11 +290,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t)
       */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC inline constexpr void resize(Index size) {
-    inline void resize(Index size)
-    {
         EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase)
-      eigen_assert(((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime==Dynamic || size<=MaxSizeAtCompileTime)) || SizeAtCompileTime == size) && size>=0);
+        eigen_assert(
+            ((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime == Dynamic || size <= MaxSizeAtCompileTime)) ||
+             SizeAtCompileTime == size) &&
+            size >= 0);
 #ifdef EIGEN_INITIALIZE_COEFFS
         bool size_changed = size != this->size();
       #endif
@@ -322,11 +316,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \sa resize(Index,Index)
       */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC inline constexpr void resize(NoChange_t, Index cols) { resize(rows(), cols); }
-    inline void resize(NoChange_t, Index cols)
-    {
-      resize(rows(), cols);
-    }
 
     /** Resizes the matrix, changing only the number of rows. For the parameter of type NoChange_t, just pass the special value \c NoChange
       * as in the example below.
@@ -336,11 +326,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \sa resize(Index,Index)
       */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC inline constexpr void resize(Index rows, NoChange_t) { resize(rows, cols()); }
-    inline void resize(Index rows, NoChange_t)
-    {
-      resize(rows, cols());
-    }
 
     /** Resizes \c *this to have the same dimensions as \a other.
       * Takes care of doing all the checking that's needed.
@@ -475,7 +461,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE PlainObjectBase() : m_storage()
     {
-//       _check_template_params();
 //       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
@@ -486,11 +471,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     explicit PlainObjectBase(internal::constructor_without_unaligned_array_assert)
       : m_storage(internal::constructor_without_unaligned_array_assert())
     {
-//       _check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+      // EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 #endif
 
-#if EIGEN_HAS_RVALUE_REFERENCES
     EIGEN_DEVICE_FUNC
     PlainObjectBase(PlainObjectBase&& other) EIGEN_NOEXCEPT
       : m_storage( std::move(other.m_storage) )
@@ -500,11 +484,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_DEVICE_FUNC
     PlainObjectBase& operator=(PlainObjectBase&& other) EIGEN_NOEXCEPT
     {
-      _check_template_params();
       m_storage = std::move(other.m_storage);
       return *this;
     }
-#endif
 
     /** Copy constructor */
     EIGEN_DEVICE_FUNC
@@ -514,17 +496,14 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols)
       : m_storage(size, rows, cols)
     {
-//       _check_template_params();
 //       EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
     }
 
-    #if EIGEN_HAS_CXX11
+    /** \brief Construct a row of column vector with fixed size from an arbitrary number of coefficients.
-    /** \brief Construct a row of column vector with fixed size from an arbitrary number of coefficients. \cpp11
       *
       * \only_for_vectors
       *
       * This constructor is for 1D array or vectors with more than 4 coefficients.
-      * There exists C++98 analogue constructors for fixed-size array/vector having 1, 2, 3, or 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.
@@ -534,7 +513,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     PlainObjectBase(const Scalar& a0, const Scalar& a1, const Scalar& a2,  const Scalar& a3, const ArgTypes&... args)
       : m_storage()
     {
-      _check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, sizeof...(args) + 4);
       m_storage.data()[0] = a0;
       m_storage.data()[1] = a1;
@@ -546,14 +524,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     }
 
     /** \brief Constructs a Matrix or Array and initializes it by elements given by an initializer list of initializer
-      * lists \cpp11
+      * lists
       */
-    EIGEN_DEVICE_FUNC
+    EIGEN_DEVICE_FUNC explicit constexpr EIGEN_STRONG_INLINE PlainObjectBase(
-    explicit EIGEN_STRONG_INLINE PlainObjectBase(const std::initializer_list<std::initializer_list<Scalar>>& list)
+        const std::initializer_list<std::initializer_list<Scalar>>& list)
-      : m_storage()
+        : m_storage() {
-    {
-      _check_template_params();
-
       size_t list_size = 0;
       if (list.begin() != list.end()) {
         list_size = list.begin()->size();
@@ -581,7 +556,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
         }
       }
     }
-    #endif  // end EIGEN_HAS_CXX11
 
     /** \sa PlainObjectBase::operator=(const EigenBase<OtherDerived>&) */
     template<typename OtherDerived>
@@ -589,7 +563,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase<OtherDerived> &other)
       : m_storage()
     {
-      _check_template_params();
       resizeLike(other);
       _set_noalias(other);
     }
@@ -600,7 +573,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase<OtherDerived> &other)
       : m_storage()
     {
-      _check_template_params();
       resizeLike(other);
       *this = other.derived();
     }
@@ -609,7 +581,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE PlainObjectBase(const ReturnByValue<OtherDerived>& other)
     {
-      _check_template_params();
       // FIXME this does not automatically transpose vectors if necessary
       resize(other.rows(), other.cols());
       other.evalTo(this->derived());
@@ -640,7 +611,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \see class Map
       */
-    //@{
+    ///@{
     static inline ConstMapType Map(const Scalar* data)
     { return ConstMapType(data); }
     static inline MapType Map(Scalar* data)
@@ -704,7 +675,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     template<int Outer, int Inner>
     static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
     { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
-    //@}
+    ///@}
 
     using Base::setConstant;
     EIGEN_DEVICE_FUNC Derived& setConstant(Index size, const Scalar& val);
@@ -800,7 +771,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 
     template<typename T0, typename T1>
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
+    EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, std::enable_if_t<Base::SizeAtCompileTime!=2,T0>* = 0)
     {
       const bool t0_is_integer_alike = internal::is_valid_index_type<T0>::value;
       const bool t1_is_integer_alike = internal::is_valid_index_type<T1>::value;
@@ -812,7 +783,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 
     template<typename T0, typename T1>
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE void _init2(const T0& val0, const T1& val1, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
+    EIGEN_STRONG_INLINE void _init2(const T0& val0, const T1& val1, std::enable_if_t<Base::SizeAtCompileTime==2,T0>* = 0)
     {
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
       m_storage.data()[0] = Scalar(val0);
@@ -822,10 +793,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     template<typename T0, typename T1>
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE void _init2(const Index& val0, const Index& val1,
-                                    typename internal::enable_if<    (!internal::is_same<Index,Scalar>::value)
+                                    std::enable_if_t<    (!internal::is_same<Index,Scalar>::value)
                                                       && (internal::is_same<T0,Index>::value)
                                                       && (internal::is_same<T1,Index>::value)
-                                                                  && Base::SizeAtCompileTime==2,T1>::type* = 0)
+                                                      && Base::SizeAtCompileTime==2,T1>* = 0)
     {
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
       m_storage.data()[0] = Scalar(val0);
@@ -836,8 +807,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     // then the argument is meant to be the size of the object.
     template<typename T>
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE void _init1(Index size, typename internal::enable_if<    (Base::SizeAtCompileTime!=1 || !internal::is_convertible<T, Scalar>::value)
+    EIGEN_STRONG_INLINE void _init1(Index size, std::enable_if_t<    (Base::SizeAtCompileTime!=1 || !internal::is_convertible<T, Scalar>::value)
-                                                                              && ((!internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value || Base::SizeAtCompileTime==Dynamic)),T>::type* = 0)
+                                                                  && ((!internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value || Base::SizeAtCompileTime==Dynamic)),T>* = 0)
     {
       // NOTE MSVC 2008 complains if we directly put bool(NumTraits<T>::IsInteger) as the EIGEN_STATIC_ASSERT argument.
       const bool is_integer_alike = internal::is_valid_index_type<T>::value;
@@ -850,7 +821,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     // We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar type can be implicitly converted)
     template<typename T>
     EIGEN_DEVICE_FUNC
-    EIGEN_STRONG_INLINE void _init1(const Scalar& val0, typename internal::enable_if<Base::SizeAtCompileTime==1 && internal::is_convertible<T, Scalar>::value,T>::type* = 0)
+    EIGEN_STRONG_INLINE void _init1(const Scalar& val0, std::enable_if_t<Base::SizeAtCompileTime==1 && internal::is_convertible<T, Scalar>::value,T>* = 0)
     {
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1)
       m_storage.data()[0] = val0;
@@ -860,10 +831,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     template<typename T>
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE void _init1(const Index& val0,
-                                    typename internal::enable_if<    (!internal::is_same<Index,Scalar>::value)
+                                    std::enable_if_t<    (!internal::is_same<Index,Scalar>::value)
                                                       && (internal::is_same<Index,T>::value)
                                                       && Base::SizeAtCompileTime==1
-                                                                  && internal::is_convertible<T, Scalar>::value,T*>::type* = 0)
+                                                      && internal::is_convertible<T, Scalar>::value,T*>* = 0)
     {
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1)
       m_storage.data()[0] = Scalar(val0);
@@ -916,10 +887,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     template<typename T>
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE void _init1(const Scalar& val0,
-                                    typename internal::enable_if<    Base::SizeAtCompileTime!=Dynamic
+                                    std::enable_if_t<    Base::SizeAtCompileTime!=Dynamic
                                                       && Base::SizeAtCompileTime!=1
                                                       && internal::is_convertible<T, Scalar>::value
-                                                                  && internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T>::type* = 0)
+                                                      && internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T>* = 0)
     {
       Base::setConstant(val0);
     }
@@ -928,12 +899,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     template<typename T>
     EIGEN_DEVICE_FUNC
     EIGEN_STRONG_INLINE void _init1(const Index& val0,
-                                    typename internal::enable_if<    (!internal::is_same<Index,Scalar>::value)
+                                    std::enable_if_t<    (!internal::is_same<Index,Scalar>::value)
                                                       && (internal::is_same<Index,T>::value)
                                                       && Base::SizeAtCompileTime!=Dynamic
                                                       && Base::SizeAtCompileTime!=1
                                                       && internal::is_convertible<T, Scalar>::value
-                                                                  && internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T*>::type* = 0)
+                                                      && internal::is_same<typename internal::traits<Derived>::XprKind,ArrayXpr>::value,T*>* = 0)
     {
       Base::setConstant(val0);
     }
@@ -964,21 +935,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     void swap(DenseBase<OtherDerived> const & other)
     { Base::swap(other.derived()); }
 
-    EIGEN_DEVICE_FUNC
-    static EIGEN_STRONG_INLINE void _check_template_params()
-    {
-      EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (int(Options)&RowMajor)==RowMajor)
-                        && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (int(Options)&RowMajor)==0)
-                        && ((RowsAtCompileTime == Dynamic) || (RowsAtCompileTime >= 0))
-                        && ((ColsAtCompileTime == Dynamic) || (ColsAtCompileTime >= 0))
-                        && ((MaxRowsAtCompileTime == Dynamic) || (MaxRowsAtCompileTime >= 0))
-                        && ((MaxColsAtCompileTime == Dynamic) || (MaxColsAtCompileTime >= 0))
-                        && (MaxRowsAtCompileTime == RowsAtCompileTime || RowsAtCompileTime==Dynamic)
-                        && (MaxColsAtCompileTime == ColsAtCompileTime || ColsAtCompileTime==Dynamic)
-                        && (Options & (DontAlign|RowMajor)) == Options),
-        INVALID_MATRIX_TEMPLATE_PARAMETERS)
-    }
-
     enum { IsPlainObjectBase = 1 };
 #endif
   public:
@@ -999,11 +955,7 @@ namespace internal {
 template <typename Derived, typename OtherDerived, bool IsVector>
 struct conservative_resize_like_impl
 {
-  #if EIGEN_HAS_TYPE_TRAITS
+  static constexpr bool IsRelocatable = std::is_trivially_copyable<typename Derived::Scalar>::value;
-  static const bool IsRelocatable = std::is_trivially_copyable<typename Derived::Scalar>::value;
-  #else
-  static const bool IsRelocatable = !NumTraits<typename Derived::Scalar>::RequireInitialization;
-  #endif
   static void run(DenseBase<Derived>& _this, Index rows, Index cols)
   {
     if (_this.rows() == rows && _this.cols() == cols) return;

libs/eigen/Eigen/src/Core/Product.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_PRODUCT_H
 #define EIGEN_PRODUCT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 template<typename Lhs, typename Rhs, int Option, typename StorageKind> class ProductImpl;
@@ -19,8 +21,8 @@ namespace internal {
 template<typename Lhs, typename Rhs, int Option>
 struct traits<Product<Lhs, Rhs, Option> >
 {
-  typedef typename remove_all<Lhs>::type LhsCleaned;
+  typedef remove_all_t<Lhs> LhsCleaned;
-  typedef typename remove_all<Rhs>::type RhsCleaned;
+  typedef remove_all_t<Rhs> RhsCleaned;
   typedef traits<LhsCleaned> LhsTraits;
   typedef traits<RhsCleaned> RhsTraits;
 
@@ -40,7 +42,7 @@ struct traits<Product<Lhs, Rhs, Option> >
     MaxColsAtCompileTime = RhsTraits::MaxColsAtCompileTime,
 
     // FIXME: only needed by GeneralMatrixMatrixTriangular
-    InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(LhsTraits::ColsAtCompileTime, RhsTraits::RowsAtCompileTime),
+    InnerSize = min_size_prefer_fixed(LhsTraits::ColsAtCompileTime, RhsTraits::RowsAtCompileTime),
 
     // The storage order is somewhat arbitrary here. The correct one will be determined through the evaluator.
     Flags = (MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1) ? RowMajorBit
@@ -58,8 +60,8 @@ struct traits<Product<Lhs, Rhs, Option> >
   *
   * \brief Expression of the product of two arbitrary matrices or vectors
   *
-  * \tparam _Lhs the type of the left-hand side expression
+  * \tparam Lhs_ the type of the left-hand side expression
-  * \tparam _Rhs the type of the right-hand side expression
+  * \tparam Rhs_ the type of the right-hand side expression
   *
   * This class represents an expression of the product of two arbitrary matrices.
   *
@@ -67,16 +69,16 @@ struct traits<Product<Lhs, Rhs, Option> >
   * \tparam Option     can be DefaultProduct, AliasFreeProduct, or LazyProduct
   *
   */
-template<typename _Lhs, typename _Rhs, int Option>
+template<typename Lhs_, typename Rhs_, int Option>
-class Product : public ProductImpl<_Lhs,_Rhs,Option,
+class Product : public ProductImpl<Lhs_,Rhs_,Option,
-                                   typename internal::product_promote_storage_type<typename internal::traits<_Lhs>::StorageKind,
+                                   typename internal::product_promote_storage_type<typename internal::traits<Lhs_>::StorageKind,
-                                                                                   typename internal::traits<_Rhs>::StorageKind,
+                                                                                   typename internal::traits<Rhs_>::StorageKind,
-                                                                                   internal::product_type<_Lhs,_Rhs>::ret>::ret>
+                                                                                   internal::product_type<Lhs_,Rhs_>::ret>::ret>
 {
   public:
 
-    typedef _Lhs Lhs;
+    typedef Lhs_ Lhs;
-    typedef _Rhs Rhs;
+    typedef Rhs_ Rhs;
 
     typedef typename ProductImpl<
         Lhs, Rhs, Option,
@@ -87,8 +89,8 @@ class Product : public ProductImpl<_Lhs,_Rhs,Option,
 
     typedef typename internal::ref_selector<Lhs>::type LhsNested;
     typedef typename internal::ref_selector<Rhs>::type RhsNested;
-    typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
+    typedef internal::remove_all_t<LhsNested> LhsNestedCleaned;
-    typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
+    typedef internal::remove_all_t<RhsNested> RhsNestedCleaned;
 
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs)

libs/eigen/Eigen/src/Core/ProductEvaluators.h

@@ -13,6 +13,8 @@
 #ifndef EIGEN_PRODUCTEVALUATORS_H
 #define EIGEN_PRODUCTEVALUATORS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -107,14 +109,14 @@ struct product_evaluator<Product<Lhs, Rhs, Options>, ProductTag, LhsShape, RhsSh
   explicit product_evaluator(const XprType& xpr)
     : m_result(xpr.rows(), xpr.cols())
   {
-    ::new (static_cast<Base*>(this)) Base(m_result);
+    internal::construct_at<Base>(this, m_result);
 
 // FIXME shall we handle nested_eval here?,
 // if so, then we must take care at removing the call to nested_eval in the specializations (e.g., in permutation_matrix_product, transposition_matrix_product, etc.)
 //     typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
 //     typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
-//     typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
+//     typedef internal::remove_all_t<LhsNested> LhsNestedCleaned;
-//     typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
+//     typedef internal::remove_all_t<RhsNested> RhsNestedCleaned;
 //
 //     const LhsNested lhs(xpr.lhs());
 //     const RhsNested rhs(xpr.rhs());
@@ -134,7 +136,7 @@ protected:
 // Dense = Product
 template< typename DstXprType, typename Lhs, typename Rhs, int Options, typename Scalar>
 struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::assign_op<Scalar,Scalar>, Dense2Dense,
-  typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
+  std::enable_if_t<(Options==DefaultProduct || Options==AliasFreeProduct)>>
 {
   typedef Product<Lhs,Rhs,Options> SrcXprType;
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -152,7 +154,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::assign_op<Scal
 // Dense += Product
 template< typename DstXprType, typename Lhs, typename Rhs, int Options, typename Scalar>
 struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::add_assign_op<Scalar,Scalar>, Dense2Dense,
-  typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
+  std::enable_if_t<(Options==DefaultProduct || Options==AliasFreeProduct)>>
 {
   typedef Product<Lhs,Rhs,Options> SrcXprType;
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -167,7 +169,7 @@ struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::add_assign_op<
 // Dense -= Product
 template< typename DstXprType, typename Lhs, typename Rhs, int Options, typename Scalar>
 struct Assignment<DstXprType, Product<Lhs,Rhs,Options>, internal::sub_assign_op<Scalar,Scalar>, Dense2Dense,
-  typename enable_if<(Options==DefaultProduct || Options==AliasFreeProduct)>::type>
+  std::enable_if_t<(Options==DefaultProduct || Options==AliasFreeProduct)>>
 {
   typedef Product<Lhs,Rhs,Options> SrcXprType;
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -296,7 +298,7 @@ void EIGEN_DEVICE_FUNC outer_product_selector_run(Dst& dst, const Lhs &lhs, cons
 template<typename Lhs, typename Rhs>
 struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,OuterProduct>
 {
-  template<typename T> struct is_row_major : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {};
+  template<typename T> struct is_row_major : std::conditional_t<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type> {};
   typedef typename Product<Lhs,Rhs>::Scalar Scalar;
 
   // TODO it would be nice to be able to exploit our *_assign_op functors for that purpose
@@ -370,7 +372,7 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,GemvProduct>
   typedef typename nested_eval<Rhs,1>::type RhsNested;
   typedef typename Product<Lhs,Rhs>::Scalar Scalar;
   enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
-  typedef typename internal::remove_all<typename internal::conditional<int(Side)==OnTheRight,LhsNested,RhsNested>::type>::type MatrixType;
+  typedef internal::remove_all_t<std::conditional_t<int(Side)==OnTheRight,LhsNested,RhsNested>> MatrixType;
 
   template<typename Dest>
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha)
@@ -427,8 +429,8 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode>
   //  3 - it makes this fallback consistent with the heavy GEMM routine.
   //  4 - it fully by-passes huge stack allocation attempts when multiplying huge fixed-size matrices.
   //      (see https://stackoverflow.com/questions/54738495)
-  // For small fixed sizes matrices, howver, the gains are less obvious, it is sometimes x2 faster, but sometimes x3 slower,
+  // For small fixed sizes matrices, however, the gains are less obvious, it is sometimes x2 faster, but sometimes x3 slower,
-  // and the behavior depends also a lot on the compiler... This is why this re-writting strategy is currently
+  // and the behavior depends also a lot on the compiler... This is why this re-writing strategy is currently
   // enabled only when falling back from the main GEMM.
   template<typename Dst, typename Func>
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
@@ -448,7 +450,7 @@ struct generic_product_impl<Lhs,Rhs,DenseShape,DenseShape,CoeffBasedProductMode>
                       blas_traits<Rhs>::extract(rhs).template conjugateIf<ConjRhs>(),
                       func,
                       actualAlpha,
-                      typename conditional<HasScalarFactor,true_type,false_type>::type());
+                      std::conditional_t<HasScalarFactor,true_type,false_type>());
   }
 
 protected:
@@ -458,7 +460,7 @@ protected:
   void eval_dynamic_impl(Dst& dst, const LhsT& lhs, const RhsT& rhs, const Func &func, const Scalar&  s /* == 1 */, false_type)
   {
     EIGEN_UNUSED_VARIABLE(s);
-    eigen_internal_assert(s==Scalar(1));
+    eigen_internal_assert(numext::is_exactly_one(s));
     call_restricted_packet_assignment_no_alias(dst, lhs.lazyProduct(rhs), func);
   }
 
@@ -526,8 +528,8 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
   typedef typename internal::nested_eval<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
   typedef typename internal::nested_eval<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
 
-  typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
+  typedef internal::remove_all_t<LhsNested> LhsNestedCleaned;
-  typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
+  typedef internal::remove_all_t<RhsNested> RhsNestedCleaned;
 
   typedef evaluator<LhsNestedCleaned> LhsEtorType;
   typedef evaluator<RhsNestedCleaned> RhsEtorType;
@@ -535,7 +537,7 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
   enum {
     RowsAtCompileTime = LhsNestedCleaned::RowsAtCompileTime,
     ColsAtCompileTime = RhsNestedCleaned::ColsAtCompileTime,
-    InnerSize = EIGEN_SIZE_MIN_PREFER_FIXED(LhsNestedCleaned::ColsAtCompileTime, RhsNestedCleaned::RowsAtCompileTime),
+    InnerSize = min_size_prefer_fixed(LhsNestedCleaned::ColsAtCompileTime, RhsNestedCleaned::RowsAtCompileTime),
     MaxRowsAtCompileTime = LhsNestedCleaned::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = RhsNestedCleaned::MaxColsAtCompileTime
   };
@@ -564,8 +566,8 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
     RhsVecPacketSize = unpacket_traits<RhsVecPacketType>::size,
 
     // Here, we don't care about alignment larger than the usable packet size.
-    LhsAlignment = EIGEN_PLAIN_ENUM_MIN(LhsEtorType::Alignment,LhsVecPacketSize*int(sizeof(typename LhsNestedCleaned::Scalar))),
+    LhsAlignment = plain_enum_min(LhsEtorType::Alignment, LhsVecPacketSize*int(sizeof(typename LhsNestedCleaned::Scalar))),
-    RhsAlignment = EIGEN_PLAIN_ENUM_MIN(RhsEtorType::Alignment,RhsVecPacketSize*int(sizeof(typename RhsNestedCleaned::Scalar))),
+    RhsAlignment = plain_enum_min(RhsEtorType::Alignment, RhsVecPacketSize*int(sizeof(typename RhsNestedCleaned::Scalar))),
 
     SameType = is_same<typename LhsNestedCleaned::Scalar,typename RhsNestedCleaned::Scalar>::value,
 
@@ -585,8 +587,8 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
     LhsOuterStrideBytes = int(LhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename LhsNestedCleaned::Scalar)),
     RhsOuterStrideBytes = int(RhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename RhsNestedCleaned::Scalar)),
 
-    Alignment = bool(CanVectorizeLhs) ? (LhsOuterStrideBytes<=0 || (int(LhsOuterStrideBytes) % EIGEN_PLAIN_ENUM_MAX(1,LhsAlignment))!=0 ? 0 : LhsAlignment)
+    Alignment = bool(CanVectorizeLhs) ? (LhsOuterStrideBytes<=0 || (int(LhsOuterStrideBytes) % plain_enum_max(1, LhsAlignment))!=0 ? 0 : LhsAlignment)
-              : bool(CanVectorizeRhs) ? (RhsOuterStrideBytes<=0 || (int(RhsOuterStrideBytes) % EIGEN_PLAIN_ENUM_MAX(1,RhsAlignment))!=0 ? 0 : RhsAlignment)
+              : bool(CanVectorizeRhs) ? (RhsOuterStrideBytes<=0 || (int(RhsOuterStrideBytes) % plain_enum_max(1, RhsAlignment))!=0 ? 0 : RhsAlignment)
               : 0,
 
     /* CanVectorizeInner deserves special explanation. It does not affect the product flags. It is not used outside
@@ -640,8 +642,8 @@ struct product_evaluator<Product<Lhs, Rhs, LazyProduct>, ProductTag, DenseShape,
   }
 
 protected:
-  typename internal::add_const_on_value_type<LhsNested>::type m_lhs;
+  add_const_on_value_type_t<LhsNested> m_lhs;
-  typename internal::add_const_on_value_type<RhsNested>::type m_rhs;
+  add_const_on_value_type_t<RhsNested> m_rhs;
 
   LhsEtorType m_lhsImpl;
   RhsEtorType m_rhsImpl;
@@ -836,22 +838,22 @@ public:
     MatrixFlags = evaluator<MatrixType>::Flags,
     DiagFlags = evaluator<DiagonalType>::Flags,
 
-    _StorageOrder = (Derived::MaxRowsAtCompileTime==1 && Derived::MaxColsAtCompileTime!=1) ? RowMajor
+    StorageOrder_ = (Derived::MaxRowsAtCompileTime==1 && Derived::MaxColsAtCompileTime!=1) ? RowMajor
                   : (Derived::MaxColsAtCompileTime==1 && Derived::MaxRowsAtCompileTime!=1) ? ColMajor
                   : MatrixFlags & RowMajorBit ? RowMajor : ColMajor,
-    _SameStorageOrder = _StorageOrder == (MatrixFlags & RowMajorBit ? RowMajor : ColMajor),
+    SameStorageOrder_ = StorageOrder_ == (MatrixFlags & RowMajorBit ? RowMajor : ColMajor),
 
-    _ScalarAccessOnDiag =  !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
+    ScalarAccessOnDiag_ =  !((int(StorageOrder_) == ColMajor && int(ProductOrder) == OnTheLeft)
-                           ||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
+                           ||(int(StorageOrder_) == RowMajor && int(ProductOrder) == OnTheRight)),
-    _SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
+    SameTypes_ = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
     // FIXME currently we need same types, but in the future the next rule should be the one
-    //_Vectorizable = bool(int(MatrixFlags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagFlags)&PacketAccessBit))),
+    //Vectorizable_ = bool(int(MatrixFlags)&PacketAccessBit) && ((!_PacketOnDiag) || (SameTypes_ && bool(int(DiagFlags)&PacketAccessBit))),
-    _Vectorizable =   bool(int(MatrixFlags)&PacketAccessBit)
+    Vectorizable_ =   bool(int(MatrixFlags)&PacketAccessBit)
-                  &&  _SameTypes
+                  &&  SameTypes_
-                  && (_SameStorageOrder || (MatrixFlags&LinearAccessBit)==LinearAccessBit)
+                  && (SameStorageOrder_ || (MatrixFlags&LinearAccessBit)==LinearAccessBit)
-                  && (_ScalarAccessOnDiag || (bool(int(DiagFlags)&PacketAccessBit))),
+                  && (ScalarAccessOnDiag_ || (bool(int(DiagFlags)&PacketAccessBit))),
-    _LinearAccessMask = (MatrixType::RowsAtCompileTime==1 || MatrixType::ColsAtCompileTime==1) ? LinearAccessBit : 0,
+    LinearAccessMask_ = (MatrixType::RowsAtCompileTime==1 || MatrixType::ColsAtCompileTime==1) ? LinearAccessBit : 0,
-    Flags = ((HereditaryBits|_LinearAccessMask) & (unsigned int)(MatrixFlags)) | (_Vectorizable ? PacketAccessBit : 0),
+    Flags = ((HereditaryBits|LinearAccessMask_) & (unsigned int)(MatrixFlags)) | (Vectorizable_ ? PacketAccessBit : 0),
     Alignment = evaluator<MatrixType>::Alignment,
 
     AsScalarProduct =     (DiagonalType::SizeAtCompileTime==1)
@@ -887,7 +889,7 @@ protected:
   {
     enum {
       InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
-      DiagonalPacketLoadMode = EIGEN_PLAIN_ENUM_MIN(LoadMode,((InnerSize%16) == 0) ? int(Aligned16) : int(evaluator<DiagonalType>::Alignment)) // FIXME hardcoded 16!!
+      DiagonalPacketLoadMode = plain_enum_min(LoadMode,((InnerSize%16) == 0) ? int(Aligned16) : int(evaluator<DiagonalType>::Alignment)) // FIXME hardcoded 16!!
     };
     return internal::pmul(m_matImpl.template packet<LoadMode,PacketType>(row, col),
                           m_diagImpl.template packet<DiagonalPacketLoadMode,PacketType>(id));
@@ -913,7 +915,7 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DiagonalSha
   typedef typename Lhs::DiagonalVectorType DiagonalType;
 
 
-  enum { StorageOrder = Base::_StorageOrder };
+  enum { StorageOrder = Base::StorageOrder_ };
 
   EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
     : Base(xpr.rhs(), xpr.lhs().diagonal())
@@ -932,7 +934,7 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DiagonalSha
     // FIXME: NVCC used to complain about the template keyword, but we have to check whether this is still the case.
     // See also similar calls below.
     return this->template packet_impl<LoadMode,PacketType>(row,col, row,
-                                 typename internal::conditional<int(StorageOrder)==RowMajor, internal::true_type, internal::false_type>::type());
+                                 std::conditional_t<int(StorageOrder)==RowMajor, internal::true_type, internal::false_type>());
   }
 
   template<int LoadMode,typename PacketType>
@@ -957,7 +959,7 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DenseShape,
   typedef Product<Lhs, Rhs, ProductKind> XprType;
   typedef typename XprType::PlainObject PlainObject;
 
-  enum { StorageOrder = Base::_StorageOrder };
+  enum { StorageOrder = Base::StorageOrder_ };
 
   EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr)
     : Base(xpr.lhs(), xpr.rhs().diagonal())
@@ -974,7 +976,7 @@ struct product_evaluator<Product<Lhs, Rhs, ProductKind>, ProductTag, DenseShape,
   EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const
   {
     return this->template packet_impl<LoadMode,PacketType>(row,col, col,
-                                 typename internal::conditional<int(StorageOrder)==ColMajor, internal::true_type, internal::false_type>::type());
+                                 std::conditional_t<int(StorageOrder)==ColMajor, internal::true_type, internal::false_type>());
   }
 
   template<int LoadMode,typename PacketType>
@@ -1001,7 +1003,7 @@ template<typename ExpressionType, int Side, bool Transposed>
 struct permutation_matrix_product<ExpressionType, Side, Transposed, DenseShape>
 {
     typedef typename nested_eval<ExpressionType, 1>::type MatrixType;
-    typedef typename remove_all<MatrixType>::type MatrixTypeCleaned;
+    typedef remove_all_t<MatrixType> MatrixTypeCleaned;
 
     template<typename Dest, typename PermutationType>
     static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Dest& dst, const PermutationType& perm, const ExpressionType& xpr)
@@ -1109,7 +1111,7 @@ template<typename ExpressionType, int Side, bool Transposed, typename Expression
 struct transposition_matrix_product
 {
   typedef typename nested_eval<ExpressionType, 1>::type MatrixType;
-  typedef typename remove_all<MatrixType>::type MatrixTypeCleaned;
+  typedef remove_all_t<MatrixType> MatrixTypeCleaned;
 
   template<typename Dest, typename TranspositionType>
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Dest& dst, const TranspositionType& tr, const ExpressionType& xpr)
@@ -1172,6 +1174,40 @@ struct generic_product_impl<Lhs, Transpose<Rhs>, MatrixShape, TranspositionsShap
   }
 };
 
+/***************************************************************************
+* skew symmetric products
+* for now we just call the generic implementation
+***************************************************************************/
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Rhs, SkewSymmetricShape, MatrixShape, ProductTag>
+{
+  template<typename Dest>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    generic_product_impl<typename Lhs::DenseMatrixType , Rhs, DenseShape, MatrixShape, ProductTag>::evalTo(dst, lhs, rhs);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag, typename MatrixShape>
+struct generic_product_impl<Lhs, Rhs, MatrixShape, SkewSymmetricShape, ProductTag>
+{
+  template<typename Dest>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    generic_product_impl<Lhs, typename Rhs::DenseMatrixType, MatrixShape, DenseShape, ProductTag>::evalTo(dst, lhs, rhs);
+  }
+};
+
+template<typename Lhs, typename Rhs, int ProductTag>
+struct generic_product_impl<Lhs, Rhs, SkewSymmetricShape, SkewSymmetricShape, ProductTag>
+{
+  template<typename Dest>
+  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs)
+  {
+    generic_product_impl<typename Lhs::DenseMatrixType, typename Rhs::DenseMatrixType, DenseShape, DenseShape, ProductTag>::evalTo(dst, lhs, rhs);
+  }
+};
+
 } // end namespace internal
 
 } // end namespace Eigen

libs/eigen/Eigen/src/Core/Random.h

@@ -10,12 +10,13 @@
 #ifndef EIGEN_RANDOM_H
 #define EIGEN_RANDOM_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
 
 template<typename Scalar> struct scalar_random_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_random_op)
   inline const Scalar operator() () const { return random<Scalar>(); }
 };
 

libs/eigen/Eigen/src/Core/Redux.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_REDUX_H
 #define EIGEN_REDUX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
@@ -198,8 +200,7 @@ struct redux_impl<Func, Evaluator, DefaultTraversal, NoUnrolling>
   Scalar run(const Evaluator &eval, const Func& func, const XprType& xpr)
   {
     eigen_assert(xpr.rows()>0 && xpr.cols()>0 && "you are using an empty matrix");
-    Scalar res;
+    Scalar res = eval.coeffByOuterInner(0, 0);
-    res = eval.coeffByOuterInner(0, 0);
     for(Index i = 1; i < xpr.innerSize(); ++i)
       res = func(res, eval.coeffByOuterInner(0, i));
     for(Index i = 1; i < xpr.outerSize(); ++i)
@@ -238,7 +239,7 @@ struct redux_impl<Func, Evaluator, LinearVectorizedTraversal, NoUnrolling>
     const int packetAlignment = unpacket_traits<PacketScalar>::alignment;
     enum {
       alignment0 = (bool(Evaluator::Flags & DirectAccessBit) && bool(packet_traits<Scalar>::AlignedOnScalar)) ? int(packetAlignment) : int(Unaligned),
-      alignment = EIGEN_PLAIN_ENUM_MAX(alignment0, Evaluator::Alignment)
+      alignment = plain_enum_max(alignment0, Evaluator::Alignment)
     };
     const Index alignedStart = internal::first_default_aligned(xpr);
     const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize);
@@ -353,12 +354,12 @@ struct redux_impl<Func, Evaluator, LinearVectorizedTraversal, CompleteUnrolling>
 };
 
 // evaluator adaptor
-template<typename _XprType>
+template<typename XprType_>
-class redux_evaluator : public internal::evaluator<_XprType>
+class redux_evaluator : public internal::evaluator<XprType_>
 {
-  typedef internal::evaluator<_XprType> Base;
+  typedef internal::evaluator<XprType_> Base;
 public:
-  typedef _XprType XprType;
+  typedef XprType_ XprType;
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
   explicit redux_evaluator(const XprType &xpr) : Base(xpr) {}
   

libs/eigen/Eigen/src/Core/Ref.h

@@ -10,20 +10,22 @@
 #ifndef EIGEN_REF_H
 #define EIGEN_REF_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
-template<typename _PlainObjectType, int _Options, typename _StrideType>
+template<typename PlainObjectType_, int Options_, typename StrideType_>
-struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
+struct traits<Ref<PlainObjectType_, Options_, StrideType_> >
-  : public traits<Map<_PlainObjectType, _Options, _StrideType> >
+  : public traits<Map<PlainObjectType_, Options_, StrideType_> >
 {
-  typedef _PlainObjectType PlainObjectType;
+  typedef PlainObjectType_ PlainObjectType;
-  typedef _StrideType StrideType;
+  typedef StrideType_ StrideType;
   enum {
-    Options = _Options,
+    Options = Options_,
-    Flags = traits<Map<_PlainObjectType, _Options, _StrideType> >::Flags | NestByRefBit,
+    Flags = traits<Map<PlainObjectType_, Options_, StrideType_> >::Flags | NestByRefBit,
-    Alignment = traits<Map<_PlainObjectType, _Options, _StrideType> >::Alignment
+    Alignment = traits<Map<PlainObjectType_, Options_, StrideType_> >::Alignment
   };
 
   template<typename Derived> struct match {
@@ -46,7 +48,7 @@ struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
       ScalarTypeMatch = internal::is_same<typename PlainObjectType::Scalar, typename Derived::Scalar>::value,
       MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch && ScalarTypeMatch
     };
-    typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
+    typedef std::conditional_t<MatchAtCompileTime,internal::true_type,internal::false_type> type;
   };
 
 };
@@ -197,8 +199,8 @@ protected:
       return false;
     }
 
-    ::new (static_cast<Base*>(this)) Base(expr.data(), rows, cols);
+    internal::construct_at<Base>(this, expr.data(), rows, cols);
-    ::new (&m_stride) StrideBase(
+    internal::construct_at(&m_stride,
       (StrideType::OuterStrideAtCompileTime == 0) ? 0 : outer_stride,
       (StrideType::InnerStrideAtCompileTime == 0) ? 0 : inner_stride );
     return true;
@@ -285,7 +287,7 @@ template<typename PlainObjectType, int Options, typename StrideType> class Ref
     typedef internal::traits<Ref> Traits;
     template<typename Derived>
     EIGEN_DEVICE_FUNC inline Ref(const PlainObjectBase<Derived>& expr,
-                                 typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0);
+                                 std::enable_if_t<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>* = 0);
   public:
 
     typedef RefBase<Ref> Base;
@@ -295,17 +297,17 @@ template<typename PlainObjectType, int Options, typename StrideType> class Ref
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename Derived>
     EIGEN_DEVICE_FUNC inline Ref(PlainObjectBase<Derived>& expr,
-                                 typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
+                                 std::enable_if_t<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>* = 0)
     {
       EIGEN_STATIC_ASSERT(bool(Traits::template match<Derived>::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH);
-      // Construction must pass since we will not create temprary storage in the non-const case.
+      // Construction must pass since we will not create temporary storage in the non-const case.
       const bool success = Base::construct(expr.derived());
       EIGEN_UNUSED_VARIABLE(success)
       eigen_assert(success);
     }
     template<typename Derived>
     EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr,
-                                 typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
+                                 std::enable_if_t<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>* = 0)
     #else
     /** Implicit constructor from any dense expression */
     template<typename Derived>
@@ -337,7 +339,7 @@ template<typename TPlainObjectType, int Options, typename StrideType> class Ref<
 
     template<typename Derived>
     EIGEN_DEVICE_FUNC inline Ref(const DenseBase<Derived>& expr,
-                                 typename internal::enable_if<bool(Traits::template match<Derived>::ScalarTypeMatch),Derived>::type* = 0)
+                                 std::enable_if_t<bool(Traits::template match<Derived>::ScalarTypeMatch),Derived>* = 0)
     {
 //      std::cout << match_helper<Derived>::HasDirectAccess << "," << match_helper<Derived>::OuterStrideMatch << "," << match_helper<Derived>::InnerStrideMatch << "\n";
 //      std::cout << int(StrideType::OuterStrideAtCompileTime) << " - " << int(Derived::OuterStrideAtCompileTime) << "\n";

libs/eigen/Eigen/src/Core/Replicate.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_REPLICATE_H
 #define EIGEN_REPLICATE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -21,7 +23,7 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
   typedef typename traits<MatrixType>::StorageKind StorageKind;
   typedef typename traits<MatrixType>::XprKind XprKind;
   typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef std::remove_reference_t<MatrixTypeNested> MatrixTypeNested_;
   enum {
     RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic
                       ? Dynamic
@@ -62,19 +64,19 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
   : public internal::dense_xpr_base< Replicate<MatrixType,RowFactor,ColFactor> >::type
 {
     typedef typename internal::traits<Replicate>::MatrixTypeNested MatrixTypeNested;
-    typedef typename internal::traits<Replicate>::_MatrixTypeNested _MatrixTypeNested;
+    typedef typename internal::traits<Replicate>::MatrixTypeNested_ MatrixTypeNested_;
   public:
 
     typedef typename internal::dense_xpr_base<Replicate>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Replicate)
-    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
+    typedef internal::remove_all_t<MatrixType> NestedExpression;
 
     template<typename OriginalMatrixType>
     EIGEN_DEVICE_FUNC
     inline explicit Replicate(const OriginalMatrixType& matrix)
       : m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
     {
-      EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
+      EIGEN_STATIC_ASSERT((internal::is_same<std::remove_const_t<MatrixType>,OriginalMatrixType>::value),
                           THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
       eigen_assert(RowFactor!=Dynamic && ColFactor!=Dynamic);
     }
@@ -84,7 +86,7 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
     inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
       : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
     {
-      EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
+      EIGEN_STATIC_ASSERT((internal::is_same<std::remove_const_t<MatrixType>,OriginalMatrixType>::value),
                           THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
     }
 
@@ -94,7 +96,7 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
     inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); }
 
     EIGEN_DEVICE_FUNC
-    const _MatrixTypeNested& nestedExpression() const
+    const MatrixTypeNested_& nestedExpression() const
     {
       return m_matrix;
     }

libs/eigen/Eigen/src/Core/Reshaped.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_RESHAPED_H
 #define EIGEN_RESHAPED_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class Reshaped
@@ -27,10 +29,9 @@ namespace Eigen {
   * It is the return type of DenseBase::reshaped(NRowsType,NColsType) and
   * most of the time this is the only way it is used.
   *
-  * However, in C++98, if you want to directly maniputate reshaped expressions,
+  * If you want to directly manipulate reshaped expressions,
-  * for instance if you want to write a function returning such an expression, you
+  * for instance if you want to write a function returning such an expression,
-  * will need to use this class. In C++11, it is advised to use the \em auto
+  * it is advised to use the \em auto keyword for such use cases.
-  * keyword for such use cases.
   *
   * Here is an example illustrating the dynamic case:
   * \include class_Reshaped.cpp
@@ -156,7 +157,7 @@ class ReshapedImpl_dense<XprType,Rows,Cols,Order,false>
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ReshapedImpl_dense)
 
     typedef typename internal::ref_selector<XprType>::non_const_type MatrixTypeNested;
-    typedef typename internal::remove_all<XprType>::type NestedExpression;
+    typedef internal::remove_all_t<XprType> NestedExpression;
 
     class InnerIterator;
 
@@ -186,12 +187,12 @@ class ReshapedImpl_dense<XprType,Rows,Cols,Order,false>
 
     /** \returns the nested expression */
     EIGEN_DEVICE_FUNC
-    const typename internal::remove_all<XprType>::type&
+    const internal::remove_all_t<XprType>&
     nestedExpression() const { return m_xpr; }
 
     /** \returns the nested expression */
     EIGEN_DEVICE_FUNC
-    typename internal::remove_reference<XprType>::type&
+    std::remove_reference_t<XprType>&
     nestedExpression() { return m_xpr; }
 
   protected:
@@ -231,7 +232,7 @@ class ReshapedImpl_dense<XprType, Rows, Cols, Order, true>
     {}
 
     EIGEN_DEVICE_FUNC
-    const typename internal::remove_all<XprTypeNested>::type& nestedExpression() const
+    const internal::remove_all_t<XprTypeNested>& nestedExpression() const
     {
       return m_xpr;
     }
@@ -250,7 +251,7 @@ class ReshapedImpl_dense<XprType, Rows, Cols, Order, true>
     EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
     inline Index outerStride() const
     {
-      return ((Flags&RowMajorBit)==RowMajorBit) ? this->cols() : this->rows();
+      return (((Flags&RowMajorBit)==RowMajorBit) ? this->cols() : this->rows()) * m_xpr.innerStride();
     }
 
   protected:
@@ -324,7 +325,7 @@ struct reshaped_evaluator<ArgType, Rows, Cols, Order, /* HasDirectAccess */ fals
 
   typedef std::pair<Index, Index> RowCol;
 
-  inline RowCol index_remap(Index rowId, Index colId) const
+  EIGEN_DEVICE_FUNC inline RowCol index_remap(Index rowId, Index colId) const
   {
     if(Order==ColMajor)
     {
@@ -443,7 +444,7 @@ struct reshaped_evaluator<ArgType, Rows, Cols, Order, /* HasDirectAccess */ true
     : mapbase_evaluator<XprType, typename XprType::PlainObject>(xpr)
   {
     // TODO: for the 3.4 release, this should be turned to an internal assertion, but let's keep it as is for the beta lifetime
-    eigen_assert(((internal::UIntPtr(xpr.data()) % EIGEN_PLAIN_ENUM_MAX(1,evaluator<XprType>::Alignment)) == 0) && "data is not aligned");
+    eigen_assert(((internal::UIntPtr(xpr.data()) % plain_enum_max(1, evaluator<XprType>::Alignment)) == 0) && "data is not aligned");
   }
 };
 

libs/eigen/Eigen/src/Core/ReturnByValue.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_RETURNBYVALUE_H
 #define EIGEN_RETURNBYVALUE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -104,7 +106,7 @@ struct evaluator<ReturnByValue<Derived> >
   EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr)
     : m_result(xpr.rows(), xpr.cols())
   {
-    ::new (static_cast<Base*>(this)) Base(m_result);
+    internal::construct_at<Base>(this, m_result);
     xpr.evalTo(m_result);
   }
 

libs/eigen/Eigen/src/Core/Reverse.h

@@ -12,6 +12,8 @@
 #ifndef EIGEN_REVERSE_H
 #define EIGEN_REVERSE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -24,13 +26,13 @@ struct traits<Reverse<MatrixType, Direction> >
   typedef typename traits<MatrixType>::StorageKind StorageKind;
   typedef typename traits<MatrixType>::XprKind XprKind;
   typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
+  typedef std::remove_reference_t<MatrixTypeNested> MatrixTypeNested_;
   enum {
     RowsAtCompileTime = MatrixType::RowsAtCompileTime,
     ColsAtCompileTime = MatrixType::ColsAtCompileTime,
     MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    Flags = _MatrixTypeNested::Flags & (RowMajorBit | LvalueBit)
+    Flags = MatrixTypeNested_::Flags & (RowMajorBit | LvalueBit)
   };
 };
 
@@ -67,7 +69,7 @@ template<typename MatrixType, int Direction> class Reverse
 
     typedef typename internal::dense_xpr_base<Reverse>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Reverse)
-    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
+    typedef internal::remove_all_t<MatrixType> NestedExpression;
     using Base::IsRowMajor;
 
   protected:
@@ -99,7 +101,7 @@ template<typename MatrixType, int Direction> class Reverse
       return -m_matrix.innerStride();
     }
 
-    EIGEN_DEVICE_FUNC const typename internal::remove_all<typename MatrixType::Nested>::type&
+    EIGEN_DEVICE_FUNC const internal::remove_all_t<typename MatrixType::Nested>&
     nestedExpression() const
     {
       return m_matrix;
@@ -173,10 +175,10 @@ struct vectorwise_reverse_inplace_impl<Vertical>
   template<typename ExpressionType>
   static void run(ExpressionType &xpr)
   {
-    const int HalfAtCompileTime = ExpressionType::RowsAtCompileTime==Dynamic?Dynamic:ExpressionType::RowsAtCompileTime/2;
+    constexpr Index HalfAtCompileTime = ExpressionType::RowsAtCompileTime==Dynamic?Dynamic:ExpressionType::RowsAtCompileTime/2;
     Index half = xpr.rows()/2;
-    xpr.topRows(fix<HalfAtCompileTime>(half))
+    xpr.template topRows<HalfAtCompileTime>(half)
-       .swap(xpr.bottomRows(fix<HalfAtCompileTime>(half)).colwise().reverse());
+       .swap(xpr.template bottomRows<HalfAtCompileTime>(half).colwise().reverse());
   }
 };
 
@@ -186,10 +188,10 @@ struct vectorwise_reverse_inplace_impl<Horizontal>
   template<typename ExpressionType>
   static void run(ExpressionType &xpr)
   {
-    const int HalfAtCompileTime = ExpressionType::ColsAtCompileTime==Dynamic?Dynamic:ExpressionType::ColsAtCompileTime/2;
+    constexpr Index HalfAtCompileTime = ExpressionType::ColsAtCompileTime==Dynamic?Dynamic:ExpressionType::ColsAtCompileTime/2;
     Index half = xpr.cols()/2;
-    xpr.leftCols(fix<HalfAtCompileTime>(half))
+    xpr.template leftCols<HalfAtCompileTime>(half)
-       .swap(xpr.rightCols(fix<HalfAtCompileTime>(half)).rowwise().reverse());
+       .swap(xpr.template rightCols<HalfAtCompileTime>(half).rowwise().reverse());
   }
 };
 

libs/eigen/Eigen/src/Core/Select.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_SELECT_H
 #define EIGEN_SELECT_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class Select
@@ -17,9 +19,9 @@ namespace Eigen {
   *
   * \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
+  * \tparam ConditionMatrixType the type of the \em condition expression which must be a boolean matrix
-  * \param ThenMatrixType the type of the \em then expression
+  * \tparam ThenMatrixType the type of the \em then expression
-  * \param ElseMatrixType the type of the \em else expression
+  * \tparam 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 DenseBase::select() and most of the time this is the only way it is used.

libs/eigen/Eigen/src/Core/SelfAdjointView.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_SELFADJOINTMATRIX_H
 #define EIGEN_SELFADJOINTMATRIX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class SelfAdjointView
@@ -18,8 +20,8 @@ namespace Eigen {
   *
   * \brief Expression of a selfadjoint matrix from a triangular part of a dense matrix
   *
-  * \param MatrixType the type of the dense matrix storing the coefficients
+  * \tparam MatrixType the type of the dense matrix storing the coefficients
-  * \param TriangularPart can be either \c #Lower or \c #Upper
+  * \tparam TriangularPart can be either \c #Lower or \c #Upper
   *
   * This class is an expression of a sefladjoint matrix from a triangular part of a matrix
   * with given dense storage of the coefficients. It is the return type of MatrixBase::selfadjointView()
@@ -33,7 +35,7 @@ template<typename MatrixType, unsigned int UpLo>
 struct traits<SelfAdjointView<MatrixType, UpLo> > : traits<MatrixType>
 {
   typedef typename ref_selector<MatrixType>::non_const_type MatrixTypeNested;
-  typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
+  typedef remove_all_t<MatrixTypeNested> MatrixTypeNestedCleaned;
   typedef MatrixType ExpressionType;
   typedef typename MatrixType::PlainObject FullMatrixType;
   enum {
@@ -46,12 +48,13 @@ struct traits<SelfAdjointView<MatrixType, UpLo> > : traits<MatrixType>
 }
 
 
-template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
+template<typename MatrixType_, unsigned int UpLo> class SelfAdjointView
-  : public TriangularBase<SelfAdjointView<_MatrixType, UpLo> >
+  : public TriangularBase<SelfAdjointView<MatrixType_, UpLo> >
 {
   public:
+    EIGEN_STATIC_ASSERT(UpLo==Lower || UpLo==Upper,SELFADJOINTVIEW_ACCEPTS_UPPER_AND_LOWER_MODE_ONLY)
 
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
     typedef TriangularBase<SelfAdjointView> Base;
     typedef typename internal::traits<SelfAdjointView>::MatrixTypeNested MatrixTypeNested;
     typedef typename internal::traits<SelfAdjointView>::MatrixTypeNestedCleaned MatrixTypeNestedCleaned;
@@ -60,8 +63,8 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
     /** \brief The type of coefficients in this matrix */
     typedef typename internal::traits<SelfAdjointView>::Scalar Scalar;
     typedef typename MatrixType::StorageIndex StorageIndex;
-    typedef typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type MatrixConjugateReturnType;
+    typedef internal::remove_all_t<typename MatrixType::ConjugateReturnType> MatrixConjugateReturnType;
-    typedef SelfAdjointView<typename internal::add_const<MatrixType>::type, UpLo> ConstSelfAdjointView;
+    typedef SelfAdjointView<std::add_const_t<MatrixType>, UpLo> ConstSelfAdjointView;
 
     enum {
       Mode = internal::traits<SelfAdjointView>::Mode,
@@ -71,10 +74,7 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
     typedef typename MatrixType::PlainObject PlainObject;
 
     EIGEN_DEVICE_FUNC
-    explicit inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
+    explicit inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix) { }
-    {
-      EIGEN_STATIC_ASSERT(UpLo==Lower || UpLo==Upper,SELFADJOINTVIEW_ACCEPTS_UPPER_AND_LOWER_MODE_ONLY);
-    }
 
     EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
     inline Index rows() const EIGEN_NOEXCEPT { return m_matrix.rows(); }
@@ -180,16 +180,16 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
       */
     template<unsigned int TriMode>
     EIGEN_DEVICE_FUNC
-    typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)),
+    std::conditional_t<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)),
                             TriangularView<MatrixType,TriMode>,
-                                   TriangularView<typename MatrixType::AdjointReturnType,TriMode> >::type
+                            TriangularView<typename MatrixType::AdjointReturnType,TriMode> >
     triangularView() const
     {
-      typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)), MatrixType&, typename MatrixType::ConstTransposeReturnType>::type tmp1(m_matrix);
+      std::conditional_t<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)), MatrixType&, typename MatrixType::ConstTransposeReturnType> tmp1(m_matrix);
-      typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)), MatrixType&, typename MatrixType::AdjointReturnType>::type tmp2(tmp1);
+      std::conditional_t<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)), MatrixType&, typename MatrixType::AdjointReturnType> tmp2(tmp1);
-      return typename internal::conditional<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)),
+      return std::conditional_t<(TriMode&(Upper|Lower))==(UpLo&(Upper|Lower)),
                           TriangularView<MatrixType,TriMode>,
-                                   TriangularView<typename MatrixType::AdjointReturnType,TriMode> >::type(tmp2);
+                          TriangularView<typename MatrixType::AdjointReturnType,TriMode> >(tmp2);
     }
 
     typedef SelfAdjointView<const MatrixConjugateReturnType,UpLo> ConjugateReturnType;
@@ -203,10 +203,10 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
      */
     template<bool Cond>
     EIGEN_DEVICE_FUNC
-    inline typename internal::conditional<Cond,ConjugateReturnType,ConstSelfAdjointView>::type
+    inline std::conditional_t<Cond,ConjugateReturnType,ConstSelfAdjointView>
     conjugateIf() const
     {
-      typedef typename internal::conditional<Cond,ConjugateReturnType,ConstSelfAdjointView>::type ReturnType;
+      typedef std::conditional_t<Cond,ConjugateReturnType,ConstSelfAdjointView> ReturnType;
       return ReturnType(m_matrix.template conjugateIf<Cond>());
     }
 
@@ -218,10 +218,10 @@ template<typename _MatrixType, unsigned int UpLo> class SelfAdjointView
 
     typedef SelfAdjointView<typename MatrixType::TransposeReturnType,TransposeMode> TransposeReturnType;
      /** \sa MatrixBase::transpose() */
+    template<class Dummy=int>
     EIGEN_DEVICE_FUNC
-    inline TransposeReturnType transpose()
+    inline TransposeReturnType transpose(std::enable_if_t<Eigen::internal::is_lvalue<MatrixType>::value, Dummy*> = nullptr)
     {
-      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
       typename MatrixType::TransposeReturnType tmp(m_matrix);
       return TransposeReturnType(tmp);
     }

libs/eigen/Eigen/src/Core/SelfCwiseBinaryOp.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_SELFCWISEBINARYOP_H
 #define EIGEN_SELFCWISEBINARYOP_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 // TODO generalize the scalar type of 'other'

libs/eigen/Eigen/src/Core/SkewSymmetricMatrix3.h

@@ -0,0 +1,412 @@
+// 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) 2007-2009 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_SKEWSYMMETRICMATRIX3_H
+#define EIGEN_SKEWSYMMETRICMATRIX3_H
+
+#include "./InternalHeaderCheck.h"
+
+namespace Eigen {
+
+/** \class SkewSymmetricBase
+ * \ingroup Core_Module
+ *
+ * \brief Base class for skew symmetric matrices and expressions
+ *
+ * This is the base class that is inherited by SkewSymmetricMatrix3 and related expression
+ * types, which internally use a three vector for storing the entries. SkewSymmetric
+ * types always represent square three times three matrices.
+ *
+ * This implementations follows class DiagonalMatrix
+ *
+ * \tparam Derived is the derived type, a SkewSymmetricMatrix3 or SkewSymmetricWrapper.
+ *
+ * \sa class SkewSymmetricMatrix3, class SkewSymmetricWrapper
+ */
+template<typename Derived>
+class SkewSymmetricBase : public EigenBase<Derived>
+{
+  public:
+    typedef typename internal::traits<Derived>::SkewSymmetricVectorType SkewSymmetricVectorType;
+    typedef typename SkewSymmetricVectorType::Scalar Scalar;
+    typedef typename SkewSymmetricVectorType::RealScalar RealScalar;
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
+
+    enum {
+      RowsAtCompileTime = SkewSymmetricVectorType::SizeAtCompileTime,
+      ColsAtCompileTime = SkewSymmetricVectorType::SizeAtCompileTime,
+      MaxRowsAtCompileTime = SkewSymmetricVectorType::MaxSizeAtCompileTime,
+      MaxColsAtCompileTime = SkewSymmetricVectorType::MaxSizeAtCompileTime,
+      IsVectorAtCompileTime = 0,
+      Flags = NoPreferredStorageOrderBit
+    };
+
+    typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
+    typedef DenseMatrixType DenseType;
+    typedef SkewSymmetricMatrix3<Scalar> PlainObject;
+
+    /** \returns a reference to the derived object. */
+    EIGEN_DEVICE_FUNC
+    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    /** \returns a const reference to the derived object. */
+    EIGEN_DEVICE_FUNC
+    inline Derived& derived() { return *static_cast<Derived*>(this); }
+
+    /**
+     * Constructs a dense matrix from \c *this. Note, this directly returns a dense matrix type,
+     * not an expression.
+     * \returns A dense matrix, with its entries set from the the derived object. */
+    EIGEN_DEVICE_FUNC
+    DenseMatrixType toDenseMatrix() const { return derived(); }
+
+    /** Determinant vanishes */
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR
+    inline Scalar determinant() const { return 0; }
+
+    /** A.transpose() = -A */
+    EIGEN_DEVICE_FUNC
+    PlainObject transpose() const { return (-vector()).asSkewSymmetric(); }
+
+    /** \returns the exponential of this matrix using Rodrigues’ formula */
+    EIGEN_DEVICE_FUNC
+    DenseMatrixType exponential() const {
+      DenseMatrixType retVal = DenseMatrixType::Identity();
+      const SkewSymmetricVectorType& v = vector();
+      if (v.isZero()) {
+        return retVal;
+      }
+      const Scalar norm2 = v.squaredNorm();
+      const Scalar norm = numext::sqrt(norm2);
+      retVal += ((((1 - numext::cos(norm))/norm2)*derived())*derived()) + (numext::sin(norm)/norm)*derived().toDenseMatrix();
+      return retVal;
+    }
+
+    /** \returns a reference to the derived object's vector of coefficients. */
+    EIGEN_DEVICE_FUNC
+    inline const SkewSymmetricVectorType& vector() const { return derived().vector(); }
+    /** \returns a const reference to the derived object's vector of coefficients. */
+    EIGEN_DEVICE_FUNC
+    inline SkewSymmetricVectorType& vector() { return derived().vector(); }
+
+    /** \returns the number of rows. */
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR 
+    inline Index rows() const { return 3; }
+    /** \returns the number of columns. */
+    EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR 
+    inline Index cols() const { return 3; }
+
+    /** \returns the matrix product of \c *this by the dense matrix, \a matrix */
+    template<typename MatrixDerived>
+    EIGEN_DEVICE_FUNC
+    Product<Derived,MatrixDerived,LazyProduct>
+    operator*(const MatrixBase<MatrixDerived> &matrix) const
+    {
+      return Product<Derived, MatrixDerived, LazyProduct>(derived(), matrix.derived());
+    }
+
+    /** \returns the matrix product of \c *this by the skew symmetric matrix, \a matrix */
+    template<typename MatrixDerived>
+    EIGEN_DEVICE_FUNC
+    Product<Derived,MatrixDerived,LazyProduct>
+    operator*(const SkewSymmetricBase<MatrixDerived> &matrix) const
+    {
+      return Product<Derived, MatrixDerived, LazyProduct>(derived(), matrix.derived());
+    }
+
+    template <typename OtherDerived>
+    using SkewSymmetricProductReturnType = SkewSymmetricWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
+        SkewSymmetricVectorType, typename OtherDerived::SkewSymmetricVectorType, product)>;
+
+    /** \returns the wedge product of \c *this by the skew symmetric matrix \a other
+     *  A wedge B = AB - BA */
+    template <typename OtherDerived>
+    EIGEN_DEVICE_FUNC SkewSymmetricProductReturnType<OtherDerived> wedge(
+        const SkewSymmetricBase<OtherDerived>& other) const {
+      return vector().cross(other.vector()).asSkewSymmetric();
+    }
+
+    using SkewSymmetricScaleReturnType =
+        SkewSymmetricWrapper<const EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(SkewSymmetricVectorType, Scalar, product)>;
+
+    /** \returns the product of \c *this by the scalar \a scalar */
+    EIGEN_DEVICE_FUNC
+    inline SkewSymmetricScaleReturnType operator*(const Scalar& scalar) const {
+      return (vector() * scalar).asSkewSymmetric();
+    }
+
+    using ScaleSkewSymmetricReturnType =
+        SkewSymmetricWrapper<const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(Scalar, SkewSymmetricVectorType, product)>;
+
+    /** \returns the product of a scalar and the skew symmetric matrix \a other */
+    EIGEN_DEVICE_FUNC
+    friend inline ScaleSkewSymmetricReturnType operator*(const Scalar& scalar, const SkewSymmetricBase& other) {
+      return (scalar * other.vector()).asSkewSymmetric();
+    }
+
+    template <typename OtherDerived>
+    using SkewSymmetricSumReturnType = SkewSymmetricWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
+        SkewSymmetricVectorType, typename OtherDerived::SkewSymmetricVectorType, sum)>;
+
+    /** \returns the sum of \c *this and the skew symmetric matrix \a other */
+    template <typename OtherDerived>
+    EIGEN_DEVICE_FUNC inline SkewSymmetricSumReturnType<OtherDerived> operator+(
+        const SkewSymmetricBase<OtherDerived>& other) const {
+      return (vector() + other.vector()).asSkewSymmetric();
+    }
+
+    template <typename OtherDerived>
+    using SkewSymmetricDifferenceReturnType = SkewSymmetricWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
+        SkewSymmetricVectorType, typename OtherDerived::SkewSymmetricVectorType, difference)>;
+
+    /** \returns the difference of \c *this and the skew symmetric matrix \a other */
+    template <typename OtherDerived>
+    EIGEN_DEVICE_FUNC inline SkewSymmetricDifferenceReturnType<OtherDerived> operator-(
+        const SkewSymmetricBase<OtherDerived>& other) const {
+      return (vector() - other.vector()).asSkewSymmetric();
+    }
+};
+
+/** \class SkewSymmetricMatrix3
+ * \ingroup Core_Module
+ *
+ * \brief Represents a 3x3 skew symmetric matrix with its storage
+ *
+ * \tparam Scalar_ the type of coefficients
+ *
+ * \sa class SkewSymmetricBase, class SkewSymmetricWrapper
+ */
+
+namespace internal {
+template<typename Scalar_>
+struct traits<SkewSymmetricMatrix3<Scalar_> >
+ : traits<Matrix<Scalar_,3,3,0,3,3> >
+{
+  typedef Matrix<Scalar_,3,1,0,3,1> SkewSymmetricVectorType;
+  typedef SkewSymmetricShape StorageKind;
+  enum {
+    Flags = LvalueBit | NoPreferredStorageOrderBit | NestByRefBit
+  };
+};
+}
+template<typename Scalar_>
+class SkewSymmetricMatrix3
+  : public SkewSymmetricBase<SkewSymmetricMatrix3<Scalar_> >
+{
+  public:
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    typedef typename internal::traits<SkewSymmetricMatrix3>::SkewSymmetricVectorType SkewSymmetricVectorType;
+    typedef const SkewSymmetricMatrix3& Nested;
+    typedef Scalar_ Scalar;
+    typedef typename internal::traits<SkewSymmetricMatrix3>::StorageKind StorageKind;
+    typedef typename internal::traits<SkewSymmetricMatrix3>::StorageIndex StorageIndex;
+    #endif
+
+  protected:
+
+    SkewSymmetricVectorType m_vector;
+
+  public:
+
+    /** const version of vector(). */
+    EIGEN_DEVICE_FUNC
+    inline const SkewSymmetricVectorType& vector() const { return m_vector; }
+    /** \returns a reference to the stored vector of coefficients. */
+    EIGEN_DEVICE_FUNC
+    inline SkewSymmetricVectorType& vector() { return m_vector; }
+
+    /** Default constructor without initialization */
+    EIGEN_DEVICE_FUNC
+    inline SkewSymmetricMatrix3() {}
+
+    /** Constructor from three scalars */
+    EIGEN_DEVICE_FUNC
+    inline SkewSymmetricMatrix3(const Scalar& x, const Scalar& y, const Scalar& z) : m_vector(x,y,z) {}
+
+    /** \brief Constructs a SkewSymmetricMatrix3 from an r-value vector type */
+    EIGEN_DEVICE_FUNC
+    explicit inline SkewSymmetricMatrix3(SkewSymmetricVectorType&& vec) : m_vector(std::move(vec)) {}
+
+    /** generic constructor from expression of the coefficients */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+        explicit inline SkewSymmetricMatrix3(const MatrixBase<OtherDerived>& other) : m_vector(other)
+    {}
+
+    /** Copy constructor. */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    inline SkewSymmetricMatrix3(const SkewSymmetricBase<OtherDerived>& other) : m_vector(other.vector()) {}
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */
+    inline SkewSymmetricMatrix3(const SkewSymmetricMatrix3& other) : m_vector(other.vector()) {}
+    #endif
+
+    /** Copy operator. */
+    template<typename OtherDerived>
+    EIGEN_DEVICE_FUNC
+    SkewSymmetricMatrix3& operator=(const SkewSymmetricBase<OtherDerived>& other)
+    {
+      m_vector = other.vector();
+      return *this;
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** This is a special case of the templated operator=. Its purpose is to
+      * prevent a default operator= from hiding the templated operator=.
+      */
+    EIGEN_DEVICE_FUNC
+    SkewSymmetricMatrix3& operator=(const SkewSymmetricMatrix3& other)
+    {
+      m_vector = other.vector();
+      return *this;
+    }
+    #endif
+
+    typedef SkewSymmetricWrapper<const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, SkewSymmetricVectorType>>
+        InitializeReturnType;
+
+    /** Initializes a skew symmetric matrix with coefficients set to zero */
+    EIGEN_DEVICE_FUNC
+    static InitializeReturnType Zero() { return SkewSymmetricVectorType::Zero().asSkewSymmetric(); }
+
+    /** Sets all coefficients to zero. */
+    EIGEN_DEVICE_FUNC
+    inline void setZero() { m_vector.setZero(); }
+};
+
+/** \class SkewSymmetricWrapper
+  * \ingroup Core_Module
+  *
+  * \brief Expression of a skew symmetric matrix
+  *
+  * \tparam SkewSymmetricVectorType_ the type of the vector of coefficients
+  *
+  * This class is an expression of a skew symmetric matrix, but not storing its own vector of coefficients,
+  * instead wrapping an existing vector expression. It is the return type of MatrixBase::asSkewSymmetric()
+  * and most of the time this is the only way that it is used.
+  *
+  * \sa class SkewSymmetricMatrix3, class SkewSymmetricBase, MatrixBase::asSkewSymmetric()
+  */
+
+namespace internal {
+template<typename SkewSymmetricVectorType_>
+struct traits<SkewSymmetricWrapper<SkewSymmetricVectorType_> >
+{
+  typedef SkewSymmetricVectorType_ SkewSymmetricVectorType;
+  typedef typename SkewSymmetricVectorType::Scalar Scalar;
+  typedef typename SkewSymmetricVectorType::StorageIndex StorageIndex;
+  typedef SkewSymmetricShape StorageKind;
+  typedef typename traits<SkewSymmetricVectorType>::XprKind XprKind;
+  enum {
+    RowsAtCompileTime = SkewSymmetricVectorType::SizeAtCompileTime,
+    ColsAtCompileTime = SkewSymmetricVectorType::SizeAtCompileTime,
+    MaxRowsAtCompileTime = SkewSymmetricVectorType::MaxSizeAtCompileTime,
+    MaxColsAtCompileTime = SkewSymmetricVectorType::MaxSizeAtCompileTime,
+    Flags =  (traits<SkewSymmetricVectorType>::Flags & LvalueBit) | NoPreferredStorageOrderBit
+  };
+};
+}
+
+template<typename SkewSymmetricVectorType_>
+class SkewSymmetricWrapper
+  : public SkewSymmetricBase<SkewSymmetricWrapper<SkewSymmetricVectorType_> >, internal::no_assignment_operator
+{
+  public:
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    typedef SkewSymmetricVectorType_ SkewSymmetricVectorType;
+    typedef SkewSymmetricWrapper Nested;
+    #endif
+
+    /** Constructor from expression of coefficients to wrap. */
+    EIGEN_DEVICE_FUNC
+    explicit inline SkewSymmetricWrapper(SkewSymmetricVectorType& a_vector) : m_vector(a_vector) {}
+
+    /** \returns a const reference to the wrapped expression of coefficients. */
+    EIGEN_DEVICE_FUNC
+    const SkewSymmetricVectorType& vector() const { return m_vector; }
+
+  protected:
+    typename SkewSymmetricVectorType::Nested m_vector;
+};
+
+/** \returns a pseudo-expression of a skew symmetric matrix with *this as vector of coefficients
+  *
+  * \only_for_vectors
+  *
+  * \sa class SkewSymmetricWrapper, class SkewSymmetricMatrix3, vector(), isSkewSymmetric()
+  **/
+template<typename Derived>
+EIGEN_DEVICE_FUNC inline const SkewSymmetricWrapper<const Derived>
+MatrixBase<Derived>::asSkewSymmetric() const
+{
+  return SkewSymmetricWrapper<const Derived>(derived());
+}
+
+/** \returns true if *this is approximately equal to a skew symmetric matrix,
+  *          within the precision given by \a prec.
+  */
+template<typename Derived>
+bool MatrixBase<Derived>::isSkewSymmetric(const RealScalar& prec) const
+{
+  if(cols() != rows()) return false;
+  return (this->transpose() + *this).isZero(prec);
+}
+
+/** \returns the matrix product of \c *this by the skew symmetric matrix \skew.
+ */
+template<typename Derived>
+template<typename SkewDerived>
+EIGEN_DEVICE_FUNC inline const Product<Derived, SkewDerived, LazyProduct>
+MatrixBase<Derived>::operator*(const SkewSymmetricBase<SkewDerived> &skew) const
+{
+  return Product<Derived, SkewDerived, LazyProduct>(derived(), skew.derived());
+}
+
+namespace internal {
+
+template<> struct storage_kind_to_shape<SkewSymmetricShape> { typedef SkewSymmetricShape Shape; };
+
+struct SkewSymmetric2Dense {};
+
+template<> struct AssignmentKind<DenseShape,SkewSymmetricShape> { typedef SkewSymmetric2Dense Kind; };
+
+// SkewSymmetric matrix to Dense assignment
+template< typename DstXprType, typename SrcXprType, typename Functor>
+struct Assignment<DstXprType, SrcXprType, Functor, SkewSymmetric2Dense>
+{
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  {
+    if((dst.rows()!=3) || (dst.cols()!=3)) {
+      dst.resize(3, 3);
+    }
+    dst.diagonal().setZero();
+    const typename SrcXprType::SkewSymmetricVectorType v = src.vector();
+    dst(0, 1) = -v(2);
+    dst(1, 0) = v(2);
+    dst(0, 2) = v(1);
+    dst(2, 0) = -v(1);
+    dst(1, 2) = -v(0);
+    dst(2, 1) = v(0);
+  }
+  
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  { dst.vector() += src.vector(); }
+  
+  static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
+  { dst.vector() -= src.vector(); }
+};
+
+} // namespace internal
+
+}  // end namespace Eigen
+
+#endif // EIGEN_SKEWSYMMETRICMATRIX3_H

libs/eigen/Eigen/src/Core/Solve.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_SOLVE_H
 #define EIGEN_SOLVE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 template<typename Decomposition, typename RhsType, typename StorageKind> class SolveImpl;
@@ -77,7 +79,7 @@ public:
 
 protected:
   const Decomposition &m_dec;
-  const RhsType       &m_rhs;
+  const typename internal::ref_selector<RhsType>::type m_rhs;
 };
 
 
@@ -123,7 +125,7 @@ struct evaluator<Solve<Decomposition,RhsType> >
   EIGEN_DEVICE_FUNC explicit evaluator(const SolveType& solve)
     : m_result(solve.rows(), solve.cols())
   {
-    ::new (static_cast<Base*>(this)) Base(m_result);
+    internal::construct_at<Base>(this, m_result);
     solve.dec()._solve_impl(solve.rhs(), m_result);
   }
 

libs/eigen/Eigen/src/Core/SolveTriangular.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_SOLVETRIANGULAR_H
 #define EIGEN_SOLVETRIANGULAR_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -87,7 +89,7 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
 
   static EIGEN_DEVICE_FUNC void run(const Lhs& lhs, Rhs& rhs)
   {
-    typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsProductTraits::extract(lhs);
+    add_const_on_value_type_t<ActualLhsType> actualLhs = LhsProductTraits::extract(lhs);
 
     const Index size = lhs.rows();
     const Index othersize = Side==OnTheLeft? rhs.cols() : rhs.rows();
@@ -174,11 +176,11 @@ EIGEN_DEVICE_FUNC void TriangularViewImpl<MatrixType,Mode,Dense>::solveInPlace(c
     return;
 
   enum { copy = (internal::traits<OtherDerived>::Flags & RowMajorBit)  && OtherDerived::IsVectorAtCompileTime && OtherDerived::SizeAtCompileTime!=1};
-  typedef typename internal::conditional<copy,
+  typedef std::conditional_t<copy,
-    typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&>::type OtherCopy;
+    typename internal::plain_matrix_type_column_major<OtherDerived>::type, OtherDerived&> OtherCopy;
   OtherCopy otherCopy(other);
 
-  internal::triangular_solver_selector<MatrixType, typename internal::remove_reference<OtherCopy>::type,
+  internal::triangular_solver_selector<MatrixType, std::remove_reference_t<OtherCopy>,
     Side, Mode>::run(derived().nestedExpression(), otherCopy);
 
   if (copy)
@@ -206,7 +208,7 @@ struct traits<triangular_solve_retval<Side, TriangularType, Rhs> >
 template<int Side, typename TriangularType, typename Rhs> struct triangular_solve_retval
  : public ReturnByValue<triangular_solve_retval<Side, TriangularType, Rhs> >
 {
-  typedef typename remove_all<typename Rhs::Nested>::type RhsNestedCleaned;
+  typedef remove_all_t<typename Rhs::Nested> RhsNestedCleaned;
   typedef ReturnByValue<triangular_solve_retval> Base;
 
   triangular_solve_retval(const TriangularType& tri, const Rhs& rhs)

libs/eigen/Eigen/src/Core/SolverBase.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_SOLVERBASE_H
 #define EIGEN_SOLVERBASE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -28,7 +30,7 @@ struct solve_assertion<Transpose<Derived> >
     template<bool Transpose_, typename Rhs>
     static void run(const type& transpose, const Rhs& b)
     {
-        internal::solve_assertion<typename internal::remove_all<Derived>::type>::template run<true>(transpose.nestedExpression(), b);
+        internal::solve_assertion<internal::remove_all_t<Derived>>::template run<true>(transpose.nestedExpression(), b);
     }
 };
 
@@ -40,7 +42,7 @@ struct solve_assertion<CwiseUnaryOp<Eigen::internal::scalar_conjugate_op<Scalar>
     template<bool Transpose_, typename Rhs>
     static void run(const type& adjoint, const Rhs& b)
     {
-        internal::solve_assertion<typename internal::remove_all<Transpose<Derived> >::type>::template run<true>(adjoint.nestedExpression(), b);
+        internal::solve_assertion<internal::remove_all_t<Transpose<Derived> >>::template run<true>(adjoint.nestedExpression(), b);
     }
 };
 } // end namespace internal
@@ -79,12 +81,11 @@ class SolverBase : public EigenBase<Derived>
     enum {
       RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
       ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
-      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
+      SizeAtCompileTime = (internal::size_of_xpr_at_compile_time<Derived>::ret),
-                                                          internal::traits<Derived>::ColsAtCompileTime>::ret),
       MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
-      MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
+      MaxSizeAtCompileTime = internal::size_at_compile_time(internal::traits<Derived>::MaxRowsAtCompileTime,
-                                                             internal::traits<Derived>::MaxColsAtCompileTime>::ret),
+                                                            internal::traits<Derived>::MaxColsAtCompileTime),
       IsVectorAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime == 1
                            || internal::traits<Derived>::MaxColsAtCompileTime == 1,
       NumDimensions = int(MaxSizeAtCompileTime) == 1 ? 0 : bool(IsVectorAtCompileTime) ? 1 : 2
@@ -105,12 +106,12 @@ class SolverBase : public EigenBase<Derived>
     inline const Solve<Derived, Rhs>
     solve(const MatrixBase<Rhs>& b) const
     {
-      internal::solve_assertion<typename internal::remove_all<Derived>::type>::template run<false>(derived(), b);
+      internal::solve_assertion<internal::remove_all_t<Derived>>::template run<false>(derived(), b);
       return Solve<Derived, Rhs>(derived(), b.derived());
     }
 
     /** \internal the return type of transpose() */
-    typedef typename internal::add_const<Transpose<const Derived> >::type ConstTransposeReturnType;
+    typedef Transpose<const Derived> ConstTransposeReturnType;
     /** \returns an expression of the transposed of the factored matrix.
       *
       * A typical usage is to solve for the transposed problem A^T x = b:
@@ -118,16 +119,16 @@ class SolverBase : public EigenBase<Derived>
       *
       * \sa adjoint(), solve()
       */
-    inline ConstTransposeReturnType transpose() const
+    inline const ConstTransposeReturnType transpose() const
     {
       return ConstTransposeReturnType(derived());
     }
 
     /** \internal the return type of adjoint() */
-    typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
+    typedef std::conditional_t<NumTraits<Scalar>::IsComplex,
-                        CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, ConstTransposeReturnType>,
+               CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, const ConstTransposeReturnType>,
-                        ConstTransposeReturnType
+               const ConstTransposeReturnType
-                     >::type AdjointReturnType;
+            > AdjointReturnType;
     /** \returns an expression of the adjoint of the factored matrix
       *
       * A typical usage is to solve for the adjoint problem A' x = b:
@@ -137,7 +138,7 @@ class SolverBase : public EigenBase<Derived>
       *
       * \sa transpose(), solve()
       */
-    inline AdjointReturnType adjoint() const
+    inline const AdjointReturnType adjoint() const
     {
       return AdjointReturnType(derived().transpose());
     }

libs/eigen/Eigen/src/Core/StableNorm.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_STABLENORM_H
 #define EIGEN_STABLENORM_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
@@ -57,7 +59,7 @@ void stable_norm_impl_inner_step(const VectorType &vec, RealScalar& ssq, RealSca
   const Index blockSize = 4096;
   
   typedef typename internal::nested_eval<VectorType,2>::type VectorTypeCopy;
-  typedef typename internal::remove_all<VectorTypeCopy>::type VectorTypeCopyClean;
+  typedef internal::remove_all_t<VectorTypeCopy> VectorTypeCopyClean;
   const VectorTypeCopy copy(vec);
   
   enum {
@@ -66,8 +68,8 @@ void stable_norm_impl_inner_step(const VectorType &vec, RealScalar& ssq, RealSca
                ) && (blockSize*sizeof(Scalar)*2<EIGEN_STACK_ALLOCATION_LIMIT)
                  && (EIGEN_MAX_STATIC_ALIGN_BYTES>0) // if we cannot allocate on the stack, then let's not bother about this optimization
   };
-  typedef typename internal::conditional<CanAlign, Ref<const Matrix<Scalar,Dynamic,1,0,blockSize,1>, internal::evaluator<VectorTypeCopyClean>::Alignment>,
+  typedef std::conditional_t<CanAlign, Ref<const Matrix<Scalar,Dynamic,1,0,blockSize,1>, internal::evaluator<VectorTypeCopyClean>::Alignment>,
-                                                   typename VectorTypeCopyClean::ConstSegmentReturnType>::type SegmentWrapper;
+                                                   typename VectorTypeCopyClean::ConstSegmentReturnType> SegmentWrapper;
   Index n = vec.size();
   
   Index bi = internal::first_default_aligned(copy);
@@ -79,7 +81,7 @@ void stable_norm_impl_inner_step(const VectorType &vec, RealScalar& ssq, RealSca
 
 template<typename VectorType>
 typename VectorType::RealScalar
-stable_norm_impl(const VectorType &vec, typename enable_if<VectorType::IsVectorAtCompileTime>::type* = 0 )
+stable_norm_impl(const VectorType &vec, std::enable_if_t<VectorType::IsVectorAtCompileTime>* = 0 )
 {
   using std::sqrt;
   using std::abs;
@@ -101,7 +103,7 @@ stable_norm_impl(const VectorType &vec, typename enable_if<VectorType::IsVectorA
 
 template<typename MatrixType>
 typename MatrixType::RealScalar
-stable_norm_impl(const MatrixType &mat, typename enable_if<!MatrixType::IsVectorAtCompileTime>::type* = 0 )
+stable_norm_impl(const MatrixType &mat, std::enable_if_t<!MatrixType::IsVectorAtCompileTime>* = 0 )
 {
   using std::sqrt;
 

libs/eigen/Eigen/src/Core/StlIterators.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_STLITERATORS_H
 #define EIGEN_STLITERATORS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -25,7 +27,7 @@ protected:
   typedef typename traits::XprType XprType;
   typedef indexed_based_stl_iterator_base<typename traits::non_const_iterator> non_const_iterator;
   typedef indexed_based_stl_iterator_base<typename traits::const_iterator> const_iterator;
-  typedef typename internal::conditional<internal::is_const<XprType>::value,non_const_iterator,const_iterator>::type other_iterator;
+  typedef std::conditional_t<internal::is_const<XprType>::value,non_const_iterator,const_iterator> other_iterator;
   // NOTE: in C++03 we cannot declare friend classes through typedefs because we need to write friend class:
   friend class indexed_based_stl_iterator_base<typename traits::const_iterator>;
   friend class indexed_based_stl_iterator_base<typename traits::non_const_iterator>;
@@ -104,7 +106,7 @@ protected:
   typedef typename traits::XprType XprType;
   typedef indexed_based_stl_reverse_iterator_base<typename traits::non_const_iterator> non_const_iterator;
   typedef indexed_based_stl_reverse_iterator_base<typename traits::const_iterator> const_iterator;
-  typedef typename internal::conditional<internal::is_const<XprType>::value,non_const_iterator,const_iterator>::type other_iterator;
+  typedef std::conditional_t<internal::is_const<XprType>::value,non_const_iterator,const_iterator> other_iterator;
   // NOTE: in C++03 we cannot declare friend classes through typedefs because we need to write friend class:
   friend class indexed_based_stl_reverse_iterator_base<typename traits::const_iterator>;
   friend class indexed_based_stl_reverse_iterator_base<typename traits::non_const_iterator>;
@@ -179,18 +181,18 @@ template<typename XprType>
 class pointer_based_stl_iterator
 {
   enum { is_lvalue  = internal::is_lvalue<XprType>::value };
-  typedef pointer_based_stl_iterator<typename internal::remove_const<XprType>::type> non_const_iterator;
+  typedef pointer_based_stl_iterator<std::remove_const_t<XprType>> non_const_iterator;
-  typedef pointer_based_stl_iterator<typename internal::add_const<XprType>::type> const_iterator;
+  typedef pointer_based_stl_iterator<std::add_const_t<XprType>> const_iterator;
-  typedef typename internal::conditional<internal::is_const<XprType>::value,non_const_iterator,const_iterator>::type other_iterator;
+  typedef std::conditional_t<internal::is_const<XprType>::value,non_const_iterator,const_iterator> other_iterator;
   // NOTE: in C++03 we cannot declare friend classes through typedefs because we need to write friend class:
-  friend class pointer_based_stl_iterator<typename internal::add_const<XprType>::type>;
+  friend class pointer_based_stl_iterator<std::add_const_t<XprType>>;
-  friend class pointer_based_stl_iterator<typename internal::remove_const<XprType>::type>;
+  friend class pointer_based_stl_iterator<std::remove_const_t<XprType>>;
 public:
   typedef Index difference_type;
   typedef typename XprType::Scalar value_type;
   typedef std::random_access_iterator_tag iterator_category;
-  typedef typename internal::conditional<bool(is_lvalue), value_type*, const value_type*>::type pointer;
+  typedef std::conditional_t<bool(is_lvalue), value_type*, const value_type*> pointer;
-  typedef typename internal::conditional<bool(is_lvalue), value_type&, const value_type&>::type reference;
+  typedef std::conditional_t<bool(is_lvalue), value_type&, const value_type&> reference;
 
 
   pointer_based_stl_iterator() EIGEN_NO_THROW : m_ptr(0) {}
@@ -256,12 +258,12 @@ protected:
   internal::variable_if_dynamic<Index, XprType::InnerStrideAtCompileTime> m_incr;
 };
 
-template<typename _XprType>
+template<typename XprType_>
-struct indexed_based_stl_iterator_traits<generic_randaccess_stl_iterator<_XprType> >
+struct indexed_based_stl_iterator_traits<generic_randaccess_stl_iterator<XprType_> >
 {
-  typedef _XprType XprType;
+  typedef XprType_ XprType;
-  typedef generic_randaccess_stl_iterator<typename internal::remove_const<XprType>::type> non_const_iterator;
+  typedef generic_randaccess_stl_iterator<std::remove_const_t<XprType>> non_const_iterator;
-  typedef generic_randaccess_stl_iterator<typename internal::add_const<XprType>::type> const_iterator;
+  typedef generic_randaccess_stl_iterator<std::add_const_t<XprType>> const_iterator;
 };
 
 template<typename XprType>
@@ -283,13 +285,13 @@ protected:
 
   // TODO currently const Transpose/Reshape expressions never returns const references,
   // so lets return by value too.
-  //typedef typename internal::conditional<bool(has_direct_access), const value_type&, const value_type>::type read_only_ref_t;
+  //typedef std::conditional_t<bool(has_direct_access), const value_type&, const value_type> read_only_ref_t;
   typedef const value_type read_only_ref_t;
 
 public:
   
-  typedef typename internal::conditional<bool(is_lvalue), value_type *, const value_type *>::type pointer;
+  typedef std::conditional_t<bool(is_lvalue), value_type *, const value_type *> pointer;
-  typedef typename internal::conditional<bool(is_lvalue), value_type&, read_only_ref_t>::type reference;
+  typedef std::conditional_t<bool(is_lvalue), value_type&, read_only_ref_t> reference;
   
   generic_randaccess_stl_iterator() : Base() {}
   generic_randaccess_stl_iterator(XprType& xpr, Index index) : Base(xpr,index) {}
@@ -301,12 +303,12 @@ public:
   pointer   operator->()        const { return &((*mp_xpr)(m_index)); }
 };
 
-template<typename _XprType, DirectionType Direction>
+template<typename XprType_, DirectionType Direction>
-struct indexed_based_stl_iterator_traits<subvector_stl_iterator<_XprType,Direction> >
+struct indexed_based_stl_iterator_traits<subvector_stl_iterator<XprType_,Direction> >
 {
-  typedef _XprType XprType;
+  typedef XprType_ XprType;
-  typedef subvector_stl_iterator<typename internal::remove_const<XprType>::type, Direction> non_const_iterator;
+  typedef subvector_stl_iterator<std::remove_const_t<XprType>, Direction> non_const_iterator;
-  typedef subvector_stl_iterator<typename internal::add_const<XprType>::type, Direction> const_iterator;
+  typedef subvector_stl_iterator<std::add_const_t<XprType>, Direction> const_iterator;
 };
 
 template<typename XprType, DirectionType Direction>
@@ -320,12 +322,12 @@ protected:
   using Base::m_index;
   using Base::mp_xpr;
 
-  typedef typename internal::conditional<Direction==Vertical,typename XprType::ColXpr,typename XprType::RowXpr>::type SubVectorType;
+  typedef std::conditional_t<Direction==Vertical,typename XprType::ColXpr,typename XprType::RowXpr> SubVectorType;
-  typedef typename internal::conditional<Direction==Vertical,typename XprType::ConstColXpr,typename XprType::ConstRowXpr>::type ConstSubVectorType;
+  typedef std::conditional_t<Direction==Vertical,typename XprType::ConstColXpr,typename XprType::ConstRowXpr> ConstSubVectorType;
 
 
 public:
-  typedef typename internal::conditional<bool(is_lvalue), SubVectorType, ConstSubVectorType>::type reference;
+  typedef std::conditional_t<bool(is_lvalue), SubVectorType, ConstSubVectorType> reference;
   typedef typename reference::PlainObject value_type;
 
 private:
@@ -349,12 +351,12 @@ public:
   pointer   operator->()        const { return (*mp_xpr).template subVector<Direction>(m_index); }
 };
 
-template<typename _XprType, DirectionType Direction>
+template<typename XprType_, DirectionType Direction>
-struct indexed_based_stl_iterator_traits<subvector_stl_reverse_iterator<_XprType,Direction> >
+struct indexed_based_stl_iterator_traits<subvector_stl_reverse_iterator<XprType_,Direction> >
 {
-  typedef _XprType XprType;
+  typedef XprType_ XprType;
-  typedef subvector_stl_reverse_iterator<typename internal::remove_const<XprType>::type, Direction> non_const_iterator;
+  typedef subvector_stl_reverse_iterator<std::remove_const_t<XprType>, Direction> non_const_iterator;
-  typedef subvector_stl_reverse_iterator<typename internal::add_const<XprType>::type, Direction> const_iterator;
+  typedef subvector_stl_reverse_iterator<std::add_const_t<XprType>, Direction> const_iterator;
 };
 
 template<typename XprType, DirectionType Direction>
@@ -368,12 +370,12 @@ protected:
   using Base::m_index;
   using Base::mp_xpr;
 
-  typedef typename internal::conditional<Direction==Vertical,typename XprType::ColXpr,typename XprType::RowXpr>::type SubVectorType;
+  typedef std::conditional_t<Direction==Vertical,typename XprType::ColXpr,typename XprType::RowXpr> SubVectorType;
-  typedef typename internal::conditional<Direction==Vertical,typename XprType::ConstColXpr,typename XprType::ConstRowXpr>::type ConstSubVectorType;
+  typedef std::conditional_t<Direction==Vertical,typename XprType::ConstColXpr,typename XprType::ConstRowXpr> ConstSubVectorType;
 
 
 public:
-  typedef typename internal::conditional<bool(is_lvalue), SubVectorType, ConstSubVectorType>::type reference;
+  typedef std::conditional_t<bool(is_lvalue), SubVectorType, ConstSubVectorType> reference;
   typedef typename reference::PlainObject value_type;
 
 private:

libs/eigen/Eigen/src/Core/Stride.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_STRIDE_H
 #define EIGEN_STRIDE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class Stride
@@ -31,27 +33,31 @@ namespace Eigen {
   * arguments to the constructor.
   *
   * Indeed, this class takes two template parameters:
-  *  \tparam _OuterStrideAtCompileTime the outer stride, or Dynamic if you want to specify it at runtime.
+  *  \tparam OuterStrideAtCompileTime_ the outer stride, or Dynamic if you want to specify it at runtime.
-  *  \tparam _InnerStrideAtCompileTime the inner stride, or Dynamic if you want to specify it at runtime.
+  *  \tparam InnerStrideAtCompileTime_ the inner stride, or Dynamic if you want to specify it at runtime.
   *
   * Here is an example:
   * \include Map_general_stride.cpp
   * Output: \verbinclude Map_general_stride.out
   *
-  * Both strides can be negative, however, a negative stride of -1 cannot be specified at compiletime
+  * Both strides can be negative. However, a negative stride of -1 cannot be specified at compile time
   * because of the ambiguity with Dynamic which is defined to -1 (historically, negative strides were
   * not allowed).
   *
+  * Note that for compile-time vectors (ColsAtCompileTime==1 or RowsAtCompile==1),
+  * the inner stride is the pointer increment between two consecutive elements,
+  * regardless of storage layout.
+  *
   * \sa class InnerStride, class OuterStride, \ref TopicStorageOrders
   */
-template<int _OuterStrideAtCompileTime, int _InnerStrideAtCompileTime>
+template<int OuterStrideAtCompileTime_, int InnerStrideAtCompileTime_>
 class Stride
 {
   public:
     typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
     enum {
-      InnerStrideAtCompileTime = _InnerStrideAtCompileTime,
+      InnerStrideAtCompileTime = InnerStrideAtCompileTime_,
-      OuterStrideAtCompileTime = _OuterStrideAtCompileTime
+      OuterStrideAtCompileTime = OuterStrideAtCompileTime_
     };
 
     /** Default constructor, for use when strides are fixed at compile time */

libs/eigen/Eigen/src/Core/Swap.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_SWAP_H
 #define EIGEN_SWAP_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {

libs/eigen/Eigen/src/Core/Transpose.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_TRANSPOSE_H
 #define EIGEN_TRANSPOSE_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -18,7 +20,7 @@ template<typename MatrixType>
 struct traits<Transpose<MatrixType> > : public traits<MatrixType>
 {
   typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
-  typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain;
+  typedef std::remove_reference_t<MatrixTypeNested> MatrixTypeNestedPlain;
   enum {
     RowsAtCompileTime = MatrixType::ColsAtCompileTime,
     ColsAtCompileTime = MatrixType::RowsAtCompileTime,
@@ -58,7 +60,7 @@ template<typename MatrixType> class Transpose
 
     typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
-    typedef typename internal::remove_all<MatrixType>::type NestedExpression;
+    typedef internal::remove_all_t<MatrixType> NestedExpression;
 
     EIGEN_DEVICE_FUNC
     explicit EIGEN_STRONG_INLINE Transpose(MatrixType& matrix) : m_matrix(matrix) {}
@@ -72,12 +74,12 @@ template<typename MatrixType> class Transpose
 
     /** \returns the nested expression */
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const typename internal::remove_all<MatrixTypeNested>::type&
+    const internal::remove_all_t<MatrixTypeNested>&
     nestedExpression() const { return m_matrix; }
 
     /** \returns the nested expression */
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    typename internal::remove_reference<MatrixTypeNested>::type&
+    std::remove_reference_t<MatrixTypeNested>&
     nestedExpression() { return m_matrix; }
 
     /** \internal */
@@ -130,11 +132,11 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     Index outerStride() const { return derived().nestedExpression().outerStride(); }
 
-    typedef typename internal::conditional<
+    typedef std::conditional_t<
               internal::is_lvalue<MatrixType>::value,
               Scalar,
               const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
+            > ScalarWithConstIfNotLvalue;
 
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
@@ -178,7 +180,7 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
   * \sa transposeInPlace(), adjoint() */
 template<typename Derived>
 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-Transpose<Derived>
+typename DenseBase<Derived>::TransposeReturnType
 DenseBase<Derived>::transpose()
 {
   return TransposeReturnType(derived());
@@ -191,7 +193,7 @@ DenseBase<Derived>::transpose()
   * \sa transposeInPlace(), adjoint() */
 template<typename Derived>
 EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-typename DenseBase<Derived>::ConstTransposeReturnType
+const typename DenseBase<Derived>::ConstTransposeReturnType
 DenseBase<Derived>::transpose() const
 {
   return ConstTransposeReturnType(derived());

libs/eigen/Eigen/src/Core/Transpositions.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_TRANSPOSITIONS_H
 #define EIGEN_TRANSPOSITIONS_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 template<typename Derived>
@@ -113,11 +115,11 @@ class TranspositionsBase
 };
 
 namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_>
-struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
+struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,StorageIndex_> >
- : traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
+ : traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,StorageIndex_> >
 {
-  typedef Matrix<_StorageIndex, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
+  typedef Matrix<StorageIndex_, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> IndicesType;
   typedef TranspositionsStorage StorageKind;
 };
 }
@@ -151,8 +153,8 @@ struct traits<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageInde
   * \sa class PermutationMatrix
   */
 
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_>
-class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
+class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,StorageIndex_> >
 {
     typedef internal::traits<Transpositions> Traits;
   public:
@@ -199,19 +201,19 @@ class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTim
 
 
 namespace internal {
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int _PacketAccess>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_, int PacketAccess_>
-struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,_PacketAccess> >
+struct traits<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,StorageIndex_>,PacketAccess_> >
- : traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex> >
+ : traits<PermutationMatrix<SizeAtCompileTime,MaxSizeAtCompileTime,StorageIndex_> >
 {
-  typedef Map<const Matrix<_StorageIndex,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, _PacketAccess> IndicesType;
+  typedef Map<const Matrix<StorageIndex_,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1>, PacketAccess_> IndicesType;
-  typedef _StorageIndex StorageIndex;
+  typedef StorageIndex_ StorageIndex;
   typedef TranspositionsStorage StorageKind;
 };
 }
 
-template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename _StorageIndex, int PacketAccess>
+template<int SizeAtCompileTime, int MaxSizeAtCompileTime, typename StorageIndex_, int PacketAccess>
-class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess>
+class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,StorageIndex_>,PacketAccess>
- : public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,PacketAccess> >
+ : public TranspositionsBase<Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,StorageIndex_>,PacketAccess> >
 {
     typedef internal::traits<Map> Traits;
   public:
@@ -260,17 +262,17 @@ class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,_StorageIndex>,P
 };
 
 namespace internal {
-template<typename _IndicesType>
+template<typename IndicesType_>
-struct traits<TranspositionsWrapper<_IndicesType> >
+struct traits<TranspositionsWrapper<IndicesType_> >
- : traits<PermutationWrapper<_IndicesType> >
+ : traits<PermutationWrapper<IndicesType_> >
 {
   typedef TranspositionsStorage StorageKind;
 };
 }
 
-template<typename _IndicesType>
+template<typename IndicesType_>
 class TranspositionsWrapper
- : public TranspositionsBase<TranspositionsWrapper<_IndicesType> >
+ : public TranspositionsBase<TranspositionsWrapper<IndicesType_> >
 {
     typedef internal::traits<TranspositionsWrapper> Traits;
   public:

libs/eigen/Eigen/src/Core/TriangularMatrix.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_TRIANGULARMATRIX_H
 #define EIGEN_TRIANGULARMATRIX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -35,14 +37,13 @@ template<typename Derived> class TriangularBase : public EigenBase<Derived>
       MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
       MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
 
-      SizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::RowsAtCompileTime,
+      SizeAtCompileTime = (internal::size_of_xpr_at_compile_time<Derived>::ret),
-                                                   internal::traits<Derived>::ColsAtCompileTime>::ret),
       /**< This is equal to the number of coefficients, i.e. the number of
           * rows times the number of columns, or to \a Dynamic if this is not
           * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */
 
-      MaxSizeAtCompileTime = (internal::size_at_compile_time<internal::traits<Derived>::MaxRowsAtCompileTime,
+      MaxSizeAtCompileTime = internal::size_at_compile_time(internal::traits<Derived>::MaxRowsAtCompileTime,
-                                                   internal::traits<Derived>::MaxColsAtCompileTime>::ret)
+                                                            internal::traits<Derived>::MaxColsAtCompileTime)
 
     };
     typedef typename internal::traits<Derived>::Scalar Scalar;
@@ -153,8 +154,8 @@ template<typename Derived> class TriangularBase : public EigenBase<Derived>
   *
   * \brief Expression of a triangular part in a matrix
   *
-  * \param MatrixType the type of the object in which we are taking the triangular part
+  * \tparam MatrixType the type of the object in which we are taking the triangular part
-  * \param Mode the kind of triangular matrix expression to construct. Can be #Upper,
+  * \tparam Mode the kind of triangular matrix expression to construct. Can be #Upper,
   *             #Lower, #UnitUpper, #UnitLower, #StrictlyUpper, or #StrictlyLower.
   *             This is in fact a bit field; it must have either #Upper or #Lower,
   *             and additionally it may have #UnitDiag or #ZeroDiag or neither.
@@ -166,39 +167,39 @@ template<typename Derived> class TriangularBase : public EigenBase<Derived>
   * \sa MatrixBase::triangularView()
   */
 namespace internal {
-template<typename MatrixType, unsigned int _Mode>
+template<typename MatrixType, unsigned int Mode_>
-struct traits<TriangularView<MatrixType, _Mode> > : traits<MatrixType>
+struct traits<TriangularView<MatrixType, Mode_> > : traits<MatrixType>
 {
   typedef typename ref_selector<MatrixType>::non_const_type MatrixTypeNested;
-  typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedNonRef;
+  typedef std::remove_reference_t<MatrixTypeNested> MatrixTypeNestedNonRef;
-  typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
+  typedef remove_all_t<MatrixTypeNested> MatrixTypeNestedCleaned;
   typedef typename MatrixType::PlainObject FullMatrixType;
   typedef MatrixType ExpressionType;
   enum {
-    Mode = _Mode,
+    Mode = Mode_,
     FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
     Flags = (MatrixTypeNestedCleaned::Flags & (HereditaryBits | FlagsLvalueBit) & (~(PacketAccessBit | DirectAccessBit | LinearAccessBit)))
   };
 };
 }
 
-template<typename _MatrixType, unsigned int _Mode, typename StorageKind> class TriangularViewImpl;
+template<typename MatrixType_, unsigned int Mode_, typename StorageKind> class TriangularViewImpl;
 
-template<typename _MatrixType, unsigned int _Mode> class TriangularView
+template<typename MatrixType_, unsigned int Mode_> class TriangularView
-  : public TriangularViewImpl<_MatrixType, _Mode, typename internal::traits<_MatrixType>::StorageKind >
+  : public TriangularViewImpl<MatrixType_, Mode_, typename internal::traits<MatrixType_>::StorageKind >
 {
   public:
 
-    typedef TriangularViewImpl<_MatrixType, _Mode, typename internal::traits<_MatrixType>::StorageKind > Base;
+    typedef TriangularViewImpl<MatrixType_, Mode_, typename internal::traits<MatrixType_>::StorageKind > Base;
     typedef typename internal::traits<TriangularView>::Scalar Scalar;
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
 
   protected:
     typedef typename internal::traits<TriangularView>::MatrixTypeNested MatrixTypeNested;
     typedef typename internal::traits<TriangularView>::MatrixTypeNestedNonRef MatrixTypeNestedNonRef;
 
-    typedef typename internal::remove_all<typename MatrixType::ConjugateReturnType>::type MatrixConjugateReturnType;
+    typedef internal::remove_all_t<typename MatrixType::ConjugateReturnType> MatrixConjugateReturnType;
-    typedef TriangularView<typename internal::add_const<MatrixType>::type, _Mode> ConstTriangularView;
+    typedef TriangularView<std::add_const_t<MatrixType>, Mode_> ConstTriangularView;
 
   public:
 
@@ -206,7 +207,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     typedef typename internal::traits<TriangularView>::MatrixTypeNestedCleaned NestedExpression;
 
     enum {
-      Mode = _Mode,
+      Mode = Mode_,
       Flags = internal::traits<TriangularView>::Flags,
       TransposeMode = (Mode & Upper ? Lower : 0)
                     | (Mode & Lower ? Upper : 0)
@@ -247,10 +248,10 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
      */
     template<bool Cond>
     EIGEN_DEVICE_FUNC
-    inline typename internal::conditional<Cond,ConjugateReturnType,ConstTriangularView>::type
+    inline std::conditional_t<Cond,ConjugateReturnType,ConstTriangularView>
     conjugateIf() const
     {
-      typedef typename internal::conditional<Cond,ConjugateReturnType,ConstTriangularView>::type ReturnType;
+      typedef std::conditional_t<Cond,ConjugateReturnType,ConstTriangularView> ReturnType;
       return ReturnType(m_matrix.template conjugateIf<Cond>());
     }
 
@@ -262,10 +263,10 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
 
     typedef TriangularView<typename MatrixType::TransposeReturnType,TransposeMode> TransposeReturnType;
      /** \sa MatrixBase::transpose() */
+    template<class Dummy=int>
     EIGEN_DEVICE_FUNC
-    inline TransposeReturnType transpose()
+    inline TransposeReturnType transpose(std::enable_if_t<Eigen::internal::is_lvalue<MatrixType>::value, Dummy*> = nullptr)
     {
-      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
       typename MatrixType::TransposeReturnType tmp(m_matrix);
       return TransposeReturnType(tmp);
     }
@@ -342,16 +343,17 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
   *
   * \sa class TriangularView, MatrixBase::triangularView()
   */
-template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_MatrixType,_Mode,Dense>
+template<typename MatrixType_, unsigned int Mode_> class TriangularViewImpl<MatrixType_,Mode_,Dense>
-  : public TriangularBase<TriangularView<_MatrixType, _Mode> >
+  : public TriangularBase<TriangularView<MatrixType_, Mode_> >
 {
   public:
 
-    typedef TriangularView<_MatrixType, _Mode> TriangularViewType;
+    typedef TriangularView<MatrixType_, Mode_> TriangularViewType;
+
     typedef TriangularBase<TriangularViewType> Base;
     typedef typename internal::traits<TriangularViewType>::Scalar Scalar;
 
-    typedef _MatrixType MatrixType;
+    typedef MatrixType_ MatrixType;
     typedef typename MatrixType::PlainObject DenseMatrixType;
     typedef DenseMatrixType PlainObject;
 
@@ -362,7 +364,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularViewImpl<_Mat
     typedef typename internal::traits<TriangularViewType>::StorageKind StorageKind;
 
     enum {
-      Mode = _Mode,
+      Mode = Mode_,
       Flags = internal::traits<TriangularViewType>::Flags
     };
 
@@ -728,10 +730,10 @@ struct evaluator_traits<TriangularView<MatrixType,Mode> >
 
 template<typename MatrixType, unsigned int Mode>
 struct unary_evaluator<TriangularView<MatrixType,Mode>, IndexBased>
- : evaluator<typename internal::remove_all<MatrixType>::type>
+ : evaluator<internal::remove_all_t<MatrixType>>
 {
   typedef TriangularView<MatrixType,Mode> XprType;
-  typedef evaluator<typename internal::remove_all<MatrixType>::type> Base;
+  typedef evaluator<internal::remove_all_t<MatrixType>> Base;
   EIGEN_DEVICE_FUNC
   unary_evaluator(const XprType &xpr) : Base(xpr.nestedExpression()) {}
 };

libs/eigen/Eigen/src/Core/VectorBlock.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_VECTORBLOCK_H
 #define EIGEN_VECTORBLOCK_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen { 
 
 namespace internal {
@@ -66,6 +68,7 @@ template<typename VectorType, int Size> class VectorBlock
     };
   public:
     EIGEN_DENSE_PUBLIC_INTERFACE(VectorBlock)
+    EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorBlock)
 
     using Base::operator=;
 
@@ -76,18 +79,14 @@ template<typename VectorType, int Size> class VectorBlock
       : Base(vector,
              IsColVector ? start : 0, IsColVector ? 0 : start,
              IsColVector ? size  : 1, IsColVector ? 1 : size)
-    {
+    { }
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorBlock);
-    }
 
     /** Fixed-size constructor
       */
     EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
     VectorBlock(VectorType& vector, Index start)
       : Base(vector, IsColVector ? start : 0, IsColVector ? 0 : start)
-    {
+    { }
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorBlock);
-    }
 };
 
 

libs/eigen/Eigen/src/Core/VectorwiseOp.h

@@ -11,6 +11,8 @@
 #ifndef EIGEN_PARTIAL_REDUX_H
 #define EIGEN_PARTIAL_REDUX_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 /** \class PartialReduxExpr
@@ -86,7 +88,6 @@ template<typename A,typename B> struct partial_redux_dummy_func;
 #define EIGEN_MAKE_PARTIAL_REDUX_FUNCTOR(MEMBER,COST,VECTORIZABLE,BINARYOP)                \
   template <typename ResultType,typename Scalar>                                                            \
   struct member_##MEMBER {                                                                  \
-    EIGEN_EMPTY_STRUCT_CTOR(member_##MEMBER)                                                \
     typedef ResultType result_type;                                                         \
     typedef BINARYOP<Scalar,Scalar> BinaryOp;   \
     template<int Size> struct Cost { enum { value = COST }; };             \
@@ -191,7 +192,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     typedef typename ExpressionType::RealScalar RealScalar;
     typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
     typedef typename internal::ref_selector<ExpressionType>::non_const_type ExpressionTypeNested;
-    typedef typename internal::remove_all<ExpressionTypeNested>::type ExpressionTypeNestedCleaned;
+    typedef internal::remove_all_t<ExpressionTypeNested> ExpressionTypeNestedCleaned;
 
     template<template<typename OutScalar,typename InputScalar> class Functor,
                       typename ReturnScalar=Scalar> struct ReturnType
@@ -230,9 +231,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     typename ExtendedType<OtherDerived>::Type
     extendedTo(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxColsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(internal::check_implication(isVertical, OtherDerived::MaxColsAtCompileTime==1),
                           YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED)
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxRowsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(internal::check_implication(isHorizontal, OtherDerived::MaxRowsAtCompileTime==1),
                           YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED)
       return typename ExtendedType<OtherDerived>::Type
                       (other.derived(),
@@ -253,9 +254,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     typename OppositeExtendedType<OtherDerived>::Type
     extendedToOpposite(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isHorizontal, OtherDerived::MaxColsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(internal::check_implication(isHorizontal, OtherDerived::MaxColsAtCompileTime==1),
                           YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED)
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(isVertical, OtherDerived::MaxRowsAtCompileTime==1),
+      EIGEN_STATIC_ASSERT(internal::check_implication(isVertical, OtherDerived::MaxRowsAtCompileTime==1),
                           YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED)
       return typename OppositeExtendedType<OtherDerived>::Type
                       (other.derived(),
@@ -594,7 +595,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
       return m_matrix += extendedTo(other.derived());
     }
 
-    /** Substracts the vector \a other to each subvector of \c *this */
+    /** Subtracts the vector \a other to each subvector of \c *this */
     template<typename OtherDerived>
     EIGEN_DEVICE_FUNC
     ExpressionType& operator-=(const DenseBase<OtherDerived>& other)
@@ -604,7 +605,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
       return m_matrix -= extendedTo(other.derived());
     }
 
-    /** Multiples each subvector of \c *this by the vector \a other */
+    /** Multiplies each subvector of \c *this by the vector \a other */
     template<typename OtherDerived>
     EIGEN_DEVICE_FUNC
     ExpressionType& operator*=(const DenseBase<OtherDerived>& other)

libs/eigen/Eigen/src/Core/Visitor.h

@@ -10,16 +10,23 @@
 #ifndef EIGEN_VISITOR_H
 #define EIGEN_VISITOR_H
 
+#include "./InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
+template<typename Visitor, typename Derived, int UnrollCount, bool Vectorize=((Derived::PacketAccess!=0) && functor_traits<Visitor>::PacketAccess)>
+struct visitor_impl;
+
 template<typename Visitor, typename Derived, int UnrollCount>
-struct visitor_impl
+struct visitor_impl<Visitor, Derived, UnrollCount, false>
 {
   enum {
-    col = (UnrollCount-1) / Derived::RowsAtCompileTime,
+    col = Derived::IsRowMajor ? (UnrollCount-1) % Derived::ColsAtCompileTime
-    row = (UnrollCount-1) % Derived::RowsAtCompileTime
+                              : (UnrollCount-1) / Derived::RowsAtCompileTime,
+    row = Derived::IsRowMajor ? (UnrollCount-1) / Derived::ColsAtCompileTime
+                              : (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
   EIGEN_DEVICE_FUNC
@@ -31,7 +38,7 @@ struct visitor_impl
 };
 
 template<typename Visitor, typename Derived>
-struct visitor_impl<Visitor, Derived, 1>
+struct visitor_impl<Visitor, Derived, 1, false>
 {
   EIGEN_DEVICE_FUNC
   static inline void run(const Derived &mat, Visitor& visitor)
@@ -42,25 +49,74 @@ struct visitor_impl<Visitor, Derived, 1>
 
 // This specialization enables visitors on empty matrices at compile-time
 template<typename Visitor, typename Derived>
-struct visitor_impl<Visitor, Derived, 0> {
+struct visitor_impl<Visitor, Derived, 0, false> {
   EIGEN_DEVICE_FUNC
   static inline void run(const Derived &/*mat*/, Visitor& /*visitor*/)
   {}
 };
 
 template<typename Visitor, typename Derived>
-struct visitor_impl<Visitor, Derived, Dynamic>
+struct visitor_impl<Visitor, Derived, Dynamic, /*Vectorize=*/false>
 {
   EIGEN_DEVICE_FUNC
   static inline void run(const Derived& mat, Visitor& visitor)
   {
     visitor.init(mat.coeff(0,0), 0, 0);
-    for(Index i = 1; i < mat.rows(); ++i)
+    if (Derived::IsRowMajor) {
+      for(Index i = 1; i < mat.cols(); ++i) {
+          visitor(mat.coeff(0, i), 0, i);
+      }
+      for(Index j = 1; j < mat.rows(); ++j) {
+        for(Index i = 0; i < mat.cols(); ++i) {
+          visitor(mat.coeff(j, i), j, i);
+        }
+      }
+    } else {
+      for(Index i = 1; i < mat.rows(); ++i) {
           visitor(mat.coeff(i, 0), i, 0);
-    for(Index j = 1; j < mat.cols(); ++j)
+      }
-      for(Index i = 0; i < mat.rows(); ++i)
+      for(Index j = 1; j < mat.cols(); ++j) {
+        for(Index i = 0; i < mat.rows(); ++i) {
           visitor(mat.coeff(i, j), i, j);
         }
+      }
+    }
+  }
+};
+
+template<typename Visitor, typename Derived, int UnrollSize>
+struct visitor_impl<Visitor, Derived, UnrollSize, /*Vectorize=*/true>
+{
+  typedef typename Derived::Scalar Scalar;
+  typedef typename packet_traits<Scalar>::type Packet;
+
+  EIGEN_DEVICE_FUNC
+  static inline void run(const Derived& mat, Visitor& visitor)
+  {
+    const Index PacketSize = packet_traits<Scalar>::size;
+    visitor.init(mat.coeff(0,0), 0, 0);
+    if (Derived::IsRowMajor) {
+      for(Index i = 0; i < mat.rows(); ++i) {
+        Index j = i == 0 ? 1 : 0;
+        for(; j+PacketSize-1 < mat.cols(); j += PacketSize) {
+          Packet p = mat.packet(i, j);
+          visitor.packet(p, i, j);
+        }
+        for(; j < mat.cols(); ++j)
+          visitor(mat.coeff(i, j), i, j);
+      }
+    } else {
+      for(Index j = 0; j < mat.cols(); ++j) {
+        Index i = j == 0 ? 1 : 0;
+        for(; i+PacketSize-1 < mat.rows(); i += PacketSize) {
+          Packet p = mat.packet(i, j);
+          visitor.packet(p, i, j);
+        }
+        for(; i < mat.rows(); ++i)
+          visitor(mat.coeff(i, j), i, j);
+      }
+    }
+  }
 };
 
 // evaluator adaptor
@@ -68,16 +124,23 @@ template<typename XprType>
 class visitor_evaluator
 {
 public:
+  typedef internal::evaluator<XprType> Evaluator;
+
+  enum {
+    PacketAccess = Evaluator::Flags & PacketAccessBit,
+    IsRowMajor = XprType::IsRowMajor,
+    RowsAtCompileTime = XprType::RowsAtCompileTime,
+    ColsAtCompileTime = XprType::ColsAtCompileTime,
+    CoeffReadCost = Evaluator::CoeffReadCost
+  };
+
+
   EIGEN_DEVICE_FUNC
   explicit visitor_evaluator(const XprType &xpr) : m_evaluator(xpr), m_xpr(xpr) { }
 
   typedef typename XprType::Scalar Scalar;
-  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef std::remove_const_t<typename XprType::CoeffReturnType> CoeffReturnType;
-
+  typedef std::remove_const_t<typename XprType::PacketReturnType> PacketReturnType;
-  enum {
-    RowsAtCompileTime = XprType::RowsAtCompileTime,
-    CoeffReadCost = internal::evaluator<XprType>::CoeffReadCost
-  };
 
   EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_xpr.rows(); }
   EIGEN_DEVICE_FUNC EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_xpr.cols(); }
@@ -85,11 +148,14 @@ public:
 
   EIGEN_DEVICE_FUNC CoeffReturnType coeff(Index row, Index col) const
   { return m_evaluator.coeff(row, col); }
+  EIGEN_DEVICE_FUNC PacketReturnType packet(Index row, Index col) const
+  { return m_evaluator.template packet<Unaligned,PacketReturnType>(row, col); }
 
 protected:
-  internal::evaluator<XprType> m_evaluator;
+  Evaluator m_evaluator;
   const XprType &m_xpr;
 };
+
 } // end namespace internal
 
 /** Applies the visitor \a visitor to the whole coefficients of the matrix or vector.
@@ -152,123 +218,131 @@ struct coeff_visitor
   }
 };
 
-/** \internal
-  * \brief Visitor computing the min coefficient with its value and coordinates
-  *
-  * \sa DenseBase::minCoeff(Index*, Index*)
-  */
-template <typename Derived, int NaNPropagation>
-struct min_coeff_visitor : coeff_visitor<Derived>
-{
-  typedef typename Derived::Scalar Scalar;
-  EIGEN_DEVICE_FUNC
-  void operator() (const Scalar& value, Index i, Index j)
-  {
-    if(value < this->res)
-    {
-      this->res = value;
-      this->row = i;
-      this->col = j;
-    }
-  }
-};
 
-template <typename Derived>
+template<typename Scalar, int NaNPropagation, bool is_min=true>
-struct min_coeff_visitor<Derived, PropagateNumbers> : coeff_visitor<Derived>
+struct minmax_compare {
-{
+  typedef typename packet_traits<Scalar>::type Packet;
-  typedef typename Derived::Scalar Scalar;
+  static EIGEN_DEVICE_FUNC inline bool compare(Scalar a, Scalar b) { return a < b; }
-  EIGEN_DEVICE_FUNC
+  static EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& p) { return predux_min<NaNPropagation>(p);}
-  void operator() (const Scalar& value, Index i, Index j)
-  {
-    if((numext::isnan)(this->res) || (!(numext::isnan)(value) && value < this->res))
-    {
-      this->res = value;
-      this->row = i;
-      this->col = j;
-    }
-  }
-};
-
-template <typename Derived>
-struct min_coeff_visitor<Derived, PropagateNaN> : coeff_visitor<Derived>
-{
-  typedef typename Derived::Scalar Scalar;
-  EIGEN_DEVICE_FUNC
-  void operator() (const Scalar& value, Index i, Index j)
-  {
-    if((numext::isnan)(value) || value < this->res)
-    {
-      this->res = value;
-      this->row = i;
-      this->col = j;
-    }
-  }
 };
 
 template<typename Scalar, int NaNPropagation>
-    struct functor_traits<min_coeff_visitor<Scalar, NaNPropagation> > {
+struct minmax_compare<Scalar, NaNPropagation, false> {
+  typedef typename packet_traits<Scalar>::type Packet;
+  static EIGEN_DEVICE_FUNC inline bool compare(Scalar a, Scalar b) { return a > b; }
+  static EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& p) { return predux_max<NaNPropagation>(p);}
+};
+
+template <typename Derived, bool is_min, int NaNPropagation>
+struct minmax_coeff_visitor : coeff_visitor<Derived>
+{
+  using Scalar = typename Derived::Scalar;
+  using Packet = typename packet_traits<Scalar>::type;
+  using Comparator = minmax_compare<Scalar, NaNPropagation, is_min>;
+
+  EIGEN_DEVICE_FUNC inline
+  void operator() (const Scalar& value, Index i, Index j)
+  {
+    if(Comparator::compare(value, this->res)) {
+      this->res = value;
+      this->row = i;
+      this->col = j;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC inline
+  void packet(const Packet& p, Index i, Index j) {
+    const Index PacketSize = packet_traits<Scalar>::size;
+    Scalar value = Comparator::predux(p);
+    if (Comparator::compare(value, this->res)) {
+      const Packet range = preverse(plset<Packet>(Scalar(1)));
+      Packet mask = pcmp_eq(pset1<Packet>(value), p);
+      Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
+      this->res = value;
+      this->row = Derived::IsRowMajor ? i : i + max_idx;;
+      this->col = Derived::IsRowMajor ? j + max_idx : j;
+    }
+  }
+};
+
+// Suppress NaN. The only case in which we return NaN is if the matrix is all NaN, in which case,
+// the row=0, col=0 is returned for the location.
+template <typename Derived, bool is_min>
+struct minmax_coeff_visitor<Derived, is_min, PropagateNumbers> : coeff_visitor<Derived>
+{
+  typedef typename Derived::Scalar Scalar;
+  using Packet = typename packet_traits<Scalar>::type;
+  using Comparator = minmax_compare<Scalar, PropagateNumbers, is_min>;
+
+  EIGEN_DEVICE_FUNC inline
+  void operator() (const Scalar& value, Index i, Index j)
+  {
+    if ((!(numext::isnan)(value) && (numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
+      this->res = value;
+      this->row = i;
+      this->col = j;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC inline
+  void packet(const Packet& p, Index i, Index j) {
+    const Index PacketSize = packet_traits<Scalar>::size;
+    Scalar value = Comparator::predux(p);
+    if ((!(numext::isnan)(value) && (numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
+      const Packet range = preverse(plset<Packet>(Scalar(1)));
+      /* mask will be zero for NaNs, so they will be ignored. */
+      Packet mask = pcmp_eq(pset1<Packet>(value), p);
+      Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
+      this->res = value;
+      this->row = Derived::IsRowMajor ? i : i + max_idx;;
+      this->col = Derived::IsRowMajor ? j + max_idx : j;
+    }
+  }
+
+};
+
+// Propagate NaN. If the matrix contains NaN, the location of the first NaN will be returned in
+// row and col.
+template <typename Derived, bool is_min>
+struct minmax_coeff_visitor<Derived, is_min, PropagateNaN> : coeff_visitor<Derived>
+{
+  typedef typename Derived::Scalar Scalar;
+  using Packet = typename packet_traits<Scalar>::type;
+  using Comparator = minmax_compare<Scalar, PropagateNaN, is_min>;
+
+  EIGEN_DEVICE_FUNC inline
+  void operator() (const Scalar& value, Index i, Index j)
+  {
+    const bool value_is_nan = (numext::isnan)(value);
+    if ((value_is_nan && !(numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
+      this->res = value;
+      this->row = i;
+      this->col = j;
+    }
+  }
+
+  EIGEN_DEVICE_FUNC inline
+  void packet(const Packet& p, Index i, Index j) {
+    const Index PacketSize = packet_traits<Scalar>::size;
+    Scalar value = Comparator::predux(p);
+    const bool value_is_nan = (numext::isnan)(value);
+    if ((value_is_nan && !(numext::isnan)(this->res)) || Comparator::compare(value, this->res)) {
+      const Packet range = preverse(plset<Packet>(Scalar(1)));
+      // If the value is NaN, pick the first position of a NaN, otherwise pick the first extremal value.
+      Packet mask = value_is_nan ? pnot(pcmp_eq(p, p)) : pcmp_eq(pset1<Packet>(value), p);
+      Index max_idx = PacketSize - static_cast<Index>(predux_max(pand(range, mask)));
+      this->res = value;
+      this->row = Derived::IsRowMajor ? i : i + max_idx;;
+      this->col = Derived::IsRowMajor ? j + max_idx : j;
+    }
+  }
+};
+
+template<typename Scalar, bool is_min, int NaNPropagation>
+struct functor_traits<minmax_coeff_visitor<Scalar, is_min, NaNPropagation> > {
   enum {
-    Cost = NumTraits<Scalar>::AddCost
+    Cost = NumTraits<Scalar>::AddCost,
-  };
+    PacketAccess = true
-};
-
-/** \internal
-  * \brief Visitor computing the max coefficient with its value and coordinates
-  *
-  * \sa DenseBase::maxCoeff(Index*, Index*)
-  */
-template <typename Derived, int NaNPropagation>
-struct max_coeff_visitor : coeff_visitor<Derived>
-{
-  typedef typename Derived::Scalar Scalar;
-  EIGEN_DEVICE_FUNC
-  void operator() (const Scalar& value, Index i, Index j)
-  {
-    if(value > this->res)
-    {
-      this->res = value;
-      this->row = i;
-      this->col = j;
-    }
-  }
-};
-
-template <typename Derived>
-struct max_coeff_visitor<Derived, PropagateNumbers> : coeff_visitor<Derived>
-{
-  typedef typename Derived::Scalar Scalar;
-  EIGEN_DEVICE_FUNC
-  void operator() (const Scalar& value, Index i, Index j)
-  {
-    if((numext::isnan)(this->res) || (!(numext::isnan)(value) && value > this->res))
-    {
-      this->res = value;
-      this->row = i;
-      this->col = j;
-    }
-  }
-};
-
-template <typename Derived>
-struct max_coeff_visitor<Derived, PropagateNaN> : coeff_visitor<Derived>
-{
-  typedef typename Derived::Scalar Scalar;
-  EIGEN_DEVICE_FUNC
-  void operator() (const Scalar& value, Index i, Index j)
-  {
-    if((numext::isnan)(value) || value > this->res)
-    {
-      this->res = value;
-      this->row = i;
-      this->col = j;
-    }
-  }
-};
-
-template<typename Scalar, int NaNPropagation>
-struct functor_traits<max_coeff_visitor<Scalar, NaNPropagation> > {
-  enum {
-    Cost = NumTraits<Scalar>::AddCost
   };
 };
 
@@ -293,7 +367,7 @@ DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
 {
   eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
 
-  internal::min_coeff_visitor<Derived, NaNPropagation> minVisitor;
+  internal::minmax_coeff_visitor<Derived, true, NaNPropagation> minVisitor;
   this->visit(minVisitor);
   *rowId = minVisitor.row;
   if (colId) *colId = minVisitor.col;
@@ -319,7 +393,7 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
   eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
 
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-      internal::min_coeff_visitor<Derived, NaNPropagation> minVisitor;
+      internal::minmax_coeff_visitor<Derived, true, NaNPropagation> minVisitor;
   this->visit(minVisitor);
   *index = IndexType((RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row);
   return minVisitor.res;
@@ -344,7 +418,7 @@ DenseBase<Derived>::maxCoeff(IndexType* rowPtr, IndexType* colPtr) const
 {
   eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
 
-  internal::max_coeff_visitor<Derived, NaNPropagation> maxVisitor;
+  internal::minmax_coeff_visitor<Derived, false, NaNPropagation> maxVisitor;
   this->visit(maxVisitor);
   *rowPtr = maxVisitor.row;
   if (colPtr) *colPtr = maxVisitor.col;
@@ -370,7 +444,7 @@ DenseBase<Derived>::maxCoeff(IndexType* index) const
   eigen_assert(this->rows()>0 && this->cols()>0 && "you are using an empty matrix");
 
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-      internal::max_coeff_visitor<Derived, NaNPropagation> maxVisitor;
+      internal::minmax_coeff_visitor<Derived, false, NaNPropagation> maxVisitor;
   this->visit(maxVisitor);
   *index = (RowsAtCompileTime==1) ? maxVisitor.col : maxVisitor.row;
   return maxVisitor.res;

libs/eigen/Eigen/src/Core/arch/AVX/Complex.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_COMPLEX_AVX_H
 #define EIGEN_COMPLEX_AVX_H
 
+#include "../../InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -99,7 +101,9 @@ template<> EIGEN_STRONG_INLINE Packet4cf ploadu<Packet4cf>(const std::complex<fl
 
 template<> EIGEN_STRONG_INLINE Packet4cf pset1<Packet4cf>(const std::complex<float>& from)
 {
-  return Packet4cf(_mm256_castpd_ps(_mm256_broadcast_sd((const double*)(const void*)&from)));
+  const float re = std::real(from);
+  const float im = std::imag(from);
+  return Packet4cf(_mm256_set_ps(im, re, im, re, im, re, im, re));
 }
 
 template<> EIGEN_STRONG_INLINE Packet4cf ploaddup<Packet4cf>(const std::complex<float>* from)
@@ -167,15 +171,12 @@ template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet4cf>(const P
                          Packet2cf(_mm256_extractf128_ps(a.v, 1))));
 }
 
+
 EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet4cf,Packet8f)
 
 template<> EIGEN_STRONG_INLINE Packet4cf pdiv<Packet4cf>(const Packet4cf& a, const Packet4cf& b)
 {
-  Packet4cf num = pmul(a, pconj(b));
+  return pdiv_complex(a, b);
-  __m256 tmp = _mm256_mul_ps(b.v, b.v);
-  __m256 tmp2    = _mm256_shuffle_ps(tmp,tmp,0xB1);
-  __m256 denom = _mm256_add_ps(tmp, tmp2);
-  return Packet4cf(_mm256_div_ps(num.v, denom));
 }
 
 template<> EIGEN_STRONG_INLINE Packet4cf pcplxflip<Packet4cf>(const Packet4cf& x)
@@ -321,10 +322,7 @@ EIGEN_MAKE_CONJ_HELPER_CPLX_REAL(Packet2cd,Packet4d)
 
 template<> EIGEN_STRONG_INLINE Packet2cd pdiv<Packet2cd>(const Packet2cd& a, const Packet2cd& b)
 {
-  Packet2cd num = pmul(a, pconj(b));
+  return pdiv_complex(a, b);
-  __m256d tmp = _mm256_mul_pd(b.v, b.v);
-  __m256d denom = _mm256_hadd_pd(tmp, tmp);
-  return Packet2cd(_mm256_div_pd(num.v, denom));
 }
 
 template<> EIGEN_STRONG_INLINE Packet2cd pcplxflip<Packet2cd>(const Packet2cd& x)

libs/eigen/Eigen/src/Core/arch/AVX/MathFunctions.h

@@ -14,52 +14,78 @@
  * Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
  */
 
+#include "../../InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
 
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
 psin<Packet8f>(const Packet8f& _x) {
   return psin_float(_x);
 }
 
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
 pcos<Packet8f>(const Packet8f& _x) {
   return pcos_float(_x);
 }
 
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
+pasin<Packet8f>(const Packet8f& _x) {
+  return pasin_float(_x);
+}
+
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
+pacos<Packet8f>(const Packet8f& _x) {
+  return pacos_float(_x);
+}
+
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
+patan<Packet8f>(const Packet8f& _x) {
+  return patan_float(_x);
+}
+
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet4d
+patan<Packet4d>(const Packet4d& _x) {
+  return patan_double(_x);
+}
+
+template <>
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
 plog<Packet8f>(const Packet8f& _x) {
   return plog_float(_x);
 }
 
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet4d
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet4d
 plog<Packet4d>(const Packet4d& _x) {
   return plog_double(_x);
 }
 
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
 plog2<Packet8f>(const Packet8f& _x) {
   return plog2_float(_x);
 }
 
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet4d
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet4d
 plog2<Packet4d>(const Packet4d& _x) {
   return plog2_double(_x);
 }
 
-template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet8f plog1p<Packet8f>(const Packet8f& _x) {
   return generic_plog1p(_x);
 }
 
-template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
 Packet8f pexpm1<Packet8f>(const Packet8f& _x) {
   return generic_expm1(_x);
 }
@@ -68,110 +94,59 @@ Packet8f pexpm1<Packet8f>(const Packet8f& _x) {
 // "m = floor(x/log(2)+1/2)" and "r" is the remainder. The result is then
 // "exp(x) = 2^m*exp(r)" where exp(r) is in the range [-1,1).
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
 pexp<Packet8f>(const Packet8f& _x) {
   return pexp_float(_x);
 }
 
 // Hyperbolic Tangent function.
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet8f
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet8f
 ptanh<Packet8f>(const Packet8f& _x) {
   return internal::generic_fast_tanh_float(_x);
 }
 
 // Exponential function for doubles.
 template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED Packet4d
+EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet4d
 pexp<Packet4d>(const Packet4d& _x) {
   return pexp_double(_x);
 }
 
-// Functions for sqrt.
-// The EIGEN_FAST_MATH version uses the _mm_rsqrt_ps approximation and one step
-// of Newton's method, at a cost of 1-2 bits of precision as opposed to the
-// exact solution. It does not handle +inf, or denormalized numbers correctly.
-// The main advantage of this approach is not just speed, but also the fact that
-// it can be inlined and pipelined with other computations, further reducing its
-// effective latency. This is similar to Quake3's fast inverse square root.
-// For detail see here: http://www.beyond3d.com/content/articles/8/
-#if EIGEN_FAST_MATH
-template <>
-EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
-Packet8f psqrt<Packet8f>(const Packet8f& _x) {
-  Packet8f minus_half_x = pmul(_x, pset1<Packet8f>(-0.5f));
-  Packet8f denormal_mask = pandnot(
-      pcmp_lt(_x, pset1<Packet8f>((std::numeric_limits<float>::min)())),
-      pcmp_lt(_x, pzero(_x)));
 
-  // Compute approximate reciprocal sqrt.
+// Notice that for newer processors, it is counterproductive to use Newton
-  Packet8f x = _mm256_rsqrt_ps(_x);
+// iteration for square root. In particular, Skylake and Zen2 processors
-  // Do a single step of Newton's iteration.
+// have approximately doubled throughput of the _mm_sqrt_ps instruction
-  x = pmul(x, pmadd(minus_half_x, pmul(x,x), pset1<Packet8f>(1.5f)));
+// compared to their predecessors.
-  // Flush results for denormals to zero.
+template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-  return pandnot(pmul(_x,x), denormal_mask);
-}
-
-#else
-
-template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
 Packet8f psqrt<Packet8f>(const Packet8f& _x) {
   return _mm256_sqrt_ps(_x);
 }
-
+template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-#endif
-
-template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
 Packet4d psqrt<Packet4d>(const Packet4d& _x) {
   return _mm256_sqrt_pd(_x);
 }
 
+
+// Even on Skylake, using Newton iteration is a win for reciprocal square root.
 #if EIGEN_FAST_MATH
-template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS
-Packet8f prsqrt<Packet8f>(const Packet8f& _x) {
+Packet8f prsqrt<Packet8f>(const Packet8f& a) {
-  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(inf, 0x7f800000);
+  // _mm256_rsqrt_ps returns -inf for negative denormals.
-  _EIGEN_DECLARE_CONST_Packet8f(one_point_five, 1.5f);
+  // _mm512_rsqrt**_ps returns -NaN for negative denormals.  We may want
-  _EIGEN_DECLARE_CONST_Packet8f(minus_half, -0.5f);
+  // consistency here.
-  _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(flt_min, 0x00800000);
+  // const Packet8f rsqrt = pselect(pcmp_lt(a, pzero(a)),
-
+  //                                pset1<Packet8f>(-NumTraits<float>::quiet_NaN()),
-  Packet8f neg_half = pmul(_x, p8f_minus_half);
+  //                                _mm256_rsqrt_ps(a));
-
+  return generic_rsqrt_newton_step<Packet8f, /*Steps=*/1>::run(a, _mm256_rsqrt_ps(a));
-  // select only the inverse sqrt of positive normal inputs (denormals are
-  // flushed to zero and cause infs as well).
-  Packet8f lt_min_mask = _mm256_cmp_ps(_x, p8f_flt_min, _CMP_LT_OQ);
-  Packet8f inf_mask =  _mm256_cmp_ps(_x, p8f_inf, _CMP_EQ_OQ);
-  Packet8f not_normal_finite_mask = _mm256_or_ps(lt_min_mask, inf_mask);
-
-  // Compute an approximate result using the rsqrt intrinsic.
-  Packet8f y_approx = _mm256_rsqrt_ps(_x);
-
-  // Do a single step of Newton-Raphson iteration to improve the approximation.
-  // This uses the formula y_{n+1} = y_n * (1.5 - y_n * (0.5 * x) * y_n).
-  // It is essential to evaluate the inner term like this because forming
-  // y_n^2 may over- or underflow.
-  Packet8f y_newton = pmul(y_approx, pmadd(y_approx, pmul(neg_half, y_approx), p8f_one_point_five));
-
-  // Select the result of the Newton-Raphson step for positive normal arguments.
-  // For other arguments, choose the output of the intrinsic. This will
-  // return rsqrt(+inf) = 0, rsqrt(x) = NaN if x < 0, and rsqrt(x) = +inf if
-  // x is zero or a positive denormalized float (equivalent to flushing positive
-  // denormalized inputs to zero).
-  return pselect<Packet8f>(not_normal_finite_mask, y_approx, y_newton);
 }
 
-#else
+template<> EIGEN_STRONG_INLINE Packet8f preciprocal<Packet8f>(const Packet8f& a) {
-template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+  return generic_reciprocal_newton_step<Packet8f, /*Steps=*/1>::run(a, _mm256_rcp_ps(a));
-Packet8f prsqrt<Packet8f>(const Packet8f& _x) {
-  _EIGEN_DECLARE_CONST_Packet8f(one, 1.0f);
-  return _mm256_div_ps(p8f_one, _mm256_sqrt_ps(_x));
 }
+
 #endif
 
-template <> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
-Packet4d prsqrt<Packet4d>(const Packet4d& _x) {
-  _EIGEN_DECLARE_CONST_Packet4d(one, 1.0);
-  return _mm256_div_pd(p4d_one, _mm256_sqrt_pd(_x));
-}
 
 F16_PACKET_FUNCTION(Packet8f, Packet8h, psin)
 F16_PACKET_FUNCTION(Packet8f, Packet8h, pcos)
@@ -183,6 +158,7 @@ F16_PACKET_FUNCTION(Packet8f, Packet8h, pexp)
 F16_PACKET_FUNCTION(Packet8f, Packet8h, ptanh)
 F16_PACKET_FUNCTION(Packet8f, Packet8h, psqrt)
 F16_PACKET_FUNCTION(Packet8f, Packet8h, prsqrt)
+F16_PACKET_FUNCTION(Packet8f, Packet8h, preciprocal)
 
 template <>
 EIGEN_STRONG_INLINE Packet8h pfrexp(const Packet8h& a, Packet8h& exponent) {
@@ -207,6 +183,7 @@ BF16_PACKET_FUNCTION(Packet8f, Packet8bf, pexp)
 BF16_PACKET_FUNCTION(Packet8f, Packet8bf, ptanh)
 BF16_PACKET_FUNCTION(Packet8f, Packet8bf, psqrt)
 BF16_PACKET_FUNCTION(Packet8f, Packet8bf, prsqrt)
+BF16_PACKET_FUNCTION(Packet8f, Packet8bf, preciprocal)
 
 template <>
 EIGEN_STRONG_INLINE Packet8bf pfrexp(const Packet8bf& a, Packet8bf& exponent) {

libs/eigen/Eigen/src/Core/arch/AVX/PacketMath.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_PACKET_MATH_AVX_H
 #define EIGEN_PACKET_MATH_AVX_H
 
+#include "../../InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {
@@ -29,28 +31,29 @@ namespace internal {
 #endif
 
 typedef __m256  Packet8f;
-typedef __m256i Packet8i;
+typedef eigen_packet_wrapper<__m256i, 0> Packet8i;
 typedef __m256d Packet4d;
+#ifndef EIGEN_VECTORIZE_AVX512FP16
 typedef eigen_packet_wrapper<__m128i, 2> Packet8h;
+#endif
 typedef eigen_packet_wrapper<__m128i, 3> Packet8bf;
 
+#ifdef EIGEN_VECTORIZE_AVX2
+// Start from 3 to be compatible with AVX512
+typedef eigen_packet_wrapper<__m256i, 3> Packet4l;
+#endif
+
 template<> struct is_arithmetic<__m256>  { enum { value = true }; };
 template<> struct is_arithmetic<__m256i> { enum { value = true }; };
 template<> struct is_arithmetic<__m256d> { enum { value = true }; };
+template<> struct is_arithmetic<Packet8i> { enum { value = true }; };
+#ifndef EIGEN_VECTORIZE_AVX512FP16
 template<> struct is_arithmetic<Packet8h> { enum { value = true }; };
+#endif
 template<> struct is_arithmetic<Packet8bf> { enum { value = true }; };
-
+#ifdef EIGEN_VECTORIZE_AVX2
-#define _EIGEN_DECLARE_CONST_Packet8f(NAME,X) \
+template<> struct is_arithmetic<Packet4l> { enum { value = true }; };
-  const Packet8f p8f_##NAME = pset1<Packet8f>(X)
+#endif
-
-#define _EIGEN_DECLARE_CONST_Packet4d(NAME,X) \
-  const Packet4d p4d_##NAME = pset1<Packet4d>(X)
-
-#define _EIGEN_DECLARE_CONST_Packet8f_FROM_INT(NAME,X) \
-  const Packet8f p8f_##NAME = _mm256_castsi256_ps(pset1<Packet8i>(X))
-
-#define _EIGEN_DECLARE_CONST_Packet8i(NAME,X) \
-  const Packet8i p8i_##NAME = pset1<Packet8i>(X)
 
 // Use the packet_traits defined in AVX512/PacketMath.h instead if we're going
 // to leverage AVX512 instructions.
@@ -67,8 +70,12 @@ template<> struct packet_traits<float>  : default_packet_traits
 
     HasCmp  = 1,
     HasDiv = 1,
+    HasReciprocal = EIGEN_FAST_MATH,
     HasSin = EIGEN_FAST_MATH,
     HasCos = EIGEN_FAST_MATH,
+    HasACos = 1,
+    HasASin = 1,
+    HasATan = 1,
     HasLog = 1,
     HasLog1p = 1,
     HasExpm1 = 1,
@@ -102,6 +109,7 @@ template<> struct packet_traits<double> : default_packet_traits
     HasExp  = 1,
     HasSqrt = 1,
     HasRsqrt = 1,
+    HasATan = 1,
     HasBlend = 1,
     HasRound = 1,
     HasFloor = 1,
@@ -196,38 +204,74 @@ struct packet_traits<bfloat16> : default_packet_traits {
     HasNdtri  = 1
   };
 };
+
+template<> struct packet_traits<int> : default_packet_traits
+{
+  typedef Packet8i type;
+  typedef Packet4i half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    HasCmp = 1,
+    HasDiv = 1,
+    size=8
+  };
+};
+
+#ifdef EIGEN_VECTORIZE_AVX2
+template<> struct packet_traits<int64_t> : default_packet_traits
+{
+  typedef Packet4l type;
+  // There is no half-size packet for current Packet4l.
+  // TODO: support as SSE path.
+  typedef Packet4l half;
+  enum {
+    Vectorizable = 1,
+    AlignedOnScalar = 1,
+    HasCmp = 1,
+    size=4
+  };
+};
+#endif
+
 #endif
 
 template<> struct scalar_div_cost<float,true> { enum { value = 14 }; };
 template<> struct scalar_div_cost<double,true> { enum { value = 16 }; };
 
-/* Proper support for integers is only provided by AVX2. In the meantime, we'll
-   use SSE instructions and packets to deal with integers.
-template<> struct packet_traits<int>    : default_packet_traits
-{
-  typedef Packet8i type;
-  enum {
-    Vectorizable = 1,
-    AlignedOnScalar = 1,
-    size=8
-  };
-};
-*/
-
 template<> struct unpacket_traits<Packet8f> {
   typedef float     type;
   typedef Packet4f  half;
   typedef Packet8i  integer_packet;
   typedef uint8_t   mask_t;
-  enum {size=8, alignment=Aligned32, vectorizable=true, masked_load_available=true, masked_store_available=true};
+  enum {size=8, alignment=Aligned32, vectorizable=true, masked_load_available=true, masked_store_available=true
+#ifdef EIGEN_VECTORIZE_AVX512
+    , masked_fpops_available=true
+#endif
+  };
 };
 template<> struct unpacket_traits<Packet4d> {
   typedef double type;
   typedef Packet2d half;
   enum {size=4, alignment=Aligned32, vectorizable=true, masked_load_available=false, masked_store_available=false};
 };
-template<> struct unpacket_traits<Packet8i> { typedef int    type; typedef Packet4i half; enum {size=8, alignment=Aligned32, vectorizable=false, masked_load_available=false, masked_store_available=false}; };
+template<> struct unpacket_traits<Packet8i> {
-template<> struct unpacket_traits<Packet8bf> { typedef bfloat16 type; typedef Packet8bf half; enum {size=8, alignment=Aligned16, vectorizable=true, masked_load_available=false, masked_store_available=false}; };
+  typedef int    type;
+  typedef Packet4i half;
+  enum {size=8, alignment=Aligned32, vectorizable=true, masked_load_available=false, masked_store_available=false};
+};
+#ifdef EIGEN_VECTORIZE_AVX2
+template<> struct unpacket_traits<Packet4l> {
+  typedef int64_t    type;
+  typedef Packet4l half;
+  enum {size=4, alignment=Aligned32, vectorizable=true, masked_load_available=false, masked_store_available=false};
+};
+#endif
+template<> struct unpacket_traits<Packet8bf> {
+  typedef bfloat16 type;
+  typedef Packet8bf half;
+  enum {size=8, alignment=Aligned16, vectorizable=true, masked_load_available=false, masked_store_available=false};
+};
 
 // Helper function for bit packing snippet of low precision comparison.
 // It packs the flags from 16x16 to 8x16.
@@ -236,6 +280,210 @@ EIGEN_STRONG_INLINE __m128i Pack16To8(Packet8f rf) {
                          _mm256_extractf128_si256(_mm256_castps_si256(rf), 1));
 }
 
+#ifdef EIGEN_VECTORIZE_AVX2
+template <>
+EIGEN_STRONG_INLINE Packet4l pset1<Packet4l>(const int64_t& from) {
+  return _mm256_set1_epi64x(from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pzero(const Packet4l& /*a*/) {
+  return _mm256_setzero_si256();
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l peven_mask(const Packet4l& /*a*/) {
+  return _mm256_set_epi64x(0ll, -1ll, 0ll, -1ll);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pload1<Packet4l>(const int64_t* from) {
+  return _mm256_set1_epi64x(*from);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l padd<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  return _mm256_add_epi64(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l plset<Packet4l>(const int64_t& a) {
+  return padd(pset1<Packet4l>(a), Packet4l(_mm256_set_epi64x(3ll, 2ll, 1ll, 0ll)));
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l psub<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  return _mm256_sub_epi64(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pnegate(const Packet4l& a) {
+  return psub(pzero(a), a);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pconj(const Packet4l& a) {
+  return a;
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pcmp_le(const Packet4l& a, const Packet4l& b) {
+  return _mm256_xor_si256(_mm256_cmpgt_epi64(a, b), _mm256_set1_epi32(-1));
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pcmp_lt(const Packet4l& a, const Packet4l& b) {
+  return _mm256_cmpgt_epi64(b, a);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pcmp_eq(const Packet4l& a, const Packet4l& b) {
+  return _mm256_cmpeq_epi64(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l ptrue<Packet4l>(const Packet4l& a) {
+  return _mm256_cmpeq_epi64(a, a);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pand<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  return _mm256_and_si256(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l por<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  return _mm256_or_si256(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pxor<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  return _mm256_xor_si256(a, b);
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pandnot<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  return _mm256_andnot_si256(b, a);
+}
+template <int N>
+EIGEN_STRONG_INLINE Packet4l plogical_shift_right(Packet4l a) {
+  return _mm256_srli_epi64(a, N);
+}
+template <int N>
+EIGEN_STRONG_INLINE Packet4l plogical_shift_left(Packet4l a) {
+  return _mm256_slli_epi64(a, N);
+}
+#ifdef EIGEN_VECTORIZE_AVX512FP16
+template <int N>
+EIGEN_STRONG_INLINE Packet4l parithmetic_shift_right(Packet4l a) { return _mm256_srai_epi64(a, N); }
+#else
+template <int N>
+EIGEN_STRONG_INLINE std::enable_if_t< (N == 0), Packet4l> parithmetic_shift_right(Packet4l a) {
+  return a;
+}
+template <int N>
+EIGEN_STRONG_INLINE std::enable_if_t< (N > 0) && (N < 32), Packet4l> parithmetic_shift_right(Packet4l a) {
+  __m256i hi_word = _mm256_srai_epi32(a, N);
+  __m256i lo_word = _mm256_srli_epi64(a, N);
+  return _mm256_blend_epi32(hi_word, lo_word, 0b01010101);
+}
+template <int N>
+EIGEN_STRONG_INLINE std::enable_if_t< (N >= 32) && (N < 63), Packet4l> parithmetic_shift_right(Packet4l a) {
+  __m256i hi_word = _mm256_srai_epi32(a, 31);
+  __m256i lo_word = _mm256_shuffle_epi32(_mm256_srai_epi32(a, N - 32), (shuffle_mask<1, 1, 3, 3>::mask));
+  return _mm256_blend_epi32(hi_word, lo_word, 0b01010101);
+}
+template <int N>
+EIGEN_STRONG_INLINE std::enable_if_t< (N == 63), Packet4l> parithmetic_shift_right(Packet4l a) {
+  return _mm256_shuffle_epi32(_mm256_srai_epi32(a, 31), (shuffle_mask<1, 1, 3, 3>::mask));
+}
+template <int N>
+EIGEN_STRONG_INLINE std::enable_if_t< (N < 0) || (N > 63), Packet4l> parithmetic_shift_right(Packet4l a) {
+  return parithmetic_shift_right<int(N&63)>(a);
+}
+#endif
+template <>
+EIGEN_STRONG_INLINE Packet4l pload<Packet4l>(const int64_t* from) {
+  EIGEN_DEBUG_ALIGNED_LOAD return _mm256_load_si256(reinterpret_cast<const __m256i*>(from));
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l ploadu<Packet4l>(const int64_t* from) {
+  EIGEN_DEBUG_UNALIGNED_LOAD return _mm256_loadu_si256(reinterpret_cast<const __m256i*>(from));
+}
+// Loads 2 int64_ts from memory a returns the packet {a0, a0, a1, a1}
+template <>
+EIGEN_STRONG_INLINE Packet4l ploaddup<Packet4l>(const int64_t* from) {
+  const Packet4l a = _mm256_castsi128_si256(_mm_loadu_si128(reinterpret_cast<const __m128i*>(from)));
+  return _mm256_permutevar8x32_epi32(a, _mm256_setr_epi32(0, 1, 0, 1, 2, 3, 2, 3));
+}
+template <>
+EIGEN_STRONG_INLINE void pstore<int64_t>(int64_t* to, const Packet4l& from) {
+  EIGEN_DEBUG_ALIGNED_STORE _mm256_storeu_si256(reinterpret_cast<__m256i*>(to), from);
+}
+template <>
+EIGEN_STRONG_INLINE void pstoreu<int64_t>(int64_t* to, const Packet4l& from) {
+  EIGEN_DEBUG_UNALIGNED_STORE _mm256_storeu_si256(reinterpret_cast<__m256i*>(to), from);
+}
+template <>
+EIGEN_DEVICE_FUNC inline Packet4l pgather<int64_t, Packet4l>(const int64_t* from, Index stride) {
+  return _mm256_set_epi64x(from[3 * stride], from[2 * stride], from[1 * stride], from[0 * stride]);
+}
+template <>
+EIGEN_DEVICE_FUNC inline void pscatter<int64_t, Packet4l>(int64_t* to, const Packet4l& from, Index stride) {
+  __m128i low = _mm256_extractf128_si256(from, 0);
+  to[stride * 0] = _mm_extract_epi64(low, 0);
+  to[stride * 1] = _mm_extract_epi64(low, 1);
+
+  __m128i high = _mm256_extractf128_si256(from, 1);
+  to[stride * 2] = _mm_extract_epi64(high, 0);
+  to[stride * 3] = _mm_extract_epi64(high, 1);
+}
+template <>
+EIGEN_STRONG_INLINE void pstore1<Packet4l>(int64_t* to, const int64_t& a) {
+  Packet4l pa = pset1<Packet4l>(a);
+  pstore(to, pa);
+}
+template <>
+EIGEN_STRONG_INLINE int64_t pfirst<Packet4l>(const Packet4l& a) {
+  return _mm_cvtsi128_si64(_mm256_castsi256_si128(a));
+}
+template <>
+EIGEN_STRONG_INLINE int64_t predux<Packet4l>(const Packet4l& a) {
+  __m128i r = _mm_add_epi64(_mm256_castsi256_si128(a), _mm256_extractf128_si256(a, 1));
+  return _mm_extract_epi64(r, 0) + _mm_extract_epi64(r, 1);
+}
+#define MM256_SHUFFLE_EPI64(A, B, M) _mm256_shuffle_pd(_mm256_castsi256_pd(A), _mm256_castsi256_pd(B), M)
+EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet4l, 4>& kernel) {
+  __m256d T0 = MM256_SHUFFLE_EPI64(kernel.packet[0], kernel.packet[1], 15);
+  __m256d T1 = MM256_SHUFFLE_EPI64(kernel.packet[0], kernel.packet[1], 0);
+  __m256d T2 = MM256_SHUFFLE_EPI64(kernel.packet[2], kernel.packet[3], 15);
+  __m256d T3 = MM256_SHUFFLE_EPI64(kernel.packet[2], kernel.packet[3], 0);
+
+  kernel.packet[1] = _mm256_castpd_si256(_mm256_permute2f128_pd(T0, T2, 32));
+  kernel.packet[3] = _mm256_castpd_si256(_mm256_permute2f128_pd(T0, T2, 49));
+  kernel.packet[0] = _mm256_castpd_si256(_mm256_permute2f128_pd(T1, T3, 32));
+  kernel.packet[2] = _mm256_castpd_si256(_mm256_permute2f128_pd(T1, T3, 49));
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pmin<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  __m256i cmp = _mm256_cmpgt_epi64(a, b);
+  __m256i a_min = _mm256_andnot_si256(cmp, a);
+  __m256i b_min = _mm256_and_si256(cmp, b);
+  return Packet4l(_mm256_or_si256(a_min, b_min));
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pmax<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  __m256i cmp = _mm256_cmpgt_epi64(a, b);
+  __m256i a_min = _mm256_and_si256(cmp, a);
+  __m256i b_min = _mm256_andnot_si256(cmp, b);
+  return Packet4l(_mm256_or_si256(a_min, b_min));
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pabs<Packet4l>(const Packet4l& a) {
+  Packet4l pz = pzero<Packet4l>(a);
+  Packet4l cmp = _mm256_cmpgt_epi64(a, pz);
+  return psub(cmp, pxor(a, cmp));
+}
+template <>
+EIGEN_STRONG_INLINE Packet4l pmul<Packet4l>(const Packet4l& a, const Packet4l& b) {
+  // 64-bit mul requires avx512, so do this with 32-bit multiplication
+  __m256i upper32_a = _mm256_srli_epi64(a, 32);
+  __m256i upper32_b = _mm256_srli_epi64(b, 32);
+
+  // upper * lower
+  __m256i mul1 = _mm256_mul_epu32(upper32_a, b);
+  __m256i mul2 = _mm256_mul_epu32(upper32_b, a);
+  // Gives us both upper*upper and lower*lower
+  __m256i mul3 = _mm256_mul_epu32(a, b);
+
+  __m256i high = _mm256_slli_epi64(_mm256_add_epi64(mul1, mul2), 32);
+  return _mm256_add_epi64(high, mul3);
+}
+#endif
 
 template<> EIGEN_STRONG_INLINE Packet8f pset1<Packet8f>(const float&  from) { return _mm256_set1_ps(from); }
 template<> EIGEN_STRONG_INLINE Packet4d pset1<Packet4d>(const double& from) { return _mm256_set1_pd(from); }
@@ -256,10 +504,17 @@ template<> EIGEN_STRONG_INLINE Packet4d peven_mask(const Packet4d& /*a*/) { retu
 template<> EIGEN_STRONG_INLINE Packet8f pload1<Packet8f>(const float*  from) { return _mm256_broadcast_ss(from); }
 template<> EIGEN_STRONG_INLINE Packet4d pload1<Packet4d>(const double* from) { return _mm256_broadcast_sd(from); }
 
-template<> EIGEN_STRONG_INLINE Packet8f plset<Packet8f>(const float& a) { return _mm256_add_ps(_mm256_set1_ps(a), _mm256_set_ps(7.0,6.0,5.0,4.0,3.0,2.0,1.0,0.0)); }
-template<> EIGEN_STRONG_INLINE Packet4d plset<Packet4d>(const double& a) { return _mm256_add_pd(_mm256_set1_pd(a), _mm256_set_pd(3.0,2.0,1.0,0.0)); }
-
 template<> EIGEN_STRONG_INLINE Packet8f padd<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_add_ps(a,b); }
+#ifdef EIGEN_VECTORIZE_AVX512
+template <>
+EIGEN_STRONG_INLINE Packet8f padd<Packet8f>(const Packet8f& a, const Packet8f& b, uint8_t umask) {
+  __mmask16 mask = static_cast<__mmask16>(umask & 0x00FF);
+  return _mm512_castps512_ps256(_mm512_maskz_add_ps(
+                                    mask,
+                                    _mm512_castps256_ps512(a),
+                                    _mm512_castps256_ps512(b)));
+}
+#endif
 template<> EIGEN_STRONG_INLINE Packet4d padd<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_add_pd(a,b); }
 template<> EIGEN_STRONG_INLINE Packet8i padd<Packet8i>(const Packet8i& a, const Packet8i& b) {
 #ifdef EIGEN_VECTORIZE_AVX2
@@ -271,6 +526,10 @@ template<> EIGEN_STRONG_INLINE Packet8i padd<Packet8i>(const Packet8i& a, const
 #endif
 }
 
+template<> EIGEN_STRONG_INLINE Packet8f plset<Packet8f>(const float& a) { return padd(pset1<Packet8f>(a), _mm256_set_ps(7.0,6.0,5.0,4.0,3.0,2.0,1.0,0.0)); }
+template<> EIGEN_STRONG_INLINE Packet4d plset<Packet4d>(const double& a) { return padd(pset1<Packet4d>(a), _mm256_set_pd(3.0,2.0,1.0,0.0)); }
+template<> EIGEN_STRONG_INLINE Packet8i plset<Packet8i>(const int& a) { return padd(pset1<Packet8i>(a), (Packet8i)_mm256_set_epi32(7,6,5,4,3,2,1,0)); }
+
 template<> EIGEN_STRONG_INLINE Packet8f psub<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_sub_ps(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4d psub<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_sub_pd(a,b); }
 template<> EIGEN_STRONG_INLINE Packet8i psub<Packet8i>(const Packet8i& a, const Packet8i& b) {
@@ -285,11 +544,17 @@ template<> EIGEN_STRONG_INLINE Packet8i psub<Packet8i>(const Packet8i& a, const
 
 template<> EIGEN_STRONG_INLINE Packet8f pnegate(const Packet8f& a)
 {
-  return _mm256_sub_ps(_mm256_set1_ps(0.0),a);
+  const Packet8f mask = _mm256_castsi256_ps(_mm256_set1_epi32(0x80000000));
+  return _mm256_xor_ps(a, mask);
 }
 template<> EIGEN_STRONG_INLINE Packet4d pnegate(const Packet4d& a)
 {
-  return _mm256_sub_pd(_mm256_set1_pd(0.0),a);
+  const Packet4d mask = _mm256_castsi256_pd(_mm256_set1_epi64x(0x8000000000000000ULL));
+  return _mm256_xor_pd(a, mask);
+}
+template<> EIGEN_STRONG_INLINE Packet8i pnegate(const Packet8i& a)
+{
+  return psub(pzero(a), a);
 }
 
 template<> EIGEN_STRONG_INLINE Packet8f pconj(const Packet8f& a) { return a; }
@@ -310,36 +575,58 @@ template<> EIGEN_STRONG_INLINE Packet8i pmul<Packet8i>(const Packet8i& a, const
 
 template<> EIGEN_STRONG_INLINE Packet8f pdiv<Packet8f>(const Packet8f& a, const Packet8f& b) { return _mm256_div_ps(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4d pdiv<Packet4d>(const Packet4d& a, const Packet4d& b) { return _mm256_div_pd(a,b); }
-template<> EIGEN_STRONG_INLINE Packet8i pdiv<Packet8i>(const Packet8i& /*a*/, const Packet8i& /*b*/)
+
-{ eigen_assert(false && "packet integer division are not supported by AVX");
+template<> EIGEN_STRONG_INLINE Packet8i pdiv<Packet8i>(const Packet8i& a, const Packet8i& b)
-  return pset1<Packet8i>(0);
+{
+#ifdef EIGEN_VECTORIZE_AVX512
+  return _mm512_cvttpd_epi32(_mm512_div_pd(_mm512_cvtepi32_pd(a), _mm512_cvtepi32_pd(b)));
+#else  
+  Packet4i lo = pdiv<Packet4i>(_mm256_extractf128_si256(a, 0), _mm256_extractf128_si256(b, 0));
+  Packet4i hi = pdiv<Packet4i>(_mm256_extractf128_si256(a, 1), _mm256_extractf128_si256(b, 1));
+  return _mm256_insertf128_si256(_mm256_castsi128_si256(lo), hi, 1);
+#endif
 }
 
 #ifdef EIGEN_VECTORIZE_FMA
-template<> EIGEN_STRONG_INLINE Packet8f pmadd(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
+template <>
-#if ( (EIGEN_COMP_GNUC_STRICT && EIGEN_COMP_GNUC<80) || (EIGEN_COMP_CLANG) )
+EIGEN_STRONG_INLINE Packet8f pmadd(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
-  // Clang stupidly generates a vfmadd213ps instruction plus some vmovaps on registers,
-  //  and even register spilling with clang>=6.0 (bug 1637).
-  // Gcc stupidly generates a vfmadd132ps instruction.
-  // So let's enforce it to generate a vfmadd231ps instruction since the most common use
-  //  case is to accumulate the result of the product.
-  Packet8f res = c;
-  __asm__("vfmadd231ps %[a], %[b], %[c]" : [c] "+x" (res) : [a] "x" (a), [b] "x" (b));
-  return res;
-#else
   return _mm256_fmadd_ps(a, b, c);
-#endif
 }
-template<> EIGEN_STRONG_INLINE Packet4d pmadd(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
+template <>
-#if ( (EIGEN_COMP_GNUC_STRICT && EIGEN_COMP_GNUC<80) || (EIGEN_COMP_CLANG) )
+EIGEN_STRONG_INLINE Packet4d pmadd(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
-  // see above
-  Packet4d res = c;
-  __asm__("vfmadd231pd %[a], %[b], %[c]" : [c] "+x" (res) : [a] "x" (a), [b] "x" (b));
-  return res;
-#else
   return _mm256_fmadd_pd(a, b, c);
-#endif
 }
+
+template <>
+EIGEN_STRONG_INLINE Packet8f pmsub(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
+  return _mm256_fmsub_ps(a, b, c);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet4d pmsub(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
+  return _mm256_fmsub_pd(a, b, c);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet8f pnmadd(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
+  return _mm256_fnmadd_ps(a, b, c);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet4d pnmadd(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
+  return _mm256_fnmadd_pd(a, b, c);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet8f pnmsub(const Packet8f& a, const Packet8f& b, const Packet8f& c) {
+  return _mm256_fnmsub_ps(a, b, c);
+}
+
+template <>
+EIGEN_STRONG_INLINE Packet4d pnmsub(const Packet4d& a, const Packet4d& b, const Packet4d& c) {
+  return _mm256_fnmsub_pd(a, b, c);
+}
+
 #endif
 
 template<> EIGEN_STRONG_INLINE Packet8f pcmp_le(const Packet8f& a, const Packet8f& b) { return _mm256_cmp_ps(a,b,_CMP_LE_OQ); }
@@ -352,7 +639,26 @@ template<> EIGEN_STRONG_INLINE Packet4d pcmp_lt(const Packet4d& a, const Packet4
 template<> EIGEN_STRONG_INLINE Packet4d pcmp_lt_or_nan(const Packet4d& a, const Packet4d& b) { return _mm256_cmp_pd(a, b, _CMP_NGE_UQ); }
 template<> EIGEN_STRONG_INLINE Packet4d pcmp_eq(const Packet4d& a, const Packet4d& b) { return _mm256_cmp_pd(a,b,_CMP_EQ_OQ); }
 
-
+template<> EIGEN_STRONG_INLINE Packet8i pcmp_le(const Packet8i& a, const Packet8i& b) {
+#ifdef EIGEN_VECTORIZE_AVX2
+  return _mm256_xor_si256(_mm256_cmpgt_epi32(a,b), _mm256_set1_epi32(-1));
+#else
+  __m128i lo = _mm_cmpgt_epi32(_mm256_extractf128_si256(a, 0), _mm256_extractf128_si256(b, 0));
+  lo = _mm_xor_si128(lo, _mm_set1_epi32(-1));
+  __m128i hi = _mm_cmpgt_epi32(_mm256_extractf128_si256(a, 1), _mm256_extractf128_si256(b, 1));
+  hi = _mm_xor_si128(hi, _mm_set1_epi32(-1));
+  return _mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1);
+#endif
+}
+template<> EIGEN_STRONG_INLINE Packet8i pcmp_lt(const Packet8i& a, const Packet8i& b) {
+#ifdef EIGEN_VECTORIZE_AVX2
+  return _mm256_cmpgt_epi32(b,a);
+#else
+  __m128i lo = _mm_cmpgt_epi32(_mm256_extractf128_si256(b, 0), _mm256_extractf128_si256(a, 0));
+  __m128i hi = _mm_cmpgt_epi32(_mm256_extractf128_si256(b, 1), _mm256_extractf128_si256(a, 1));
+  return _mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1);
+#endif
+}
 template<> EIGEN_STRONG_INLINE Packet8i pcmp_eq(const Packet8i& a, const Packet8i& b) {
 #ifdef EIGEN_VECTORIZE_AVX2
   return _mm256_cmpeq_epi32(a,b);
@@ -388,6 +694,15 @@ template<> EIGEN_STRONG_INLINE Packet4d pmin<Packet4d>(const Packet4d& a, const
   return _mm256_min_pd(b,a);
 #endif
 }
+template<> EIGEN_STRONG_INLINE Packet8i pmin<Packet8i>(const Packet8i& a, const Packet8i& b) {
+#ifdef EIGEN_VECTORIZE_AVX2
+  return _mm256_min_epi32(a, b);
+#else
+  __m128i lo = _mm_min_epi32(_mm256_extractf128_si256(a, 0), _mm256_extractf128_si256(b, 0));
+  __m128i hi = _mm_min_epi32(_mm256_extractf128_si256(a, 1), _mm256_extractf128_si256(b, 1));
+  return _mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1);
+#endif
+}
 
 template<> EIGEN_STRONG_INLINE Packet8f pmax<Packet8f>(const Packet8f& a, const Packet8f& b) {
 #if EIGEN_COMP_GNUC && EIGEN_COMP_GNUC < 63
@@ -411,6 +726,21 @@ template<> EIGEN_STRONG_INLINE Packet4d pmax<Packet4d>(const Packet4d& a, const
   return _mm256_max_pd(b,a);
 #endif
 }
+template<> EIGEN_STRONG_INLINE Packet8i pmax<Packet8i>(const Packet8i& a, const Packet8i& b) {
+#ifdef EIGEN_VECTORIZE_AVX2
+  return _mm256_max_epi32(a, b);
+#else
+  __m128i lo = _mm_max_epi32(_mm256_extractf128_si256(a, 0), _mm256_extractf128_si256(b, 0));
+  __m128i hi = _mm_max_epi32(_mm256_extractf128_si256(a, 1), _mm256_extractf128_si256(b, 1));
+  return _mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1);
+#endif
+}
+
+#ifdef EIGEN_VECTORIZE_AVX2
+template<> EIGEN_STRONG_INLINE Packet8i psign(const Packet8i& a) {
+  return _mm256_sign_epi32(_mm256_set1_epi32(1), a);
+}
+#endif
 
 // Add specializations for min/max with prescribed NaN progation.
 template<>
@@ -583,11 +913,16 @@ template<> EIGEN_STRONG_INLINE Packet4d ploadu<Packet4d>(const double* from) { E
 template<> EIGEN_STRONG_INLINE Packet8i ploadu<Packet8i>(const int* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm256_loadu_si256(reinterpret_cast<const __m256i*>(from)); }
 
 template<> EIGEN_STRONG_INLINE Packet8f ploadu<Packet8f>(const float* from, uint8_t umask) {
+#ifdef EIGEN_VECTORIZE_AVX512
+  __mmask16 mask = static_cast<__mmask16>(umask & 0x00FF);
+  EIGEN_DEBUG_UNALIGNED_LOAD return  _mm512_castps512_ps256(_mm512_maskz_loadu_ps(mask, from));
+#else
   Packet8i mask = _mm256_set1_epi8(static_cast<char>(umask));
   const Packet8i bit_mask = _mm256_set_epi32(0xffffff7f, 0xffffffbf, 0xffffffdf, 0xffffffef, 0xfffffff7, 0xfffffffb, 0xfffffffd, 0xfffffffe);
   mask = por<Packet8i>(mask, bit_mask);
   mask = pcmp_eq<Packet8i>(mask, _mm256_set1_epi32(0xffffffff));
   EIGEN_DEBUG_UNALIGNED_LOAD return _mm256_maskload_ps(from, mask);
+#endif
 }
 
 // Loads 4 floats from memory a returns the packet {a0, a0  a1, a1, a2, a2, a3, a3}
@@ -605,12 +940,26 @@ template<> EIGEN_STRONG_INLINE Packet8f ploaddup<Packet8f>(const float* from)
   // then we can perform a consistent permutation on the global register to get everything in shape:
   return  _mm256_permute_ps(tmp, _MM_SHUFFLE(3,3,2,2));
 }
-// Loads 2 doubles from memory a returns the packet {a0, a0  a1, a1}
+// Loads 2 doubles from memory a returns the packet {a0, a0, a1, a1}
 template<> EIGEN_STRONG_INLINE Packet4d ploaddup<Packet4d>(const double* from)
 {
   Packet4d tmp = _mm256_broadcast_pd((const __m128d*)(const void*)from);
   return  _mm256_permute_pd(tmp, 3<<2);
 }
+// Loads 4 integers from memory a returns the packet {a0, a0, a1, a1, a2, a2, a3, a3}
+template<> EIGEN_STRONG_INLINE Packet8i ploaddup<Packet8i>(const int* from)
+{
+#ifdef EIGEN_VECTORIZE_AVX2
+  const Packet8i a = _mm256_castsi128_si256(ploadu<Packet4i>(from));
+  return _mm256_permutevar8x32_epi32(a, _mm256_setr_epi32(0, 0, 1, 1, 2, 2, 3, 3));
+#else
+  __m256 tmp = _mm256_broadcast_ps((const __m128*)(const void*)from);
+  // mimic an "inplace" permutation of the lower 128bits using a blend
+  tmp = _mm256_blend_ps(tmp,_mm256_castps128_ps256(_mm_permute_ps( _mm256_castps256_ps128(tmp), _MM_SHUFFLE(1,0,1,0))), 15);
+  // then we can perform a consistent permutation on the global register to get everything in shape:
+  return  _mm256_castps_si256(_mm256_permute_ps(tmp, _MM_SHUFFLE(3,3,2,2)));
+#endif
+}
 
 // Loads 2 floats from memory a returns the packet {a0, a0  a0, a0, a1, a1, a1, a1}
 template<> EIGEN_STRONG_INLINE Packet8f ploadquad<Packet8f>(const float* from)
@@ -618,6 +967,10 @@ template<> EIGEN_STRONG_INLINE Packet8f ploadquad<Packet8f>(const float* from)
   Packet8f tmp = _mm256_castps128_ps256(_mm_broadcast_ss(from));
   return _mm256_insertf128_ps(tmp, _mm_broadcast_ss(from+1), 1);
 }
+template<> EIGEN_STRONG_INLINE Packet8i ploadquad<Packet8i>(const int* from)
+{
+  return _mm256_insertf128_si256(_mm256_set1_epi32(*from), _mm_set1_epi32(*(from+1)), 1);
+}
 
 template<> EIGEN_STRONG_INLINE void pstore<float>(float*   to, const Packet8f& from) { EIGEN_DEBUG_ALIGNED_STORE _mm256_store_ps(to, from); }
 template<> EIGEN_STRONG_INLINE void pstore<double>(double* to, const Packet4d& from) { EIGEN_DEBUG_ALIGNED_STORE _mm256_store_pd(to, from); }
@@ -628,11 +981,16 @@ template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet4d&
 template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*       to, const Packet8i& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm256_storeu_si256(reinterpret_cast<__m256i*>(to), from); }
 
 template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*   to, const Packet8f& from, uint8_t umask) {
+#ifdef EIGEN_VECTORIZE_AVX512
+  __mmask16 mask = static_cast<__mmask16>(umask & 0x00FF);
+  EIGEN_DEBUG_UNALIGNED_STORE return _mm512_mask_storeu_ps(to, mask, _mm512_castps256_ps512(from));
+#else
   Packet8i mask = _mm256_set1_epi8(static_cast<char>(umask));
   const Packet8i bit_mask = _mm256_set_epi32(0xffffff7f, 0xffffffbf, 0xffffffdf, 0xffffffef, 0xfffffff7, 0xfffffffb, 0xfffffffd, 0xfffffffe);
   mask = por<Packet8i>(mask, bit_mask);
   mask = pcmp_eq<Packet8i>(mask, _mm256_set1_epi32(0xffffffff));
   EIGEN_DEBUG_UNALIGNED_STORE return _mm256_maskstore_ps(to, mask, from);
+#endif
 }
 
 // NOTE: leverage _mm256_i32gather_ps and _mm256_i32gather_pd if AVX2 instructions are available
@@ -646,6 +1004,11 @@ template<> EIGEN_DEVICE_FUNC inline Packet4d pgather<double, Packet4d>(const dou
 {
   return _mm256_set_pd(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
 }
+template<> EIGEN_DEVICE_FUNC inline Packet8i pgather<int, Packet8i>(const int* from, Index stride)
+{
+  return _mm256_set_epi32(from[7*stride], from[6*stride], from[5*stride], from[4*stride],
+                          from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
+}
 
 template<> EIGEN_DEVICE_FUNC inline void pscatter<float, Packet8f>(float* to, const Packet8f& from, Index stride)
 {
@@ -670,6 +1033,20 @@ template<> EIGEN_DEVICE_FUNC inline void pscatter<double, Packet4d>(double* to,
   to[stride*2] = _mm_cvtsd_f64(high);
   to[stride*3] = _mm_cvtsd_f64(_mm_shuffle_pd(high, high, 1));
 }
+template<> EIGEN_DEVICE_FUNC inline void pscatter<int, Packet8i>(int* to, const Packet8i& from, Index stride)
+{
+  __m128i low = _mm256_extractf128_si256(from, 0);
+  to[stride*0] = _mm_extract_epi32(low, 0);
+  to[stride*1] = _mm_extract_epi32(low, 1);
+  to[stride*2] = _mm_extract_epi32(low, 2);
+  to[stride*3] = _mm_extract_epi32(low, 3);
+
+  __m128i high = _mm256_extractf128_si256(from, 1);
+  to[stride*4] = _mm_extract_epi32(high, 0);
+  to[stride*5] = _mm_extract_epi32(high, 1);
+  to[stride*6] = _mm_extract_epi32(high, 2);
+  to[stride*7] = _mm_extract_epi32(high, 3);
+}
 
 template<> EIGEN_STRONG_INLINE void pstore1<Packet8f>(float* to, const float& a)
 {
@@ -720,6 +1097,17 @@ template<> EIGEN_STRONG_INLINE Packet4d preverse(const Packet4d& a)
     return _mm256_permute_pd(swap_halves,5);
   #endif
 }
+template<> EIGEN_STRONG_INLINE Packet8i preverse(const Packet8i& a)
+{
+  return _mm256_castps_si256(preverse(_mm256_castsi256_ps(a)));
+}
+
+#ifdef EIGEN_VECTORIZE_AVX2
+template<> EIGEN_STRONG_INLINE Packet4l preverse(const Packet4l& a)
+{
+  return _mm256_castpd_si256(preverse(_mm256_castsi256_pd(a)));
+}
+#endif
 
 // pabs should be ok
 template<> EIGEN_STRONG_INLINE Packet8f pabs(const Packet8f& a)
@@ -732,6 +1120,23 @@ template<> EIGEN_STRONG_INLINE Packet4d pabs(const Packet4d& a)
   const Packet4d mask = _mm256_castsi256_pd(_mm256_setr_epi32(0xFFFFFFFF,0x7FFFFFFF,0xFFFFFFFF,0x7FFFFFFF,0xFFFFFFFF,0x7FFFFFFF,0xFFFFFFFF,0x7FFFFFFF));
   return _mm256_and_pd(a,mask);
 }
+template<> EIGEN_STRONG_INLINE Packet8i pabs(const Packet8i& a)
+{
+#ifdef EIGEN_VECTORIZE_AVX2
+  return _mm256_abs_epi32(a);
+#else
+  __m128i lo = _mm_abs_epi32(_mm256_extractf128_si256(a, 0));
+  __m128i hi = _mm_abs_epi32(_mm256_extractf128_si256(a, 1));
+  return _mm256_insertf128_si256(_mm256_castsi128_si256(lo), (hi), 1);
+#endif
+}
+
+template<> EIGEN_STRONG_INLINE Packet8h  psignbit(const Packet8h&  a) { return _mm_srai_epi16(a, 15); }
+template<> EIGEN_STRONG_INLINE Packet8bf psignbit(const Packet8bf& a) { return _mm_srai_epi16(a, 15); }
+template<> EIGEN_STRONG_INLINE Packet8f  psignbit(const Packet8f&  a) { return _mm256_castsi256_ps(parithmetic_shift_right<31>((Packet8i)_mm256_castps_si256(a))); }
+#ifdef EIGEN_VECTORIZE_AVX2
+template<> EIGEN_STRONG_INLINE Packet4d  psignbit(const Packet4d& a)  { return _mm256_castsi256_pd(parithmetic_shift_right<63>((Packet4l)_mm256_castpd_si256(a))); }
+#endif
 
 template<> EIGEN_STRONG_INLINE Packet8f pfrexp<Packet8f>(const Packet8f& a, Packet8f& exponent) {
   return pfrexp_generic(a,exponent);
@@ -803,11 +1208,19 @@ template<> EIGEN_STRONG_INLINE double predux<Packet4d>(const Packet4d& a)
 {
   return predux(Packet2d(_mm_add_pd(_mm256_castpd256_pd128(a),_mm256_extractf128_pd(a,1))));
 }
+template<> EIGEN_STRONG_INLINE int predux<Packet8i>(const Packet8i& a)
+{
+  return predux(Packet4i(_mm_add_epi32(_mm256_castsi256_si128(a),_mm256_extractf128_si256(a,1))));
+}
 
 template<> EIGEN_STRONG_INLINE Packet4f predux_half_dowto4<Packet8f>(const Packet8f& a)
 {
   return _mm_add_ps(_mm256_castps256_ps128(a),_mm256_extractf128_ps(a,1));
 }
+template<> EIGEN_STRONG_INLINE Packet4i predux_half_dowto4<Packet8i>(const Packet8i& a)
+{
+  return _mm_add_epi32(_mm256_castsi256_si128(a),_mm256_extractf128_si256(a,1));
+}
 
 template<> EIGEN_STRONG_INLINE float predux_mul<Packet8f>(const Packet8f& a)
 {
@@ -859,6 +1272,11 @@ template<> EIGEN_STRONG_INLINE bool predux_any(const Packet8f& x)
   return _mm256_movemask_ps(x) != 0;
 }
 
+template<> EIGEN_STRONG_INLINE bool predux_any(const Packet8i& x)
+{
+  return _mm256_movemask_ps(_mm256_castsi256_ps(x)) != 0;
+}
+
 EIGEN_DEVICE_FUNC inline void
 ptranspose(PacketBlock<Packet8f,8>& kernel) {
   __m256 T0 = _mm256_unpacklo_ps(kernel.packet[0], kernel.packet[1]);
@@ -905,6 +1323,66 @@ ptranspose(PacketBlock<Packet8f,4>& kernel) {
   kernel.packet[3] = _mm256_permute2f128_ps(S2, S3, 0x31);
 }
 
+#define MM256_SHUFFLE_EPI32(A, B, M) \
+  _mm256_castps_si256(_mm256_shuffle_ps(_mm256_castsi256_ps(A), _mm256_castsi256_ps(B), M))
+
+#ifndef EIGEN_VECTORIZE_AVX2
+#define MM256_UNPACKLO_EPI32(A, B) \
+  _mm256_castps_si256(_mm256_unpacklo_ps(_mm256_castsi256_ps(A), _mm256_castsi256_ps(B)))
+#define MM256_UNPACKHI_EPI32(A, B) \
+  _mm256_castps_si256(_mm256_unpackhi_ps(_mm256_castsi256_ps(A), _mm256_castsi256_ps(B)))
+#else
+#define MM256_UNPACKLO_EPI32(A, B) _mm256_unpacklo_epi32(A, B)
+#define MM256_UNPACKHI_EPI32(A, B) _mm256_unpackhi_epi32(A, B)
+#endif
+
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet8i,8>& kernel) {
+  __m256i T0 = MM256_UNPACKLO_EPI32(kernel.packet[0], kernel.packet[1]);
+  __m256i T1 = MM256_UNPACKHI_EPI32(kernel.packet[0], kernel.packet[1]);
+  __m256i T2 = MM256_UNPACKLO_EPI32(kernel.packet[2], kernel.packet[3]);
+  __m256i T3 = MM256_UNPACKHI_EPI32(kernel.packet[2], kernel.packet[3]);
+  __m256i T4 = MM256_UNPACKLO_EPI32(kernel.packet[4], kernel.packet[5]);
+  __m256i T5 = MM256_UNPACKHI_EPI32(kernel.packet[4], kernel.packet[5]);
+  __m256i T6 = MM256_UNPACKLO_EPI32(kernel.packet[6], kernel.packet[7]);
+  __m256i T7 = MM256_UNPACKHI_EPI32(kernel.packet[6], kernel.packet[7]);
+  __m256i S0 = MM256_SHUFFLE_EPI32(T0,T2,_MM_SHUFFLE(1,0,1,0));
+  __m256i S1 = MM256_SHUFFLE_EPI32(T0,T2,_MM_SHUFFLE(3,2,3,2));
+  __m256i S2 = MM256_SHUFFLE_EPI32(T1,T3,_MM_SHUFFLE(1,0,1,0));
+  __m256i S3 = MM256_SHUFFLE_EPI32(T1,T3,_MM_SHUFFLE(3,2,3,2));
+  __m256i S4 = MM256_SHUFFLE_EPI32(T4,T6,_MM_SHUFFLE(1,0,1,0));
+  __m256i S5 = MM256_SHUFFLE_EPI32(T4,T6,_MM_SHUFFLE(3,2,3,2));
+  __m256i S6 = MM256_SHUFFLE_EPI32(T5,T7,_MM_SHUFFLE(1,0,1,0));
+  __m256i S7 = MM256_SHUFFLE_EPI32(T5,T7,_MM_SHUFFLE(3,2,3,2));
+  kernel.packet[0] = _mm256_permute2f128_si256(S0, S4, 0x20);
+  kernel.packet[1] = _mm256_permute2f128_si256(S1, S5, 0x20);
+  kernel.packet[2] = _mm256_permute2f128_si256(S2, S6, 0x20);
+  kernel.packet[3] = _mm256_permute2f128_si256(S3, S7, 0x20);
+  kernel.packet[4] = _mm256_permute2f128_si256(S0, S4, 0x31);
+  kernel.packet[5] = _mm256_permute2f128_si256(S1, S5, 0x31);
+  kernel.packet[6] = _mm256_permute2f128_si256(S2, S6, 0x31);
+  kernel.packet[7] = _mm256_permute2f128_si256(S3, S7, 0x31);
+}
+
+EIGEN_DEVICE_FUNC inline void
+ptranspose(PacketBlock<Packet8i,4>& kernel) {
+  __m256i T0 = MM256_UNPACKLO_EPI32(kernel.packet[0], kernel.packet[1]);
+  __m256i T1 = MM256_UNPACKHI_EPI32(kernel.packet[0], kernel.packet[1]);
+  __m256i T2 = MM256_UNPACKLO_EPI32(kernel.packet[2], kernel.packet[3]);
+  __m256i T3 = MM256_UNPACKHI_EPI32(kernel.packet[2], kernel.packet[3]);
+
+  __m256i S0 = MM256_SHUFFLE_EPI32(T0,T2,_MM_SHUFFLE(1,0,1,0));
+  __m256i S1 = MM256_SHUFFLE_EPI32(T0,T2,_MM_SHUFFLE(3,2,3,2));
+  __m256i S2 = MM256_SHUFFLE_EPI32(T1,T3,_MM_SHUFFLE(1,0,1,0));
+  __m256i S3 = MM256_SHUFFLE_EPI32(T1,T3,_MM_SHUFFLE(3,2,3,2));
+
+  kernel.packet[0] = _mm256_permute2f128_si256(S0, S1, 0x20);
+  kernel.packet[1] = _mm256_permute2f128_si256(S2, S3, 0x20);
+  kernel.packet[2] = _mm256_permute2f128_si256(S0, S1, 0x31);
+  kernel.packet[3] = _mm256_permute2f128_si256(S2, S3, 0x31);
+}
+
 EIGEN_DEVICE_FUNC inline void
 ptranspose(PacketBlock<Packet4d,4>& kernel) {
   __m256d T0 = _mm256_shuffle_pd(kernel.packet[0], kernel.packet[1], 15);
@@ -919,21 +1397,37 @@ ptranspose(PacketBlock<Packet4d,4>& kernel) {
 }
 
 template<> EIGEN_STRONG_INLINE Packet8f pblend(const Selector<8>& ifPacket, const Packet8f& thenPacket, const Packet8f& elsePacket) {
+#ifdef EIGEN_VECTORIZE_AVX2  
+  const __m256i zero = _mm256_setzero_si256();
+  const __m256i select = _mm256_set_epi32(ifPacket.select[7], ifPacket.select[6], ifPacket.select[5], ifPacket.select[4], ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
+  __m256i false_mask = _mm256_cmpeq_epi32(zero, select);
+  return _mm256_blendv_ps(thenPacket, elsePacket, _mm256_castsi256_ps(false_mask));
+#else
   const __m256 zero = _mm256_setzero_ps();
   const __m256 select = _mm256_set_ps(ifPacket.select[7], ifPacket.select[6], ifPacket.select[5], ifPacket.select[4], ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
   __m256 false_mask = _mm256_cmp_ps(select, zero, _CMP_EQ_UQ);
   return _mm256_blendv_ps(thenPacket, elsePacket, false_mask);
+#endif
 }
+
 template<> EIGEN_STRONG_INLINE Packet4d pblend(const Selector<4>& ifPacket, const Packet4d& thenPacket, const Packet4d& elsePacket) {
+#ifdef EIGEN_VECTORIZE_AVX2  
+  const __m256i zero = _mm256_setzero_si256();
+  const __m256i select = _mm256_set_epi64x(ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
+  __m256i false_mask = _mm256_cmpeq_epi64(select, zero);
+  return _mm256_blendv_pd(thenPacket, elsePacket, _mm256_castsi256_pd(false_mask));
+#else
   const __m256d zero = _mm256_setzero_pd();
   const __m256d select = _mm256_set_pd(ifPacket.select[3], ifPacket.select[2], ifPacket.select[1], ifPacket.select[0]);
   __m256d false_mask = _mm256_cmp_pd(select, zero, _CMP_EQ_UQ);
   return _mm256_blendv_pd(thenPacket, elsePacket, false_mask);
+#endif
 }
 
 // Packet math for Eigen::half
-
+#ifndef EIGEN_VECTORIZE_AVX512FP16
 template<> struct unpacket_traits<Packet8h> { typedef Eigen::half type; enum {size=8, alignment=Aligned16, vectorizable=true, masked_load_available=false, masked_store_available=false}; typedef Packet8h half; };
+#endif
 
 template<> EIGEN_STRONG_INLINE Packet8h pset1<Packet8h>(const Eigen::half& from) {
   return _mm_set1_epi16(numext::bit_cast<numext::uint16_t>(from));
@@ -989,18 +1483,9 @@ EIGEN_STRONG_INLINE Packet8f half2float(const Packet8h& a) {
 #ifdef EIGEN_HAS_FP16_C
   return _mm256_cvtph_ps(a);
 #else
-  EIGEN_ALIGN32 Eigen::half aux[8];
+  Eigen::internal::Packet8f pp = _mm256_castsi256_ps(_mm256_insertf128_si256(
-  pstore(aux, a);
+      _mm256_castsi128_si256(half2floatsse(a)), half2floatsse(_mm_srli_si128(a, 8)), 1));
-  float f0(aux[0]);
+  return pp;
-  float f1(aux[1]);
-  float f2(aux[2]);
-  float f3(aux[3]);
-  float f4(aux[4]);
-  float f5(aux[5]);
-  float f6(aux[6]);
-  float f7(aux[7]);
-
-  return _mm256_set_ps(f7, f6, f5, f4, f3, f2, f1, f0);
 #endif
 }
 
@@ -1008,17 +1493,9 @@ EIGEN_STRONG_INLINE Packet8h float2half(const Packet8f& a) {
 #ifdef EIGEN_HAS_FP16_C
   return _mm256_cvtps_ph(a, _MM_FROUND_TO_NEAREST_INT|_MM_FROUND_NO_EXC);
 #else
-  EIGEN_ALIGN32 float aux[8];
+  __m128i lo = float2half(_mm256_extractf128_ps(a, 0));
-  pstore(aux, a);
+  __m128i hi = float2half(_mm256_extractf128_ps(a, 1));
-  const numext::uint16_t s0 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[0]));
+  return   _mm_packus_epi32(lo, hi);
-  const numext::uint16_t s1 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[1]));
-  const numext::uint16_t s2 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[2]));
-  const numext::uint16_t s3 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[3]));
-  const numext::uint16_t s4 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[4]));
-  const numext::uint16_t s5 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[5]));
-  const numext::uint16_t s6 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[6]));
-  const numext::uint16_t s7 = numext::bit_cast<numext::uint16_t>(Eigen::half(aux[7]));
-  return _mm_set_epi16(s7, s6, s5, s4, s3, s2, s1, s0);
 #endif
 }
 
@@ -1097,6 +1574,7 @@ template<> EIGEN_STRONG_INLINE Packet8h pnegate(const Packet8h& a) {
   return _mm_xor_si128(a, sign_mask);
 }
 
+#ifndef EIGEN_VECTORIZE_AVX512FP16
 template<> EIGEN_STRONG_INLINE Packet8h padd<Packet8h>(const Packet8h& a, const Packet8h& b) {
   Packet8f af = half2float(a);
   Packet8f bf = half2float(b);
@@ -1124,6 +1602,7 @@ template<> EIGEN_STRONG_INLINE Packet8h pdiv<Packet8h>(const Packet8h& a, const
   Packet8f rf = pdiv(af, bf);
   return float2half(rf);
 }
+#endif
 
 template<> EIGEN_STRONG_INLINE Packet8h pgather<Eigen::half, Packet8h>(const Eigen::half* from, Index stride)
 {
@@ -1152,11 +1631,14 @@ template<> EIGEN_STRONG_INLINE void pscatter<Eigen::half, Packet8h>(Eigen::half*
   to[stride*7] = aux[7];
 }
 
+
+#ifndef EIGEN_VECTORIZE_AVX512FP16
 template<> EIGEN_STRONG_INLINE Eigen::half predux<Packet8h>(const Packet8h& a) {
   Packet8f af = half2float(a);
   float reduced = predux<Packet8f>(af);
   return Eigen::half(reduced);
 }
+#endif
 
 template<> EIGEN_STRONG_INLINE Eigen::half predux_max<Packet8h>(const Packet8h& a) {
   Packet8f af = half2float(a);
@@ -1272,7 +1754,6 @@ EIGEN_STRONG_INLINE Packet8f Bf16ToF32(const Packet8bf& a) {
 
 // Convert float to bfloat16 according to round-to-nearest-even/denormals algorithm.
 EIGEN_STRONG_INLINE Packet8bf F32ToBf16(const Packet8f& a) {
-  Packet8bf r;
 
   __m256i input = _mm256_castps_si256(a);
 

libs/eigen/Eigen/src/Core/arch/AVX/TypeCasting.h

@@ -10,6 +10,8 @@
 #ifndef EIGEN_TYPE_CASTING_AVX_H
 #define EIGEN_TYPE_CASTING_AVX_H
 
+#include "../../InternalHeaderCheck.h"
+
 namespace Eigen {
 
 namespace internal {