bump version number

(transplanted from 54559094ec
)

.clang-format

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

.git-blame-ignore-revs

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

.gitattributes

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

.gitlab-ci.yml

@@ -1,38 +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:
-# automatically cancels a job when a new pipeline for the same branch is triggered
-  interruptible: true
-
-stages:
-  - checkformat
-  - build
-  - test
-  - deploy
-
-variables:
-  # CMake build directory.
-  EIGEN_CI_BUILDDIR: .build
-  # Specify the CMake build target.
-  EIGEN_CI_BUILD_TARGET: ""
-  # If a test regex is specified, that will be selected.
-  # Otherwise, we will try a label if specified.
-  EIGEN_CI_CTEST_REGEX: ""
-  EIGEN_CI_CTEST_LABEL: ""
-  EIGEN_CI_CTEST_ARGS: ""
-
-include:
-  - "/ci/checkformat.gitlab-ci.yml"
-  - "/ci/common.gitlab-ci.yml"
-  - "/ci/build.linux.gitlab-ci.yml"
-  - "/ci/build.windows.gitlab-ci.yml"
-  - "/ci/test.linux.gitlab-ci.yml"
-  - "/ci/test.windows.gitlab-ci.yml"
-  - "/ci/deploy.gitlab-ci.yml"

.gitlab/issue_templates/Bug Report.md

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

.gitlab/issue_templates/Feature Request.md

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

.gitlab/merge_request_templates/Merge Request Template.md

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

.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_*
@@ -27,15 +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

.krazy

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

COPYING.APACHE

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

COPYING.BSD

@@ -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
+
+ Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+                            Preamble
+
+  The GNU General Public License is a free, copyleft license for
+software and other kinds of works.
+
+  The licenses for most software and other practical works are designed
+to take away your freedom to share and change the works.  By contrast,
+the GNU General Public License is intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users.  We, the Free Software Foundation, use the
+GNU General Public License for most of our software; it applies also to
+any other work released this way by its authors.  You can apply it to
+your programs, too.
+
+  When we speak of free software, we are referring to freedom, not
+price.  Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
+them if you wish), that you receive source code or can get it if you
+want it, that you can change the software or use pieces of it in new
+free programs, and that you know you can do these things.
+
+  To protect your rights, we need to prevent others from denying you
+these rights or asking you to surrender the rights.  Therefore, you have
+certain responsibilities if you distribute copies of the software, or if
+you modify it: responsibilities to respect the freedom of others.
+
+  For example, if you distribute copies of such a program, whether
+gratis or for a fee, you must pass on to the recipients the same
+freedoms that you received.  You must make sure that they, too, receive
+or can get the source code.  And you must show them these terms so they
+know their rights.
+
+  Developers that use the GNU GPL protect your rights with two steps:
+(1) assert copyright on the software, and (2) offer you this License
+giving you legal permission to copy, distribute and/or modify it.
+
+  For the developers' and authors' protection, the GPL clearly explains
+that there is no warranty for this free software.  For both users' and
+authors' sake, the GPL requires that modified versions be marked as
+changed, so that their problems will not be attributed erroneously to
+authors of previous versions.
+
+  Some devices are designed to deny users access to install or run
+modified versions of the software inside them, although the manufacturer
+can do so.  This is fundamentally incompatible with the aim of
+protecting users' freedom to change the software.  The systematic
+pattern of such abuse occurs in the area of products for individuals to
+use, which is precisely where it is most unacceptable.  Therefore, we
+have designed this version of the GPL to prohibit the practice for those
+products.  If such problems arise substantially in other domains, we
+stand ready to extend this provision to those domains in future versions
+of the GPL, as needed to protect the freedom of users.
+
+  Finally, every program is threatened constantly by software patents.
+States should not allow patents to restrict development and use of
+software on general-purpose computers, but in those that do, we wish to
+avoid the special danger that patents applied to a free program could
+make it effectively proprietary.  To prevent this, the GPL assures that
+patents cannot be used to render the program non-free.
+
+  The precise terms and conditions for copying, distribution and
+modification follow.
+
+                       TERMS AND CONDITIONS
+
+  0. Definitions.
+
+  "This License" refers to version 3 of the GNU General Public License.
+
+  "Copyright" also means copyright-like laws that apply to other kinds of
+works, such as semiconductor masks.
+
+  "The Program" refers to any copyrightable work licensed under this
+License.  Each licensee is addressed as "you".  "Licensees" and
+"recipients" may be individuals or organizations.
+
+  To "modify" a work means to copy from or adapt all or part of the work
+in a fashion requiring copyright permission, other than the making of an
+exact copy.  The resulting work is called a "modified version" of the
+earlier work or a work "based on" the earlier work.
+
+  A "covered work" means either the unmodified Program or a work based
+on the Program.
+
+  To "propagate" a work means to do anything with it that, without
+permission, would make you directly or secondarily liable for
+infringement under applicable copyright law, except executing it on a
+computer or modifying a private copy.  Propagation includes copying,
+distribution (with or without modification), making available to the
+public, and in some countries other activities as well.
+
+  To "convey" a work means any kind of propagation that enables other
+parties to make or receive copies.  Mere interaction with a user through
+a computer network, with no transfer of a copy, is not conveying.
+
+  An interactive user interface displays "Appropriate Legal Notices"
+to the extent that it includes a convenient and prominently visible
+feature that (1) displays an appropriate copyright notice, and (2)
+tells the user that there is no warranty for the work (except to the
+extent that warranties are provided), that licensees may convey the
+work under this License, and how to view a copy of this License.  If
+the interface presents a list of user commands or options, such as a
+menu, a prominent item in the list meets this criterion.
+
+  1. Source Code.
+
+  The "source code" for a work means the preferred form of the work
+for making modifications to it.  "Object code" means any non-source
+form of a work.
+
+  A "Standard Interface" means an interface that either is an official
+standard defined by a recognized standards body, or, in the case of
+interfaces specified for a particular programming language, one that
+is widely used among developers working in that language.
+
+  The "System Libraries" of an executable work include anything, other
+than the work as a whole, that (a) is included in the normal form of
+packaging a Major Component, but which is not part of that Major
+Component, and (b) serves only to enable use of the work with that
+Major Component, or to implement a Standard Interface for which an
+implementation is available to the public in source code form.  A
+"Major Component", in this context, means a major essential component
+(kernel, window system, and so on) of the specific operating system
+(if any) on which the executable work runs, or a compiler used to
+produce the work, or an object code interpreter used to run it.
+
+  The "Corresponding Source" for a work in object code form means all
+the source code needed to generate, install, and (for an executable
+work) run the object code and to modify the work, including scripts to
+control those activities.  However, it does not include the work's
+System Libraries, or general-purpose tools or generally available free
+programs which are used unmodified in performing those activities but
+which are not part of the work.  For example, Corresponding Source
+includes interface definition files associated with source files for
+the work, and the source code for shared libraries and dynamically
+linked subprograms that the work is specifically designed to require,
+such as by intimate data communication or control flow between those
+subprograms and other parts of the work.
+
+  The Corresponding Source need not include anything that users
+can regenerate automatically from other parts of the Corresponding
+Source.
+
+  The Corresponding Source for a work in source code form is that
+same work.
+
+  2. Basic Permissions.
+
+  All rights granted under this License are granted for the term of
+copyright on the Program, and are irrevocable provided the stated
+conditions are met.  This License explicitly affirms your unlimited
+permission to run the unmodified Program.  The output from running a
+covered work is covered by this License only if the output, given its
+content, constitutes a covered work.  This License acknowledges your
+rights of fair use or other equivalent, as provided by copyright law.
+
+  You may make, run and propagate covered works that you do not
+convey, without conditions so long as your license otherwise remains
+in force.  You may convey covered works to others for the sole purpose
+of having them make modifications exclusively for you, or provide you
+with facilities for running those works, provided that you comply with
+the terms of this License in conveying all material for which you do
+not control copyright.  Those thus making or running the covered works
+for you must do so exclusively on your behalf, under your direction
+and control, on terms that prohibit them from making any copies of
+your copyrighted material outside their relationship with you.
+
+  Conveying under any other circumstances is permitted solely under
+the conditions stated below.  Sublicensing is not allowed; section 10
+makes it unnecessary.
+
+  3. Protecting Users' Legal Rights From Anti-Circumvention Law.
+
+  No covered work shall be deemed part of an effective technological
+measure under any applicable law fulfilling obligations under article
+11 of the WIPO copyright treaty adopted on 20 December 1996, or
+similar laws prohibiting or restricting circumvention of such
+measures.
+
+  When you convey a covered work, you waive any legal power to forbid
+circumvention of technological measures to the extent such circumvention
+is effected by exercising rights under this License with respect to
+the covered work, and you disclaim any intention to limit operation or
+modification of the work as a means of enforcing, against the work's
+users, your or third parties' legal rights to forbid circumvention of
+technological measures.
+
+  4. Conveying Verbatim Copies.
+
+  You may convey verbatim copies of the Program's source code as you
+receive it, in any medium, provided that you conspicuously and
+appropriately publish on each copy an appropriate copyright notice;
+keep intact all notices stating that this License and any
+non-permissive terms added in accord with section 7 apply to the code;
+keep intact all notices of the absence of any warranty; and give all
+recipients a copy of this License along with the Program.
+
+  You may charge any price or no price for each copy that you convey,
+and you may offer support or warranty protection for a fee.
+
+  5. Conveying Modified Source Versions.
+
+  You may convey a work based on the Program, or the modifications to
+produce it from the Program, in the form of source code under the
+terms of section 4, provided that you also meet all of these conditions:
+
+    a) The work must carry prominent notices stating that you modified
+    it, and giving a relevant date.
+
+    b) The work must carry prominent notices stating that it is
+    released under this License and any conditions added under section
+    7.  This requirement modifies the requirement in section 4 to
+    "keep intact all notices".
+
+    c) You must license the entire work, as a whole, under this
+    License to anyone who comes into possession of a copy.  This
+    License will therefore apply, along with any applicable section 7
+    additional terms, to the whole of the work, and all its parts,
+    regardless of how they are packaged.  This License gives no
+    permission to license the work in any other way, but it does not
+    invalidate such permission if you have separately received it.
+
+    d) If the work has interactive user interfaces, each must display
+    Appropriate Legal Notices; however, if the Program has interactive
+    interfaces that do not display Appropriate Legal Notices, your
+    work need not make them do so.
+
+  A compilation of a covered work with other separate and independent
+works, which are not by their nature extensions of the covered work,
+and which are not combined with it such as to form a larger program,
+in or on a volume of a storage or distribution medium, is called an
+"aggregate" if the compilation and its resulting copyright are not
+used to limit the access or legal rights of the compilation's users
+beyond what the individual works permit.  Inclusion of a covered work
+in an aggregate does not cause this License to apply to the other
+parts of the aggregate.
+
+  6. Conveying Non-Source Forms.
+
+  You may convey a covered work in object code form under the terms
+of sections 4 and 5, provided that you also convey the
+machine-readable Corresponding Source under the terms of this License,
+in one of these ways:
+
+    a) Convey the object code in, or embodied in, a physical product
+    (including a physical distribution medium), accompanied by the
+    Corresponding Source fixed on a durable physical medium
+    customarily used for software interchange.
+
+    b) Convey the object code in, or embodied in, a physical product
+    (including a physical distribution medium), accompanied by a
+    written offer, valid for at least three years and valid for as
+    long as you offer spare parts or customer support for that product
+    model, to give anyone who possesses the object code either (1) a
+    copy of the Corresponding Source for all the software in the
+    product that is covered by this License, on a durable physical
+    medium customarily used for software interchange, for a price no
+    more than your reasonable cost of physically performing this
+    conveying of source, or (2) access to copy the
+    Corresponding Source from a network server at no charge.
+
+    c) Convey individual copies of the object code with a copy of the
+    written offer to provide the Corresponding Source.  This
+    alternative is allowed only occasionally and noncommercially, and
+    only if you received the object code with such an offer, in accord
+    with subsection 6b.
+
+    d) Convey the object code by offering access from a designated
+    place (gratis or for a charge), and offer equivalent access to the
+    Corresponding Source in the same way through the same place at no
+    further charge.  You need not require recipients to copy the
+    Corresponding Source along with the object code.  If the place to
+    copy the object code is a network server, the Corresponding Source
+    may be on a different server (operated by you or a third party)
+    that supports equivalent copying facilities, provided you maintain
+    clear directions next to the object code saying where to find the
+    Corresponding Source.  Regardless of what server hosts the
+    Corresponding Source, you remain obligated to ensure that it is
+    available for as long as needed to satisfy these requirements.
+
+    e) Convey the object code using peer-to-peer transmission, provided
+    you inform other peers where the object code and Corresponding
+    Source of the work are being offered to the general public at no
+    charge under subsection 6d.
+
+  A separable portion of the object code, whose source code is excluded
+from the Corresponding Source as a System Library, need not be
+included in conveying the object code work.
+
+  A "User Product" is either (1) a "consumer product", which means any
+tangible personal property which is normally used for personal, family,
+or household purposes, or (2) anything designed or sold for incorporation
+into a dwelling.  In determining whether a product is a consumer product,
+doubtful cases shall be resolved in favor of coverage.  For a particular
+product received by a particular user, "normally used" refers to a
+typical or common use of that class of product, regardless of the status
+of the particular user or of the way in which the particular user
+actually uses, or expects or is expected to use, the product.  A product
+is a consumer product regardless of whether the product has substantial
+commercial, industrial or non-consumer uses, unless such uses represent
+the only significant mode of use of the product.
+
+  "Installation Information" for a User Product means any methods,
+procedures, authorization keys, or other information required to install
+and execute modified versions of a covered work in that User Product from
+a modified version of its Corresponding Source.  The information must
+suffice to ensure that the continued functioning of the modified object
+code is in no case prevented or interfered with solely because
+modification has been made.
+
+  If you convey an object code work under this section in, or with, or
+specifically for use in, a User Product, and the conveying occurs as
+part of a transaction in which the right of possession and use of the
+User Product is transferred to the recipient in perpetuity or for a
+fixed term (regardless of how the transaction is characterized), the
+Corresponding Source conveyed under this section must be accompanied
+by the Installation Information.  But this requirement does not apply
+if neither you nor any third party retains the ability to install
+modified object code on the User Product (for example, the work has
+been installed in ROM).
+
+  The requirement to provide Installation Information does not include a
+requirement to continue to provide support service, warranty, or updates
+for a work that has been modified or installed by the recipient, or for
+the User Product in which it has been modified or installed.  Access to a
+network may be denied when the modification itself materially and
+adversely affects the operation of the network or violates the rules and
+protocols for communication across the network.
+
+  Corresponding Source conveyed, and Installation Information provided,
+in accord with this section must be in a format that is publicly
+documented (and with an implementation available to the public in
+source code form), and must require no special password or key for
+unpacking, reading or copying.
+
+  7. Additional Terms.
+
+  "Additional permissions" are terms that supplement the terms of this
+License by making exceptions from one or more of its conditions.
+Additional permissions that are applicable to the entire Program shall
+be treated as though they were included in this License, to the extent
+that they are valid under applicable law.  If additional permissions
+apply only to part of the Program, that part may be used separately
+under those permissions, but the entire Program remains governed by
+this License without regard to the additional permissions.
+
+  When you convey a copy of a covered work, you may at your option
+remove any additional permissions from that copy, or from any part of
+it.  (Additional permissions may be written to require their own
+removal in certain cases when you modify the work.)  You may place
+additional permissions on material, added by you to a covered work,
+for which you have or can give appropriate copyright permission.
+
+  Notwithstanding any other provision of this License, for material you
+add to a covered work, you may (if authorized by the copyright holders of
+that material) supplement the terms of this License with terms:
+
+    a) Disclaiming warranty or limiting liability differently from the
+    terms of sections 15 and 16 of this License; or
+
+    b) Requiring preservation of specified reasonable legal notices or
+    author attributions in that material or in the Appropriate Legal
+    Notices displayed by works containing it; or
+
+    c) Prohibiting misrepresentation of the origin of that material, or
+    requiring that modified versions of such material be marked in
+    reasonable ways as different from the original version; or
+
+    d) Limiting the use for publicity purposes of names of licensors or
+    authors of the material; or
+
+    e) Declining to grant rights under trademark law for use of some
+    trade names, trademarks, or service marks; or
+
+    f) Requiring indemnification of licensors and authors of that
+    material by anyone who conveys the material (or modified versions of
+    it) with contractual assumptions of liability to the recipient, for
+    any liability that these contractual assumptions directly impose on
+    those licensors and authors.
+
+  All other non-permissive additional terms are considered "further
+restrictions" within the meaning of section 10.  If the Program as you
+received it, or any part of it, contains a notice stating that it is
+governed by this License along with a term that is a further
+restriction, you may remove that term.  If a license document contains
+a further restriction but permits relicensing or conveying under this
+License, you may add to a covered work material governed by the terms
+of that license document, provided that the further restriction does
+not survive such relicensing or conveying.
+
+  If you add terms to a covered work in accord with this section, you
+must place, in the relevant source files, a statement of the
+additional terms that apply to those files, or a notice indicating
+where to find the applicable terms.
+
+  Additional terms, permissive or non-permissive, may be stated in the
+form of a separately written license, or stated as exceptions;
+the above requirements apply either way.
+
+  8. Termination.
+
+  You may not propagate or modify a covered work except as expressly
+provided under this License.  Any attempt otherwise to propagate or
+modify it is void, and will automatically terminate your rights under
+this License (including any patent licenses granted under the third
+paragraph of section 11).
+
+  However, if you cease all violation of this License, then your
+license from a particular copyright holder is reinstated (a)
+provisionally, unless and until the copyright holder explicitly and
+finally terminates your license, and (b) permanently, if the copyright
+holder fails to notify you of the violation by some reasonable means
+prior to 60 days after the cessation.
+
+  Moreover, your license from a particular copyright holder is
+reinstated permanently if the copyright holder notifies you of the
+violation by some reasonable means, this is the first time you have
+received notice of violation of this License (for any work) from that
+copyright holder, and you cure the violation prior to 30 days after
+your receipt of the notice.
+
+  Termination of your rights under this section does not terminate the
+licenses of parties who have received copies or rights from you under
+this License.  If your rights have been terminated and not permanently
+reinstated, you do not qualify to receive new licenses for the same
+material under section 10.
+
+  9. Acceptance Not Required for Having Copies.
+
+  You are not required to accept this License in order to receive or
+run a copy of the Program.  Ancillary propagation of a covered work
+occurring solely as a consequence of using peer-to-peer transmission
+to receive a copy likewise does not require acceptance.  However,
+nothing other than this License grants you permission to propagate or
+modify any covered work.  These actions infringe copyright if you do
+not accept this License.  Therefore, by modifying or propagating a
+covered work, you indicate your acceptance of this License to do so.
+
+  10. Automatic Licensing of Downstream Recipients.
+
+  Each time you convey a covered work, the recipient automatically
+receives a license from the original licensors, to run, modify and
+propagate that work, subject to this License.  You are not responsible
+for enforcing compliance by third parties with this License.
+
+  An "entity transaction" is a transaction transferring control of an
+organization, or substantially all assets of one, or subdividing an
+organization, or merging organizations.  If propagation of a covered
+work results from an entity transaction, each party to that
+transaction who receives a copy of the work also receives whatever
+licenses to the work the party's predecessor in interest had or could
+give under the previous paragraph, plus a right to possession of the
+Corresponding Source of the work from the predecessor in interest, if
+the predecessor has it or can get it with reasonable efforts.
+
+  You may not impose any further restrictions on the exercise of the
+rights granted or affirmed under this License.  For example, you may
+not impose a license fee, royalty, or other charge for exercise of
+rights granted under this License, and you may not initiate litigation
+(including a cross-claim or counterclaim in a lawsuit) alleging that
+any patent claim is infringed by making, using, selling, offering for
+sale, or importing the Program or any portion of it.
+
+  11. Patents.
+
+  A "contributor" is a copyright holder who authorizes use under this
+License of the Program or a work on which the Program is based.  The
+work thus licensed is called the contributor's "contributor version".
+
+  A contributor's "essential patent claims" are all patent claims
+owned or controlled by the contributor, whether already acquired or
+hereafter acquired, that would be infringed by some manner, permitted
+by this License, of making, using, or selling its contributor version,
+but do not include claims that would be infringed only as a
+consequence of further modification of the contributor version.  For
+purposes of this definition, "control" includes the right to grant
+patent sublicenses in a manner consistent with the requirements of
+this License.
+
+  Each contributor grants you a non-exclusive, worldwide, royalty-free
+patent license under the contributor's essential patent claims, to
+make, use, sell, offer for sale, import and otherwise run, modify and
+propagate the contents of its contributor version.
+
+  In the following three paragraphs, a "patent license" is any express
+agreement or commitment, however denominated, not to enforce a patent
+(such as an express permission to practice a patent or covenant not to
+sue for patent infringement).  To "grant" such a patent license to a
+party means to make such an agreement or commitment not to enforce a
+patent against the party.
+
+  If you convey a covered work, knowingly relying on a patent license,
+and the Corresponding Source of the work is not available for anyone
+to copy, free of charge and under the terms of this License, through a
+publicly available network server or other readily accessible means,
+then you must either (1) cause the Corresponding Source to be so
+available, or (2) arrange to deprive yourself of the benefit of the
+patent license for this particular work, or (3) arrange, in a manner
+consistent with the requirements of this License, to extend the patent
+license to downstream recipients.  "Knowingly relying" means you have
+actual knowledge that, but for the patent license, your conveying the
+covered work in a country, or your recipient's use of the covered work
+in a country, would infringe one or more identifiable patents in that
+country that you have reason to believe are valid.
+
+  If, pursuant to or in connection with a single transaction or
+arrangement, you convey, or propagate by procuring conveyance of, a
+covered work, and grant a patent license to some of the parties
+receiving the covered work authorizing them to use, propagate, modify
+or convey a specific copy of the covered work, then the patent license
+you grant is automatically extended to all recipients of the covered
+work and works based on it.
+
+  A patent license is "discriminatory" if it does not include within
+the scope of its coverage, prohibits the exercise of, or is
+conditioned on the non-exercise of one or more of the rights that are
+specifically granted under this License.  You may not convey a covered
+work if you are a party to an arrangement with a third party that is
+in the business of distributing software, under which you make payment
+to the third party based on the extent of your activity of conveying
+the work, and under which the third party grants, to any of the
+parties who would receive the covered work from you, a discriminatory
+patent license (a) in connection with copies of the covered work
+conveyed by you (or copies made from those copies), or (b) primarily
+for and in connection with specific products or compilations that
+contain the covered work, unless you entered into that arrangement,
+or that patent license was granted, prior to 28 March 2007.
+
+  Nothing in this License shall be construed as excluding or limiting
+any implied license or other defenses to infringement that may
+otherwise be available to you under applicable patent law.
+
+  12. No Surrender of Others' Freedom.
+
+  If conditions are imposed on you (whether by court order, agreement or
+otherwise) that contradict the conditions of this License, they do not
+excuse you from the conditions of this License.  If you cannot convey a
+covered work so as to satisfy simultaneously your obligations under this
+License and any other pertinent obligations, then as a consequence you may
+not convey it at all.  For example, if you agree to terms that obligate you
+to collect a royalty for further conveying from those to whom you convey
+the Program, the only way you could satisfy both those terms and this
+License would be to refrain entirely from conveying the Program.
+
+  13. Use with the GNU Affero General Public License.
+
+  Notwithstanding any other provision of this License, you have
+permission to link or combine any covered work with a work licensed
+under version 3 of the GNU Affero General Public License into a single
+combined work, and to convey the resulting work.  The terms of this
+License will continue to apply to the part which is the covered work,
+but the special requirements of the GNU Affero General Public License,
+section 13, concerning interaction through a network will apply to the
+combination as such.
+
+  14. Revised Versions of this License.
+
+  The Free Software Foundation may publish revised and/or new versions of
+the GNU General Public License from time to time.  Such new versions will
+be similar in spirit to the present version, but may differ in detail to
+address new problems or concerns.
+
+  Each version is given a distinguishing version number.  If the
+Program specifies that a certain numbered version of the GNU General
+Public License "or any later version" applies to it, you have the
+option of following the terms and conditions either of that numbered
+version or of any later version published by the Free Software
+Foundation.  If the Program does not specify a version number of the
+GNU General Public License, you may choose any version ever published
+by the Free Software Foundation.
+
+  If the Program specifies that a proxy can decide which future
+versions of the GNU General Public License can be used, that proxy's
+public statement of acceptance of a version permanently authorizes you
+to choose that version for the Program.
+
+  Later license versions may give you additional or different
+permissions.  However, no additional obligations are imposed on any
+author or copyright holder as a result of your choosing to follow a
+later version.
+
+  15. Disclaimer of Warranty.
+
+  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
+HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
+OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
+THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
+IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
+ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. Limitation of Liability.
+
+  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
+THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
+GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
+USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
+DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
+PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
+EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
+SUCH DAMAGES.
+
+  17. Interpretation of Sections 15 and 16.
+
+  If the disclaimer of warranty and limitation of liability provided
+above cannot be given local legal effect according to their terms,
+reviewing courts shall apply local law that most closely approximates
+an absolute waiver of all civil liability in connection with the
+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+                     END OF TERMS AND CONDITIONS
+
+            How to Apply These Terms to Your New Programs
+
+  If you develop a new program, and you want it to be of the greatest
+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
+
+  To do so, attach the following notices to the program.  It is safest
+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the program's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This program is free software: you can redistribute it and/or modify
+    it under the terms of the GNU General Public License as published by
+    the Free Software Foundation, either version 3 of the License, or
+    (at your option) any later version.
+
+    This program is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+    GNU General Public License for more details.
+
+    You should have received a copy of the GNU General Public License
+    along with this program.  If not, see <http://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+  If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
+
+    <program>  Copyright (C) <year>  <name of author>
+    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+    This is free software, and you are welcome to redistribute it
+    under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License.  Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+  You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+<http://www.gnu.org/licenses/>.
+
+  The GNU General Public License does not permit incorporating your program
+into proprietary programs.  If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library.  If this is what you want to do, use the GNU Lesser General
+Public License instead of this License.  But first, please read
+<http://www.gnu.org/philosophy/why-not-lgpl.html>.

COPYING.LGPL

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

COPYING.MINPACK

@@ -1,51 +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

@@ -2,5 +2,14 @@ Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
   http://www.mozilla.org/MPL/2.0/
   http://www.mozilla.org/MPL/2.0/FAQ.html
 
-Some files contain third-party code under BSD or other MPL2-compatible licenses,
-whence the other COPYING.* files here.
+Some files contain third-party code under BSD or LGPL licenses, whence the other
+COPYING.* files here.
+
+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)
+##   ENABLE_TESTING()
+##   INCLUDE(CTest)
 set(CTEST_PROJECT_NAME "Eigen")
 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=Eigen")
 set(CTEST_DROP_SITE_CDASH TRUE)
-#set(CTEST_PROJECT_SUBPROJECTS
-#Official
-#Unsupported
-#)

CTestCustom.cmake.in

@@ -1,4 +1,4 @@
 
-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@)
+## A tribute to Dynamic!
+set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_WARNINGS "33331")
+set(CTEST_CUSTOM_MAXIMUM_NUMBER_OF_ERRORS "33331")

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

@@ -1,43 +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 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.
- *
- */
+  * \defgroup CholmodSupport_Module CholmodSupport module
+  *
+  * This module provides an interface to the Cholmod library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * It provides the two following main factorization classes:
+  * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
+  * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
+  *
+  * For the sake of completeness, this module also propose the two following classes:
+  * - class CholmodSimplicialLLT
+  * - class CholmodSimplicialLDLT
+  * Note that these classes does not bring any particular advantage compared to the built-in
+  * SimplicialLLT and SimplicialLDLT factorization classes.
+  *
+  * \code
+  * #include <Eigen/CholmodSupport>
+  * \endcode
+  *
+  * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies.
+  * The dependencies depend on how cholmod has been compiled.
+  * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
-// 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

@@ -8,71 +8,126 @@
 // 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>
-#endif
-
-#ifdef EIGEN_EXCEPTIONS
-#include <new>
-#endif
-
-// Disable the ipa-cp-clone optimization flag with MinGW 6.x or older (enabled by default with -O3)
-// See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details.
-#if EIGEN_COMP_MINGW && EIGEN_GNUC_STRICT_LESS_THAN(6, 0, 0)
-#pragma GCC optimize("-fno-ipa-cp-clone")
-#endif
-
-// Prevent ICC from specializing std::complex operators that silently fail
-// on device. This allows us to use our own device-compatible specializations
-// instead.
-#if EIGEN_COMP_ICC && defined(EIGEN_GPU_COMPILE_PHASE) && !defined(_OVERRIDE_COMPLEX_SPECIALIZATION_)
-#define _OVERRIDE_COMPLEX_SPECIALIZATION_ 1
-#endif
 #include <complex>
 
 // this include file manages BLAS and MKL related macros
 // and inclusion of their respective header files
 #include "src/Core/util/MKL_support.h"
 
-#if defined(EIGEN_HAS_CUDA_FP16) || defined(EIGEN_HAS_HIP_FP16)
-#define EIGEN_HAS_GPU_FP16
+// 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
 
-#if defined(EIGEN_HAS_CUDA_BF16) || defined(EIGEN_HAS_HIP_BF16)
-#define EIGEN_HAS_GPU_BF16
+#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__) || EIGEN_GNUC_AT_LEAST(4,2) )
+    #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
+  #endif
+#endif
+
+#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" {
+      #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
+    } // 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
 
 // MSVC for windows mobile does not have the errno.h file
-#if !(EIGEN_COMP_MSVC && EIGEN_OS_WINCE) && !EIGEN_COMP_ARM
+#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
 #define EIGEN_HAS_ERRNO
 #endif
 
@@ -82,315 +137,186 @@
 #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) && !EIGEN_OS_WINCE
-#include <intrin.h>
+#if defined(_MSC_VER) && (defined(_M_IX86)||defined(_M_X64))
+  #include <intrin.h>
 #endif
 
-#if defined(EIGEN_USE_SYCL)
-#undef min
-#undef max
-#undef isnan
-#undef isinf
-#undef isfinite
-#include <CL/sycl.hpp>
-#include <map>
-#include <thread>
-#include <utility>
-#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM0
-#define EIGEN_SYCL_LOCAL_THREAD_DIM0 16
-#endif
-#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM1
-#define EIGEN_SYCL_LOCAL_THREAD_DIM1 16
-#endif
+#if defined(_CPPUNWIND) || defined(__EXCEPTIONS)
+  #define EIGEN_EXCEPTIONS
 #endif
 
-#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS || defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API || \
-    defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS || defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API ||  \
-    defined EIGEN2_SUPPORT
-// This will generate an error message:
-#error Eigen2-support is only available up to version 3.2. Please go to "http://eigen.tuxfamily.org/index.php?title=Eigen2" for further information
+#ifdef EIGEN_EXCEPTIONS
+  #include <new>
 #endif
 
+/** \brief Namespace containing all symbols from the %Eigen library. */
 namespace Eigen {
 
-// we use size_t frequently and we'll never remember to prepend it with std:: every time just to
+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
+// gcc 4.6.0 wants std:: for ptrdiff_t 
 using std::ptrdiff_t;
 
-}  // namespace Eigen
-
 /** \defgroup Core_Module Core module
- * This is the main module of Eigen providing dense matrix and vector support
- * (both fixed and dynamic size) with all the features corresponding to a BLAS library
- * and much more...
- *
- * \code
- * #include <Eigen/Core>
- * \endcode
- */
+  * This is the main module of Eigen providing dense matrix and vector support
+  * (both fixed and dynamic size) with all the features corresponding to a BLAS library
+  * and much more...
+  *
+  * \code
+  * #include <Eigen/Core>
+  * \endcode
+  */
 
-#ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
-#endif
-#endif
+/** \defgroup Support_modules Support modules [category]
+  * Category of modules which add support for external libraries.
+  */
 
-// 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/StaticAssert.h"
+#include "src/Core/util/Meta.h"
 #include "src/Core/util/XprHelper.h"
+#include "src/Core/util/StaticAssert.h"
 #include "src/Core/util/Memory.h"
-#include "src/Core/util/IntegralConstant.h"
-#include "src/Core/util/Serializer.h"
-#include "src/Core/util/SymbolicIndex.h"
-#include "src/Core/util/EmulateArray.h"
-#include "src/Core/util/MoreMeta.h"
 
 #include "src/Core/NumTraits.h"
 #include "src/Core/MathFunctions.h"
-#include "src/Core/RandomImpl.h"
 #include "src/Core/GenericPacketMath.h"
-#include "src/Core/MathFunctionsImpl.h"
-#include "src/Core/arch/Default/ConjHelper.h"
-// Generic half float support
-#include "src/Core/arch/Default/Half.h"
-#include "src/Core/arch/Default/BFloat16.h"
-#include "src/Core/arch/Default/GenericPacketMathFunctionsFwd.h"
 
-#if defined EIGEN_VECTORIZE_AVX512
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/AVX/PacketMath.h"
-#include "src/Core/arch/AVX/Reductions.h"
-#include "src/Core/arch/AVX512/PacketMath.h"
-#include "src/Core/arch/AVX512/Reductions.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/PacketMathFP16.h"
-#endif
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/AVX/TypeCasting.h"
-#include "src/Core/arch/AVX512/TypeCasting.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/TypeCastingFP16.h"
-#endif
-#include "src/Core/arch/SSE/Complex.h"
-#include "src/Core/arch/AVX/Complex.h"
-#include "src/Core/arch/AVX512/Complex.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/AVX/MathFunctions.h"
-#include "src/Core/arch/AVX512/MathFunctions.h"
-#if defined EIGEN_VECTORIZE_AVX512FP16
-#include "src/Core/arch/AVX512/MathFunctionsFP16.h"
-#endif
-#include "src/Core/arch/AVX512/TrsmKernel.h"
-#elif defined EIGEN_VECTORIZE_AVX
-// Use AVX for floats and doubles, SSE for integers
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/SSE/Complex.h"
-#include "src/Core/arch/AVX/PacketMath.h"
-#include "src/Core/arch/AVX/Reductions.h"
-#include "src/Core/arch/AVX/TypeCasting.h"
-#include "src/Core/arch/AVX/Complex.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/AVX/MathFunctions.h"
-#elif defined EIGEN_VECTORIZE_SSE
-#include "src/Core/arch/SSE/PacketMath.h"
-#include "src/Core/arch/SSE/Reductions.h"
-#include "src/Core/arch/SSE/TypeCasting.h"
-#include "src/Core/arch/SSE/MathFunctions.h"
-#include "src/Core/arch/SSE/Complex.h"
-#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_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
+  #include "src/Core/arch/NEON/PacketMath.h"
+  #include "src/Core/arch/NEON/Complex.h"
 #endif
 
 #include "src/Core/arch/Default/Settings.h"
-// This file provides generic implementations valid for scalar as well
-#include "src/Core/arch/Default/GenericPacketMathFunctions.h"
 
-#include "src/Core/functors/TernaryFunctors.h"
-#include "src/Core/functors/BinaryFunctors.h"
-#include "src/Core/functors/UnaryFunctors.h"
-#include "src/Core/functors/NullaryFunctors.h"
-#include "src/Core/functors/StlFunctors.h"
-#include "src/Core/functors/AssignmentFunctors.h"
-
-// Specialized functors for GPU.
-#ifdef EIGEN_GPUCC
-#include "src/Core/arch/GPU/Complex.h"
-#endif
-
-// Specializations of vectorized activation functions for NEON.
-#ifdef EIGEN_VECTORIZE_NEON
-#include "src/Core/arch/NEON/UnaryFunctors.h"
-#endif
-
-#include "src/Core/util/IndexedViewHelper.h"
-#include "src/Core/util/ReshapedHelper.h"
-#include "src/Core/ArithmeticSequence.h"
-#ifndef EIGEN_NO_IO
-#include "src/Core/IO.h"
-#endif
+#include "src/Core/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/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/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"
@@ -404,48 +330,37 @@ using std::ptrdiff_t;
 #include "src/Core/products/TriangularSolverMatrix.h"
 #include "src/Core/products/TriangularSolverVector.h"
 #include "src/Core/BandMatrix.h"
-#include "src/Core/CoreIterators.h"
-#include "src/Core/ConditionEstimator.h"
-
-#if defined(EIGEN_VECTORIZE_VSX)
-#include "src/Core/arch/AltiVec/MatrixProduct.h"
-#elif defined EIGEN_VECTORIZE_NEON
-#include "src/Core/arch/NEON/GeneralBlockPanelKernel.h"
-#elif defined EIGEN_VECTORIZE_LSX
-#include "src/Core/arch/LSX/GeneralBlockPanelKernel.h"
-#endif
-
-#if defined(EIGEN_VECTORIZE_AVX512)
-#include "src/Core/arch/AVX512/GemmKernel.h"
-#endif
 
+#include "src/Core/BooleanRedux.h"
 #include "src/Core/Select.h"
 #include "src/Core/VectorwiseOp.h"
-#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
 
 #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/Eigen

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

Eigen/Eigen2Support

@@ -0,0 +1,82 @@
+// 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
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+/** \ingroup Support_modules
+  * \defgroup Eigen2Support_Module Eigen2 support module
+  * 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

@@ -1,40 +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 "src/Core/util/DisableStupidWarnings.h"
+
 #include "Cholesky"
 #include "Jacobi"
 #include "Householder"
 #include "LU"
 #include "Geometry"
 
-#include "src/Core/util/DisableStupidWarnings.h"
-
 /** \defgroup Eigenvalues_Module Eigenvalues module
- *
- *
- *
- * This module mainly provides various eigenvalue solvers.
- * This module also provides some MatrixBase methods, including:
- *  - MatrixBase::eigenvalues(),
- *  - MatrixBase::operatorNorm()
- *
- * \code
- * #include <Eigen/Eigenvalues>
- * \endcode
- */
+  *
+  *
+  *
+  * This module mainly provides various eigenvalue solvers.
+  * This module also provides some MatrixBase methods, including:
+  *  - MatrixBase::eigenvalues(),
+  *  - MatrixBase::operatorNorm()
+  *
+  * \code
+  * #include <Eigen/Eigenvalues>
+  * \endcode
+  */
 
-#include "src/misc/RealSvd2x2.h"
-
-// IWYU pragma: begin_exports
 #include "src/Eigenvalues/Tridiagonalization.h"
 #include "src/Eigenvalues/RealSchur.h"
 #include "src/Eigenvalues/EigenSolver.h"
@@ -43,21 +33,14 @@
 #include "src/Eigenvalues/HessenbergDecomposition.h"
 #include "src/Eigenvalues/ComplexSchur.h"
 #include "src/Eigenvalues/ComplexEigenSolver.h"
-#include "src/Eigenvalues/RealQZ.h"
-#include "src/Eigenvalues/GeneralizedEigenSolver.h"
 #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
 #ifdef EIGEN_USE_LAPACKE
-#ifdef EIGEN_USE_MKL
-#include "mkl_lapacke.h"
-#else
-#include "src/misc/lapacke.h"
+#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/Geometry

@@ -1,59 +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 "src/Core/util/DisableStupidWarnings.h"
+
 #include "SVD"
 #include "LU"
 #include <limits>
 
-#include "src/Core/util/DisableStupidWarnings.h"
+#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
- *  - \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
- */
+  *
+  *
+  *
+  * 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"
 
-// 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/HouseholderSequence.h"
 #include "src/Householder/BlockHouseholder.h"
-// IWYU pragma: end_exports
 
 #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"
 
-/**
+/** \ingroup Sparse_modules
   * \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 umfpack has been compiled. For a
- * cmake based project, you can use our FindKLU.cmake module to help you in this task.
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/KLUSupport/KLUSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_KLUSUPPORT_MODULE_H

Eigen/LU

@@ -1,10 +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
 
@@ -13,34 +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
+  */
 
+#include "src/misc/Solve.h"
 #include "src/misc/Kernel.h"
 #include "src/misc/Image.h"
-
-// IWYU pragma: begin_exports
 #include "src/LU/FullPivLU.h"
 #include "src/LU/PartialPivLU.h"
 #ifdef EIGEN_USE_LAPACKE
-#include "src/misc/lapacke_helpers.h"
-#include "src/LU/PartialPivLU_LAPACKE.h"
+#include "src/LU/PartialPivLU_MKL.h"
 #endif
 #include "src/LU/Determinant.h"
-#include "src/LU/InverseImpl.h"
+#include "src/LU/Inverse.h"
 
-#if defined EIGEN_VECTORIZE_SSE || defined EIGEN_VECTORIZE_NEON
-#include "src/LU/arch/InverseSize4.h"
+#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

@@ -1,35 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_METISSUPPORT_MODULE_H
-#define EIGEN_METISSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-#include <metis.h>
-}
-
-/** \ingroup Support_modules
- * \defgroup MetisSupport_Module MetisSupport module
- *
- * \code
- * #include <Eigen/MetisSupport>
- * \endcode
- * This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis).
- * It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink
- */
-
-// IWYU pragma: begin_exports
-#include "src/MetisSupport/MetisSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_METISSUPPORT_MODULE_H

Eigen/OrderingMethods

@@ -1,10 +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 +5,19 @@
 
 #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
- */
+/** \ingroup Sparse_modules
+  * \defgroup OrderingMethods_Module OrderingMethods module
+  *
+  * This module is currently for internal use only.
+  *
+  *
+  * \code
+  * #include <Eigen/OrderingMethods>
+  * \endcode
+  */
 
-// IWYU pragma: begin_exports
 #include "src/OrderingMethods/Amd.h"
-#include "src/OrderingMethods/Ordering.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_ORDERINGMETHODS_MODULE_H
+#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 resuires PaStiX version 5.x compiled without MPI
- * support. The dependencies depend on how PaSTiX has been compiled. For a cmake based project, you can use our
- * FindPaSTiX.cmake module to help you in this task.
- *
- */
+  * \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

@@ -1,48 +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 "src/Core/util/DisableStupidWarnings.h"
+
 #include "Cholesky"
 #include "Jacobi"
 #include "Householder"
 
-#include "src/Core/util/DisableStupidWarnings.h"
-
 /** \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
+  */
 
-// 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"
 
-void *qMalloc(std::size_t size) { return Eigen::internal::aligned_malloc(size); }
+void *qMalloc(size_t size)
+{
+  return Eigen::internal::aligned_malloc(size);
+}
 
-void qFree(void *ptr) { Eigen::internal::aligned_free(ptr); }
+void qFree(void *ptr)
+{
+  Eigen::internal::aligned_free(ptr);
+}
 
-void *qRealloc(void *ptr, std::size_t size) {
-  void *newPtr = Eigen::internal::aligned_malloc(size);
-  std::memcpy(newPtr, ptr, size);
+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 @@ 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

@@ -1,41 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPQRSUPPORT_MODULE_H
-#define EIGEN_SPQRSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include "SuiteSparseQR.hpp"
-
-/** \ingroup Support_modules
- * \defgroup SPQRSupport_Module SuiteSparseQR module
- *
- * This module provides an interface to the SPQR library, which is part of the <a
- * href="http://www.suitesparse.com">suitesparse</a> package.
- *
- * \code
- * #include <Eigen/SPQRSupport>
- * \endcode
- *
- * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be
- * linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...). For a cmake based project, you can use
- * our FindSPQR.cmake and FindCholmod.Cmake modules
- *
- */
-
-#include "CholmodSupport"
-
-// IWYU pragma: begin_exports
-#include "src/SPQRSupport/SuiteSparseQRSupport.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif

Eigen/SVD

@@ -1,10 +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_SVD_MODULE_H
 #define EIGEN_SVD_MODULE_H
 
@@ -15,42 +8,30 @@
 #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/misc/RealSvd2x2.h"
-#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"
-#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

@@ -1,33 +1,23 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SPARSE_MODULE_H
 #define EIGEN_SPARSE_MODULE_H
 
-/** \defgroup Sparse_Module Sparse meta-module
+/** \defgroup Sparse_modules Sparse modules
   *
   * Meta-module including all related modules:
-  * - \ref SparseCore_Module
-  * - \ref OrderingMethods_Module
-  * - \ref SparseCholesky_Module
-  * - \ref SparseLU_Module
-  * - \ref SparseQR_Module
-  * - \ref IterativeLinearSolvers_Module
+  * - SparseCore
+  * - OrderingMethods
+  * - SparseCholesky
+  * - IterativeLinearSolvers
   *
-    \code
-    #include <Eigen/Sparse>
-    \endcode
+  * \code
+  * #include <Eigen/Sparse>
+  * \endcode
   */
 
 #include "SparseCore"
 #include "OrderingMethods"
 #include "SparseCholesky"
-#include "SparseLU"
-#include "SparseQR"
 #include "IterativeLinearSolvers"
 
-#endif  // EIGEN_SPARSE_MODULE_H
+#endif // EIGEN_SPARSE_MODULE_H
+

Eigen/SparseCholesky

@@ -1,40 +1,30 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2013 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
 #ifndef EIGEN_SPARSECHOLESKY_MODULE_H
 #define EIGEN_SPARSECHOLESKY_MODULE_H
 
 #include "SparseCore"
-#include "OrderingMethods"
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-/**
- * \defgroup SparseCholesky_Module SparseCholesky module
- *
- * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian)
- * matrices. Those decompositions are accessible via the following classes:
- *  - SimplicialLLt,
- *  - SimplicialLDLt
- *
- * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
- *
- * \code
- * #include <Eigen/SparseCholesky>
- * \endcode
- */
+/** \ingroup Sparse_modules
+  * \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
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
-// IWYU pragma: begin_exports
 #include "src/SparseCholesky/SimplicialCholesky.h"
-#include "src/SparseCholesky/SimplicialCholesky_impl.h"
-// IWYU pragma: end_exports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_SPARSECHOLESKY_MODULE_H
+#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
 
@@ -17,54 +10,57 @@
 #include <cstdlib>
 #include <cstring>
 #include <algorithm>
-#include <numeric>
 
-/**
- * \defgroup SparseCore_Module SparseCore module
- *
- * This module provides a sparse matrix representation, and basic associated matrix manipulations
- * and operations.
- *
- * See the \ref TutorialSparse "Sparse tutorial"
- *
- * \code
- * #include <Eigen/SparseCore>
- * \endcode
- *
- * This module depends on: Core.
- */
+/** \ingroup Sparse_modules
+  * \defgroup SparseCore_Module SparseCore module
+  *
+  * This module provides a sparse matrix representation, and basic associatd matrix manipulations
+  * and operations.
+  *
+  * See the \ref TutorialSparse "Sparse tutorial"
+  *
+  * \code
+  * #include <Eigen/SparseCore>
+  * \endcode
+  *
+  * This module depends on: Core.
+  */
+
+namespace Eigen {
+
+/** The type used to identify a general sparse storage. */
+struct Sparse {};
+
+}
 
-// 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/CoreIterators.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/SparseAssign.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

@@ -1,50 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
-// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSELU_MODULE_H
-#define EIGEN_SPARSELU_MODULE_H
-
-#include "SparseCore"
-
-/**
- * \defgroup SparseLU_Module SparseLU module
- * This module defines a supernodal factorization of general sparse matrices.
- * The code is fully optimized for supernode-panel updates with specialized kernels.
- * Please, see the documentation of the SparseLU class for more details.
- */
-
-// Ordering interface
-#include "OrderingMethods"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-// IWYU pragma: begin_exports
-#include "src/SparseLU/SparseLU_Structs.h"
-#include "src/SparseLU/SparseLU_SupernodalMatrix.h"
-#include "src/SparseLU/SparseLUImpl.h"
-#include "src/SparseCore/SparseColEtree.h"
-#include "src/SparseLU/SparseLU_Memory.h"
-#include "src/SparseLU/SparseLU_heap_relax_snode.h"
-#include "src/SparseLU/SparseLU_relax_snode.h"
-#include "src/SparseLU/SparseLU_pivotL.h"
-#include "src/SparseLU/SparseLU_panel_dfs.h"
-#include "src/SparseLU/SparseLU_kernel_bmod.h"
-#include "src/SparseLU/SparseLU_panel_bmod.h"
-#include "src/SparseLU/SparseLU_column_dfs.h"
-#include "src/SparseLU/SparseLU_column_bmod.h"
-#include "src/SparseLU/SparseLU_copy_to_ucol.h"
-#include "src/SparseLU/SparseLU_pruneL.h"
-#include "src/SparseLU/SparseLU_Utils.h"
-#include "src/SparseLU/SparseLU.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_SPARSELU_MODULE_H

Eigen/SparseQR

@@ -1,38 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_SPARSEQR_MODULE_H
-#define EIGEN_SPARSEQR_MODULE_H
-
-#include "SparseCore"
-#include "OrderingMethods"
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \defgroup SparseQR_Module SparseQR module
- * \brief Provides QR decomposition for sparse matrices
- *
- * This module provides a simplicial version of the left-looking Sparse QR decomposition.
- * The columns of the input matrix should be reordered to limit the fill-in during the
- * decomposition. Built-in methods (COLAMD, AMD) or external  methods (METIS) can be used to this end.
- * See the \link OrderingMethods_Module OrderingMethods\endlink module for the list
- * of built-in and external ordering methods.
- *
- * \code
- * #include <Eigen/SparseQR>
- * \endcode
- *
- *
- */
-
-// IWYU pragma: begin_exports
-#include "src/SparseCore/SparseColEtree.h"
-#include "src/SparseQR/SparseQR.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif

Eigen/StdDeque

@@ -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
 
@@ -26,45 +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 <time.h>
-
-#include <vector>
-#include <atomic>
-#include <condition_variable>
-#include <deque>
-#include <mutex>
-#include <thread>
-#include <functional>
-#include <memory>
-#include <utility>
-
-// There are non-parenthesized calls to "max" in the  <unordered_map> header,
-// which trigger a check in test/main.h causing compilation to fail.
-// We work around the check here by removing the check for max in
-// the case where we have to emulate thread_local.
-#ifdef max
-#undef max
-#endif
-#include <unordered_map>
-
-#include "src/Core/util/Meta.h"
-#include "src/Core/util/MaxSizeVector.h"
-
-#ifndef EIGEN_MUTEX
-#define EIGEN_MUTEX std::mutex
-#endif
-#ifndef EIGEN_MUTEX_LOCK
-#define EIGEN_MUTEX_LOCK std::unique_lock<std::mutex>
-#endif
-#ifndef EIGEN_CONDVAR
-#define EIGEN_CONDVAR std::condition_variable
-#endif
-
-// IWYU pragma: begin_exports
-#include "src/ThreadPool/ThreadLocal.h"
-#include "src/ThreadPool/ThreadYield.h"
-#include "src/ThreadPool/ThreadCancel.h"
-#include "src/ThreadPool/EventCount.h"
-#include "src/ThreadPool/RunQueue.h"
-#include "src/ThreadPool/ThreadPoolInterface.h"
-#include "src/ThreadPool/ThreadEnvironment.h"
-#include "src/ThreadPool/Barrier.h"
-#include "src/ThreadPool/NonBlockingThreadPool.h"
-#include "src/ThreadPool/CoreThreadPoolDevice.h"
-#include "src/ThreadPool/ForkJoin.h"
-// IWYU pragma: end_exports
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif  // EIGEN_CXX11_THREADPOOL_MODULE_H

Eigen/UmfPackSupport

@@ -1,10 +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.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * It provides the following factorization class:
+  * - class UmfPackLU: a multifrontal sequential LU factorization.
+  *
+  * \code
+  * #include <Eigen/UmfPackSupport>
+  * \endcode
+  *
+  * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies.
+  * The dependencies depend on how umfpack has been compiled.
+  * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
 
-// IWYU pragma: begin_exports
 #include "src/UmfPackSupport/UmfPackSupport.h"
-// IWYU pragma: endexports
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
-#endif  // EIGEN_UMFPACKSUPPORT_MODULE_H
+#endif // EIGEN_UMFPACKSUPPORT_MODULE_H

Eigen/Version

@@ -1,14 +0,0 @@
-#ifndef EIGEN_VERSION_H
-#define EIGEN_VERSION_H
-
-// The "WORLD" version will forever remain "3" for the "Eigen3" library.
-#define EIGEN_WORLD_VERSION 3
-// As of Eigen3 5.0.0, we have moved to Semantic Versioning (semver.org).
-#define EIGEN_MAJOR_VERSION 5
-#define EIGEN_MINOR_VERSION 0
-#define EIGEN_PATCH_VERSION 1
-#define EIGEN_PRERELEASE_VERSION ""
-#define EIGEN_BUILD_VERSION ""
-#define EIGEN_VERSION_STRING "5.0.1"
-
-#endif  // EIGEN_VERSION_H

Eigen/src/AccelerateSupport/AccelerateSupport.h

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

Eigen/src/AccelerateSupport/InternalHeaderCheck.h

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

Eigen/src/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

@@ -10,411 +10,382 @@
 #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_isInitialized(false) {}
+    /** \brief Default Constructor with memory preallocation
+      *
+      * Like the default constructor but with preallocation of the internal data
+      * according to the specified problem \a size.
+      * \sa LLT()
+      */
+    LLT(Index size) : m_matrix(size, size),
+                    m_isInitialized(false) {}
 
-  /** \brief Default Constructor with memory preallocation
-   *
-   * Like the default constructor but with preallocation of the internal data
-   * according to the specified problem \a size.
-   * \sa LLT()
-   */
-  explicit LLT(Index size) : m_matrix(size, size), m_isInitialized(false) {}
+    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_isInitialized(false) {
-    compute(matrix.derived());
-  }
+    /** \returns a view of the upper triangular matrix U */
+    inline typename Traits::MatrixU matrixU() const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      return Traits::getU(m_matrix);
+    }
 
-  /** \brief Constructs a LLT factorization from a given matrix
-   *
-   * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when
-   * \c MatrixType is a Eigen::Ref.
-   *
-   * \sa LLT(const EigenBase&)
-   */
-  template <typename InputType>
-  explicit LLT(EigenBase<InputType>& matrix) : m_matrix(matrix.derived()), m_isInitialized(false) {
-    compute(matrix.derived());
-  }
+    /** \returns a view of the 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 const 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:
+    /** \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) {
-  using std::sqrt;
+template<typename MatrixType, typename VectorType>
+static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
+{
   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);
+  int n = mat.cols();
+  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(int 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) {
+      int 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));
-      RealScalar dj = numext::abs2(Ljj);
+    for(int j=0; j<n; ++j)
+    {
+      RealScalar Ljj = real(mat.coeff(j,j));
+      RealScalar dj = abs2(Ljj);
       Scalar wj = temp.coeff(j);
-      RealScalar swj2 = sigma * numext::abs2(wj);
-      RealScalar gamma = dj * beta + swj2;
+      RealScalar swj2 = sigma*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*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) {
-    using std::sqrt;
-
-    eigen_assert(mat.rows() == mat.cols());
+  template<typename MatrixType>
+  static typename MatrixType::Index unblocked(MatrixType& mat)
+  {
+    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 = real(mat.coeff(k,k));
+      if (k>0) x -= A10.squaredNorm();
+      if (x<=RealScalar(0))
+        return k;
+      mat.coeffRef(k,k) = x = sqrt(x);
+      if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint();
+      if (rs>0) A21 *= RealScalar(1)/x;
     }
     return -1;
   }
 
-  template <typename MatrixType>
-  static 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)
+{
+  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);
@@ -424,59 +395,60 @@ 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);
 }
@@ -484,31 +456,33 @@ 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 const 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 const 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) ? Success : NumericalIssue; \
+    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
- *
- * \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

@@ -10,367 +10,299 @@
 #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 EIGEN_STRONG_INLINE constexpr Array() : Base() { EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED }
-#else
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array() = default;
-#endif
-  /** \brief Move constructor */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(Array&&) = default;
-  EIGEN_DEVICE_FUNC Array& operator=(Array&& other) noexcept(std::is_nothrow_move_assignable<Scalar>::value) {
-    Base::operator=(std::move(other));
-    return *this;
-  }
+    /** 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 the fixed number of rows (resp. columns) of \c *this.
-   *
-   *
-   * Example: \include Array_variadic_ctor_cxx11.cpp
-   * Output: \verbinclude Array_variadic_ctor_cxx11.out
-   *
-   * \sa Array(const std::initializer_list<std::initializer_list<Scalar>>&)
-   * \sa Array(const Scalar&), Array(const Scalar&,const Scalar&)
-   */
-  template <typename... ArgTypes>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3,
-                                              const ArgTypes&... args)
-      : Base(a0, a1, a2, a3, args...) {}
-
-  /** \brief Constructs an array and initializes it from the coefficients given as initializer-lists grouped by row.
-   * \cpp11
-   *
-   * In the general case, the constructor takes a list of rows, each row being represented as a list of coefficients:
-   *
-   * Example: \include Array_initializer_list_23_cxx11.cpp
-   * Output: \verbinclude Array_initializer_list_23_cxx11.out
-   *
-   * Each of the inner initializer lists must contain the exact same number of elements, otherwise an assertion is
-   * triggered.
-   *
-   * In the case of a compile-time column 1D array, implicit transposition from a single row is allowed.
-   * Therefore <code> Array<int,Dynamic,1>{{1,2,3,4,5}}</code> is legal and the more verbose syntax
-   * <code>Array<int,Dynamic,1>{{1},{2},{3},{4},{5}}</code> can be avoided:
-   *
-   * Example: \include Array_initializer_list_vector_cxx11.cpp
-   * Output: \verbinclude Array_initializer_list_vector_cxx11.out
-   *
-   * In the case of fixed-sized arrays, the initializer list sizes must exactly match the array sizes,
-   * and implicit transposition is allowed for compile-time 1D arrays only.
-   *
-   * \sa  Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args)
-   */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(
-      const std::initializer_list<std::initializer_list<Scalar>>& list)
-      : Base(list) {}
+    /** 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 explicit Array() : Base()
+    {
+      Base::_check_template_params();
+      EIGEN_INITIALIZE_BY_ZERO_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 EIGEN_STRONG_INLINE constexpr Array(const Array&) = default;
-
- private:
-  struct PrivateType {};
-
- public:
-  /** \sa MatrixBase::operator=(const EigenBase<OtherDerived>&) */
-  template <typename OtherDerived>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(
-      const EigenBase<OtherDerived>& other,
-      std::enable_if_t<internal::is_convertible<typename OtherDerived::Scalar, Scalar>::value, PrivateType> =
-          PrivateType())
-      : Base(other.derived()) {}
-
-  EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return 1; }
-  EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return this->innerSize(); }
-
-#ifdef EIGEN_ARRAY_PLUGIN
-#include EIGEN_ARRAY_PLUGIN
+    // 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_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
+    }
 #endif
 
- private:
-  template <typename MatrixType, typename OtherDerived, bool SwapPointers>
-  friend struct internal::matrix_swap_impl;
+    /** 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_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename T0, typename T1>
+    EIGEN_STRONG_INLINE Array(const T0& x, const T1& y)
+    {
+      Base::_check_template_params();
+      this->template _init2<T0,T1>(x, y);
+    }
+    #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& x, const Scalar& y);
+    #endif
+
+    /** constructs an initialized 3D vector with given coefficients */
+    EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
+      m_storage.data()[0] = x;
+      m_storage.data()[1] = y;
+      m_storage.data()[2] = z;
+    }
+    /** constructs an initialized 4D vector with given coefficients */
+    EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
+    {
+      Base::_check_template_params();
+      EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
+      m_storage.data()[0] = x;
+      m_storage.data()[1] = y;
+      m_storage.data()[2] = z;
+      m_storage.data()[3] = w;
+    }
+
+    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(other.rows(), other.cols());
+      *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

@@ -10,204 +10,219 @@
 #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;
+    using internal::special_scalar_op_base<Derived,typename internal::traits<Derived>::Scalar,
+                typename NumTraits<typename internal::traits<Derived>::Scalar>::Real>::operator*;
 
-  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 typename internal::traits<Derived>::StorageKind StorageKind;
+    typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::traits<Derived>::Scalar Scalar;
+    typedef typename internal::packet_traits<Scalar>::type PacketScalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
 
-  using Base::coeff;
-  using Base::coeffRef;
-  using Base::cols;
-  using Base::const_cast_derived;
-  using Base::derived;
-  using Base::lazyAssign;
-  using Base::rows;
-  using Base::size;
-  using Base::operator-;
-  using Base::operator=;
-  using Base::operator+=;
-  using Base::operator-=;
-  using Base::operator*=;
-  using Base::operator/=;
+    typedef DenseBase<Derived> Base;
+    using Base::RowsAtCompileTime;
+    using Base::ColsAtCompileTime;
+    using Base::SizeAtCompileTime;
+    using Base::MaxRowsAtCompileTime;
+    using Base::MaxColsAtCompileTime;
+    using Base::MaxSizeAtCompileTime;
+    using Base::IsVectorAtCompileTime;
+    using Base::Flags;
+    using Base::CoeffReadCost;
 
-  typedef typename Base::CoeffReturnType CoeffReturnType;
+    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::PlainObject PlainObject;
+    typedef typename Base::CoeffReturnType CoeffReturnType;
 
-  /** \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
+#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 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 ArrayBase<Derived>& array() { return *this; }
-  EIGEN_DEVICE_FUNC 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 MatrixWrapper<Derived> matrix() { return MatrixWrapper<Derived>(derived()); }
-  EIGEN_DEVICE_FUNC const MatrixWrapper<const Derived> matrix() const {
-    return MatrixWrapper<const Derived>(derived());
-  }
-
-  //     template<typename Dest>
-  //     inline void evalTo(Dest& dst) const { dst = matrix(); }
-
- protected:
-  EIGEN_DEFAULT_COPY_CONSTRUCTOR(ArrayBase)
-  EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(ArrayBase)
-
- private:
-  explicit ArrayBase(Index);
-  ArrayBase(Index, Index);
-  template <typename OtherDerived>
-  explicit ArrayBase(const ArrayBase<OtherDerived>&);
-
- protected:
-  // mixing arrays and matrices is not legal
-  template <typename OtherDerived>
-  Derived& operator+=(const MatrixBase<OtherDerived>&) {
-    EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1,
-                        YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);
-    return *this;
-  }
-  // mixing arrays and matrices is not legal
-  template <typename OtherDerived>
-  Derived& operator-=(const MatrixBase<OtherDerived>&) {
-    EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1,
-                        YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);
-    return *this;
-  }
+  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

@@ -10,156 +10,231 @@
 #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 use.
- *
- * \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
-  };
 };
-}  // 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 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.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 row, Index col) const
+    {
+      return m_expression.coeff(row, col);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
-    return m_expression.coeffRef(rowId, colId);
-  }
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      return m_expression.const_cast_derived().coeffRef(row, col);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
+    inline const Scalar& coeffRef(Index row, Index col) const
+    {
+      return m_expression.const_cast_derived().coeffRef(row, col);
+    }
 
-  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 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 row, Index col) const
+    {
+      return m_expression.template packet<LoadMode>(row, col);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
+    }
+
+    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& x)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
+    }
+
+    template<typename Dest>
+    inline void evalTo(Dest& dst) const { dst = m_expression; }
+
+    const typename internal::remove_all<NestedExpressionType>::type& 
+    nestedExpression() const 
+    {
+      return m_expression;
+    }
+
+  protected:
+    NestedExpressionType m_expression;
 };
 
 /** \class MatrixWrapper
- * \ingroup Core_Module
- *
- * \brief Expression of an array as a mathematical vector or matrix
- *
- * This class is the return type of ArrayBase::matrix(), and most of the time
- * this is the only way it is use.
- *
- * \sa MatrixBase::matrix(), class ArrayWrapper
- */
+  * \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
-  };
 };
-}  // 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& matrix) : m_expression(matrix) {}
 
-  EIGEN_DEVICE_FUNC 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.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 row, Index col) const
+    {
+      return m_expression.coeff(row, col);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const {
-    return m_expression.derived().coeffRef(rowId, colId);
-  }
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      return m_expression.const_cast_derived().coeffRef(row, col);
+    }
 
-  EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); }
+    inline const Scalar& coeffRef(Index row, Index col) const
+    {
+      return m_expression.derived().coeffRef(row, col);
+    }
 
-  EIGEN_DEVICE_FUNC 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 row, Index col) const
+    {
+      return m_expression.template packet<LoadMode>(row, col);
+    }
+
+    template<int LoadMode>
+    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
+    }
+
+    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& x)
+    {
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
+    }
+
+    const typename internal::remove_all<NestedExpressionType>::type& 
+    nestedExpression() const 
+    {
+      return m_expression;
+    }
+
+  protected:
+    NestedExpressionType m_expression;
 };
 
-}  // end namespace Eigen
+} // end namespace Eigen
 
-#endif  // EIGEN_ARRAYWRAPPER_H
+#endif // EIGEN_ARRAYWRAPPER_H

Eigen/src/Core/Assign.h

@@ -12,69 +12,572 @@
 #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 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, int 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 &, int) {}
+};
+
+/***********************
+*** 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, int 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 &, int) {}
+};
+
+/***************************************************************************
+* 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 packet_traits<typename Derived1::Scalar> PacketTraits;
+    enum {
+      packetSize = PacketTraits::size,
+      alignable = PacketTraits::AlignedOnScalar,
+      dstAlignment = alignable ? Aligned : int(assign_traits<Derived1,Derived2>::DstIsAligned) ,
+      srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
+    };
+    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) || assign_traits<Derived1,Derived2>::DstIsAligned) ? 0
+                       : internal::first_aligned(&dst.coeffRef(0,0), 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(OtherDerived::Flags) & EvalBeforeAssigningBit) != 0,
+         bool NeedToTranspose = Derived::IsVectorAtCompileTime
+                && OtherDerived::IsVectorAtCompileTime
+                && ((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 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 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 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 EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::operator=(const DenseBase& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const MatrixBase& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
+template<typename Derived>
 template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const DenseBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other) {
-  internal::call_assignment(derived(), other.derived());
-  return derived();
-}
-
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(
-    const ReturnByValue<OtherDerived>& other) {
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const EigenBase<OtherDerived>& other)
+{
   other.derived().evalTo(derived());
   return derived();
 }
 
-}  // end namespace Eigen
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
+{
+  other.evalTo(derived());
+  return derived();
+}
 
-#endif  // EIGEN_ASSIGN_H
+} // end namespace Eigen
+
+#endif // EIGEN_ASSIGN_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.
+#ifdef _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

@@ -11,419 +11,347 @@
 #ifndef EIGEN_BLOCK_H
 #define EIGEN_BLOCK_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-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,
-    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,
-    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,
-    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
-  };
-};
-
-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
-
-template <typename XprType, int BlockRows, int BlockCols, bool InnerPanel, typename StorageKind>
-class BlockImpl;
+namespace Eigen { 
 
 /** \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>;
-
- 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 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 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 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());
-  }
-};
-
-// The generic default implementation for dense block simply 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>
-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 EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index i) : Impl(xpr, i) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol)
-      : Impl(xpr, startRow, startCol) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows,
-                                                  Index blockCols)
-      : Impl(xpr, startRow, startCol, blockRows, blockCols) {}
-};
+  * \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)
+  * \param _DirectAccessStatus \internal used for partial specialization
+  *
+  * 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, bool HasDirectAccess>
+struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel, HasDirectAccess> > : 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,
+    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),
+    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) ? LinearAccessBit : 0,
+    FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
+    FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
+    Flags0 = traits<XprType>::Flags & ( (HereditaryBits & ~RowMajorBit) |
+                                        DirectAccessBit |
+                                        MaskPacketAccessBit |
+                                        MaskAlignedBit),
+    Flags = Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit
+  };
+};
+}
 
-/** \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 Block
+  : public internal::dense_xpr_base<Block<XprType, BlockRows, BlockCols, InnerPanel, HasDirectAccess> >::type
+{
+  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<Block>::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Block)
 
-  // class InnerIterator; // FIXME apparently never used
+    class InnerIterator;
 
-  /** Column or Row constructor
-   */
-  EIGEN_DEVICE_FUNC inline BlockImpl_dense(XprType& xpr, Index i)
+    /** Column or Row constructor
+      */
+    inline Block(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())
+    {
+      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 inline 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 Block(XprType& xpr, Index startRow, Index startCol)
+      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
+        m_blockRows(BlockRows), m_blockCols(BlockCols)
+    {
+      EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
+      eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
+             && startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
+    }
 
-  /** Dynamic-size constructor
-   */
-  EIGEN_DEVICE_FUNC inline 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 Block(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)
+    {
+      eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
+          && (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
+      eigen_assert(startRow >= 0 && blockRows >= 0 && startRow + blockRows <= xpr.rows()
+          && startCol >= 0 && blockCols >= 0 && startCol + blockCols <= xpr.cols());
+    }
 
-  EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); }
-  EIGEN_DEVICE_FUNC inline Index cols() const { return m_blockCols.value(); }
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
 
-  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 Index rows() const { return m_blockRows.value(); }
+    inline Index cols() const { return m_blockCols.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 Scalar& coeffRef(Index row, Index col)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(XprType)
+      return m_xpr.const_cast_derived()
+               .coeffRef(row + m_startRow.value(), col + 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());
-  }
+    inline const Scalar& coeffRef(Index row, Index col) const
+    {
+      return m_xpr.derived()
+               .coeffRef(row + m_startRow.value(), col + 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_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const
+    {
+      return m_xpr.coeff(row + m_startRow.value(), col + m_startCol.value());
+    }
 
-  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 row, Index col) const
+    {
+      return m_xpr.template packet<Unaligned>
+              (row + m_startRow.value(), col + 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 row, Index col, const PacketScalar& x)
+    {
+      m_xpr.const_cast_derived().template writePacket<Unaligned>
+              (row + m_startRow.value(), col + m_startCol.value(), x);
+    }
 
-#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& x)
+    {
+      m_xpr.const_cast_derived().template writePacket<Unaligned>
+         (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
+          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), x);
+    }
 
-  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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 };
+/** \internal */
+template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel>
+class Block<XprType,BlockRows,BlockCols, InnerPanel,true>
+  : public MapBase<Block<XprType, BlockRows, BlockCols, InnerPanel, true> >
+{
+  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<Block> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Block)
 
- public:
-  typedef MapBase<BlockType> Base;
-  EIGEN_DENSE_PUBLIC_INTERFACE(BlockType)
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
 
-  /** 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();
-  }
+    /** Column or Row constructor
+      */
+    inline Block(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)
+    {
+      eigen_assert( (i>=0) && (
+          ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i<xpr.rows())
+        ||((BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) && i<xpr.cols())));
+      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();
-  }
+    /** Fixed-size constructor
+      */
+    inline Block(XprType& xpr, Index startRow, Index startCol)
+      : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol))), m_xpr(xpr)
+    {
+      eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
+             && startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
+      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();
-  }
+    /** Dynamic-size constructor
+      */
+    inline Block(XprType& xpr,
+          Index startRow, Index startCol,
+          Index blockRows, Index blockCols)
+      : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol)), blockRows, blockCols),
+        m_xpr(xpr)
+    {
+      eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
+             && (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
+      eigen_assert(startRow >= 0 && blockRows >= 0 && startRow + blockRows <= xpr.rows()
+             && startCol >= 0 && blockCols >= 0 && startCol + blockCols <= xpr.cols());
+      init();
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t<XprTypeNested>& nestedExpression() const noexcept {
-    return m_xpr;
-  }
+    const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const 
+    { 
+      return m_xpr; 
+    }
+      
+    /** \sa MapBase::innerStride() */
+    inline Index innerStride() const
+    {
+      return internal::traits<Block>::HasSameStorageOrderAsXprType
+             ? m_xpr.innerStride()
+             : m_xpr.outerStride();
+    }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE XprType& nestedExpression() { return m_xpr; }
+    /** \sa MapBase::outerStride() */
+    inline Index outerStride() const
+    {
+      return m_outerStride;
+    }
 
-  /** \sa MapBase::innerStride() */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index innerStride() const noexcept {
-    return internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.innerStride() : m_xpr.outerStride();
-  }
-
-  /** \sa MapBase::outerStride() */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index outerStride() const noexcept {
-    return internal::traits<BlockType>::HasSameStorageOrderAsXprType ? m_xpr.outerStride() : m_xpr.innerStride();
-  }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startRow() const noexcept { return m_startRow.value(); }
-
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 Block(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<Block>::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 Eigen
 
-}  // end namespace Eigen
-
-#endif  // EIGEN_BLOCK_H
+#endif // EIGEN_BLOCK_H

Eigen/src/Core/BooleanRedux.h

@@ -0,0 +1,138 @@
+// 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, 1>
+{
+  static inline bool run(const Derived &mat) { return mat.coeff(0, 0); }
+};
+
+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, 1>
+{
+  static inline bool run(const Derived &mat) { return mat.coeff(0, 0); }
+};
+
+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();
+}
+
+} // 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

@@ -11,139 +11,129 @@
 #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 inline CommaInitializer(XprType& xpr, const Scalar& s)
-      : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1) {
-    eigen_assert(m_xpr.rows() > 0 && m_xpr.cols() > 0 && "Cannot comma-initialize a 0x0 matrix (operator<<)");
-    m_xpr.coeffRef(0, 0) = s;
+  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;
-  }
-
-  /* Copy/Move constructor which transfers ownership. This is crucial in
-   * absence of return value optimization to avoid assertions during destruction. */
-  // FIXME in C++11 mode this could be replaced by a proper RValue constructor
-  EIGEN_DEVICE_FUNC inline CommaInitializer(const CommaInitializer& o)
-      : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) {
-    // Mark original object as finished. In absence of R-value references we need to const_cast:
-    const_cast<CommaInitializer&>(o).m_row = m_xpr.rows();
-    const_cast<CommaInitializer&>(o).m_col = m_xpr.cols();
-    const_cast<CommaInitializer&>(o).m_currentBlockRows = 0;
+  template<typename OtherDerived>
+  inline CommaInitializer(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;
   }
 
   /* 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 (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()
+      && "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
+  *
+  * \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

@@ -1,173 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2016 Rasmus Munk Larsen (rmlarsen@google.com)
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_CONDITIONESTIMATOR_H
-#define EIGEN_CONDITIONESTIMATOR_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Vector, typename RealVector, bool IsComplex>
-struct rcond_compute_sign {
-  static inline Vector run(const Vector& v) {
-    const RealVector v_abs = v.cwiseAbs();
-    return (v_abs.array() == static_cast<typename Vector::RealScalar>(0))
-        .select(Vector::Ones(v.size()), v.cwiseQuotient(v_abs));
-  }
-};
-
-// Partial specialization to avoid elementwise division for real vectors.
-template <typename Vector>
-struct rcond_compute_sign<Vector, Vector, false> {
-  static inline Vector run(const Vector& v) {
-    return (v.array() < static_cast<typename Vector::RealScalar>(0))
-        .select(-Vector::Ones(v.size()), Vector::Ones(v.size()));
-  }
-};
-
-/**
- * \returns an estimate of ||inv(matrix)||_1 given a decomposition of
- * \a matrix that implements .solve() and .adjoint().solve() methods.
- *
- * This function implements Algorithms 4.1 and 5.1 from
- *   http://www.maths.manchester.ac.uk/~higham/narep/narep135.pdf
- * which also forms the basis for the condition number estimators in
- * LAPACK. Since at most 10 calls to the solve method of dec are
- * performed, the total cost is O(dims^2), as opposed to O(dims^3)
- * needed to compute the inverse matrix explicitly.
- *
- * The most common usage is in estimating the condition number
- * ||matrix||_1 * ||inv(matrix)||_1. The first term ||matrix||_1 can be
- * computed directly in O(n^2) operations.
- *
- * Supports the following decompositions: FullPivLU, PartialPivLU, LDLT, and
- * LLT.
- *
- * \sa FullPivLU, PartialPivLU, LDLT, LLT.
- */
-template <typename Decomposition>
-typename Decomposition::RealScalar rcond_invmatrix_L1_norm_estimate(const Decomposition& dec) {
-  typedef typename Decomposition::MatrixType MatrixType;
-  typedef typename Decomposition::Scalar Scalar;
-  typedef typename Decomposition::RealScalar RealScalar;
-  typedef typename internal::plain_col_type<MatrixType>::type Vector;
-  typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVector;
-  const bool is_complex = (NumTraits<Scalar>::IsComplex != 0);
-
-  eigen_assert(dec.rows() == dec.cols());
-  const Index n = dec.rows();
-  if (n == 0) return 0;
-
-    // Disable Index to float conversion warning
-#ifdef __INTEL_COMPILER
-#pragma warning push
-#pragma warning(disable : 2259)
-#endif
-  Vector v = dec.solve(Vector::Ones(n) / Scalar(n));
-#ifdef __INTEL_COMPILER
-#pragma warning pop
-#endif
-
-  // lower_bound is a lower bound on
-  //   ||inv(matrix)||_1  = sup_v ||inv(matrix) v||_1 / ||v||_1
-  // and is the objective maximized by the ("super-") gradient ascent
-  // algorithm below.
-  RealScalar lower_bound = v.template lpNorm<1>();
-  if (n == 1) return lower_bound;
-
-  // Gradient ascent algorithm follows: We know that the optimum is achieved at
-  // one of the simplices v = e_i, so in each iteration we follow a
-  // super-gradient to move towards the optimal one.
-  RealScalar old_lower_bound = lower_bound;
-  Vector sign_vector(n);
-  Vector old_sign_vector;
-  Index v_max_abs_index = -1;
-  Index old_v_max_abs_index = v_max_abs_index;
-  for (int k = 0; k < 4; ++k) {
-    sign_vector = internal::rcond_compute_sign<Vector, RealVector, is_complex>::run(v);
-    if (k > 0 && !is_complex && sign_vector == old_sign_vector) {
-      // Break if the solution stagnated.
-      break;
-    }
-    // v_max_abs_index = argmax |real( inv(matrix)^T * sign_vector )|
-    v = dec.adjoint().solve(sign_vector);
-    v.real().cwiseAbs().maxCoeff(&v_max_abs_index);
-    if (v_max_abs_index == old_v_max_abs_index) {
-      // Break if the solution stagnated.
-      break;
-    }
-    // Move to the new simplex e_j, where j = v_max_abs_index.
-    v = dec.solve(Vector::Unit(n, v_max_abs_index));  // v = inv(matrix) * e_j.
-    lower_bound = v.template lpNorm<1>();
-    if (lower_bound <= old_lower_bound) {
-      // Break if the gradient step did not increase the lower_bound.
-      break;
-    }
-    if (!is_complex) {
-      old_sign_vector = sign_vector;
-    }
-    old_v_max_abs_index = v_max_abs_index;
-    old_lower_bound = lower_bound;
-  }
-  // The following calculates an independent estimate of ||matrix||_1 by
-  // multiplying matrix by a vector with entries of slowly increasing
-  // magnitude and alternating sign:
-  //   v_i = (-1)^{i} (1 + (i / (dim-1))), i = 0,...,dim-1.
-  // This improvement to Hager's algorithm above is due to Higham. It was
-  // added to make the algorithm more robust in certain corner cases where
-  // large elements in the matrix might otherwise escape detection due to
-  // exact cancellation (especially when op and op_adjoint correspond to a
-  // sequence of backsubstitutions and permutations), which could cause
-  // Hager's algorithm to vastly underestimate ||matrix||_1.
-  Scalar alternating_sign(RealScalar(1));
-  for (Index i = 0; i < n; ++i) {
-    // The static_cast is needed when Scalar is a complex and RealScalar implements expression templates
-    v[i] = alternating_sign * static_cast<RealScalar>(RealScalar(1) + (RealScalar(i) / (RealScalar(n - 1))));
-    alternating_sign = -alternating_sign;
-  }
-  v = dec.solve(v);
-  const RealScalar alternate_lower_bound = (2 * v.template lpNorm<1>()) / (3 * RealScalar(n));
-  return numext::maxi(lower_bound, alternate_lower_bound);
-}
-
-/** \brief Reciprocal condition number estimator.
- *
- * Computing a decomposition of a dense matrix takes O(n^3) operations, while
- * this method estimates the condition number quickly and reliably in O(n^2)
- * operations.
- *
- * \returns an estimate of the reciprocal condition number
- * (1 / (||matrix||_1 * ||inv(matrix)||_1)) of matrix, given ||matrix||_1 and
- * its decomposition. Supports the following decompositions: FullPivLU,
- * PartialPivLU, LDLT, and LLT.
- *
- * \sa FullPivLU, PartialPivLU, LDLT, LLT.
- */
-template <typename Decomposition>
-typename Decomposition::RealScalar rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm,
-                                                         const Decomposition& dec) {
-  typedef typename Decomposition::RealScalar RealScalar;
-  eigen_assert(dec.rows() == dec.cols());
-  if (dec.rows() == 0) return NumTraits<RealScalar>::infinity();
-  if (numext::is_exactly_zero(matrix_norm)) return RealScalar(0);
-  if (dec.rows() == 1) return RealScalar(1);
-  const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec);
-  return (numext::is_exactly_zero(inverse_matrix_norm) ? RealScalar(0)
-                                                       : (RealScalar(1) / inverse_matrix_norm) / matrix_norm);
-}
-
-}  // namespace internal
-
-}  // namespace Eigen
-
-#endif

Eigen/src/Core/CoreIterators.h

@@ -1,141 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// This Source Code Form is subject to the terms of the Mozilla
-// Public License v. 2.0. If a copy of the MPL was not distributed
-// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
-
-#ifndef EIGEN_COREITERATORS_H
-#define EIGEN_COREITERATORS_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-/* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
- */
-
-namespace internal {
-
-template <typename XprType, typename EvaluatorKind>
-class inner_iterator_selector;
-
-}
-
-/** \class InnerIterator
- * \brief An InnerIterator allows to loop over the element of any matrix expression.
- *
- * \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is
- * constructed.
- *
- * TODO: add a usage example
- */
-template <typename XprType>
-class InnerIterator {
- protected:
-  typedef internal::inner_iterator_selector<XprType, typename internal::evaluator_traits<XprType>::Kind> IteratorType;
-  typedef internal::evaluator<XprType> EvaluatorType;
-  typedef typename internal::traits<XprType>::Scalar Scalar;
-
- public:
-  /** Construct an iterator over the \a outerId -th row or column of \a xpr */
-  InnerIterator(const XprType &xpr, const Index &outerId) : m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize()) {}
-
-  /// \returns the value of the current coefficient.
-  EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); }
-  /** Increment the iterator \c *this to the next non-zero coefficient.
-   * Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView
-   */
-  EIGEN_STRONG_INLINE InnerIterator &operator++() {
-    m_iter.operator++();
-    return *this;
-  }
-  EIGEN_STRONG_INLINE InnerIterator &operator+=(Index i) {
-    m_iter.operator+=(i);
-    return *this;
-  }
-  EIGEN_STRONG_INLINE InnerIterator operator+(Index i) {
-    InnerIterator result(*this);
-    result += i;
-    return result;
-  }
-
-  /// \returns the column or row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
-  /// \returns the row index of the current coefficient.
-  EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
-  /// \returns the column index of the current coefficient.
-  EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
-  /// \returns \c true if the iterator \c *this still references a valid coefficient.
-  EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
-
- protected:
-  EvaluatorType m_eval;
-  IteratorType m_iter;
-
- private:
-  // If you get here, then you're not using the right InnerIterator type, e.g.:
-  //   SparseMatrix<double,RowMajor> A;
-  //   SparseMatrix<double>::InnerIterator it(A,0);
-  template <typename T>
-  InnerIterator(const EigenBase<T> &, Index outer);
-};
-
-namespace internal {
-
-// Generic inner iterator implementation for dense objects
-template <typename XprType>
-class inner_iterator_selector<XprType, IndexBased> {
- protected:
-  typedef evaluator<XprType> EvaluatorType;
-  typedef typename traits<XprType>::Scalar Scalar;
-  enum { IsRowMajor = (XprType::Flags & RowMajorBit) == RowMajorBit };
-
- public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize)
-      : m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize) {}
-
-  EIGEN_STRONG_INLINE Scalar value() const {
-    return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner) : m_eval.coeff(m_inner, m_outer);
-  }
-
-  EIGEN_STRONG_INLINE inner_iterator_selector &operator++() {
-    m_inner++;
-    return *this;
-  }
-
-  EIGEN_STRONG_INLINE Index index() const { return m_inner; }
-  inline Index row() const { return IsRowMajor ? m_outer : index(); }
-  inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-  EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner >= 0; }
-
- protected:
-  const EvaluatorType &m_eval;
-  Index m_inner;
-  const Index m_outer;
-  const Index m_end;
-};
-
-// For iterator-based evaluator, inner-iterator is already implemented as
-// evaluator<>::InnerIterator
-template <typename XprType>
-class inner_iterator_selector<XprType, IteratorBased> : public evaluator<XprType>::InnerIterator {
- protected:
-  typedef typename evaluator<XprType>::InnerIterator Base;
-  typedef evaluator<XprType> EvaluatorType;
-
- public:
-  EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId,
-                                              const Index & /*innerSize*/)
-      : Base(eval, outerId) {}
-};
-
-}  // end namespace internal
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_COREITERATORS_H

Eigen/src/Core/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 +50,180 @@ 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),
+    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + 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_allows_mixing_real_and_complex<BINOP>::ret \
+                        ? int(internal::is_same<typename NumTraits<LHS>::Real, typename NumTraits<RHS>::Real>::value) \
+                        : 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& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
+      : m_lhs(lhs), m_rhs(rhs), 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(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
+    }
 
-#if EIGEN_COMP_MSVC
-  // Required for Visual Studio or the Copy constructor will probably not get inlined!
-  EIGEN_STRONG_INLINE CwiseBinaryOp(const CwiseBinaryOp<BinaryOp, LhsType, RhsType>&) = default;
-#endif
+    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 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 EIGEN_STRONG_INLINE constexpr Index rows() const noexcept {
-    // return the fixed size type if available to enable compile time optimizations
-    return internal::traits<internal::remove_all_t<LhsNested>>::RowsAtCompileTime == Dynamic ? m_rhs.rows()
-                                                                                             : m_lhs.rows();
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept {
-    // return the fixed size type if available to enable compile time optimizations
-    return internal::traits<internal::remove_all_t<LhsNested>>::ColsAtCompileTime == Dynamic ? m_rhs.cols()
-                                                                                             : m_lhs.cols();
-  }
-
-  /** \returns the left hand side nested expression */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const LhsNested_& lhs() const { return m_lhs; }
-  /** \returns the right hand side nested expression */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const RhsNested_& rhs() const { return m_rhs; }
-  /** \returns the functor representing the binary operation */
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const BinaryOp& functor() const { return m_functor; }
-
- protected:
-  LhsNested m_lhs;
-  RhsNested m_rhs;
-  const BinaryOp m_functor;
+  protected:
+    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 row, Index col) const
+    {
+      return derived().functor()(derived().lhs().coeff(row, col),
+                                 derived().rhs().coeff(row, col));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    {
+      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(row, col),
+                                          derived().rhs().template packet<LoadMode>(row, col));
+    }
+
+    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_STRONG_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_STRONG_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 EIGEN_STRONG_INLINE Index rows() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
-        internal::traits<internal::remove_all_t<Arg2Nested>>::RowsAtCompileTime == Dynamic)
-      return m_arg3.rows();
-    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::RowsAtCompileTime == Dynamic &&
-             internal::traits<internal::remove_all_t<Arg3Nested>>::RowsAtCompileTime == Dynamic)
-      return m_arg2.rows();
-    else
-      return m_arg1.rows();
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const {
-    // return the fixed size type if available to enable compile time
-    // optimizations
-    if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
-        internal::traits<internal::remove_all_t<Arg2Nested>>::ColsAtCompileTime == Dynamic)
-      return m_arg3.cols();
-    else if (internal::traits<internal::remove_all_t<Arg1Nested>>::ColsAtCompileTime == Dynamic &&
-             internal::traits<internal::remove_all_t<Arg3Nested>>::ColsAtCompileTime == Dynamic)
-      return m_arg2.cols();
-    else
-      return m_arg1.cols();
-  }
-
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC const Arg1Nested_& arg1() const { return m_arg1; }
-  /** \returns the first argument nested expression */
-  EIGEN_DEVICE_FUNC const Arg2Nested_& arg2() const { return m_arg2; }
-  /** \returns the third argument nested expression */
-  EIGEN_DEVICE_FUNC const Arg3Nested_& arg3() const { return m_arg3; }
-  /** \returns the functor representing the ternary operation */
-  EIGEN_DEVICE_FUNC const TernaryOp& functor() const { return m_functor; }
-
- protected:
-  Arg1Nested m_arg1;
-  Arg2Nested m_arg2;
-  Arg3Nested m_arg3;
-  const TernaryOp m_functor;
-};
-
-// Generic API dispatcher
-template <typename TernaryOp, typename Arg1, typename Arg2, typename Arg3, typename StorageKind>
-class CwiseTernaryOpImpl : public internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type {
- public:
-  typedef typename internal::generic_xpr_base<CwiseTernaryOp<TernaryOp, Arg1, Arg2, Arg3>>::type Base;
-};
-
-}  // end namespace Eigen
-
-#endif  // EIGEN_CWISE_TERNARY_OP_H

Eigen/src/Core/CwiseUnaryOp.h

@@ -1,7 +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
@@ -11,81 +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 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 = _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 EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_xpr.rows(); }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_xpr.cols(); }
+    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 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 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 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 row, Index col) const
+    {
+      return derived().functor()(derived().nestedExpression().coeff(row, col));
+    }
+
+    template<int LoadMode>
+    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    {
+      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(row, col));
+    }
+
+    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

@@ -10,158 +10,126 @@
 #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 = 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
   };
 };
+}
 
-// 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 : internal::no_assignment_operator,
+  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 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 EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_matrix.rows(); }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_matrix.cols(); }
+    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 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 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 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)
+
+    inline Index innerStride() const
+    {
+      return derived().nestedExpression().innerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
+    }
+
+    inline Index outerStride() const
+    {
+      return derived().nestedExpression().outerStride();
+    }
+
+    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
@@ -13,561 +13,291 @@
 #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
-
-#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
+struct constructor_without_unaligned_array_assert {};
 
 /** \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.
- */
-
+  * 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 EIGEN_STRONG_INLINE 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
+          int Alignment = (MatrixOrArrayOptions&DontAlign) ? 0
+                        : (((Size*sizeof(T))%16)==0) ? 16
+                        : 0 >
+struct plain_array
+{
+  T array[Size];
+  plain_array() {}
+  plain_array(constructor_without_unaligned_array_assert) {}
 };
 
+#ifdef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask)
+#else
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
+    eigen_assert((reinterpret_cast<size_t>(array) & sizemask) == 0 \
+              && "this assertion is explained here: " \
+              "http://eigen.tuxfamily.org/dox-devel/TopicUnalignedArrayAssert.html" \
+              " **** READ THIS WEB PAGE !!! ****");
+#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 EIGEN_STRONG_INLINE constexpr plain_array() = default;
-#else
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() { EIGEN_MAKE_STACK_ALLOCATION_ASSERT(Size * sizeof(T)) }
-#endif
+struct plain_array<T, Size, MatrixOrArrayOptions, 16>
+{
+  EIGEN_USER_ALIGN16 T array[Size];
+  plain_array() { EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf) }
+  plain_array(constructor_without_unaligned_array_assert) {}
 };
 
-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 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 Size, int Rows, int Cols, int Options>
-class DenseStorage_impl {
-  plain_array<T, Size, Options> m_data;
-
- public:
-#ifndef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-#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);
-  }
-#endif
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/,
-                                                                          Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) {
-    m_rows = rows;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) {
-    m_rows = rows;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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;
-
- public:
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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);
-  }
-  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 EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) {
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) {
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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);
-  }
-  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 EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index cols) {
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index cols) {
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl&) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/,
-                                                                          Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index rows, Index /*cols*/)
-      : m_rows(rows) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
-    numext::swap(m_rows, other.m_rows);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) {
-    m_rows = rows;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) {
-    m_rows = rows;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; }
-};
-template <typename T, int Rows, int Options>
-class DenseStorage_impl<T, 0, Rows, Dynamic, Options> {
-  Index m_cols = 0;
-
- public:
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index cols)
-      : m_cols(cols) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
-    numext::swap(m_cols, other.m_cols);
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) {
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) {
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index rows, Index cols)
-      : m_rows(rows), m_cols(cols) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept {
-    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_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index cols) {
-    m_rows = rows;
-    m_cols = cols;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
-    this->swap(other);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
-    this->swap(other);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept {
-    this->swap(other);
-    return *this;
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(const DenseStorage&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(Index size, Index rows, Index cols)
-      : Base(size, rows, cols) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage(DenseStorage&&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage() = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(const DenseStorage&) = default;
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(Index size, Index rows, Index cols)
-      : Base(size, rows, cols) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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 EIGEN_STRONG_INLINE constexpr DenseStorage(DenseStorage&& other)
-      : DenseStorage(static_cast<const DenseStorage&>(other)) {}
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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:
+    inline explicit DenseStorage() {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()) {}
+    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
+    static inline DenseIndex rows(void) {return _Rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
 };
 
-}  // end namespace Eigen
+// null matrix
+template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0, _Rows, _Cols, _Options>
+{
+  public:
+    inline explicit DenseStorage() {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
+    inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void swap(DenseStorage& ) {}
+    static inline DenseIndex rows(void) {return _Rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
+    inline const T *data() const { return 0; }
+    inline T *data() { return 0; }
+};
 
-#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:
+    inline explicit DenseStorage() : m_rows(0), m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
+    inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex cols) : m_rows(rows), m_cols(cols) {}
+    inline void swap(DenseStorage& other)
+    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
+    inline void resize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
+};
+
+// dynamic-size matrix with fixed-size storage and fixed width
+template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Size, Dynamic, _Cols, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_rows;
+  public:
+    inline explicit DenseStorage() : m_rows(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
+    inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex) : m_rows(rows) {}
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return _Cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
+    inline void resize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
+};
+
+// dynamic-size matrix with fixed-size storage and fixed height
+template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Size, _Rows, Dynamic, _Options>
+{
+    internal::plain_array<T,Size,_Options> m_data;
+    DenseIndex m_cols;
+  public:
+    inline explicit DenseStorage() : m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+      : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
+    inline DenseStorage(DenseIndex, DenseIndex, DenseIndex cols) : m_cols(cols) {}
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    inline DenseIndex rows(void) const {return _Rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
+    inline void resize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
+    inline const T *data() const { return m_data.array; }
+    inline T *data() { return m_data.array; }
+};
+
+// purely dynamic matrix.
+template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynamic, _Options>
+{
+    T *m_data;
+    DenseIndex m_rows;
+    DenseIndex m_cols;
+  public:
+    inline explicit DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert)
+       : m_data(0), m_rows(0), m_cols(0) {}
+    inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex cols)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols) 
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
+    inline void swap(DenseStorage& other)
+    { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
+    inline DenseIndex rows(void) const {return m_rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex cols)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
+      m_rows = rows;
+      m_cols = cols;
+    }
+    void resize(DenseIndex size, DenseIndex rows, DenseIndex cols)
+    {
+      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 = rows;
+      m_cols = cols;
+    }
+    inline const T *data() const { return m_data; }
+    inline T *data() { return m_data; }
+};
+
+// matrix with dynamic width and fixed height (so that matrix has dynamic size).
+template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Rows, Dynamic, _Options>
+{
+    T *m_data;
+    DenseIndex m_cols;
+  public:
+    inline explicit DenseStorage() : m_data(0), m_cols(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
+    inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
+    static inline DenseIndex rows(void) {return _Rows;}
+    inline DenseIndex cols(void) const {return m_cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
+      m_cols = cols;
+    }
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex cols)
+    {
+      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 = cols;
+    }
+    inline const T *data() const { return m_data; }
+    inline T *data() { return m_data; }
+};
+
+// matrix with dynamic height and fixed width (so that matrix has dynamic size).
+template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dynamic, _Cols, _Options>
+{
+    T *m_data;
+    DenseIndex m_rows;
+  public:
+    inline explicit DenseStorage() : m_data(0), m_rows(0) {}
+    inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
+    inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
+    { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
+    inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
+    inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
+    inline DenseIndex rows(void) const {return m_rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
+    inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex)
+    {
+      m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
+      m_rows = rows;
+    }
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex rows, 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 = rows;
+    }
+    inline const T *data() const { return m_data; }
+    inline T *data() { return m_data; }
+};
+
+} // 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 EIGEN_STRONG_INLINE 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

@@ -11,209 +11,226 @@
 #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) == Dynamic || 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 == Dynamic ? 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 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());
-  }
+    typedef typename internal::dense_xpr_base<Diagonal>::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
 
-  EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
+    inline Diagonal(MatrixType& matrix, Index index = DiagIndex) : m_matrix(matrix), m_index(index) {}
 
-  EIGEN_DEVICE_FUNC 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)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min)(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 &(m_matrix.coeffRef(rowOffset(), colOffset())); }
-  EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(m_matrix.coeffRef(rowOffset(), colOffset())); }
+    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 index)
+    {
+      EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
+      return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index idx) const {
-    return m_matrix.coeff(idx + rowOffset(), idx + colOffset());
-  }
+    inline const Scalar& coeffRef(Index index) const
+    {
+      return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC inline const internal::remove_all_t<typename MatrixType::Nested>& nestedExpression() const {
-    return m_matrix;
-  }
+    inline CoeffReturnType coeff(Index index) const
+    {
+      return m_matrix.coeff(index+rowOffset(), index+colOffset());
+    }
 
-  EIGEN_DEVICE_FUNC 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 EIGEN_STRONG_INLINE constexpr Index absDiagIndex() const noexcept {
-    return m_index.value() > 0 ? m_index.value() : -m_index.value();
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rowOffset() const noexcept {
-    return m_index.value() > 0 ? 0 : -m_index.value();
-  }
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE 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_dynamic<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 inline 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 inline const typename MatrixBase<Derived>::ConstDiagonalReturnType MatrixBase<Derived>::diagonal()
-    const {
+template<typename Derived>
+inline const 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 inline 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>::template DiagonalIndexReturnType<Dynamic>::Type
+MatrixBase<Derived>::diagonal(Index index)
+{
+  return typename DiagonalIndexReturnType<Dynamic>::Type(derived(), index);
 }
 
 /** This is the const version of diagonal(Index). */
-template <typename Derived>
-EIGEN_DEVICE_FUNC inline 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>::template ConstDiagonalIndexReturnType<Dynamic>::Type
+MatrixBase<Derived>::diagonal(Index index) const
+{
+  return typename ConstDiagonalIndexReturnType<Dynamic>::Type(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 inline 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 inline 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

@@ -11,410 +11,285 @@
 #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 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>
+    void addTo(MatrixBase<DenseDerived> &other) const
+    { other.diagonal() += diagonal(); }
+    template<typename DenseDerived>
+    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 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);
-  }
+    template<typename MatrixDerived>
+    const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
+    operator*(const MatrixBase<MatrixDerived> &matrix) const;
 
-  /** \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();
+    }
+    
+    #ifdef EIGEN2_SUPPORT
+    template<typename OtherDerived>
+    bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
+    {
+      return diagonal().isApprox(other.diagonal(), precision);
+    }
+    template<typename OtherDerived>
+    bool isApprox(const MatrixBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const
+    {
+      return toDenseMatrix().isApprox(other, precision);
+    }
+    #endif
 };
 
+template<typename Derived>
+template<typename DenseDerived>
+void DiagonalBase<Derived>::evalTo(MatrixBase<DenseDerived> &other) const
+{
+  other.setZero();
+  other.diagonal() = diagonal();
+}
+#endif
+
 /** \class DiagonalMatrix
- * \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 inline const DiagonalVectorType& diagonal() const { return m_diagonal; }
-  /** \returns a reference to the stored vector of diagonal coefficients. */
-  EIGEN_DEVICE_FUNC inline DiagonalVectorType& diagonal() { return m_diagonal; }
+    DiagonalVectorType m_diagonal;
 
-  /** Default constructor without initialization */
-  EIGEN_DEVICE_FUNC inline DiagonalMatrix() {}
+  public:
 
-  /** Constructs a diagonal matrix with given dimension  */
-  EIGEN_DEVICE_FUNC 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 inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x, y) {}
+    /** Default constructor without initialization */
+    inline DiagonalMatrix() {}
 
-  /** 3D constructor. */
-  EIGEN_DEVICE_FUNC 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 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 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 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 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 explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
+    /** Constructor from expression of diagonal coefficients to wrap. */
+    inline DiagonalWrapper(DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
 
-  /** \returns a const reference to the wrapped expression of diagonal coefficients. */
-  EIGEN_DEVICE_FUNC 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 inline 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(RealScalar prec) const
+{
+  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 = internal::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;
 }
 
-namespace internal {
+} // end namespace Eigen
 
-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 +11,113 @@
 #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,
+    _PacketOnDiag = !((int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft)
+                    ||(int(_StorageOrder) == ColMajor && 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::Flags)&PacketAccessBit))),
+    _Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && ((!_PacketOnDiag) || (bool(int(DiagonalType::Flags)&PacketAccessBit))),
+
+    Flags = (HereditaryBits & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),
+    CoeffReadCost = NumTraits<Scalar>::MulCost + MatrixType::CoeffReadCost + 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()));
+    }
+
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+
+    const Scalar coeff(Index row, Index col) const
+    {
+      return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col);
+    }
+
+    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());
+    }
+
+  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)) ? 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> &diagonal) const
+{
+  return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), diagonal.derived());
+}
+
+/** \returns the diagonal matrix product of \c *this by the matrix \a matrix.
+  */
+template<typename DiagonalDerived>
+template<typename MatrixDerived>
+inline const DiagonalProduct<MatrixDerived, DiagonalDerived, OnTheLeft>
+DiagonalBase<DiagonalDerived>::operator*(const MatrixBase<MatrixDerived> &matrix) const
+{
+  return DiagonalProduct<MatrixDerived, DiagonalDerived, OnTheLeft>(matrix.derived(), derived());
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_DIAGONALPRODUCT_H

Eigen/src/Core/Dot.h

@@ -10,259 +10,252 @@
 #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 EIGEN_STRONG_INLINE Real run(const Derived& a) {
-    Scalar result = a.unaryExpr(squared_norm_functor<Scalar>()).sum();
-    return numext::real(result) + numext::imag(result);
+// 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 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 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>
+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 equals to the dot product of \c *this with itself.
- *
- * \sa dot(), norm(), lpNorm()
- */
-template <typename Derived>
-EIGEN_DEVICE_FUNC 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 internal::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 equals 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
+{
+  return internal::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)
+  {
+    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());
-  return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
+  *          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, RealScalar prec) const
+{
+  typename internal::nested<Derived,2>::type nested(derived());
+  typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
+  return internal::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(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

Eigen/src/Core/EigenBase.h

@@ -11,139 +11,150 @@
 #ifndef EIGEN_EIGENBASE_H
 #define EIGEN_EIGENBASE_H
 
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
 namespace Eigen {
 
-/** \class EigenBase
- * \ingroup Core_Module
- *
- * Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
- *
- * In other words, an EigenBase object is an object that can be copied into a MatrixBase.
- *
- * Besides MatrixBase-derived classes, this also includes special matrix classes such as diagonal matrices, etc.
- *
- * Notice that this class is trivial, it is only used to disambiguate overloaded functions.
- *
- * \sa \blank \ref TopicClassHierarchy
- */
-template <typename Derived>
-struct EigenBase {
-  //   typedef typename internal::plain_matrix_type<Derived>::type PlainObject;
+/** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
+  *
+  * In other words, an EigenBase object is an object that can be copied into a MatrixBase.
+  *
+  * Besides MatrixBase-derived classes, this also includes special matrix classes such as diagonal matrices, etc.
+  *
+  * Notice that this class is trivial, it is only used to disambiguate overloaded functions.
+  *
+  * \sa \ref TopicClassHierarchy
+  */
+template<typename Derived> struct EigenBase
+{
+//   typedef typename internal::plain_matrix_type<Derived>::type PlainObject;
 
-  /** \brief The interface type of indices
-   * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE.
-   * \sa StorageIndex, \ref TopicPreprocessorDirectives.
-   * DEPRECATED: Since Eigen 3.3, its usage is deprecated. Use Eigen::Index instead.
-   * Deprecation is not marked with a doxygen comment because there are too many existing usages to add the deprecation
-   * attribute.
-   */
-  typedef Eigen::Index Index;
-
-  // FIXME is it needed?
   typedef typename internal::traits<Derived>::StorageKind StorageKind;
+  typedef typename internal::traits<Derived>::Index Index;
 
   /** \returns a reference to the derived object */
-  EIGEN_DEVICE_FUNC constexpr Derived& derived() { return *static_cast<Derived*>(this); }
+  Derived& derived() { return *static_cast<Derived*>(this); }
   /** \returns a const reference to the derived object */
-  EIGEN_DEVICE_FUNC constexpr const Derived& derived() const { return *static_cast<const Derived*>(this); }
+  const Derived& derived() const { return *static_cast<const Derived*>(this); }
 
-  EIGEN_DEVICE_FUNC inline constexpr Derived& const_cast_derived() const {
-    return *static_cast<Derived*>(const_cast<EigenBase*>(this));
-  }
-  EIGEN_DEVICE_FUNC inline const Derived& const_derived() const { return *static_cast<const Derived*>(this); }
+  inline Derived& const_cast_derived() const
+  { return *static_cast<Derived*>(const_cast<EigenBase*>(this)); }
+  inline const Derived& const_derived() const
+  { return *static_cast<const Derived*>(this); }
 
   /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
-  EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return derived().rows(); }
+  inline Index rows() const { return derived().rows(); }
   /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
-  EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return derived().cols(); }
+  inline Index cols() const { return derived().cols(); }
   /** \returns the number of coefficients, which is rows()*cols().
-   * \sa rows(), cols(), SizeAtCompileTime. */
-  EIGEN_DEVICE_FUNC constexpr Index size() const noexcept { return rows() * cols(); }
+    * \sa rows(), cols(), SizeAtCompileTime. */
+  inline Index size() const { return rows() * cols(); }
 
   /** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC inline void evalTo(Dest& dst) const {
-    derived().evalTo(dst);
-  }
+  template<typename Dest> inline void evalTo(Dest& dst) const
+  { derived().evalTo(dst); }
 
   /** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC inline void addTo(Dest& dst) const {
+  template<typename Dest> inline void addTo(Dest& dst) const
+  {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
-    typename Dest::PlainObject res(rows(), cols());
+    typename Dest::PlainObject res(rows(),cols());
     evalTo(res);
     dst += res;
   }
 
   /** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC inline void subTo(Dest& dst) const {
+  template<typename Dest> inline void subTo(Dest& dst) const
+  {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
-    typename Dest::PlainObject res(rows(), cols());
+    typename Dest::PlainObject res(rows(),cols());
     evalTo(res);
     dst -= res;
   }
 
   /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC inline void applyThisOnTheRight(Dest& dst) const {
+  template<typename Dest> inline void applyThisOnTheRight(Dest& dst) const
+  {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
     dst = dst * this->derived();
   }
 
   /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */
-  template <typename Dest>
-  EIGEN_DEVICE_FUNC inline void applyThisOnTheLeft(Dest& dst) const {
+  template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
+  {
     // This is the default implementation,
     // derived class can reimplement it in a more optimized way.
     dst = this->derived() * dst;
   }
 
-  template <typename Device>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper<Derived, Device> device(Device& device);
-  template <typename Device>
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper<const Derived, Device> device(Device& device) const;
 };
 
 /***************************************************************************
- * Implementation of matrix base methods
- ***************************************************************************/
+* Implementation of matrix base methods
+***************************************************************************/
 
 /** \brief Copies the generic expression \a other into *this.
- *
- * \details The expression must provide a (templated) evalTo(Derived& dst) const
- * function which does the actual job. In practice, this allows any user to write
- * its own special matrix without having to modify MatrixBase
- *
- * \returns a reference to *this.
- */
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived>& other) {
-  call_assignment(derived(), other.derived());
+  *
+  * \details The expression must provide a (templated) evalTo(Derived& dst) const
+  * function which does the actual job. In practice, this allows any user to write
+  * its own special matrix without having to modify MatrixBase
+  *
+  * \returns a reference to *this.
+  */
+template<typename Derived>
+template<typename OtherDerived>
+Derived& DenseBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
+{
+  other.derived().evalTo(derived());
   return derived();
 }
 
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived>& other) {
-  call_assignment(derived(), other.derived(), internal::add_assign_op<Scalar, typename OtherDerived::Scalar>());
+template<typename Derived>
+template<typename OtherDerived>
+Derived& DenseBase<Derived>::operator+=(const EigenBase<OtherDerived> &other)
+{
+  other.derived().addTo(derived());
   return derived();
 }
 
-template <typename Derived>
-template <typename OtherDerived>
-EIGEN_DEVICE_FUNC Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived>& other) {
-  call_assignment(derived(), other.derived(), internal::sub_assign_op<Scalar, typename OtherDerived::Scalar>());
+template<typename Derived>
+template<typename OtherDerived>
+Derived& DenseBase<Derived>::operator-=(const EigenBase<OtherDerived> &other)
+{
+  other.derived().subTo(derived());
   return derived();
 }
 
-}  // end namespace Eigen
+/** replaces \c *this by \c *this * \a other.
+  *
+  * \returns a reference to \c *this
+  */
+template<typename Derived>
+template<typename OtherDerived>
+inline Derived&
+MatrixBase<Derived>::operator*=(const EigenBase<OtherDerived> &other)
+{
+  other.derived().applyThisOnTheRight(derived());
+  return derived();
+}
 
-#endif  // EIGEN_EIGENBASE_H
+/** replaces \c *this by \c *this * \a other. It is equivalent to MatrixBase::operator*=() */
+template<typename Derived>
+template<typename OtherDerived>
+inline void MatrixBase<Derived>::applyOnTheRight(const EigenBase<OtherDerived> &other)
+{
+  other.derived().applyThisOnTheRight(derived());
+}
+
+/** replaces \c *this by \c *this * \a other. */
+template<typename Derived>
+template<typename OtherDerived>
+inline void MatrixBase<Derived>::applyOnTheLeft(const EigenBase<OtherDerived> &other)
+{
+  other.derived().applyThisOnTheLeft(derived());
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_EIGENBASE_H

Eigen/src/Core/Fill.h

@@ -1,138 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2024 Charles 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_FILL_H
-#define EIGEN_FILL_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Xpr>
-struct eigen_fill_helper : std::false_type {};
-
-template <typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
-struct eigen_fill_helper<Matrix<Scalar, Rows, Cols, Options, MaxRows, MaxCols>> : std::true_type {};
-
-template <typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
-struct eigen_fill_helper<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols>> : std::true_type {};
-
-template <typename Xpr, int BlockRows, int BlockCols>
-struct eigen_fill_helper<Block<Xpr, BlockRows, BlockCols, /*InnerPanel*/ true>> : eigen_fill_helper<Xpr> {};
-
-template <typename Xpr, int BlockRows, int BlockCols>
-struct eigen_fill_helper<Block<Xpr, BlockRows, BlockCols, /*InnerPanel*/ false>>
-    : std::integral_constant<bool, eigen_fill_helper<Xpr>::value &&
-                                       (Xpr::IsRowMajor ? (BlockRows == 1) : (BlockCols == 1))> {};
-
-template <typename Xpr, int Options>
-struct eigen_fill_helper<Map<Xpr, Options, Stride<0, 0>>> : eigen_fill_helper<Xpr> {};
-
-template <typename Xpr, int Options, int OuterStride_>
-struct eigen_fill_helper<Map<Xpr, Options, Stride<OuterStride_, 0>>>
-    : std::integral_constant<bool, eigen_fill_helper<Xpr>::value &&
-                                       enum_eq_not_dynamic(OuterStride_, Xpr::InnerSizeAtCompileTime)> {};
-
-template <typename Xpr, int Options, int OuterStride_>
-struct eigen_fill_helper<Map<Xpr, Options, Stride<OuterStride_, 1>>>
-    : eigen_fill_helper<Map<Xpr, Options, Stride<OuterStride_, 0>>> {};
-
-template <typename Xpr, int Options, int InnerStride_>
-struct eigen_fill_helper<Map<Xpr, Options, InnerStride<InnerStride_>>>
-    : eigen_fill_helper<Map<Xpr, Options, Stride<0, InnerStride_>>> {};
-
-template <typename Xpr, int Options, int OuterStride_>
-struct eigen_fill_helper<Map<Xpr, Options, OuterStride<OuterStride_>>>
-    : eigen_fill_helper<Map<Xpr, Options, Stride<OuterStride_, 0>>> {};
-
-template <typename Xpr>
-struct eigen_fill_impl<Xpr, /*use_fill*/ false> {
-  using Scalar = typename Xpr::Scalar;
-  using Func = scalar_constant_op<Scalar>;
-  using PlainObject = typename Xpr::PlainObject;
-  using Constant = typename PlainObject::ConstantReturnType;
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst, const Scalar& val) {
-    const Constant src(dst.rows(), dst.cols(), val);
-    run(dst, src);
-  }
-  template <typename SrcXpr>
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst, const SrcXpr& src) {
-    call_dense_assignment_loop(dst, src, assign_op<Scalar, Scalar>());
-  }
-};
-
-#if EIGEN_COMP_MSVC || defined(EIGEN_GPU_COMPILE_PHASE)
-template <typename Xpr>
-struct eigen_fill_impl<Xpr, /*use_fill*/ true> : eigen_fill_impl<Xpr, /*use_fill*/ false> {};
-#else
-template <typename Xpr>
-struct eigen_fill_impl<Xpr, /*use_fill*/ true> {
-  using Scalar = typename Xpr::Scalar;
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst, const Scalar& val) {
-    const Scalar val_copy = val;
-    using std::fill_n;
-    fill_n(dst.data(), dst.size(), val_copy);
-  }
-  template <typename SrcXpr>
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst, const SrcXpr& src) {
-    resize_if_allowed(dst, src, assign_op<Scalar, Scalar>());
-    const Scalar& val = src.functor()();
-    run(dst, val);
-  }
-};
-#endif
-
-template <typename Xpr>
-struct eigen_memset_helper {
-  static constexpr bool value =
-      std::is_trivially_copyable<typename Xpr::Scalar>::value && eigen_fill_helper<Xpr>::value;
-};
-
-template <typename Xpr>
-struct eigen_zero_impl<Xpr, /*use_memset*/ false> {
-  using Scalar = typename Xpr::Scalar;
-  using PlainObject = typename Xpr::PlainObject;
-  using Zero = typename PlainObject::ZeroReturnType;
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst) {
-    const Zero src(dst.rows(), dst.cols());
-    run(dst, src);
-  }
-  template <typename SrcXpr>
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst, const SrcXpr& src) {
-    call_dense_assignment_loop(dst, src, assign_op<Scalar, Scalar>());
-  }
-};
-
-template <typename Xpr>
-struct eigen_zero_impl<Xpr, /*use_memset*/ true> {
-  using Scalar = typename Xpr::Scalar;
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst) {
-    const std::ptrdiff_t num_bytes = dst.size() * static_cast<std::ptrdiff_t>(sizeof(Scalar));
-    if (num_bytes <= 0) return;
-    void* dst_ptr = static_cast<void*>(dst.data());
-#ifndef EIGEN_NO_DEBUG
-    eigen_assert((dst_ptr != nullptr) && "null pointer dereference error!");
-#endif
-    EIGEN_USING_STD(memset);
-    memset(dst_ptr, 0, static_cast<std::size_t>(num_bytes));
-  }
-  template <typename SrcXpr>
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst, const SrcXpr& src) {
-    resize_if_allowed(dst, src, assign_op<Scalar, Scalar>());
-    run(dst);
-  }
-};
-
-}  // namespace internal
-}  // namespace Eigen
-
-#endif  // EIGEN_FILL_H

Eigen/src/Core/FindCoeff.h

@@ -1,464 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2025 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_FIND_COEFF_H
-#define EIGEN_FIND_COEFF_H
-
-// IWYU pragma: private
-#include "./InternalHeaderCheck.h"
-
-namespace Eigen {
-
-namespace internal {
-
-template <typename Scalar, int NaNPropagation, bool IsInteger = NumTraits<Scalar>::IsInteger>
-struct max_coeff_functor {
-  EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const {
-    return candidate > incumbent;
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const {
-    return pcmp_lt(incumbent, candidate);
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const {
-    return predux_max(a);
-  }
-};
-
-template <typename Scalar>
-struct max_coeff_functor<Scalar, PropagateNaN, false> {
-  EIGEN_DEVICE_FUNC inline Scalar compareCoeff(const Scalar& incumbent, const Scalar& candidate) {
-    return (candidate > incumbent) || ((candidate != candidate) && (incumbent == incumbent));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) {
-    return pandnot(pcmp_lt_or_nan(incumbent, candidate), pisnan(incumbent));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const {
-    return predux_max<PropagateNaN>(a);
-  }
-};
-
-template <typename Scalar>
-struct max_coeff_functor<Scalar, PropagateNumbers, false> {
-  EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const {
-    return (candidate > incumbent) || ((candidate == candidate) && (incumbent != incumbent));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const {
-    return pandnot(pcmp_lt_or_nan(incumbent, candidate), pisnan(candidate));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const {
-    return predux_max<PropagateNumbers>(a);
-  }
-};
-
-template <typename Scalar, int NaNPropagation, bool IsInteger = NumTraits<Scalar>::IsInteger>
-struct min_coeff_functor {
-  EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const {
-    return candidate < incumbent;
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const {
-    return pcmp_lt(candidate, incumbent);
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const {
-    return predux_min(a);
-  }
-};
-
-template <typename Scalar>
-struct min_coeff_functor<Scalar, PropagateNaN, false> {
-  EIGEN_DEVICE_FUNC inline Scalar compareCoeff(const Scalar& incumbent, const Scalar& candidate) {
-    return (candidate < incumbent) || ((candidate != candidate) && (incumbent == incumbent));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) {
-    return pandnot(pcmp_lt_or_nan(candidate, incumbent), pisnan(incumbent));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const {
-    return predux_min<PropagateNaN>(a);
-  }
-};
-
-template <typename Scalar>
-struct min_coeff_functor<Scalar, PropagateNumbers, false> {
-  EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const {
-    return (candidate < incumbent) || ((candidate == candidate) && (incumbent != incumbent));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const {
-    return pandnot(pcmp_lt_or_nan(candidate, incumbent), pisnan(candidate));
-  }
-  template <typename Packet>
-  EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const {
-    return predux_min<PropagateNumbers>(a);
-  }
-};
-
-template <typename Scalar>
-struct min_max_traits {
-  static constexpr bool PacketAccess = packet_traits<Scalar>::Vectorizable;
-};
-template <typename Scalar, int NaNPropagation>
-struct functor_traits<max_coeff_functor<Scalar, NaNPropagation>> : min_max_traits<Scalar> {};
-template <typename Scalar, int NaNPropagation>
-struct functor_traits<min_coeff_functor<Scalar, NaNPropagation>> : min_max_traits<Scalar> {};
-
-template <typename Evaluator, typename Func, bool Linear, bool Vectorize>
-struct find_coeff_loop;
-template <typename Evaluator, typename Func>
-struct find_coeff_loop<Evaluator, Func, /*Linear*/ false, /*Vectorize*/ false> {
-  using Scalar = typename Evaluator::Scalar;
-  static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& res, Index& outer, Index& inner) {
-    Index outerSize = eval.outerSize();
-    Index innerSize = eval.innerSize();
-
-    /* initialization performed in calling function */
-    /* result = eval.coeff(0, 0); */
-    /* outer = 0; */
-    /* inner = 0; */
-
-    for (Index j = 0; j < outerSize; j++) {
-      for (Index i = 0; i < innerSize; i++) {
-        Scalar xprCoeff = eval.coeffByOuterInner(j, i);
-        bool newRes = func.compareCoeff(res, xprCoeff);
-        if (newRes) {
-          outer = j;
-          inner = i;
-          res = xprCoeff;
-        }
-      }
-    }
-  }
-};
-template <typename Evaluator, typename Func>
-struct find_coeff_loop<Evaluator, Func, /*Linear*/ true, /*Vectorize*/ false> {
-  using Scalar = typename Evaluator::Scalar;
-  static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& res, Index& index) {
-    Index size = eval.size();
-
-    /* initialization performed in calling function */
-    /* result = eval.coeff(0); */
-    /* index = 0; */
-
-    for (Index k = 0; k < size; k++) {
-      Scalar xprCoeff = eval.coeff(k);
-      bool newRes = func.compareCoeff(res, xprCoeff);
-      if (newRes) {
-        index = k;
-        res = xprCoeff;
-      }
-    }
-  }
-};
-template <typename Evaluator, typename Func>
-struct find_coeff_loop<Evaluator, Func, /*Linear*/ false, /*Vectorize*/ true> {
-  using ScalarImpl = find_coeff_loop<Evaluator, Func, false, false>;
-  using Scalar = typename Evaluator::Scalar;
-  using Packet = typename Evaluator::Packet;
-  static constexpr int PacketSize = unpacket_traits<Packet>::size;
-  static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& result, Index& outer,
-                                           Index& inner) {
-    Index outerSize = eval.outerSize();
-    Index innerSize = eval.innerSize();
-    Index packetEnd = numext::round_down(innerSize, PacketSize);
-
-    /* initialization performed in calling function */
-    /* result = eval.coeff(0, 0); */
-    /* outer = 0; */
-    /* inner = 0; */
-
-    bool checkPacket = false;
-
-    for (Index j = 0; j < outerSize; j++) {
-      Packet resultPacket = pset1<Packet>(result);
-      for (Index i = 0; i < packetEnd; i += PacketSize) {
-        Packet xprPacket = eval.template packetByOuterInner<Unaligned, Packet>(j, i);
-        if (predux_any(func.comparePacket(resultPacket, xprPacket))) {
-          outer = j;
-          inner = i;
-          result = func.predux(xprPacket);
-          resultPacket = pset1<Packet>(result);
-          checkPacket = true;
-        }
-      }
-
-      for (Index i = packetEnd; i < innerSize; i++) {
-        Scalar xprCoeff = eval.coeffByOuterInner(j, i);
-        if (func.compareCoeff(result, xprCoeff)) {
-          outer = j;
-          inner = i;
-          result = xprCoeff;
-          checkPacket = false;
-        }
-      }
-    }
-
-    if (checkPacket) {
-      result = eval.coeffByOuterInner(outer, inner);
-      Index i_end = inner + PacketSize;
-      for (Index i = inner; i < i_end; i++) {
-        Scalar xprCoeff = eval.coeffByOuterInner(outer, i);
-        if (func.compareCoeff(result, xprCoeff)) {
-          inner = i;
-          result = xprCoeff;
-        }
-      }
-    }
-  }
-};
-template <typename Evaluator, typename Func>
-struct find_coeff_loop<Evaluator, Func, /*Linear*/ true, /*Vectorize*/ true> {
-  using ScalarImpl = find_coeff_loop<Evaluator, Func, true, false>;
-  using Scalar = typename Evaluator::Scalar;
-  using Packet = typename Evaluator::Packet;
-  static constexpr int PacketSize = unpacket_traits<Packet>::size;
-  static constexpr int Alignment = Evaluator::Alignment;
-
-  static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& result, Index& index) {
-    Index size = eval.size();
-    Index packetEnd = numext::round_down(size, PacketSize);
-
-    /* initialization performed in calling function */
-    /* result = eval.coeff(0); */
-    /* index = 0; */
-
-    Packet resultPacket = pset1<Packet>(result);
-    bool checkPacket = false;
-
-    for (Index k = 0; k < packetEnd; k += PacketSize) {
-      Packet xprPacket = eval.template packet<Alignment, Packet>(k);
-      if (predux_any(func.comparePacket(resultPacket, xprPacket))) {
-        index = k;
-        result = func.predux(xprPacket);
-        resultPacket = pset1<Packet>(result);
-        checkPacket = true;
-      }
-    }
-
-    for (Index k = packetEnd; k < size; k++) {
-      Scalar xprCoeff = eval.coeff(k);
-      if (func.compareCoeff(result, xprCoeff)) {
-        index = k;
-        result = xprCoeff;
-        checkPacket = false;
-      }
-    }
-
-    if (checkPacket) {
-      result = eval.coeff(index);
-      Index k_end = index + PacketSize;
-      for (Index k = index; k < k_end; k++) {
-        Scalar xprCoeff = eval.coeff(k);
-        if (func.compareCoeff(result, xprCoeff)) {
-          index = k;
-          result = xprCoeff;
-        }
-      }
-    }
-  }
-};
-
-template <typename Derived>
-struct find_coeff_evaluator : public evaluator<Derived> {
-  using Base = evaluator<Derived>;
-  using Scalar = typename Derived::Scalar;
-  using Packet = typename packet_traits<Scalar>::type;
-  static constexpr int Flags = Base::Flags;
-  static constexpr bool IsRowMajor = bool(Flags & RowMajorBit);
-  EIGEN_DEVICE_FUNC inline find_coeff_evaluator(const Derived& xpr) : Base(xpr), m_xpr(xpr) {}
-
-  EIGEN_DEVICE_FUNC inline Scalar coeffByOuterInner(Index outer, Index inner) const {
-    Index row = IsRowMajor ? outer : inner;
-    Index col = IsRowMajor ? inner : outer;
-    return Base::coeff(row, col);
-  }
-  template <int LoadMode, typename PacketType>
-  EIGEN_DEVICE_FUNC inline PacketType packetByOuterInner(Index outer, Index inner) const {
-    Index row = IsRowMajor ? outer : inner;
-    Index col = IsRowMajor ? inner : outer;
-    return Base::template packet<LoadMode, PacketType>(row, col);
-  }
-
-  EIGEN_DEVICE_FUNC inline Index innerSize() const { return m_xpr.innerSize(); }
-  EIGEN_DEVICE_FUNC inline Index outerSize() const { return m_xpr.outerSize(); }
-  EIGEN_DEVICE_FUNC inline Index size() const { return m_xpr.size(); }
-
-  const Derived& m_xpr;
-};
-
-template <typename Derived, typename Func>
-struct find_coeff_impl {
-  using Evaluator = find_coeff_evaluator<Derived>;
-  static constexpr int Flags = Evaluator::Flags;
-  static constexpr int Alignment = Evaluator::Alignment;
-  static constexpr bool IsRowMajor = Derived::IsRowMajor;
-  static constexpr int MaxInnerSizeAtCompileTime =
-      IsRowMajor ? Derived::MaxColsAtCompileTime : Derived::MaxRowsAtCompileTime;
-  static constexpr int MaxSizeAtCompileTime = Derived::MaxSizeAtCompileTime;
-
-  using Scalar = typename Derived::Scalar;
-  using Packet = typename Evaluator::Packet;
-
-  static constexpr int PacketSize = unpacket_traits<Packet>::size;
-  static constexpr bool Linearize = bool(Flags & LinearAccessBit);
-  static constexpr bool DontVectorize =
-      enum_lt_not_dynamic(Linearize ? MaxSizeAtCompileTime : MaxInnerSizeAtCompileTime, PacketSize);
-  static constexpr bool Vectorize =
-      !DontVectorize && bool(Flags & PacketAccessBit) && functor_traits<Func>::PacketAccess;
-
-  using Loop = find_coeff_loop<Evaluator, Func, Linearize, Vectorize>;
-
-  template <bool ForwardLinearAccess = Linearize, std::enable_if_t<!ForwardLinearAccess, bool> = true>
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& xpr, Func& func, Scalar& res, Index& outer,
-                                                        Index& inner) {
-    Evaluator eval(xpr);
-    Loop::run(eval, func, res, outer, inner);
-  }
-  template <bool ForwardLinearAccess = Linearize, std::enable_if_t<ForwardLinearAccess, bool> = true>
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& xpr, Func& func, Scalar& res, Index& outer,
-                                                        Index& inner) {
-    // where possible, use the linear loop and back-calculate the outer and inner indices
-    Index index = 0;
-    run(xpr, func, res, index);
-    outer = index / xpr.innerSize();
-    inner = index % xpr.innerSize();
-  }
-  static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& xpr, Func& func, Scalar& res, Index& index) {
-    Evaluator eval(xpr);
-    Loop::run(eval, func, res, index);
-  }
-};
-
-template <typename Derived, typename IndexType, typename Func>
-EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar findCoeff(const DenseBase<Derived>& mat, Func& func,
-                                                                       IndexType* rowPtr, IndexType* colPtr) {
-  eigen_assert(mat.rows() > 0 && mat.cols() > 0 && "you are using an empty matrix");
-  using Scalar = typename DenseBase<Derived>::Scalar;
-  using FindCoeffImpl = internal::find_coeff_impl<Derived, Func>;
-  Index outer = 0;
-  Index inner = 0;
-  Scalar res = mat.coeff(0, 0);
-  FindCoeffImpl::run(mat.derived(), func, res, outer, inner);
-  *rowPtr = internal::convert_index<IndexType>(Derived::IsRowMajor ? outer : inner);
-  if (colPtr) *colPtr = internal::convert_index<IndexType>(Derived::IsRowMajor ? inner : outer);
-  return res;
-}
-
-template <typename Derived, typename IndexType, typename Func>
-EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar findCoeff(const DenseBase<Derived>& mat, Func& func,
-                                                                       IndexType* indexPtr) {
-  eigen_assert(mat.size() > 0 && "you are using an empty matrix");
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  using Scalar = typename DenseBase<Derived>::Scalar;
-  using FindCoeffImpl = internal::find_coeff_impl<Derived, Func>;
-  Index index = 0;
-  Scalar res = mat.coeff(0);
-  FindCoeffImpl::run(mat.derived(), func, res, index);
-  *indexPtr = internal::convert_index<IndexType>(index);
-  return res;
-}
-
-}  // namespace internal
-
-/** \fn DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
- * \returns the minimum of all coefficients of *this and puts in *row and *col its location.
- *
- * If there are multiple coefficients with the same extreme value, the location of the first instance is returned.
- *
- * In case \c *this contains NaN, NaNPropagation determines the behavior:
- *   NaNPropagation == PropagateFast : undefined
- *   NaNPropagation == PropagateNaN : result is NaN
- *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
- * \warning the matrix must be not empty, otherwise an assertion is triggered.
- *
- * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visit(), DenseBase::minCoeff()
- */
-template <typename Derived>
-template <int NaNPropagation, typename IndexType>
-EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::minCoeff(IndexType* rowPtr,
-                                                                                          IndexType* colPtr) const {
-  using Func = internal::min_coeff_functor<Scalar, NaNPropagation>;
-  Func func;
-  return internal::findCoeff(derived(), func, rowPtr, colPtr);
-}
-
-/** \returns the minimum of all coefficients of *this and puts in *index its location.
- *
- * If there are multiple coefficients with the same extreme value, the location of the first instance is returned.
- *
- * In case \c *this contains NaN, NaNPropagation determines the behavior:
- *   NaNPropagation == PropagateFast : undefined
- *   NaNPropagation == PropagateNaN : result is NaN
- *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
- * \warning the matrix must be not empty, otherwise an assertion is triggered.
- *
- * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visit(),
- * DenseBase::minCoeff()
- */
-template <typename Derived>
-template <int NaNPropagation, typename IndexType>
-EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::minCoeff(IndexType* indexPtr) const {
-  using Func = internal::min_coeff_functor<Scalar, NaNPropagation>;
-  Func func;
-  return internal::findCoeff(derived(), func, indexPtr);
-}
-
-/** \fn DenseBase<Derived>::maxCoeff(IndexType* rowId, IndexType* colId) const
- * \returns the maximum of all coefficients of *this and puts in *row and *col its location.
- *
- * If there are multiple coefficients with the same extreme value, the location of the first instance is returned.
- *
- * In case \c *this contains NaN, NaNPropagation determines the behavior:
- *   NaNPropagation == PropagateFast : undefined
- *   NaNPropagation == PropagateNaN : result is NaN
- *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
- * \warning the matrix must be not empty, otherwise an assertion is triggered.
- *
- * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::maxCoeff()
- */
-template <typename Derived>
-template <int NaNPropagation, typename IndexType>
-EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::maxCoeff(IndexType* rowPtr,
-                                                                                          IndexType* colPtr) const {
-  using Func = internal::max_coeff_functor<Scalar, NaNPropagation>;
-  Func func;
-  return internal::findCoeff(derived(), func, rowPtr, colPtr);
-}
-
-/** \returns the maximum of all coefficients of *this and puts in *index its location.
- *
- * If there are multiple coefficients with the same extreme value, the location of the first instance is returned.
- *
- * In case \c *this contains NaN, NaNPropagation determines the behavior:
- *   NaNPropagation == PropagateFast : undefined
- *   NaNPropagation == PropagateNaN : result is NaN
- *   NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN
- * \warning the matrix must be not empty, otherwise an assertion is triggered.
- *
- * \sa DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visitor(),
- * DenseBase::maxCoeff()
- */
-template <typename Derived>
-template <int NaNPropagation, typename IndexType>
-EIGEN_DEVICE_FUNC typename internal::traits<Derived>::Scalar DenseBase<Derived>::maxCoeff(IndexType* indexPtr) const {
-  using Func = internal::max_coeff_functor<Scalar, NaNPropagation>;
-  Func func;
-  return internal::findCoeff(derived(), func, indexPtr);
-}
-
-}  // namespace Eigen
-
-#endif  // EIGEN_FIND_COEFF_H