bump to 3.2.9

(grafted from 476beed7f8
)

.clang-format

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

.clang-tidy

@@ -1,37 +0,0 @@
----
-# Conservative clang-tidy configuration for Eigen.
-#
-# Focuses on bug-finding checks with low false-positive rates.
-# Intentionally omits style-enforcement checks (modernize-*, google-*,
-# cppcoreguidelines-*) since Eigen has its own conventions and is a
-# heavily-templated math library where many "modern C++" idioms don't apply.
-
-Checks: >
-  -*,
-  bugprone-*,
-  -bugprone-narrowing-conversions,
-  -bugprone-easily-swappable-parameters,
-  -bugprone-implicit-widening-of-multiplication-result,
-  -bugprone-exception-escape,
-  misc-redundant-expression,
-  misc-unused-using-decls,
-  misc-misleading-identifier,
-  performance-for-range-copy,
-  performance-implicit-conversion-in-loop,
-  performance-unnecessary-copy-initialization,
-  performance-unnecessary-value-param,
-  readability-container-size-empty,
-  readability-duplicate-include,
-  readability-misleading-indentation,
-  readability-redundant-control-flow,
-  readability-redundant-smartptr-get,
-
-WarningsAsErrors: ''
-
-HeaderFilterRegex: 'Eigen/.*|test/.*|blas/.*|lapack/.*|unsupported/Eigen/.*'
-
-# Eigen uses its own assert macros.
-CheckOptions:
-  - key: bugprone-assert-side-effect.AssertMacros
-    value: 'eigen_assert,eigen_internal_assert,EIGEN_STATIC_ASSERT,VERIFY,VERIFY_IS_APPROX,VERIFY_IS_EQUAL,VERIFY_IS_MUCH_SMALLER_THAN,VERIFY_IS_NOT_APPROX,VERIFY_IS_NOT_EQUAL,VERIFY_IS_UNITARY,VERIFY_RAISES_ASSERT'
-...

.git-blame-ignore-revs

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

.gitattributes

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

.gitlab-ci.yml

@@ -1,52 +0,0 @@
-# This file is part of Eigen, a lightweight C++ template library
-# for linear algebra.
-#
-# Copyright (C) 2023, The Eigen Authors
-#
-# This Source Code Form is subject to the terms of the Mozilla
-# Public License v. 2.0. If a copy of the MPL was not distributed
-# with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-default:
-  interruptible: true
-
-# For MR pipelines, auto-cancel running jobs when new commits are pushed.
-# For scheduled (nightly) pipelines, never auto-cancel so all jobs run to
-# completion and all failures are visible for debugging.
-workflow:
-  auto_cancel:
-    on_new_commit: interruptible
-    on_job_failure: none
-  rules:
-    - if: $CI_PIPELINE_SOURCE == "schedule"
-      auto_cancel:
-        on_new_commit: none
-    - when: always
-
-stages:
-  - checkformat
-  - build
-  - test
-  - benchmark
-  - deploy
-
-variables:
-  # CMake build directory.
-  EIGEN_CI_BUILDDIR: .build
-  # Specify the CMake build target.
-  EIGEN_CI_BUILD_TARGET: ""
-  # If a test regex is specified, that will be selected.
-  # Otherwise, we will try a label if specified.
-  EIGEN_CI_CTEST_REGEX: ""
-  EIGEN_CI_CTEST_LABEL: ""
-  EIGEN_CI_CTEST_ARGS: ""
-
-include:
-  - "/ci/checkformat.gitlab-ci.yml"
-  - "/ci/common.gitlab-ci.yml"
-  - "/ci/build.linux.gitlab-ci.yml"
-  - "/ci/build.windows.gitlab-ci.yml"
-  - "/ci/test.linux.gitlab-ci.yml"
-  - "/ci/test.windows.gitlab-ci.yml"
-  - "/ci/benchmark.gitlab-ci.yml"
-  - "/ci/deploy.gitlab-ci.yml"

.gitlab/issue_templates/Bug Report.md

@@ -1,59 +0,0 @@
-<!--
-Thank you for submitting an issue!
-
-Before opening a new issue, please search for keywords in the existing [list of issues](https://gitlab.com/libeigen/eigen/-/issues?state=opened) to verify it isn't a duplicate.
--->
-
-### Summary
-<!-- Summarize the bug encountered concisely. -->
-
-### Environment
-<!-- Please provide your development environment. -->
-- **Operating System** : Windows/Linux
-- **Architecture** : x64/Arm64/PowerPC ...
-- **Eigen Version** : 5.0.0
-- **Compiler Version** : gcc-12.0
-- **Compile Flags** : -O3 -march=native
-- **Vector Extension** : SSE/AVX/NEON ...
-
-### Minimal Example
-<!--
-Please create a minimal reproducing example here that exhibits the problematic behavior.
-The example should be complete, in that it can fully build and run.  See the [the guidelines on stackoverflow](https://stackoverflow.com/help/minimal-reproducible-example) for how to create a good minimal example.
-
-You can also link to [godbolt](https://godbolt.org). Note that you need to click 
-the "Share" button in the top right-hand corner of the godbolt page to get the share link
-instead of the URL in your browser address bar. 
--->
-
-```cpp
-// Insert  your code here.
-```
-
-### Steps to reproduce the issue
-<!-- Describe the necessary steps to reproduce the issue. -->
-
-1. first step
-2. second step
-3. ... 
-
-### What is the current *bug* behavior?
-<!-- Describe what actually happens. -->
-
-### What is the expected *correct* behavior?
-<!-- Describe what you should see instead. -->
-
-### Relevant logs
-<!-- Add relevant build logs or program output within blocks marked by " ``` " -->
-
-### [Optional] Benchmark scripts and results
-<!-- Please share any benchmark scripts - either standalone, or using [Google Benchmark](https://github.com/google/benchmark). -->
-
-### Anything else that might help
-<!--
-It will be better to provide us more information to help narrow down the cause. 
-Including but not limited to the following: 
-- lines of code that might help us diagnose the problem. 
-- potential ways to address the issue.
-- last known working/first broken version (release number or commit hash).
---> 

.gitlab/issue_templates/Feature Request.md

@@ -1,14 +0,0 @@
-<!--
-Thank you for submitting a Feature Request!
-
-If you want to run ideas by the maintainers and the Eigen community first, 
-you can chat about them on the [Eigen Discord server](https://discord.gg/2SkEJGqZjR).
--->
-
-### Describe the feature you would like to be implemented.
-
-### Why Would such a feature be useful for other users?
-
-### Any hints on how to implement the requested feature?
-
-### Additional resources

.gitlab/merge_request_templates/Default.md

@@ -1,30 +0,0 @@
-<!--
-Thanks for contributing a merge request!
-
-We recommend that first-time contributors read our [contribution guidelines](https://eigen.tuxfamily.org/index.php?title=Contributing_to_Eigen).
-
-Before submitting the MR, please complete the following checks:
-- Create one PR per feature or bugfix,
-- Run the test suite to verify your changes.
-  See our [test guidelines](https://eigen.tuxfamily.org/index.php?title=Tests).
-- Add tests to cover the bug addressed or any new feature.
-- Document new features.  If it is a substantial change, add it to the [Changelog](https://gitlab.com/libeigen/eigen/-/blob/master/CHANGELOG.md).
-- Leave the following box checked when submitting: `Allow commits from members who can merge to the target branch`.
-  This allows us to rebase and merge your change.
-
-Note that we are a team of volunteers; we appreciate your patience during the review process.
--->
-
-### Description
-<!--Please explain your changes.-->
-
-%{first_multiline_commit}
-
-### Reference issue
-<!--
-You can link to a specific issue using the gitlab syntax #<issue number>.
-If the MR fixes an issue, write "Fixes #<issue number>" to have the issue automatically closed on merge.
--->
-
-### Additional information
-<!--Any additional information you think is important.-->

.hgeol

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

.hgignore

@@ -1,3 +1,4 @@
+syntax: glob
 qrc_*cxx
 *.orig
 *.pyc
@@ -12,7 +13,7 @@ core
 core.*
 *.bak
 *~
-*.build*
+build*
 *.moc.*
 *.moc
 ui_*
@@ -27,16 +28,5 @@ activity.png
 *.rej
 log
 patch
-*.patch
 a
 a.*
-lapack/testing
-lapack/reference
-.*project
-.settings
-Makefile
-!ci/build.gitlab-ci.yml
-!scripts/buildtests.in
-!Eigen/Core
-!Eigen/src/Core
-CLAUDE.md

COPYING.APACHE

@@ -1,203 +0,0 @@
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COPYING.BSD

@@ -23,4 +23,4 @@
  ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
  (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-*/
+*/

COPYING.GPL

@@ -0,0 +1,674 @@
+                    GNU GENERAL PUBLIC LICENSE
+                       Version 3, 29 June 2007
+
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+ Everyone is permitted to copy and distribute verbatim copies
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+
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+
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+<http://www.gnu.org/philosophy/why-not-lgpl.html>.

COPYING.LGPL

@@ -0,0 +1,502 @@
+                  GNU LESSER GENERAL PUBLIC LICENSE
+                       Version 2.1, February 1999
+
+ Copyright (C) 1991, 1999 Free Software Foundation, Inc.
+ 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+ Everyone is permitted to copy and distribute verbatim copies
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+
+[This is the first released version of the Lesser GPL.  It also counts
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+
+                            Preamble
+
+  The licenses for most software are designed to take away your
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+
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+
+  <signature of Ty Coon>, 1 April 1990
+  Ty Coon, President of Vice
+
+That's all there is to it!

COPYING.MINPACK

@@ -1,51 +1,52 @@
-Minpack Copyright Notice (1999) University of Chicago.  All rights reserved
-
-Redistribution and use in source and binary forms, with or
-without modification, are permitted provided that the
-following conditions are met:
-
-1. Redistributions of source code must retain the above
-copyright notice, this list of conditions and the following
-disclaimer.
-
-2. Redistributions in binary form must reproduce the above
-copyright notice, this list of conditions and the following
-disclaimer in the documentation and/or other materials
-provided with the distribution.
-
-3. The end-user documentation included with the
-redistribution, if any, must include the following
-acknowledgment:
-
-   "This product includes software developed by the
-   University of Chicago, as Operator of Argonne National
-   Laboratory.
-
-Alternately, this acknowledgment may appear in the software
-itself, if and wherever such third-party acknowledgments
-normally appear.
-
-4. WARRANTY DISCLAIMER. THE SOFTWARE IS SUPPLIED "AS IS"
-WITHOUT WARRANTY OF ANY KIND. THE COPYRIGHT HOLDER, THE
-UNITED STATES, THE UNITED STATES DEPARTMENT OF ENERGY, AND
-THEIR EMPLOYEES: (1) DISCLAIM ANY WARRANTIES, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO ANY IMPLIED WARRANTIES
-OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE
-OR NON-INFRINGEMENT, (2) DO NOT ASSUME ANY LEGAL LIABILITY
-OR RESPONSIBILITY FOR THE ACCURACY, COMPLETENESS, OR
-USEFULNESS OF THE SOFTWARE, (3) DO NOT REPRESENT THAT USE OF
-THE SOFTWARE WOULD NOT INFRINGE PRIVATELY OWNED RIGHTS, (4)
-DO NOT WARRANT THAT THE SOFTWARE WILL FUNCTION
-UNINTERRUPTED, THAT IT IS ERROR-FREE OR THAT ANY ERRORS WILL
-BE CORRECTED.
-
-5. LIMITATION OF LIABILITY. IN NO EVENT WILL THE COPYRIGHT
-HOLDER, THE UNITED STATES, THE UNITED STATES DEPARTMENT OF
-ENERGY, OR THEIR EMPLOYEES: BE LIABLE FOR ANY INDIRECT,
-INCIDENTAL, CONSEQUENTIAL, SPECIAL OR PUNITIVE DAMAGES OF
-ANY KIND OR NATURE, INCLUDING BUT NOT LIMITED TO LOSS OF
-PROFITS OR LOSS OF DATA, FOR ANY REASON WHATSOEVER, WHETHER
-SUCH LIABILITY IS ASSERTED ON THE BASIS OF CONTRACT, TORT
-(INCLUDING NEGLIGENCE OR STRICT LIABILITY), OR OTHERWISE,
-EVEN IF ANY OF SAID PARTIES HAS BEEN WARNED OF THE
-POSSIBILITY OF SUCH LOSS OR DAMAGES.
+Minpack Copyright Notice (1999) University of Chicago.  All rights reserved
+
+Redistribution and use in source and binary forms, with or
+without modification, are permitted provided that the
+following conditions are met:
+
+1. Redistributions of source code must retain the above
+copyright notice, this list of conditions and the following
+disclaimer.
+
+2. Redistributions in binary form must reproduce the above
+copyright notice, this list of conditions and the following
+disclaimer in the documentation and/or other materials
+provided with the distribution.
+
+3. The end-user documentation included with the
+redistribution, if any, must include the following
+acknowledgment:
+
+   "This product includes software developed by the
+   University of Chicago, as Operator of Argonne National
+   Laboratory.
+
+Alternately, this acknowledgment may appear in the software
+itself, if and wherever such third-party acknowledgments
+normally appear.
+
+4. WARRANTY DISCLAIMER. THE SOFTWARE IS SUPPLIED "AS IS"
+WITHOUT WARRANTY OF ANY KIND. THE COPYRIGHT HOLDER, THE
+UNITED STATES, THE UNITED STATES DEPARTMENT OF ENERGY, AND
+THEIR EMPLOYEES: (1) DISCLAIM ANY WARRANTIES, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO ANY IMPLIED WARRANTIES
+OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE
+OR NON-INFRINGEMENT, (2) DO NOT ASSUME ANY LEGAL LIABILITY
+OR RESPONSIBILITY FOR THE ACCURACY, COMPLETENESS, OR
+USEFULNESS OF THE SOFTWARE, (3) DO NOT REPRESENT THAT USE OF
+THE SOFTWARE WOULD NOT INFRINGE PRIVATELY OWNED RIGHTS, (4)
+DO NOT WARRANT THAT THE SOFTWARE WILL FUNCTION
+UNINTERRUPTED, THAT IT IS ERROR-FREE OR THAT ANY ERRORS WILL
+BE CORRECTED.
+
+5. LIMITATION OF LIABILITY. IN NO EVENT WILL THE COPYRIGHT
+HOLDER, THE UNITED STATES, THE UNITED STATES DEPARTMENT OF
+ENERGY, OR THEIR EMPLOYEES: BE LIABLE FOR ANY INDIRECT,
+INCIDENTAL, CONSEQUENTIAL, SPECIAL OR PUNITIVE DAMAGES OF
+ANY KIND OR NATURE, INCLUDING BUT NOT LIMITED TO LOSS OF
+PROFITS OR LOSS OF DATA, FOR ANY REASON WHATSOEVER, WHETHER
+SUCH LIABILITY IS ASSERTED ON THE BASIS OF CONTRACT, TORT
+(INCLUDING NEGLIGENCE OR STRICT LIABILITY), OR OTHERWISE,
+EVEN IF ANY OF SAID PARTIES HAS BEEN WARNED OF THE
+POSSIBILITY OF SUCH LOSS OR DAMAGES.
+

COPYING.MPL2

@@ -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 https://mozilla.org/MPL/2.0/.
+  file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 If it is not possible or desirable to put the notice in a particular
 file, then You may include the notice in a location (such as a LICENSE

COPYING.README

@@ -2,10 +2,17 @@ Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
   http://www.mozilla.org/MPL/2.0/
   http://www.mozilla.org/MPL/2.0/FAQ.html
 
-Some files contain third-party code under BSD, LGPL, Apache, or other
-MPL2-compatible licenses, hence the other COPYING.* files here.
+Some files contain third-party code under BSD or LGPL licenses, whence the other
+COPYING.* files here.
 
-Note that some optional external dependencies (e.g. FFTW, MPFR C++)
-are distributed under different licenses, including the GPL. Refer to
-the individual source files and their respective COPYING files for
-details.
+All the LGPL code is either LGPL 2.1-only, or LGPL 2.1-or-later.
+For this reason, the COPYING.LGPL file contains the LGPL 2.1 text.
+
+If you want to guarantee that the Eigen code that you are #including is licensed
+under the MPL2 and possibly more permissive licenses (like BSD), #define this
+preprocessor symbol:
+  EIGEN_MPL2_ONLY
+For example, with most compilers, you could add this to your project CXXFLAGS:
+  -DEIGEN_MPL2_ONLY
+This will cause a compilation error to be generated if you #include any code that is
+LGPL licensed.

CTestConfig.cmake

@@ -2,16 +2,12 @@
 ## Then modify the CMakeLists.txt file in the root directory of your
 ## project to incorporate the testing dashboard.
 ## # The following are required to uses Dart and the Cdash dashboard
-##   enable_testing()
-##   include(CTest)
-set(CTEST_PROJECT_NAME "Eigen")
+##   ENABLE_TESTING()
+##   INCLUDE(CTest)
+set(CTEST_PROJECT_NAME "Eigen3.2")
 set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
 
 set(CTEST_DROP_METHOD "http")
-set(CTEST_DROP_SITE "my.cdash.org")
-set(CTEST_DROP_LOCATION "/submit.php?project=Eigen")
+set(CTEST_DROP_SITE "manao.inria.fr")
+set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen3.2")
 set(CTEST_DROP_SITE_CDASH TRUE)
-#set(CTEST_PROJECT_SUBPROJECTS
-#Official
-#Unsupported
-#)

CTestCustom.cmake.in

@@ -1,4 +1,3 @@
 
 set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "2000")
 set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS   "2000")
-list(APPEND CTEST_CUSTOM_ERROR_EXCEPTION    @EIGEN_CTEST_ERROR_EXCEPTION@)

Eigen/AccelerateSupport

@@ -1,52 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ACCELERATESUPPORT_MODULE_H
-#define EIGEN_ACCELERATESUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \ingroup Support_modules
- * \defgroup AccelerateSupport_Module AccelerateSupport module
- *
- * This module provides an interface to the Apple Accelerate library.
- * It provides the seven following main factorization classes:
- * - class AccelerateLLT: a Cholesky (LL^T) factorization.
- * - class AccelerateLDLT: the default LDL^T factorization.
- * - class AccelerateLDLTUnpivoted: a Cholesky-like LDL^T factorization with only 1x1 pivots and no pivoting
- * - class AccelerateLDLTSBK: an LDL^T factorization with Supernode Bunch-Kaufman and static pivoting
- * - class AccelerateLDLTTPP: an LDL^T factorization with full threshold partial pivoting
- * - class AccelerateQR: a QR factorization
- * - class AccelerateCholeskyAtA: a QR factorization without storing Q (equivalent to A^TA = R^T R)
- *
- * \code
- * #include <Eigen/AccelerateSupport>
- * \endcode
- *
- * In order to use this module, the Accelerate headers must be accessible from
- * the include paths, and your binary must be linked to the Accelerate framework.
- * The Accelerate library is only available on Apple hardware.
- *
- * Note that many of the algorithms can be influenced by the UpLo template
- * argument. All matrices are assumed to be symmetric. For example, the following
- * creates an LDLT factorization where your matrix is symmetric (implicit) and
- * uses the lower triangle:
- *
- * \code
- * AccelerateLDLT<SparseMatrix<float>, Lower> ldlt;
- * \endcode
- */
-
-// IWYU pragma: begin_exports
-#include "src/AccelerateSupport/AccelerateSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_ACCELERATESUPPORT_MODULE_H

Eigen/Array

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

Eigen/CMakeLists.txt

@@ -0,0 +1,19 @@
+include(RegexUtils)
+test_escape_string_as_regex()
+
+file(GLOB Eigen_directory_files "*")
+
+escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
+
+foreach(f ${Eigen_directory_files})
+  if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/src")
+    list(APPEND Eigen_directory_files_to_install ${f})
+  endif()
+endforeach(f ${Eigen_directory_files})
+
+install(FILES
+  ${Eigen_directory_files_to_install}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen COMPONENT Devel
+  )
+
+add_subdirectory(src)

Eigen/Cholesky

@@ -1,41 +1,32 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_CHOLESKY_MODULE_H
 #define EIGEN_CHOLESKY_MODULE_H
 
 #include "Core"
-#include "Jacobi"
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup Cholesky_Module Cholesky module
- *
- * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
- * Those decompositions are also accessible via the following methods:
- *  - MatrixBase::llt()
- *  - MatrixBase::ldlt()
- *  - SelfAdjointView::llt()
- *  - SelfAdjointView::ldlt()
- *
- * \code
- * #include <Eigen/Cholesky>
- * \endcode
- */
+  *
+  *
+  *
+  * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
+  * Those decompositions are accessible via the following MatrixBase methods:
+  *  - MatrixBase::llt(),
+  *  - MatrixBase::ldlt()
+  *
+  * \code
+  * #include <Eigen/Cholesky>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
+#include "src/misc/Solve.h"
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/misc/lapacke_helpers.h"
-#include "src/Cholesky/LLT_LAPACKE.h"
+#include "src/Cholesky/LLT_MKL.h"
 #endif
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_CHOLESKY_MODULE_H
+#endif // EIGEN_CHOLESKY_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/CholmodSupport

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_CHOLMODSUPPORT_MODULE_H
 #define EIGEN_CHOLMODSUPPORT_MODULE_H
 
@@ -12,37 +5,41 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-#include <cholmod.h>
+extern "C" {
+  #include <cholmod.h>
+}
 
 /** \ingroup Support_modules
- * \defgroup CholmodSupport_Module CholmodSupport module
- *
- * This module provides an interface to the Cholmod library which is part of the <a
- * href="http://www.suitesparse.com">suitesparse</a> package. It provides the two following main factorization classes:
- * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
- * - class CholmodDecomposition: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of
- * the underlying factorization method (supernodal or simplicial).
- *
- * For the sake of completeness, this module also propose the two following classes:
- * - class CholmodSimplicialLLT
- * - class CholmodSimplicialLDLT
- * Note that these classes do not bring any particular advantage compared to the built-in
- * SimplicialLLT and SimplicialLDLT factorization classes.
- *
- * \code
- * #include <Eigen/CholmodSupport>
- * \endcode
- *
- * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be
- * linked to the cholmod library and its dependencies. The dependencies depend on how cholmod has been compiled. For a
- * cmake based project, you can use our FindCholmod.cmake module to help you in this task.
- *
- */
+  * \defgroup CholmodSupport_Module CholmodSupport module
+  *
+  * This module provides an interface to the Cholmod library which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
+  * It provides the two following main factorization classes:
+  * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
+  * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
+  *
+  * For the sake of completeness, this module also propose the two following classes:
+  * - class CholmodSimplicialLLT
+  * - class CholmodSimplicialLDLT
+  * Note that these classes does not bring any particular advantage compared to the built-in
+  * SimplicialLLT and SimplicialLDLT factorization classes.
+  *
+  * \code
+  * #include <Eigen/CholmodSupport>
+  * \endcode
+  *
+  * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies.
+  * The dependencies depend on how cholmod has been compiled.
+  * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
-// IWYU pragma: begin_exports
 #include "src/CholmodSupport/CholmodSupport.h"
-// IWYU pragma: end_exports
+
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_CHOLMODSUPPORT_MODULE_H
+#endif // EIGEN_CHOLMODSUPPORT_MODULE_H
+

Eigen/Core

@@ -8,66 +8,138 @@
 // 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_MODULE_H
-#define EIGEN_CORE_MODULE_H
+#ifndef EIGEN_CORE_H
+#define EIGEN_CORE_H
 
-// Eigen version information.
-#include "Version"
-
-// first thing Eigen does: stop the compiler from reporting useless warnings.
+// first thing Eigen does: stop the compiler from committing suicide
 #include "src/Core/util/DisableStupidWarnings.h"
 
 // then include this file where all our macros are defined. It's really important to do it first because
-// it's where we do all the compiler/OS/arch detections and define most defaults.
+// it's where we do all the alignment settings (platform detection and honoring the user's will if he
+// defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization.
 #include "src/Core/util/Macros.h"
 
-// This detects SSE/AVX/NEON/etc. and configure alignment settings
-#include "src/Core/util/ConfigureVectorization.h"
-
-// We need cuda_runtime.h/hip_runtime.h to ensure that
-// the EIGEN_USING_STD macro works properly on the device side
-#if defined(EIGEN_CUDACC)
-#include <cuda_runtime.h>
-#elif defined(EIGEN_HIPCC)
-#include <hip/hip_runtime.h>
+// Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3)
+// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
+#if defined(__MINGW32__) && EIGEN_GNUC_AT_LEAST(4,6)
+  #pragma GCC optimize ("-fno-ipa-cp-clone")
 #endif
 
-#ifdef EIGEN_EXCEPTIONS
-#include <new>
-#endif
-
-// Prevent ICC from specializing std::complex operators that silently fail
-// on device. This allows us to use our own device-compatible specializations
-// instead.
-#if EIGEN_COMP_ICC && defined(EIGEN_GPU_COMPILE_PHASE) && !defined(_OVERRIDE_COMPLEX_SPECIALIZATION_)
-#define _OVERRIDE_COMPLEX_SPECIALIZATION_ 1
-#endif
 #include <complex>
 
 // this include file manages BLAS and MKL related macros
 // and inclusion of their respective header files
 #include "src/Core/util/MKL_support.h"
-#include "src/Core/util/AOCL_Support.h"
 
+// if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into
+// account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks
+#if !EIGEN_ALIGN
+  #ifndef EIGEN_DONT_VECTORIZE
+    #define EIGEN_DONT_VECTORIZE
+  #endif
+#endif
 
-// EIGEN_HAS_GPU_FP16 is now always true when compiling with CUDA or HIP.
-// Use EIGEN_GPUCC (compile-time) or EIGEN_GPU_COMPILE_PHASE (device phase) instead.
-// TODO: Remove EIGEN_HAS_GPU_BF16 similarly once HIP bf16 guards are cleaned up.
+#ifdef _MSC_VER
+  #include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
+  #if (_MSC_VER >= 1500) // 2008 or later
+    // Remember that usage of defined() in a #define is undefined by the standard.
+    // a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP.
+    #if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(_M_X64)
+      #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
+    #endif
+  #endif
+#else
+  // Remember that usage of defined() in a #define is undefined by the standard
+  #if (defined __SSE2__) && ( (!defined __GNUC__) || (defined __INTEL_COMPILER) || EIGEN_GNUC_AT_LEAST(4,2) )
+    #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
+  #endif
+#endif
 
-#if defined(EIGEN_HAS_CUDA_BF16) || defined(EIGEN_HAS_HIP_BF16)
-#define EIGEN_HAS_GPU_BF16
+#ifndef EIGEN_DONT_VECTORIZE
+
+  #if defined (EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC) || defined(EIGEN_SSE2_ON_MSVC_2008_OR_LATER)
+
+    // Defines symbols for compile-time detection of which instructions are
+    // used.
+    // EIGEN_VECTORIZE_YY is defined if and only if the instruction set YY is used
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_SSE
+    #define EIGEN_VECTORIZE_SSE2
+
+    // Detect sse3/ssse3/sse4:
+    // gcc and icc defines __SSE3__, ...
+    // there is no way to know about this on msvc. You can define EIGEN_VECTORIZE_SSE* if you
+    // want to force the use of those instructions with msvc.
+    #ifdef __SSE3__
+      #define EIGEN_VECTORIZE_SSE3
+    #endif
+    #ifdef __SSSE3__
+      #define EIGEN_VECTORIZE_SSSE3
+    #endif
+    #ifdef __SSE4_1__
+      #define EIGEN_VECTORIZE_SSE4_1
+    #endif
+    #ifdef __SSE4_2__
+      #define EIGEN_VECTORIZE_SSE4_2
+    #endif
+
+    // include files
+
+    // This extern "C" works around a MINGW-w64 compilation issue
+    // https://sourceforge.net/tracker/index.php?func=detail&aid=3018394&group_id=202880&atid=983354
+    // In essence, intrin.h is included by windows.h and also declares intrinsics (just as emmintrin.h etc. below do).
+    // However, intrin.h uses an extern "C" declaration, and g++ thus complains of duplicate declarations
+    // with conflicting linkage.  The linkage for intrinsics doesn't matter, but at that stage the compiler doesn't know;
+    // so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too.
+    // notice that since these are C headers, the extern "C" is theoretically needed anyways.
+    extern "C" {
+      // In theory we should only include immintrin.h and not the other *mmintrin.h header files directly.
+      // Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus:
+      #if defined(__INTEL_COMPILER) && __INTEL_COMPILER >= 1110
+        #include <immintrin.h>
+      #else
+        #include <emmintrin.h>
+        #include <xmmintrin.h>
+        #ifdef  EIGEN_VECTORIZE_SSE3
+        #include <pmmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSSE3
+        #include <tmmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSE4_1
+        #include <smmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSE4_2
+        #include <nmmintrin.h>
+        #endif
+      #endif
+    } // end extern "C"
+  #elif defined __ALTIVEC__
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_ALTIVEC
+    #include <altivec.h>
+    // We need to #undef all these ugly tokens defined in <altivec.h>
+    // => use __vector instead of vector
+    #undef bool
+    #undef vector
+    #undef pixel
+  #elif defined  __ARM_NEON
+    #define EIGEN_VECTORIZE
+    #define EIGEN_VECTORIZE_NEON
+    #include <arm_neon.h>
+  #endif
 #endif
 
 #if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE)
-#define EIGEN_HAS_OPENMP
+  #define EIGEN_HAS_OPENMP
 #endif
 
 #ifdef EIGEN_HAS_OPENMP
-#include <atomic>
 #include <omp.h>
 #endif
 
-#if !EIGEN_COMP_ARM
+// MSVC for windows mobile does not have the errno.h file
+#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
 #define EIGEN_HAS_ERRNO
 #endif
 
@@ -77,334 +149,183 @@
 #include <cstddef>
 #include <cstdlib>
 #include <cmath>
+#include <cassert>
 #include <functional>
-#ifndef EIGEN_NO_IO
-#include <sstream>
 #include <iosfwd>
-#endif
 #include <cstring>
 #include <string>
 #include <limits>
-#include <climits>  // for CHAR_BIT
+#include <climits> // for CHAR_BIT
 // for min/max:
 #include <algorithm>
 
-#include <array>
-#include <memory>
-#include <vector>
-
-// for std::is_nothrow_move_assignable
-#include <type_traits>
-
-// for std::this_thread::yield().
-#if !defined(EIGEN_USE_BLAS) && (defined(EIGEN_HAS_OPENMP) || defined(EIGEN_GEMM_THREADPOOL))
-#include <thread>
-#endif
-
-// for __cpp_lib feature test macros
-#if defined(__has_include) && __has_include(<version>)
-#include <version>
-#endif
-
-// for std::bit_cast()
-#if defined(__cpp_lib_bit_cast) && __cpp_lib_bit_cast >= 201806L
-#include <bit>
-#endif
-
 // for outputting debug info
 #ifdef EIGEN_DEBUG_ASSIGN
 #include <iostream>
 #endif
 
 // required for __cpuid, needs to be included after cmath
-// also required for _BitScanReverse on Windows on ARM
-#if EIGEN_COMP_MSVC && (EIGEN_ARCH_i386_OR_x86_64 || EIGEN_ARCH_ARM64)
-#include <intrin.h>
+#if defined(_MSC_VER) && (defined(_M_IX86)||defined(_M_X64)) && (!defined(_WIN32_WCE))
+  #include <intrin.h>
 #endif
 
-// Required for querying cache sizes on Linux and macOS.
-#if EIGEN_OS_LINUX
-#include <unistd.h>
-#elif EIGEN_OS_MAC
-#include <sys/types.h>
-#include <sys/sysctl.h>
+#if defined(_CPPUNWIND) || defined(__EXCEPTIONS)
+  #define EIGEN_EXCEPTIONS
 #endif
 
-#if defined(EIGEN_USE_SYCL)
-#undef min
-#undef max
-#undef isnan
-#undef isinf
-#undef isfinite
-#include <CL/sycl.hpp>
-#include <map>
-#include <thread>
-#include <utility>
-#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM0
-#define EIGEN_SYCL_LOCAL_THREAD_DIM0 16
-#endif
-#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM1
-#define EIGEN_SYCL_LOCAL_THREAD_DIM1 16
-#endif
+#ifdef EIGEN_EXCEPTIONS
+  #include <new>
 #endif
 
+/** \brief Namespace containing all symbols from the %Eigen library. */
 namespace Eigen {
 
+inline static const char *SimdInstructionSetsInUse(void) {
+#if defined(EIGEN_VECTORIZE_SSE4_2)
+  return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2";
+#elif defined(EIGEN_VECTORIZE_SSE4_1)
+  return "SSE, SSE2, SSE3, SSSE3, SSE4.1";
+#elif defined(EIGEN_VECTORIZE_SSSE3)
+  return "SSE, SSE2, SSE3, SSSE3";
+#elif defined(EIGEN_VECTORIZE_SSE3)
+  return "SSE, SSE2, SSE3";
+#elif defined(EIGEN_VECTORIZE_SSE2)
+  return "SSE, SSE2";
+#elif defined(EIGEN_VECTORIZE_ALTIVEC)
+  return "AltiVec";
+#elif defined(EIGEN_VECTORIZE_NEON)
+  return "ARM NEON";
+#else
+  return "None";
+#endif
+}
+
+} // end namespace Eigen
+
+#define STAGE10_FULL_EIGEN2_API             10
+#define STAGE20_RESOLVE_API_CONFLICTS       20
+#define STAGE30_FULL_EIGEN3_API             30
+#define STAGE40_FULL_EIGEN3_STRICTNESS      40
+#define STAGE99_NO_EIGEN2_SUPPORT           99
+
+#if   defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE40_FULL_EIGEN3_STRICTNESS
+#elif defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
+#elif defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE20_RESOLVE_API_CONFLICTS
+#elif defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API
+  #define EIGEN2_SUPPORT
+  #define EIGEN2_SUPPORT_STAGE STAGE10_FULL_EIGEN2_API
+#elif defined EIGEN2_SUPPORT
+  // default to stage 3, that's what it's always meant
+  #define EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API
+  #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API
+#else
+  #define EIGEN2_SUPPORT_STAGE STAGE99_NO_EIGEN2_SUPPORT
+#endif
+
+#ifdef EIGEN2_SUPPORT
+#undef minor
+#endif
+
+// we use size_t frequently and we'll never remember to prepend it with std:: everytime just to
+// ensure QNX/QCC support
 using std::size_t;
+// gcc 4.6.0 wants std:: for ptrdiff_t 
 using std::ptrdiff_t;
 
-}  // namespace Eigen
-
 /** \defgroup Core_Module Core module
- * This is the main module of Eigen providing dense matrix and vector support
- * (both fixed and dynamic size) with all the features corresponding to a BLAS library
- * and much more...
- *
- * \code
- * #include <Eigen/Core>
- * \endcode
- */
+  * This is the main module of Eigen providing dense matrix and vector support
+  * (both fixed and dynamic size) with all the features corresponding to a BLAS library
+  * and much more...
+  *
+  * \code
+  * #include <Eigen/Core>
+  * \endcode
+  */
 
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#elif defined(EIGEN_LAPACKE_SYSTEM)
-#include <lapacke.h>
-#else
-#include "src/misc/lapacke.h"
-#endif
-#endif
-
-// IWYU pragma: begin_exports
 #include "src/Core/util/Constants.h"
-#include "src/Core/util/Meta.h"
-#include "src/Core/util/Assert.h"
 #include "src/Core/util/ForwardDeclarations.h"
+#include "src/Core/util/Meta.h"
 #include "src/Core/util/StaticAssert.h"
 #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/util/EmulateArray.h"
-#include "src/Core/util/MoreMeta.h"
 
 #include "src/Core/NumTraits.h"
 #include "src/Core/MathFunctions.h"
-#include "src/Core/RandomImpl.h"
 #include "src/Core/GenericPacketMath.h"
-#include "src/Core/MathFunctionsImpl.h"
-#include "src/Core/arch/Default/ConjHelper.h"
-// Generic half float support
-#include "src/Core/arch/Default/Half.h"
-#include "src/Core/arch/Default/BFloat16.h"
-#include "src/Core/arch/Default/GenericPacketMathFunctionsFwd.h"
 
-#if defined(EIGEN_VECTORIZE_GENERIC) && !defined(EIGEN_DONT_VECTORIZE)
-#include "src/Core/arch/clang/PacketMath.h"
-#include "src/Core/arch/clang/TypeCasting.h"
-#include "src/Core/arch/clang/Complex.h"
-#include "src/Core/arch/clang/Reductions.h"
-#include "src/Core/arch/clang/MathFunctions.h"
-#else
-#if defined EIGEN_VECTORIZE_AVX512
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/AVX/PacketMath.h"
-#include "src/Core/arch/AVX/Reductions.h"
-#include "src/Core/arch/AVX512/PacketMath.h"
-#include "src/Core/arch/AVX512/Reductions.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/PacketMathFP16.h"
-#endif
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/AVX/TypeCasting.h"
-#include "src/Core/arch/AVX512/TypeCasting.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/TypeCastingFP16.h"
-#endif
-#include "src/Core/arch/SSE/Complex.h"
-#include "src/Core/arch/AVX/Complex.h"
-#include "src/Core/arch/AVX512/Complex.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/AVX/MathFunctions.h"
-#include "src/Core/arch/AVX512/MathFunctions.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/MathFunctionsFP16.h"
-#endif
-#include "src/Core/arch/AVX512/TrsmKernel.h"
-#elif defined EIGEN_VECTORIZE_AVX
-// Use AVX for floats and doubles, SSE for integers
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/SSE/Complex.h"
-#include "src/Core/arch/AVX/PacketMath.h"
-#include "src/Core/arch/AVX/Reductions.h"
-#include "src/Core/arch/AVX/TypeCasting.h"
-#include "src/Core/arch/AVX/Complex.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/AVX/MathFunctions.h"
-#elif defined EIGEN_VECTORIZE_SSE
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/SSE/Complex.h"
-#endif
-
-#if defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX)
-#include "src/Core/arch/AltiVec/PacketMath.h"
-#include "src/Core/arch/AltiVec/TypeCasting.h"
-#include "src/Core/arch/AltiVec/MathFunctions.h"
-#include "src/Core/arch/AltiVec/Complex.h"
+#if defined EIGEN_VECTORIZE_SSE
+  #include "src/Core/arch/SSE/PacketMath.h"
+  #include "src/Core/arch/SSE/MathFunctions.h"
+  #include "src/Core/arch/SSE/Complex.h"
+#elif defined EIGEN_VECTORIZE_ALTIVEC
+  #include "src/Core/arch/AltiVec/PacketMath.h"
+  #include "src/Core/arch/AltiVec/Complex.h"
 #elif defined EIGEN_VECTORIZE_NEON
-#include "src/Core/arch/NEON/PacketMath.h"
-#include "src/Core/arch/NEON/TypeCasting.h"
-#include "src/Core/arch/NEON/MathFunctions.h"
-#include "src/Core/arch/NEON/Complex.h"
-#elif defined EIGEN_VECTORIZE_LSX
-#include "src/Core/arch/LSX/PacketMath.h"
-#include "src/Core/arch/LSX/TypeCasting.h"
-#include "src/Core/arch/LSX/MathFunctions.h"
-#include "src/Core/arch/LSX/Complex.h"
-#elif defined EIGEN_VECTORIZE_SVE
-#include "src/Core/arch/SVE/PacketMath.h"
-#include "src/Core/arch/SVE/TypeCasting.h"
-#include "src/Core/arch/SVE/MathFunctions.h"
-#elif defined EIGEN_VECTORIZE_RVV10
-#include "src/Core/arch/RVV10/PacketMath.h"
-#include "src/Core/arch/RVV10/PacketMath4.h"
-#include "src/Core/arch/RVV10/PacketMath2.h"
-#include "src/Core/arch/RVV10/TypeCasting.h"
-#include "src/Core/arch/RVV10/MathFunctions.h"
-#if defined EIGEN_VECTORIZE_RVV10FP16
-#include "src/Core/arch/RVV10/PacketMathFP16.h"
+  #include "src/Core/arch/NEON/PacketMath.h"
+  #include "src/Core/arch/NEON/Complex.h"
 #endif
-#if defined EIGEN_VECTORIZE_RVV10BF16
-#include "src/Core/arch/RVV10/PacketMathBF16.h"
-#endif
-#elif defined EIGEN_VECTORIZE_ZVECTOR
-#include "src/Core/arch/ZVector/PacketMath.h"
-#include "src/Core/arch/ZVector/MathFunctions.h"
-#include "src/Core/arch/ZVector/Complex.h"
-#elif defined EIGEN_VECTORIZE_MSA
-#include "src/Core/arch/MSA/PacketMath.h"
-#include "src/Core/arch/MSA/MathFunctions.h"
-#include "src/Core/arch/MSA/Complex.h"
-#elif defined EIGEN_VECTORIZE_HVX
-#include "src/Core/arch/HVX/PacketMath.h"
-#endif
-
-#if defined EIGEN_VECTORIZE_GPU
-#include "src/Core/arch/GPU/PacketMath.h"
-#include "src/Core/arch/GPU/MathFunctions.h"
-#include "src/Core/arch/GPU/TypeCasting.h"
-#endif
-
-#if defined(EIGEN_USE_SYCL)
-#include "src/Core/arch/SYCL/InteropHeaders.h"
-#if !defined(EIGEN_DONT_VECTORIZE_SYCL)
-#include "src/Core/arch/SYCL/PacketMath.h"
-#include "src/Core/arch/SYCL/MathFunctions.h"
-#include "src/Core/arch/SYCL/TypeCasting.h"
-#endif
-#endif
-
-#endif  // #ifndef EIGEN_VECTORIZE_GENERIC
 
 #include "src/Core/arch/Default/Settings.h"
-// This file provides generic implementations valid for scalar as well
-#include "src/Core/arch/Default/GenericPacketMathFunctions.h"
 
-#include "src/Core/functors/TernaryFunctors.h"
-#include "src/Core/functors/BinaryFunctors.h"
-#include "src/Core/functors/UnaryFunctors.h"
-#include "src/Core/functors/NullaryFunctors.h"
-#include "src/Core/functors/StlFunctors.h"
-#include "src/Core/functors/AssignmentFunctors.h"
-
-// Specialized functors for GPU.
-#ifdef EIGEN_GPUCC
-#include "src/Core/arch/GPU/Complex.h"
-#endif
-
-// Specializations of vectorized activation functions for NEON.
-#ifdef EIGEN_VECTORIZE_NEON
-#include "src/Core/arch/NEON/UnaryFunctors.h"
-#endif
-
-#include "src/Core/util/IndexedViewHelper.h"
-#include "src/Core/util/ReshapedHelper.h"
-#include "src/Core/ArithmeticSequence.h"
-#ifndef EIGEN_NO_IO
-#include "src/Core/IO.h"
-#endif
+#include "src/Core/Functors.h"
 #include "src/Core/DenseCoeffsBase.h"
 #include "src/Core/DenseBase.h"
 #include "src/Core/MatrixBase.h"
 #include "src/Core/EigenBase.h"
 
-#include "src/Core/Product.h"
-#include "src/Core/CoreEvaluators.h"
-#include "src/Core/AssignEvaluator.h"
-#include "src/Core/RealView.h"
-#include "src/Core/Assign.h"
+#ifndef EIGEN_PARSED_BY_DOXYGEN // work around Doxygen bug triggered by Assign.h r814874
+                                // at least confirmed with Doxygen 1.5.5 and 1.5.6
+  #include "src/Core/Assign.h"
+#endif
 
-#include "src/Core/ArrayBase.h"
 #include "src/Core/util/BlasUtil.h"
 #include "src/Core/DenseStorage.h"
 #include "src/Core/NestByValue.h"
-
+#include "src/Core/ForceAlignedAccess.h"
 #include "src/Core/ReturnByValue.h"
 #include "src/Core/NoAlias.h"
 #include "src/Core/PlainObjectBase.h"
 #include "src/Core/Matrix.h"
 #include "src/Core/Array.h"
-#include "src/Core/Fill.h"
-#include "src/Core/CwiseTernaryOp.h"
 #include "src/Core/CwiseBinaryOp.h"
 #include "src/Core/CwiseUnaryOp.h"
 #include "src/Core/CwiseNullaryOp.h"
 #include "src/Core/CwiseUnaryView.h"
 #include "src/Core/SelfCwiseBinaryOp.h"
-#include "src/Core/InnerProduct.h"
 #include "src/Core/Dot.h"
 #include "src/Core/StableNorm.h"
-#include "src/Core/Stride.h"
 #include "src/Core/MapBase.h"
+#include "src/Core/Stride.h"
 #include "src/Core/Map.h"
-#include "src/Core/Ref.h"
 #include "src/Core/Block.h"
 #include "src/Core/VectorBlock.h"
-#include "src/Core/IndexedView.h"
-#include "src/Core/Reshaped.h"
+#include "src/Core/Ref.h"
 #include "src/Core/Transpose.h"
 #include "src/Core/DiagonalMatrix.h"
 #include "src/Core/Diagonal.h"
 #include "src/Core/DiagonalProduct.h"
-#include "src/Core/SkewSymmetricMatrix3.h"
-#include "src/Core/Redux.h"
-#include "src/Core/Visitor.h"
-#include "src/Core/FindCoeff.h"
-#include "src/Core/Fuzzy.h"
-#include "src/Core/Swap.h"
-#include "src/Core/CommaInitializer.h"
-#include "src/Core/GeneralProduct.h"
-#include "src/Core/Solve.h"
-#include "src/Core/Inverse.h"
-#include "src/Core/SolverBase.h"
 #include "src/Core/PermutationMatrix.h"
 #include "src/Core/Transpositions.h"
+#include "src/Core/Redux.h"
+#include "src/Core/Visitor.h"
+#include "src/Core/Fuzzy.h"
+#include "src/Core/IO.h"
+#include "src/Core/Swap.h"
+#include "src/Core/CommaInitializer.h"
+#include "src/Core/Flagged.h"
+#include "src/Core/ProductBase.h"
+#include "src/Core/GeneralProduct.h"
 #include "src/Core/TriangularMatrix.h"
 #include "src/Core/SelfAdjointView.h"
 #include "src/Core/products/GeneralBlockPanelKernel.h"
-#include "src/Core/DeviceWrapper.h"
-#ifdef EIGEN_GEMM_THREADPOOL
-#include "ThreadPool"
-#endif
 #include "src/Core/products/Parallelizer.h"
-#include "src/Core/ProductEvaluators.h"
+#include "src/Core/products/CoeffBasedProduct.h"
 #include "src/Core/products/GeneralMatrixVector.h"
 #include "src/Core/products/GeneralMatrixMatrix.h"
 #include "src/Core/SolveTriangular.h"
@@ -419,55 +340,37 @@ using std::ptrdiff_t;
 #include "src/Core/products/TriangularSolverVector.h"
 #include "src/Core/BandMatrix.h"
 #include "src/Core/CoreIterators.h"
-#include "src/Core/ConditionEstimator.h"
-
-#if !defined(EIGEN_VECTORIZE_GENERIC)
-#if defined(EIGEN_VECTORIZE_VSX)
-#include "src/Core/arch/AltiVec/MatrixProduct.h"
-#elif defined EIGEN_VECTORIZE_NEON
-#include "src/Core/arch/NEON/GeneralBlockPanelKernel.h"
-#elif defined EIGEN_VECTORIZE_LSX
-#include "src/Core/arch/LSX/GeneralBlockPanelKernel.h"
-#elif defined EIGEN_VECTORIZE_RVV10
-#include "src/Core/arch/RVV10/GeneralBlockPanelKernel.h"
-#endif
-
-#if defined(EIGEN_VECTORIZE_AVX512)
-#include "src/Core/arch/AVX512/GemmKernel.h"
-#endif
-#endif
 
+#include "src/Core/BooleanRedux.h"
 #include "src/Core/Select.h"
 #include "src/Core/VectorwiseOp.h"
-#include "src/Core/PartialReduxEvaluator.h"
 #include "src/Core/Random.h"
 #include "src/Core/Replicate.h"
 #include "src/Core/Reverse.h"
+#include "src/Core/ArrayBase.h"
 #include "src/Core/ArrayWrapper.h"
-#include "src/Core/StlIterators.h"
 
 #ifdef EIGEN_USE_BLAS
-#include "src/Core/products/GeneralMatrixMatrix_BLAS.h"
-#include "src/Core/products/GeneralMatrixVector_BLAS.h"
-#include "src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h"
-#include "src/Core/products/SelfadjointMatrixMatrix_BLAS.h"
-#include "src/Core/products/SelfadjointMatrixVector_BLAS.h"
-#include "src/Core/products/TriangularMatrixMatrix_BLAS.h"
-#include "src/Core/products/TriangularMatrixVector_BLAS.h"
-#include "src/Core/products/TriangularSolverMatrix_BLAS.h"
-#endif  // EIGEN_USE_BLAS
+#include "src/Core/products/GeneralMatrixMatrix_MKL.h"
+#include "src/Core/products/GeneralMatrixVector_MKL.h"
+#include "src/Core/products/GeneralMatrixMatrixTriangular_MKL.h"
+#include "src/Core/products/SelfadjointMatrixMatrix_MKL.h"
+#include "src/Core/products/SelfadjointMatrixVector_MKL.h"
+#include "src/Core/products/TriangularMatrixMatrix_MKL.h"
+#include "src/Core/products/TriangularMatrixVector_MKL.h"
+#include "src/Core/products/TriangularSolverMatrix_MKL.h"
+#endif // EIGEN_USE_BLAS
 
 #ifdef EIGEN_USE_MKL_VML
 #include "src/Core/Assign_MKL.h"
 #endif
 
-#ifdef EIGEN_USE_AOCL_VML
-#include "src/Core/Assign_AOCL.h"
-#endif
-
 #include "src/Core/GlobalFunctions.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_CORE_MODULE_H
+#ifdef EIGEN2_SUPPORT
+#include "Eigen2Support"
+#endif
+
+#endif // EIGEN_CORE_H

Eigen/Dense

@@ -1,13 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_DENSE_MODULE_H
-#define EIGEN_DENSE_MODULE_H
-
 #include "Core"
 #include "LU"
 #include "Cholesky"
@@ -15,5 +5,3 @@
 #include "SVD"
 #include "Geometry"
 #include "Eigenvalues"
-
-#endif  // EIGEN_DENSE_MODULE_H

Eigen/Eigen

@@ -1,14 +1,2 @@
-// 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_EIGEN_MODULE_H
-#define EIGEN_EIGEN_MODULE_H
-
 #include "Dense"
-#include "Sparse"
-
-#endif  // EIGEN_EIGEN_MODULE_H
+//#include "Sparse"

Eigen/Eigen2Support

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

Eigen/Eigenvalues

@@ -1,35 +1,30 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_EIGENVALUES_MODULE_H
 #define EIGEN_EIGENVALUES_MODULE_H
 
 #include "Core"
 
-#include "Cholesky"
-#include "LU"
-#include "Geometry"
-#include "Sparse"  // Needed by ComplexQZ.
-
 #include "src/Core/util/DisableStupidWarnings.h"
 
-/** \defgroup Eigenvalues_Module Eigenvalues module
- *
- * This module mainly provides various eigenvalue solvers.
- * This module also provides some MatrixBase methods, including:
- *  - MatrixBase::eigenvalues(),
- *  - MatrixBase::operatorNorm()
- *
- * \code
- * #include <Eigen/Eigenvalues>
- * \endcode
- */
+#include "Cholesky"
+#include "Jacobi"
+#include "Householder"
+#include "LU"
+#include "Geometry"
+
+/** \defgroup Eigenvalues_Module Eigenvalues module
+  *
+  *
+  *
+  * This module mainly provides various eigenvalue solvers.
+  * This module also provides some MatrixBase methods, including:
+  *  - MatrixBase::eigenvalues(),
+  *  - MatrixBase::operatorNorm()
+  *
+  * \code
+  * #include <Eigen/Eigenvalues>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
 #include "src/Eigenvalues/Tridiagonalization.h"
 #include "src/Eigenvalues/RealSchur.h"
 #include "src/Eigenvalues/EigenSolver.h"
@@ -39,23 +34,15 @@
 #include "src/Eigenvalues/ComplexSchur.h"
 #include "src/Eigenvalues/ComplexEigenSolver.h"
 #include "src/Eigenvalues/RealQZ.h"
-#include "src/Eigenvalues/ComplexQZ.h"
 #include "src/Eigenvalues/GeneralizedEigenSolver.h"
 #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
 #ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#elif defined(EIGEN_LAPACKE_SYSTEM)
-#include <lapacke.h>
-#else
-#include "src/misc/lapacke.h"
+#include "src/Eigenvalues/RealSchur_MKL.h"
+#include "src/Eigenvalues/ComplexSchur_MKL.h"
+#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h"
 #endif
-#include "src/Eigenvalues/RealSchur_LAPACKE.h"
-#include "src/Eigenvalues/ComplexSchur_LAPACKE.h"
-#include "src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h"
-#endif
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_EIGENVALUES_MODULE_H
+#endif // EIGEN_EIGENVALUES_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/GPU

@@ -1,55 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_GPU_MODULE_H
-#define EIGEN_GPU_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup GPU_Module GPU module
- *
- * GPU-accelerated solvers and operations using NVIDIA CUDA libraries
- * (cuSOLVER, cuBLAS, cuSPARSE, cuFFT, cuDSS).
- *
- * This module provides explicit GPU solver classes that coexist with Eigen's
- * CPU solvers. Unlike the LAPACKE dispatch (which replaces the CPU
- * implementation globally), GPU classes are separate types the user
- * instantiates by choice:
- *
- * \code
- * #define EIGEN_USE_GPU
- * #include <Eigen/GPU>
- *
- * // CPU path (unchanged)
- * Eigen::LLT<Eigen::MatrixXd> llt_cpu(A);
- *
- * // GPU path (explicit)
- * Eigen::GpuLLT<double> llt_gpu(A);   // L stays on device
- * auto X = llt_gpu.solve(B);          // only B transferred per solve
- * \endcode
- *
- * Requires CUDA 11.4+. See CLAUDE.md.
- */
-
-#ifdef EIGEN_USE_GPU
-// IWYU pragma: begin_exports
-#include "src/GPU/DeviceMatrix.h"
-#include "src/GPU/GpuContext.h"
-#include "src/GPU/DeviceExpr.h"
-#include "src/GPU/DeviceBlasExpr.h"
-#include "src/GPU/DeviceSolverExpr.h"
-#include "src/GPU/DeviceDispatch.h"
-#include "src/GPU/GpuLLT.h"
-#include "src/GPU/GpuLU.h"
-// IWYU pragma: end_exports
-#endif
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_GPU_MODULE_H

Eigen/Geometry

@@ -1,61 +1,63 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_GEOMETRY_MODULE_H
 #define EIGEN_GEOMETRY_MODULE_H
 
 #include "Core"
 
-#include "SVD"
-#include "LU"
-
 #include "src/Core/util/DisableStupidWarnings.h"
 
-/** \defgroup Geometry_Module Geometry module
- *
- * This module provides support for:
- *  - fixed-size homogeneous transformations
- *  - translation, scaling, 2D and 3D rotations
- *  - \link Quaternion quaternions \endlink
- *  - cross products (\ref MatrixBase::cross(), \ref MatrixBase::cross3())
- *  - orthogonal vector generation (MatrixBase::unitOrthogonal)
- *  - some linear components: \link ParametrizedLine parametrized-lines \endlink and \link Hyperplane hyperplanes \endlink
- *  - \link AlignedBox axis aligned bounding boxes \endlink
- *  - \link umeyama() least-square transformation fitting \endlink
- * \code
- * #include <Eigen/Geometry>
- * \endcode
- */
+#include "SVD"
+#include "LU"
+#include <limits>
+
+#ifndef M_PI
+#define M_PI 3.14159265358979323846
+#endif
+
+/** \defgroup Geometry_Module Geometry module
+  *
+  *
+  *
+  * This module provides support for:
+  *  - fixed-size homogeneous transformations
+  *  - translation, scaling, 2D and 3D rotations
+  *  - quaternions
+  *  - \ref MatrixBase::cross() "cross product"
+  *  - \ref MatrixBase::unitOrthogonal() "orthognal vector generation"
+  *  - some linear components: parametrized-lines and hyperplanes
+  *
+  * \code
+  * #include <Eigen/Geometry>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
 #include "src/Geometry/OrthoMethods.h"
 #include "src/Geometry/EulerAngles.h"
-#include "src/Geometry/Homogeneous.h"
-#include "src/Geometry/RotationBase.h"
-#include "src/Geometry/Rotation2D.h"
-#include "src/Geometry/Quaternion.h"
-#include "src/Geometry/AngleAxis.h"
-#include "src/Geometry/Transform.h"
-#include "src/Geometry/Translation.h"
-#include "src/Geometry/Scaling.h"
-#include "src/Geometry/Hyperplane.h"
-#include "src/Geometry/ParametrizedLine.h"
-#include "src/Geometry/AlignedBox.h"
-#include "src/Geometry/Umeyama.h"
 
-#ifndef EIGEN_VECTORIZE_GENERIC
-// TODO(rmlarsen): Make these work with generic vectorization if possible.
-// Use the SSE optimized version whenever possible.
-#if (defined EIGEN_VECTORIZE_SSE) || (defined EIGEN_VECTORIZE_NEON)
-#include "src/Geometry/arch/Geometry_SIMD.h"
+#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
+  #include "src/Geometry/Homogeneous.h"
+  #include "src/Geometry/RotationBase.h"
+  #include "src/Geometry/Rotation2D.h"
+  #include "src/Geometry/Quaternion.h"
+  #include "src/Geometry/AngleAxis.h"
+  #include "src/Geometry/Transform.h"
+  #include "src/Geometry/Translation.h"
+  #include "src/Geometry/Scaling.h"
+  #include "src/Geometry/Hyperplane.h"
+  #include "src/Geometry/ParametrizedLine.h"
+  #include "src/Geometry/AlignedBox.h"
+  #include "src/Geometry/Umeyama.h"
+
+  #if defined EIGEN_VECTORIZE_SSE
+    #include "src/Geometry/arch/Geometry_SSE.h"
+  #endif
 #endif
+
+#ifdef EIGEN2_SUPPORT
+#include "src/Eigen2Support/Geometry/All.h"
 #endif
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_GEOMETRY_MODULE_H
+#endif // EIGEN_GEOMETRY_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */
+

Eigen/Householder

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_HOUSEHOLDER_MODULE_H
 #define EIGEN_HOUSEHOLDER_MODULE_H
 
@@ -13,19 +6,18 @@
 #include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup Householder_Module Householder module
- * This module provides Householder transformations.
- *
- * \code
- * #include <Eigen/Householder>
- * \endcode
- */
+  * This module provides Householder transformations.
+  *
+  * \code
+  * #include <Eigen/Householder>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
 #include "src/Householder/Householder.h"
-#include "src/Householder/BlockHouseholder.h"
 #include "src/Householder/HouseholderSequence.h"
-// IWYU pragma: end_exports
+#include "src/Householder/BlockHouseholder.h"
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_HOUSEHOLDER_MODULE_H
+#endif // EIGEN_HOUSEHOLDER_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/IterativeLinearSolvers

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
 #define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
 
@@ -13,40 +6,35 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-/**
+/** 
   * \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module
   *
-  * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a
-  squared matrix, usually very large and sparse.
+  * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
   * Those solvers are accessible via the following classes:
   *  - ConjugateGradient for selfadjoint (hermitian) matrices,
-  *  - LeastSquaresConjugateGradient for rectangular least-square problems,
   *  - BiCGSTAB for general square matrices.
   *
   * These iterative solvers are associated with some preconditioners:
   *  - IdentityPreconditioner - not really useful
-  *  - DiagonalPreconditioner - also called Jacobi preconditioner, work very well on diagonal dominant matrices.
-  *  - IncompleteLUT - incomplete LU factorization with dual thresholding
+  *  - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices.
+  *  - IncompleteILUT - incomplete LU factorization with dual thresholding
   *
-  * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport,
-  UmfPackSupport, SuperLUSupport, AccelerateSupport.
+  * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
   *
-    \code
-    #include <Eigen/IterativeLinearSolvers>
-    \endcode
+  * \code
+  * #include <Eigen/IterativeLinearSolvers>
+  * \endcode
   */
 
-// IWYU pragma: begin_exports
-#include "src/IterativeLinearSolvers/SolveWithGuess.h"
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
 #include "src/IterativeLinearSolvers/IterativeSolverBase.h"
 #include "src/IterativeLinearSolvers/BasicPreconditioners.h"
 #include "src/IterativeLinearSolvers/ConjugateGradient.h"
-#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h"
 #include "src/IterativeLinearSolvers/BiCGSTAB.h"
 #include "src/IterativeLinearSolvers/IncompleteLUT.h"
-#include "src/IterativeLinearSolvers/IncompleteCholesky.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
+#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H

Eigen/Jacobi

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_JACOBI_MODULE_H
 #define EIGEN_JACOBI_MODULE_H
 
@@ -13,21 +6,21 @@
 #include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup Jacobi_Module Jacobi module
- * This module provides Jacobi and Givens rotations.
- *
- * \code
- * #include <Eigen/Jacobi>
- * \endcode
- *
- * In addition to listed classes, it defines the two following MatrixBase methods to apply a Jacobi or Givens rotation:
- *  - MatrixBase::applyOnTheLeft()
- *  - MatrixBase::applyOnTheRight().
- */
+  * This module provides Jacobi and Givens rotations.
+  *
+  * \code
+  * #include <Eigen/Jacobi>
+  * \endcode
+  *
+  * In addition to listed classes, it defines the two following MatrixBase methods to apply a Jacobi or Givens rotation:
+  *  - MatrixBase::applyOnTheLeft()
+  *  - MatrixBase::applyOnTheRight().
+  */
 
-// IWYU pragma: begin_exports
 #include "src/Jacobi/Jacobi.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_JACOBI_MODULE_H
+#endif // EIGEN_JACOBI_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */
+

Eigen/KLUSupport

@@ -1,43 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_KLUSUPPORT_MODULE_H
-#define EIGEN_KLUSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-#include <btf.h>
-#include <klu.h>
-}
-
-/** \ingroup Support_modules
- * \defgroup KLUSupport_Module KLUSupport module
- *
- * This module provides an interface to the KLU library which is part of the <a
- * href="http://www.suitesparse.com">suitesparse</a> package. It provides the following factorization class:
- * - class KLU: a sparse LU factorization, well-suited for circuit simulation.
- *
- * \code
- * #include <Eigen/KLUSupport>
- * \endcode
- *
- * In order to use this module, the klu and btf headers must be accessible from the include paths, and your binary must
- * be linked to the klu library and its dependencies. The dependencies depend on how KLU has been compiled. For a
- * cmake based project, you can use our FindKLU.cmake module to help you in this task.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/KLUSupport/KLUSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_KLUSUPPORT_MODULE_H

Eigen/LU

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_LU_MODULE_H
 #define EIGEN_LU_MODULE_H
 
@@ -13,37 +6,36 @@
 #include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup LU_Module LU module
- * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
- * This module defines the following MatrixBase methods:
- *  - MatrixBase::inverse()
- *  - MatrixBase::determinant()
- *
- * \code
- * #include <Eigen/LU>
- * \endcode
- */
+  * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
+  * This module defines the following MatrixBase methods:
+  *  - MatrixBase::inverse()
+  *  - MatrixBase::determinant()
+  *
+  * \code
+  * #include <Eigen/LU>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
+#include "src/misc/Solve.h"
 #include "src/misc/Kernel.h"
 #include "src/misc/Image.h"
-#include "src/misc/RankRevealingBase.h"
 #include "src/LU/FullPivLU.h"
 #include "src/LU/PartialPivLU.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/misc/lapacke_helpers.h"
-#include "src/LU/PartialPivLU_LAPACKE.h"
+#include "src/LU/PartialPivLU_MKL.h"
 #endif
 #include "src/LU/Determinant.h"
-#include "src/LU/InverseImpl.h"
+#include "src/LU/Inverse.h"
 
-#ifndef EIGEN_VECTORIZE_GENERIC
-// TODO(rmlarsen): Make these work with generic vectorization if possible.
-#if defined EIGEN_VECTORIZE_SSE || defined EIGEN_VECTORIZE_NEON
-#include "src/LU/arch/InverseSize4.h"
+#if defined EIGEN_VECTORIZE_SSE
+  #include "src/LU/arch/Inverse_SSE.h"
 #endif
+
+#ifdef EIGEN2_SUPPORT
+  #include "src/Eigen2Support/LU.h"
 #endif
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_LU_MODULE_H
+#endif // EIGEN_LU_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/LeastSquares

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

Eigen/MetisSupport

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_METISSUPPORT_MODULE_H
 #define EIGEN_METISSUPPORT_MODULE_H
 
@@ -16,20 +9,20 @@ extern "C" {
 #include <metis.h>
 }
 
-/** \ingroup Support_modules
- * \defgroup MetisSupport_Module MetisSupport module
- *
- * \code
- * #include <Eigen/MetisSupport>
- * \endcode
- * This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis).
- * It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink
- */
 
-// IWYU pragma: begin_exports
+/** \ingroup Support_modules
+  * \defgroup MetisSupport_Module MetisSupport module
+  *
+  * \code
+  * #include <Eigen/MetisSupport>
+  * \endcode
+  * This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis). 
+  * It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink
+  */
+
+
 #include "src/MetisSupport/MetisSupport.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_METISSUPPORT_MODULE_H
+#endif // EIGEN_METISSUPPORT_MODULE_H

Eigen/OrderingMethods

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_ORDERINGMETHODS_MODULE_H
 #define EIGEN_ORDERINGMETHODS_MODULE_H
 
@@ -12,62 +5,62 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-/**
- * \defgroup OrderingMethods_Module OrderingMethods module
- *
- * This module is currently for internal use only
- *
- * It defines various built-in and external ordering methods for sparse matrices.
- * They are typically used to reduce the number of elements during
- * the sparse matrix decomposition (LLT, LU, QR).
- * Precisely, in a preprocessing step, a permutation matrix P is computed using
- * those ordering methods and applied to the columns of the matrix.
- * Using for instance the sparse Cholesky decomposition, it is expected that
- * the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A).
- *
- *
- * Usage :
- * \code
- * #include <Eigen/OrderingMethods>
- * \endcode
- *
- * A simple usage is as a template parameter in the sparse decomposition classes :
- *
- * \code
- * SparseLU<MatrixType, COLAMDOrdering<int> > solver;
- * \endcode
- *
- * \code
- * SparseQR<MatrixType, COLAMDOrdering<int> > solver;
- * \endcode
- *
- * It is possible as well to call directly a particular ordering method for your own purpose,
- * \code
- * AMDOrdering<int> ordering;
- * PermutationMatrix<Dynamic, Dynamic, int> perm;
- * SparseMatrix<double> A;
- * //Fill the matrix ...
- *
- * ordering(A, perm); // Call AMD
- * \endcode
- *
- * \note Some of these methods (like AMD or METIS), need the sparsity pattern
- * of the input matrix to be symmetric. When the matrix is structurally unsymmetric,
- * Eigen computes internally the pattern of \f$A^T*A\f$ before calling the method.
- * If your matrix is already symmetric (at least in structure), you can avoid that
- * by calling the method with a SelfAdjointView type.
- *
- * \code
- *  // Call the ordering on the pattern of the lower triangular matrix A
- * ordering(A.selfadjointView<Lower>(), perm);
- * \endcode
- */
+/** 
+  * \defgroup OrderingMethods_Module OrderingMethods module
+  *
+  * This module is currently for internal use only
+  * 
+  * It defines various built-in and external ordering methods for sparse matrices. 
+  * They are typically used to reduce the number of elements during 
+  * the sparse matrix decomposition (LLT, LU, QR).
+  * Precisely, in a preprocessing step, a permutation matrix P is computed using 
+  * those ordering methods and applied to the columns of the matrix. 
+  * Using for instance the sparse Cholesky decomposition, it is expected that 
+  * the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A).
+  * 
+  * 
+  * Usage : 
+  * \code
+  * #include <Eigen/OrderingMethods>
+  * \endcode
+  * 
+  * A simple usage is as a template parameter in the sparse decomposition classes : 
+  * 
+  * \code 
+  * SparseLU<MatrixType, COLAMDOrdering<int> > solver;
+  * \endcode 
+  * 
+  * \code 
+  * SparseQR<MatrixType, COLAMDOrdering<int> > solver;
+  * \endcode
+  * 
+  * It is possible as well to call directly a particular ordering method for your own purpose, 
+  * \code 
+  * AMDOrdering<int> ordering;
+  * PermutationMatrix<Dynamic, Dynamic, int> perm;
+  * SparseMatrix<double> A; 
+  * //Fill the matrix ...
+  * 
+  * ordering(A, perm); // Call AMD
+  * \endcode
+  * 
+  * \note Some of these methods (like AMD or METIS), need the sparsity pattern 
+  * of the input matrix to be symmetric. When the matrix is structurally unsymmetric, 
+  * Eigen computes internally the pattern of \f$A^T*A\f$ before calling the method.
+  * If your matrix is already symmetric (at leat in structure), you can avoid that
+  * by calling the method with a SelfAdjointView type.
+  * 
+  * \code
+  *  // Call the ordering on the pattern of the lower triangular matrix A
+  * ordering(A.selfadjointView<Lower>(), perm);
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
+#ifndef EIGEN_MPL2_ONLY
 #include "src/OrderingMethods/Amd.h"
-#include "src/OrderingMethods/Ordering.h"
-// IWYU pragma: end_exports
+#endif
 
+#include "src/OrderingMethods/Ordering.h"
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_ORDERINGMETHODS_MODULE_H
+#endif // EIGEN_ORDERINGMETHODS_MODULE_H

Eigen/PaStiXSupport

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_PASTIXSUPPORT_MODULE_H
 #define EIGEN_PASTIXSUPPORT_MODULE_H
 
@@ -12,6 +5,7 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
+#include <complex.h>
 extern "C" {
 #include <pastix_nompi.h>
 #include <pastix.h>
@@ -22,30 +16,31 @@ extern "C" {
 #endif
 
 /** \ingroup Support_modules
- * \defgroup PaStiXSupport_Module PaStiXSupport module
- *
- * This module provides an interface to the <a href="http://pastix.gforge.inria.fr/">PaSTiX</a> library.
- * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver.
- * It provides the two following main factorization classes:
- * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization.
- * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization.
- * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern).
- *
- * \code
- * #include <Eigen/PaStiXSupport>
- * \endcode
- *
- * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be
- * linked to the PaSTiX library and its dependencies. This wrapper requires PaStiX version 5.x compiled without MPI
- * support. The dependencies depend on how PaSTiX has been compiled. For a cmake based project, you can use our
- * FindPaSTiX.cmake module to help you in this task.
- *
- */
+  * \defgroup PaStiXSupport_Module PaStiXSupport module
+  * 
+  * This module provides an interface to the <a href="http://pastix.gforge.inria.fr/">PaSTiX</a> library.
+  * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver.
+  * It provides the two following main factorization classes:
+  * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization.
+  * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization.
+  * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern).
+  * 
+  * \code
+  * #include <Eigen/PaStiXSupport>
+  * \endcode
+  *
+  * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be linked to the PaSTiX library and its dependencies.
+  * The dependencies depend on how PaSTiX has been compiled.
+  * For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
-// IWYU pragma: begin_exports
 #include "src/PaStiXSupport/PaStiXSupport.h"
-// IWYU pragma: end_exports
+
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_PASTIXSUPPORT_MODULE_H
+#endif // EIGEN_PASTIXSUPPORT_MODULE_H

Eigen/PardisoSupport

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_PARDISOSUPPORT_MODULE_H
 #define EIGEN_PARDISOSUPPORT_MODULE_H
 
@@ -14,25 +7,24 @@
 
 #include <mkl_pardiso.h>
 
-/** \ingroup Support_modules
- * \defgroup PardisoSupport_Module PardisoSupport module
- *
- * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers.
- *
- * \code
- * #include <Eigen/PardisoSupport>
- * \endcode
- *
- * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be
- * linked to the MKL library and its dependencies. See this \ref TopicUsingIntelMKL "page" for more information on
- * MKL-Eigen integration.
- *
- */
+#include <unsupported/Eigen/SparseExtra>
+
+/** \ingroup Support_modules
+  * \defgroup PardisoSupport_Module PardisoSupport module
+  *
+  * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers.
+  *
+  * \code
+  * #include <Eigen/PardisoSupport>
+  * \endcode
+  *
+  * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be linked to the MKL library and its dependencies.
+  * See this \ref TopicUsingIntelMKL "page" for more information on MKL-Eigen integration.
+  * 
+  */
 
-// IWYU pragma: begin_exports
 #include "src/PardisoSupport/PardisoSupport.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_PARDISOSUPPORT_MODULE_H
+#endif // EIGEN_PARDISOSUPPORT_MODULE_H

Eigen/QR

@@ -1,47 +1,45 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_QR_MODULE_H
 #define EIGEN_QR_MODULE_H
 
 #include "Core"
 
-#include "Cholesky"
-#include "Householder"
-
 #include "src/Core/util/DisableStupidWarnings.h"
 
+#include "Cholesky"
+#include "Jacobi"
+#include "Householder"
+
 /** \defgroup QR_Module QR module
- *
- * This module provides various QR decompositions
- * This module also provides some MatrixBase methods, including:
- *  - MatrixBase::householderQr()
- *  - MatrixBase::colPivHouseholderQr()
- *  - MatrixBase::fullPivHouseholderQr()
- *
- * \code
- * #include <Eigen/QR>
- * \endcode
- */
+  *
+  *
+  *
+  * This module provides various QR decompositions
+  * This module also provides some MatrixBase methods, including:
+  *  - MatrixBase::qr(),
+  *
+  * \code
+  * #include <Eigen/QR>
+  * \endcode
+  */
 
-#include "src/misc/RankRevealingBase.h"
-
-// IWYU pragma: begin_exports
+#include "src/misc/Solve.h"
 #include "src/QR/HouseholderQR.h"
 #include "src/QR/FullPivHouseholderQR.h"
 #include "src/QR/ColPivHouseholderQR.h"
-#include "src/QR/CompleteOrthogonalDecomposition.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/misc/lapacke_helpers.h"
-#include "src/QR/HouseholderQR_LAPACKE.h"
-#include "src/QR/ColPivHouseholderQR_LAPACKE.h"
+#include "src/QR/HouseholderQR_MKL.h"
+#include "src/QR/ColPivHouseholderQR_MKL.h"
+#endif
+
+#ifdef EIGEN2_SUPPORT
+#include "src/Eigen2Support/QR.h"
 #endif
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_QR_MODULE_H
+#ifdef EIGEN2_SUPPORT
+#include "Eigenvalues"
+#endif
+
+#endif // EIGEN_QR_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/QtAlignedMalloc

@@ -1,9 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_QTMALLOC_MODULE_H
 #define EIGEN_QTMALLOC_MODULE_H
@@ -14,13 +8,20 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-inline void *qMalloc(std::size_t size) { return Eigen::internal::aligned_malloc(size); }
+void *qMalloc(size_t size)
+{
+  return Eigen::internal::aligned_malloc(size);
+}
 
-inline void qFree(void *ptr) { Eigen::internal::aligned_free(ptr); }
+void qFree(void *ptr)
+{
+  Eigen::internal::aligned_free(ptr);
+}
 
-inline void *qRealloc(void *ptr, std::size_t size) {
-  void *newPtr = Eigen::internal::aligned_malloc(size);
-  std::memcpy(newPtr, ptr, size);
+void *qRealloc(void *ptr, size_t size)
+{
+  void* newPtr = Eigen::internal::aligned_malloc(size);
+  memcpy(newPtr, ptr, size);
   Eigen::internal::aligned_free(ptr);
   return newPtr;
 }
@@ -29,4 +30,5 @@ inline void *qRealloc(void *ptr, std::size_t size) {
 
 #endif
 
-#endif  // EIGEN_QTMALLOC_MODULE_H
+#endif // EIGEN_QTMALLOC_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/SPQRSupport

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SPQRSUPPORT_MODULE_H
 #define EIGEN_SPQRSUPPORT_MODULE_H
 
@@ -15,27 +8,22 @@
 #include "SuiteSparseQR.hpp"
 
 /** \ingroup Support_modules
- * \defgroup SPQRSupport_Module SuiteSparseQR module
- *
- * This module provides an interface to the SPQR library, which is part of the <a
- * href="http://www.suitesparse.com">suitesparse</a> package.
- *
- * \code
- * #include <Eigen/SPQRSupport>
- * \endcode
- *
- * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be
- * linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...). For a cmake based project, you can use
- * our FindSPQR.cmake and FindCholmod.Cmake modules
- *
- */
+  * \defgroup SPQRSupport_Module SuiteSparseQR module
+  * 
+  * This module provides an interface to the SPQR library, which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
+  *
+  * \code
+  * #include <Eigen/SPQRSupport>
+  * \endcode
+  *
+  * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...).
+  * For a cmake based project, you can use our FindSPQR.cmake and FindCholmod.Cmake modules
+  *
+  */
 
-#include "CholmodSupport"
-
-// IWYU pragma: begin_exports
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+#include "src/CholmodSupport/CholmodSupport.h"
 #include "src/SPQRSupport/SuiteSparseQRSupport.h"
-// IWYU pragma: end_exports
 
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_SPQRSUPPORT_MODULE_H
+#endif

Eigen/SVD

@@ -1,53 +1,37 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SVD_MODULE_H
 #define EIGEN_SVD_MODULE_H
 
 #include "QR"
+#include "Householder"
+#include "Jacobi"
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup SVD_Module SVD module
- *
- * This module provides SVD decomposition for matrices (both real and complex).
- * Two decomposition algorithms are provided:
- *  - JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very
- * slow for larger ones.
- *  - BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast
- * for large problems. These decompositions are accessible via the respective classes and following MatrixBase methods:
- *  - MatrixBase::jacobiSvd()
- *  - MatrixBase::bdcSvd()
- *
- * \code
- * #include <Eigen/SVD>
- * \endcode
- */
+  *
+  *
+  *
+  * This module provides SVD decomposition for matrices (both real and complex).
+  * This decomposition is accessible via the following MatrixBase method:
+  *  - MatrixBase::jacobiSvd()
+  *
+  * \code
+  * #include <Eigen/SVD>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
-#include "src/SVD/UpperBidiagonalization.h"
-#include "src/SVD/SVDBase.h"
+#include "src/misc/Solve.h"
 #include "src/SVD/JacobiSVD.h"
-#include "src/SVD/BDCSVD.h"
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#elif defined(EIGEN_LAPACKE_SYSTEM)
-#include <lapacke.h>
-#else
-#include "src/misc/lapacke.h"
+#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
+#include "src/SVD/JacobiSVD_MKL.h"
 #endif
-#ifndef EIGEN_USE_LAPACKE_STRICT
-#include "src/SVD/JacobiSVD_LAPACKE.h"
+#include "src/SVD/UpperBidiagonalization.h"
+
+#ifdef EIGEN2_SUPPORT
+#include "src/Eigen2Support/SVD.h"
 #endif
-#include "src/SVD/BDCSVD_LAPACKE.h"
-#endif
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_SVD_MODULE_H
+#endif // EIGEN_SVD_MODULE_H
+/* vim: set filetype=cpp et sw=2 ts=2 ai: */

Eigen/Sparse

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SPARSE_MODULE_H
 #define EIGEN_SPARSE_MODULE_H
 
@@ -18,9 +11,9 @@
   * - \ref SparseQR_Module
   * - \ref IterativeLinearSolvers_Module
   *
-    \code
-    #include <Eigen/Sparse>
-    \endcode
+  * \code
+  * #include <Eigen/Sparse>
+  * \endcode
   */
 
 #include "SparseCore"
@@ -30,4 +23,5 @@
 #include "SparseQR"
 #include "IterativeLinearSolvers"
 
-#endif  // EIGEN_SPARSE_MODULE_H
+#endif // EIGEN_SPARSE_MODULE_H
+

Eigen/SparseCholesky

@@ -15,26 +15,33 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-/**
- * \defgroup SparseCholesky_Module SparseCholesky module
- *
- * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian)
- * matrices. Those decompositions are accessible via the following classes:
- *  - SimplicialLLt,
- *  - SimplicialLDLt
- *
- * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
- *
- * \code
- * #include <Eigen/SparseCholesky>
- * \endcode
- */
+/** 
+  * \defgroup SparseCholesky_Module SparseCholesky module
+  *
+  * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) matrices.
+  * Those decompositions are accessible via the following classes:
+  *  - SimplicialLLt,
+  *  - SimplicialLDLt
+  *
+  * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
+  *
+  * \code
+  * #include <Eigen/SparseCholesky>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
+#ifdef EIGEN_MPL2_ONLY
+#error The SparseCholesky module has nothing to offer in MPL2 only mode
+#endif
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 #include "src/SparseCholesky/SimplicialCholesky.h"
+
+#ifndef EIGEN_MPL2_ONLY
 #include "src/SparseCholesky/SimplicialCholesky_impl.h"
-// IWYU pragma: end_exports
+#endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_SPARSECHOLESKY_MODULE_H
+#endif // EIGEN_SPARSECHOLESKY_MODULE_H

Eigen/SparseCore

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SPARSECORE_MODULE_H
 #define EIGEN_SPARSECORE_MODULE_H
 
@@ -12,55 +5,60 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
+#include <vector>
 #include <map>
-#include <numeric>
+#include <cstdlib>
+#include <cstring>
+#include <algorithm>
 
-/**
- * \defgroup SparseCore_Module SparseCore module
- *
- * This module provides a sparse matrix representation, and basic associated matrix manipulations
- * and operations.
- *
- * See the \ref TutorialSparse "Sparse tutorial"
- *
- * \code
- * #include <Eigen/SparseCore>
- * \endcode
- *
- * This module depends on: Core.
- */
+/** 
+  * \defgroup SparseCore_Module SparseCore module
+  *
+  * This module provides a sparse matrix representation, and basic associated matrix manipulations
+  * and operations.
+  *
+  * See the \ref TutorialSparse "Sparse tutorial"
+  *
+  * \code
+  * #include <Eigen/SparseCore>
+  * \endcode
+  *
+  * This module depends on: Core.
+  */
+
+namespace Eigen {
+
+/** The type used to identify a general sparse storage. */
+struct Sparse {};
+
+}
 
-// IWYU pragma: begin_exports
 #include "src/SparseCore/SparseUtil.h"
 #include "src/SparseCore/SparseMatrixBase.h"
-#include "src/SparseCore/SparseAssign.h"
 #include "src/SparseCore/CompressedStorage.h"
 #include "src/SparseCore/AmbiVector.h"
-#include "src/SparseCore/SparseCompressedBase.h"
 #include "src/SparseCore/SparseMatrix.h"
-#include "src/SparseCore/SparseMap.h"
+#include "src/SparseCore/MappedSparseMatrix.h"
 #include "src/SparseCore/SparseVector.h"
-#include "src/SparseCore/SparseRef.h"
+#include "src/SparseCore/SparseBlock.h"
+#include "src/SparseCore/SparseTranspose.h"
 #include "src/SparseCore/SparseCwiseUnaryOp.h"
 #include "src/SparseCore/SparseCwiseBinaryOp.h"
-#include "src/SparseCore/SparseTranspose.h"
-#include "src/SparseCore/SparseBlock.h"
 #include "src/SparseCore/SparseDot.h"
+#include "src/SparseCore/SparsePermutation.h"
 #include "src/SparseCore/SparseRedux.h"
-#include "src/SparseCore/SparseView.h"
-#include "src/SparseCore/SparseDiagonalProduct.h"
+#include "src/SparseCore/SparseFuzzy.h"
 #include "src/SparseCore/ConservativeSparseSparseProduct.h"
 #include "src/SparseCore/SparseSparseProductWithPruning.h"
 #include "src/SparseCore/SparseProduct.h"
 #include "src/SparseCore/SparseDenseProduct.h"
-#include "src/SparseCore/SparseSelfAdjointView.h"
+#include "src/SparseCore/SparseDiagonalProduct.h"
 #include "src/SparseCore/SparseTriangularView.h"
+#include "src/SparseCore/SparseSelfAdjointView.h"
 #include "src/SparseCore/TriangularSolver.h"
-#include "src/SparseCore/SparsePermutation.h"
-#include "src/SparseCore/SparseFuzzy.h"
-#include "src/SparseCore/SparseSolverBase.h"
-// IWYU pragma: end_exports
+#include "src/SparseCore/SparseView.h"
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_SPARSECORE_MODULE_H
+#endif // EIGEN_SPARSECORE_MODULE_H
+

Eigen/SparseLU

@@ -13,19 +13,21 @@
 
 #include "SparseCore"
 
-/**
- * \defgroup SparseLU_Module SparseLU module
- * This module defines a supernodal factorization of general sparse matrices.
- * The code is fully optimized for supernode-panel updates with specialized kernels.
- * Please, see the documentation of the SparseLU class for more details.
- */
+/** 
+  * \defgroup SparseLU_Module SparseLU module
+  * This module defines a supernodal factorization of general sparse matrices.
+  * The code is fully optimized for supernode-panel updates with specialized kernels.
+  * Please, see the documentation of the SparseLU class for more details.
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
 // Ordering interface
 #include "OrderingMethods"
 
-#include "src/Core/util/DisableStupidWarnings.h"
+#include "src/SparseLU/SparseLU_gemm_kernel.h"
 
-// IWYU pragma: begin_exports
 #include "src/SparseLU/SparseLU_Structs.h"
 #include "src/SparseLU/SparseLU_SupernodalMatrix.h"
 #include "src/SparseLU/SparseLUImpl.h"
@@ -43,8 +45,5 @@
 #include "src/SparseLU/SparseLU_pruneL.h"
 #include "src/SparseLU/SparseLU_Utils.h"
 #include "src/SparseLU/SparseLU.h"
-// IWYU pragma: end_exports
 
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_SPARSELU_MODULE_H
+#endif // EIGEN_SPARSELU_MODULE_H

Eigen/SparseQR

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SPARSEQR_MODULE_H
 #define EIGEN_SPARSEQR_MODULE_H
 
@@ -13,26 +6,28 @@
 #include "src/Core/util/DisableStupidWarnings.h"
 
 /** \defgroup SparseQR_Module SparseQR module
- * \brief Provides QR decomposition for sparse matrices
- *
- * This module provides a simplicial version of the left-looking Sparse QR decomposition.
- * The columns of the input matrix should be reordered to limit the fill-in during the
- * decomposition. Built-in methods (COLAMD, AMD) or external  methods (METIS) can be used to this end.
- * See the \link OrderingMethods_Module OrderingMethods\endlink module for the list
- * of built-in and external ordering methods.
- *
- * \code
- * #include <Eigen/SparseQR>
- * \endcode
- *
- *
- */
+  * \brief Provides QR decomposition for sparse matrices
+  * 
+  * This module provides a simplicial version of the left-looking Sparse QR decomposition. 
+  * The columns of the input matrix should be reordered to limit the fill-in during the 
+  * decomposition. Built-in methods (COLAMD, AMD) or external  methods (METIS) can be used to this end.
+  * See the \link OrderingMethods_Module OrderingMethods\endlink module for the list 
+  * of built-in and external ordering methods.
+  * 
+  * \code
+  * #include <Eigen/SparseQR>
+  * \endcode
+  * 
+  * 
+  */
 
-// IWYU pragma: begin_exports
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "OrderingMethods"
 #include "src/SparseCore/SparseColEtree.h"
 #include "src/SparseQR/SparseQR.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_SPARSEQR_MODULE_H
+#endif

Eigen/StdDeque

@@ -14,17 +14,14 @@
 #include "Core"
 #include <deque>
 
-#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \
-    (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
+#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
 
 #define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...)
 
 #else
 
-// IWYU pragma: begin_exports
 #include "src/StlSupport/StdDeque.h"
-// IWYU pragma: end_exports
 
 #endif
 
-#endif  // EIGEN_STDDEQUE_MODULE_H
+#endif // EIGEN_STDDEQUE_MODULE_H

Eigen/StdList

@@ -13,17 +13,14 @@
 #include "Core"
 #include <list>
 
-#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \
-    (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
+#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */    
 
 #define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...)
 
 #else
 
-// IWYU pragma: begin_exports
 #include "src/StlSupport/StdList.h"
-// IWYU pragma: end_exports
 
 #endif
 
-#endif  // EIGEN_STDLIST_MODULE_H
+#endif // EIGEN_STDLIST_MODULE_H

Eigen/StdVector

@@ -14,17 +14,14 @@
 #include "Core"
 #include <vector>
 
-#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \
-    (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */
+#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */
 
 #define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...)
 
 #else
 
-// IWYU pragma: begin_exports
 #include "src/StlSupport/StdVector.h"
-// IWYU pragma: end_exports
 
 #endif
 
-#endif  // EIGEN_STDVECTOR_MODULE_H
+#endif // EIGEN_STDVECTOR_MODULE_H

Eigen/SuperLUSupport

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SUPERLUSUPPORT_MODULE_H
 #define EIGEN_SUPERLUSUPPORT_MODULE_H
 
@@ -16,7 +9,6 @@
 #define EIGEN_EMPTY_WAS_ALREADY_DEFINED
 #endif
 
-// Required by SuperLU headers, which expect int_t to be defined as a global typedef.
 typedef int int_t;
 #include <slu_Cnames.h>
 #include <supermatrix.h>
@@ -27,45 +19,41 @@ typedef int int_t;
 // If EMPTY was already defined then we don't undef it.
 
 #if defined(EIGEN_EMPTY_WAS_ALREADY_DEFINED)
-#undef EIGEN_EMPTY_WAS_ALREADY_DEFINED
+# undef EIGEN_EMPTY_WAS_ALREADY_DEFINED
 #elif defined(EMPTY)
-#undef EMPTY
+# undef EMPTY
 #endif
 
 #define SUPERLU_EMPTY (-1)
 
-namespace Eigen {
-struct SluMatrix;
-}
+namespace Eigen { struct SluMatrix; }
 
 /** \ingroup Support_modules
- * \defgroup SuperLUSupport_Module SuperLUSupport module
- *
- * This module provides an interface to the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library.
- * It provides the following factorization class:
- * - class SuperLU: a supernodal sequential LU factorization.
- * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative
- * methods).
- *
- * \warning This wrapper requires at least versions 4.0 of SuperLU. The 3.x versions are not supported.
- *
- * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined
- * because it is too polluting.
- *
- * \code
- * #include <Eigen/SuperLUSupport>
- * \endcode
- *
- * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be
- * linked to the superlu library and its dependencies. The dependencies depend on how superlu has been compiled. For a
- * cmake based project, you can use our FindSuperLU.cmake module to help you in this task.
- *
- */
+  * \defgroup SuperLUSupport_Module SuperLUSupport module
+  *
+  * This module provides an interface to the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library.
+  * It provides the following factorization class:
+  * - class SuperLU: a supernodal sequential LU factorization.
+  * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods).
+  *
+  * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting.
+  *
+  * \code
+  * #include <Eigen/SuperLUSupport>
+  * \endcode
+  *
+  * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be linked to the superlu library and its dependencies.
+  * The dependencies depend on how superlu has been compiled.
+  * For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
-// IWYU pragma: begin_exports
 #include "src/SuperLUSupport/SuperLUSupport.h"
-// IWYU pragma: end_exports
+
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_SUPERLUSUPPORT_MODULE_H
+#endif // EIGEN_SUPERLUSUPPORT_MODULE_H

Eigen/ThreadPool

@@ -1,80 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2016 Benoit Steiner <benoit.steiner.goog@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_THREADPOOL_MODULE_H
-#define EIGEN_THREADPOOL_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup ThreadPool_Module ThreadPool Module
- *
- * This module provides 2 threadpool implementations
- *  - a simple reference implementation
- *  - a faster non blocking implementation
- *
- * \code
- * #include <Eigen/ThreadPool>
- * \endcode
- */
-
-#include <cstddef>
-#include <cstring>
-#include <ctime>
-
-#include <vector>
-#include <atomic>
-#include <condition_variable>
-#include <deque>
-#include <mutex>
-#include <thread>
-#include <functional>
-#include <memory>
-#include <utility>
-
-// There are non-parenthesized calls to "max" in the  <unordered_map> header,
-// which trigger a check in test/main.h causing compilation to fail.
-// We work around the check here by removing the check for max in
-// the case where we have to emulate thread_local.
-#ifdef max
-#undef max
-#endif
-#include <unordered_map>
-
-#include "src/Core/util/Meta.h"
-#include "src/Core/util/MaxSizeVector.h"
-
-#ifndef EIGEN_MUTEX
-#define EIGEN_MUTEX std::mutex
-#endif
-#ifndef EIGEN_MUTEX_LOCK
-#define EIGEN_MUTEX_LOCK std::unique_lock<std::mutex>
-#endif
-#ifndef EIGEN_CONDVAR
-#define EIGEN_CONDVAR std::condition_variable
-#endif
-
-// IWYU pragma: begin_exports
-#include "src/ThreadPool/ThreadLocal.h"
-#include "src/ThreadPool/ThreadYield.h"
-#include "src/ThreadPool/ThreadCancel.h"
-#include "src/ThreadPool/EventCount.h"
-#include "src/ThreadPool/RunQueue.h"
-#include "src/ThreadPool/ThreadPoolInterface.h"
-#include "src/ThreadPool/ThreadEnvironment.h"
-#include "src/ThreadPool/Barrier.h"
-#include "src/ThreadPool/NonBlockingThreadPool.h"
-#include "src/ThreadPool/CoreThreadPoolDevice.h"
-#include "src/ThreadPool/ForkJoin.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_THREADPOOL_MODULE_H

Eigen/UmfPackSupport

@@ -1,10 +1,3 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_UMFPACKSUPPORT_MODULE_H
 #define EIGEN_UMFPACKSUPPORT_MODULE_H
 
@@ -17,26 +10,27 @@ extern "C" {
 }
 
 /** \ingroup Support_modules
- * \defgroup UmfPackSupport_Module UmfPackSupport module
- *
- * This module provides an interface to the UmfPack library which is part of the <a
- * href="http://www.suitesparse.com">suitesparse</a> package. It provides the following factorization class:
- * - class UmfPackLU: a multifrontal sequential LU factorization.
- *
- * \code
- * #include <Eigen/UmfPackSupport>
- * \endcode
- *
- * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be
- * linked to the umfpack library and its dependencies. The dependencies depend on how umfpack has been compiled. For a
- * cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
- *
- */
+  * \defgroup UmfPackSupport_Module UmfPackSupport module
+  *
+  * This module provides an interface to the UmfPack library which is part of the <a href="http://www.suitesparse.com">suitesparse</a> package.
+  * It provides the following factorization class:
+  * - class UmfPackLU: a multifrontal sequential LU factorization.
+  *
+  * \code
+  * #include <Eigen/UmfPackSupport>
+  * \endcode
+  *
+  * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies.
+  * The dependencies depend on how umfpack has been compiled.
+  * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
-// IWYU pragma: begin_exports
 #include "src/UmfPackSupport/UmfPackSupport.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_UMFPACKSUPPORT_MODULE_H
+#endif // EIGEN_UMFPACKSUPPORT_MODULE_H

Eigen/Version

@@ -1,21 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_VERSION_H
-#define EIGEN_VERSION_H
-
-// The "WORLD" version will forever remain "3" for the "Eigen3" library.
-#define EIGEN_WORLD_VERSION 3
-// As of Eigen3 5.0.0, we have moved to Semantic Versioning (semver.org).
-#define EIGEN_MAJOR_VERSION 5
-#define EIGEN_MINOR_VERSION 0
-#define EIGEN_PATCH_VERSION 1
-#define EIGEN_PRERELEASE_VERSION "dev"
-#define EIGEN_BUILD_VERSION "master"
-#define EIGEN_VERSION_STRING "5.0.1-dev+master"
-
-#endif  // EIGEN_VERSION_H

Eigen/src/AccelerateSupport/AccelerateSupport.h

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

Eigen/src/AccelerateSupport/InternalHeaderCheck.h

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

Eigen/src/CMakeLists.txt

@@ -0,0 +1,7 @@
+file(GLOB Eigen_src_subdirectories "*")
+escape_string_as_regex(ESCAPED_CMAKE_CURRENT_SOURCE_DIR "${CMAKE_CURRENT_SOURCE_DIR}")
+foreach(f ${Eigen_src_subdirectories})
+  if(NOT f MATCHES "\\.txt" AND NOT f MATCHES "${ESCAPED_CMAKE_CURRENT_SOURCE_DIR}/[.].+" )
+    add_subdirectory(${f})
+  endif()
+endforeach()

Eigen/src/Cholesky/CMakeLists.txt

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

Eigen/src/Cholesky/InternalHeaderCheck.h

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

Eigen/src/Cholesky/LLT.h

@@ -10,413 +10,392 @@
 #ifndef EIGEN_LLT_H
 #define EIGEN_LLT_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+namespace Eigen { 
 
-namespace Eigen {
-
-namespace internal {
-
-template <typename MatrixType_, int UpLo_>
-struct traits<LLT<MatrixType_, UpLo_> > : traits<MatrixType_> {
-  typedef MatrixXpr XprKind;
-  typedef SolverStorage StorageKind;
-  typedef int StorageIndex;
-  enum { Flags = 0 };
-};
-
-template <typename MatrixType, int UpLo>
-struct LLT_Traits;
-}  // namespace internal
+namespace internal{
+template<typename MatrixType, int UpLo> struct LLT_Traits;
+}
 
 /** \ingroup Cholesky_Module
- *
- * \class LLT
- *
- * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
- *
- * \tparam MatrixType_ the type of the matrix of which we are computing the LL^T Cholesky decomposition
- * \tparam UpLo_ the triangular part that will be used for the decomposition: Lower (default) or Upper.
- *               The other triangular part won't be read.
- *
- * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
- * matrix A such that A = LL^* = U^*U, where L is lower triangular.
- *
- * While the Cholesky decomposition is particularly useful to solve selfadjoint problems like  D^*D x = b,
- * for that purpose, we recommend the Cholesky decomposition without square root which is more stable
- * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other
- * situations like generalised eigen problems with hermitian matrices.
- *
- * Remember that Cholesky decompositions are not rank-revealing. This LLT decomposition is only stable on positive
- * definite matrices, use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine
- * whether a system of equations has a solution.
- *
- * Example: \include LLT_example.cpp
- * Output: \verbinclude LLT_example.out
- *
- * \b Performance: for best performance, it is recommended to use a column-major storage format
- * with the Lower triangular part (the default), or, equivalently, a row-major storage format
- * with the Upper triangular part. Otherwise, you might get a 20% slowdown for the full factorization
- * step, and rank-updates can be up to 3 times slower.
- *
- * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism.
- *
- * Note that during the decomposition, only the lower (or upper, as defined by UpLo_) triangular part of A is
- * considered. Therefore, the strict lower part does not have to store correct values.
- *
- * \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT
- */
-template <typename MatrixType_, int UpLo_>
-class LLT : public SolverBase<LLT<MatrixType_, UpLo_> > {
- public:
-  typedef MatrixType_ MatrixType;
-  typedef SolverBase<LLT> Base;
-  friend class SolverBase<LLT>;
+  *
+  * \class LLT
+  *
+  * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
+  *
+  * \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
+  * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
+  *             The other triangular part won't be read.
+  *
+  * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
+  * matrix A such that A = LL^* = U^*U, where L is lower triangular.
+  *
+  * While the Cholesky decomposition is particularly useful to solve selfadjoint problems like  D^*D x = b,
+  * for that purpose, we recommend the Cholesky decomposition without square root which is more stable
+  * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other
+  * situations like generalised eigen problems with hermitian matrices.
+  *
+  * Remember that Cholesky decompositions are not rank-revealing. This LLT decomposition is only stable on positive definite matrices,
+  * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations
+  * has a solution.
+  *
+  * Example: \include LLT_example.cpp
+  * Output: \verbinclude LLT_example.out
+  *    
+  * \sa MatrixBase::llt(), class LDLT
+  */
+ /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH)
+  * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
+  * the strict lower part does not have to store correct values.
+  */
+template<typename _MatrixType, int _UpLo> class LLT
+{
+  public:
+    typedef _MatrixType MatrixType;
+    enum {
+      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      Options = MatrixType::Options,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
 
-  EIGEN_GENERIC_PUBLIC_INTERFACE(LLT)
-  enum { MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime };
+    enum {
+      PacketSize = internal::packet_traits<Scalar>::size,
+      AlignmentMask = int(PacketSize)-1,
+      UpLo = _UpLo
+    };
 
-  enum { PacketSize = internal::packet_traits<Scalar>::size, AlignmentMask = int(PacketSize) - 1, UpLo = UpLo_ };
+    typedef internal::LLT_Traits<MatrixType,UpLo> Traits;
 
-  typedef internal::LLT_Traits<MatrixType, UpLo> Traits;
+    /**
+      * \brief Default Constructor.
+      *
+      * The default constructor is useful in cases in which the user intends to
+      * perform decompositions via LLT::compute(const MatrixType&).
+      */
+    LLT() : m_matrix(), m_isInitialized(false) {}
 
-  /**
-   * \brief Default Constructor.
-   *
-   * The default constructor is useful in cases in which the user intends to
-   * perform decompositions via LLT::compute(const MatrixType&).
-   */
-  LLT() : m_matrix(), m_l1_norm(0), m_isInitialized(false), m_info(InvalidInput) {}
+    /** \brief Default Constructor with memory preallocation
+      *
+      * Like the default constructor but with preallocation of the internal data
+      * according to the specified problem \a size.
+      * \sa LLT()
+      */
+    LLT(Index size) : m_matrix(size, size),
+                    m_isInitialized(false) {}
 
-  /** \brief Default Constructor with memory preallocation
-   *
-   * Like the default constructor but with preallocation of the internal data
-   * according to the specified problem \a size.
-   * \sa LLT()
-   */
-  explicit LLT(Index size) : m_matrix(size, size), m_l1_norm(0), m_isInitialized(false), m_info(InvalidInput) {}
+    LLT(const MatrixType& matrix)
+      : m_matrix(matrix.rows(), matrix.cols()),
+        m_isInitialized(false)
+    {
+      compute(matrix);
+    }
 
-  template <typename InputType>
-  explicit LLT(const EigenBase<InputType>& matrix)
-      : m_matrix(matrix.rows(), matrix.cols()), m_l1_norm(0), m_isInitialized(false), m_info(InvalidInput) {
-    compute(matrix.derived());
-  }
+    /** \returns a view of the upper triangular matrix U */
+    inline typename Traits::MatrixU matrixU() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return Traits::getU(m_matrix);
+    }
 
-  /** \brief Constructs a LLT factorization from a given matrix
-   *
-   * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when
-   * \c MatrixType is a Eigen::Ref.
-   *
-   * \sa LLT(const EigenBase&)
-   */
-  template <typename InputType>
-  explicit LLT(EigenBase<InputType>& matrix)
-      : m_matrix(matrix.derived()), m_l1_norm(0), m_isInitialized(false), m_info(InvalidInput) {
-    compute(matrix.derived());
-  }
+    /** \returns a view of the lower triangular matrix L */
+    inline typename Traits::MatrixL matrixL() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return Traits::getL(m_matrix);
+    }
 
-  /** \returns a view of the upper triangular matrix U */
-  inline typename Traits::MatrixU matrixU() const {
-    eigen_assert(m_isInitialized && "LLT is not initialized.");
-    return Traits::getU(m_matrix);
-  }
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * Since this LLT class assumes anyway that the matrix A is invertible, the solution
+      * theoretically exists and is unique regardless of b.
+      *
+      * Example: \include LLT_solve.cpp
+      * Output: \verbinclude LLT_solve.out
+      *
+      * \sa solveInPlace(), MatrixBase::llt()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<LLT, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      eigen_assert(m_matrix.rows()==b.rows()
+                && "LLT::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<LLT, Rhs>(*this, b.derived());
+    }
 
-  /** \returns a view of the lower triangular matrix L */
-  inline typename Traits::MatrixL matrixL() const {
-    eigen_assert(m_isInitialized && "LLT is not initialized.");
-    return Traits::getL(m_matrix);
-  }
+    #ifdef EIGEN2_SUPPORT
+    template<typename OtherDerived, typename ResultType>
+    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const
+    {
+      *result = this->solve(b);
+      return true;
+    }
+    
+    bool isPositiveDefinite() const { return true; }
+    #endif
 
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
-   *
-   * Since this LLT class assumes anyway that the matrix A is invertible, the solution
-   * theoretically exists and is unique regardless of b.
-   *
-   * Example: \include LLT_solve.cpp
-   * Output: \verbinclude LLT_solve.out
-   *
-   * \sa solveInPlace(), MatrixBase::llt(), SelfAdjointView::llt()
-   */
-  template <typename Rhs>
-  inline Solve<LLT, Rhs> solve(const MatrixBase<Rhs>& b) const;
-#endif
+    template<typename Derived>
+    void solveInPlace(MatrixBase<Derived> &bAndX) const;
 
-  template <typename Derived>
-  void solveInPlace(const MatrixBase<Derived>& bAndX) const;
+    LLT& compute(const MatrixType& matrix);
 
-  template <typename InputType>
-  LLT& compute(const EigenBase<InputType>& matrix);
+    /** \returns the LLT decomposition matrix
+      *
+      * TODO: document the storage layout
+      */
+    inline const MatrixType& matrixLLT() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return m_matrix;
+    }
 
-  /** \returns an estimate of the reciprocal condition number of the matrix of
-   *  which \c *this is the Cholesky decomposition.
-   */
-  RealScalar rcond() const {
-    eigen_assert(m_isInitialized && "LLT is not initialized.");
-    eigen_assert(m_info == Success && "LLT failed because matrix appears to be negative");
-    return internal::rcond_estimate_helper(m_l1_norm, *this);
-  }
+    MatrixType reconstructedMatrix() const;
 
-  /** \returns the LLT decomposition matrix
-   *
-   * TODO: document the storage layout
-   */
-  inline const MatrixType& matrixLLT() const {
-    eigen_assert(m_isInitialized && "LLT is not initialized.");
-    return m_matrix;
-  }
 
-  MatrixType reconstructedMatrix() const;
+    /** \brief Reports whether previous computation was successful.
+      *
+      * \returns \c Success if computation was succesful,
+      *          \c NumericalIssue if the matrix.appears to be negative.
+      */
+    ComputationInfo info() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return m_info;
+    }
 
-  /** \brief Reports whether previous computation was successful.
-   *
-   * \returns \c Success if computation was successful,
-   *          \c NumericalIssue if the matrix.appears not to be positive definite.
-   */
-  ComputationInfo info() const {
-    eigen_assert(m_isInitialized && "LLT is not initialized.");
-    return m_info;
-  }
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
 
-  /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix
-   * is self-adjoint.
-   *
-   * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as:
-   * \code x = decomposition.adjoint().solve(b) \endcode
-   */
-  const LLT& adjoint() const noexcept { return *this; }
+    template<typename VectorType>
+    LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
 
-  constexpr Index rows() const noexcept { return m_matrix.rows(); }
-  constexpr Index cols() const noexcept { return m_matrix.cols(); }
-
-  template <typename VectorType>
-  LLT& rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
-
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  template <typename RhsType, typename DstType>
-  void _solve_impl(const RhsType& rhs, DstType& dst) const;
-
-  template <bool Conjugate, typename RhsType, typename DstType>
-  void _solve_impl_transposed(const RhsType& rhs, DstType& dst) const;
-#endif
-
- protected:
-  EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
-
-  /** \internal
-   * Used to compute and store L
-   * The strict upper part is not used and even not initialized.
-   */
-  MatrixType m_matrix;
-  RealScalar m_l1_norm;
-  bool m_isInitialized;
-  ComputationInfo m_info;
+  protected:
+    
+    static void check_template_parameters()
+    {
+      EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
+    }
+    
+    /** \internal
+      * Used to compute and store L
+      * The strict upper part is not used and even not initialized.
+      */
+    MatrixType m_matrix;
+    bool m_isInitialized;
+    ComputationInfo m_info;
 };
 
 namespace internal {
 
-template <typename Scalar, int UpLo>
-struct llt_inplace;
+template<typename Scalar, int UpLo> struct llt_inplace;
 
-template <typename MatrixType, typename VectorType>
-static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec,
-                                   const typename MatrixType::RealScalar& sigma) {
+template<typename MatrixType, typename VectorType>
+static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
+{
   using std::sqrt;
   typedef typename MatrixType::Scalar Scalar;
   typedef typename MatrixType::RealScalar RealScalar;
+  typedef typename MatrixType::Index Index;
   typedef typename MatrixType::ColXpr ColXpr;
-  typedef internal::remove_all_t<ColXpr> ColXprCleaned;
+  typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
   typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
-  typedef Matrix<Scalar, Dynamic, 1> TempVectorType;
+  typedef Matrix<Scalar,Dynamic,1> TempVectorType;
   typedef typename TempVectorType::SegmentReturnType TempVecSegment;
 
   Index n = mat.cols();
-  eigen_assert(mat.rows() == n && vec.size() == n);
+  eigen_assert(mat.rows()==n && vec.size()==n);
 
   TempVectorType temp;
 
-  if (sigma > 0) {
+  if(sigma>0)
+  {
     // This version is based on Givens rotations.
     // It is faster than the other one below, but only works for updates,
     // i.e., for sigma > 0
     temp = sqrt(sigma) * vec;
 
-    for (Index i = 0; i < n; ++i) {
+    for(Index i=0; i<n; ++i)
+    {
       JacobiRotation<Scalar> g;
-      g.makeGivens(mat(i, i), -temp(i), &mat(i, i));
+      g.makeGivens(mat(i,i), -temp(i), &mat(i,i));
 
-      Index rs = n - i - 1;
-      if (rs > 0) {
+      Index rs = n-i-1;
+      if(rs>0)
+      {
         ColXprSegment x(mat.col(i).tail(rs));
         TempVecSegment y(temp.tail(rs));
         apply_rotation_in_the_plane(x, y, g);
       }
     }
-  } else {
+  }
+  else
+  {
     temp = vec;
     RealScalar beta = 1;
-    for (Index j = 0; j < n; ++j) {
-      RealScalar Ljj = numext::real(mat.coeff(j, j));
+    for(Index j=0; j<n; ++j)
+    {
+      RealScalar Ljj = numext::real(mat.coeff(j,j));
       RealScalar dj = numext::abs2(Ljj);
       Scalar wj = temp.coeff(j);
-      RealScalar swj2 = sigma * numext::abs2(wj);
-      RealScalar gamma = dj * beta + swj2;
+      RealScalar swj2 = sigma*numext::abs2(wj);
+      RealScalar gamma = dj*beta + swj2;
 
-      RealScalar x = dj + swj2 / beta;
-      if (x <= RealScalar(0)) return j;
+      RealScalar x = dj + swj2/beta;
+      if (x<=RealScalar(0))
+        return j;
       RealScalar nLjj = sqrt(x);
-      mat.coeffRef(j, j) = nLjj;
-      beta += swj2 / dj;
+      mat.coeffRef(j,j) = nLjj;
+      beta += swj2/dj;
 
       // Update the terms of L
-      Index rs = n - j - 1;
-      if (rs) {
-        temp.tail(rs) -= (wj / Ljj) * mat.col(j).tail(rs);
-        if (!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);
+      Index rs = n-j-1;
+      if(rs)
+      {
+        temp.tail(rs) -= (wj/Ljj) * mat.col(j).tail(rs);
+        if(gamma != 0)
+          mat.col(j).tail(rs) = (nLjj/Ljj) * mat.col(j).tail(rs) + (nLjj * sigma*numext::conj(wj)/gamma)*temp.tail(rs);
       }
     }
   }
   return -1;
 }
 
-template <typename Scalar>
-struct llt_inplace<Scalar, Lower> {
+template<typename Scalar> struct llt_inplace<Scalar, Lower>
+{
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  template <typename MatrixType>
-  static Index unblocked(MatrixType& mat) {
+  template<typename MatrixType>
+  static typename MatrixType::Index unblocked(MatrixType& mat)
+  {
     using std::sqrt;
-
-    eigen_assert(mat.rows() == mat.cols());
+    typedef typename MatrixType::Index Index;
+    
+    eigen_assert(mat.rows()==mat.cols());
     const Index size = mat.rows();
-    for (Index k = 0; k < size; ++k) {
-      Index rs = size - k - 1;  // remaining size
+    for(Index k = 0; k < size; ++k)
+    {
+      Index rs = size-k-1; // remaining size
 
-      Block<MatrixType, Dynamic, 1> A21(mat, k + 1, k, rs, 1);
-      Block<MatrixType, 1, Dynamic> A10(mat, k, 0, 1, k);
-      Block<MatrixType, Dynamic, Dynamic> A20(mat, k + 1, 0, rs, k);
+      Block<MatrixType,Dynamic,1> A21(mat,k+1,k,rs,1);
+      Block<MatrixType,1,Dynamic> A10(mat,k,0,1,k);
+      Block<MatrixType,Dynamic,Dynamic> A20(mat,k+1,0,rs,k);
 
-      RealScalar x = numext::real(mat.coeff(k, k));
-      if (k > 0) x -= A10.squaredNorm();
-      if (x <= RealScalar(0)) return k;
-      mat.coeffRef(k, k) = x = sqrt(x);
-      if (k > 0 && rs > 0) A21.noalias() -= A20 * A10.adjoint();
-      if (rs > 0) A21 /= x;
+      RealScalar x = numext::real(mat.coeff(k,k));
+      if (k>0) x -= A10.squaredNorm();
+      if (x<=RealScalar(0))
+        return k;
+      mat.coeffRef(k,k) = x = sqrt(x);
+      if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint();
+      if (rs>0) A21 /= x;
     }
     return -1;
   }
 
-  template <typename MatrixType>
-  static Index blocked(MatrixType& m) {
-    eigen_assert(m.rows() == m.cols());
+  template<typename MatrixType>
+  static typename MatrixType::Index blocked(MatrixType& m)
+  {
+    typedef typename MatrixType::Index Index;
+    eigen_assert(m.rows()==m.cols());
     Index size = m.rows();
-    if (size < 32) return unblocked(m);
+    if(size<32)
+      return unblocked(m);
 
-    Index blockSize = size / 8;
-    blockSize = (blockSize / 16) * 16;
-    blockSize = (std::min)((std::max)(blockSize, Index(8)), Index(128));
+    Index blockSize = size/8;
+    blockSize = (blockSize/16)*16;
+    blockSize = (std::min)((std::max)(blockSize,Index(8)), Index(128));
 
-    for (Index k = 0; k < size; k += blockSize) {
+    for (Index k=0; k<size; k+=blockSize)
+    {
       // partition the matrix:
       //       A00 |  -  |  -
       // lu  = A10 | A11 |  -
       //       A20 | A21 | A22
-      Index bs = (std::min)(blockSize, size - k);
+      Index bs = (std::min)(blockSize, size-k);
       Index rs = size - k - bs;
-      Block<MatrixType, Dynamic, Dynamic> A11(m, k, k, bs, bs);
-      Block<MatrixType, Dynamic, Dynamic> A21(m, k + bs, k, rs, bs);
-      Block<MatrixType, Dynamic, Dynamic> A22(m, k + bs, k + bs, rs, rs);
+      Block<MatrixType,Dynamic,Dynamic> A11(m,k,   k,   bs,bs);
+      Block<MatrixType,Dynamic,Dynamic> A21(m,k+bs,k,   rs,bs);
+      Block<MatrixType,Dynamic,Dynamic> A22(m,k+bs,k+bs,rs,rs);
 
       Index ret;
-      if ((ret = unblocked(A11)) >= 0) return k + ret;
-      if (rs > 0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
-      if (rs > 0)
-        A22.template selfadjointView<Lower>().rankUpdate(A21,
-                                                         typename NumTraits<RealScalar>::Literal(-1));  // bottleneck
+      if((ret=unblocked(A11))>=0) return k+ret;
+      if(rs>0) A11.adjoint().template triangularView<Upper>().template solveInPlace<OnTheRight>(A21);
+      if(rs>0) A22.template selfadjointView<Lower>().rankUpdate(A21,-1); // bottleneck
     }
     return -1;
   }
 
-  template <typename MatrixType, typename VectorType>
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) {
+  template<typename MatrixType, typename VectorType>
+  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
+  {
     return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
   }
 };
-
-template <typename Scalar>
-struct llt_inplace<Scalar, Upper> {
+  
+template<typename Scalar> struct llt_inplace<Scalar, Upper>
+{
   typedef typename NumTraits<Scalar>::Real RealScalar;
 
-  template <typename MatrixType>
-  static EIGEN_STRONG_INLINE Index unblocked(MatrixType& mat) {
+  template<typename MatrixType>
+  static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat)
+  {
     Transpose<MatrixType> matt(mat);
     return llt_inplace<Scalar, Lower>::unblocked(matt);
   }
-  template <typename MatrixType>
-  static EIGEN_STRONG_INLINE Index blocked(MatrixType& mat) {
+  template<typename MatrixType>
+  static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat)
+  {
     Transpose<MatrixType> matt(mat);
     return llt_inplace<Scalar, Lower>::blocked(matt);
   }
-  template <typename MatrixType, typename VectorType>
-  static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) {
+  template<typename MatrixType, typename VectorType>
+  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
+  {
     Transpose<MatrixType> matt(mat);
     return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
   }
 };
 
-template <typename MatrixType>
-struct LLT_Traits<MatrixType, Lower> {
+template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
+{
   typedef const TriangularView<const MatrixType, Lower> MatrixL;
   typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); }
-  static bool inplace_decomposition(MatrixType& m) {
-    return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m) == -1;
-  }
+  static inline MatrixL getL(const MatrixType& m) { return m; }
+  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  static bool inplace_decomposition(MatrixType& m)
+  { return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
 };
 
-template <typename MatrixType>
-struct LLT_Traits<MatrixType, Upper> {
+template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
+{
   typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
   typedef const TriangularView<const MatrixType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); }
-  static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); }
-  static bool inplace_decomposition(MatrixType& m) {
-    return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m) == -1;
-  }
+  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixU getU(const MatrixType& m) { return m; }
+  static bool inplace_decomposition(MatrixType& m)
+  { return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; }
 };
 
-}  // end namespace internal
+} // end namespace internal
 
 /** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix
- *
- * \returns a reference to *this
- *
- * Example: \include TutorialLinAlgComputeTwice.cpp
- * Output: \verbinclude TutorialLinAlgComputeTwice.out
- */
-template <typename MatrixType, int UpLo_>
-template <typename InputType>
-LLT<MatrixType, UpLo_>& LLT<MatrixType, UpLo_>::compute(const EigenBase<InputType>& a) {
-  eigen_assert(a.rows() == a.cols());
+  *
+  * \returns a reference to *this
+  *
+  * Example: \include TutorialLinAlgComputeTwice.cpp
+  * Output: \verbinclude TutorialLinAlgComputeTwice.out
+  */
+template<typename MatrixType, int _UpLo>
+LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
+{
+  check_template_parameters();
+  
+  eigen_assert(a.rows()==a.cols());
   const Index size = a.rows();
   m_matrix.resize(size, size);
-  if (!internal::is_same_dense(m_matrix, a.derived())) m_matrix = a.derived();
-
-  // Compute matrix L1 norm = max abs column sum.
-  m_l1_norm = RealScalar(0);
-  // TODO: move this code to SelfAdjointView
-  for (Index col = 0; col < size; ++col) {
-    RealScalar abs_col_sum;
-    if (UpLo_ == Lower)
-      abs_col_sum =
-          m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>();
-    else
-      abs_col_sum =
-          m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>();
-    if (abs_col_sum > m_l1_norm) m_l1_norm = abs_col_sum;
-  }
+  m_matrix = a;
 
   m_isInitialized = true;
   bool ok = Traits::inplace_decomposition(m_matrix);
@@ -426,59 +405,60 @@ LLT<MatrixType, UpLo_>& LLT<MatrixType, UpLo_>::compute(const EigenBase<InputTyp
 }
 
 /** Performs a rank one update (or dowdate) of the current decomposition.
- * If A = LL^* before the rank one update,
- * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector
- * of same dimension.
- */
-template <typename MatrixType_, int UpLo_>
-template <typename VectorType>
-LLT<MatrixType_, UpLo_>& LLT<MatrixType_, UpLo_>::rankUpdate(const VectorType& v, const RealScalar& sigma) {
+  * If A = LL^* before the rank one update,
+  * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector
+  * of same dimension.
+  */
+template<typename _MatrixType, int _UpLo>
+template<typename VectorType>
+LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma)
+{
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType);
-  eigen_assert(v.size() == m_matrix.cols());
+  eigen_assert(v.size()==m_matrix.cols());
   eigen_assert(m_isInitialized);
-  if (internal::llt_inplace<typename MatrixType::Scalar, UpLo>::rankUpdate(m_matrix, v, sigma) >= 0)
+  if(internal::llt_inplace<typename MatrixType::Scalar, UpLo>::rankUpdate(m_matrix,v,sigma)>=0)
     m_info = NumericalIssue;
   else
     m_info = Success;
 
   return *this;
 }
+    
+namespace internal {
+template<typename _MatrixType, int UpLo, typename Rhs>
+struct solve_retval<LLT<_MatrixType, UpLo>, Rhs>
+  : solve_retval_base<LLT<_MatrixType, UpLo>, Rhs>
+{
+  typedef LLT<_MatrixType,UpLo> LLTType;
+  EIGEN_MAKE_SOLVE_HELPERS(LLTType,Rhs)
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-template <typename MatrixType_, int UpLo_>
-template <typename RhsType, typename DstType>
-void LLT<MatrixType_, UpLo_>::_solve_impl(const RhsType& rhs, DstType& dst) const {
-  _solve_impl_transposed<true>(rhs, dst);
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dst = rhs();
+    dec().solveInPlace(dst);
+  }
+};
 }
 
-template <typename MatrixType_, int UpLo_>
-template <bool Conjugate, typename RhsType, typename DstType>
-void LLT<MatrixType_, UpLo_>::_solve_impl_transposed(const RhsType& rhs, DstType& dst) const {
-  dst = rhs;
-
-  matrixL().template conjugateIf<!Conjugate>().solveInPlace(dst);
-  matrixU().template conjugateIf<!Conjugate>().solveInPlace(dst);
-}
-#endif
-
 /** \internal use x = llt_object.solve(x);
- *
- * This is the \em in-place version of solve().
- *
- * \param bAndX represents both the right-hand side matrix b and result x.
- *
- * This version avoids a copy when the right hand side matrix b is not needed anymore.
- *
- * \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
- * This function will const_cast it, so constness isn't honored here.
- *
- * \sa LLT::solve(), MatrixBase::llt()
- */
-template <typename MatrixType, int UpLo_>
-template <typename Derived>
-void LLT<MatrixType, UpLo_>::solveInPlace(const MatrixBase<Derived>& bAndX) const {
+  * 
+  * This is the \em in-place version of solve().
+  *
+  * \param bAndX represents both the right-hand side matrix b and result x.
+  *
+  * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD.
+  *
+  * This version avoids a copy when the right hand side matrix b is not
+  * needed anymore.
+  *
+  * \sa LLT::solve(), MatrixBase::llt()
+  */
+template<typename MatrixType, int _UpLo>
+template<typename Derived>
+void LLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
+{
   eigen_assert(m_isInitialized && "LLT is not initialized.");
-  eigen_assert(m_matrix.rows() == bAndX.rows());
+  eigen_assert(m_matrix.rows()==bAndX.rows());
   matrixL().solveInPlace(bAndX);
   matrixU().solveInPlace(bAndX);
 }
@@ -486,31 +466,33 @@ void LLT<MatrixType, UpLo_>::solveInPlace(const MatrixBase<Derived>& bAndX) cons
 /** \returns the matrix represented by the decomposition,
  * i.e., it returns the product: L L^*.
  * This function is provided for debug purpose. */
-template <typename MatrixType, int UpLo_>
-MatrixType LLT<MatrixType, UpLo_>::reconstructedMatrix() const {
+template<typename MatrixType, int _UpLo>
+MatrixType LLT<MatrixType,_UpLo>::reconstructedMatrix() const
+{
   eigen_assert(m_isInitialized && "LLT is not initialized.");
   return matrixL() * matrixL().adjoint().toDenseMatrix();
 }
 
 /** \cholesky_module
- * \returns the LLT decomposition of \c *this
- * \sa SelfAdjointView::llt()
- */
-template <typename Derived>
-inline LLT<typename MatrixBase<Derived>::PlainObject> MatrixBase<Derived>::llt() const {
+  * \returns the LLT decomposition of \c *this
+  */
+template<typename Derived>
+inline const LLT<typename MatrixBase<Derived>::PlainObject>
+MatrixBase<Derived>::llt() const
+{
   return LLT<PlainObject>(derived());
 }
 
 /** \cholesky_module
- * \returns the LLT decomposition of \c *this
- * \sa SelfAdjointView::llt()
- */
-template <typename MatrixType, unsigned int UpLo>
-inline LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo> SelfAdjointView<MatrixType, UpLo>::llt()
-    const {
-  return LLT<PlainObject, UpLo>(m_matrix);
+  * \returns the LLT decomposition of \c *this
+  */
+template<typename MatrixType, unsigned int UpLo>
+inline const LLT<typename SelfAdjointView<MatrixType, UpLo>::PlainObject, UpLo>
+SelfAdjointView<MatrixType, UpLo>::llt() const
+{
+  return LLT<PlainObject,UpLo>(m_matrix);
 }
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_LLT_H
+#endif // EIGEN_LLT_H

Eigen/src/Cholesky/LLT_LAPACKE.h

@@ -1,124 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to LAPACKe
- *     LLt decomposition based on LAPACKE_?potrf function.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_LLT_LAPACKE_H
-#define EIGEN_LLT_LAPACKE_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-namespace lapacke_helpers {
-// -------------------------------------------------------------------------------------------------------------------
-//        Dispatch for rank update handling upper and lower parts
-// -------------------------------------------------------------------------------------------------------------------
-
-template <UpLoType Mode>
-struct rank_update {};
-
-template <>
-struct rank_update<Lower> {
-  template <typename MatrixType, typename VectorType>
-  static Index run(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) {
-    return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
-  }
-};
-
-template <>
-struct rank_update<Upper> {
-  template <typename MatrixType, typename VectorType>
-  static Index run(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) {
-    Transpose<MatrixType> matt(mat);
-    return Eigen::internal::llt_rank_update_lower(matt, vec.conjugate(), sigma);
-  }
-};
-
-// -------------------------------------------------------------------------------------------------------------------
-//        Generic lapacke llt implementation that hands of to the dispatches
-// -------------------------------------------------------------------------------------------------------------------
-
-template <typename Scalar, UpLoType Mode>
-struct lapacke_llt {
-  EIGEN_STATIC_ASSERT(((Mode == Lower) || (Mode == Upper)), MODE_MUST_BE_UPPER_OR_LOWER)
-  template <typename MatrixType>
-  static Index blocked(MatrixType &m) {
-    eigen_assert(m.rows() == m.cols());
-    if (m.rows() == 0) {
-      return -1;
-    }
-    /* Set up parameters for ?potrf */
-    lapack_int size = to_lapack(m.rows());
-    lapack_int matrix_order = lapack_storage_of(m);
-    constexpr char uplo = Mode == Upper ? 'U' : 'L';
-    Scalar *a = &(m.coeffRef(0, 0));
-    lapack_int lda = to_lapack(m.outerStride());
-
-    lapack_int info = potrf(matrix_order, uplo, size, to_lapack(a), lda);
-    info = (info == 0) ? -1 : info > 0 ? info - 1 : size;
-    return info;
-  }
-
-  template <typename MatrixType, typename VectorType>
-  static Index rankUpdate(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) {
-    return rank_update<Mode>::run(mat, vec, sigma);
-  }
-};
-}  // namespace lapacke_helpers
-// end namespace lapacke_helpers
-
-/*
- * Here, we just put the generic implementation from lapacke_llt into a full specialization of the llt_inplace
- * type. By being a full specialization, the versions defined here thus get precedence over the generic implementation
- * in LLT.h for double, float and complex double, complex float types.
- */
-
-#define EIGEN_LAPACKE_LLT(EIGTYPE)                                                             \
-  template <>                                                                                  \
-  struct llt_inplace<EIGTYPE, Lower> : public lapacke_helpers::lapacke_llt<EIGTYPE, Lower> {}; \
-  template <>                                                                                  \
-  struct llt_inplace<EIGTYPE, Upper> : public lapacke_helpers::lapacke_llt<EIGTYPE, Upper> {};
-
-EIGEN_LAPACKE_LLT(double)
-EIGEN_LAPACKE_LLT(float)
-EIGEN_LAPACKE_LLT(std::complex<double>)
-EIGEN_LAPACKE_LLT(std::complex<float>)
-
-#undef EIGEN_LAPACKE_LLT
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_LLT_LAPACKE_H

Eigen/src/Cholesky/LLT_MKL.h

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

Eigen/src/CholmodSupport/CMakeLists.txt

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

Eigen/src/CholmodSupport/InternalHeaderCheck.h

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

Eigen/src/Core/ArithmeticSequence.h

@@ -1,239 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2017 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_ARITHMETIC_SEQUENCE_H
-#define EIGEN_ARITHMETIC_SEQUENCE_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-// Helper to cleanup the type of the increment:
-template <typename T>
-struct cleanup_seq_incr {
-  typedef typename cleanup_index_type<T, DynamicIndex>::type type;
-};
-
-}  // namespace internal
-
-//--------------------------------------------------------------------------------
-// seq(first,last,incr) and seqN(first,size,incr)
-//--------------------------------------------------------------------------------
-
-template <typename FirstType = Index, typename SizeType = Index, typename IncrType = internal::FixedInt<1> >
-class ArithmeticSequence;
-
-template <typename FirstType, typename SizeType, typename IncrType>
-ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                   typename internal::cleanup_index_type<SizeType>::type,
-                   typename internal::cleanup_seq_incr<IncrType>::type>
-seqN(FirstType first, SizeType size, IncrType incr);
-
-/** \class ArithmeticSequence
- * \ingroup Core_Module
- *
- * This class represents an arithmetic progression \f$ a_0, a_1, a_2, ..., a_{n-1}\f$ defined by
- * its \em first value \f$ a_0 \f$, its \em size (aka length) \em n, and the \em increment (aka stride)
- * that is equal to \f$ a_{i+1}-a_{i}\f$ for any \em i.
- *
- * It is internally used as the return type of the Eigen::seq and Eigen::seqN functions, and as the input arguments
- * of DenseBase::operator()(const RowIndices&, const ColIndices&), and most of the time this is the
- * only way it is used.
- *
- * \tparam FirstType type of the first element, usually an Index,
- *                   but internally it can be a symbolic expression
- * \tparam SizeType type representing the size of the sequence, usually an Index
- *                  or a compile time integral constant. Internally, it can also be a symbolic expression
- * \tparam IncrType type of the increment, can be a runtime Index, or a compile time integral constant (default is
- * compile-time 1)
- *
- * \sa Eigen::seq, Eigen::seqN, DenseBase::operator()(const RowIndices&, const ColIndices&), class IndexedView
- */
-template <typename FirstType, typename SizeType, typename IncrType>
-class ArithmeticSequence {
- public:
-  constexpr ArithmeticSequence() = default;
-  constexpr ArithmeticSequence(FirstType first, SizeType size) : m_first(first), m_size(size) {}
-  constexpr ArithmeticSequence(FirstType first, SizeType size, IncrType incr)
-      : m_first(first), m_size(size), m_incr(incr) {}
-
-  enum {
-    // SizeAtCompileTime = internal::get_fixed_value<SizeType>::value,
-    IncrAtCompileTime = internal::get_fixed_value<IncrType, DynamicIndex>::value
-  };
-
-  /** \returns the size, i.e., number of elements, of the sequence */
-  constexpr Index size() const { return m_size; }
-
-  /** \returns the first element \f$ a_0 \f$ in the sequence */
-  constexpr Index first() const { return m_first; }
-
-  /** \returns the value \f$ a_i \f$ at index \a i in the sequence. */
-  constexpr Index operator[](Index i) const { return m_first + i * m_incr; }
-
-  constexpr const FirstType& firstObject() const { return m_first; }
-  constexpr const SizeType& sizeObject() const { return m_size; }
-  constexpr const IncrType& incrObject() const { return m_incr; }
-
- protected:
-  FirstType m_first;
-  SizeType m_size;
-  IncrType m_incr;
-
- public:
-  constexpr auto reverse() const -> decltype(Eigen::seqN(m_first + (m_size + fix<-1>()) * m_incr, m_size, -m_incr)) {
-    return seqN(m_first + (m_size + fix<-1>()) * m_incr, m_size, -m_incr);
-  }
-};
-
-/** \returns an ArithmeticSequence starting at \a first, of length \a size, and increment \a incr
- *
- * \sa seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) */
-template <typename FirstType, typename SizeType, typename IncrType>
-ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                   typename internal::cleanup_index_type<SizeType>::type,
-                   typename internal::cleanup_seq_incr<IncrType>::type>
-seqN(FirstType first, SizeType size, IncrType incr) {
-  return ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                            typename internal::cleanup_index_type<SizeType>::type,
-                            typename internal::cleanup_seq_incr<IncrType>::type>(first, size, incr);
-}
-
-/** \returns an ArithmeticSequence starting at \a first, of length \a size, and unit increment
- *
- * \sa seqN(FirstType,SizeType,IncrType), seq(FirstType,LastType) */
-template <typename FirstType, typename SizeType>
-ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                   typename internal::cleanup_index_type<SizeType>::type>
-seqN(FirstType first, SizeType size) {
-  return ArithmeticSequence<typename internal::cleanup_index_type<FirstType>::type,
-                            typename internal::cleanup_index_type<SizeType>::type>(first, size);
-}
-
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-
-/** \returns an ArithmeticSequence starting at \a f, up (or down) to \a l, and with positive (or negative) increment \a
- * incr
- *
- * It is essentially an alias to:
- * \code
- * seqN(f, (l-f+incr)/incr, incr);
- * \endcode
- *
- * \sa seqN(FirstType,SizeType,IncrType), seq(FirstType,LastType)
- */
-template <typename FirstType, typename LastType, typename IncrType>
-auto seq(FirstType f, LastType l, IncrType incr);
-
-/** \returns an ArithmeticSequence starting at \a f, up (or down) to \a l, and unit increment
- *
- * It is essentially an alias to:
- * \code
- * seqN(f,l-f+1);
- * \endcode
- *
- * \sa seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType)
- */
-template <typename FirstType, typename LastType>
-auto seq(FirstType f, LastType l);
-
-#else  // EIGEN_PARSED_BY_DOXYGEN
-
-template <typename FirstType, typename LastType>
-auto seq(FirstType f, LastType l)
-    -> decltype(seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-                     (typename internal::cleanup_index_type<LastType>::type(l) -
-                      typename internal::cleanup_index_type<FirstType>::type(f) + fix<1>()))) {
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-              (typename internal::cleanup_index_type<LastType>::type(l) -
-               typename internal::cleanup_index_type<FirstType>::type(f) + fix<1>()));
-}
-
-template <typename FirstType, typename LastType, typename IncrType>
-auto seq(FirstType f, LastType l, IncrType incr)
-    -> decltype(seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-                     (typename internal::cleanup_index_type<LastType>::type(l) -
-                      typename internal::cleanup_index_type<FirstType>::type(f) +
-                      typename internal::cleanup_seq_incr<IncrType>::type(incr)) /
-                         typename internal::cleanup_seq_incr<IncrType>::type(incr),
-                     typename internal::cleanup_seq_incr<IncrType>::type(incr))) {
-  typedef typename internal::cleanup_seq_incr<IncrType>::type CleanedIncrType;
-  return seqN(typename internal::cleanup_index_type<FirstType>::type(f),
-              (typename internal::cleanup_index_type<LastType>::type(l) -
-               typename internal::cleanup_index_type<FirstType>::type(f) + CleanedIncrType(incr)) /
-                  CleanedIncrType(incr),
-              CleanedIncrType(incr));
-}
-
-#endif  // EIGEN_PARSED_BY_DOXYGEN
-
-namespace placeholders {
-
-/** \cpp11
- * \returns a symbolic ArithmeticSequence representing the last \a size elements with increment \a incr.
- *
- * It is a shortcut for: \code seqN(last-(size-fix<1>)*incr, size, incr) \endcode
- * \anchor Eigen_placeholders_lastN
- * \sa lastN(SizeType), seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) */
-template <typename SizeType, typename IncrType>
-auto lastN(SizeType size, IncrType incr)
-    -> decltype(seqN(Eigen::placeholders::last - (size - fix<1>()) * incr, size, incr)) {
-  return seqN(Eigen::placeholders::last - (size - fix<1>()) * incr, size, incr);
-}
-
-/** \cpp11
- * \returns a symbolic ArithmeticSequence representing the last \a size elements with a unit increment.
- *
- *  It is a shortcut for: \code seq(last+fix<1>-size, last) \endcode
- *
- * \sa lastN(SizeType,IncrType, seqN(FirstType,SizeType), seq(FirstType,LastType) */
-template <typename SizeType>
-auto lastN(SizeType size) -> decltype(seqN(Eigen::placeholders::last + fix<1>() - size, size)) {
-  return seqN(Eigen::placeholders::last + fix<1>() - size, size);
-}
-
-}  // namespace placeholders
-
-/** \namespace Eigen::indexing
-  * \ingroup Core_Module
-  *
-  * The sole purpose of this namespace is to be able to import all functions
-  * and symbols that are expected to be used within operator() for indexing
-  * and slicing. If you already imported the whole Eigen namespace:
-  * \code using namespace Eigen; \endcode
-  * then you are already all set. Otherwise, if you don't want/cannot import
-  * the whole Eigen namespace, the following line:
-  * \code using namespace Eigen::indexing; \endcode
-  * is equivalent to:
-  * \code
-  using Eigen::fix;
-  using Eigen::seq;
-  using Eigen::seqN;
-  using Eigen::placeholders::all;
-  using Eigen::placeholders::last;
-  using Eigen::placeholders::lastN;  // c++11 only
-  using Eigen::placeholders::lastp1;
-  \endcode
-  */
-namespace indexing {
-using Eigen::fix;
-using Eigen::seq;
-using Eigen::seqN;
-using Eigen::placeholders::all;
-using Eigen::placeholders::last;
-using Eigen::placeholders::lastN;
-using Eigen::placeholders::lastp1;
-}  // namespace indexing
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_ARITHMETIC_SEQUENCE_H

Eigen/src/Core/Array.h

@@ -10,365 +10,314 @@
 #ifndef EIGEN_ARRAY_H
 #define EIGEN_ARRAY_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
 namespace Eigen {
 
+/** \class Array 
+  * \ingroup Core_Module
+  *
+  * \brief General-purpose arrays with easy API for coefficient-wise operations
+  *
+  * The %Array class is very similar to the Matrix class. It provides
+  * general-purpose one- and two-dimensional arrays. The difference between the
+  * %Array and the %Matrix class is primarily in the API: the API for the
+  * %Array class provides easy access to coefficient-wise operations, while the
+  * API for the %Matrix class provides easy access to linear-algebra
+  * operations.
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
+  *
+  * \sa \ref TutorialArrayClass, \ref TopicClassHierarchy
+  */
 namespace internal {
-template <typename Scalar_, int Rows_, int Cols_, int Options_, int MaxRows_, int MaxCols_>
-struct traits<Array<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_>>
-    : traits<Matrix<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_>> {
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+struct traits<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > : traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
+{
   typedef ArrayXpr XprKind;
-  typedef ArrayBase<Array<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_>> XprBase;
+  typedef ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > XprBase;
 };
-}  // namespace internal
+}
 
-/** \class Array
- * \ingroup Core_Module
- *
- * \brief General-purpose arrays with easy API for coefficient-wise operations
- *
- * The %Array class is very similar to the Matrix class. It provides
- * general-purpose one- and two-dimensional arrays. The difference between the
- * %Array and the %Matrix class is primarily in the API: the API for the
- * %Array class provides easy access to coefficient-wise operations, while the
- * API for the %Matrix class provides easy access to linear-algebra
- * operations.
- *
- * See documentation of class Matrix for detailed information on the template parameters
- * storage layout.
- *
- * This class can be extended with the help of the plugin mechanism described on the page
- * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN.
- *
- * \sa \blank \ref TutorialArrayClass, \ref TopicClassHierarchy
- */
-template <typename Scalar_, int Rows_, int Cols_, int Options_, int MaxRows_, int MaxCols_>
-class Array : public PlainObjectBase<Array<Scalar_, Rows_, Cols_, Options_, MaxRows_, MaxCols_>> {
- public:
-  typedef PlainObjectBase<Array> Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(Array)
+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:
 
-  enum { Options = Options_ };
-  typedef typename Base::PlainObject PlainObject;
+    typedef PlainObjectBase<Array> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Array)
 
- protected:
-  template <typename Derived, typename OtherDerived, bool IsVector>
-  friend struct internal::conservative_resize_like_impl;
+    enum { Options = _Options };
+    typedef typename Base::PlainObject PlainObject;
 
-  using Base::m_storage;
+  protected:
+    template <typename Derived, typename OtherDerived, bool IsVector>
+    friend struct internal::conservative_resize_like_impl;
 
- public:
-  using Base::base;
-  using Base::coeff;
-  using Base::coeffRef;
+    using Base::m_storage;
 
-  /**
-   * The usage of
-   *   using Base::operator=;
-   * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
-   * the usage of 'using'. This should be done only for operator=.
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived>& other) {
-    return Base::operator=(other);
-  }
+  public:
 
-  /** Set all the entries to \a value.
-   * \sa DenseBase::setConstant(), DenseBase::fill()
-   */
-  /* This overload is needed because the usage of
-   *   using Base::operator=;
-   * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
-   * the usage of 'using'. This should be done only for operator=.
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const Scalar& value) {
-    Base::setConstant(value);
-    return *this;
-  }
+    using Base::base;
+    using Base::coeff;
+    using Base::coeffRef;
 
-  /** Copies the value of the expression \a other into \c *this with automatic resizing.
-   *
-   * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
-   * it will be initialized.
-   *
-   * Note that copying a row-vector into a vector (and conversely) is allowed.
-   * The resizing, if any, is then done in the appropriate way so that row-vectors
-   * remain row-vectors and vectors remain vectors.
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const DenseBase<OtherDerived>& other) {
-    return Base::_set(other);
-  }
+    /**
+      * The usage of
+      *   using Base::operator=;
+      * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped
+      * the usage of 'using'. This should be done only for operator=.
+      */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array& operator=(const EigenBase<OtherDerived> &other)
+    {
+      return Base::operator=(other);
+    }
 
-  /**
-   * \brief Assigns arrays to each other.
-   *
-   * \note This is a special case of the templated operator=. Its purpose is
-   * to prevent a default operator= from hiding the templated operator=.
-   *
-   * \callgraph
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const Array& other) { return Base::_set(other); }
+    /** Copies the value of the expression \a other into \c *this with automatic resizing.
+      *
+      * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
+      * it will be initialized.
+      *
+      * Note that copying a row-vector into a vector (and conversely) is allowed.
+      * The resizing, if any, is then done in the appropriate way so that row-vectors
+      * remain row-vectors and vectors remain vectors.
+      */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array& operator=(const ArrayBase<OtherDerived>& other)
+    {
+      return Base::_set(other);
+    }
 
-  /** Default constructor.
-   *
-   * For fixed-size matrices, does nothing.
-   *
-   * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
-   * is called a null matrix. This constructor is the unique way to create null matrices: resizing
-   * a matrix to 0 is not supported.
-   *
-   * \sa resize(Index,Index)
-   */
-#ifdef EIGEN_INITIALIZE_COEFFS
-  EIGEN_DEVICE_FUNC constexpr Array() : Base() { EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
-#else
-  EIGEN_DEVICE_FUNC constexpr Array() = default;
-#endif
-  /** \brief Move constructor */
-  EIGEN_DEVICE_FUNC constexpr Array(Array&&) = default;
-  EIGEN_DEVICE_FUNC Array& operator=(Array&& other) noexcept(std::is_nothrow_move_assignable<Scalar>::value) {
-    Base::operator=(std::move(other));
-    return *this;
-  }
+    /** This is a special case of the templated operator=. Its purpose is to
+      * prevent a default operator= from hiding the templated operator=.
+      */
+    EIGEN_STRONG_INLINE Array& operator=(const Array& other)
+    {
+      return Base::_set(other);
+    }
 
-  /** \brief Construct a row of column vector with fixed size from an arbitrary number of coefficients.
-   *
-   * \only_for_vectors
-   *
-   * This constructor is for 1D array or vectors with more than 4 coefficients.
-   *
-   * \warning To construct a column (resp. row) vector of fixed length, the number of values passed to this
-   * constructor must match the fixed number of rows (resp. columns) of \c *this.
-   *
-   *
-   * Example: \include Array_variadic_ctor_cxx11.cpp
-   * Output: \verbinclude Array_variadic_ctor_cxx11.out
-   *
-   * \sa Array(const std::initializer_list<std::initializer_list<Scalar>>&)
-   * \sa Array(const Scalar&), Array(const Scalar&,const Scalar&)
-   */
-  template <typename... ArgTypes>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3,
-                                              const ArgTypes&... args)
-      : Base(a0, a1, a2, a3, args...) {}
-
-  /** \brief Constructs an array and initializes it from the coefficients given as initializer-lists grouped by row.
-   * \cpp11
-   *
-   * In the general case, the constructor takes a list of rows, each row being represented as a list of coefficients:
-   *
-   * Example: \include Array_initializer_list_23_cxx11.cpp
-   * Output: \verbinclude Array_initializer_list_23_cxx11.out
-   *
-   * Each of the inner initializer lists must contain the exact same number of elements, otherwise an assertion is
-   * triggered.
-   *
-   * In the case of a compile-time column 1D array, implicit transposition from a single row is allowed.
-   * Therefore <code> Array<int,Dynamic,1>{{1,2,3,4,5}}</code> is legal and the more verbose syntax
-   * <code>Array<int,Dynamic,1>{{1},{2},{3},{4},{5}}</code> can be avoided:
-   *
-   * Example: \include Array_initializer_list_vector_cxx11.cpp
-   * Output: \verbinclude Array_initializer_list_vector_cxx11.out
-   *
-   * In the case of fixed-sized arrays, the initializer list sizes must exactly match the array sizes,
-   * and implicit transposition is allowed for compile-time 1D arrays only.
-   *
-   * \sa  Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
-   */
-  EIGEN_DEVICE_FUNC constexpr Array(const std::initializer_list<std::initializer_list<Scalar>>& list) : Base(list) {}
+    /** Default constructor.
+      *
+      * For fixed-size matrices, does nothing.
+      *
+      * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
+      * is called a null matrix. This constructor is the unique way to create null matrices: resizing
+      * a matrix to 0 is not supported.
+      *
+      * \sa resize(Index,Index)
+      */
+    EIGEN_STRONG_INLINE Array() : Base()
+    {
+      Base::_check_template_params();
+      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-  template <typename T>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array(const T& x) {
-    Base::template _init1<T>(x);
-  }
-
-  template <typename T0, typename T1>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1) {
-    this->template _init2<T0, T1>(val0, val1);
-  }
-
-#else
-  /** \brief Constructs a fixed-sized array initialized with coefficients starting at \a data */
-  EIGEN_DEVICE_FUNC explicit Array(const Scalar* data);
-  /** Constructs a vector or row-vector with given dimension. \only_for_vectors
-   *
-   * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
-   * it is redundant to pass the dimension here, so it makes more sense to use the default
-   * constructor Array() instead.
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array(Index dim);
-  /** constructs an initialized 1x1 Array with the given coefficient
-   * \sa const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args */
-  Array(const Scalar& value);
-  /** constructs an uninitialized array with \a rows rows and \a cols columns.
-   *
-   * This is useful for dynamic-size arrays. For fixed-size arrays,
-   * it is redundant to pass these parameters, so one should use the default constructor
-   * Array() instead. */
-  Array(Index rows, Index cols);
-  /** constructs an initialized 2D vector with given coefficients
-   * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args) */
-  Array(const Scalar& val0, const Scalar& val1);
-#endif  // end EIGEN_PARSED_BY_DOXYGEN
-
-  /** constructs an initialized 3D vector with given coefficients
-   * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2) {
-    EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
-    m_storage.data()[0] = val0;
-    m_storage.data()[1] = val1;
-    m_storage.data()[2] = val2;
-  }
-  /** constructs an initialized 4D vector with given coefficients
-   * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2,
-                                              const Scalar& val3) {
-    EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
-    m_storage.data()[0] = val0;
-    m_storage.data()[1] = val1;
-    m_storage.data()[2] = val2;
-    m_storage.data()[3] = val3;
-  }
-
-  /** Copy constructor */
-  EIGEN_DEVICE_FUNC constexpr Array(const Array&) = default;
-
- private:
-  struct PrivateType {};
-
- public:
-  /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Array(
-      const EigenBase<OtherDerived>& other,
-      std::enable_if_t<internal::is_convertible<typename OtherDerived::Scalar, Scalar>::value, PrivateType> =
-          PrivateType())
-      : Base(other.derived()) {}
-
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return 1; }
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return this->innerSize(); }
-
-#ifdef EIGEN_ARRAY_PLUGIN
-#include EIGEN_ARRAY_PLUGIN
+    // FIXME is it still needed ??
+    /** \internal */
+    Array(internal::constructor_without_unaligned_array_assert)
+      : Base(internal::constructor_without_unaligned_array_assert())
+    {
+      Base::_check_template_params();
+      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    }
 #endif
 
- private:
-  template <typename MatrixType, typename OtherDerived, bool SwapPointers>
-  friend struct internal::matrix_swap_impl;
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
+    Array(Array&& other)
+      : Base(std::move(other))
+    {
+      Base::_check_template_params();
+      if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic)
+        Base::_set_noalias(other);
+    }
+    Array& operator=(Array&& other)
+    {
+      other.swap(*this);
+      return *this;
+    }
+#endif
+
+    /** Constructs a vector or row-vector with given dimension. \only_for_vectors
+      *
+      * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
+      * it is redundant to pass the dimension here, so it makes more sense to use the default
+      * constructor Matrix() instead.
+      */
+    EIGEN_STRONG_INLINE explicit Array(Index dim)
+      : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(Array)
+      eigen_assert(dim >= 0);
+      eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
+      EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename T0, typename T1>
+    EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
+    {
+      Base::_check_template_params();
+      this->template _init2<T0,T1>(val0, val1);
+    }
+    #else
+    /** constructs an uninitialized matrix with \a rows rows and \a cols columns.
+      *
+      * This is useful for dynamic-size matrices. For fixed-size matrices,
+      * it is redundant to pass these parameters, so one should use the default constructor
+      * Matrix() instead. */
+    Array(Index rows, Index cols);
+    /** constructs an initialized 2D vector with given coefficients */
+    Array(const Scalar& val0, const Scalar& val1);
+    #endif
+
+    /** constructs an initialized 3D vector with given coefficients */
+    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
+      m_storage.data()[0] = val0;
+      m_storage.data()[1] = val1;
+      m_storage.data()[2] = val2;
+    }
+    /** constructs an initialized 4D vector with given coefficients */
+    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
+      m_storage.data()[0] = val0;
+      m_storage.data()[1] = val1;
+      m_storage.data()[2] = val2;
+      m_storage.data()[3] = val3;
+    }
+
+    explicit Array(const Scalar *data);
+
+    /** Constructor copying the value of the expression \a other */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array(const ArrayBase<OtherDerived>& other)
+             : Base(other.rows() * other.cols(), other.rows(), other.cols())
+    {
+      Base::_check_template_params();
+      Base::_set_noalias(other);
+    }
+    /** Copy constructor */
+    EIGEN_STRONG_INLINE Array(const Array& other)
+            : Base(other.rows() * other.cols(), other.rows(), other.cols())
+    {
+      Base::_check_template_params();
+      Base::_set_noalias(other);
+    }
+    /** Copy constructor with in-place evaluation */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array(const ReturnByValue<OtherDerived>& other)
+    {
+      Base::_check_template_params();
+      Base::resize(other.rows(), other.cols());
+      other.evalTo(*this);
+    }
+
+    /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Array(const EigenBase<OtherDerived> &other)
+      : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
+    {
+      Base::_check_template_params();
+      Base::_resize_to_match(other);
+      *this = other;
+    }
+
+    /** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
+      * data pointers.
+      */
+    template<typename OtherDerived>
+    void swap(ArrayBase<OtherDerived> const & other)
+    { this->_swap(other.derived()); }
+
+    inline Index innerStride() const { return 1; }
+    inline Index outerStride() const { return this->innerSize(); }
+
+    #ifdef EIGEN_ARRAY_PLUGIN
+    #include EIGEN_ARRAY_PLUGIN
+    #endif
+
+  private:
+
+    template<typename MatrixType, typename OtherDerived, bool SwapPointers>
+    friend struct internal::matrix_swap_impl;
 };
 
 /** \defgroup arraytypedefs Global array typedefs
- * \ingroup Core_Module
- *
- * %Eigen defines several typedef shortcuts for most common 1D and 2D array types.
- *
- * The general patterns are the following:
- *
- * \c ArrayRowsColsType where \c Rows and \c Cols can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for
- * dynamic size, and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c
- * cd for complex double.
- *
- * For example, \c Array33d is a fixed-size 3x3 array type of doubles, and \c ArrayXXf is a dynamic-size matrix of
- * floats.
- *
- * There are also \c ArraySizeType which are self-explanatory. For example, \c Array4cf is
- * a fixed-size 1D array of 4 complex floats.
- *
- * With \cpp11, template alias are also defined for common sizes.
- * They follow the same pattern as above except that the scalar type suffix is replaced by a
- * template parameter, i.e.:
- *   - `ArrayRowsCols<Type>` where `Rows` and `Cols` can be \c 2,\c 3,\c 4, or \c X for fixed or dynamic size.
- *   - `ArraySize<Type>` where `Size` can be \c 2,\c 3,\c 4 or \c X for fixed or dynamic size 1D arrays.
- *
- * \sa class Array
- */
+  * \ingroup Core_Module
+  *
+  * Eigen defines several typedef shortcuts for most common 1D and 2D array types.
+  *
+  * The general patterns are the following:
+  *
+  * \c ArrayRowsColsType where \c Rows and \c Cols can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size,
+  * and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c cd
+  * for complex double.
+  *
+  * For example, \c Array33d is a fixed-size 3x3 array type of doubles, and \c ArrayXXf is a dynamic-size matrix of floats.
+  *
+  * There are also \c ArraySizeType which are self-explanatory. For example, \c Array4cf is
+  * a fixed-size 1D array of 4 complex floats.
+  *
+  * \sa class Array
+  */
 
-#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix)        \
-  /** \ingroup arraytypedefs */                                              \
-  typedef Array<Type, Size, Size> Array##SizeSuffix##SizeSuffix##TypeSuffix; \
-  /** \ingroup arraytypedefs */                                              \
-  typedef Array<Type, Size, 1> Array##SizeSuffix##TypeSuffix;
+#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix)   \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Size, Size> Array##SizeSuffix##SizeSuffix##TypeSuffix;  \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Size, 1>    Array##SizeSuffix##TypeSuffix;
 
-#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size)  \
-  /** \ingroup arraytypedefs */                                  \
-  typedef Array<Type, Size, Dynamic> Array##Size##X##TypeSuffix; \
-  /** \ingroup arraytypedefs */                                  \
-  typedef Array<Type, Dynamic, Size> Array##X##Size##TypeSuffix;
+#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size)         \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Size, Dynamic> Array##Size##X##TypeSuffix;  \
+/** \ingroup arraytypedefs */                                    \
+typedef Array<Type, Dynamic, Size> Array##X##Size##TypeSuffix;
 
 #define EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \
-  EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 2, 2)           \
-  EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 3, 3)           \
-  EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 4, 4)           \
-  EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Dynamic, X)     \
-  EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 2)        \
-  EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 3)        \
-  EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 4)
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 2, 2) \
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 3, 3) \
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 4, 4) \
+EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \
+EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \
+EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \
+EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 4)
 
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(int, i)
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(float, f)
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(double, d)
-EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<float>, cf)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(int,                  i)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(float,                f)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(double,               d)
+EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<float>,  cf)
 EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
 
 #undef EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES
 #undef EIGEN_MAKE_ARRAY_TYPEDEFS
-#undef EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS
 
-#define EIGEN_MAKE_ARRAY_TYPEDEFS(Size, SizeSuffix)              \
-  /** \ingroup arraytypedefs */                                  \
-  /** \brief \cpp11 */                                           \
-  template <typename Type>                                       \
-  using Array##SizeSuffix##SizeSuffix = Array<Type, Size, Size>; \
-  /** \ingroup arraytypedefs */                                  \
-  /** \brief \cpp11 */                                           \
-  template <typename Type>                                       \
-  using Array##SizeSuffix = Array<Type, Size, 1>;
-
-#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Size)        \
-  /** \ingroup arraytypedefs */                      \
-  /** \brief \cpp11 */                               \
-  template <typename Type>                           \
-  using Array##Size##X = Array<Type, Size, Dynamic>; \
-  /** \ingroup arraytypedefs */                      \
-  /** \brief \cpp11 */                               \
-  template <typename Type>                           \
-  using Array##X##Size = Array<Type, Dynamic, Size>;
-
-EIGEN_MAKE_ARRAY_TYPEDEFS(2, 2)
-EIGEN_MAKE_ARRAY_TYPEDEFS(3, 3)
-EIGEN_MAKE_ARRAY_TYPEDEFS(4, 4)
-EIGEN_MAKE_ARRAY_TYPEDEFS(Dynamic, X)
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(2)
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(3)
-EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(4)
-
-#undef EIGEN_MAKE_ARRAY_TYPEDEFS
-#undef EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS
+#undef EIGEN_MAKE_ARRAY_TYPEDEFS_LARGE
 
 #define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
-  using Eigen::Matrix##SizeSuffix##TypeSuffix;                               \
-  using Eigen::Vector##SizeSuffix##TypeSuffix;                               \
-  using Eigen::RowVector##SizeSuffix##TypeSuffix;
+using Eigen::Matrix##SizeSuffix##TypeSuffix; \
+using Eigen::Vector##SizeSuffix##TypeSuffix; \
+using Eigen::RowVector##SizeSuffix##TypeSuffix;
 
-#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(TypeSuffix)       \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X)
+#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(TypeSuffix) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
 
-#define EIGEN_USING_ARRAY_TYPEDEFS        \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(i)  \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(f)  \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d)  \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \
-  EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd)
+#define EIGEN_USING_ARRAY_TYPEDEFS \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(i) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(f) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \
+EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd)
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_ARRAY_H
+#endif // EIGEN_ARRAY_H

Eigen/src/Core/ArrayBase.h

@@ -10,201 +10,217 @@
 #ifndef EIGEN_ARRAYBASE_H
 #define EIGEN_ARRAYBASE_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+namespace Eigen { 
 
-namespace Eigen {
-
-template <typename ExpressionType>
-class MatrixWrapper;
+template<typename ExpressionType> class MatrixWrapper;
 
 /** \class ArrayBase
- * \ingroup Core_Module
- *
- * \brief Base class for all 1D and 2D array, and related expressions
- *
- * An array is similar to a dense vector or matrix. While matrices are mathematical
- * objects with well defined linear algebra operators, an array is just a collection
- * of scalar values arranged in a one or two dimensional fashion. As the main consequence,
- * all operations applied to an array are performed coefficient wise. Furthermore,
- * arrays support scalar math functions of the c++ standard library (e.g., std::sin(x)), and convenient
- * constructors allowing to easily write generic code working for both scalar values
- * and arrays.
- *
- * This class is the base that is inherited by all array expression types.
- *
- * \tparam Derived is the derived type, e.g., an array or an expression type.
- *
- * This class can be extended with the help of the plugin mechanism described on the page
- * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN.
- *
- * \sa class MatrixBase, \ref TopicClassHierarchy
- */
-template <typename Derived>
-class ArrayBase : public DenseBase<Derived> {
- public:
+  * \ingroup Core_Module
+  *
+  * \brief Base class for all 1D and 2D array, and related expressions
+  *
+  * An array is similar to a dense vector or matrix. While matrices are mathematical
+  * objects with well defined linear algebra operators, an array is just a collection
+  * of scalar values arranged in a one or two dimensionnal fashion. As the main consequence,
+  * all operations applied to an array are performed coefficient wise. Furthermore,
+  * arrays support scalar math functions of the c++ standard library (e.g., std::sin(x)), and convenient
+  * constructors allowing to easily write generic code working for both scalar values
+  * and arrays.
+  *
+  * This class is the base that is inherited by all array expression types.
+  *
+  * \tparam Derived is the derived type, e.g., an array or an expression type.
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN.
+  *
+  * \sa class MatrixBase, \ref TopicClassHierarchy
+  */
+template<typename Derived> class ArrayBase
+  : public DenseBase<Derived>
+{
+  public:
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-  /** The base class for a given storage type. */
-  typedef ArrayBase StorageBaseType;
+    /** The base class for a given storage type. */
+    typedef ArrayBase StorageBaseType;
 
-  typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl;
+    typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl;
 
-  typedef typename internal::traits<Derived>::StorageKind StorageKind;
-  typedef typename internal::traits<Derived>::Scalar Scalar;
-  typedef typename internal::packet_traits<Scalar>::type PacketScalar;
-  typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
 
-  typedef DenseBase<Derived> Base;
-  using Base::ColsAtCompileTime;
-  using Base::Flags;
-  using Base::IsVectorAtCompileTime;
-  using Base::MaxColsAtCompileTime;
-  using Base::MaxRowsAtCompileTime;
-  using Base::MaxSizeAtCompileTime;
-  using Base::RowsAtCompileTime;
-  using Base::SizeAtCompileTime;
+    typedef DenseBase<Derived> Base;
+    using Base::operator*;
+    using Base::RowsAtCompileTime;
+    using Base::ColsAtCompileTime;
+    using Base::SizeAtCompileTime;
+    using Base::MaxRowsAtCompileTime;
+    using Base::MaxColsAtCompileTime;
+    using Base::MaxSizeAtCompileTime;
+    using Base::IsVectorAtCompileTime;
+    using Base::Flags;
+    using Base::CoeffReadCost;
 
-  using Base::coeff;
-  using Base::coeffRef;
-  using Base::cols;
-  using Base::const_cast_derived;
-  using Base::derived;
-  using Base::lazyAssign;
-  using Base::rows;
-  using Base::size;
-  using Base::operator-;
-  using Base::operator=;
-  using Base::operator+=;
-  using Base::operator-=;
-  using Base::operator*=;
-  using Base::operator/=;
+    using Base::derived;
+    using Base::const_cast_derived;
+    using Base::rows;
+    using Base::cols;
+    using Base::size;
+    using Base::coeff;
+    using Base::coeffRef;
+    using Base::lazyAssign;
+    using Base::operator=;
+    using Base::operator+=;
+    using Base::operator-=;
+    using Base::operator*=;
+    using Base::operator/=;
 
-  typedef typename Base::CoeffReturnType CoeffReturnType;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
 
-  typedef typename Base::PlainObject PlainObject;
+#endif // not EIGEN_PARSED_BY_DOXYGEN
 
-  /** \internal Represents a matrix with all coefficients equal to one another*/
-  typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> ConstantReturnType;
-#endif  // not EIGEN_PARSED_BY_DOXYGEN
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal the plain matrix type corresponding to this expression. Note that is not necessarily
+      * exactly the return type of eval(): in the case of plain matrices, the return type of eval() is a const
+      * reference to a matrix, not a matrix! It is however guaranteed that the return type of eval() is either
+      * PlainObject or const PlainObject&.
+      */
+    typedef Array<typename internal::traits<Derived>::Scalar,
+                internal::traits<Derived>::RowsAtCompileTime,
+                internal::traits<Derived>::ColsAtCompileTime,
+                AutoAlign | (internal::traits<Derived>::Flags&RowMajorBit ? RowMajor : ColMajor),
+                internal::traits<Derived>::MaxRowsAtCompileTime,
+                internal::traits<Derived>::MaxColsAtCompileTime
+          > PlainObject;
+
+
+    /** \internal Represents a matrix with all coefficients equal to one another*/
+    typedef CwiseNullaryOp<internal::scalar_constant_op<Scalar>,Derived> ConstantReturnType;
+#endif // not EIGEN_PARSED_BY_DOXYGEN
 
 #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase
-#define EIGEN_DOC_UNARY_ADDONS(X, Y)
-#include "../plugins/MatrixCwiseUnaryOps.inc"
-#include "../plugins/ArrayCwiseUnaryOps.inc"
-#include "../plugins/CommonCwiseBinaryOps.inc"
-#include "../plugins/MatrixCwiseBinaryOps.inc"
-#include "../plugins/ArrayCwiseBinaryOps.inc"
-#ifdef EIGEN_ARRAYBASE_PLUGIN
-#include EIGEN_ARRAYBASE_PLUGIN
-#endif
+#   include "../plugins/CommonCwiseUnaryOps.h"
+#   include "../plugins/MatrixCwiseUnaryOps.h"
+#   include "../plugins/ArrayCwiseUnaryOps.h"
+#   include "../plugins/CommonCwiseBinaryOps.h"
+#   include "../plugins/MatrixCwiseBinaryOps.h"
+#   include "../plugins/ArrayCwiseBinaryOps.h"
+#   ifdef EIGEN_ARRAYBASE_PLUGIN
+#     include EIGEN_ARRAYBASE_PLUGIN
+#   endif
 #undef EIGEN_CURRENT_STORAGE_BASE_CLASS
-#undef EIGEN_DOC_UNARY_ADDONS
 
-  /** Special case of the template operator=, in order to prevent the compiler
-   * from generating a default operator= (issue hit with g++ 4.1)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const ArrayBase& other) {
-    internal::call_assignment(derived(), other.derived());
-    return derived();
-  }
+    /** Special case of the template operator=, in order to prevent the compiler
+      * from generating a default operator= (issue hit with g++ 4.1)
+      */
+    Derived& operator=(const ArrayBase& other)
+    {
+      return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
+    }
 
-  /** Set all the entries to \a value.
-   * \sa DenseBase::setConstant(), DenseBase::fill() */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const Scalar& value) {
-    Base::setConstant(value);
-    return derived();
-  }
+    Derived& operator+=(const Scalar& scalar)
+    { return *this = derived() + scalar; }
+    Derived& operator-=(const Scalar& scalar)
+    { return *this = derived() - scalar; }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const Scalar& other) {
-    internal::call_assignment(this->derived(), PlainObject::Constant(rows(), cols(), other),
-                              internal::add_assign_op<Scalar, Scalar>());
-    return derived();
-  }
+    template<typename OtherDerived>
+    Derived& operator+=(const ArrayBase<OtherDerived>& other);
+    template<typename OtherDerived>
+    Derived& operator-=(const ArrayBase<OtherDerived>& other);
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const Scalar& other) {
-    internal::call_assignment(this->derived(), PlainObject::Constant(rows(), cols(), other),
-                              internal::sub_assign_op<Scalar, Scalar>());
-    return derived();
-  }
+    template<typename OtherDerived>
+    Derived& operator*=(const ArrayBase<OtherDerived>& other);
 
-  /** replaces \c *this by \c *this + \a other.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
+    template<typename OtherDerived>
+    Derived& operator/=(const ArrayBase<OtherDerived>& other);
 
-  /** replaces \c *this by \c *this - \a other.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
+  public:
+    ArrayBase<Derived>& array() { return *this; }
+    const ArrayBase<Derived>& array() const { return *this; }
 
-  /** replaces \c *this by \c *this * \a other coefficient wise.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::mul_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
+    /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
+      * \sa MatrixBase::array() */
+    MatrixWrapper<Derived> matrix() { return derived(); }
+    const MatrixWrapper<const Derived> matrix() const { return derived(); }
 
-  /** replaces \c *this by \c *this / \a other coefficient wise.
-   *
-   * \returns a reference to \c *this
-   */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const ArrayBase<OtherDerived>& other) {
-    call_assignment(derived(), other.derived(), internal::div_assign_op<Scalar, typename OtherDerived::Scalar>());
-    return derived();
-  }
+//     template<typename Dest>
+//     inline void evalTo(Dest& dst) const { dst = matrix(); }
 
- public:
-  EIGEN_DEVICE_FUNC constexpr ArrayBase<Derived>& array() { return *this; }
-  EIGEN_DEVICE_FUNC constexpr const ArrayBase<Derived>& array() const { return *this; }
+  protected:
+    ArrayBase() : Base() {}
 
-  /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array
-   * \sa MatrixBase::array() */
-  EIGEN_DEVICE_FUNC constexpr MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); }
-  EIGEN_DEVICE_FUNC constexpr const MatrixWrapper<const Derived> matrix() const {
-    return MatrixWrapper<const Derived>(derived());
-  }
-
- protected:
-  EIGEN_DEFAULT_COPY_CONSTRUCTOR(ArrayBase)
-  EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(ArrayBase)
-
- private:
-  explicit ArrayBase(Index);
-  ArrayBase(Index, Index);
-  template <typename OtherDerived>
-  explicit ArrayBase(const ArrayBase<OtherDerived>&);
-
- protected:
-  // mixing arrays and matrices is not legal
-  template <typename OtherDerived>
-  Derived& operator+=(const MatrixBase<OtherDerived>&) {
-    EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1,
-                        YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);
-    return *this;
-  }
-  // mixing arrays and matrices is not legal
-  template <typename OtherDerived>
-  Derived& operator-=(const MatrixBase<OtherDerived>&) {
-    EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1,
-                        YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);
-    return *this;
-  }
+  private:
+    explicit ArrayBase(Index);
+    ArrayBase(Index,Index);
+    template<typename OtherDerived> explicit ArrayBase(const ArrayBase<OtherDerived>&);
+  protected:
+    // mixing arrays and matrices is not legal
+    template<typename OtherDerived> Derived& operator+=(const MatrixBase<OtherDerived>& )
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
+    // mixing arrays and matrices is not legal
+    template<typename OtherDerived> Derived& operator-=(const MatrixBase<OtherDerived>& )
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
 };
 
-}  // end namespace Eigen
+/** replaces \c *this by \c *this - \a other.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator-=(const ArrayBase<OtherDerived> &other)
+{
+  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
 
-#endif  // EIGEN_ARRAYBASE_H
+/** replaces \c *this by \c *this + \a other.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator+=(const ArrayBase<OtherDerived>& other)
+{
+  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
+
+/** replaces \c *this by \c *this * \a other coefficient wise.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator*=(const ArrayBase<OtherDerived>& other)
+{
+  SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
+
+/** replaces \c *this by \c *this / \a other coefficient wise.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
+{
+  SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
+  return derived();
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_ARRAYBASE_H

Eigen/src/Core/ArrayWrapper.h

@@ -10,157 +10,255 @@
 #ifndef EIGEN_ARRAYWRAPPER_H
 #define EIGEN_ARRAYWRAPPER_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
+namespace Eigen { 
 
 /** \class ArrayWrapper
- * \ingroup Core_Module
- *
- * \brief Expression of a mathematical vector or matrix as an array object
- *
- * This class is the return type of MatrixBase::array(), and most of the time
- * this is the only way it is used.
- *
- * \sa MatrixBase::array(), class MatrixWrapper
- */
+  * \ingroup Core_Module
+  *
+  * \brief Expression of a mathematical vector or matrix as an array object
+  *
+  * This class is the return type of MatrixBase::array(), and most of the time
+  * this is the only way it is use.
+  *
+  * \sa MatrixBase::array(), class MatrixWrapper
+  */
 
 namespace internal {
-template <typename ExpressionType>
-struct traits<ArrayWrapper<ExpressionType> > : public traits<remove_all_t<typename ExpressionType::Nested> > {
+template<typename ExpressionType>
+struct traits<ArrayWrapper<ExpressionType> >
+  : public traits<typename remove_all<typename ExpressionType::Nested>::type >
+{
   typedef ArrayXpr XprKind;
   // Let's remove NestByRefBit
   enum {
-    Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
-    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
-    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
+    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags = Flags0 & ~NestByRefBit
   };
 };
-}  // namespace internal
+}
 
-template <typename ExpressionType>
-class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> > {
- public:
-  typedef ArrayBase<ArrayWrapper> Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
-  typedef internal::remove_all_t<ExpressionType> NestedExpression;
+template<typename ExpressionType>
+class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
+{
+  public:
+    typedef ArrayBase<ArrayWrapper> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper)
 
-  typedef std::conditional_t<internal::is_lvalue<ExpressionType>::value, Scalar, const Scalar>
-      ScalarWithConstIfNotLvalue;
+    typedef typename internal::conditional<
+                       internal::is_lvalue<ExpressionType>::value,
+                       Scalar,
+                       const Scalar
+                     >::type ScalarWithConstIfNotLvalue;
 
-  typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
+    typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
 
-  using Base::coeffRef;
+    inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
 
-  EIGEN_DEVICE_FUNC constexpr explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix)
-      : m_expression(matrix) {}
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
 
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); }
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); }
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); }
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
+    inline const Scalar* data() const { return m_expression.data(); }
 
-  EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-  EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); }
+    inline CoeffReturnType coeff(Index rowId, Index colId) const
+    {
+      return m_expression.coeff(rowId, colId);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
-    return m_expression.coeffRef(rowId, colId);
-  }
+    inline Scalar& coeffRef(Index rowId, Index colId)
+    {
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
+    {
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
+    }
 
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC inline void evalTo(Dest& dst) const {
-    dst = m_expression;
-  }
+    inline CoeffReturnType coeff(Index index) const
+    {
+      return m_expression.coeff(index);
+    }
 
-  EIGEN_DEVICE_FUNC constexpr const internal::remove_all_t<NestedExpressionType>& nestedExpression() const {
-    return m_expression;
-  }
+    inline Scalar& coeffRef(Index index)
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
 
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index)  */
-  EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); }
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index,Index)*/
-  EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); }
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
 
- protected:
-  NestedExpressionType m_expression;
+    template<int LoadMode>
+    inline const PacketScalar packet(Index rowId, Index colId) const
+    {
+      return m_expression.template packet<LoadMode>(rowId, colId);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index index) const
+    {
+      return m_expression.template packet<LoadMode>(index);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index index, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
+    }
+
+    template<typename Dest>
+    inline void evalTo(Dest& dst) const { dst = m_expression; }
+
+    const typename internal::remove_all<NestedExpressionType>::type& 
+    nestedExpression() const 
+    {
+      return m_expression;
+    }
+
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index)  */
+    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index,Index)*/
+    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
+  protected:
+    NestedExpressionType m_expression;
 };
 
 /** \class MatrixWrapper
- * \ingroup Core_Module
- *
- * \brief Expression of an array as a mathematical vector or matrix
- *
- * This class is the return type of ArrayBase::matrix(), and most of the time
- * this is the only way it is used.
- *
- * \sa MatrixBase::matrix(), class ArrayWrapper
- */
+  * \ingroup Core_Module
+  *
+  * \brief Expression of an array as a mathematical vector or matrix
+  *
+  * This class is the return type of ArrayBase::matrix(), and most of the time
+  * this is the only way it is use.
+  *
+  * \sa MatrixBase::matrix(), class ArrayWrapper
+  */
 
 namespace internal {
-template <typename ExpressionType>
-struct traits<MatrixWrapper<ExpressionType> > : public traits<remove_all_t<typename ExpressionType::Nested> > {
+template<typename ExpressionType>
+struct traits<MatrixWrapper<ExpressionType> >
+ : public traits<typename remove_all<typename ExpressionType::Nested>::type >
+{
   typedef MatrixXpr XprKind;
   // Let's remove NestByRefBit
   enum {
-    Flags0 = traits<remove_all_t<typename ExpressionType::Nested> >::Flags,
-    LvalueBitFlag = is_lvalue<ExpressionType>::value ? LvalueBit : 0,
-    Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag
+    Flags0 = traits<typename remove_all<typename ExpressionType::Nested>::type >::Flags,
+    Flags = Flags0 & ~NestByRefBit
   };
 };
-}  // namespace internal
+}
 
-template <typename ExpressionType>
-class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> > {
- public:
-  typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
-  typedef internal::remove_all_t<ExpressionType> NestedExpression;
+template<typename ExpressionType>
+class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
+{
+  public:
+    typedef MatrixBase<MatrixWrapper<ExpressionType> > Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper)
 
-  typedef std::conditional_t<internal::is_lvalue<ExpressionType>::value, Scalar, const Scalar>
-      ScalarWithConstIfNotLvalue;
+    typedef typename internal::conditional<
+                       internal::is_lvalue<ExpressionType>::value,
+                       Scalar,
+                       const Scalar
+                     >::type ScalarWithConstIfNotLvalue;
 
-  typedef typename internal::ref_selector<ExpressionType>::non_const_type NestedExpressionType;
+    typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
 
-  using Base::coeffRef;
+    inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
 
-  EIGEN_DEVICE_FUNC constexpr explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
+    inline Index rows() const { return m_expression.rows(); }
+    inline Index cols() const { return m_expression.cols(); }
+    inline Index outerStride() const { return m_expression.outerStride(); }
+    inline Index innerStride() const { return m_expression.innerStride(); }
 
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); }
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); }
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); }
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
+    inline const Scalar* data() const { return m_expression.data(); }
 
-  EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-  EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); }
+    inline CoeffReturnType coeff(Index rowId, Index colId) const
+    {
+      return m_expression.coeff(rowId, colId);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
-    return m_expression.derived().coeffRef(rowId, colId);
-  }
+    inline Scalar& coeffRef(Index rowId, Index colId)
+    {
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
+    {
+      return m_expression.derived().coeffRef(rowId, colId);
+    }
 
-  EIGEN_DEVICE_FUNC constexpr const internal::remove_all_t<NestedExpressionType>& nestedExpression() const {
-    return m_expression;
-  }
+    inline CoeffReturnType coeff(Index index) const
+    {
+      return m_expression.coeff(index);
+    }
 
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index)  */
-  EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); }
-  /** Forwards the resizing request to the nested expression
-   * \sa DenseBase::resize(Index,Index)*/
-  EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); }
+    inline Scalar& coeffRef(Index index)
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
 
- protected:
-  NestedExpressionType m_expression;
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_expression.const_cast_derived().coeffRef(index);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index rowId, Index colId) const
+    {
+      return m_expression.template packet<LoadMode>(rowId, colId);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
+    }
+
+    template<int LoadMode>
+    inline const PacketScalar packet(Index index) const
+    {
+      return m_expression.template packet<LoadMode>(index);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index index, const PacketScalar& val)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
+    }
+
+    const typename internal::remove_all<NestedExpressionType>::type& 
+    nestedExpression() const 
+    {
+      return m_expression;
+    }
+
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index)  */
+    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index,Index)*/
+    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
+  protected:
+    NestedExpressionType m_expression;
 };
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_ARRAYWRAPPER_H
+#endif // EIGEN_ARRAYWRAPPER_H

Eigen/src/Core/Assign.h

@@ -12,73 +12,579 @@
 #ifndef EIGEN_ASSIGN_H
 #define EIGEN_ASSIGN_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
 namespace Eigen {
 
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::lazyAssign(
-    const DenseBase<OtherDerived>& other) {
-  enum { SameType = internal::is_same<typename Derived::Scalar, typename OtherDerived::Scalar>::value };
+namespace internal {
+
+/***************************************************************************
+* Part 1 : the logic deciding a strategy for traversal and unrolling       *
+***************************************************************************/
+
+template <typename Derived, typename OtherDerived>
+struct assign_traits
+{
+public:
+  enum {
+    DstIsAligned = Derived::Flags & AlignedBit,
+    DstHasDirectAccess = Derived::Flags & DirectAccessBit,
+    SrcIsAligned = OtherDerived::Flags & AlignedBit,
+    JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned
+  };
+
+private:
+  enum {
+    InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
+              : int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
+              : int(Derived::RowsAtCompileTime),
+    InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
+              : int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
+              : int(Derived::MaxRowsAtCompileTime),
+    MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
+    PacketSize = packet_traits<typename Derived::Scalar>::size
+  };
+
+  enum {
+    StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
+    MightVectorize = StorageOrdersAgree
+                  && (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
+    MayInnerVectorize  = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
+                       && int(DstIsAligned) && int(SrcIsAligned),
+    MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
+    MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
+                       && (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
+      /* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
+         so it's only good for large enough sizes. */
+    MaySliceVectorize  = MightVectorize && DstHasDirectAccess
+                       && (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
+      /* slice vectorization can be slow, so we only want it if the slices are big, which is
+         indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
+         in a fixed-size matrix */
+  };
+
+public:
+  enum {
+    Traversal = int(MayInnerVectorize)  ? int(InnerVectorizedTraversal)
+              : int(MayLinearVectorize) ? int(LinearVectorizedTraversal)
+              : int(MaySliceVectorize)  ? int(SliceVectorizedTraversal)
+              : int(MayLinearize)       ? int(LinearTraversal)
+                                        : int(DefaultTraversal),
+    Vectorized = int(Traversal) == InnerVectorizedTraversal
+              || int(Traversal) == LinearVectorizedTraversal
+              || int(Traversal) == SliceVectorizedTraversal
+  };
+
+private:
+  enum {
+    UnrollingLimit      = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
+    MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
+                       && int(OtherDerived::CoeffReadCost) != Dynamic
+                       && int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
+    MayUnrollInner      = int(InnerSize) != Dynamic
+                       && int(OtherDerived::CoeffReadCost) != Dynamic
+                       && int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
+  };
+
+public:
+  enum {
+    Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
+                ? (
+                    int(MayUnrollCompletely) ? int(CompleteUnrolling)
+                  : int(MayUnrollInner)      ? int(InnerUnrolling)
+                                             : int(NoUnrolling)
+                  )
+              : int(Traversal) == int(LinearVectorizedTraversal)
+                ? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling) : int(NoUnrolling) )
+              : int(Traversal) == int(LinearTraversal)
+                ? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) : int(NoUnrolling) )
+              : int(NoUnrolling)
+  };
+
+#ifdef EIGEN_DEBUG_ASSIGN
+  static void debug()
+  {
+    EIGEN_DEBUG_VAR(DstIsAligned)
+    EIGEN_DEBUG_VAR(SrcIsAligned)
+    EIGEN_DEBUG_VAR(JointAlignment)
+    EIGEN_DEBUG_VAR(InnerSize)
+    EIGEN_DEBUG_VAR(InnerMaxSize)
+    EIGEN_DEBUG_VAR(PacketSize)
+    EIGEN_DEBUG_VAR(StorageOrdersAgree)
+    EIGEN_DEBUG_VAR(MightVectorize)
+    EIGEN_DEBUG_VAR(MayLinearize)
+    EIGEN_DEBUG_VAR(MayInnerVectorize)
+    EIGEN_DEBUG_VAR(MayLinearVectorize)
+    EIGEN_DEBUG_VAR(MaySliceVectorize)
+    EIGEN_DEBUG_VAR(Traversal)
+    EIGEN_DEBUG_VAR(UnrollingLimit)
+    EIGEN_DEBUG_VAR(MayUnrollCompletely)
+    EIGEN_DEBUG_VAR(MayUnrollInner)
+    EIGEN_DEBUG_VAR(Unrolling)
+  }
+#endif
+};
+
+/***************************************************************************
+* Part 2 : meta-unrollers
+***************************************************************************/
+
+/************************
+*** Default traversal ***
+************************/
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct assign_DefaultTraversal_CompleteUnrolling
+{
+  enum {
+    outer = Index / Derived1::InnerSizeAtCompileTime,
+    inner = Index % Derived1::InnerSizeAtCompileTime
+  };
+
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    dst.copyCoeffByOuterInner(outer, inner, src);
+    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
+};
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct assign_DefaultTraversal_InnerUnrolling
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
+  {
+    dst.copyCoeffByOuterInner(outer, Index, src);
+    assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, outer);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
+};
+
+/***********************
+*** Linear traversal ***
+***********************/
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct assign_LinearTraversal_CompleteUnrolling
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    dst.copyCoeff(Index, src);
+    assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct assign_innervec_CompleteUnrolling
+{
+  enum {
+    outer = Index / Derived1::InnerSizeAtCompileTime,
+    inner = Index % Derived1::InnerSizeAtCompileTime,
+    JointAlignment = assign_traits<Derived1,Derived2>::JointAlignment
+  };
+
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    dst.template copyPacketByOuterInner<Derived2, Aligned, JointAlignment>(outer, inner, src);
+    assign_innervec_CompleteUnrolling<Derived1, Derived2,
+      Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
+};
+
+template<typename Derived1, typename Derived2, int Index, int Stop>
+struct assign_innervec_InnerUnrolling
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer)
+  {
+    dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, Index, src);
+    assign_innervec_InnerUnrolling<Derived1, Derived2,
+      Index+packet_traits<typename Derived1::Scalar>::size, Stop>::run(dst, src, outer);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Stop>
+struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {}
+};
+
+/***************************************************************************
+* Part 3 : implementation of all cases
+***************************************************************************/
+
+template<typename Derived1, typename Derived2,
+         int Traversal = assign_traits<Derived1, Derived2>::Traversal,
+         int Unrolling = assign_traits<Derived1, Derived2>::Unrolling,
+         int Version = Specialized>
+struct assign_impl;
+
+/************************
+*** Default traversal ***
+************************/
+
+template<typename Derived1, typename Derived2, int Unrolling, int Version>
+struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling, Version>
+{
+  static inline void run(Derived1 &, const Derived2 &) { }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
+  {
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; ++inner)
+        dst.copyCoeffByOuterInner(outer, inner, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling, Version>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+      ::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
+        ::run(dst, src, outer);
+  }
+};
+
+/***********************
+*** Linear traversal ***
+***********************/
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
+  {
+    const Index size = dst.size();
+    for(Index i = 0; i < size; ++i)
+      dst.copyCoeff(i, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Version>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+      ::run(dst, src);
+  }
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
+  {
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index packetSize = packet_traits<typename Derived1::Scalar>::size;
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; inner+=packetSize)
+        dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, inner, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling, Version>
+{
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
+      ::run(dst, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      assign_innervec_InnerUnrolling<Derived1, Derived2, 0, Derived1::InnerSizeAtCompileTime>
+        ::run(dst, src, outer);
+  }
+};
+
+/***************************
+*** Linear vectorization ***
+***************************/
+
+template <bool IsAligned = false>
+struct unaligned_assign_impl
+{
+  template <typename Derived, typename OtherDerived>
+  static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, typename Derived::Index, typename Derived::Index) {}
+};
+
+template <>
+struct unaligned_assign_impl<false>
+{
+  // MSVC must not inline this functions. If it does, it fails to optimize the
+  // packet access path.
+#ifdef _MSC_VER
+  template <typename Derived, typename OtherDerived>
+  static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
+#else
+  template <typename Derived, typename OtherDerived>
+  static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end)
+#endif
+  {
+    for (typename Derived::Index index = start; index < end; ++index)
+      dst.copyCoeff(index, src);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    const Index size = dst.size();
+    typedef packet_traits<typename Derived1::Scalar> PacketTraits;
+    enum {
+      packetSize = PacketTraits::size,
+      dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
+      srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
+    };
+    const Index alignedStart = assign_traits<Derived1,Derived2>::DstIsAligned ? 0
+                             : internal::first_aligned(&dst.coeffRef(0), size);
+    const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
+
+    unaligned_assign_impl<assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
+
+    for(Index index = alignedStart; index < alignedEnd; index += packetSize)
+    {
+      dst.template copyPacket<Derived2, dstAlignment, srcAlignment>(index, src);
+    }
+
+    unaligned_assign_impl<>::run(src,dst,alignedEnd,size);
+  }
+};
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  {
+    enum { size = Derived1::SizeAtCompileTime,
+           packetSize = packet_traits<typename Derived1::Scalar>::size,
+           alignedSize = (size/packetSize)*packetSize };
+
+    assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, alignedSize>::run(dst, src);
+    assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, alignedSize, size>::run(dst, src);
+  }
+};
+
+/**************************
+*** Slice vectorization ***
+***************************/
+
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Version>
+{
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1 &dst, const Derived2 &src)
+  {
+    typedef typename Derived1::Scalar Scalar;
+    typedef packet_traits<Scalar> PacketTraits;
+    enum {
+      packetSize = PacketTraits::size,
+      alignable = PacketTraits::AlignedOnScalar,
+      dstIsAligned = assign_traits<Derived1,Derived2>::DstIsAligned,
+      dstAlignment = alignable ? Aligned : int(dstIsAligned),
+      srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
+    };
+    const Scalar *dst_ptr = &dst.coeffRef(0,0);
+    if((!bool(dstIsAligned)) && (size_t(dst_ptr) % sizeof(Scalar))>0)
+    {
+      // the pointer is not aligend-on scalar, so alignment is not possible
+      return assign_impl<Derived1,Derived2,DefaultTraversal,NoUnrolling>::run(dst, src);
+    }
+    const Index packetAlignedMask = packetSize - 1;
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
+    Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned(dst_ptr, innerSize);
+
+    for(Index outer = 0; outer < outerSize; ++outer)
+    {
+      const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
+      // do the non-vectorizable part of the assignment
+      for(Index inner = 0; inner<alignedStart ; ++inner)
+        dst.copyCoeffByOuterInner(outer, inner, src);
+
+      // do the vectorizable part of the assignment
+      for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize)
+        dst.template copyPacketByOuterInner<Derived2, dstAlignment, Unaligned>(outer, inner, src);
+
+      // do the non-vectorizable part of the assignment
+      for(Index inner = alignedEnd; inner<innerSize ; ++inner)
+        dst.copyCoeffByOuterInner(outer, inner, src);
+
+      alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
+    }
+  }
+};
+
+} // end namespace internal
+
+/***************************************************************************
+* Part 4 : implementation of DenseBase methods
+***************************************************************************/
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>
+  ::lazyAssign(const DenseBase<OtherDerived>& other)
+{
+  enum{
+    SameType = internal::is_same<typename Derived::Scalar,typename OtherDerived::Scalar>::value
+  };
 
   EIGEN_STATIC_ASSERT_LVALUE(Derived)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived, OtherDerived)
-  EIGEN_STATIC_ASSERT(
-      SameType,
-      YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
+  EIGEN_STATIC_ASSERT(SameType,YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
+#ifdef EIGEN_DEBUG_ASSIGN
+  internal::assign_traits<Derived, OtherDerived>::debug();
+#endif
   eigen_assert(rows() == other.rows() && cols() == other.cols());
-  internal::call_assignment_no_alias(derived(), other.derived());
-
+  internal::assign_impl<Derived, OtherDerived, int(SameType) ? int(internal::assign_traits<Derived, OtherDerived>::Traversal)
+                                                       : int(InvalidTraversal)>::run(derived(),other.derived());
+#ifndef EIGEN_NO_DEBUG
+  checkTransposeAliasing(other.derived());
+#endif
   return derived();
 }
 
-template <typename Derived>
+namespace internal {
+
+template<typename Derived, typename OtherDerived,
+         bool EvalBeforeAssigning = (int(internal::traits<OtherDerived>::Flags) & EvalBeforeAssigningBit) != 0,
+         bool NeedToTranspose = ((int(Derived::RowsAtCompileTime) == 1 && int(OtherDerived::ColsAtCompileTime) == 1)
+                              |   // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
+                                  // revert to || as soon as not needed anymore.
+                                  (int(Derived::ColsAtCompileTime) == 1 && int(OtherDerived::RowsAtCompileTime) == 1))
+                              && int(Derived::SizeAtCompileTime) != 1>
+struct assign_selector;
+
+template<typename Derived, typename OtherDerived>
+struct assign_selector<Derived,OtherDerived,false,false> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
+  template<typename ActualDerived, typename ActualOtherDerived>
+  static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { other.evalTo(dst); return dst; }
+};
+template<typename Derived, typename OtherDerived>
+struct assign_selector<Derived,OtherDerived,true,false> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
+};
+template<typename Derived, typename OtherDerived>
+struct assign_selector<Derived,OtherDerived,false,true> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
+  template<typename ActualDerived, typename ActualOtherDerived>
+  static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { Transpose<ActualDerived> dstTrans(dst); other.evalTo(dstTrans); return dst; }
+};
+template<typename Derived, typename OtherDerived>
+struct assign_selector<Derived,OtherDerived,true,true> {
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
+};
+
+} // end namespace internal
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
+{
+  return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other)
+{
+  return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other)
+{
+  return internal::assign_selector<Derived,Derived>::run(derived(), other.derived());
+}
+
+template<typename Derived>
 template <typename OtherDerived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(
-    const DenseBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other)
+{
+  return internal::assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
 }
 
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
+template<typename Derived>
 template <typename OtherDerived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(
-    const DenseBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
+{
+  return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
 }
 
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(
-    const EigenBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
+{
+  return internal::assign_selector<Derived,OtherDerived,false>::evalTo(derived(), other.derived());
 }
 
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(
-    const ReturnByValue<OtherDerived>& other) {
-  other.derived().evalTo(derived());
-  return derived();
-}
+} // end namespace Eigen
 
-}  // end namespace Eigen
-
-#endif  // EIGEN_ASSIGN_H
+#endif // EIGEN_ASSIGN_H

Eigen/src/Core/Assign_AOCL.h

@@ -1,301 +0,0 @@
-/*
- * This Source Code Form is subject to the terms of the Mozilla Public
- * License, v. 2.0. If a copy of the MPL was not distributed with this
- * file, You can obtain one at https://mozilla.org/MPL/2.0/.
- *
- * Assign_AOCL.h - AOCL Vectorized Math Dispatch Layer for Eigen
- *
- * Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
- *
- * Description:
- * ------------
- * This file implements a high-performance dispatch layer that automatically
- * routes Eigen's element-wise mathematical operations to AMD Optimizing CPU
- * Libraries (AOCL) Vector Math Library (VML) functions when beneficial for
- * performance.
- *
- * The dispatch system uses C++ template specialization to intercept Eigen's
- * assignment operations and redirect them to AOCL's VRDA functions, which
- * provide optimized implementations for AMD Zen architectures.
- *
- * Key Features:
- * -------------
- * 1. Automatic Dispatch: Seamlessly routes supported operations to AOCL without
- *    requiring code changes in user applications
- *
- * 2. Performance Optimization: Uses AOCL VRDA functions optimized for Zen
- * family processors with automatic SIMD instruction selection (AVX2, AVX-512)
- *
- * 3. Threshold-Based Activation: Only activates for vectors larger than
- *    EIGEN_AOCL_VML_THRESHOLD (default: 128 elements) to avoid overhead on
- * small vectors
- *
- * 4. Precision-Specific Handling:
- *    - Double precision: AOCL VRDA vectorized functions
- *    - Single precision: Scalar fallback (preserves correctness)
- *
- * 5. Memory Layout Compatibility: Ensures direct memory access and compatible
- *    storage orders between source and destination for optimal performance
- *
- * Supported Operations:
- * ---------------------
- * UNARY OPERATIONS (vector → vector):
- * - Transcendental: exp(), sin(), cos(), sqrt(), log(), log10(), log2()
- *
- * BINARY OPERATIONS (vector op vector → vector):
- * - Arithmetic: +, *, pow()
- *
- * Template Specialization Mechanism:
- * -----------------------------------
- * The system works by specializing Eigen's Assignment template for:
- * 1. CwiseUnaryOp with scalar_*_op functors (unary operations)
- * 2. CwiseBinaryOp with scalar_*_op functors (binary operations)
- * 3. Dense2Dense assignment context with AOCL-compatible traits
- *
- * Dispatch conditions (all must be true):
- * - Source and destination have DirectAccessBit (contiguous memory)
- * - Compatible storage orders (both row-major or both column-major)
- * - Vector size ≥ EIGEN_AOCL_VML_THRESHOLD or Dynamic size
- * - Supported data type (currently double precision for VRDA)
- *
- * Integration Example:
- * --------------------
- * // Standard Eigen code - no changes required
- * VectorXd x = VectorXd::Random(10000);
- * VectorXd y = VectorXd::Random(10000);
- * VectorXd result;
- *
- * // These operations are automatically dispatched to AOCL:
- * result = x.array().exp();              // → amd_vrda_exp()
- * result = x.array().sin();              // → amd_vrda_sin()
- * result = x.array() + y.array();        // → amd_vrda_add()
- * result = x.array().pow(y.array());     // → amd_vrda_pow()
- *
- * Configuration:
- * --------------
- * Required preprocessor definitions:
- * - EIGEN_USE_AOCL_ALL or EIGEN_USE_AOCL_MT: Enable AOCL integration
- * - EIGEN_USE_AOCL_VML: Enable Vector Math Library dispatch
- *
- * Compilation Requirements:
- * -------------------------
- * Include paths:
- * - AOCL headers: -I${AOCL_ROOT}/include
- * - Eigen headers: -I/path/to/eigen
- *
- * Link libraries:
- * - AOCL MathLib: -lamdlibm
- * - Standard math: -lm
- *
- * Compiler flags:
- * - Optimization: -O3 (required for inlining)
- * - Architecture: -march=znver5 or -march=native
- * - Vectorization: -mfma -mavx512f (if supported)
- *
- * Platform Support:
- * ------------------
- * - Primary: Linux x86_64 with AMD Zen family processors
- * - Compilers: GCC 8+, Clang 10+, AOCC (recommended)
- * - AOCL Version: 4.0+ (with VRDA support)
- *
- * Error Handling:
- * ---------------
- * - Graceful fallback to scalar operations for unsupported configurations
- * - Compile-time detection of AOCL availability
- * - Runtime size and alignment validation with eigen_assert()
- *
- * Developer:
- * ----------
- * Name: Sharad Saurabh Bhaskar
- * Email: shbhaska@amd.com
- * Organization: Advanced Micro Devices, Inc.
- */
-
-
-#ifndef EIGEN_ASSIGN_AOCL_H
-#define EIGEN_ASSIGN_AOCL_H
-
-namespace Eigen {
-namespace internal {
-
-// Traits for unary operations.
-template <typename Dst, typename Src> class aocl_assign_traits {
-private:
-  enum {
-    DstHasDirectAccess = !!(Dst::Flags & DirectAccessBit),
-    SrcHasDirectAccess = !!(Src::Flags & DirectAccessBit),
-    StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
-    InnerSize = Dst::IsVectorAtCompileTime   ? int(Dst::SizeAtCompileTime)
-                : (Dst::Flags & RowMajorBit) ? int(Dst::ColsAtCompileTime)
-                                             : int(Dst::RowsAtCompileTime),
-    LargeEnough =
-        (InnerSize == Dynamic) || (InnerSize >= EIGEN_AOCL_VML_THRESHOLD)
-  };
-
-public:
-  enum {
-    EnableAoclVML = DstHasDirectAccess && SrcHasDirectAccess &&
-                    StorageOrdersAgree && LargeEnough,
-    Traversal = LinearTraversal
-  };
-};
-
-// Traits for binary operations (e.g., add, pow).
-template <typename Dst, typename Lhs, typename Rhs>
-class aocl_assign_binary_traits {
-private:
-  enum {
-    DstHasDirectAccess = !!(Dst::Flags & DirectAccessBit),
-    LhsHasDirectAccess = !!(Lhs::Flags & DirectAccessBit),
-    RhsHasDirectAccess = !!(Rhs::Flags & DirectAccessBit),
-    StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Lhs::IsRowMajor)) &&
-                         (int(Dst::IsRowMajor) == int(Rhs::IsRowMajor)),
-    InnerSize = Dst::IsVectorAtCompileTime   ? int(Dst::SizeAtCompileTime)
-                : (Dst::Flags & RowMajorBit) ? int(Dst::ColsAtCompileTime)
-                                             : int(Dst::RowsAtCompileTime),
-    LargeEnough =
-        (InnerSize == Dynamic) || (InnerSize >= EIGEN_AOCL_VML_THRESHOLD)
-  };
-
-public:
-  enum {
-    EnableAoclVML = DstHasDirectAccess && LhsHasDirectAccess &&
-                    RhsHasDirectAccess && StorageOrdersAgree && LargeEnough
-  };
-};
-
-// Unary operation dispatch for float (scalar fallback).
-#define EIGEN_AOCL_VML_UNARY_CALL_FLOAT(EIGENOP)                               \
-  template <typename DstXprType, typename SrcXprNested>                        \
-  struct Assignment<                                                           \
-      DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<float>, SrcXprNested>,    \
-      assign_op<float, float>, Dense2Dense,                                    \
-      std::enable_if_t<                                                        \
-          aocl_assign_traits<DstXprType, SrcXprNested>::EnableAoclVML>> {      \
-    typedef CwiseUnaryOp<scalar_##EIGENOP##_op<float>, SrcXprNested>           \
-        SrcXprType;                                                            \
-    static void run(DstXprType &dst, const SrcXprType &src,                    \
-                    const assign_op<float, float> &) {                         \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());      \
-      Eigen::Index n = dst.size();                                             \
-      if (n <= 0)                                                              \
-        return;                                                                \
-      const float *input =                                                     \
-          reinterpret_cast<const float *>(src.nestedExpression().data());      \
-      float *output = reinterpret_cast<float *>(dst.data());                   \
-      for (Eigen::Index i = 0; i < n; ++i) {                                   \
-        output[i] = std::EIGENOP(input[i]);                                    \
-      }                                                                        \
-    }                                                                          \
-  };
-
-// Unary operation dispatch for double (AOCL vectorized).
-#define EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(EIGENOP, AOCLOP)                      \
-  template <typename DstXprType, typename SrcXprNested>                        \
-  struct Assignment<                                                           \
-      DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<double>, SrcXprNested>,   \
-      assign_op<double, double>, Dense2Dense,                                  \
-      std::enable_if_t<                                                        \
-          aocl_assign_traits<DstXprType, SrcXprNested>::EnableAoclVML>> {      \
-    typedef CwiseUnaryOp<scalar_##EIGENOP##_op<double>, SrcXprNested>          \
-        SrcXprType;                                                            \
-    static void run(DstXprType &dst, const SrcXprType &src,                    \
-                    const assign_op<double, double> &) {                       \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());      \
-      Eigen::Index n = dst.size();                                             \
-      eigen_assert(n <= INT_MAX && "AOCL does not support arrays larger than INT_MAX"); \
-      if (n <= 0)                                                              \
-        return;                                                                \
-      const double *input =                                                    \
-          reinterpret_cast<const double *>(src.nestedExpression().data());     \
-      double *output = reinterpret_cast<double *>(dst.data());                 \
-      int aocl_n = internal::convert_index<int>(n);                            \
-      AOCLOP(aocl_n, const_cast<double *>(input), output);                     \
-    }                                                                          \
-  };
-
-// Instantiate unary calls for float (scalar).
-// EIGEN_AOCL_VML_UNARY_CALL_FLOAT(exp)
-
-// Instantiate unary calls for double (AOCL vectorized).
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(exp2, amd_vrda_exp2)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(exp, amd_vrda_exp)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(sin, amd_vrda_sin)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(cos, amd_vrda_cos)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(sqrt, amd_vrda_sqrt)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(cbrt, amd_vrda_cbrt)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(abs, amd_vrda_fabs)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(log, amd_vrda_log)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(log10, amd_vrda_log10)
-EIGEN_AOCL_VML_UNARY_CALL_DOUBLE(log2, amd_vrda_log2)
-
-// Binary operation dispatch for float (scalar fallback).
-#define EIGEN_AOCL_VML_BINARY_CALL_FLOAT(EIGENOP, STDFUNC)                     \
-  template <typename DstXprType, typename LhsXprNested, typename RhsXprNested> \
-  struct Assignment<                                                           \
-      DstXprType,                                                              \
-      CwiseBinaryOp<scalar_##EIGENOP##_op<float, float>, LhsXprNested,         \
-                    RhsXprNested>,                                             \
-      assign_op<float, float>, Dense2Dense,                                    \
-      std::enable_if_t<aocl_assign_binary_traits<                              \
-          DstXprType, LhsXprNested, RhsXprNested>::EnableAoclVML>> {           \
-    typedef CwiseBinaryOp<scalar_##EIGENOP##_op<float, float>, LhsXprNested,   \
-                          RhsXprNested>                                        \
-        SrcXprType;                                                            \
-    static void run(DstXprType &dst, const SrcXprType &src,                    \
-                    const assign_op<float, float> &) {                         \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());      \
-      Eigen::Index n = dst.size();                                             \
-      if (n <= 0)                                                              \
-        return;                                                                \
-      const float *lhs = reinterpret_cast<const float *>(src.lhs().data());    \
-      const float *rhs = reinterpret_cast<const float *>(src.rhs().data());    \
-      float *output = reinterpret_cast<float *>(dst.data());                   \
-      for (Eigen::Index i = 0; i < n; ++i) {                                   \
-        output[i] = STDFUNC(lhs[i], rhs[i]);                                   \
-      }                                                                        \
-    }                                                                          \
-  };
-
-// Binary operation dispatch for double (AOCL vectorized).
-#define EIGEN_AOCL_VML_BINARY_CALL_DOUBLE(EIGENOP, AOCLOP)                     \
-  template <typename DstXprType, typename LhsXprNested, typename RhsXprNested> \
-  struct Assignment<                                                           \
-      DstXprType,                                                              \
-      CwiseBinaryOp<scalar_##EIGENOP##_op<double, double>, LhsXprNested,       \
-                    RhsXprNested>,                                             \
-      assign_op<double, double>, Dense2Dense,                                  \
-      std::enable_if_t<aocl_assign_binary_traits<                              \
-          DstXprType, LhsXprNested, RhsXprNested>::EnableAoclVML>> {           \
-    typedef CwiseBinaryOp<scalar_##EIGENOP##_op<double, double>, LhsXprNested, \
-                          RhsXprNested>                                        \
-        SrcXprType;                                                            \
-    static void run(DstXprType &dst, const SrcXprType &src,                    \
-                    const assign_op<double, double> &) {                       \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());      \
-      Eigen::Index n = dst.size();                                             \
-      eigen_assert(n <= INT_MAX && "AOCL does not support arrays larger than INT_MAX"); \
-      if (n <= 0)                                                              \
-        return;                                                                \
-      const double *lhs = reinterpret_cast<const double *>(src.lhs().data());  \
-      const double *rhs = reinterpret_cast<const double *>(src.rhs().data());  \
-      double *output = reinterpret_cast<double *>(dst.data());                 \
-      int aocl_n = internal::convert_index<int>(n);                            \
-      AOCLOP(aocl_n, const_cast<double *>(lhs), const_cast<double *>(rhs), output); \
-    }                                                                          \
-  };
-
-// Instantiate binary calls for float (scalar).
-// EIGEN_AOCL_VML_BINARY_CALL_FLOAT(sum, std::plus<float>)  // Using
-// scalar_sum_op for addition EIGEN_AOCL_VML_BINARY_CALL_FLOAT(pow, std::pow)
-
-// Instantiate binary calls for double (AOCL vectorized).
-EIGEN_AOCL_VML_BINARY_CALL_DOUBLE(sum, amd_vrda_add) // Using scalar_sum_op for addition
-EIGEN_AOCL_VML_BINARY_CALL_DOUBLE(pow, amd_vrda_pow)
-EIGEN_AOCL_VML_BINARY_CALL_DOUBLE(max, amd_vrda_fmax)
-EIGEN_AOCL_VML_BINARY_CALL_DOUBLE(min, amd_vrda_fmin)
-
-} // namespace internal
-} // namespace Eigen
-
-#endif // EIGEN_ASSIGN_AOCL_H

Eigen/src/Core/Assign_MKL.h

@@ -1,6 +1,5 @@
 /*
  Copyright (c) 2011, Intel Corporation. All rights reserved.
- Copyright (C) 2015 Gael Guennebaud <gael.guennebaud@inria.fr>
 
  Redistribution and use in source and binary forms, with or without modification,
  are permitted provided that the following conditions are met:
@@ -34,150 +33,192 @@
 #ifndef EIGEN_ASSIGN_VML_H
 #define EIGEN_ASSIGN_VML_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
+namespace Eigen { 
 
 namespace internal {
 
-template <typename Dst, typename Src>
-class vml_assign_traits {
- private:
-  enum {
-    DstHasDirectAccess = Dst::Flags & DirectAccessBit,
-    SrcHasDirectAccess = Src::Flags & DirectAccessBit,
-    StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
-    InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
-                : int(Dst::Flags) & RowMajorBit ? int(Dst::ColsAtCompileTime)
-                                                : int(Dst::RowsAtCompileTime),
-    InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
-                   : int(Dst::Flags) & RowMajorBit ? int(Dst::MaxColsAtCompileTime)
-                                                   : int(Dst::MaxRowsAtCompileTime),
-    MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
+template<typename Op> struct vml_call
+{ enum { IsSupported = 0 }; };
 
-    MightEnableVml = bool(StorageOrdersAgree) && bool(DstHasDirectAccess) && bool(SrcHasDirectAccess) &&
-                     Src::InnerStrideAtCompileTime == 1 && Dst::InnerStrideAtCompileTime == 1,
-    MightLinearize = bool(MightEnableVml) && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
-    VmlSize = bool(MightLinearize) ? MaxSizeAtCompileTime : InnerMaxSize,
-    LargeEnough = (VmlSize == Dynamic) || VmlSize >= EIGEN_MKL_VML_THRESHOLD
-  };
+template<typename Dst, typename Src, typename UnaryOp>
+class vml_assign_traits
+{
+  private:
+    enum {
+      DstHasDirectAccess = Dst::Flags & DirectAccessBit,
+      SrcHasDirectAccess = Src::Flags & DirectAccessBit,
 
- public:
-  enum { EnableVml = MightEnableVml && LargeEnough, Traversal = MightLinearize ? LinearTraversal : DefaultTraversal };
+      StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
+      InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
+                : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
+                : int(Dst::RowsAtCompileTime),
+      InnerMaxSize  = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
+                    : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
+                    : int(Dst::MaxRowsAtCompileTime),
+      MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
+
+      MightEnableVml =  vml_call<UnaryOp>::IsSupported && StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess
+                     && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
+      MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
+      VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
+      LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD,
+      MayEnableVml = MightEnableVml && LargeEnough,
+      MayLinearize = MayEnableVml && MightLinearize
+    };
+  public:
+    enum {
+      Traversal = MayLinearize ? LinearVectorizedTraversal
+                : MayEnableVml ? InnerVectorizedTraversal
+                : DefaultTraversal
+    };
 };
 
-#define EIGEN_PP_EXPAND(ARG) ARG
-#if !defined(EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
-#define EIGEN_VMLMODE_EXPAND_xLA , VML_HA
+template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling,
+         int VmlTraversal = vml_assign_traits<Derived1, Derived2, UnaryOp>::Traversal >
+struct vml_assign_impl
+  : assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>
+{
+};
+
+template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
+struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, InnerVectorizedTraversal>
+{
+  typedef typename Derived1::Scalar Scalar;
+  typedef typename Derived1::Index Index;
+  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
+  {
+    // in case we want to (or have to) skip VML at runtime we can call:
+    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer) {
+      const Scalar *src_ptr = src.IsRowMajor ?  &(src.nestedExpression().coeffRef(outer,0)) :
+                                                &(src.nestedExpression().coeffRef(0, outer));
+      Scalar *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));
+      vml_call<UnaryOp>::run(src.functor(), innerSize, src_ptr, dst_ptr );
+    }
+  }
+};
+
+template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
+struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, LinearVectorizedTraversal>
+{
+  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
+  {
+    // in case we want to (or have to) skip VML at runtime we can call:
+    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
+    vml_call<UnaryOp>::run(src.functor(), dst.size(), src.nestedExpression().data(), dst.data() );
+  }
+};
+
+// Macroses
+
+#define EIGEN_MKL_VML_SPECIALIZE_ASSIGN(TRAVERSAL,UNROLLING) \
+  template<typename Derived1, typename Derived2, typename UnaryOp> \
+  struct assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>, TRAVERSAL, UNROLLING, Specialized>  {  \
+    static inline void run(Derived1 &dst, const Eigen::CwiseUnaryOp<UnaryOp, Derived2> &src) { \
+      vml_assign_impl<Derived1,Derived2,UnaryOp,TRAVERSAL,UNROLLING>::run(dst, src); \
+    } \
+  };
+
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,InnerUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,InnerUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,CompleteUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,NoUnrolling)
+EIGEN_MKL_VML_SPECIALIZE_ASSIGN(SliceVectorizedTraversal,NoUnrolling)
+
+
+#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
+#define  EIGEN_MKL_VML_MODE VML_HA
 #else
-#define EIGEN_VMLMODE_EXPAND_xLA , VML_LA
+#define  EIGEN_MKL_VML_MODE VML_LA
 #endif
 
-#define EIGEN_VMLMODE_EXPAND_x_
-
-#define EIGEN_VMLMODE_PREFIX_xLA vm
-#define EIGEN_VMLMODE_PREFIX_x_ v
-#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_x, VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                      \
-  template <typename DstXprType, typename SrcXprNested>                                                    \
-  struct Assignment<DstXprType, CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested>,              \
-                    assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense,                                          \
-                    std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> {            \
-    typedef CwiseUnaryOp<scalar_##EIGENOP##_op<EIGENTYPE>, SrcXprNested> SrcXprType;                       \
-    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
-      resize_if_allowed(dst, src, func);                                                                   \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                  \
-      if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == (int)LinearTraversal) {                \
-        VMLOP(dst.size(), (const VMLTYPE *)src.nestedExpression().data(),                                  \
-              (VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                     \
-      } else {                                                                                             \
-        const Index outerSize = dst.outerSize();                                                           \
-        for (Index outer = 0; outer < outerSize; ++outer) {                                                \
-          const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer, 0))         \
-                                                    : &(src.nestedExpression().coeffRef(0, outer));        \
-          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer));     \
-          VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr,                                                 \
-                (VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                      \
-        }                                                                                                  \
-      }                                                                                                    \
-    }                                                                                                      \
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)     \
+  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
+    enum { IsSupported = 1 };                                                    \
+    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
+                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
+      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst);                           \
+    }                                                                            \
   };
 
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)                                                \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), s##VMLOP), float, float, VMLMODE) \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), d##VMLOP), double, double, VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)                                   \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), c##VMLOP), scomplex, \
-                                   MKL_Complex8, VMLMODE)                                                 \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), z##VMLOP), dcomplex, \
-                                   MKL_Complex16, VMLMODE)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE)  \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE)
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA)
-// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,   Abs,    _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _)
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(cbrt, Cbrt, _)
-
-#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE)                        \
-  template <typename DstXprType, typename SrcXprNested, typename Plain>                                    \
-  struct Assignment<DstXprType,                                                                            \
-                    CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested,               \
-                                  const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>>,   \
-                    assign_op<EIGENTYPE, EIGENTYPE>, Dense2Dense,                                          \
-                    std::enable_if_t<vml_assign_traits<DstXprType, SrcXprNested>::EnableVml>> {            \
-    typedef CwiseBinaryOp<scalar_##EIGENOP##_op<EIGENTYPE, EIGENTYPE>, SrcXprNested,                       \
-                          const CwiseNullaryOp<internal::scalar_constant_op<EIGENTYPE>, Plain>>            \
-        SrcXprType;                                                                                        \
-    static void run(DstXprType &dst, const SrcXprType &src, const assign_op<EIGENTYPE, EIGENTYPE> &func) { \
-      resize_if_allowed(dst, src, func);                                                                   \
-      eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());                                  \
-      VMLTYPE exponent = reinterpret_cast<const VMLTYPE &>(src.rhs().functor().m_other);                   \
-      if (vml_assign_traits<DstXprType, SrcXprNested>::Traversal == LinearTraversal) {                     \
-        VMLOP(dst.size(), (const VMLTYPE *)src.lhs().data(), exponent,                                     \
-              (VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                     \
-      } else {                                                                                             \
-        const Index outerSize = dst.outerSize();                                                           \
-        for (Index outer = 0; outer < outerSize; ++outer) {                                                \
-          const EIGENTYPE *src_ptr =                                                                       \
-              src.IsRowMajor ? &(src.lhs().coeffRef(outer, 0)) : &(src.lhs().coeffRef(0, outer));          \
-          EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer));     \
-          VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, exponent,                                       \
-                (VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE));                      \
-        }                                                                                                  \
-      }                                                                                                    \
-    }                                                                                                      \
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)  \
+  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
+    enum { IsSupported = 1 };                                                    \
+    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
+                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
+      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
+      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst, vmlMode);                  \
+    }                                                                            \
   };
 
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA)
+#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)       \
+  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
+    enum { IsSupported = 1 };                                                    \
+    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& func,        \
+                          int size, const EIGENTYPE* src, EIGENTYPE* dst) {      \
+      EIGENTYPE exponent = func.m_exponent;                                      \
+      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
+      VMLOP(&size, (const VMLTYPE*)src, (const VMLTYPE*)&exponent,               \
+                        (VMLTYPE*)dst, &vmlMode);                                \
+    }                                                                            \
+  };
 
-}  // end namespace internal
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                   \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vs##VMLOP, float, float)             \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vd##VMLOP, double, double)
 
-}  // end namespace Eigen
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)                \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vc##VMLOP, scomplex, MKL_Complex8)   \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vz##VMLOP, dcomplex, MKL_Complex16)
 
-#endif  // EIGEN_ASSIGN_VML_H
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP)                        \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                         \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)
+
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vms##VMLOP, float, float)         \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmd##VMLOP, double, double)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)             \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmc##VMLOP, scomplex, MKL_Complex8)  \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmz##VMLOP, dcomplex, MKL_Complex16)
+
+#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(EIGENOP, VMLOP)                     \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                      \
+  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)
+
+
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sin,  Sin)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos,  Cos)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan,  Tan)
+//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,  Abs)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp,  Exp)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log,  Ln)
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sqrt, Sqrt)
+
+EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr)
+
+// The vm*powx functions are not avaibale in the windows version of MKL.
+#ifndef _WIN32
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16)
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_ASSIGN_VML_H

Eigen/src/Core/BandMatrix.h

@@ -10,329 +10,325 @@
 #ifndef EIGEN_BANDMATRIX_H
 #define EIGEN_BANDMATRIX_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
+namespace Eigen { 
 
 namespace internal {
 
-template <typename Derived>
-class BandMatrixBase : public EigenBase<Derived> {
- public:
-  enum {
-    Flags = internal::traits<Derived>::Flags,
-    CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
-    RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
-    ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
-    MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
-    Supers = internal::traits<Derived>::Supers,
-    Subs = internal::traits<Derived>::Subs,
-    Options = internal::traits<Derived>::Options
-  };
-  typedef typename internal::traits<Derived>::Scalar Scalar;
-  typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime> DenseMatrixType;
-  typedef typename DenseMatrixType::StorageIndex StorageIndex;
-  typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
-  typedef EigenBase<Derived> Base;
+template<typename Derived>
+class BandMatrixBase : public EigenBase<Derived>
+{
+  public:
 
- protected:
-  enum {
-    DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic,
-    SizeAtCompileTime = min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime)
-  };
-
- public:
-  using Base::cols;
-  using Base::derived;
-  using Base::rows;
-
-  /** \returns the number of super diagonals */
-  inline Index supers() const { return derived().supers(); }
-
-  /** \returns the number of sub diagonals */
-  inline Index subs() const { return derived().subs(); }
-
-  /** \returns an expression of the underlying coefficient matrix */
-  inline const CoefficientsType& coeffs() const { return derived().coeffs(); }
-
-  /** \returns an expression of the underlying coefficient matrix */
-  inline CoefficientsType& coeffs() { return derived().coeffs(); }
-
-  /** \returns a vector expression of the \a i -th column,
-   * only the meaningful part is returned.
-   * \warning the internal storage must be column major. */
-  inline Block<CoefficientsType, Dynamic, 1> col(Index i) {
-    EIGEN_STATIC_ASSERT((int(Options) & int(RowMajor)) == 0, THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
-    Index start = 0;
-    Index len = coeffs().rows();
-    if (i <= supers()) {
-      start = supers() - i;
-      len = (std::min)(rows(), std::max<Index>(0, coeffs().rows() - (supers() - i)));
-    } else if (i >= rows() - subs())
-      len = std::max<Index>(0, coeffs().rows() - (i + 1 - rows() + subs()));
-    return Block<CoefficientsType, Dynamic, 1>(coeffs(), start, i, len, 1);
-  }
-
-  /** \returns a vector expression of the main diagonal */
-  inline Block<CoefficientsType, 1, SizeAtCompileTime> diagonal() {
-    return Block<CoefficientsType, 1, SizeAtCompileTime>(coeffs(), supers(), 0, 1, (std::min)(rows(), cols()));
-  }
-
-  /** \returns a vector expression of the main diagonal (const version) */
-  inline const Block<const CoefficientsType, 1, SizeAtCompileTime> diagonal() const {
-    return Block<const CoefficientsType, 1, SizeAtCompileTime>(coeffs(), supers(), 0, 1, (std::min)(rows(), cols()));
-  }
-
-  template <int Index>
-  struct DiagonalIntReturnType {
     enum {
-      ReturnOpposite =
-          (int(Options) & int(SelfAdjoint)) && (((Index) > 0 && Supers == 0) || ((Index) < 0 && Subs == 0)),
-      Conjugate = ReturnOpposite && NumTraits<Scalar>::IsComplex,
-      ActualIndex = ReturnOpposite ? -Index : Index,
-      DiagonalSize =
-          (RowsAtCompileTime == Dynamic || ColsAtCompileTime == Dynamic)
-              ? Dynamic
-              : (ActualIndex < 0 ? min_size_prefer_dynamic(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
-                                 : min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
+      Flags = internal::traits<Derived>::Flags,
+      CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
+      RowsAtCompileTime = internal::traits<Derived>::RowsAtCompileTime,
+      ColsAtCompileTime = internal::traits<Derived>::ColsAtCompileTime,
+      MaxRowsAtCompileTime = internal::traits<Derived>::MaxRowsAtCompileTime,
+      MaxColsAtCompileTime = internal::traits<Derived>::MaxColsAtCompileTime,
+      Supers = internal::traits<Derived>::Supers,
+      Subs   = internal::traits<Derived>::Subs,
+      Options = internal::traits<Derived>::Options
     };
-    typedef Block<CoefficientsType, 1, DiagonalSize> BuildType;
-    typedef std::conditional_t<Conjugate, CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, BuildType>, BuildType>
-        Type;
-  };
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef Matrix<Scalar,RowsAtCompileTime,ColsAtCompileTime> DenseMatrixType;
+    typedef typename DenseMatrixType::Index Index;
+    typedef typename internal::traits<Derived>::CoefficientsType CoefficientsType;
+    typedef EigenBase<Derived> Base;
 
-  /** \returns a vector expression of the \a N -th sub or super diagonal */
-  template <int N>
-  inline typename DiagonalIntReturnType<N>::Type diagonal() {
-    return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers() - N, (std::max)(0, N), 1, diagonalLength(N));
-  }
+  protected:
+    enum {
+      DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic))
+                            ? 1 + Supers + Subs
+                            : Dynamic,
+      SizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime)
+    };
 
-  /** \returns a vector expression of the \a N -th sub or super diagonal */
-  template <int N>
-  inline const typename DiagonalIntReturnType<N>::Type diagonal() const {
-    return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers() - N, (std::max)(0, N), 1, diagonalLength(N));
-  }
+  public:
+    
+    using Base::derived;
+    using Base::rows;
+    using Base::cols;
 
-  /** \returns a vector expression of the \a i -th sub or super diagonal */
-  inline Block<CoefficientsType, 1, Dynamic> diagonal(Index i) {
-    eigen_assert((i < 0 && -i <= subs()) || (i >= 0 && i <= supers()));
-    return Block<CoefficientsType, 1, Dynamic>(coeffs(), supers() - i, std::max<Index>(0, i), 1, diagonalLength(i));
-  }
+    /** \returns the number of super diagonals */
+    inline Index supers() const { return derived().supers(); }
 
-  /** \returns a vector expression of the \a i -th sub or super diagonal */
-  inline const Block<const CoefficientsType, 1, Dynamic> diagonal(Index i) const {
-    eigen_assert((i < 0 && -i <= subs()) || (i >= 0 && i <= supers()));
-    return Block<const CoefficientsType, 1, Dynamic>(coeffs(), supers() - i, std::max<Index>(0, i), 1,
-                                                     diagonalLength(i));
-  }
+    /** \returns the number of sub diagonals */
+    inline Index subs() const { return derived().subs(); }
+    
+    /** \returns an expression of the underlying coefficient matrix */
+    inline const CoefficientsType& coeffs() const { return derived().coeffs(); }
+    
+    /** \returns an expression of the underlying coefficient matrix */
+    inline CoefficientsType& coeffs() { return derived().coeffs(); }
 
-  template <typename Dest>
-  inline void evalTo(Dest& dst) const {
-    dst.resize(rows(), cols());
-    dst.setZero();
-    dst.diagonal() = diagonal();
-    for (Index i = 1; i <= supers(); ++i) dst.diagonal(i) = diagonal(i);
-    for (Index i = 1; i <= subs(); ++i) dst.diagonal(-i) = diagonal(-i);
-  }
+    /** \returns a vector expression of the \a i -th column,
+      * only the meaningful part is returned.
+      * \warning the internal storage must be column major. */
+    inline Block<CoefficientsType,Dynamic,1> col(Index i)
+    {
+      EIGEN_STATIC_ASSERT((Options&RowMajor)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+      Index start = 0;
+      Index len = coeffs().rows();
+      if (i<=supers())
+      {
+        start = supers()-i;
+        len = (std::min)(rows(),std::max<Index>(0,coeffs().rows() - (supers()-i)));
+      }
+      else if (i>=rows()-subs())
+        len = std::max<Index>(0,coeffs().rows() - (i + 1 - rows() + subs()));
+      return Block<CoefficientsType,Dynamic,1>(coeffs(), start, i, len, 1);
+    }
 
-  DenseMatrixType toDenseMatrix() const {
-    DenseMatrixType res(rows(), cols());
-    evalTo(res);
-    return res;
-  }
+    /** \returns a vector expression of the main diagonal */
+    inline Block<CoefficientsType,1,SizeAtCompileTime> diagonal()
+    { return Block<CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
 
- protected:
-  inline Index diagonalLength(Index i) const {
-    return i < 0 ? (std::min)(cols(), rows() + i) : (std::min)(rows(), cols() - i);
-  }
+    /** \returns a vector expression of the main diagonal (const version) */
+    inline const Block<const CoefficientsType,1,SizeAtCompileTime> diagonal() const
+    { return Block<const CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
+
+    template<int Index> struct DiagonalIntReturnType {
+      enum {
+        ReturnOpposite = (Options&SelfAdjoint) && (((Index)>0 && Supers==0) || ((Index)<0 && Subs==0)),
+        Conjugate = ReturnOpposite && NumTraits<Scalar>::IsComplex,
+        ActualIndex = ReturnOpposite ? -Index : Index,
+        DiagonalSize = (RowsAtCompileTime==Dynamic || ColsAtCompileTime==Dynamic)
+                     ? Dynamic
+                     : (ActualIndex<0
+                     ? EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime, RowsAtCompileTime + ActualIndex)
+                     : EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime - ActualIndex))
+      };
+      typedef Block<CoefficientsType,1, DiagonalSize> BuildType;
+      typedef typename internal::conditional<Conjugate,
+                 CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>,BuildType >,
+                 BuildType>::type Type;
+    };
+
+    /** \returns a vector expression of the \a N -th sub or super diagonal */
+    template<int N> inline typename DiagonalIntReturnType<N>::Type diagonal()
+    {
+      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
+    }
+
+    /** \returns a vector expression of the \a N -th sub or super diagonal */
+    template<int N> inline const typename DiagonalIntReturnType<N>::Type diagonal() const
+    {
+      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
+    }
+
+    /** \returns a vector expression of the \a i -th sub or super diagonal */
+    inline Block<CoefficientsType,1,Dynamic> diagonal(Index i)
+    {
+      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
+      return Block<CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
+    }
+
+    /** \returns a vector expression of the \a i -th sub or super diagonal */
+    inline const Block<const CoefficientsType,1,Dynamic> diagonal(Index i) const
+    {
+      eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers()));
+      return Block<const CoefficientsType,1,Dynamic>(coeffs(), supers()-i, std::max<Index>(0,i), 1, diagonalLength(i));
+    }
+    
+    template<typename Dest> inline void evalTo(Dest& dst) const
+    {
+      dst.resize(rows(),cols());
+      dst.setZero();
+      dst.diagonal() = diagonal();
+      for (Index i=1; i<=supers();++i)
+        dst.diagonal(i) = diagonal(i);
+      for (Index i=1; i<=subs();++i)
+        dst.diagonal(-i) = diagonal(-i);
+    }
+
+    DenseMatrixType toDenseMatrix() const
+    {
+      DenseMatrixType res(rows(),cols());
+      evalTo(res);
+      return res;
+    }
+
+  protected:
+
+    inline Index diagonalLength(Index i) const
+    { return i<0 ? (std::min)(cols(),rows()+i) : (std::min)(rows(),cols()-i); }
 };
 
 /**
- * \class BandMatrix
- * \ingroup Core_Module
- *
- * \brief Represents a rectangular matrix with a banded storage
- *
- * \tparam Scalar_ Numeric type, i.e. float, double, int
- * \tparam Rows_ Number of rows, or \b Dynamic
- * \tparam Cols_ Number of columns, or \b Dynamic
- * \tparam Supers_ Number of super diagonal
- * \tparam Subs_ Number of sub diagonal
- * \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
- *                  The former controls \ref TopicStorageOrders "storage order", and defaults to
- *                  column-major. The latter controls whether the matrix represents a selfadjoint
- *                  matrix in which case either Supers of Subs have to be null.
- *
- * \sa class TridiagonalMatrix
- */
+  * \class BandMatrix
+  * \ingroup Core_Module
+  *
+  * \brief Represents a rectangular matrix with a banded storage
+  *
+  * \param _Scalar Numeric type, i.e. float, double, int
+  * \param Rows Number of rows, or \b Dynamic
+  * \param Cols Number of columns, or \b Dynamic
+  * \param Supers Number of super diagonal
+  * \param Subs Number of sub diagonal
+  * \param _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint
+  *                 The former controls \ref TopicStorageOrders "storage order", and defaults to
+  *                 column-major. The latter controls whether the matrix represents a selfadjoint 
+  *                 matrix in which case either Supers of Subs have to be null.
+  *
+  * \sa class TridiagonalMatrix
+  */
 
-template <typename Scalar_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct traits<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> > {
-  typedef Scalar_ Scalar;
+template<typename _Scalar, int _Rows, int _Cols, int _Supers, int _Subs, int _Options>
+struct traits<BandMatrix<_Scalar,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  typedef _Scalar Scalar;
   typedef Dense StorageKind;
-  typedef Eigen::Index StorageIndex;
+  typedef DenseIndex Index;
   enum {
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
-    RowsAtCompileTime = Rows_,
-    ColsAtCompileTime = Cols_,
-    MaxRowsAtCompileTime = Rows_,
-    MaxColsAtCompileTime = Cols_,
+    RowsAtCompileTime = _Rows,
+    ColsAtCompileTime = _Cols,
+    MaxRowsAtCompileTime = _Rows,
+    MaxColsAtCompileTime = _Cols,
     Flags = LvalueBit,
-    Supers = Supers_,
-    Subs = Subs_,
-    Options = Options_,
-    DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic
+    Supers = _Supers,
+    Subs = _Subs,
+    Options = _Options,
+    DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic
   };
-  typedef Matrix<Scalar, DataRowsAtCompileTime, ColsAtCompileTime, int(Options) & int(RowMajor) ? RowMajor : ColMajor>
-      CoefficientsType;
+  typedef Matrix<Scalar,DataRowsAtCompileTime,ColsAtCompileTime,Options&RowMajor?RowMajor:ColMajor> CoefficientsType;
 };
 
-template <typename Scalar_, int Rows, int Cols, int Supers, int Subs, int Options>
-class BandMatrix : public BandMatrixBase<BandMatrix<Scalar_, Rows, Cols, Supers, Subs, Options> > {
- public:
-  typedef typename internal::traits<BandMatrix>::Scalar Scalar;
-  typedef typename internal::traits<BandMatrix>::StorageIndex StorageIndex;
-  typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
+template<typename _Scalar, int Rows, int Cols, int Supers, int Subs, int Options>
+class BandMatrix : public BandMatrixBase<BandMatrix<_Scalar,Rows,Cols,Supers,Subs,Options> >
+{
+  public:
 
-  explicit inline BandMatrix(Index rows = Rows, Index cols = Cols, Index supers = Supers, Index subs = Subs)
-      : m_coeffs(1 + supers + subs, cols), m_rows(rows), m_supers(supers), m_subs(subs) {}
+    typedef typename internal::traits<BandMatrix>::Scalar Scalar;
+    typedef typename internal::traits<BandMatrix>::Index Index;
+    typedef typename internal::traits<BandMatrix>::CoefficientsType CoefficientsType;
 
-  /** \returns the number of columns */
-  constexpr Index rows() const { return m_rows.value(); }
+    inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs)
+      : m_coeffs(1+supers+subs,cols),
+        m_rows(rows), m_supers(supers), m_subs(subs)
+    {
+    }
 
-  /** \returns the number of rows */
-  constexpr Index cols() const { return m_coeffs.cols(); }
+    /** \returns the number of columns */
+    inline Index rows() const { return m_rows.value(); }
 
-  /** \returns the number of super diagonals */
-  constexpr Index supers() const { return m_supers.value(); }
+    /** \returns the number of rows */
+    inline Index cols() const { return m_coeffs.cols(); }
 
-  /** \returns the number of sub diagonals */
-  constexpr Index subs() const { return m_subs.value(); }
+    /** \returns the number of super diagonals */
+    inline Index supers() const { return m_supers.value(); }
 
-  inline const CoefficientsType& coeffs() const { return m_coeffs; }
-  inline CoefficientsType& coeffs() { return m_coeffs; }
+    /** \returns the number of sub diagonals */
+    inline Index subs() const { return m_subs.value(); }
 
- protected:
-  CoefficientsType m_coeffs;
-  internal::variable_if_dynamic<Index, Rows> m_rows;
-  internal::variable_if_dynamic<Index, Supers> m_supers;
-  internal::variable_if_dynamic<Index, Subs> m_subs;
+    inline const CoefficientsType& coeffs() const { return m_coeffs; }
+    inline CoefficientsType& coeffs() { return m_coeffs; }
+
+  protected:
+
+    CoefficientsType m_coeffs;
+    internal::variable_if_dynamic<Index, Rows>   m_rows;
+    internal::variable_if_dynamic<Index, Supers> m_supers;
+    internal::variable_if_dynamic<Index, Subs>   m_subs;
 };
 
-template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
+template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
 class BandMatrixWrapper;
 
-template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct traits<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> > {
-  typedef typename CoefficientsType_::Scalar Scalar;
-  typedef typename CoefficientsType_::StorageKind StorageKind;
-  typedef typename CoefficientsType_::StorageIndex StorageIndex;
+template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+struct traits<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  typedef typename _CoefficientsType::Scalar Scalar;
+  typedef typename _CoefficientsType::StorageKind StorageKind;
+  typedef typename _CoefficientsType::Index Index;
   enum {
-    CoeffReadCost = internal::traits<CoefficientsType_>::CoeffReadCost,
-    RowsAtCompileTime = Rows_,
-    ColsAtCompileTime = Cols_,
-    MaxRowsAtCompileTime = Rows_,
-    MaxColsAtCompileTime = Cols_,
+    CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost,
+    RowsAtCompileTime = _Rows,
+    ColsAtCompileTime = _Cols,
+    MaxRowsAtCompileTime = _Rows,
+    MaxColsAtCompileTime = _Cols,
     Flags = LvalueBit,
-    Supers = Supers_,
-    Subs = Subs_,
-    Options = Options_,
-    DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic
+    Supers = _Supers,
+    Subs = _Subs,
+    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_>
-class BandMatrixWrapper
-    : public BandMatrixBase<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> > {
- public:
-  typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
-  typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
-  typedef typename internal::traits<BandMatrixWrapper>::StorageIndex StorageIndex;
+template<typename _CoefficientsType,int _Rows, int _Cols, int _Supers, int _Subs,int _Options>
+class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsType,_Rows,_Cols,_Supers,_Subs,_Options> >
+{
+  public:
 
-  explicit inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows = Rows_, Index cols = Cols_,
-                                    Index supers = Supers_, Index subs = Subs_)
-      : m_coeffs(coeffs), m_rows(rows), m_supers(supers), m_subs(subs) {
-    EIGEN_UNUSED_VARIABLE(cols);
-    // eigen_assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
-  }
+    typedef typename internal::traits<BandMatrixWrapper>::Scalar Scalar;
+    typedef typename internal::traits<BandMatrixWrapper>::CoefficientsType CoefficientsType;
+    typedef typename internal::traits<BandMatrixWrapper>::Index Index;
 
-  /** \returns the number of columns */
-  constexpr Index rows() const { return m_rows.value(); }
+    inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs)
+      : m_coeffs(coeffs),
+        m_rows(rows), m_supers(supers), m_subs(subs)
+    {
+      EIGEN_UNUSED_VARIABLE(cols);
+      //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
+    }
 
-  /** \returns the number of rows */
-  constexpr Index cols() const { return m_coeffs.cols(); }
+    /** \returns the number of columns */
+    inline Index rows() const { return m_rows.value(); }
 
-  /** \returns the number of super diagonals */
-  constexpr Index supers() const { return m_supers.value(); }
+    /** \returns the number of rows */
+    inline Index cols() const { return m_coeffs.cols(); }
 
-  /** \returns the number of sub diagonals */
-  constexpr Index subs() const { return m_subs.value(); }
+    /** \returns the number of super diagonals */
+    inline Index supers() const { return m_supers.value(); }
 
-  inline const CoefficientsType& coeffs() const { return m_coeffs; }
+    /** \returns the number of sub diagonals */
+    inline Index subs() const { return m_subs.value(); }
 
- protected:
-  const CoefficientsType& m_coeffs;
-  internal::variable_if_dynamic<Index, Rows_> m_rows;
-  internal::variable_if_dynamic<Index, Supers_> m_supers;
-  internal::variable_if_dynamic<Index, Subs_> m_subs;
+    inline const CoefficientsType& coeffs() const { return m_coeffs; }
+
+  protected:
+
+    const CoefficientsType& m_coeffs;
+    internal::variable_if_dynamic<Index, _Rows>   m_rows;
+    internal::variable_if_dynamic<Index, _Supers> m_supers;
+    internal::variable_if_dynamic<Index, _Subs>   m_subs;
 };
 
 /**
- * \class TridiagonalMatrix
- * \ingroup Core_Module
- *
- * \brief Represents a tridiagonal matrix with a compact banded storage
- *
- * \tparam Scalar Numeric type, i.e. float, double, int
- * \tparam Size Number of rows and cols, or \b Dynamic
- * \tparam Options Can be 0 or \b SelfAdjoint
- *
- * \sa class BandMatrix
- */
-template <typename Scalar, int Size, int Options>
-class TridiagonalMatrix : public BandMatrix<Scalar, Size, Size, Options & SelfAdjoint ? 0 : 1, 1, Options | RowMajor> {
-  typedef BandMatrix<Scalar, Size, Size, Options & SelfAdjoint ? 0 : 1, 1, Options | RowMajor> Base;
-  typedef typename Base::StorageIndex StorageIndex;
+  * \class TridiagonalMatrix
+  * \ingroup Core_Module
+  *
+  * \brief Represents a tridiagonal matrix with a compact banded storage
+  *
+  * \param _Scalar Numeric type, i.e. float, double, int
+  * \param Size Number of rows and cols, or \b Dynamic
+  * \param _Options Can be 0 or \b SelfAdjoint
+  *
+  * \sa class BandMatrix
+  */
+template<typename Scalar, int Size, int Options>
+class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor>
+{
+    typedef BandMatrix<Scalar,Size,Size,Options&SelfAdjoint?0:1,1,Options|RowMajor> Base;
+    typedef typename Base::Index Index;
+  public:
+    TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {}
 
- public:
-  explicit TridiagonalMatrix(Index size = Size) : Base(size, size, Options & SelfAdjoint ? 0 : 1, 1) {}
-
-  inline typename Base::template DiagonalIntReturnType<1>::Type super() { return Base::template diagonal<1>(); }
-  inline const typename Base::template DiagonalIntReturnType<1>::Type super() const {
-    return Base::template diagonal<1>();
-  }
-  inline typename Base::template DiagonalIntReturnType<-1>::Type sub() { return Base::template diagonal<-1>(); }
-  inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const {
-    return Base::template diagonal<-1>();
-  }
-
- protected:
+    inline typename Base::template DiagonalIntReturnType<1>::Type super()
+    { return Base::template diagonal<1>(); }
+    inline const typename Base::template DiagonalIntReturnType<1>::Type super() const
+    { return Base::template diagonal<1>(); }
+    inline typename Base::template DiagonalIntReturnType<-1>::Type sub()
+    { return Base::template diagonal<-1>(); }
+    inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const
+    { return Base::template diagonal<-1>(); }
+  protected:
 };
 
-struct BandShape {};
+} // end namespace internal
 
-template <typename Scalar_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct evaluator_traits<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> >
-    : public evaluator_traits_base<BandMatrix<Scalar_, Rows_, Cols_, Supers_, Subs_, Options_> > {
-  typedef BandShape Shape;
-};
+} // end namespace Eigen
 
-template <typename CoefficientsType_, int Rows_, int Cols_, int Supers_, int Subs_, int Options_>
-struct evaluator_traits<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> >
-    : public evaluator_traits_base<BandMatrixWrapper<CoefficientsType_, Rows_, Cols_, Supers_, Subs_, Options_> > {
-  typedef BandShape Shape;
-};
-
-template <>
-struct AssignmentKind<DenseShape, BandShape> {
-  typedef EigenBase2EigenBase Kind;
-};
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_BANDMATRIX_H
+#endif // EIGEN_BANDMATRIX_H

Eigen/src/Core/Block.h

@@ -11,417 +11,396 @@
 #ifndef EIGEN_BLOCK_H
 #define EIGEN_BLOCK_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+namespace Eigen { 
 
-namespace Eigen {
+/** \class Block
+  * \ingroup Core_Module
+  *
+  * \brief Expression of a fixed-size or dynamic-size block
+  *
+  * \param XprType the type of the expression in which we are taking a block
+  * \param BlockRows the number of rows of the block we are taking at compile time (optional)
+  * \param BlockCols the number of columns of the block we are taking at compile time (optional)
+  *
+  * This class represents an expression of either a fixed-size or dynamic-size block. It is the return
+  * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
+  * most of the time this is the only way it is used.
+  *
+  * However, if you want to directly maniputate block expressions,
+  * for instance if you want to write a function returning such an expression, you
+  * will need to use this class.
+  *
+  * Here is an example illustrating the dynamic case:
+  * \include class_Block.cpp
+  * Output: \verbinclude class_Block.out
+  *
+  * \note Even though this expression has dynamic size, in the case where \a XprType
+  * has fixed size, this expression inherits a fixed maximal size which means that evaluating
+  * it does not cause a dynamic memory allocation.
+  *
+  * Here is an example illustrating the fixed-size case:
+  * \include class_FixedBlock.cpp
+  * Output: \verbinclude class_FixedBlock.out
+  *
+  * \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock
+  */
 
 namespace internal {
-template <typename XprType_, int BlockRows, int BlockCols, bool InnerPanel_>
-struct traits<Block<XprType_, BlockRows, BlockCols, InnerPanel_>> : traits<XprType_> {
-  typedef typename traits<XprType_>::Scalar Scalar;
-  typedef typename traits<XprType_>::StorageKind StorageKind;
-  typedef typename traits<XprType_>::XprKind XprKind;
-  typedef typename ref_selector<XprType_>::type XprTypeNested;
-  typedef std::remove_reference_t<XprTypeNested> XprTypeNested_;
-  enum {
-    MatrixRows = traits<XprType_>::RowsAtCompileTime,
-    MatrixCols = traits<XprType_>::ColsAtCompileTime,
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
+struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel> > : traits<XprType>
+{
+  typedef typename traits<XprType>::Scalar Scalar;
+  typedef typename traits<XprType>::StorageKind StorageKind;
+  typedef typename traits<XprType>::XprKind XprKind;
+  typedef typename nested<XprType>::type XprTypeNested;
+  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  enum{
+    MatrixRows = traits<XprType>::RowsAtCompileTime,
+    MatrixCols = traits<XprType>::ColsAtCompileTime,
     RowsAtCompileTime = MatrixRows == 0 ? 0 : BlockRows,
     ColsAtCompileTime = MatrixCols == 0 ? 0 : BlockCols,
-    MaxRowsAtCompileTime = BlockRows == 0                 ? 0
-                           : RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime)
-                                                          : int(traits<XprType_>::MaxRowsAtCompileTime),
-    MaxColsAtCompileTime = BlockCols == 0                 ? 0
-                           : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
-                                                          : int(traits<XprType_>::MaxColsAtCompileTime),
-
-    XprTypeIsRowMajor = (int(traits<XprType_>::Flags) & RowMajorBit) != 0,
-    IsRowMajor = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1)   ? 1
-                 : (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) ? 0
-                                                                            : XprTypeIsRowMajor,
+    MaxRowsAtCompileTime = BlockRows==0 ? 0
+                         : RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime)
+                         : int(traits<XprType>::MaxRowsAtCompileTime),
+    MaxColsAtCompileTime = BlockCols==0 ? 0
+                         : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime)
+                         : int(traits<XprType>::MaxColsAtCompileTime),
+    XprTypeIsRowMajor = (int(traits<XprType>::Flags)&RowMajorBit) != 0,
+    IsDense = is_same<StorageKind,Dense>::value,
+    IsRowMajor = (IsDense&&MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1
+               : (IsDense&&MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0
+               : XprTypeIsRowMajor,
     HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor),
     InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
-    InnerStrideAtCompileTime = HasSameStorageOrderAsXprType ? int(inner_stride_at_compile_time<XprType_>::ret)
-                                                            : int(outer_stride_at_compile_time<XprType_>::ret),
-    OuterStrideAtCompileTime = HasSameStorageOrderAsXprType ? int(outer_stride_at_compile_time<XprType_>::ret)
-                                                            : int(inner_stride_at_compile_time<XprType_>::ret),
-
-    // FIXME, this traits is rather specialized for dense object and it needs to be cleaned further
-    FlagsLvalueBit = is_lvalue<XprType_>::value ? LvalueBit : 0,
+    InnerStrideAtCompileTime = HasSameStorageOrderAsXprType
+                             ? int(inner_stride_at_compile_time<XprType>::ret)
+                             : int(outer_stride_at_compile_time<XprType>::ret),
+    OuterStrideAtCompileTime = HasSameStorageOrderAsXprType
+                             ? int(outer_stride_at_compile_time<XprType>::ret)
+                             : int(inner_stride_at_compile_time<XprType>::ret),
+    MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits<Scalar>::size) == 0)
+                       && (InnerStrideAtCompileTime == 1)
+                        ? PacketAccessBit : 0,
+    MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) == 0)) ? AlignedBit : 0,
+    FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (traits<XprType>::Flags&LinearAccessBit))) ? LinearAccessBit : 0,
+    FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
     FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
-    Flags = (traits<XprType_>::Flags & (DirectAccessBit | (InnerPanel_ ? CompressedAccessBit : 0))) | FlagsLvalueBit |
-            FlagsRowMajorBit,
-    // FIXME DirectAccessBit should not be handled by expressions
-    //
-    // Alignment is needed by MapBase's assertions
-    // We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the
-    // respective evaluator
-    Alignment = 0,
-    InnerPanel = InnerPanel_ ? 1 : 0
+    Flags0 = traits<XprType>::Flags & ( (HereditaryBits & ~RowMajorBit) |
+                                        DirectAccessBit |
+                                        MaskPacketAccessBit |
+                                        MaskAlignedBit),
+    Flags = Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit
   };
 };
 
-template <typename XprType, int BlockRows = Dynamic, int BlockCols = Dynamic, bool InnerPanel = false,
-          bool HasDirectAccess = internal::has_direct_access<XprType>::ret>
-class BlockImpl_dense;
+template<typename XprType, int BlockRows=Dynamic, int BlockCols=Dynamic, bool InnerPanel = false,
+         bool HasDirectAccess = internal::has_direct_access<XprType>::ret> class BlockImpl_dense;
+         
+} // end namespace internal
 
-}  // end namespace internal
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind> class BlockImpl;
 
-template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind>
-class BlockImpl;
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel> class Block
+  : public BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind>
+{
+    typedef BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> Impl;
+  public:
+    //typedef typename Impl::Base Base;
+    typedef Impl Base;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
+  
+    /** Column or Row constructor
+      */
+    inline Block(XprType& xpr, Index i) : Impl(xpr,i)
+    {
+      eigen_assert( (i>=0) && (
+          ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i<xpr.rows())
+        ||((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && i<xpr.cols())));
+    }
 
-/** \class Block
- * \ingroup Core_Module
- *
- * \brief Expression of a fixed-size or dynamic-size block
- *
- * \tparam XprType the type of the expression in which we are taking a block
- * \tparam BlockRows the number of rows of the block we are taking at compile time (optional)
- * \tparam BlockCols the number of columns of the block we are taking at compile time (optional)
- * \tparam InnerPanel is true, if the block maps to a set of rows of a row major matrix or
- *         to set of columns of a column major matrix (optional). The parameter allows to determine
- *         at compile time whether aligned access is possible on the block expression.
- *
- * This class represents an expression of either a fixed-size or dynamic-size block. It is the return
- * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block<int,int>(Index,Index) and
- * most of the time this is the only way it is used.
- *
- * However, if you want to directly manipulate block expressions,
- * for instance if you want to write a function returning such an expression, you
- * will need to use this class.
- *
- * Here is an example illustrating the dynamic case:
- * \include class_Block.cpp
- * Output: \verbinclude class_Block.out
- *
- * \note Even though this expression has dynamic size, in the case where \a XprType
- * has fixed size, this expression inherits a fixed maximal size which means that evaluating
- * it does not cause a dynamic memory allocation.
- *
- * Here is an example illustrating the fixed-size case:
- * \include class_FixedBlock.cpp
- * Output: \verbinclude class_FixedBlock.out
- *
- * \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock
- */
-template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
-class Block
-    : public BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> {
-  typedef BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, typename internal::traits<XprType>::StorageKind> Impl;
-  using BlockHelper = internal::block_xpr_helper<Block>;
+    /** Fixed-size constructor
+      */
+    inline Block(XprType& xpr, Index a_startRow, Index a_startCol)
+      : Impl(xpr, a_startRow, a_startCol)
+    {
+      EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
+      eigen_assert(a_startRow >= 0 && BlockRows >= 1 && a_startRow + BlockRows <= xpr.rows()
+             && a_startCol >= 0 && BlockCols >= 1 && a_startCol + BlockCols <= xpr.cols());
+    }
 
- public:
-  // typedef typename Impl::Base Base;
-  typedef Impl Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(Block)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
-
-  typedef internal::remove_all_t<XprType> NestedExpression;
-
-  /** Column or Row constructor
-   */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Block(XprType& xpr, Index i) : Impl(xpr, i) {
-    eigen_assert((i >= 0) && (((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) && i < xpr.rows()) ||
-                              ((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) && i < xpr.cols())));
-  }
-
-  /** Fixed-size constructor
-   */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Block(XprType& xpr, Index startRow, Index startCol)
-      : Impl(xpr, startRow, startCol) {
-    EIGEN_STATIC_ASSERT(RowsAtCompileTime != Dynamic && ColsAtCompileTime != Dynamic,
-                        THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
-    eigen_assert(startRow >= 0 && BlockRows >= 0 && startRow + BlockRows <= xpr.rows() && startCol >= 0 &&
-                 BlockCols >= 0 && startCol + BlockCols <= xpr.cols());
-  }
-
-  /** Dynamic-size constructor
-   */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Block(XprType& xpr, Index startRow, Index startCol, Index blockRows,
-                                                        Index blockCols)
-      : Impl(xpr, startRow, startCol, blockRows, blockCols) {
-    eigen_assert((RowsAtCompileTime == Dynamic || RowsAtCompileTime == blockRows) &&
-                 (ColsAtCompileTime == Dynamic || ColsAtCompileTime == blockCols));
-    eigen_assert(startRow >= 0 && blockRows >= 0 && startRow <= xpr.rows() - blockRows && startCol >= 0 &&
-                 blockCols >= 0 && startCol <= xpr.cols() - blockCols);
-  }
-
-  // convert nested blocks (e.g. Block<Block<MatrixType>>) to a simple block expression (Block<MatrixType>)
-
-  using ConstUnwindReturnType = Block<const typename BlockHelper::BaseType, BlockRows, BlockCols, InnerPanel>;
-  using UnwindReturnType = Block<typename BlockHelper::BaseType, BlockRows, BlockCols, InnerPanel>;
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ConstUnwindReturnType unwind() const {
-    return ConstUnwindReturnType(BlockHelper::base(*this), BlockHelper::row(*this, 0), BlockHelper::col(*this, 0),
-                                 this->rows(), this->cols());
-  }
-
-  template <typename T = Block, typename EnableIf = std::enable_if_t<!std::is_const<T>::value>>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE UnwindReturnType unwind() {
-    return UnwindReturnType(BlockHelper::base(*this), BlockHelper::row(*this, 0), BlockHelper::col(*this, 0),
-                            this->rows(), this->cols());
-  }
+    /** Dynamic-size constructor
+      */
+    inline Block(XprType& xpr,
+          Index a_startRow, Index a_startCol,
+          Index blockRows, Index blockCols)
+      : Impl(xpr, a_startRow, a_startCol, blockRows, blockCols)
+    {
+      eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
+          && (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
+      eigen_assert(a_startRow >= 0 && blockRows >= 0 && a_startRow  <= xpr.rows() - blockRows
+          && a_startCol >= 0 && blockCols >= 0 && a_startCol <= xpr.cols() - blockCols);
+    }
 };
-
-// The generic default implementation for dense block simply forward to the internal::BlockImpl_dense
+         
+// The generic default implementation for dense block simplu forward to the internal::BlockImpl_dense
 // that must be specialized for direct and non-direct access...
-template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
 class BlockImpl<XprType, BlockRows, BlockCols, InnerPanel, Dense>
-    : public internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> {
-  typedef internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> Impl;
-  typedef typename XprType::StorageIndex StorageIndex;
-
- public:
-  typedef Impl Base;
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index i) : Impl(xpr, i) {}
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol)
-      : Impl(xpr, startRow, startCol) {}
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol,
-                                                            Index blockRows, Index blockCols)
-      : Impl(xpr, startRow, startCol, blockRows, blockCols) {}
+  : public internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel>
+{
+    typedef internal::BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel> Impl;
+    typedef typename XprType::Index Index;
+  public:
+    typedef Impl Base;
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl)
+    inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {}
+    inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol) : Impl(xpr, a_startRow, a_startCol) {}
+    inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol, Index blockRows, Index blockCols)
+      : Impl(xpr, a_startRow, a_startCol, blockRows, blockCols) {}
 };
 
 namespace internal {
 
 /** \internal Internal implementation of dense Blocks in the general case. */
-template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess>
-class BlockImpl_dense : public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel>>::type {
-  typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
-  typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool HasDirectAccess> class BlockImpl_dense
+  : public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel> >::type
+{
+    typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+  public:
 
- public:
-  typedef typename internal::dense_xpr_base<BlockType>::type Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
+    typedef typename internal::dense_xpr_base<BlockType>::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
 
-  /** Column or Row constructor
-   */
-  EIGEN_DEVICE_FUNC constexpr BlockImpl_dense(XprType& xpr, Index i)
+    class InnerIterator;
+
+    /** Column or Row constructor
+      */
+    inline BlockImpl_dense(XprType& xpr, Index i)
       : m_xpr(xpr),
         // It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime,
         // and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1,
         // all other cases are invalid.
         // The case a 1x1 matrix seems ambiguous, but the result is the same anyway.
-        m_startRow((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) ? i : 0),
-        m_startCol((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) ? i : 0),
-        m_blockRows(BlockRows == 1 ? 1 : xpr.rows()),
-        m_blockCols(BlockCols == 1 ? 1 : xpr.cols()) {}
+        m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0),
+        m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0),
+        m_blockRows(BlockRows==1 ? 1 : xpr.rows()),
+        m_blockCols(BlockCols==1 ? 1 : xpr.cols())
+    {}
 
-  /** Fixed-size constructor
-   */
-  EIGEN_DEVICE_FUNC constexpr BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
-      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(BlockRows), m_blockCols(BlockCols) {}
+    /** Fixed-size constructor
+      */
+    inline BlockImpl_dense(XprType& xpr, Index a_startRow, Index a_startCol)
+      : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
+                    m_blockRows(BlockRows), m_blockCols(BlockCols)
+    {}
 
-  /** Dynamic-size constructor
-   */
-  EIGEN_DEVICE_FUNC constexpr BlockImpl_dense(XprType& xpr, Index startRow, Index startCol, Index blockRows,
-                                              Index blockCols)
-      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(blockRows), m_blockCols(blockCols) {}
+    /** Dynamic-size constructor
+      */
+    inline BlockImpl_dense(XprType& xpr,
+          Index a_startRow, Index a_startCol,
+          Index blockRows, Index blockCols)
+      : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
+                    m_blockRows(blockRows), m_blockCols(blockCols)
+    {}
 
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_blockRows.value(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_blockCols.value(); }
+    inline Index rows() const { return m_blockRows.value(); }
+    inline Index cols() const { return m_blockCols.value(); }
 
-  EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index rowId, Index colId) {
-    EIGEN_STATIC_ASSERT_LVALUE(XprType)
-    return m_xpr.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
-  }
+    inline Scalar& coeffRef(Index rowId, Index colId)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(XprType)
+      return m_xpr.const_cast_derived()
+               .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
-    return m_xpr.derived().coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
-  }
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
+    {
+      return m_xpr.derived()
+               .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const {
-    return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
-  }
+    EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const
+    {
+      return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
+    }
 
-  EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index) {
-    EIGEN_STATIC_ASSERT_LVALUE(XprType)
-    return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-  }
-
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const {
-    return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-  }
-
-  EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const {
-    return m_xpr.coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+    inline Scalar& coeffRef(Index index)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(XprType)
+      return m_xpr.const_cast_derived()
+             .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
                        m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-  }
+    }
 
-  template <int LoadMode>
-  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());
-  }
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_xpr.const_cast_derived()
+             .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+                       m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+    }
 
-  template <int LoadMode>
-  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);
-  }
+    inline const CoeffReturnType coeff(Index index) const
+    {
+      return m_xpr
+             .coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+                    m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+    }
 
-  template <int LoadMode>
-  EIGEN_DEVICE_FUNC inline PacketScalar packet(Index index) const {
-    return m_xpr.template packet<Unaligned>(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                                            m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
-  }
+    template<int LoadMode>
+    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>
-  EIGEN_DEVICE_FUNC inline void writePacket(Index index, const PacketScalar& val) {
-    m_xpr.template writePacket<Unaligned>(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-                                          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val);
-  }
+    template<int LoadMode>
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
+    {
+      m_xpr.const_cast_derived().template writePacket<Unaligned>
+              (rowId + m_startRow.value(), colId + m_startCol.value(), val);
+    }
 
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-  /** \sa MapBase::data() */
-  EIGEN_DEVICE_FUNC constexpr const Scalar* data() const;
-  EIGEN_DEVICE_FUNC inline Index innerStride() const;
-  EIGEN_DEVICE_FUNC inline Index outerStride() const;
-#endif
+    template<int LoadMode>
+    inline PacketScalar packet(Index index) const
+    {
+      return m_xpr.template packet<Unaligned>
+              (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+               m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0));
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression() const {
-    return m_xpr;
-  }
+    template<int LoadMode>
+    inline void writePacket(Index index, const PacketScalar& val)
+    {
+      m_xpr.const_cast_derived().template writePacket<Unaligned>
+         (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val);
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE XprType& nestedExpression() { return m_xpr; }
+    #ifdef EIGEN_PARSED_BY_DOXYGEN
+    /** \sa MapBase::data() */
+    inline const Scalar* data() const;
+    inline Index innerStride() const;
+    inline Index outerStride() const;
+    #endif
 
-  EIGEN_DEVICE_FUNC constexpr StorageIndex startRow() const noexcept { return m_startRow.value(); }
+    const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const 
+    { 
+      return m_xpr; 
+    }
+      
+    Index startRow() const 
+    { 
+      return m_startRow.value(); 
+    }
+      
+    Index startCol() const 
+    { 
+      return m_startCol.value(); 
+    }
 
-  EIGEN_DEVICE_FUNC constexpr StorageIndex startCol() const noexcept { return m_startCol.value(); }
+  protected:
 
- protected:
-  XprTypeNested m_xpr;
-  const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows == 1) ? 0 : Dynamic>
-      m_startRow;
-  const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols == 1) ? 0 : Dynamic>
-      m_startCol;
-  const internal::variable_if_dynamic<StorageIndex, RowsAtCompileTime> m_blockRows;
-  const internal::variable_if_dynamic<StorageIndex, ColsAtCompileTime> m_blockCols;
+    const typename XprType::Nested m_xpr;
+    const internal::variable_if_dynamic<Index, XprType::RowsAtCompileTime == 1 ? 0 : Dynamic> m_startRow;
+    const internal::variable_if_dynamic<Index, XprType::ColsAtCompileTime == 1 ? 0 : Dynamic> m_startCol;
+    const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_blockRows;
+    const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_blockCols;
 };
 
 /** \internal Internal implementation of dense Blocks in the direct access case.*/
-template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
-class BlockImpl_dense<XprType, BlockRows, BlockCols, InnerPanel, true>
-    : public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel>> {
-  typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
-  typedef typename internal::ref_selector<XprType>::non_const_type XprTypeNested;
-  enum { XprTypeIsRowMajor = (int(traits<XprType>::Flags) & RowMajorBit) != 0 };
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
+class BlockImpl_dense<XprType,BlockRows,BlockCols, InnerPanel,true>
+  : public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel> >
+{
+    typedef Block<XprType, BlockRows, BlockCols, InnerPanel> BlockType;
+  public:
 
-  /** \internal Returns base+offset (unless base is null, in which case returns null).
-   * Adding an offset to nullptr is undefined behavior, so we must avoid it.
-   */
-  template <typename Scalar>
-  EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static Scalar* add_to_nullable_pointer(Scalar* base, Index offset) {
-    return base != nullptr ? base + offset : nullptr;
-  }
+    typedef MapBase<BlockType> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
 
- public:
-  typedef MapBase<BlockType> Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
+    /** Column or Row constructor
+      */
+    inline BlockImpl_dense(XprType& xpr, Index i)
+      : Base(internal::const_cast_ptr(&xpr.coeffRef(
+              (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0,
+              (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)),
+             BlockRows==1 ? 1 : xpr.rows(),
+             BlockCols==1 ? 1 : xpr.cols()),
+        m_xpr(xpr)
+    {
+      init();
+    }
 
-  /** Column or Row constructor
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index i)
-      : Base((BlockRows == 0 || BlockCols == 0)
-                 ? nullptr
-                 : add_to_nullable_pointer(
-                       xpr.data(),
-                       i * (((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor)) ||
-                                    ((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) &&
-                                     (XprTypeIsRowMajor))
-                                ? xpr.innerStride()
-                                : xpr.outerStride())),
-             BlockRows == 1 ? 1 : xpr.rows(), BlockCols == 1 ? 1 : xpr.cols()),
-        m_xpr(xpr),
-        m_startRow((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) ? i : 0),
-        m_startCol((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) ? i : 0) {
-    init();
-  }
+    /** Fixed-size constructor
+      */
+    inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
+      : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol))), m_xpr(xpr)
+    {
+      init();
+    }
 
-  /** Fixed-size constructor
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index startRow, Index startCol)
-      : Base((BlockRows == 0 || BlockCols == 0)
-                 ? nullptr
-                 : add_to_nullable_pointer(xpr.data(),
-                                           xpr.innerStride() * (XprTypeIsRowMajor ? startCol : startRow) +
-                                               xpr.outerStride() * (XprTypeIsRowMajor ? startRow : startCol))),
-        m_xpr(xpr),
-        m_startRow(startRow),
-        m_startCol(startCol) {
-    init();
-  }
+    /** Dynamic-size constructor
+      */
+    inline BlockImpl_dense(XprType& xpr,
+          Index startRow, Index startCol,
+          Index blockRows, Index blockCols)
+      : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol)), blockRows, blockCols),
+        m_xpr(xpr)
+    {
+      init();
+    }
 
-  /** Dynamic-size constructor
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index startRow, Index startCol, Index blockRows,
-                                                        Index blockCols)
-      : Base((blockRows == 0 || blockCols == 0)
-                 ? nullptr
-                 : add_to_nullable_pointer(xpr.data(),
-                                           xpr.innerStride() * (XprTypeIsRowMajor ? startCol : startRow) +
-                                               xpr.outerStride() * (XprTypeIsRowMajor ? startRow : startCol)),
-             blockRows, blockCols),
-        m_xpr(xpr),
-        m_startRow(startRow),
-        m_startCol(startCol) {
-    init();
-  }
+    const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const 
+    { 
+      return m_xpr; 
+    }
+      
+    /** \sa MapBase::innerStride() */
+    inline Index innerStride() const
+    {
+      return internal::traits<BlockType>::HasSameStorageOrderAsXprType
+             ? m_xpr.innerStride()
+             : m_xpr.outerStride();
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression() const noexcept {
-    return m_xpr;
-  }
+    /** \sa MapBase::outerStride() */
+    inline Index outerStride() const
+    {
+      return m_outerStride;
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE XprType& nestedExpression() { return m_xpr; }
-
-  /** \sa MapBase::innerStride() */
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept {
-    return internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.innerStride() : m_xpr.outerStride();
-  }
-
-  /** \sa MapBase::outerStride() */
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept {
-    return internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.outerStride() : m_xpr.innerStride();
-  }
-
-  EIGEN_DEVICE_FUNC constexpr StorageIndex startRow() const noexcept { return m_startRow.value(); }
-
-  EIGEN_DEVICE_FUNC constexpr StorageIndex startCol() const noexcept { return m_startCol.value(); }
-
-#ifndef __SUNPRO_CC
+  #ifndef __SUNPRO_CC
   // FIXME sunstudio is not friendly with the above friend...
   // META-FIXME there is no 'friend' keyword around here. Is this obsolete?
- protected:
-#endif
+  protected:
+  #endif
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  /** \internal used by allowAligned() */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows,
-                                                        Index blockCols)
-      : Base(data, blockRows, blockCols), m_xpr(xpr) {
-    init();
-  }
-#endif
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal used by allowAligned() */
+    inline BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows, Index blockCols)
+      : Base(data, blockRows, blockCols), m_xpr(xpr)
+    {
+      init();
+    }
+    #endif
 
- protected:
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void init() {
-    m_outerStride =
-        internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.outerStride() : m_xpr.innerStride();
-  }
+  protected:
+    void init()
+    {
+      m_outerStride = internal::traits<BlockType>::HasSameStorageOrderAsXprType
+                    ? m_xpr.outerStride()
+                    : m_xpr.innerStride();
+    }
 
-  XprTypeNested m_xpr;
-  const internal::variable_if_dynamic<StorageIndex, (XprType::RowsAtCompileTime == 1 && BlockRows == 1) ? 0 : Dynamic>
-      m_startRow;
-  const internal::variable_if_dynamic<StorageIndex, (XprType::ColsAtCompileTime == 1 && BlockCols == 1) ? 0 : Dynamic>
-      m_startCol;
-  Index m_outerStride;
+    typename XprType::Nested m_xpr;
+    Index m_outerStride;
 };
 
-}  // end namespace internal
+} // end namespace internal
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_BLOCK_H
+#endif // EIGEN_BLOCK_H

Eigen/src/Core/BooleanRedux.h

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

Eigen/src/Core/CMakeLists.txt

@@ -0,0 +1,10 @@
+FILE(GLOB Eigen_Core_SRCS "*.h")
+
+INSTALL(FILES
+  ${Eigen_Core_SRCS}
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Core COMPONENT Devel
+  )
+
+ADD_SUBDIRECTORY(products)
+ADD_SUBDIRECTORY(util)
+ADD_SUBDIRECTORY(arch)

Eigen/src/Core/CommaInitializer.h

@@ -11,45 +11,43 @@
 #ifndef EIGEN_COMMAINITIALIZER_H
 #define EIGEN_COMMAINITIALIZER_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
+namespace Eigen { 
 
 /** \class CommaInitializer
- * \ingroup Core_Module
- *
- * \brief Helper class used by the comma initializer operator
- *
- * This class is internally used to implement the comma initializer feature. It is
- * the return type of MatrixBase::operator<<, and most of the time this is the only
- * way it is used.
- *
- * \sa \blank \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
- */
-template <typename XprType>
-struct CommaInitializer {
+  * \ingroup Core_Module
+  *
+  * \brief Helper class used by the comma initializer operator
+  *
+  * This class is internally used to implement the comma initializer feature. It is
+  * the return type of MatrixBase::operator<<, and most of the time this is the only
+  * way it is used.
+  *
+  * \sa \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished()
+  */
+template<typename XprType>
+struct CommaInitializer
+{
   typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::Index Index;
 
-  EIGEN_DEVICE_FUNC constexpr CommaInitializer(XprType& xpr, const Scalar& s)
-      : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1) {
-    eigen_assert(m_xpr.rows() > 0 && m_xpr.cols() > 0 && "Cannot comma-initialize a 0x0 matrix (operator<<)");
-    m_xpr.coeffRef(0, 0) = s;
+  inline CommaInitializer(XprType& xpr, const Scalar& s)
+    : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1)
+  {
+    m_xpr.coeffRef(0,0) = s;
   }
 
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
-      : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows()) {
-    eigen_assert(m_xpr.rows() >= other.rows() && m_xpr.cols() >= other.cols() &&
-                 "Cannot comma-initialize a 0x0 matrix (operator<<)");
-    m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>(0, 0, other.rows(),
-                                                                                           other.cols()) = other;
+  template<typename OtherDerived>
+  inline CommaInitializer(XprType& xpr, const DenseBase<OtherDerived>& other)
+    : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows())
+  {
+    m_xpr.block(0, 0, other.rows(), other.cols()) = other;
   }
 
-  /* Copy/Move constructor which transfers ownership. This is crucial in
+  /* Copy/Move constructor which transfers ownership. This is crucial in 
    * absence of return value optimization to avoid assertions during destruction. */
-  EIGEN_DEVICE_FUNC inline CommaInitializer(const CommaInitializer& o)
-      : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
+  // FIXME in C++11 mode this could be replaced by a proper RValue constructor
+  inline CommaInitializer(const CommaInitializer& o)
+  : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
     // Mark original object as finished. In absence of R-value references we need to const_cast:
     const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
     const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
@@ -57,92 +55,103 @@ struct CommaInitializer {
   }
 
   /* inserts a scalar value in the target matrix */
-  EIGEN_DEVICE_FUNC CommaInitializer &operator,(const Scalar& s) {
-    if (m_col == m_xpr.cols()) {
-      m_row += m_currentBlockRows;
+  CommaInitializer& operator,(const Scalar& s)
+  {
+    if (m_col==m_xpr.cols())
+    {
+      m_row+=m_currentBlockRows;
       m_col = 0;
       m_currentBlockRows = 1;
-      eigen_assert(m_row < m_xpr.rows() && "Too many rows passed to comma initializer (operator<<)");
+      eigen_assert(m_row<m_xpr.rows()
+        && "Too many rows passed to comma initializer (operator<<)");
     }
-    eigen_assert(m_col < m_xpr.cols() && "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows == 1);
+    eigen_assert(m_col<m_xpr.cols()
+      && "Too many coefficients passed to comma initializer (operator<<)");
+    eigen_assert(m_currentBlockRows==1);
     m_xpr.coeffRef(m_row, m_col++) = s;
     return *this;
   }
 
   /* inserts a matrix expression in the target matrix */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC CommaInitializer &operator,(const DenseBase<OtherDerived>& other) {
-    if (m_col == m_xpr.cols() && (other.cols() != 0 || other.rows() != m_currentBlockRows)) {
-      m_row += m_currentBlockRows;
+  template<typename OtherDerived>
+  CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
+  {
+    if(other.rows()==0)
+    {
+      m_col += other.cols();
+      return *this;
+    }
+    if (m_col==m_xpr.cols())
+    {
+      m_row+=m_currentBlockRows;
       m_col = 0;
       m_currentBlockRows = other.rows();
-      eigen_assert(m_row + m_currentBlockRows <= m_xpr.rows() &&
-                   "Too many rows passed to comma initializer (operator<<)");
+      eigen_assert(m_row+m_currentBlockRows<=m_xpr.rows()
+        && "Too many rows passed to comma initializer (operator<<)");
     }
-    eigen_assert((m_col + other.cols() <= m_xpr.cols()) &&
-                 "Too many coefficients passed to comma initializer (operator<<)");
-    eigen_assert(m_currentBlockRows == other.rows());
-    m_xpr.template block<OtherDerived::RowsAtCompileTime, OtherDerived::ColsAtCompileTime>(m_row, m_col, other.rows(),
-                                                                                           other.cols()) = other;
+    eigen_assert((m_col<m_xpr.cols() || (m_xpr.cols()==0 && m_col==0))
+      && "Too many coefficients passed to comma initializer (operator<<)");
+    eigen_assert(m_currentBlockRows==other.rows());
+    if (OtherDerived::SizeAtCompileTime != Dynamic)
+      m_xpr.template block<OtherDerived::RowsAtCompileTime != Dynamic ? OtherDerived::RowsAtCompileTime : 1,
+                              OtherDerived::ColsAtCompileTime != Dynamic ? OtherDerived::ColsAtCompileTime : 1>
+                    (m_row, m_col) = other;
+    else
+      m_xpr.block(m_row, m_col, other.rows(), other.cols()) = other;
     m_col += other.cols();
     return *this;
   }
 
-  EIGEN_DEVICE_FUNC inline ~CommaInitializer()
-#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS
-      noexcept(false)  // Eigen::eigen_assert_exception
-#endif
+  inline ~CommaInitializer()
   {
-    finished();
+    eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows()
+         && m_col == m_xpr.cols()
+         && "Too few coefficients passed to comma initializer (operator<<)");
   }
 
   /** \returns the built matrix once all its coefficients have been set.
-   * Calling finished is 100% optional. Its purpose is to write expressions
-   * like this:
-   * \code
-   * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
-   * \endcode
-   */
-  EIGEN_DEVICE_FUNC inline XprType& finished() {
-    eigen_assert(((m_row + m_currentBlockRows) == m_xpr.rows() || m_xpr.cols() == 0) && m_col == m_xpr.cols() &&
-                 "Too few coefficients passed to comma initializer (operator<<)");
-    return m_xpr;
-  }
+    * Calling finished is 100% optional. Its purpose is to write expressions
+    * like this:
+    * \code
+    * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished());
+    * \endcode
+    */
+  inline XprType& finished() { return m_xpr; }
 
-  XprType& m_xpr;            // target expression
-  Index m_row;               // current row id
-  Index m_col;               // current col id
-  Index m_currentBlockRows;  // current block height
+  XprType& m_xpr;   // target expression
+  Index m_row;              // current row id
+  Index m_col;              // current col id
+  Index m_currentBlockRows; // current block height
 };
 
 /** \anchor MatrixBaseCommaInitRef
- * Convenient operator to set the coefficients of a matrix.
- *
- * The coefficients must be provided in a row major order and exactly match
- * the size of the matrix. Otherwise an assertion is raised.
- *
- * Example: \include MatrixBase_set.cpp
- * Output: \verbinclude MatrixBase_set.out
- *
- * \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary
- * order.
- *
- * \sa CommaInitializer::finished(), class CommaInitializer
- */
-template <typename Derived>
-EIGEN_DEVICE_FUNC inline CommaInitializer<Derived> DenseBase<Derived>::operator<<(const Scalar& s) {
+  * Convenient operator to set the coefficients of a matrix.
+  *
+  * The coefficients must be provided in a row major order and exactly match
+  * the size of the matrix. Otherwise an assertion is raised.
+  *
+  * Example: \include MatrixBase_set.cpp
+  * Output: \verbinclude MatrixBase_set.out
+  * 
+  * \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary order.
+  *
+  * \sa CommaInitializer::finished(), class CommaInitializer
+  */
+template<typename Derived>
+inline CommaInitializer<Derived> DenseBase<Derived>::operator<< (const Scalar& s)
+{
   return CommaInitializer<Derived>(*static_cast<Derived*>(this), s);
 }
 
 /** \sa operator<<(const Scalar&) */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC inline CommaInitializer<Derived> DenseBase<Derived>::operator<<(
-    const DenseBase<OtherDerived>& other) {
-  return CommaInitializer<Derived>(*static_cast<Derived*>(this), other);
+template<typename Derived>
+template<typename OtherDerived>
+inline CommaInitializer<Derived>
+DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
+{
+  return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
 }
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_COMMAINITIALIZER_H
+#endif // EIGEN_COMMAINITIALIZER_H

Eigen/src/Core/ConditionEstimator.h

@@ -1,164 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2016 Rasmus Munk Larsen (rmlarsen@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_CONDITIONESTIMATOR_H
-#define EIGEN_CONDITIONESTIMATOR_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Vector, typename RealVector, bool IsComplex>
-struct rcond_compute_sign {
-  static inline Vector run(const Vector& v) {
-    const RealVector v_abs = v.cwiseAbs();
-    return (v_abs.array() == static_cast<typename Vector::RealScalar>(0))
-        .select(Vector::Ones(v.size()), v.cwiseQuotient(v_abs));
-  }
-};
-
-// Partial specialization to avoid elementwise division for real vectors.
-template <typename Vector>
-struct rcond_compute_sign<Vector, Vector, false> {
-  static inline Vector run(const Vector& v) {
-    return (v.array() < static_cast<typename Vector::RealScalar>(0))
-        .select(-Vector::Ones(v.size()), Vector::Ones(v.size()));
-  }
-};
-
-/**
- * \returns an estimate of ||inv(matrix)||_1 given a decomposition of
- * \a matrix that implements .solve() and .adjoint().solve() methods.
- *
- * This function implements Algorithms 4.1 and 5.1 from
- *   Higham, "Experience with a Matrix Norm Estimator",
- *   SIAM J. Sci. Stat. Comput., 11(4):804-809, 1990.
- * with Higham's alternating-sign safety-net estimate from
- *   Higham and Tisseur, "A Block Algorithm for Matrix 1-Norm Estimation,
- *   with an Application to 1-Norm Pseudospectra", SIAM J. Matrix Anal. Appl.,
- *   21(4):1185-1201, 2000.
- *
- * The Hager/Higham gradient ascent uses at most 5 iterations of 2 solves
- * each, giving a total cost of O(n^2).
- *
- * Supports the following decompositions: FullPivLU, PartialPivLU, LDLT, LLT.
- *
- * \sa FullPivLU, PartialPivLU, LDLT, LLT.
- */
-template <typename Decomposition>
-typename Decomposition::RealScalar rcond_invmatrix_L1_norm_estimate(const Decomposition& dec) {
-  typedef typename Decomposition::MatrixType MatrixType;
-  typedef typename Decomposition::Scalar Scalar;
-  typedef typename Decomposition::RealScalar RealScalar;
-  typedef typename internal::plain_col_type<MatrixType>::type Vector;
-  typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVector;
-  const bool is_complex = (NumTraits<Scalar>::IsComplex != 0);
-
-  eigen_assert(dec.rows() == dec.cols());
-  const Index n = dec.rows();
-  if (n == 0) return RealScalar(0);
-
-    // Disable Index to float conversion warning
-#ifdef __INTEL_COMPILER
-#pragma warning push
-#pragma warning(disable : 2259)
-#endif
-  Vector v = dec.solve(Vector::Ones(n) / Scalar(n));
-#ifdef __INTEL_COMPILER
-#pragma warning pop
-#endif
-
-  // lower_bound is a lower bound on
-  //   ||inv(matrix)||_1  = sup_v ||inv(matrix) v||_1 / ||v||_1
-  // and is the objective maximized by the supergradient ascent algorithm below.
-  RealScalar lower_bound = v.template lpNorm<1>();
-  if (n == 1) return lower_bound;
-
-  // Gradient ascent: the optimum is achieved at a unit vector e_j. Each
-  // iteration follows the supergradient to find which unit vector to probe next.
-  RealScalar old_lower_bound = lower_bound;
-  Vector sign_vector(n);
-  Vector old_sign_vector;
-  Index v_max_abs_index = -1;
-  Index old_v_max_abs_index = v_max_abs_index;
-  for (int k = 0; k < 4; ++k) {
-    sign_vector = internal::rcond_compute_sign<Vector, RealVector, is_complex>::run(v);
-    if (k > 0 && !is_complex && sign_vector == old_sign_vector) {
-      // Break if the sign vector stagnated.
-      break;
-    }
-    // Supergradient: z = A^{-T} * sign(v), pick argmax |z_i|.
-    v = dec.adjoint().solve(sign_vector);
-    v.real().cwiseAbs().maxCoeff(&v_max_abs_index);
-    if (v_max_abs_index == old_v_max_abs_index) {
-      // Optimality: supergradient points to the same unit vector.
-      break;
-    }
-    // Probe the best unit vector: v = A^{-1} * e_j.
-    v = dec.solve(Vector::Unit(n, v_max_abs_index));
-    lower_bound = v.template lpNorm<1>();
-    if (lower_bound <= old_lower_bound) {
-      // No improvement from the gradient step.
-      break;
-    }
-    if (!is_complex) {
-      old_sign_vector = sign_vector;
-    }
-    old_v_max_abs_index = v_max_abs_index;
-    old_lower_bound = lower_bound;
-  }
-  // Higham's alternating-sign estimate: an independent safety-net that catches
-  // cases where the gradient ascent converges to a local maximum due to exact
-  // cancellation patterns (especially with permutations and backsubstitutions).
-  //   v_i = (-1)^i * (1 + i/(n-1)), then estimate = 2*||A^{-1}*v||_1 / (3*n).
-  Scalar alternating_sign(RealScalar(1));
-  for (Index i = 0; i < n; ++i) {
-    // The static_cast is needed when Scalar is complex and RealScalar uses expression templates.
-    v[i] = alternating_sign * static_cast<RealScalar>(RealScalar(1) + (RealScalar(i) / (RealScalar(n - 1))));
-    alternating_sign = -alternating_sign;
-  }
-  v = dec.solve(v);
-  const RealScalar alt_est = (RealScalar(2) * v.template lpNorm<1>()) / (RealScalar(3) * RealScalar(n));
-  return numext::maxi(lower_bound, alt_est);
-}
-
-/** \brief Reciprocal condition number estimator.
- *
- * Computing a decomposition of a dense matrix takes O(n^3) operations, while
- * this method estimates the condition number quickly and reliably in O(n^2)
- * operations.
- *
- * \returns an estimate of the reciprocal condition number
- * (1 / (||matrix||_1 * ||inv(matrix)||_1)) of matrix, given ||matrix||_1 and
- * its decomposition. Supports the following decompositions: FullPivLU,
- * PartialPivLU, LDLT, and LLT.
- *
- * \sa FullPivLU, PartialPivLU, LDLT, LLT.
- */
-template <typename Decomposition>
-typename Decomposition::RealScalar rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm,
-                                                         const Decomposition& dec) {
-  typedef typename Decomposition::RealScalar RealScalar;
-  eigen_assert(dec.rows() == dec.cols());
-  if (dec.rows() == 0) return NumTraits<RealScalar>::infinity();
-  if (numext::is_exactly_zero(matrix_norm)) return RealScalar(0);
-  if (dec.rows() == 1) return RealScalar(1);
-  const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec);
-  return (numext::is_exactly_zero(inverse_matrix_norm) ? RealScalar(0)
-                                                       : (RealScalar(1) / inverse_matrix_norm) / matrix_norm);
-}
-
-}  // namespace internal
-
-}  // namespace Eigen
-
-#endif

Eigen/src/Core/CoreIterators.h

@@ -1,7 +1,7 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
@@ -10,132 +10,52 @@
 #ifndef EIGEN_COREITERATORS_H
 #define EIGEN_COREITERATORS_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
+namespace Eigen { 
 
 /* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
  */
 
-namespace internal {
+/** \ingroup SparseCore_Module
+  * \class InnerIterator
+  * \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression
+  *
+  * todo
+  */
 
-template <typename XprType, typename EvaluatorKind>
-class inner_iterator_selector;
+// generic version for dense matrix and expressions
+template<typename Derived> class DenseBase<Derived>::InnerIterator
+{
+  protected:
+    typedef typename Derived::Scalar Scalar;
+    typedef typename Derived::Index Index;
 
-}
+    enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit };
+  public:
+    EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, Index outer)
+      : m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.innerSize())
+    {}
 
-/** \class InnerIterator
- * \brief An InnerIterator allows to loop over the element of any matrix expression.
- *
- * \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is
- * constructed.
- *
- * TODO: add a usage example
- */
-template <typename XprType>
-class InnerIterator {
- protected:
-  typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
-  typedef internal::evaluator<XprType> EvaluatorType;
-  typedef typename internal::traits<XprType>::Scalar Scalar;
+    EIGEN_STRONG_INLINE Scalar value() const
+    {
+      return (IsRowMajor) ? m_expression.coeff(m_outer, m_inner)
+                          : m_expression.coeff(m_inner, m_outer);
+    }
 
- public:
-  /** Construct an iterator over the \a outerId -th row or column of \a xpr */
-  InnerIterator(const XprType &xpr, const Index &outerId) : m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize()) {}
+    EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
 
-  /// \returns the value of the current coefficient.
-  EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
-  /** Increment the iterator \c *this to the next non-zero coefficient.
-   * Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
-   */
-  EIGEN_STRONG_INLINE InnerIterator &operator++() {
-    m_iter.operator++();
-    return *this;
-  }
-  EIGEN_STRONG_INLINE InnerIterator &operator+=(Index i) {
-    m_iter.operator+=(i);
-    return *this;
-  }
-  EIGEN_STRONG_INLINE InnerIterator operator+(Index i) const {
-    InnerIterator result(*this);
-    result += i;
-    return result;
-  }
+    EIGEN_STRONG_INLINE Index index() const { return m_inner; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
 
-  /// \returns the column or row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
-  /// \returns the row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
-  /// \returns the column index of the current coefficient.
-  EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
-  /// \returns \c true if the iterator \c *this still references a valid coefficient.
-  EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
+    EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
 
- protected:
-  EvaluatorType m_eval;
-  IteratorType m_iter;
-
- private:
-  // If you get here, then you're not using the right InnerIterator type, e.g.:
-  //   SparseMatrix<double,RowMajor> A;
-  //   SparseMatrix<double>::InnerIterator it(A,0);
-  template <typename T>
-  InnerIterator(const EigenBase<T> &, Index outer);
+  protected:
+    const Derived& m_expression;
+    Index m_inner;
+    const Index m_outer;
+    const Index m_end;
 };
 
-namespace internal {
+} // end namespace Eigen
 
-// Generic inner iterator implementation for dense objects
-template <typename XprType>
-class inner_iterator_selector<XprType, IndexBased> {
- protected:
-  typedef evaluator<XprType> EvaluatorType;
-  typedef typename traits<XprType>::Scalar Scalar;
-  enum { IsRowMajor = (XprType::Flags & RowMajorBit) == RowMajorBit };
-
- public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
-      : m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize) {}
-
-  EIGEN_STRONG_INLINE Scalar value() const {
-    return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner) : m_eval.coeff(m_inner, m_outer);
-  }
-
-  EIGEN_STRONG_INLINE inner_iterator_selector &operator++() {
-    m_inner++;
-    return *this;
-  }
-
-  EIGEN_STRONG_INLINE Index index() const { return m_inner; }
-  inline Index row() const { return IsRowMajor ? m_outer : index(); }
-  inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-  EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner >= 0; }
-
- protected:
-  const EvaluatorType &m_eval;
-  Index m_inner;
-  const Index m_outer;
-  const Index m_end;
-};
-
-// For iterator-based evaluator, inner-iterator is already implemented as
-// evaluator<>::InnerIterator
-template <typename XprType>
-class inner_iterator_selector<XprType, IteratorBased> : public evaluator<XprType>::InnerIterator {
- protected:
-  typedef typename evaluator<XprType>::InnerIterator Base;
-  typedef evaluator<XprType> EvaluatorType;
-
- public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId,
-                                              const Index & /*innerSize*/)
-      : Base(eval, outerId) {}
-};
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_COREITERATORS_H
+#endif // EIGEN_COREITERATORS_H

Eigen/src/Core/CwiseBinaryOp.h

@@ -1,7 +1,7 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
@@ -11,17 +11,35 @@
 #ifndef EIGEN_CWISE_BINARY_OP_H
 #define EIGEN_CWISE_BINARY_OP_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
 namespace Eigen {
 
+/** \class CwiseBinaryOp
+  * \ingroup Core_Module
+  *
+  * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
+  *
+  * \param BinaryOp template functor implementing the operator
+  * \param Lhs the type of the left-hand side
+  * \param Rhs the type of the right-hand side
+  *
+  * This class represents an expression  where a coefficient-wise binary operator is applied to two expressions.
+  * It is the return type of binary operators, by which we mean only those binary operators where
+  * both the left-hand side and the right-hand side are Eigen expressions.
+  * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp.
+  *
+  * Most of the time, this is the only way that it is used, so you typically don't have to name
+  * CwiseBinaryOp types explicitly.
+  *
+  * \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp
+  */
+
 namespace internal {
-template <typename BinaryOp, typename Lhs, typename Rhs>
-struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs>> {
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
   // we must not inherit from traits<Lhs> since it has
   // the potential to cause problems with MSVC
-  typedef remove_all_t<Lhs> Ancestor;
+  typedef typename remove_all<Lhs>::type Ancestor;
   typedef typename traits<Ancestor>::XprKind XprKind;
   enum {
     RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
@@ -32,135 +50,181 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs>> {
 
   // even though we require Lhs and Rhs to have the same scalar type (see CwiseBinaryOp constructor),
   // we still want to handle the case when the result type is different.
-  typedef typename result_of<BinaryOp(const typename Lhs::Scalar&, const typename Rhs::Scalar&)>::type Scalar;
-  typedef typename cwise_promote_storage_type<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind,
-                                              BinaryOp>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<Lhs>::StorageIndex, typename traits<Rhs>::StorageIndex>::type
-      StorageIndex;
+  typedef typename result_of<
+                     BinaryOp(
+                       typename Lhs::Scalar,
+                       typename Rhs::Scalar
+                     )
+                   >::type Scalar;
+  typedef typename promote_storage_type<typename traits<Lhs>::StorageKind,
+                                           typename traits<Rhs>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<Lhs>::Index,
+                                         typename traits<Rhs>::Index>::type Index;
   typedef typename Lhs::Nested LhsNested;
   typedef typename Rhs::Nested RhsNested;
-  typedef std::remove_reference_t<LhsNested> LhsNested_;
-  typedef std::remove_reference_t<RhsNested> RhsNested_;
+  typedef typename remove_reference<LhsNested>::type _LhsNested;
+  typedef typename remove_reference<RhsNested>::type _RhsNested;
   enum {
-    Flags = cwise_promote_storage_order<typename traits<Lhs>::StorageKind, typename traits<Rhs>::StorageKind,
-                                        LhsNested_::Flags & RowMajorBit, RhsNested_::Flags & RowMajorBit>::value
+    LhsCoeffReadCost = _LhsNested::CoeffReadCost,
+    RhsCoeffReadCost = _RhsNested::CoeffReadCost,
+    LhsFlags = _LhsNested::Flags,
+    RhsFlags = _RhsNested::Flags,
+    SameType = is_same<typename _LhsNested::Scalar,typename _RhsNested::Scalar>::value,
+    StorageOrdersAgree = (int(Lhs::Flags)&RowMajorBit)==(int(Rhs::Flags)&RowMajorBit),
+    Flags0 = (int(LhsFlags) | int(RhsFlags)) & (
+        HereditaryBits
+      | (int(LhsFlags) & int(RhsFlags) &
+           ( AlignedBit
+           | (StorageOrdersAgree ? LinearAccessBit : 0)
+           | (functor_traits<BinaryOp>::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)
+           )
+        )
+     ),
+    Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit),
+    Cost0 = EIGEN_ADD_COST(LhsCoeffReadCost,RhsCoeffReadCost),
+    CoeffReadCost = EIGEN_ADD_COST(Cost0,functor_traits<BinaryOp>::Cost)
   };
 };
-}  // end namespace internal
+} // end namespace internal
 
-template <typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
+// we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor
+// that would take two operands of different types. If there were such an example, then this check should be
+// moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as
+// currently they take only one typename Scalar template parameter.
+// It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
+// So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
+// add together a float matrix and a double matrix.
+#define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \
+  EIGEN_STATIC_ASSERT((internal::functor_is_product_like<BINOP>::ret \
+                        ? int(internal::scalar_product_traits<LHS, RHS>::Defined) \
+                        : int(internal::is_same<LHS, RHS>::value)), \
+    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+
+template<typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
 class CwiseBinaryOpImpl;
 
-/** \class CwiseBinaryOp
- * \ingroup Core_Module
- *
- * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions
- *
- * \tparam BinaryOp template functor implementing the operator
- * \tparam LhsType the type of the left-hand side
- * \tparam RhsType the type of the right-hand side
- *
- * This class represents an expression  where a coefficient-wise binary operator is applied to two expressions.
- * It is the return type of binary operators, by which we mean only those binary operators where
- * both the left-hand side and the right-hand side are Eigen expressions.
- * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp.
- *
- * Most of the time, this is the only way that it is used, so you typically don't have to name
- * CwiseBinaryOp types explicitly.
- *
- * \sa MatrixBase::binaryExpr(const MatrixBase<OtherDerived> &,const CustomBinaryOp &) const, class CwiseUnaryOp, class
- * CwiseNullaryOp
- */
-template <typename BinaryOp, typename LhsType, typename RhsType>
-class CwiseBinaryOp : public CwiseBinaryOpImpl<BinaryOp, LhsType, RhsType,
-                                               typename internal::cwise_promote_storage_type<
-                                                   typename internal::traits<LhsType>::StorageKind,
-                                                   typename internal::traits<RhsType>::StorageKind, BinaryOp>::ret>,
-                      internal::no_assignment_operator {
- public:
-  typedef internal::remove_all_t<BinaryOp> Functor;
-  typedef internal::remove_all_t<LhsType> Lhs;
-  typedef internal::remove_all_t<RhsType> Rhs;
+template<typename BinaryOp, typename Lhs, typename Rhs>
+class CwiseBinaryOp : internal::no_assignment_operator,
+  public CwiseBinaryOpImpl<
+          BinaryOp, Lhs, Rhs,
+          typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
+                                           typename internal::traits<Rhs>::StorageKind>::ret>
+{
+  public:
 
-  typedef typename CwiseBinaryOpImpl<
-      BinaryOp, LhsType, RhsType,
-      typename internal::cwise_promote_storage_type<typename internal::traits<LhsType>::StorageKind,
-                                                    typename internal::traits<Rhs>::StorageKind, BinaryOp>::ret>::Base
-      Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
+    typedef typename CwiseBinaryOpImpl<
+        BinaryOp, Lhs, Rhs,
+        typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
+                                         typename internal::traits<Rhs>::StorageKind>::ret>::Base Base;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp)
 
-  EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp, typename Lhs::Scalar, typename Rhs::Scalar)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
+    typedef typename internal::nested<Lhs>::type LhsNested;
+    typedef typename internal::nested<Rhs>::type RhsNested;
+    typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
+    typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
 
-  typedef typename internal::ref_selector<LhsType>::type LhsNested;
-  typedef typename internal::ref_selector<RhsType>::type RhsNested;
-  typedef std::remove_reference_t<LhsNested> LhsNested_;
-  typedef std::remove_reference_t<RhsNested> RhsNested_;
+    EIGEN_STRONG_INLINE 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());
+    }
 
-#if EIGEN_COMP_MSVC
-  // Required for Visual Studio, which may fail to inline the copy constructor otherwise.
-  EIGEN_STRONG_INLINE CwiseBinaryOp(const CwiseBinaryOp<BinaryOp, LhsType, RhsType>&) = default;
-#endif
+    EIGEN_STRONG_INLINE Index rows() const {
+      // return the fixed size type if available to enable compile time optimizations
+      if (internal::traits<typename internal::remove_all<LhsNested>::type>::RowsAtCompileTime==Dynamic)
+        return m_rhs.rows();
+      else
+        return m_lhs.rows();
+    }
+    EIGEN_STRONG_INLINE Index cols() const {
+      // return the fixed size type if available to enable compile time optimizations
+      if (internal::traits<typename internal::remove_all<LhsNested>::type>::ColsAtCompileTime==Dynamic)
+        return m_rhs.cols();
+      else
+        return m_lhs.cols();
+    }
 
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs,
-                                                                const BinaryOp& func = BinaryOp())
-      : m_lhs(aLhs), m_rhs(aRhs), m_functor(func) {
-    eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
-  }
+    /** \returns the left hand side nested expression */
+    const _LhsNested& lhs() const { return m_lhs; }
+    /** \returns the right hand side nested expression */
+    const _RhsNested& rhs() const { return m_rhs; }
+    /** \returns the functor representing the binary operation */
+    const BinaryOp& functor() const { return m_functor; }
 
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept {
-    // return the fixed size type if available to enable compile time optimizations
-    return internal::traits<internal::remove_all_t<LhsNested>>::RowsAtCompileTime == Dynamic ? m_rhs.rows()
-                                                                                             : m_lhs.rows();
-  }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept {
-    // return the fixed size type if available to enable compile time optimizations
-    return internal::traits<internal::remove_all_t<LhsNested>>::ColsAtCompileTime == Dynamic ? m_rhs.cols()
-                                                                                             : m_lhs.cols();
-  }
-
-  /** \returns the left hand side nested expression */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE const LhsNested_& lhs() const { return m_lhs; }
-  /** \returns the right hand side nested expression */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE const RhsNested_& rhs() const { return m_rhs; }
-  /** \returns the functor representing the binary operation */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE const BinaryOp& functor() const { return m_functor; }
-
- protected:
-  LhsNested m_lhs;
-  RhsNested m_rhs;
-  const BinaryOp m_functor;
+  protected:
+    LhsNested m_lhs;
+    RhsNested m_rhs;
+    const BinaryOp m_functor;
 };
 
-// Generic API dispatcher
-template <typename BinaryOp, typename Lhs, typename Rhs, typename StorageKind>
-class CwiseBinaryOpImpl : public internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs>>::type {
- public:
-  typedef typename internal::generic_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs>>::type Base;
+template<typename BinaryOp, typename Lhs, typename Rhs>
+class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
+  : public internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type
+{
+    typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
+  public:
+
+    typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
+
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
+    {
+      return derived().functor()(derived().lhs().coeff(rowId, colId),
+                                 derived().rhs().coeff(rowId, colId));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
+    {
+      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
+                                          derived().rhs().template packet<LoadMode>(rowId, colId));
+    }
+
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
+    {
+      return derived().functor()(derived().lhs().coeff(index),
+                                 derived().rhs().coeff(index));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
+    {
+      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(index),
+                                          derived().rhs().template packet<LoadMode>(index));
+    }
 };
 
 /** replaces \c *this by \c *this - \a other.
- *
- * \returns a reference to \c *this
- */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Derived& MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived>& other) {
-  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>());
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+MatrixBase<Derived>::operator-=(const MatrixBase<OtherDerived> &other)
+{
+  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
   return derived();
 }
 
 /** replaces \c *this by \c *this + \a other.
- *
- * \returns a reference to \c *this
- */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Derived& MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other) {
-  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar, typename OtherDerived::Scalar>());
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
+{
+  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived> tmp(derived());
+  tmp = other.derived();
   return derived();
 }
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_CWISE_BINARY_OP_H
+#endif // EIGEN_CWISE_BINARY_OP_H

Eigen/src/Core/CwiseTernaryOp.h

@@ -1,171 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2016 Eugene Brevdo <ebrevdo@gmail.com>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CWISE_TERNARY_OP_H
-#define EIGEN_CWISE_TERNARY_OP_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3>
-struct traits<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>> {
-  // we must not inherit from traits<Arg1> since it has
-  // the potential to cause problems with MSVC
-  typedef remove_all_t<Arg1> Ancestor;
-  typedef typename traits<Ancestor>::XprKind XprKind;
-  enum {
-    RowsAtCompileTime = traits<Ancestor>::RowsAtCompileTime,
-    ColsAtCompileTime = traits<Ancestor>::ColsAtCompileTime,
-    MaxRowsAtCompileTime = traits<Ancestor>::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = traits<Ancestor>::MaxColsAtCompileTime
-  };
-
-  // even though we require Arg1, Arg2, and Arg3 to have the same scalar type
-  // (see CwiseTernaryOp constructor),
-  // we still want to handle the case when the result type is different.
-  typedef typename result_of<TernaryOp(const typename Arg1::Scalar&, const typename Arg2::Scalar&,
-                                       const typename Arg3::Scalar&)>::type Scalar;
-
-  typedef typename internal::traits<Arg1>::StorageKind StorageKind;
-  typedef typename internal::traits<Arg1>::StorageIndex StorageIndex;
-
-  typedef typename Arg1::Nested Arg1Nested;
-  typedef typename Arg2::Nested Arg2Nested;
-  typedef typename Arg3::Nested Arg3Nested;
-  typedef std::remove_reference_t<Arg1Nested> Arg1Nested_;
-  typedef std::remove_reference_t<Arg2Nested> Arg2Nested_;
-  typedef std::remove_reference_t<Arg3Nested> Arg3Nested_;
-  enum { Flags = Arg1Nested_::Flags & RowMajorBit };
-};
-}  // end namespace internal
-
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3, typename StorageKind>
-class CwiseTernaryOpImpl;
-
-/** \class CwiseTernaryOp
- * \ingroup Core_Module
- *
- * \brief Generic expression where a coefficient-wise ternary operator is
- * applied to two expressions
- *
- * \tparam TernaryOp template functor implementing the operator
- * \tparam Arg1Type the type of the first argument
- * \tparam Arg2Type the type of the second argument
- * \tparam Arg3Type the type of the third argument
- *
- * This class represents an expression where a coefficient-wise ternary
- * operator is applied to three expressions.
- * It is the return type of ternary operators, by which we mean only those
- * ternary operators where
- * all three arguments are Eigen expressions.
- * For example, the return type of betainc(matrix1, matrix2, matrix3) is a
- * CwiseTernaryOp.
- *
- * Most of the time, this is the only way that it is used, so you typically
- * don't have to name
- * CwiseTernaryOp types explicitly.
- *
- * \sa MatrixBase::ternaryExpr(const MatrixBase<Argument2> &, const
- * MatrixBase<Argument3> &, const CustomTernaryOp &) const, class CwiseBinaryOp,
- * class CwiseUnaryOp, class CwiseNullaryOp
- */
-template <typename TernaryOp, typename Arg1Type, typename Arg2Type, typename Arg3Type>
-class CwiseTernaryOp : public CwiseTernaryOpImpl<TernaryOp, Arg1Type, Arg2Type, Arg3Type,
-                                                 typename internal::traits<Arg1Type>::StorageKind>,
-                       internal::no_assignment_operator {
- public:
-  typedef internal::remove_all_t<Arg1Type> Arg1;
-  typedef internal::remove_all_t<Arg2Type> Arg2;
-  typedef internal::remove_all_t<Arg3Type> Arg3;
-
-  // require the sizes to match
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg2)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg3)
-
-  // The index types should match
-  EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
-                                         typename internal::traits<Arg2Type>::StorageKind>::value),
-                      STORAGE_KIND_MUST_MATCH)
-  EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Arg1Type>::StorageKind,
-                                         typename internal::traits<Arg3Type>::StorageKind>::value),
-                      STORAGE_KIND_MUST_MATCH)
-
-  typedef typename CwiseTernaryOpImpl<TernaryOp, Arg1Type, Arg2Type, Arg3Type,
-                                      typename internal::traits<Arg1Type>::StorageKind>::Base Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseTernaryOp)
-
-  typedef typename internal::ref_selector<Arg1Type>::type Arg1Nested;
-  typedef typename internal::ref_selector<Arg2Type>::type Arg2Nested;
-  typedef typename internal::ref_selector<Arg3Type>::type Arg3Nested;
-  typedef std::remove_reference_t<Arg1Nested> Arg1Nested_;
-  typedef std::remove_reference_t<Arg2Nested> Arg2Nested_;
-  typedef std::remove_reference_t<Arg3Nested> Arg3Nested_;
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseTernaryOp(const Arg1& a1, const Arg2& a2, const Arg3& a3,
-                                                       const TernaryOp& func = TernaryOp())
-      : m_arg1(a1), m_arg2(a2), m_arg3(a3), m_functor(func) {
-    eigen_assert(a1.rows() == a2.rows() && a1.cols() == a2.cols() && a1.rows() == a3.rows() && a1.cols() == a3.cols());
-  }
-
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Index rows() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
-        internal::traits<internal::remove_all_t<Arg2Nested>>::RowsAtCompileTime == Dynamic)
-      return m_arg3.rows();
-    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
-             internal::traits<internal::remove_all_t<Arg3Nested>>::RowsAtCompileTime == Dynamic)
-      return m_arg2.rows();
-    else
-      return m_arg1.rows();
-  }
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Index cols() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
-        internal::traits<internal::remove_all_t<Arg2Nested>>::ColsAtCompileTime == Dynamic)
-      return m_arg3.cols();
-    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
-             internal::traits<internal::remove_all_t<Arg3Nested>>::ColsAtCompileTime == Dynamic)
-      return m_arg2.cols();
-    else
-      return m_arg1.cols();
-  }
-
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC constexpr const Arg1Nested_& arg1() const { return m_arg1; }
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC constexpr const Arg2Nested_& arg2() const { return m_arg2; }
-  /** \returns the third argument nested expression */
-  EIGEN_DEVICE_FUNC constexpr const Arg3Nested_& arg3() const { return m_arg3; }
-  /** \returns the functor representing the ternary operation */
-  EIGEN_DEVICE_FUNC constexpr const TernaryOp& functor() const { return m_functor; }
-
- protected:
-  Arg1Nested m_arg1;
-  Arg2Nested m_arg2;
-  Arg3Nested m_arg3;
-  const TernaryOp m_functor;
-};
-
-// Generic API dispatcher
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3, typename StorageKind>
-class CwiseTernaryOpImpl : public internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type {
- public:
-  typedef typename internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type Base;
-};
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_CWISE_TERNARY_OP_H

Eigen/src/Core/CwiseUnaryOp.h

@@ -1,7 +1,7 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
@@ -11,85 +11,116 @@
 #ifndef EIGEN_CWISE_UNARY_OP_H
 #define EIGEN_CWISE_UNARY_OP_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-template <typename UnaryOp, typename XprType>
-struct traits<CwiseUnaryOp<UnaryOp, XprType> > : traits<XprType> {
-  typedef typename result_of<UnaryOp(const typename XprType::Scalar&)>::type Scalar;
-  typedef typename XprType::Nested XprTypeNested;
-  typedef std::remove_reference_t<XprTypeNested> XprTypeNested_;
-  enum { Flags = XprTypeNested_::Flags & RowMajorBit };
-};
-}  // namespace internal
-
-template <typename UnaryOp, typename XprType, typename StorageKind>
-class CwiseUnaryOpImpl;
+namespace Eigen { 
 
 /** \class CwiseUnaryOp
- * \ingroup Core_Module
- *
- * \brief Generic expression where a coefficient-wise unary operator is applied to an expression
- *
- * \tparam UnaryOp template functor implementing the operator
- * \tparam XprType the type of the expression to which we are applying the unary operator
- *
- * This class represents an expression where a unary operator is applied to an expression.
- * It is the return type of all operations taking exactly 1 input expression, regardless of the
- * presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix
- * is considered unary, because only the right-hand side is an expression, and its
- * return type is a specialization of CwiseUnaryOp.
- *
- * Most of the time, this is the only way that it is used, so you typically don't have to name
- * CwiseUnaryOp types explicitly.
- *
- * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp
- */
-template <typename UnaryOp, typename XprType>
-class CwiseUnaryOp : public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>,
-                     internal::no_assignment_operator {
- public:
-  typedef typename CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>::Base Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
-  typedef typename internal::ref_selector<XprType>::type XprTypeNested;
-  typedef internal::remove_all_t<XprType> NestedExpression;
+  * \ingroup Core_Module
+  *
+  * \brief Generic expression where a coefficient-wise unary operator is applied to an expression
+  *
+  * \param UnaryOp template functor implementing the operator
+  * \param XprType the type of the expression to which we are applying the unary operator
+  *
+  * This class represents an expression where a unary operator is applied to an expression.
+  * It is the return type of all operations taking exactly 1 input expression, regardless of the
+  * presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix
+  * is considered unary, because only the right-hand side is an expression, and its
+  * return type is a specialization of CwiseUnaryOp.
+  *
+  * Most of the time, this is the only way that it is used, so you typically don't have to name
+  * CwiseUnaryOp types explicitly.
+  *
+  * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp
+  */
 
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE explicit CwiseUnaryOp(const XprType& xpr,
-                                                                        const UnaryOp& func = UnaryOp())
+namespace internal {
+template<typename UnaryOp, typename XprType>
+struct traits<CwiseUnaryOp<UnaryOp, XprType> >
+ : traits<XprType>
+{
+  typedef typename result_of<
+                     UnaryOp(typename XprType::Scalar)
+                   >::type Scalar;
+  typedef typename XprType::Nested XprTypeNested;
+  typedef typename remove_reference<XprTypeNested>::type _XprTypeNested;
+  enum {
+    Flags = _XprTypeNested::Flags & (
+      HereditaryBits | LinearAccessBit | AlignedBit
+      | (functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0)),
+    CoeffReadCost = EIGEN_ADD_COST(_XprTypeNested::CoeffReadCost, functor_traits<UnaryOp>::Cost)
+  };
+};
+}
+
+template<typename UnaryOp, typename XprType, typename StorageKind>
+class CwiseUnaryOpImpl;
+
+template<typename UnaryOp, typename XprType>
+class CwiseUnaryOp : internal::no_assignment_operator,
+  public CwiseUnaryOpImpl<UnaryOp, XprType, typename internal::traits<XprType>::StorageKind>
+{
+  public:
+
+    typedef typename CwiseUnaryOpImpl<UnaryOp, XprType,typename internal::traits<XprType>::StorageKind>::Base Base;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
+
+    inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp())
       : m_xpr(xpr), m_functor(func) {}
 
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_xpr.rows(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_xpr.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); }
 
-  /** \returns the functor representing the unary operation */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE const UnaryOp& functor() const { return m_functor; }
+    /** \returns the functor representing the unary operation */
+    const UnaryOp& functor() const { return m_functor; }
 
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression()
-      const {
-    return m_xpr;
-  }
+    /** \returns the nested expression */
+    const typename internal::remove_all<typename XprType::Nested>::type&
+    nestedExpression() const { return m_xpr; }
 
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE internal::remove_all_t<XprTypeNested>& nestedExpression() {
-    return m_xpr;
-  }
+    /** \returns the nested expression */
+    typename internal::remove_all<typename XprType::Nested>::type&
+    nestedExpression() { return m_xpr.const_cast_derived(); }
 
- protected:
-  XprTypeNested m_xpr;
-  const UnaryOp m_functor;
+  protected:
+    typename XprType::Nested m_xpr;
+    const UnaryOp m_functor;
 };
 
-// Generic API dispatcher
-template <typename UnaryOp, typename XprType, typename StorageKind>
-class CwiseUnaryOpImpl : public internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type {
- public:
-  typedef typename internal::generic_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
+// This is the generic implementation for dense storage.
+// It can be used for any expression types implementing the dense concept.
+template<typename UnaryOp, typename XprType>
+class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
+  : public internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type
+{
+  public:
+
+    typedef CwiseUnaryOp<UnaryOp, XprType> Derived;
+    typedef typename internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(rowId, colId));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
+    {
+      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(rowId, colId));
+    }
+
+    EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(index));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index index) const
+    {
+      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(index));
+    }
 };
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_CWISE_UNARY_OP_H
+#endif // EIGEN_CWISE_UNARY_OP_H

Eigen/src/Core/CwiseUnaryView.h

@@ -10,160 +10,130 @@
 #ifndef EIGEN_CWISE_UNARY_VIEW_H
 #define EIGEN_CWISE_UNARY_VIEW_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
 namespace Eigen {
 
+/** \class CwiseUnaryView
+  * \ingroup Core_Module
+  *
+  * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
+  *
+  * \param ViewOp template functor implementing the view
+  * \param MatrixType the type of the matrix we are applying the unary operator
+  *
+  * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector.
+  * It is the return type of real() and imag(), and most of the time this is the only way it is used.
+  *
+  * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
+  */
+
 namespace internal {
-template <typename ViewOp, typename MatrixType, typename StrideType>
-struct traits<CwiseUnaryView<ViewOp, MatrixType, StrideType> > : traits<MatrixType> {
-  typedef typename result_of<ViewOp(typename traits<MatrixType>::Scalar&)>::type1 ScalarRef;
-  static_assert(std::is_reference<ScalarRef>::value, "Views must return a reference type.");
-  typedef remove_all_t<ScalarRef> Scalar;
+template<typename ViewOp, typename MatrixType>
+struct traits<CwiseUnaryView<ViewOp, MatrixType> >
+ : traits<MatrixType>
+{
+  typedef typename result_of<
+                     ViewOp(typename traits<MatrixType>::Scalar)
+                   >::type Scalar;
   typedef typename MatrixType::Nested MatrixTypeNested;
-  typedef remove_all_t<MatrixTypeNested> MatrixTypeNested_;
+  typedef typename remove_all<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
-    FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags =
-        traits<MatrixTypeNested_>::Flags &
-        (RowMajorBit | FlagsLvalueBit | DirectAccessBit),  // FIXME DirectAccessBit should not be handled by expressions
-    MatrixTypeInnerStride = inner_stride_at_compile_time<MatrixType>::ret,
+    Flags = (traits<_MatrixTypeNested>::Flags & (HereditaryBits | LvalueBit | LinearAccessBit | DirectAccessBit)),
+    CoeffReadCost = EIGEN_ADD_COST(traits<_MatrixTypeNested>::CoeffReadCost, functor_traits<ViewOp>::Cost),
+    MatrixTypeInnerStride =  inner_stride_at_compile_time<MatrixType>::ret,
     // need to cast the sizeof's from size_t to int explicitly, otherwise:
     // "error: no integral type can represent all of the enumerator values
-    InnerStrideAtCompileTime =
-        StrideType::InnerStrideAtCompileTime == 0
-            ? (MatrixTypeInnerStride == Dynamic
-                   ? int(Dynamic)
-                   : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)))
-            : int(StrideType::InnerStrideAtCompileTime),
-
-    OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0
-                                   ? (outer_stride_at_compile_time<MatrixType>::ret == Dynamic
-                                          ? int(Dynamic)
-                                          : outer_stride_at_compile_time<MatrixType>::ret *
-                                                int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)))
-                                   : int(StrideType::OuterStrideAtCompileTime)
+    InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic
+                             ? int(Dynamic)
+                             : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)),
+    OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret == Dynamic
+                             ? int(Dynamic)
+                             : outer_stride_at_compile_time<MatrixType>::ret * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar))
   };
 };
+}
 
-// Generic API dispatcher
-template <typename ViewOp, typename XprType, typename StrideType, typename StorageKind,
-          bool Mutable = !std::is_const<XprType>::value>
-class CwiseUnaryViewImpl : public generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type {
- public:
-  typedef typename generic_xpr_base<CwiseUnaryView<ViewOp, XprType, StrideType> >::type Base;
-};
+template<typename ViewOp, typename MatrixType, typename StorageKind>
+class CwiseUnaryViewImpl;
 
-template <typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false>
-    : public dense_xpr_base<CwiseUnaryView<ViewOp, MatrixType, StrideType> >::type {
- public:
-  typedef CwiseUnaryView<ViewOp, MatrixType, StrideType> Derived;
-  typedef typename dense_xpr_base<CwiseUnaryView<ViewOp, MatrixType, StrideType> >::type Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
+template<typename ViewOp, typename MatrixType>
+class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
+{
+  public:
 
-  EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeffRef(0)); }
+    typedef typename CwiseUnaryViewImpl<ViewOp, MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
+    EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
 
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const {
-    return StrideType::InnerStrideAtCompileTime != 0 ? int(StrideType::InnerStrideAtCompileTime)
-                                                     : derived().nestedExpression().innerStride() *
-                                                           sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar);
-  }
-
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const {
-    return StrideType::OuterStrideAtCompileTime != 0 ? int(StrideType::OuterStrideAtCompileTime)
-                                                     : derived().nestedExpression().outerStride() *
-                                                           sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar);
-  }
-
- protected:
-  EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl)
-
-  // Allow const access to coeffRef for the case of direct access being enabled.
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const {
-    return internal::evaluator<Derived>(derived()).coeffRef(index);
-  }
-
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const {
-    return internal::evaluator<Derived>(derived()).coeffRef(row, col);
-  }
-};
-
-template <typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, true>
-    : public CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false> {
- public:
-  typedef CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType, Dense, false> Base;
-  typedef CwiseUnaryView<ViewOp, MatrixType, StrideType> Derived;
-  EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
-
-  using Base::data;
-  EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) {
-    return internal::evaluator<Derived>(derived()).coeffRef(row, col);
-  }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) {
-    return internal::evaluator<Derived>(derived()).coeffRef(index);
-  }
-
- protected:
-  EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl)
-};
-
-}  // namespace internal
-
-/** \class CwiseUnaryView
- * \ingroup Core_Module
- *
- * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector
- *
- * \tparam ViewOp template functor implementing the view
- * \tparam MatrixType the type of the matrix we are applying the unary operator
- *
- * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector.
- * It is the return type of real() and imag(), and most of the time this is the only way it is used.
- *
- * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp
- */
-template <typename ViewOp, typename MatrixType, typename StrideType>
-class CwiseUnaryView : public internal::CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType,
-                                                           typename internal::traits<MatrixType>::StorageKind> {
- public:
-  typedef typename internal::CwiseUnaryViewImpl<ViewOp, MatrixType, StrideType,
-                                                typename internal::traits<MatrixType>::StorageKind>::Base Base;
-  EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView)
-  typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;
-  typedef internal::remove_all_t<MatrixType> NestedExpression;
-
-  explicit EIGEN_DEVICE_FUNC constexpr inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp())
+    inline CwiseUnaryView(const MatrixType& mat, const ViewOp& func = ViewOp())
       : m_matrix(mat), m_functor(func) {}
 
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView)
 
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_matrix.rows(); }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_matrix.cols(); }
+    EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
 
-  /** \returns the functor representing unary operation */
-  EIGEN_DEVICE_FUNC constexpr const ViewOp& functor() const { return m_functor; }
+    /** \returns the functor representing unary operation */
+    const ViewOp& functor() const { return m_functor; }
 
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC constexpr const internal::remove_all_t<MatrixTypeNested>& nestedExpression() const {
-    return m_matrix;
-  }
+    /** \returns the nested expression */
+    const typename internal::remove_all<typename MatrixType::Nested>::type&
+    nestedExpression() const { return m_matrix; }
 
-  /** \returns the nested expression */
-  EIGEN_DEVICE_FUNC constexpr std::remove_reference_t<MatrixTypeNested>& nestedExpression() { return m_matrix; }
+    /** \returns the nested expression */
+    typename internal::remove_all<typename MatrixType::Nested>::type&
+    nestedExpression() { return m_matrix.const_cast_derived(); }
 
- protected:
-  MatrixTypeNested m_matrix;
-  ViewOp m_functor;
+  protected:
+    // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC
+    typename internal::nested<MatrixType>::type m_matrix;
+    ViewOp m_functor;
 };
 
-}  // namespace Eigen
+template<typename ViewOp, typename MatrixType>
+class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
+  : public internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type
+{
+  public:
 
-#endif  // EIGEN_CWISE_UNARY_VIEW_H
+    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
+    typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
+
+    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
+    
+    inline Scalar* data() { return &coeffRef(0); }
+    inline const Scalar* data() const { return &coeff(0); }
+
+    inline Index innerStride() const
+    {
+      return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
+    }
+
+    inline Index outerStride() const
+    {
+      return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
+    }
+
+    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(row, col));
+    }
+
+    EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(index));
+    }
+
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
+    {
+      return derived().functor()(const_cast_derived().nestedExpression().coeffRef(row, col));
+    }
+
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
+    {
+      return derived().functor()(const_cast_derived().nestedExpression().coeffRef(index));
+    }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_CWISE_UNARY_VIEW_H

Eigen/src/Core/DenseStorage.h

@@ -3,7 +3,7 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2010-2013 Hauke Heibel <hauke.heibel@gmail.com>
+// Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
 //
 // This Source Code Form is subject to the terms of the Mozilla
 // Public License v. 2.0. If a copy of the MPL was not distributed
@@ -13,534 +13,422 @@
 #define EIGEN_MATRIXSTORAGE_H
 
 #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X) \
-  X;                                                \
-  EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
+  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN EIGEN_DENSE_STORAGE_CTOR_PLUGIN;
 #else
-#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X)
+  #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
 #endif
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
 namespace Eigen {
 
 namespace internal {
 
-#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
-#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment)
-#else
-#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment)                                        \
-  eigen_assert((is_constant_evaluated() || (std::uintptr_t(array) % Alignment == 0)) &&     \
-               "this assertion is explained here: "                                         \
-               "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
-               " **** READ THIS WEB PAGE !!! ****");
-#endif
+struct constructor_without_unaligned_array_assert {};
 
-#if EIGEN_STACK_ALLOCATION_LIMIT
-#define EIGEN_MAKE_STACK_ALLOCATION_ASSERT(X) \
-  EIGEN_STATIC_ASSERT(X <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG)
-#else
-#define EIGEN_MAKE_STACK_ALLOCATION_ASSERT(X)
-#endif
-
-/** \internal
- * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned:
- * to 16 bytes boundary if the total size is a multiple of 16 bytes.
- */
-
-template <typename T, int Size, int MatrixOrArrayOptions,
-          int Alignment = (MatrixOrArrayOptions & DontAlign) ? 0 : compute_default_alignment<T, Size>::value>
-struct plain_array {
-  EIGEN_ALIGN_TO_BOUNDARY(Alignment) T array[Size];
-#if defined(EIGEN_NO_DEBUG) || defined(EIGEN_TESTING_PLAINOBJECT_CTOR)
-  EIGEN_DEVICE_FUNC constexpr plain_array() = default;
-#else
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() {
-    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment)
-    EIGEN_MAKE_STACK_ALLOCATION_ASSERT(Size * sizeof(T))
-  }
-#endif
-};
-
-template <typename T, int Size, int MatrixOrArrayOptions>
-struct plain_array<T, Size, MatrixOrArrayOptions, 0> {
-  // on some 32-bit platforms, stack-allocated arrays are aligned to 4 bytes, not the preferred alignment of T
-  EIGEN_ALIGN_TO_BOUNDARY(alignof(T)) T array[Size];
-#if defined(EIGEN_NO_DEBUG) || defined(EIGEN_TESTING_PLAINOBJECT_CTOR)
-  EIGEN_DEVICE_FUNC constexpr plain_array() = default;
-#else
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() { EIGEN_MAKE_STACK_ALLOCATION_ASSERT(Size * sizeof(T)) }
-#endif
-};
-
-template <typename T, int Size, int Options, int Alignment>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap_plain_array(plain_array<T, Size, Options, Alignment>& a,
-                                                                      plain_array<T, Size, Options, Alignment>& b,
-                                                                      Index a_size, Index b_size) {
-  Index common_size = numext::mini(a_size, b_size);
-  std::swap_ranges(a.array, a.array + common_size, b.array);
-  if (a_size > b_size)
-    smart_copy(a.array + common_size, a.array + a_size, b.array + common_size);
-  else if (b_size > a_size)
-    smart_copy(b.array + common_size, b.array + b_size, a.array + common_size);
+template<typename T, int Size> void check_static_allocation_size()
+{
+  // if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit
+  #if EIGEN_STACK_ALLOCATION_LIMIT
+  EIGEN_STATIC_ASSERT(Size * sizeof(T) <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+  #endif
 }
 
-template <typename T, int Size, int Rows, int Cols, int Options>
-class DenseStorage_impl {
-  plain_array<T, Size, Options> m_data;
+/** \internal
+  * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned:
+  * to 16 bytes boundary if the total size is a multiple of 16 bytes.
+  */
+template <typename T, int Size, int MatrixOrArrayOptions,
+          int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
+                        : (((Size*sizeof(T))%16)==0) ? 16
+                        : 0 >
+struct plain_array
+{
+  T array[Size];
 
- public:
-#ifndef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
+  plain_array() 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    check_static_allocation_size<T,Size>();
+  }
+};
+
+#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask)
+#elif EIGEN_GNUC_AT_LEAST(4,7) 
+  // GCC 4.7 is too aggressive in its optimizations and remove the alignement test based on the fact the array is declared to be aligned.
+  // See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900
+  // Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined:
+  template<typename PtrType>
+  EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; }
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
+    eigen_assert((reinterpret_cast<size_t>(eigen_unaligned_array_assert_workaround_gcc47(array)) & sizemask) == 0 \
+              && "this assertion is explained here: " \
+              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
+              " **** READ THIS WEB PAGE !!! ****");
 #else
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size)
-    smart_copy(other.m_data.array, other.m_data.array + Size, m_data.array);
-  }
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
+    eigen_assert((reinterpret_cast<size_t>(array) & sizemask) == 0 \
+              && "this assertion is explained here: " \
+              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
+              " **** READ THIS WEB PAGE !!! ****");
 #endif
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
-    numext::swap(m_data, other.m_data);
-  }
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return Rows * Cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
-};
-template <typename T, int Size, int Cols, int Options>
-class DenseStorage_impl<T, Size, Dynamic, Cols, Options> {
-  plain_array<T, Size, Options> m_data;
-  Index m_rows = 0;
 
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
-      : m_rows(other.m_rows) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
-    smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index /*cols*/)
-      : m_rows(rows) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-    EIGEN_UNUSED_VARIABLE(size);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
-    smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
-    m_rows = other.m_rows;
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
-    swap_plain_array(m_data, other.m_data, size(), other.size());
-    numext::swap(m_rows, other.m_rows);
-  }
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) { m_rows = rows; }
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) { m_rows = rows; }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return m_rows * Cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
-};
-template <typename T, int Size, int Rows, int Options>
-class DenseStorage_impl<T, Size, Rows, Dynamic, Options> {
-  plain_array<T, Size, Options> m_data;
-  Index m_cols = 0;
+template <typename T, int Size, int MatrixOrArrayOptions>
+struct plain_array<T, Size, MatrixOrArrayOptions, 16>
+{
+  EIGEN_USER_ALIGN16 T array[Size];
 
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
-      : m_cols(other.m_cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
-    smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
+  plain_array() 
+  { 
+    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf);
+    check_static_allocation_size<T,Size>();
   }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index /*rows*/, Index cols)
-      : m_cols(cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-    EIGEN_UNUSED_VARIABLE(size);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
-    smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
-    m_cols = other.m_cols;
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
-    swap_plain_array(m_data, other.m_data, size(), other.size());
-    numext::swap(m_cols, other.m_cols);
-  }
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) { m_cols = cols; }
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) { m_cols = cols; }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return Rows * m_cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
-};
-template <typename T, int Size, int Options>
-class DenseStorage_impl<T, Size, Dynamic, Dynamic, Options> {
-  plain_array<T, Size, Options> m_data;
-  Index m_rows = 0;
-  Index m_cols = 0;
 
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
-      : m_rows(other.m_rows), m_cols(other.m_cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
-    smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    check_static_allocation_size<T,Size>();
   }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index cols)
-      : m_rows(rows), m_cols(cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-    EIGEN_UNUSED_VARIABLE(size);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
-    smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array);
-    m_rows = other.m_rows;
-    m_cols = other.m_cols;
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) {
-    swap_plain_array(m_data, other.m_data, size(), other.size());
-    numext::swap(m_rows, other.m_rows);
-    numext::swap(m_cols, other.m_cols);
-  }
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index rows, Index cols) {
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index rows, Index cols) {
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return m_rows * m_cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data.array; }
 };
-// null matrix variants
-template <typename T, int Rows, int Cols, int Options>
-class DenseStorage_impl<T, 0, Rows, Cols, Options> {
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage_impl&) {}
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return Rows * Cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return nullptr; }
-};
-template <typename T, int Cols, int Options>
-class DenseStorage_impl<T, 0, Dynamic, Cols, Options> {
-  Index m_rows = 0;
 
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(Index /*size*/, Index rows, Index /*cols*/) : m_rows(rows) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage_impl& other) noexcept { numext::swap(m_rows, other.m_rows); }
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) { m_rows = rows; }
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) { m_rows = rows; }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return m_rows * Cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return nullptr; }
+template <typename T, int MatrixOrArrayOptions, int Alignment>
+struct plain_array<T, 0, MatrixOrArrayOptions, Alignment>
+{
+  EIGEN_USER_ALIGN16 T array[1];
+  plain_array() {}
+  plain_array(constructor_without_unaligned_array_assert) {}
 };
-template <typename T, int Rows, int Options>
-class DenseStorage_impl<T, 0, Rows, Dynamic, Options> {
-  Index m_cols = 0;
 
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index cols) : m_cols(cols) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage_impl& other) noexcept { numext::swap(m_cols, other.m_cols); }
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) { m_cols = cols; }
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) { m_cols = cols; }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return Rows * m_cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return nullptr; }
-};
-template <typename T, int Options>
-class DenseStorage_impl<T, 0, Dynamic, Dynamic, Options> {
-  Index m_rows = 0;
-  Index m_cols = 0;
-
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(Index /*size*/, Index rows, Index cols) : m_rows(rows), m_cols(cols) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage_impl& other) noexcept {
-    numext::swap(m_rows, other.m_rows);
-    numext::swap(m_cols, other.m_cols);
-  }
-  EIGEN_DEVICE_FUNC constexpr void conservativeResize(Index /*size*/, Index rows, Index cols) {
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC constexpr void resize(Index /*size*/, Index rows, Index cols) {
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return m_rows * m_cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return nullptr; }
-};
-// fixed-size matrix with dynamic memory allocation not currently supported
-template <typename T, int Rows, int Cols, int Options>
-class DenseStorage_impl<T, Dynamic, Rows, Cols, Options> {};
-// dynamic-sized variants
-template <typename T, int Cols, int Options>
-class DenseStorage_impl<T, Dynamic, Dynamic, Cols, Options> {
-  static constexpr bool Align = (Options & DontAlign) == 0;
-  T* m_data = nullptr;
-  Index m_rows = 0;
-
- public:
-  static constexpr int Size = Dynamic;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
-      : m_data(conditional_aligned_new_auto<T, Align>(other.size())), m_rows(other.m_rows) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
-    smart_copy(other.m_data, other.m_data + other.size(), m_data);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index /*cols*/)
-      : m_data(conditional_aligned_new_auto<T, Align>(size)), m_rows(rows) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-  }
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept
-      : m_data(other.m_data), m_rows(other.m_rows) {
-    other.m_data = nullptr;
-    other.m_rows = 0;
-  }
-  EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto<T, Align>(m_data, size()); }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
-    resize(other.size(), other.rows(), other.cols());
-    smart_copy(other.m_data, other.m_data + other.size(), m_data);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
-    this->swap(other);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage_impl& other) noexcept {
-    numext::swap(m_data, other.m_data);
-    numext::swap(m_rows, other.m_rows);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index rows, Index /*cols*/) {
-    m_data = conditional_aligned_realloc_new_auto<T, Align>(m_data, size, this->size());
-    m_rows = rows;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index rows, Index /*cols*/) {
-    Index oldSize = this->size();
-    if (oldSize != size) {
-      conditional_aligned_delete_auto<T, Align>(m_data, oldSize);
-      m_data = conditional_aligned_new_auto<T, Align>(size);
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-    }
-    m_rows = rows;
-  }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return m_rows * Cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return m_data; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data; }
-};
-template <typename T, int Rows, int Options>
-class DenseStorage_impl<T, Dynamic, Rows, Dynamic, Options> {
-  static constexpr bool Align = (Options & DontAlign) == 0;
-  T* m_data = nullptr;
-  Index m_cols = 0;
-
- public:
-  static constexpr int Size = Dynamic;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
-      : m_data(conditional_aligned_new_auto<T, Align>(other.size())), m_cols(other.m_cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
-    smart_copy(other.m_data, other.m_data + other.size(), m_data);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index /*rows*/, Index cols)
-      : m_data(conditional_aligned_new_auto<T, Align>(size)), m_cols(cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-  }
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept
-      : m_data(other.m_data), m_cols(other.m_cols) {
-    other.m_data = nullptr;
-    other.m_cols = 0;
-  }
-  EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto<T, Align>(m_data, size()); }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
-    resize(other.size(), other.rows(), other.cols());
-    smart_copy(other.m_data, other.m_data + other.size(), m_data);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
-    this->swap(other);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage_impl& other) noexcept {
-    numext::swap(m_data, other.m_data);
-    numext::swap(m_cols, other.m_cols);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index /*rows*/, Index cols) {
-    m_data = conditional_aligned_realloc_new_auto<T, Align>(m_data, size, this->size());
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index /*rows*/, Index cols) {
-    Index oldSize = this->size();
-    if (oldSize != size) {
-      conditional_aligned_delete_auto<T, Align>(m_data, oldSize);
-      m_data = conditional_aligned_new_auto<T, Align>(size);
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-    }
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return Rows * m_cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return m_data; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data; }
-};
-template <typename T, int Options>
-class DenseStorage_impl<T, Dynamic, Dynamic, Dynamic, Options> {
-  static constexpr bool Align = (Options & DontAlign) == 0;
-  T* m_data = nullptr;
-  Index m_rows = 0;
-  Index m_cols = 0;
-
- public:
-  static constexpr int Size = Dynamic;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other)
-      : m_data(conditional_aligned_new_auto<T, Align>(other.size())), m_rows(other.m_rows), m_cols(other.m_cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size())
-    smart_copy(other.m_data, other.m_data + other.size(), m_data);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index cols)
-      : m_data(conditional_aligned_new_auto<T, Align>(size)), m_rows(rows), m_cols(cols) {
-    EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-  }
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept
-      : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {
-    other.m_data = nullptr;
-    other.m_rows = 0;
-    other.m_cols = 0;
-  }
-  EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto<T, Align>(m_data, size()); }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) {
-    resize(other.size(), other.rows(), other.cols());
-    smart_copy(other.m_data, other.m_data + other.size(), m_data);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
-    this->swap(other);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC constexpr void swap(DenseStorage_impl& other) noexcept {
-    numext::swap(m_data, other.m_data);
-    numext::swap(m_rows, other.m_rows);
-    numext::swap(m_cols, other.m_cols);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index rows, Index cols) {
-    m_data = conditional_aligned_realloc_new_auto<T, Align>(m_data, size, this->size());
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index rows, Index cols) {
-    Index oldSize = this->size();
-    if (oldSize != size) {
-      conditional_aligned_delete_auto<T, Align>(m_data, oldSize);
-      m_data = conditional_aligned_new_auto<T, Align>(size);
-      EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({})
-    }
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC constexpr Index size() const { return m_rows * m_cols; }
-  EIGEN_DEVICE_FUNC constexpr T* data() { return m_data; }
-  EIGEN_DEVICE_FUNC constexpr const T* data() const { return m_data; }
-};
-template <typename T, int Size, int Rows, int Cols>
-struct use_default_move {
-  static constexpr bool DynamicObject = Size == Dynamic;
-  static constexpr bool TrivialObject =
-      (!NumTraits<T>::RequireInitialization) && (Rows >= 0) && (Cols >= 0) && (Size == Rows * Cols);
-  static constexpr bool value = DynamicObject || TrivialObject;
-};
-}  // end namespace internal
+} // end namespace internal
 
 /** \internal
- *
- * \class DenseStorage_impl
- * \ingroup Core_Module
- *
- * \brief Stores the data of a matrix
- *
- * This class stores the data of fixed-size, dynamic-size or mixed matrices
- * in a way as compact as possible.
- *
- * \sa Matrix
- */
-template <typename T, int Size, int Rows, int Cols, int Options,
-          bool Trivial = internal::use_default_move<T, Size, Rows, Cols>::value>
-class DenseStorage : public internal::DenseStorage_impl<T, Size, Rows, Cols, Options> {
-  using Base = internal::DenseStorage_impl<T, Size, Rows, Cols, Options>;
+  *
+  * \class DenseStorage
+  * \ingroup Core_Module
+  *
+  * \brief Stores the data of a matrix
+  *
+  * This class stores the data of fixed-size, dynamic-size or mixed matrices
+  * in a way as compact as possible.
+  *
+  * \sa Matrix
+  */
+template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage;
 
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage() = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage(const DenseStorage&) = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage(Index size, Index rows, Index cols) : Base(size, rows, cols) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage& operator=(const DenseStorage&) = default;
-  // if DenseStorage meets the requirements of use_default_move, then use the move construction and move assignment
-  // operation defined in DenseStorage_impl, or the compiler-generated version if none is defined
-  EIGEN_DEVICE_FUNC constexpr DenseStorage(DenseStorage&&) = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage& operator=(DenseStorage&&) = default;
-};
-template <typename T, int Size, int Rows, int Cols, int Options>
-class DenseStorage<T, Size, Rows, Cols, Options, false>
-    : public internal::DenseStorage_impl<T, Size, Rows, Cols, Options> {
-  using Base = internal::DenseStorage_impl<T, Size, Rows, Cols, Options>;
-
- public:
-  EIGEN_DEVICE_FUNC constexpr DenseStorage() = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage(const DenseStorage&) = default;
-  EIGEN_DEVICE_FUNC constexpr DenseStorage(Index size, Index rows, Index cols) : Base(size, rows, cols) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage& operator=(const DenseStorage&) = default;
-  // if DenseStorage does not meet the requirements of use_default_move, then defer to the copy construction and copy
-  // assignment behavior
-  EIGEN_DEVICE_FUNC constexpr DenseStorage(DenseStorage&& other)
-      : DenseStorage(static_cast<const DenseStorage&>(other)) {}
-  EIGEN_DEVICE_FUNC constexpr DenseStorage& operator=(DenseStorage&& other) {
-    *this = other;
-    return *this;
-  }
+// purely fixed-size matrix
+template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseStorage
+{
+    internal::plain_array<T,Size,_Options> m_data;
+  public:
+    DenseStorage() {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data) {}
+    DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other) m_data = other.m_data;
+      return *this;
+    }
+    DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
+    static DenseIndex rows(void) {return _Rows;}
+    static DenseIndex cols(void) {return _Cols;}
+    void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    const T *data() const { return m_data.array; }
+    T *data() { return m_data.array; }
 };
 
-}  // end namespace Eigen
+// null matrix
+template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
+{
+  public:
+    DenseStorage() {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert) {}
+    DenseStorage(const DenseStorage&) {}
+    DenseStorage& operator=(const DenseStorage&) { return *this; }
+    DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    void swap(DenseStorage& ) {}
+    static DenseIndex rows(void) {return _Rows;}
+    static DenseIndex cols(void) {return _Cols;}
+    void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    const T *data() const { return 0; }
+    T *data() { return 0; }
+};
 
-#endif  // EIGEN_MATRIX_H
+// more specializations for null matrices; these are necessary to resolve ambiguities
+template<typename T, int _Options> class DenseStorage<T, 0, Dynamic, Dynamic, _Options>
+: public DenseStorage<T, 0, 0, 0, _Options> { };
+
+template<typename T, int _Rows, int _Options> class DenseStorage<T, 0, _Rows, Dynamic, _Options>
+: public DenseStorage<T, 0, 0, 0, _Options> { };
+
+template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic, _Cols, _Options>
+: public DenseStorage<T, 0, 0, 0, _Options> { };
+
+// dynamic-size matrix with fixed-size storage
+template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_rows;
+    DenseIndex m_cols;
+  public:
+    DenseStorage() : m_rows(0), m_cols(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {}
+    DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        m_data = other.m_data;
+        m_rows = other.m_rows;
+        m_cols = other.m_cols;
+      }
+      return *this;
+    }
+    DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
+    void swap(DenseStorage& other)
+    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
+    DenseIndex rows() const {return m_rows;}
+    DenseIndex cols() const {return m_cols;}
+    void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+    void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+    const T *data() const { return m_data.array; }
+    T *data() { return m_data.array; }
+};
+
+// dynamic-size matrix with fixed-size storage and fixed width
+template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_rows;
+  public:
+    DenseStorage() : m_rows(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {}
+    DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        m_data = other.m_data;
+        m_rows = other.m_rows;
+      }
+      return *this;
+    }
+    DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
+    void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    DenseIndex rows(void) const {return m_rows;}
+    DenseIndex cols(void) const {return _Cols;}
+    void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+    void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+    const T *data() const { return m_data.array; }
+    T *data() { return m_data.array; }
+};
+
+// dynamic-size matrix with fixed-size storage and fixed height
+template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_cols;
+  public:
+    DenseStorage() : m_cols(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
+    DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {}
+    DenseStorage& operator=(const DenseStorage& other)
+    {
+      if (this != &other)
+      {
+        m_data = other.m_data;
+        m_cols = other.m_cols;
+      }
+      return *this;
+    }
+    DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
+    void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    DenseIndex rows(void) const {return _Rows;}
+    DenseIndex cols(void) const {return m_cols;}
+    void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+    void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+    const T *data() const { return m_data.array; }
+    T *data() { return m_data.array; }
+};
+
+// purely dynamic matrix.
+template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
+{
+    T *m_data;
+    DenseIndex m_rows;
+    DenseIndex m_cols;
+  public:
+    DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert)
+       : m_data(0), m_rows(0), m_cols(0) {}
+    DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
+    DenseStorage(DenseStorage&& other)
+      : m_data(std::move(other.m_data))
+      , m_rows(std::move(other.m_rows))
+      , m_cols(std::move(other.m_cols))
+    {
+      other.m_data = nullptr;
+    }
+    DenseStorage& operator=(DenseStorage&& other)
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_rows, other.m_rows);
+      swap(m_cols, other.m_cols);
+      return *this;
+    }
+#endif
+    ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
+    void swap(DenseStorage& other)
+    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
+    DenseIndex rows(void) const {return m_rows;}
+    DenseIndex cols(void) const {return m_cols;}
+    void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
+      m_rows = nbRows;
+      m_cols = nbCols;
+    }
+    void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+    {
+      if(size != m_rows*m_cols)
+      {
+        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_rows = nbRows;
+      m_cols = nbCols;
+    }
+    const T *data() const { return m_data; }
+    T *data() { return m_data; }
+  private:
+    DenseStorage(const DenseStorage&);
+    DenseStorage& operator=(const DenseStorage&);
+};
+
+// matrix with dynamic width and fixed height (so that matrix has dynamic size).
+template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
+{
+    T *m_data;
+    DenseIndex m_cols;
+  public:
+    DenseStorage() : m_data(0), m_cols(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
+    DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
+    DenseStorage(DenseStorage&& other)
+      : m_data(std::move(other.m_data))
+      , m_cols(std::move(other.m_cols))
+    {
+      other.m_data = nullptr;
+    }
+    DenseStorage& operator=(DenseStorage&& other)
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_cols, other.m_cols);
+      return *this;
+    }
+#endif
+    ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
+    void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    static DenseIndex rows(void) {return _Rows;}
+    DenseIndex cols(void) const {return m_cols;}
+    void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
+      m_cols = nbCols;
+    }
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols)
+    {
+      if(size != _Rows*m_cols)
+      {
+        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_cols = nbCols;
+    }
+    const T *data() const { return m_data; }
+    T *data() { return m_data; }
+  private:
+    DenseStorage(const DenseStorage&);
+    DenseStorage& operator=(const DenseStorage&);
+};
+
+// matrix with dynamic height and fixed width (so that matrix has dynamic size).
+template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
+{
+    T *m_data;
+    DenseIndex m_rows;
+  public:
+    DenseStorage() : m_data(0), m_rows(0) {}
+    DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
+    DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+#ifdef EIGEN_HAVE_RVALUE_REFERENCES
+    DenseStorage(DenseStorage&& other)
+      : m_data(std::move(other.m_data))
+      , m_rows(std::move(other.m_rows))
+    {
+      other.m_data = nullptr;
+    }
+    DenseStorage& operator=(DenseStorage&& other)
+    {
+      using std::swap;
+      swap(m_data, other.m_data);
+      swap(m_rows, other.m_rows);
+      return *this;
+    }
+#endif
+    ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
+    void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    DenseIndex rows(void) const {return m_rows;}
+    static DenseIndex cols(void) {return _Cols;}
+    void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
+      m_rows = nbRows;
+    }
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex)
+    {
+      if(size != m_rows*_Cols)
+      {
+        internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows);
+        if (size)
+          m_data = internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size);
+        else
+          m_data = 0;
+        EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
+      }
+      m_rows = nbRows;
+    }
+    const T *data() const { return m_data; }
+    T *data() { return m_data; }
+  private:
+    DenseStorage(const DenseStorage&);
+    DenseStorage& operator=(const DenseStorage&);
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_MATRIX_H

Eigen/src/Core/DeviceWrapper.h

@@ -1,153 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2023 Charlie Schlosser <cs.schlosser@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_DEVICEWRAPPER_H
-#define EIGEN_DEVICEWRAPPER_H
-
-namespace Eigen {
-template <typename Derived, typename Device>
-struct DeviceWrapper {
-  using Base = EigenBase<internal::remove_all_t<Derived>>;
-  using Scalar = typename Derived::Scalar;
-
-  EIGEN_DEVICE_FUNC DeviceWrapper(Base& xpr, Device& device) : m_xpr(xpr.derived()), m_device(device) {}
-  EIGEN_DEVICE_FUNC DeviceWrapper(const Base& xpr, Device& device) : m_xpr(xpr.derived()), m_device(device) {}
-
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const EigenBase<OtherDerived>& other) {
-    using AssignOp = internal::assign_op<Scalar, typename OtherDerived::Scalar>;
-    internal::call_assignment(*this, other.derived(), AssignOp());
-    return m_xpr;
-  }
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const EigenBase<OtherDerived>& other) {
-    using AddAssignOp = internal::add_assign_op<Scalar, typename OtherDerived::Scalar>;
-    internal::call_assignment(*this, other.derived(), AddAssignOp());
-    return m_xpr;
-  }
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const EigenBase<OtherDerived>& other) {
-    using SubAssignOp = internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>;
-    internal::call_assignment(*this, other.derived(), SubAssignOp());
-    return m_xpr;
-  }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& derived() { return m_xpr; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Device& device() { return m_device; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NoAlias<DeviceWrapper, EigenBase> noalias() {
-    return NoAlias<DeviceWrapper, EigenBase>(*this);
-  }
-
-  Derived& m_xpr;
-  Device& m_device;
-};
-
-namespace internal {
-
-// this is where we differentiate between lazy assignment and specialized kernels (e.g. matrix products)
-template <typename DstXprType, typename SrcXprType, typename Functor, typename Device,
-          typename Kind = typename AssignmentKind<typename evaluator_traits<DstXprType>::Shape,
-                                                  typename evaluator_traits<SrcXprType>::Shape>::Kind,
-          typename EnableIf = void>
-struct AssignmentWithDevice;
-
-// unless otherwise specified, use the default product implementation
-template <typename DstXprType, typename Lhs, typename Rhs, int Options, typename Functor, typename Device,
-          typename Weak>
-struct AssignmentWithDevice<DstXprType, Product<Lhs, Rhs, Options>, Functor, Device, Dense2Dense, Weak> {
-  using SrcXprType = Product<Lhs, Rhs, Options>;
-  using Base = Assignment<DstXprType, SrcXprType, Functor>;
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, const Functor& func,
-                                                        Device&) {
-    Base::run(dst, src, func);
-  }
-};
-
-// specialization for coeffcient-wise assignment
-template <typename DstXprType, typename SrcXprType, typename Functor, typename Device, typename Weak>
-struct AssignmentWithDevice<DstXprType, SrcXprType, Functor, Device, Dense2Dense, Weak> {
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, const Functor& func,
-                                                        Device& device) {
-#ifndef EIGEN_NO_DEBUG
-    internal::check_for_aliasing(dst, src);
-#endif
-
-    call_dense_assignment_loop(dst, src, func, device);
-  }
-};
-
-// this allows us to use the default evaluation scheme if it is not specialized for the device
-template <typename Kernel, typename Device, int Traversal = Kernel::AssignmentTraits::Traversal,
-          int Unrolling = Kernel::AssignmentTraits::Unrolling>
-struct dense_assignment_loop_with_device {
-  using Base = dense_assignment_loop<Kernel, Traversal, Unrolling>;
-  static EIGEN_DEVICE_FUNC constexpr void run(Kernel& kernel, Device&) { Base::run(kernel); }
-};
-
-// entry point for a generic expression with device
-template <typename Dst, typename Src, typename Func, typename Device>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias(DeviceWrapper<Dst, Device> dst,
-                                                                              const Src& src, const Func& func) {
-  enum {
-    NeedToTranspose = ((int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1) ||
-                       (int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1)) &&
-                      int(Dst::SizeAtCompileTime) != 1
-  };
-
-  using ActualDstTypeCleaned = std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst>;
-  using ActualDstType = std::conditional_t<NeedToTranspose, Transpose<Dst>, Dst&>;
-  ActualDstType actualDst(dst.derived());
-
-  // TODO: check whether this is the right place to perform these checks:
-  EIGEN_STATIC_ASSERT_LVALUE(Dst)
-  EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned, Src)
-  EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename ActualDstTypeCleaned::Scalar, typename Src::Scalar);
-
-  // this provides a mechanism for specializing simple assignments, matrix products, etc
-  AssignmentWithDevice<ActualDstTypeCleaned, Src, Func, Device>::run(actualDst, src, func, dst.device());
-}
-
-// copy and pasted from AssignEvaluator except forward device to kernel
-template <typename DstXprType, typename SrcXprType, typename Functor, typename Device>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src,
-                                                                                const Functor& func, Device& device) {
-  using DstEvaluatorType = evaluator<DstXprType>;
-  using SrcEvaluatorType = evaluator<SrcXprType>;
-
-  SrcEvaluatorType srcEvaluator(src);
-
-  // NOTE To properly handle A = (A*A.transpose())/s with A rectangular,
-  // we need to resize the destination after the source evaluator has been created.
-  resize_if_allowed(dst, src, func);
-
-  DstEvaluatorType dstEvaluator(dst);
-
-  using Kernel = generic_dense_assignment_kernel<DstEvaluatorType, SrcEvaluatorType, Functor>;
-
-  Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived());
-
-  dense_assignment_loop_with_device<Kernel, Device>::run(kernel, device);
-}
-
-}  // namespace internal
-
-template <typename Derived>
-template <typename Device>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper<Derived, Device> EigenBase<Derived>::device(Device& device) {
-  return DeviceWrapper<Derived, Device>(derived(), device);
-}
-
-template <typename Derived>
-template <typename Device>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper<const Derived, Device> EigenBase<Derived>::device(
-    Device& device) const {
-  return DeviceWrapper<const Derived, Device>(derived(), device);
-}
-}  // namespace Eigen
-#endif

Eigen/src/Core/Diagonal.h

@@ -11,211 +11,227 @@
 #ifndef EIGEN_DIAGONAL_H
 #define EIGEN_DIAGONAL_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
+namespace Eigen { 
 
 /** \class Diagonal
- * \ingroup Core_Module
- *
- * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
- *
- * \tparam MatrixType the type of the object in which we are taking a sub/main/super 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.
- *
- * The matrix is not required to be square.
- *
- * This class represents an expression of the main diagonal, or any sub/super diagonal
- * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the
- * time this is the only way it is used.
- *
- * \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index)
- */
+  * \ingroup Core_Module
+  *
+  * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix
+  *
+  * \param MatrixType the type of the object in which we are taking a sub/main/super diagonal
+  * \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal.
+  *              A positive value means a superdiagonal, a negative value means a subdiagonal.
+  *              You can also use Dynamic so the index can be set at runtime.
+  *
+  * The matrix is not required to be square.
+  *
+  * This class represents an expression of the main diagonal, or any sub/super diagonal
+  * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the
+  * time this is the only way it is used.
+  *
+  * \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index)
+  */
 
 namespace internal {
-template <typename MatrixType, int DiagIndex>
-struct traits<Diagonal<MatrixType, DiagIndex> > : traits<MatrixType> {
-  typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
-  typedef std::remove_reference_t<MatrixTypeNested> MatrixTypeNested_;
+template<typename MatrixType, int DiagIndex>
+struct traits<Diagonal<MatrixType,DiagIndex> >
+ : traits<MatrixType>
+{
+  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   typedef typename MatrixType::StorageKind StorageKind;
   enum {
-    RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic)
-                            ? Dynamic
-                            : (plain_enum_min(MatrixType::RowsAtCompileTime - plain_enum_max(-DiagIndex, 0),
-                                              MatrixType::ColsAtCompileTime - plain_enum_max(DiagIndex, 0))),
+    RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
+                      : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                                              MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
     ColsAtCompileTime = 1,
-    MaxRowsAtCompileTime =
-        int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
-        : DiagIndex == DynamicIndex
-            ? min_size_prefer_fixed(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime)
-            : (plain_enum_min(MatrixType::MaxRowsAtCompileTime - plain_enum_max(-DiagIndex, 0),
-                              MatrixType::MaxColsAtCompileTime - plain_enum_max(DiagIndex, 0))),
+    MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
+                         : DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
+                                                                              MatrixType::MaxColsAtCompileTime)
+                         : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                                                 MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
     MaxColsAtCompileTime = 1,
     MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
-    Flags = (unsigned int)MatrixTypeNested_::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) &
-            ~RowMajorBit,  // FIXME DirectAccessBit should not be handled by expressions
+    Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit,
+    CoeffReadCost = _MatrixTypeNested::CoeffReadCost,
     MatrixTypeOuterStride = outer_stride_at_compile_time<MatrixType>::ret,
-    InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride + 1,
+    InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1,
     OuterStrideAtCompileTime = 0
   };
 };
-}  // namespace internal
+}
 
-template <typename MatrixType, int DiagIndex_>
-class Diagonal : public internal::dense_xpr_base<Diagonal<MatrixType, DiagIndex_> >::type {
- public:
-  enum { DiagIndex = DiagIndex_ };
-  typedef typename internal::dense_xpr_base<Diagonal>::type Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
+template<typename MatrixType, int _DiagIndex> class Diagonal
+   : public internal::dense_xpr_base< Diagonal<MatrixType,_DiagIndex> >::type
+{
+  public:
 
-  EIGEN_DEVICE_FUNC constexpr explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex)
-      : m_matrix(matrix), m_index(a_index) {
-    eigen_assert(a_index <= m_matrix.cols() && -a_index <= m_matrix.rows());
-  }
+    enum { DiagIndex = _DiagIndex };
+    typedef typename internal::dense_xpr_base<Diagonal>::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
 
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
+    inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
 
-  EIGEN_DEVICE_FUNC constexpr inline Index rows() const {
-    return m_index.value() < 0 ? numext::mini<Index>(m_matrix.cols(), m_matrix.rows() + m_index.value())
-                               : numext::mini<Index>(m_matrix.rows(), m_matrix.cols() - m_index.value());
-  }
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
 
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return 1; }
+    inline Index rows() const
+    { return m_index.value()<0 ? (std::min<Index>)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min<Index>)(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
 
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_matrix.outerStride() + 1; }
+    inline Index cols() const { return 1; }
 
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return 0; }
+    inline Index innerStride() const
+    {
+      return m_matrix.outerStride() + 1;
+    }
 
-  typedef std::conditional_t<internal::is_lvalue<MatrixType>::value, Scalar, const Scalar> ScalarWithConstIfNotLvalue;
+    inline Index outerStride() const
+    {
+      return 0;
+    }
 
-  EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() {
-    return rows() > 0 ? &(m_matrix.coeffRef(rowOffset(), colOffset())) : nullptr;
-  }
-  EIGEN_DEVICE_FUNC inline const Scalar* data() const {
-    return rows() > 0 ? &(m_matrix.coeffRef(rowOffset(), colOffset())) : nullptr;
-  }
+    typedef typename internal::conditional<
+                       internal::is_lvalue<MatrixType>::value,
+                       Scalar,
+                       const Scalar
+                     >::type ScalarWithConstIfNotLvalue;
 
-  EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index) {
-    EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-    return m_matrix.coeffRef(row + rowOffset(), row + colOffset());
-  }
+    inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
+    inline const Scalar* data() const { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index) const {
-    return m_matrix.coeffRef(row + rowOffset(), row + colOffset());
-  }
+    inline Scalar& coeffRef(Index row, Index)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
+      return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index row, Index) const {
-    return m_matrix.coeff(row + rowOffset(), row + colOffset());
-  }
+    inline const Scalar& coeffRef(Index row, Index) const
+    {
+      return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index idx) {
-    EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-    return m_matrix.coeffRef(idx + rowOffset(), idx + colOffset());
-  }
+    inline CoeffReturnType coeff(Index row, Index) const
+    {
+      return m_matrix.coeff(row+rowOffset(), row+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index idx) const {
-    return m_matrix.coeffRef(idx + rowOffset(), idx + colOffset());
-  }
+    inline Scalar& coeffRef(Index idx)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
+      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index idx) const {
-    return m_matrix.coeff(idx + rowOffset(), idx + colOffset());
-  }
+    inline const Scalar& coeffRef(Index idx) const
+    {
+      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC constexpr inline const internal::remove_all_t<typename MatrixType::Nested>& nestedExpression()
-      const {
-    return m_matrix;
-  }
+    inline CoeffReturnType coeff(Index idx) const
+    {
+      return m_matrix.coeff(idx+rowOffset(), idx+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC constexpr inline Index index() const { return m_index.value(); }
+    const typename internal::remove_all<typename MatrixType::Nested>::type& 
+    nestedExpression() const 
+    {
+      return m_matrix;
+    }
 
- protected:
-  typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
-  const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
+    int index() const
+    {
+      return m_index.value();
+    }
 
- private:
-  // some compilers may fail to optimize std::max etc in case of compile-time constants...
-  EIGEN_DEVICE_FUNC constexpr Index absDiagIndex() const noexcept {
-    return m_index.value() > 0 ? m_index.value() : -m_index.value();
-  }
-  EIGEN_DEVICE_FUNC constexpr Index rowOffset() const noexcept { return m_index.value() > 0 ? 0 : -m_index.value(); }
-  EIGEN_DEVICE_FUNC constexpr Index colOffset() const noexcept { return m_index.value() > 0 ? m_index.value() : 0; }
-  // trigger a compile-time error if someone try to call packet
-  template <int LoadMode>
-  typename MatrixType::PacketReturnType packet(Index) const;
-  template <int LoadMode>
-  typename MatrixType::PacketReturnType packet(Index, Index) const;
+  protected:
+    typename MatrixType::Nested m_matrix;
+    const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
+
+  private:
+    // some compilers may fail to optimize std::max etc in case of compile-time constants...
+    EIGEN_STRONG_INLINE Index absDiagIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); }
+    EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); }
+    EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; }
+    // triger a compile time error is someone try to call packet
+    template<int LoadMode> typename MatrixType::PacketReturnType packet(Index) const;
+    template<int LoadMode> typename MatrixType::PacketReturnType packet(Index,Index) const;
 };
 
 /** \returns an expression of the main diagonal of the matrix \c *this
- *
- * \c *this is not required to be square.
- *
- * Example: \include MatrixBase_diagonal.cpp
- * Output: \verbinclude MatrixBase_diagonal.out
- *
- * \sa class Diagonal */
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr typename MatrixBase<Derived>::DiagonalReturnType MatrixBase<Derived>::diagonal() {
-  return DiagonalReturnType(derived());
+  *
+  * \c *this is not required to be square.
+  *
+  * Example: \include MatrixBase_diagonal.cpp
+  * Output: \verbinclude MatrixBase_diagonal.out
+  *
+  * \sa class Diagonal */
+template<typename Derived>
+inline typename MatrixBase<Derived>::DiagonalReturnType
+MatrixBase<Derived>::diagonal()
+{
+  return derived();
 }
 
 /** This is the const version of diagonal(). */
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr const typename MatrixBase<Derived>::ConstDiagonalReturnType MatrixBase<Derived>::diagonal()
-    const {
+template<typename Derived>
+inline typename MatrixBase<Derived>::ConstDiagonalReturnType
+MatrixBase<Derived>::diagonal() const
+{
   return ConstDiagonalReturnType(derived());
 }
 
 /** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
- *
- * \c *this is not required to be square.
- *
- * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
- * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
- *
- * Example: \include MatrixBase_diagonal_int.cpp
- * Output: \verbinclude MatrixBase_diagonal_int.out
- *
- * \sa MatrixBase::diagonal(), class Diagonal */
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr Diagonal<Derived, DynamicIndex> MatrixBase<Derived>::diagonal(Index index) {
-  return Diagonal<Derived, DynamicIndex>(derived(), index);
+  *
+  * \c *this is not required to be square.
+  *
+  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
+  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
+  *
+  * Example: \include MatrixBase_diagonal_int.cpp
+  * Output: \verbinclude MatrixBase_diagonal_int.out
+  *
+  * \sa MatrixBase::diagonal(), class Diagonal */
+template<typename Derived>
+inline typename MatrixBase<Derived>::DiagonalDynamicIndexReturnType
+MatrixBase<Derived>::diagonal(Index index)
+{
+  return DiagonalDynamicIndexReturnType(derived(), index);
 }
 
 /** This is the const version of diagonal(Index). */
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr const Diagonal<const Derived, DynamicIndex> MatrixBase<Derived>::diagonal(
-    Index index) const {
-  return Diagonal<const Derived, DynamicIndex>(derived(), index);
+template<typename Derived>
+inline typename MatrixBase<Derived>::ConstDiagonalDynamicIndexReturnType
+MatrixBase<Derived>::diagonal(Index index) const
+{
+  return ConstDiagonalDynamicIndexReturnType(derived(), index);
 }
 
 /** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this
- *
- * \c *this is not required to be square.
- *
- * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
- * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
- *
- * Example: \include MatrixBase_diagonal_template_int.cpp
- * Output: \verbinclude MatrixBase_diagonal_template_int.out
- *
- * \sa MatrixBase::diagonal(), class Diagonal */
-template <typename Derived>
-template <int Index_>
-EIGEN_DEVICE_FUNC constexpr Diagonal<Derived, Index_> MatrixBase<Derived>::diagonal() {
-  return Diagonal<Derived, Index_>(derived());
+  *
+  * \c *this is not required to be square.
+  *
+  * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0
+  * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal.
+  *
+  * Example: \include MatrixBase_diagonal_template_int.cpp
+  * Output: \verbinclude MatrixBase_diagonal_template_int.out
+  *
+  * \sa MatrixBase::diagonal(), class Diagonal */
+template<typename Derived>
+template<int Index>
+inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Index>::Type
+MatrixBase<Derived>::diagonal()
+{
+  return derived();
 }
 
 /** This is the const version of diagonal<int>(). */
-template <typename Derived>
-template <int Index_>
-EIGEN_DEVICE_FUNC constexpr const Diagonal<const Derived, Index_> MatrixBase<Derived>::diagonal() const {
-  return Diagonal<const Derived, Index_>(derived());
+template<typename Derived>
+template<int Index>
+inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Index>::Type
+MatrixBase<Derived>::diagonal() const
+{
+  return derived();
 }
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_DIAGONAL_H
+#endif // EIGEN_DIAGONAL_H

Eigen/src/Core/DiagonalMatrix.h

@@ -11,463 +11,303 @@
 #ifndef EIGEN_DIAGONALMATRIX_H
 #define EIGEN_DIAGONALMATRIX_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+namespace Eigen { 
 
-namespace Eigen {
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+template<typename Derived>
+class DiagonalBase : public EigenBase<Derived>
+{
+  public:
+    typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
+    typedef typename DiagonalVectorType::Scalar Scalar;
+    typedef typename DiagonalVectorType::RealScalar RealScalar;
+    typedef typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
 
-/** \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> {
- public:
-  typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
-  typedef typename DiagonalVectorType::Scalar Scalar;
-  typedef typename DiagonalVectorType::RealScalar RealScalar;
-  typedef typename internal::traits<Derived>::StorageKind StorageKind;
-  typedef typename internal::traits<Derived>::StorageIndex StorageIndex;
+    enum {
+      RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+      ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+      MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
+      MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
+      IsVectorAtCompileTime = 0,
+      Flags = 0
+    };
 
-  enum {
-    RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-    MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-    IsVectorAtCompileTime = 0,
-    Flags = NoPreferredStorageOrderBit
-  };
+    typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime> DenseMatrixType;
+    typedef DenseMatrixType DenseType;
+    typedef DiagonalMatrix<Scalar,DiagonalVectorType::SizeAtCompileTime,DiagonalVectorType::MaxSizeAtCompileTime> PlainObject;
 
-  typedef Matrix<Scalar, RowsAtCompileTime, ColsAtCompileTime, 0, MaxRowsAtCompileTime, MaxColsAtCompileTime>
-      DenseMatrixType;
-  typedef DenseMatrixType DenseType;
-  typedef DiagonalMatrix<Scalar, DiagonalVectorType::SizeAtCompileTime, DiagonalVectorType::MaxSizeAtCompileTime>
-      PlainObject;
+    inline const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    inline Derived& derived() { return *static_cast<Derived*>(this); }
 
-  /** \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); }
+    DenseMatrixType toDenseMatrix() const { return derived(); }
+    template<typename DenseDerived>
+    void evalTo(MatrixBase<DenseDerived> &other) const;
+    template<typename DenseDerived>
+    inline void addTo(MatrixBase<DenseDerived> &other) const
+    { other.diagonal() += diagonal(); }
+    template<typename DenseDerived>
+    inline void subTo(MatrixBase<DenseDerived> &other) const
+    { other.diagonal() -= diagonal(); }
 
-  /**
-   * 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 derived object. */
-  EIGEN_DEVICE_FUNC DenseMatrixType toDenseMatrix() const { return derived(); }
+    inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); }
+    inline DiagonalVectorType& diagonal() { return derived().diagonal(); }
 
-  /** \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(); }
+    inline Index rows() const { return diagonal().size(); }
+    inline Index cols() const { return diagonal().size(); }
 
-  /** \returns the value of the coefficient as if \c *this was a dense matrix. */
-  EIGEN_DEVICE_FUNC inline Scalar coeff(Index row, Index col) const {
-    eigen_assert(row >= 0 && col >= 0 && row < rows() && col <= cols());
-    return row == col ? diagonal().coeff(row) : Scalar(0);
-  }
+    /** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
+      */
+    template<typename MatrixDerived>
+    const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
+    operator*(const MatrixBase<MatrixDerived> &matrix) const
+    {
+      return DiagonalProduct<MatrixDerived, Derived, OnTheLeft>(matrix.derived(), derived());
+    }
 
-  /** \returns the number of rows. */
-  EIGEN_DEVICE_FUNC constexpr Index rows() const { return diagonal().size(); }
-  /** \returns the number of columns. */
-  EIGEN_DEVICE_FUNC constexpr 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> operator*(
-      const MatrixBase<MatrixDerived>& matrix) const {
-    return Product<Derived, MatrixDerived, LazyProduct>(derived(), matrix.derived());
-  }
-
-  template <typename OtherDerived>
-  using DiagonalProductReturnType = DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
-      DiagonalVectorType, typename OtherDerived::DiagonalVectorType, product)>;
-
-  /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a other */
-  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 DiagonalInverseReturnType inverse() const {
-    return diagonal().cwiseInverse().asDiagonal();
-  }
-
-  using DiagonalScaleReturnType =
-      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 ScaleDiagonalReturnType operator*(const Scalar& scalar,
-                                                                          const DiagonalBase& other) {
-    return (scalar * other.diagonal()).asDiagonal();
-  }
-
-  template <typename OtherDerived>
-  using DiagonalSumReturnType = DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
-      DiagonalVectorType, typename OtherDerived::DiagonalVectorType, sum)>;
-
-  /** \returns the sum of \c *this and the diagonal matrix \a other */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC inline const DiagonalSumReturnType<OtherDerived> operator+(
-      const DiagonalBase<OtherDerived>& other) const {
-    return (diagonal() + other.diagonal()).asDiagonal();
-  }
-
-  template <typename OtherDerived>
-  using DiagonalDifferenceReturnType = DiagonalWrapper<const EIGEN_CWISE_BINARY_RETURN_TYPE(
-      DiagonalVectorType, typename OtherDerived::DiagonalVectorType, difference)>;
-
-  /** \returns the difference of \c *this and the diagonal matrix \a other */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC inline const DiagonalDifferenceReturnType<OtherDerived> operator-(
-      const DiagonalBase<OtherDerived>& other) const {
-    return (diagonal() - other.diagonal()).asDiagonal();
-  }
+    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
+    inverse() const
+    {
+      return diagonal().cwiseInverse();
+    }
+    
+    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+    operator*(const Scalar& scalar) const
+    {
+      return diagonal() * scalar;
+    }
+    friend inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+    operator*(const Scalar& scalar, const DiagonalBase& other)
+    {
+      return other.diagonal() * scalar;
+    }
+    
+    #ifdef EIGEN2_SUPPORT
+    template<typename OtherDerived>
+    bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
+    {
+      return diagonal().isApprox(other.diagonal(), precision);
+    }
+    template<typename OtherDerived>
+    bool isApprox(const MatrixBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
+    {
+      return toDenseMatrix().isApprox(other, precision);
+    }
+    #endif
 };
 
+template<typename Derived>
+template<typename DenseDerived>
+inline void DiagonalBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
+{
+  other.setZero();
+  other.diagonal() = diagonal();
+}
+#endif
+
 /** \class DiagonalMatrix
- * \ingroup Core_Module
- *
- * \brief Represents a diagonal matrix with its storage
- *
- * \tparam Scalar_ the type of coefficients
- * \tparam SizeAtCompileTime the dimension of the matrix, or Dynamic
- * \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 DiagonalBase, class DiagonalWrapper
- */
+  * \ingroup Core_Module
+  *
+  * \brief Represents a diagonal matrix with its storage
+  *
+  * \param _Scalar the type of coefficients
+  * \param SizeAtCompileTime the dimension of the matrix, or Dynamic
+  * \param MaxSizeAtCompileTime the dimension of the matrix, or Dynamic. This parameter is optional and defaults
+  *        to SizeAtCompileTime. Most of the time, you do not need to specify it.
+  *
+  * \sa class DiagonalWrapper
+  */
 
 namespace internal {
-template <typename Scalar_, int SizeAtCompileTime, int MaxSizeAtCompileTime>
-struct traits<DiagonalMatrix<Scalar_, SizeAtCompileTime, MaxSizeAtCompileTime>>
-    : traits<Matrix<Scalar_, SizeAtCompileTime, SizeAtCompileTime, 0, MaxSizeAtCompileTime, MaxSizeAtCompileTime>> {
-  typedef Matrix<Scalar_, SizeAtCompileTime, 1, 0, MaxSizeAtCompileTime, 1> DiagonalVectorType;
-  typedef DiagonalShape StorageKind;
-  enum { Flags = LvalueBit | NoPreferredStorageOrderBit | NestByRefBit };
+template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
+struct traits<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
+ : traits<Matrix<_Scalar,SizeAtCompileTime,SizeAtCompileTime,0,MaxSizeAtCompileTime,MaxSizeAtCompileTime> >
+{
+  typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType;
+  typedef Dense StorageKind;
+  typedef DenseIndex Index;
+  enum {
+    Flags = LvalueBit
+  };
 };
-}  // namespace internal
-template <typename Scalar_, int SizeAtCompileTime, int MaxSizeAtCompileTime>
-class DiagonalMatrix : public DiagonalBase<DiagonalMatrix<Scalar_, SizeAtCompileTime, MaxSizeAtCompileTime>> {
- public:
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  typedef typename internal::traits<DiagonalMatrix>::DiagonalVectorType DiagonalVectorType;
-  typedef const DiagonalMatrix& Nested;
-  typedef Scalar_ Scalar;
-  typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
-  typedef typename internal::traits<DiagonalMatrix>::StorageIndex StorageIndex;
-#endif
+}
+template<typename _Scalar, int SizeAtCompileTime, int MaxSizeAtCompileTime>
+class DiagonalMatrix
+  : public DiagonalBase<DiagonalMatrix<_Scalar,SizeAtCompileTime,MaxSizeAtCompileTime> >
+{
+  public:
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    typedef typename internal::traits<DiagonalMatrix>::DiagonalVectorType DiagonalVectorType;
+    typedef const DiagonalMatrix& Nested;
+    typedef _Scalar Scalar;
+    typedef typename internal::traits<DiagonalMatrix>::StorageKind StorageKind;
+    typedef typename internal::traits<DiagonalMatrix>::Index Index;
+    #endif
 
- protected:
-  DiagonalVectorType m_diagonal;
+  protected:
 
- public:
-  /** const version of diagonal(). */
-  EIGEN_DEVICE_FUNC constexpr inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
-  /** \returns a reference to the stored vector of diagonal coefficients. */
-  EIGEN_DEVICE_FUNC constexpr inline DiagonalVectorType& diagonal() { return m_diagonal; }
+    DiagonalVectorType m_diagonal;
 
-  /** Default constructor without initialization */
-  EIGEN_DEVICE_FUNC constexpr inline DiagonalMatrix() {}
+  public:
 
-  /** Constructs a diagonal matrix with given dimension  */
-  EIGEN_DEVICE_FUNC constexpr explicit inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
+    /** const version of diagonal(). */
+    inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
+    /** \returns a reference to the stored vector of diagonal coefficients. */
+    inline DiagonalVectorType& diagonal() { return m_diagonal; }
 
-  /** 2D constructor. */
-  EIGEN_DEVICE_FUNC constexpr inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x, y) {}
+    /** Default constructor without initialization */
+    inline DiagonalMatrix() {}
 
-  /** 3D constructor. */
-  EIGEN_DEVICE_FUNC constexpr inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z)
-      : m_diagonal(x, y, z) {}
+    /** Constructs a diagonal matrix with given dimension  */
+    inline DiagonalMatrix(Index dim) : m_diagonal(dim) {}
 
-  /** \brief Construct a diagonal matrix with fixed size from an arbitrary number of 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.
-   *
-   * \sa DiagonalMatrix(const Scalar&, const Scalar&)
-   * \sa DiagonalMatrix(const Scalar&, const Scalar&, const Scalar&)
-   */
-  template <typename... ArgTypes>
-  EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE DiagonalMatrix(const Scalar& a0, const Scalar& a1, const Scalar& a2,
-                                                                 const ArgTypes&... args)
-      : m_diagonal(a0, a1, a2, args...) {}
+    /** 2D constructor. */
+    inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {}
 
-  /** \brief Constructs a DiagonalMatrix and initializes it by elements given by an initializer list of initializer
-   * lists \cpp11
-   */
-  EIGEN_DEVICE_FUNC explicit EIGEN_STRONG_INLINE DiagonalMatrix(
-      const std::initializer_list<std::initializer_list<Scalar>>& list)
-      : m_diagonal(list) {}
+    /** 3D constructor. */
+    inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {}
 
-  /** \brief Constructs a DiagonalMatrix from an r-value diagonal vector type */
-  EIGEN_DEVICE_FUNC constexpr explicit inline DiagonalMatrix(DiagonalVectorType&& diag) : m_diagonal(std::move(diag)) {}
+    /** Copy constructor. */
+    template<typename OtherDerived>
+    inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other) : m_diagonal(other.diagonal()) {}
 
-  /** Copy constructor. */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC constexpr inline DiagonalMatrix(const DiagonalBase<OtherDerived>& other)
-      : m_diagonal(other.diagonal()) {}
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */
+    inline DiagonalMatrix(const DiagonalMatrix& other) : m_diagonal(other.diagonal()) {}
+    #endif
 
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */
-  inline DiagonalMatrix(const DiagonalMatrix& other) : m_diagonal(other.diagonal()) {}
-#endif
+    /** generic constructor from expression of the diagonal coefficients */
+    template<typename OtherDerived>
+    explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other) : m_diagonal(other)
+    {}
 
-  /** generic constructor from expression of the diagonal coefficients */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC constexpr explicit inline DiagonalMatrix(const MatrixBase<OtherDerived>& other)
-      : m_diagonal(other) {}
+    /** Copy operator. */
+    template<typename OtherDerived>
+    DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other)
+    {
+      m_diagonal = other.diagonal();
+      return *this;
+    }
 
-  /** Copy operator. */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC DiagonalMatrix& operator=(const DiagonalBase<OtherDerived>& other) {
-    m_diagonal = other.diagonal();
-    return *this;
-  }
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** This is a special case of the templated operator=. Its purpose is to
+      * prevent a default operator= from hiding the templated operator=.
+      */
+    DiagonalMatrix& operator=(const DiagonalMatrix& other)
+    {
+      m_diagonal = other.diagonal();
+      return *this;
+    }
+    #endif
 
-#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 DiagonalMatrix& operator=(const DiagonalMatrix& other) {
-    m_diagonal = other.diagonal();
-    return *this;
-  }
-#endif
-
-  typedef DiagonalWrapper<const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, DiagonalVectorType>>
-      InitializeReturnType;
-
-  typedef DiagonalWrapper<const CwiseNullaryOp<internal::scalar_zero_op<Scalar>, DiagonalVectorType>>
-      ZeroInitializeReturnType;
-
-  /** Initializes a diagonal matrix of size SizeAtCompileTime with coefficients set to zero */
-  EIGEN_DEVICE_FUNC static const ZeroInitializeReturnType Zero() { return DiagonalVectorType::Zero().asDiagonal(); }
-  /** Initializes a diagonal matrix of size dim with coefficients set to zero */
-  EIGEN_DEVICE_FUNC static const ZeroInitializeReturnType 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); }
-  /** Sets all coefficients to zero. */
-  EIGEN_DEVICE_FUNC inline void setZero() { m_diagonal.setZero(); }
-  /** Resizes and sets all coefficients to zero. */
-  EIGEN_DEVICE_FUNC inline void setZero(Index size) { m_diagonal.setZero(size); }
-  /** Sets this matrix to be the identity matrix of the current size. */
-  EIGEN_DEVICE_FUNC inline void setIdentity() { m_diagonal.setOnes(); }
-  /** Sets this matrix to be the identity matrix of the given size. */
-  EIGEN_DEVICE_FUNC inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
+    /** Resizes to given size. */
+    inline void resize(Index size) { m_diagonal.resize(size); }
+    /** Sets all coefficients to zero. */
+    inline void setZero() { m_diagonal.setZero(); }
+    /** Resizes and sets all coefficients to zero. */
+    inline void setZero(Index size) { m_diagonal.setZero(size); }
+    /** Sets this matrix to be the identity matrix of the current size. */
+    inline void setIdentity() { m_diagonal.setOnes(); }
+    /** Sets this matrix to be the identity matrix of the given size. */
+    inline void setIdentity(Index size) { m_diagonal.setOnes(size); }
 };
 
 /** \class DiagonalWrapper
- * \ingroup Core_Module
- *
- * \brief Expression of a diagonal matrix
- *
- * \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()
- * and most of the time this is the only way that it is used.
- *
- * \sa class DiagonalMatrix, class DiagonalBase, MatrixBase::asDiagonal()
- */
+  * \ingroup Core_Module
+  *
+  * \brief Expression of a diagonal matrix
+  *
+  * \param _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()
+  * and most of the time this is the only way that it is used.
+  *
+  * \sa class DiagonalMatrix, class DiagonalBase, MatrixBase::asDiagonal()
+  */
 
 namespace internal {
-template <typename DiagonalVectorType_>
-struct traits<DiagonalWrapper<DiagonalVectorType_>> {
-  typedef DiagonalVectorType_ DiagonalVectorType;
+template<typename _DiagonalVectorType>
+struct traits<DiagonalWrapper<_DiagonalVectorType> >
+{
+  typedef _DiagonalVectorType DiagonalVectorType;
   typedef typename DiagonalVectorType::Scalar Scalar;
-  typedef typename DiagonalVectorType::StorageIndex StorageIndex;
-  typedef DiagonalShape StorageKind;
-  typedef typename traits<DiagonalVectorType>::XprKind XprKind;
+  typedef typename DiagonalVectorType::Index Index;
+  typedef typename DiagonalVectorType::StorageKind StorageKind;
   enum {
     RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
     ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
-    MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-    MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime,
-    Flags = (traits<DiagonalVectorType>::Flags & LvalueBit) | NoPreferredStorageOrderBit
+    MaxRowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+    MaxColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime,
+    Flags =  traits<DiagonalVectorType>::Flags & LvalueBit
   };
 };
-}  // namespace internal
+}
 
-template <typename DiagonalVectorType_>
-class DiagonalWrapper : public DiagonalBase<DiagonalWrapper<DiagonalVectorType_>>, internal::no_assignment_operator {
- public:
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-  typedef DiagonalVectorType_ DiagonalVectorType;
-  typedef DiagonalWrapper Nested;
-#endif
+template<typename _DiagonalVectorType>
+class DiagonalWrapper
+  : public DiagonalBase<DiagonalWrapper<_DiagonalVectorType> >, internal::no_assignment_operator
+{
+  public:
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    typedef _DiagonalVectorType DiagonalVectorType;
+    typedef DiagonalWrapper Nested;
+    #endif
 
-  /** Constructor from expression of diagonal coefficients to wrap. */
-  EIGEN_DEVICE_FUNC constexpr explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal)
-      : m_diagonal(a_diagonal) {}
+    /** Constructor from expression of diagonal coefficients to wrap. */
+    inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
 
-  /** \returns a const reference to the wrapped expression of diagonal coefficients. */
-  EIGEN_DEVICE_FUNC constexpr const DiagonalVectorType& diagonal() const { return m_diagonal; }
+    /** \returns a const reference to the wrapped expression of diagonal coefficients. */
+    const DiagonalVectorType& diagonal() const { return m_diagonal; }
 
- protected:
-  typename DiagonalVectorType::Nested m_diagonal;
+  protected:
+    typename DiagonalVectorType::Nested m_diagonal;
 };
 
 /** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients
- *
- * \only_for_vectors
- *
- * Example: \include MatrixBase_asDiagonal.cpp
- * Output: \verbinclude MatrixBase_asDiagonal.out
- *
- * \sa class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal()
- **/
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr const DiagonalWrapper<const Derived> MatrixBase<Derived>::asDiagonal() const {
-  return DiagonalWrapper<const Derived>(derived());
+  *
+  * \only_for_vectors
+  *
+  * Example: \include MatrixBase_asDiagonal.cpp
+  * Output: \verbinclude MatrixBase_asDiagonal.out
+  *
+  * \sa class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal()
+  **/
+template<typename Derived>
+inline const DiagonalWrapper<const Derived>
+MatrixBase<Derived>::asDiagonal() const
+{
+  return derived();
 }
 
 /** \returns true if *this is approximately equal to a diagonal matrix,
- *          within the precision given by \a prec.
- *
- * Example: \include MatrixBase_isDiagonal.cpp
- * Output: \verbinclude MatrixBase_isDiagonal.out
- *
- * \sa asDiagonal()
- */
-template <typename Derived>
-bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const {
-  if (cols() != rows()) return false;
+  *          within the precision given by \a prec.
+  *
+  * Example: \include MatrixBase_isDiagonal.cpp
+  * Output: \verbinclude MatrixBase_isDiagonal.out
+  *
+  * \sa asDiagonal()
+  */
+template<typename Derived>
+bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
+{
+  using std::abs;
+  if(cols() != rows()) return false;
   RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);
-  for (Index j = 0; j < cols(); ++j) {
-    RealScalar absOnDiagonal = numext::abs(coeff(j, j));
-    if (absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
+  for(Index j = 0; j < cols(); ++j)
+  {
+    RealScalar absOnDiagonal = abs(coeff(j,j));
+    if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal;
   }
-  for (Index j = 0; j < cols(); ++j)
-    for (Index i = 0; i < j; ++i) {
-      if (!internal::isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false;
-      if (!internal::isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false;
+  for(Index j = 0; j < cols(); ++j)
+    for(Index i = 0; i < j; ++i)
+    {
+      if(!internal::isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false;
+      if(!internal::isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false;
     }
   return true;
 }
 
-/** \returns DiagonalWrapper.
- *
- * Example: \include MatrixBase_diagonalView.cpp
- * Output: \verbinclude MatrixBase_diagonalView.out
- *
- * \sa diagonalView()
- */
+} // end namespace Eigen
 
-/** This is the non-const version of diagonalView() with DiagIndex_ . */
-template <typename Derived>
-template <int DiagIndex_>
-EIGEN_DEVICE_FUNC constexpr DiagonalWrapper<Diagonal<Derived, DiagIndex_>> MatrixBase<Derived>::diagonalView() {
-  typedef Diagonal<Derived, DiagIndex_> DiagType;
-  typedef DiagonalWrapper<DiagType> ReturnType;
-  DiagType diag(this->derived());
-  return ReturnType(diag);
-}
-
-/** This is the const version of diagonalView() with DiagIndex_ . */
-template <typename Derived>
-template <int DiagIndex_>
-EIGEN_DEVICE_FUNC constexpr DiagonalWrapper<Diagonal<const Derived, DiagIndex_>> MatrixBase<Derived>::diagonalView()
-    const {
-  typedef Diagonal<const Derived, DiagIndex_> DiagType;
-  typedef DiagonalWrapper<DiagType> ReturnType;
-  DiagType diag(this->derived());
-  return ReturnType(diag);
-}
-
-/** This is the non-const version of diagonalView() with dynamic index. */
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr DiagonalWrapper<Diagonal<Derived, DynamicIndex>> MatrixBase<Derived>::diagonalView(
-    Index index) {
-  typedef Diagonal<Derived, DynamicIndex> DiagType;
-  typedef DiagonalWrapper<DiagType> ReturnType;
-  DiagType diag(this->derived(), index);
-  return ReturnType(diag);
-}
-
-/** This is the const version of diagonalView() with dynamic index. */
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr DiagonalWrapper<Diagonal<const Derived, DynamicIndex>> MatrixBase<Derived>::diagonalView(
-    Index index) const {
-  typedef Diagonal<const Derived, DynamicIndex> DiagType;
-  typedef DiagonalWrapper<DiagType> ReturnType;
-  DiagType diag(this->derived(), index);
-  return ReturnType(diag);
-}
-
-namespace internal {
-
-template <>
-struct storage_kind_to_shape<DiagonalShape> {
-  typedef DiagonalShape Shape;
-};
-
-struct Diagonal2Dense {};
-
-template <>
-struct AssignmentKind<DenseShape, DiagonalShape> {
-  typedef Diagonal2Dense Kind;
-};
-
-// Diagonal matrix to Dense assignment
-template <typename DstXprType, typename SrcXprType, typename Functor>
-struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Dense> {
-  static EIGEN_DEVICE_FUNC void run(
-      DstXprType& dst, const SrcXprType& src,
-      const internal::assign_op<typename DstXprType::Scalar, typename SrcXprType::Scalar>& /*func*/) {
-    Index dstRows = src.rows();
-    Index dstCols = src.cols();
-    if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols);
-
-    dst.setZero();
-    dst.diagonal() = src.diagonal();
-  }
-
-  static EIGEN_DEVICE_FUNC void run(
-      DstXprType& dst, const SrcXprType& src,
-      const internal::add_assign_op<typename DstXprType::Scalar, typename SrcXprType::Scalar>& /*func*/) {
-    dst.diagonal() += src.diagonal();
-  }
-
-  static EIGEN_DEVICE_FUNC void run(
-      DstXprType& dst, const SrcXprType& src,
-      const internal::sub_assign_op<typename DstXprType::Scalar, typename SrcXprType::Scalar>& /*func*/) {
-    dst.diagonal() -= src.diagonal();
-  }
-};
-
-}  // namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_DIAGONALMATRIX_H
+#endif // EIGEN_DIAGONALMATRIX_H

Eigen/src/Core/DiagonalProduct.h

@@ -11,20 +11,121 @@
 #ifndef EIGEN_DIAGONALPRODUCT_H
 #define EIGEN_DIAGONALPRODUCT_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
+namespace Eigen { 
 
-namespace Eigen {
+namespace internal {
+template<typename MatrixType, typename DiagonalType, int ProductOrder>
+struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
+ : traits<MatrixType>
+{
+  typedef typename scalar_product_traits<typename MatrixType::Scalar, typename DiagonalType::Scalar>::ReturnType Scalar;
+  enum {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
 
-/** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
- */
-template <typename Derived>
-template <typename DiagonalDerived>
-EIGEN_DEVICE_FUNC inline const Product<Derived, DiagonalDerived, LazyProduct> MatrixBase<Derived>::operator*(
-    const DiagonalBase<DiagonalDerived> &a_diagonal) const {
-  return Product<Derived, DiagonalDerived, LazyProduct>(derived(), a_diagonal.derived());
+    _StorageOrder = MatrixType::Flags & RowMajorBit ? RowMajor : ColMajor,
+    _ScalarAccessOnDiag =  !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft)
+                          ||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)),
+    _SameTypes = is_same<typename MatrixType::Scalar, typename DiagonalType::Scalar>::value,
+    // FIXME currently we need same types, but in the future the next rule should be the one
+    //_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
+    _Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))),
+    _LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0,
+
+    Flags = ((HereditaryBits|_LinearAccessMask|AlignedBit) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit),
+    Cost0 = EIGEN_ADD_COST(NumTraits<Scalar>::MulCost, MatrixType::CoeffReadCost),
+    CoeffReadCost = EIGEN_ADD_COST(Cost0,DiagonalType::DiagonalVectorType::CoeffReadCost)
+  };
+};
 }
 
-}  // end namespace Eigen
+template<typename MatrixType, typename DiagonalType, int ProductOrder>
+class DiagonalProduct : internal::no_assignment_operator,
+                        public MatrixBase<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
+{
+  public:
 
-#endif  // EIGEN_DIAGONALPRODUCT_H
+    typedef MatrixBase<DiagonalProduct> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(DiagonalProduct)
+
+    inline DiagonalProduct(const MatrixType& matrix, const DiagonalType& diagonal)
+      : m_matrix(matrix), m_diagonal(diagonal)
+    {
+      eigen_assert(diagonal.diagonal().size() == (ProductOrder == OnTheLeft ? matrix.rows() : matrix.cols()));
+    }
+
+    EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); }
+
+    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+    {
+      return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
+    }
+    
+    EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const
+    {
+      enum {
+        StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
+      };
+      return coeff(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    {
+      enum {
+        StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor
+      };
+      const Index indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col;
+      return packet_impl<LoadMode>(row,col,indexInDiagonalVector,typename internal::conditional<
+        ((int(StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
+       ||(int(StorageOrder) == ColMajor && int(ProductOrder) == OnTheRight)), internal::true_type, internal::false_type>::type());
+    }
+    
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const
+    {
+      enum {
+        StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor
+      };
+      return packet<LoadMode>(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx);
+    }
+
+  protected:
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::true_type) const
+    {
+      return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
+                     internal::pset1<PacketScalar>(m_diagonal.diagonal().coeff(id)));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::false_type) const
+    {
+      enum {
+        InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime,
+        DiagonalVectorPacketLoadMode = (LoadMode == Aligned && (((InnerSize%16) == 0) || (int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit)==AlignedBit) ? Aligned : Unaligned)
+      };
+      return internal::pmul(m_matrix.template packet<LoadMode>(row, col),
+                     m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
+    }
+
+    typename MatrixType::Nested m_matrix;
+    typename DiagonalType::Nested m_diagonal;
+};
+
+/** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
+  */
+template<typename Derived>
+template<typename DiagonalDerived>
+inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
+MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
+{
+  return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), a_diagonal.derived());
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_DIAGONALPRODUCT_H

Eigen/src/Core/Dot.h

@@ -10,258 +10,254 @@
 #ifndef EIGEN_DOT_H
 #define EIGEN_DOT_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
+namespace Eigen { 
 
 namespace internal {
 
-template <typename Derived, typename Scalar = typename traits<Derived>::Scalar>
-struct squared_norm_impl {
-  using Real = typename NumTraits<Scalar>::Real;
-  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE Real run(const Derived& a) {
-    return a.realView().cwiseAbs2().sum();
+// helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot
+// with mismatched types, the compiler emits errors about failing to instantiate cwiseProduct BEFORE
+// looking at the static assertions. Thus this is a trick to get better compile errors.
+template<typename T, typename U,
+// the NeedToTranspose condition here is taken straight from Assign.h
+         bool NeedToTranspose = T::IsVectorAtCompileTime
+                && U::IsVectorAtCompileTime
+                && ((int(T::RowsAtCompileTime) == 1 && int(U::ColsAtCompileTime) == 1)
+                      |  // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&".
+                         // revert to || as soon as not needed anymore.
+                    (int(T::ColsAtCompileTime) == 1 && int(U::RowsAtCompileTime) == 1))
+>
+struct dot_nocheck
+{
+  typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
+  static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
+  {
+    return a.template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
   }
 };
 
-template <typename Derived>
-struct squared_norm_impl<Derived, bool> {
-  static EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE bool run(const Derived& a) { return a.any(); }
+template<typename T, typename U>
+struct dot_nocheck<T, U, true>
+{
+  typedef typename scalar_product_traits<typename traits<T>::Scalar,typename traits<U>::Scalar>::ReturnType ResScalar;
+  static inline ResScalar run(const MatrixBase<T>& a, const MatrixBase<U>& b)
+  {
+    return a.transpose().template binaryExpr<scalar_conj_product_op<typename traits<T>::Scalar,typename traits<U>::Scalar> >(b).sum();
+  }
 };
 
-}  // end namespace internal
+} // end namespace internal
 
-/** \fn MatrixBase::dot
- * \returns the dot product of *this with other.
- *
- * \only_for_vectors
- *
- * \note If the scalar type is complex numbers, then this function returns the hermitian
- * (sesquilinear) dot product, conjugate-linear in the first variable and linear in the
- * second variable.
- *
- * \sa squaredNorm(), norm()
- */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE
-    typename ScalarBinaryOpTraits<typename internal::traits<Derived>::Scalar,
-                                  typename internal::traits<OtherDerived>::Scalar>::ReturnType
-    MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const {
-  return internal::dot_impl<Derived, OtherDerived>::run(derived(), other.derived());
+/** \returns the dot product of *this with other.
+  *
+  * \only_for_vectors
+  *
+  * \note If the scalar type is complex numbers, then this function returns the hermitian
+  * (sesquilinear) dot product, conjugate-linear in the first variable and linear in the
+  * second variable.
+  *
+  * \sa squaredNorm(), norm()
+  */
+template<typename Derived>
+template<typename OtherDerived>
+inline typename internal::scalar_product_traits<typename internal::traits<Derived>::Scalar,typename internal::traits<OtherDerived>::Scalar>::ReturnType
+MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
+  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
+  typedef internal::scalar_conj_product_op<Scalar,typename OtherDerived::Scalar> func;
+  EIGEN_CHECK_BINARY_COMPATIBILIY(func,Scalar,typename OtherDerived::Scalar);
+
+  eigen_assert(size() == other.size());
+
+  return internal::dot_nocheck<Derived,OtherDerived>::run(*this, other);
 }
 
+#ifdef EIGEN2_SUPPORT
+/** \returns the dot product of *this with other, with the Eigen2 convention that the dot product is linear in the first variable
+  * (conjugating the second variable). Of course this only makes a difference in the complex case.
+  *
+  * This method is only available in EIGEN2_SUPPORT mode.
+  *
+  * \only_for_vectors
+  *
+  * \sa dot()
+  */
+template<typename Derived>
+template<typename OtherDerived>
+typename internal::traits<Derived>::Scalar
+MatrixBase<Derived>::eigen2_dot(const MatrixBase<OtherDerived>& other) const
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
+  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
+  EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
+    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+
+  eigen_assert(size() == other.size());
+
+  return internal::dot_nocheck<OtherDerived,Derived>::run(other,*this);
+}
+#endif
+
+
 //---------- implementation of L2 norm and related functions ----------
 
-/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the squared Frobenius norm.
- * In both cases, it consists in the sum of the square of all the matrix entries.
- * For vectors, this is also equal to the dot product of \c *this with itself.
- *
- * \sa dot(), norm(), lpNorm()
- */
-template <typename Derived>
-EIGEN_DEVICE_FUNC constexpr EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
-MatrixBase<Derived>::squaredNorm() const {
-  return internal::squared_norm_impl<Derived>::run(derived());
+/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm.
+  * In both cases, it consists in the sum of the square of all the matrix entries.
+  * For vectors, this is also equals to the dot product of \c *this with itself.
+  *
+  * \sa dot(), norm()
+  */
+template<typename Derived>
+EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
+{
+  return numext::real((*this).cwiseAbs2().sum());
 }
 
 /** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm.
- * In both cases, it consists in the square root of the sum of the square of all the matrix entries.
- * For vectors, this is also equal to the square root of the dot product of \c *this with itself.
- *
- * \sa lpNorm(), dot(), squaredNorm()
- */
-template <typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
-MatrixBase<Derived>::norm() const {
-  return numext::sqrt(squaredNorm());
+  * In both cases, it consists in the square root of the sum of the square of all the matrix entries.
+  * For vectors, this is also equals to the square root of the dot product of \c *this with itself.
+  *
+  * \sa dot(), squaredNorm()
+  */
+template<typename Derived>
+inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm() const
+{
+  using std::sqrt;
+  return sqrt(squaredNorm());
 }
 
-/** \returns an expression of the quotient of \c *this by its own norm.
- *
- * \warning If the input vector is too small (i.e., this->norm()==0),
- *          then this function returns a copy of the input.
- *
- * \only_for_vectors
- *
- * \sa norm(), normalize()
- */
-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_;
-  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))
-    return n / numext::sqrt(z);
-  else
-    return n;
+/** \returns an expression of the quotient of *this by its own norm.
+  *
+  * \only_for_vectors
+  *
+  * \sa norm(), normalize()
+  */
+template<typename Derived>
+inline const typename MatrixBase<Derived>::PlainObject
+MatrixBase<Derived>::normalized() const
+{
+  typedef typename internal::nested<Derived>::type Nested;
+  typedef typename internal::remove_reference<Nested>::type _Nested;
+  _Nested n(derived());
+  return n / n.norm();
 }
 
 /** Normalizes the vector, i.e. divides it by its own norm.
- *
- * \only_for_vectors
- *
- * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged.
- *
- * \sa norm(), normalized()
- */
-template <typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase<Derived>::normalize() {
-  RealScalar z = squaredNorm();
-  // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU
-  if (z > RealScalar(0)) derived() /= numext::sqrt(z);
-}
-
-/** \returns an expression of the quotient of \c *this by its own norm while avoiding underflow and overflow.
- *
- * \only_for_vectors
- *
- * This method is analogue to the normalized() method, but it reduces the risk of
- * underflow and overflow when computing the norm.
- *
- * \warning If the input vector is too small (i.e., this->norm()==0),
- *          then this function returns a copy of the input.
- *
- * \sa stableNorm(), stableNormalize(), normalized()
- */
-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_;
-  Nested_ n(derived());
-  RealScalar w = n.cwiseAbs().maxCoeff();
-  RealScalar z = (n / w).squaredNorm();
-  if (z > RealScalar(0))
-    return n / (numext::sqrt(z) * w);
-  else
-    return n;
-}
-
-/** Normalizes the vector while avoid underflow and overflow
- *
- * \only_for_vectors
- *
- * This method is analogue to the normalize() method, but it reduces the risk of
- * underflow and overflow when computing the norm.
- *
- * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged.
- *
- * \sa stableNorm(), stableNormalized(), normalize()
- */
-template <typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase<Derived>::stableNormalize() {
-  RealScalar w = cwiseAbs().maxCoeff();
-  RealScalar z = (derived() / w).squaredNorm();
-  if (z > RealScalar(0)) derived() /= numext::sqrt(z) * w;
+  *
+  * \only_for_vectors
+  *
+  * \sa norm(), normalized()
+  */
+template<typename Derived>
+inline void MatrixBase<Derived>::normalize()
+{
+  *this /= norm();
 }
 
 //---------- implementation of other norms ----------
 
 namespace internal {
 
-template <typename Derived, int p>
-struct lpNorm_selector {
+template<typename Derived, int p>
+struct lpNorm_selector
+{
   typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
-  EIGEN_DEVICE_FUNC static inline RealScalar run(const MatrixBase<Derived>& m) {
-    EIGEN_USING_STD(pow)
-    return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1) / p);
+  static inline RealScalar run(const MatrixBase<Derived>& m)
+  {
+    using std::pow;
+    return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
   }
 };
 
-template <typename Derived>
-struct lpNorm_selector<Derived, 1> {
-  EIGEN_DEVICE_FUNC static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(
-      const MatrixBase<Derived>& m) {
+template<typename Derived>
+struct lpNorm_selector<Derived, 1>
+{
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  {
     return m.cwiseAbs().sum();
   }
 };
 
-template <typename Derived>
-struct lpNorm_selector<Derived, 2> {
-  EIGEN_DEVICE_FUNC static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(
-      const MatrixBase<Derived>& m) {
+template<typename Derived>
+struct lpNorm_selector<Derived, 2>
+{
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  {
     return m.norm();
   }
 };
 
-template <typename Derived>
-struct lpNorm_selector<Derived, Infinity> {
-  typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
-  EIGEN_DEVICE_FUNC static inline RealScalar run(const MatrixBase<Derived>& m) {
-    if (Derived::SizeAtCompileTime == 0 || (Derived::SizeAtCompileTime == Dynamic && m.size() == 0))
-      return RealScalar(0);
+template<typename Derived>
+struct lpNorm_selector<Derived, Infinity>
+{
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  {
     return m.cwiseAbs().maxCoeff();
   }
 };
 
-}  // end namespace internal
+} // end namespace internal
 
-/** \returns the \b coefficient-wise \f$ \ell^p \f$ norm of \c *this, that is, returns the p-th root of the sum of the
- * p-th powers of the absolute values of the coefficients of \c *this. If \a p is the special value \a Eigen::Infinity,
- * this function returns the \f$ \ell^\infty \f$ norm, that is the maximum of the absolute values of the coefficients of
- * \c *this.
- *
- * In all cases, if \c *this is empty, then the value 0 is returned.
- *
- * \note For matrices, this function does not compute the <a
- * href="https://en.wikipedia.org/wiki/Operator_norm">operator-norm</a>. That is, if \c *this is a matrix, then its
- * coefficients are interpreted as a 1D vector. Nonetheless, you can easily compute the 1-norm and \f$\infty\f$-norm
- * matrix operator norms using \link TutorialReductionsVisitorsBroadcastingReductionsNorm partial reductions \endlink.
- *
- * \sa norm()
- */
-template <typename Derived>
-template <int p>
-#ifndef EIGEN_PARSED_BY_DOXYGEN
-EIGEN_DEVICE_FUNC inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
-#else
-EIGEN_DEVICE_FUNC MatrixBase<Derived>::RealScalar
-#endif
-MatrixBase<Derived>::lpNorm() const {
+/** \returns the \f$ \ell^p \f$ norm of *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values
+  *          of the coefficients of *this. If \a p is the special value \a Eigen::Infinity, this function returns the \f$ \ell^\infty \f$
+  *          norm, that is the maximum of the absolute values of the coefficients of *this.
+  *
+  * \sa norm()
+  */
+template<typename Derived>
+template<int p>
+inline typename NumTraits<typename internal::traits<Derived>::Scalar>::Real
+MatrixBase<Derived>::lpNorm() const
+{
   return internal::lpNorm_selector<Derived, p>::run(*this);
 }
 
 //---------- implementation of isOrthogonal / isUnitary ----------
 
 /** \returns true if *this is approximately orthogonal to \a other,
- *          within the precision given by \a prec.
- *
- * Example: \include MatrixBase_isOrthogonal.cpp
- * Output: \verbinclude MatrixBase_isOrthogonal.out
- */
-template <typename Derived>
-template <typename OtherDerived>
-bool MatrixBase<Derived>::isOrthogonal(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const {
-  typename internal::nested_eval<Derived, 2>::type nested(derived());
-  typename internal::nested_eval<OtherDerived, 2>::type otherNested(other.derived());
+  *          within the precision given by \a prec.
+  *
+  * Example: \include MatrixBase_isOrthogonal.cpp
+  * Output: \verbinclude MatrixBase_isOrthogonal.out
+  */
+template<typename Derived>
+template<typename OtherDerived>
+bool MatrixBase<Derived>::isOrthogonal
+(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const
+{
+  typename internal::nested<Derived,2>::type nested(derived());
+  typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
   return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
 }
 
 /** \returns true if *this is approximately an unitary matrix,
- *          within the precision given by \a prec. In the case where the \a Scalar
- *          type is real numbers, a unitary matrix is an orthogonal matrix, whence the name.
- *
- * \note This can be used to check whether a family of vectors forms an orthonormal basis.
- *       Indeed, \c m.isUnitary() returns true if and only if the columns (equivalently, the rows) of m form an
- *       orthonormal basis.
- *
- * Example: \include MatrixBase_isUnitary.cpp
- * Output: \verbinclude MatrixBase_isUnitary.out
- */
-template <typename Derived>
-bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const {
-  typename internal::nested_eval<Derived, 1>::type self(derived());
-  for (Index i = 0; i < cols(); ++i) {
-    if (!internal::isApprox(self.col(i).squaredNorm(), static_cast<RealScalar>(1), prec)) return false;
-    for (Index j = 0; j < i; ++j)
-      if (!internal::isMuchSmallerThan(self.col(i).dot(self.col(j)), static_cast<Scalar>(1), prec)) return false;
+  *          within the precision given by \a prec. In the case where the \a Scalar
+  *          type is real numbers, a unitary matrix is an orthogonal matrix, whence the name.
+  *
+  * \note This can be used to check whether a family of vectors forms an orthonormal basis.
+  *       Indeed, \c m.isUnitary() returns true if and only if the columns (equivalently, the rows) of m form an
+  *       orthonormal basis.
+  *
+  * Example: \include MatrixBase_isUnitary.cpp
+  * Output: \verbinclude MatrixBase_isUnitary.out
+  */
+template<typename Derived>
+bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const
+{
+  typename Derived::Nested nested(derived());
+  for(Index i = 0; i < cols(); ++i)
+  {
+    if(!internal::isApprox(nested.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
+      return false;
+    for(Index j = 0; j < i; ++j)
+      if(!internal::isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast<Scalar>(1), prec))
+        return false;
   }
   return true;
 }
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_DOT_H
+#endif // EIGEN_DOT_H