Add CI to build docs

(grafted from 4cd4be97a7
)

.gitignore

@@ -0,0 +1,41 @@
+qrc_*cxx
+*.orig
+*.pyc
+*.diff
+diff
+*.save
+save
+*.old
+*.gmo
+*.qm
+core
+core.*
+*.bak
+*~
+*.build*
+*.moc.*
+*.moc
+ui_*
+CMakeCache.txt
+tags
+.*.swp
+activity.png
+*.out
+*.php*
+*.log
+*.orig
+*.rej
+log
+patch
+*.patch
+a
+a.*
+lapack/testing
+lapack/reference
+.*project
+.settings
+Makefile
+!ci/build.gitlab-ci.yml
+!scripts/buildtests.in
+!Eigen/Core
+!Eigen/src/Core

.gitlab-ci.yml

@@ -0,0 +1,28 @@
+# This file is part of Eigen, a lightweight C++ template library
+# for linear algebra.
+#
+# Copyright (C) 2023, The Eigen Authors
+#
+# This Source Code Form is subject to the terms of the Mozilla
+# Public License v. 2.0. If a copy of the MPL was not distributed
+# with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+stages:
+  - build
+  - 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/common.gitlab-ci.yml"
+  - "/ci/build.linux.gitlab-ci.yml"
+  - "/ci/deploy.gitlab-ci.yml"

COPYING.LGPL

@@ -1,165 +1,502 @@
                   GNU LESSER GENERAL PUBLIC LICENSE
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+                       Version 2.1, February 1999
 
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+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
+specifies a version number of this License which applies to it and
+"any later version", you have the option of following the terms and
+conditions either of that version or of any later version published by
+the Free Software Foundation.  If the Library does not specify a
+license version number, you may choose any version ever published by
+the Free Software Foundation.
+
+  14. If you wish to incorporate parts of the Library into other free
+programs whose distribution conditions are incompatible with these,
+write to the author to ask for permission.  For software which is
+copyrighted by the Free Software Foundation, write to the Free
+Software Foundation; we sometimes make exceptions for this.  Our
+decision will be guided by the two goals of preserving the free status
+of all derivatives of our free software and of promoting the sharing
+and reuse of software generally.
+
+                            NO WARRANTY
+
+  15. BECAUSE THE LIBRARY IS LICENSED FREE OF CHARGE, THERE IS NO
+WARRANTY FOR THE LIBRARY, TO THE EXTENT PERMITTED BY APPLICABLE LAW.
+EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR
+OTHER PARTIES PROVIDE THE LIBRARY "AS IS" WITHOUT WARRANTY OF ANY
+KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE
+LIBRARY IS WITH YOU.  SHOULD THE LIBRARY PROVE DEFECTIVE, YOU ASSUME
+THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+  16. IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN
+WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MAY MODIFY
+AND/OR REDISTRIBUTE THE LIBRARY AS PERMITTED ABOVE, BE LIABLE TO YOU
+FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR
+CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE
+LIBRARY (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING
+RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A
+FAILURE OF THE LIBRARY TO OPERATE WITH ANY OTHER SOFTWARE), EVEN IF
+SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH
+DAMAGES.
+
+                     END OF TERMS AND CONDITIONS
+
+           How to Apply These Terms to Your New Libraries
+
+  If you develop a new library, and you want it to be of the greatest
+possible use to the public, we recommend making it free software that
+everyone can redistribute and change.  You can do so by permitting
+redistribution under these terms (or, alternatively, under the terms of the
+ordinary General Public License).
+
+  To apply these terms, attach the following notices to the library.  It is
+safest to attach them to the start of each source file to most effectively
+convey the exclusion of warranty; and each file should have at least the
+"copyright" line and a pointer to where the full notice is found.
+
+    <one line to give the library's name and a brief idea of what it does.>
+    Copyright (C) <year>  <name of author>
+
+    This library is free software; you can redistribute it and/or
+    modify it under the terms of the GNU Lesser General Public
+    License as published by the Free Software Foundation; either
+    version 2.1 of the License, or (at your option) any later version.
+
+    This library is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+    Lesser General Public License for more details.
+
+    You should have received a copy of the GNU Lesser General Public
+    License along with this library; if not, write to the Free Software
+    Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
+
+Also add information on how to contact you by electronic and paper mail.
+
+You should also get your employer (if you work as a programmer) or your
+school, if any, to sign a "copyright disclaimer" for the library, if
+necessary.  Here is a sample; alter the names:
+
+  Yoyodyne, Inc., hereby disclaims all copyright interest in the
+  library `Frob' (a library for tweaking knobs) written by James Random Hacker.
+
+  <signature of Ty Coon>, 1 April 1990
+  Ty Coon, President of Vice
+
+That's all there is to it!

COPYING.README

@@ -5,6 +5,9 @@ Eigen is primarily MPL2 licensed. See COPYING.MPL2 and these links:
 Some files contain third-party code under BSD or LGPL licenses, whence the other
 COPYING.* files here.
 
+All the LGPL code is either LGPL 2.1-only, or LGPL 2.1-or-later.
+For this reason, the COPYING.LGPL file contains the LGPL 2.1 text.
+
 If you want to guarantee that the Eigen code that you are #including is licensed
 under the MPL2 and possibly more permissive licenses (like BSD), #define this
 preprocessor symbol:

CTestConfig.cmake

@@ -4,10 +4,10 @@
 ## # The following are required to uses Dart and the Cdash dashboard
 ##   ENABLE_TESTING()
 ##   INCLUDE(CTest)
-set(CTEST_PROJECT_NAME "Eigen")
+set(CTEST_PROJECT_NAME "Eigen3.1")
 set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
 
 set(CTEST_DROP_METHOD "http")
 set(CTEST_DROP_SITE "manao.inria.fr")
-set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen")
+set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen3.1")
-set(CTEST_DROP_SITE_CDASH TRUE)
+set(CTEST_DROP_SITE_CDASH TRUE)

Eigen/Core

@@ -44,7 +44,7 @@
   #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) )
+  #if (defined __SSE2__) && ( (!defined __GNUC__) || (defined __INTEL_COMPILER) || EIGEN_GNUC_AT_LEAST(4,2) )
     #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC
   #endif
 #endif

Eigen/SparseCholesky

@@ -2,6 +2,7 @@
 #define EIGEN_SPARSECHOLESKY_MODULE_H
 
 #include "SparseCore"
+#include "OrderingMethods"
 
 #include "src/Core/util/DisableStupidWarnings.h"
 

Eigen/src/Cholesky/LDLT.h

@@ -277,15 +277,13 @@ template<> struct ldlt_inplace<Lower>
         // are compared; if any diagonal is negligible compared
         // to the largest overall, the algorithm bails.
         cutoff = abs(NumTraits<Scalar>::epsilon() * biggest_in_corner);
-
-        if(sign)
-          *sign = real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0 ? 1 : -1;
       }
 
       // Finish early if the matrix is not full rank.
       if(biggest_in_corner < cutoff)
       {
         for(Index i = k; i < size; i++) transpositions.coeffRef(i) = i;
+        if(sign) *sign = 0;
         break;
       }
 
@@ -326,6 +324,16 @@ template<> struct ldlt_inplace<Lower>
       }
       if((rs>0) && (abs(mat.coeffRef(k,k)) > cutoff))
         A21 /= mat.coeffRef(k,k);
+      
+      if(sign)
+      {
+        // LDLT is not guaranteed to work for indefinite matrices, but let's try to get the sign right
+        int newSign = real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0;
+        if(k == 0)
+          *sign = newSign;
+        else if(*sign != newSign)
+          *sign = 0;
+      }
     }
 
     return true;
@@ -534,8 +542,7 @@ template<typename Derived>
 bool LDLT<MatrixType,_UpLo>::solveInPlace(MatrixBase<Derived> &bAndX) const
 {
   eigen_assert(m_isInitialized && "LDLT is not initialized.");
-  const Index size = m_matrix.rows();
+  eigen_assert(m_matrix.rows() == bAndX.rows());
-  eigen_assert(size == bAndX.rows());
 
   bAndX = this->solve(bAndX);
 

Eigen/src/Core/ArrayWrapper.h

@@ -55,7 +55,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     inline Index outerStride() const { return m_expression.outerStride(); }
     inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
     inline CoeffReturnType coeff(Index row, Index col) const
@@ -121,6 +121,13 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
       return m_expression;
     }
 
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index)  */
+    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index,Index)*/
+    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
   protected:
     NestedExpressionType m_expression;
 };
@@ -168,7 +175,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     inline Index outerStride() const { return m_expression.outerStride(); }
     inline Index innerStride() const { return m_expression.innerStride(); }
 
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
+    inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
     inline CoeffReturnType coeff(Index row, Index col) const
@@ -231,6 +238,13 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
       return m_expression;
     }
 
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index)  */
+    void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); }
+    /** Forwards the resizing request to the nested expression
+      * \sa DenseBase::resize(Index,Index)*/
+    void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); }
+
   protected:
     NestedExpressionType m_expression;
 };

Eigen/src/Core/Assign_MKL.h

@@ -210,7 +210,7 @@ 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
+#ifndef _WIN32
 EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float)
 EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double)
 EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8)

Eigen/src/Core/CommaInitializer.h

@@ -65,6 +65,8 @@ struct CommaInitializer
   template<typename OtherDerived>
   CommaInitializer& operator,(const DenseBase<OtherDerived>& other)
   {
+    if(other.cols()==0 || other.rows()==0)
+      return *this;
     if (m_col==m_xpr.cols())
     {
       m_row+=m_currentBlockRows;

Eigen/src/Core/CwiseUnaryView.h

@@ -44,9 +44,10 @@ struct traits<CwiseUnaryView<ViewOp, MatrixType> >
     // "error: no integral type can represent all of the enumerator values
     InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic
                              ? int(Dynamic)
-                             : int(MatrixTypeInnerStride)
+                             : int(MatrixTypeInnerStride) * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)),
-                               * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar)),
+    OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret == Dynamic
-    OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
+                             ? int(Dynamic)
+                             : outer_stride_at_compile_time<MatrixType>::ret * int(sizeof(typename traits<MatrixType>::Scalar) / sizeof(Scalar))
   };
 };
 }
@@ -55,8 +56,7 @@ template<typename ViewOp, typename MatrixType, typename StorageKind>
 class CwiseUnaryViewImpl;
 
 template<typename ViewOp, typename MatrixType>
-class CwiseUnaryView : internal::no_assignment_operator,
+class CwiseUnaryView : public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
-  public CwiseUnaryViewImpl<ViewOp, MatrixType, typename internal::traits<MatrixType>::StorageKind>
 {
   public:
 
@@ -98,6 +98,10 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
     typedef typename internal::dense_xpr_base< CwiseUnaryView<ViewOp, MatrixType> >::type Base;
 
     EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl)
+    
+    inline Scalar* data() { return &coeffRef(0); }
+    inline const Scalar* data() const { return &coeff(0); }
 
     inline Index innerStride() const
     {
@@ -106,7 +110,7 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
 
     inline Index outerStride() const
     {
-      return derived().nestedExpression().outerStride();
+      return derived().nestedExpression().outerStride() * sizeof(typename internal::traits<MatrixType>::Scalar) / sizeof(Scalar);
     }
 
     EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const

Eigen/src/Core/DenseStorage.h

@@ -39,13 +39,24 @@ struct plain_array
   plain_array(constructor_without_unaligned_array_assert) {}
 };
 
-#ifdef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
+#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT)
   #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask)
+#elif EIGEN_GNUC_AT_LEAST(4,7) 
+  // GCC 4.7 is too aggressive in its optimizations and remove the alignement test based on the fact the array is declared to be aligned.
+  // See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900
+  // Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined:
+  template<typename PtrType>
+  EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; }
+  #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
+    eigen_assert((reinterpret_cast<size_t>(eigen_unaligned_array_assert_workaround_gcc47(array)) & sizemask) == 0 \
+              && "this assertion is explained here: " \
+              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
+              " **** READ THIS WEB PAGE !!! ****");
 #else
   #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \
     eigen_assert((reinterpret_cast<size_t>(array) & sizemask) == 0 \
               && "this assertion is explained here: " \
-              "http://eigen.tuxfamily.org/dox-devel/TopicUnalignedArrayAssert.html" \
+              "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \
               " **** READ THIS WEB PAGE !!! ****");
 #endif
 

Eigen/src/Core/DiagonalMatrix.h

@@ -20,6 +20,7 @@ class DiagonalBase : public EigenBase<Derived>
   public:
     typedef typename internal::traits<Derived>::DiagonalVectorType DiagonalVectorType;
     typedef typename DiagonalVectorType::Scalar Scalar;
+    typedef typename DiagonalVectorType::RealScalar RealScalar;
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
     typedef typename internal::traits<Derived>::Index Index;
 
@@ -65,6 +66,17 @@ class DiagonalBase : public EigenBase<Derived>
       return diagonal().cwiseInverse();
     }
     
+    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+    operator*(const Scalar& scalar) const
+    {
+      return diagonal() * scalar;
+    }
+    friend inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_multiple_op<Scalar>, const DiagonalVectorType> >
+    operator*(const Scalar& scalar, const DiagonalBase& other)
+    {
+      return other.diagonal() * scalar;
+    }
+    
     #ifdef EIGEN2_SUPPORT
     template<typename OtherDerived>
     bool isApprox(const DiagonalBase<OtherDerived>& other, typename NumTraits<Scalar>::Real precision = NumTraits<Scalar>::dummy_precision()) const

Eigen/src/Core/Functors.h

@@ -447,7 +447,7 @@ struct functor_traits<scalar_log_op<Scalar> >
  * indeed it seems better to declare m_other as a Packet and do the pset1() once
  * in the constructor. However, in practice:
  *  - GCC does not like m_other as a Packet and generate a load every time it needs it
- *  - on the other hand GCC is able to moves the pset1() away the loop :)
+ *  - on the other hand GCC is able to moves the pset1() outside the loop :)
  *  - simpler code ;)
  * (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y)
  */
@@ -478,33 +478,6 @@ template<typename Scalar1,typename Scalar2>
 struct functor_traits<scalar_multiple2_op<Scalar1,Scalar2> >
 { enum { Cost = NumTraits<Scalar1>::MulCost, PacketAccess = false }; };
 
-template<typename Scalar, bool IsInteger>
-struct scalar_quotient1_impl {
-  typedef typename packet_traits<Scalar>::type Packet;
-  // FIXME default copy constructors seems bugged with std::complex<>
-  EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
-  EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(static_cast<Scalar>(1) / other) {}
-  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; }
-  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
-  { return internal::pmul(a, pset1<Packet>(m_other)); }
-  const Scalar m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_quotient1_impl<Scalar,false> >
-{ enum { Cost = NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasMul }; };
-
-template<typename Scalar>
-struct scalar_quotient1_impl<Scalar,true> {
-  // FIXME default copy constructors seems bugged with std::complex<>
-  EIGEN_STRONG_INLINE scalar_quotient1_impl(const scalar_quotient1_impl& other) : m_other(other.m_other) { }
-  EIGEN_STRONG_INLINE scalar_quotient1_impl(const Scalar& other) : m_other(other) {}
-  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
-  typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
-};
-template<typename Scalar>
-struct functor_traits<scalar_quotient1_impl<Scalar,true> >
-{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
-
 /** \internal
   * \brief Template functor to divide a scalar by a fixed other one
   *
@@ -514,14 +487,19 @@ struct functor_traits<scalar_quotient1_impl<Scalar,true> >
   * \sa class CwiseUnaryOp, MatrixBase::operator/
   */
 template<typename Scalar>
-struct scalar_quotient1_op : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger > {
+struct scalar_quotient1_op {
-  EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other)
+  typedef typename packet_traits<Scalar>::type Packet;
-    : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger >(other) {}
+  // FIXME default copy constructors seems bugged with std::complex<>
+  EIGEN_STRONG_INLINE scalar_quotient1_op(const scalar_quotient1_op& other) : m_other(other.m_other) { }
+  EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other) : m_other(other) {}
+  EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
+  EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
+  { return internal::pdiv(a, pset1<Packet>(m_other)); }
+  typename add_const_on_value_type<typename NumTraits<Scalar>::Nested>::type m_other;
 };
 template<typename Scalar>
 struct functor_traits<scalar_quotient1_op<Scalar> >
-: functor_traits<scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger> >
+{ enum { Cost = 2 * NumTraits<Scalar>::MulCost, PacketAccess = packet_traits<Scalar>::HasDiv }; };
-{};
 
 // nullary functors
 
@@ -555,8 +533,11 @@ template <typename Scalar, bool RandomAccess> struct linspaced_op_impl;
 // linear access for packet ops:
 // 1) initialization
 //   base = [low, ..., low] + ([step, ..., step] * [-size, ..., 0])
-// 2) each step
+// 2) each step (where size is 1 for coeff access or PacketSize for packet access)
 //   base += [size*step, ..., size*step]
+//
+// TODO: Perhaps it's better to initialize lazily (so not in the constructor but in packetOp)
+//       in order to avoid the padd() in operator() ?
 template <typename Scalar>
 struct linspaced_op_impl<Scalar,false>
 {
@@ -565,10 +546,15 @@ struct linspaced_op_impl<Scalar,false>
   linspaced_op_impl(Scalar low, Scalar step) :
   m_low(low), m_step(step),
   m_packetStep(pset1<Packet>(packet_traits<Scalar>::size*step)),
-  m_base(padd(pset1<Packet>(low),pmul(pset1<Packet>(step),plset<Scalar>(-packet_traits<Scalar>::size)))) {}
+  m_base(padd(pset1<Packet>(low), pmul(pset1<Packet>(step),plset<Scalar>(-packet_traits<Scalar>::size)))) {}
 
   template<typename Index>
-  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; }
+  EIGEN_STRONG_INLINE const Scalar operator() (Index i) const 
+  { 
+    m_base = padd(m_base, pset1<Packet>(m_step));
+    return m_low+i*m_step; 
+  }
+
   template<typename Index>
   EIGEN_STRONG_INLINE const Packet packetOp(Index) const { return m_base = padd(m_base,m_packetStep); }
 

Eigen/src/Core/MatrixBase.h

@@ -237,7 +237,7 @@ template<typename Derived> class MatrixBase
     
     // huuuge hack. make Eigen2's matrix.part<Diagonal>() work in eigen3. Problem: Diagonal is now a class template instead
     // of an integer constant. Solution: overload the part() method template wrt template parameters list.
-    template<template<typename T, int n> class U>
+    template<template<typename T, int N> class U>
     const DiagonalWrapper<ConstDiagonalReturnType> part() const
     { return diagonal().asDiagonal(); }
     #endif // EIGEN2_SUPPORT

Eigen/src/Core/PermutationMatrix.h

@@ -105,13 +105,13 @@ class PermutationBase : public EigenBase<Derived>
     #endif
 
     /** \returns the number of rows */
-    inline Index rows() const { return indices().size(); }
+    inline Index rows() const { return Index(indices().size()); }
 
     /** \returns the number of columns */
-    inline Index cols() const { return indices().size(); }
+    inline Index cols() const { return Index(indices().size()); }
 
     /** \returns the size of a side of the respective square matrix, i.e., the number of indices */
-    inline Index size() const { return indices().size(); }
+    inline Index size() const { return Index(indices().size()); }
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename DenseDerived>

Eigen/src/Core/PlainObjectBase.h

@@ -551,6 +551,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       eigen_assert((this->size()==0 || (IsVectorAtCompileTime ? (this->size() == other.size())
                  : (rows() == other.rows() && cols() == other.cols())))
         && "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined");
+      EIGEN_ONLY_USED_FOR_DEBUG(other);
       #else
       resizeLike(other);
       #endif

Eigen/src/Core/StableNorm.h

@@ -13,6 +13,7 @@
 namespace Eigen { 
 
 namespace internal {
+
 template<typename ExpressionType, typename Scalar>
 inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale)
 {
@@ -76,21 +77,20 @@ MatrixBase<Derived>::blueNorm() const
   using std::pow;
   using std::min;
   using std::max;
-  static Index nmax = -1;
+  static bool initialized = false;
   static RealScalar b1, b2, s1m, s2m, overfl, rbig, relerr;
-  if(nmax <= 0)
+  if(!initialized)
   {
-    int nbig, ibeta, it, iemin, iemax, iexp;
+    int ibeta, it, iemin, iemax, iexp;
     RealScalar abig, eps;
     // This program calculates the machine-dependent constants
-    // bl, b2, slm, s2m, relerr overfl, nmax
+    // bl, b2, slm, s2m, relerr overfl
     // from the "basic" machine-dependent numbers
-    // nbig, ibeta, it, iemin, iemax, rbig.
+    // ibeta, it, iemin, iemax, rbig.
     // The following define the basic machine-dependent constants.
     // For portability, the PORT subprograms "ilmaeh" and "rlmach"
     // are used. For any specific computer, each of the assignment
     // statements can be replaced
-    nbig  = (std::numeric_limits<Index>::max)();            // largest integer
     ibeta = std::numeric_limits<RealScalar>::radix;         // base for floating-point numbers
     it    = std::numeric_limits<RealScalar>::digits;        // number of base-beta digits in mantissa
     iemin = std::numeric_limits<RealScalar>::min_exponent;  // minimum exponent
@@ -111,8 +111,7 @@ MatrixBase<Derived>::blueNorm() const
     eps     = RealScalar(pow(double(ibeta), 1-it));
     relerr  = internal::sqrt(eps);         // tolerance for neglecting asml
     abig    = RealScalar(1.0/eps - 1.0);
-    if (RealScalar(nbig)>abig)  nmax = int(abig);  // largest safe n
+    initialized = true;
-    else                        nmax = nbig;
   }
   Index n = size();
   RealScalar ab2 = b2 / RealScalar(n);
@@ -131,7 +130,6 @@ MatrixBase<Derived>::blueNorm() const
     abig = internal::sqrt(abig);
     if(abig > overfl)
     {
-      eigen_assert(false && "overflow");
       return rbig;
     }
     if(amed > RealScalar(0))

Eigen/src/Core/Transpose.h

@@ -104,6 +104,7 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
 
     typedef typename internal::TransposeImpl_base<MatrixType>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl)
 
     inline Index innerStride() const { return derived().nestedExpression().innerStride(); }
     inline Index outerStride() const { return derived().nestedExpression().outerStride(); }
@@ -252,7 +253,7 @@ struct inplace_transpose_selector;
 template<typename MatrixType>
 struct inplace_transpose_selector<MatrixType,true> { // square matrix
   static void run(MatrixType& m) {
-    m.template triangularView<StrictlyUpper>().swap(m.transpose());
+    m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
   }
 };
 
@@ -260,7 +261,7 @@ template<typename MatrixType>
 struct inplace_transpose_selector<MatrixType,false> { // non square matrix
   static void run(MatrixType& m) {
     if (m.rows()==m.cols())
-      m.template triangularView<StrictlyUpper>().swap(m.transpose());
+      m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose());
     else
       m = m.transpose().eval();
   }
@@ -353,7 +354,7 @@ struct check_transpose_aliasing_run_time_selector
 {
   static bool run(const Scalar* dest, const OtherDerived& src)
   {
-    return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src));
+    return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src));
   }
 };
 
@@ -362,8 +363,8 @@ struct check_transpose_aliasing_run_time_selector<Scalar,DestIsTransposed,CwiseB
 {
   static bool run(const Scalar* dest, const CwiseBinaryOp<BinOp,DerivedA,DerivedB>& src)
   {
-    return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src.lhs())))
+    return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.lhs())))
-        || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src.rhs())));
+        || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.rhs())));
   }
 };
 

Eigen/src/Core/TriangularMatrix.h

@@ -511,6 +511,7 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
+  typedef typename Derived1::Scalar Scalar;
   static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
@@ -520,7 +521,7 @@ struct triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
         for(Index i = maxi; i < dst.rows(); ++i)
-          dst.coeffRef(i, j) = 0;
+          dst.coeffRef(i, j) = Scalar(0);
     }
   }
 };

Eigen/src/Core/arch/SSE/MathFunctions.h

@@ -31,7 +31,8 @@ Packet4f plog<Packet4f>(const Packet4f& _x)
 
   /* the smallest non denormalized float number */
   _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(min_norm_pos,  0x00800000);
-
+  _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(minus_inf,     0xff800000);//-1.f/0.f);
+  
   /* natural logarithm computed for 4 simultaneous float
     return NaN for x <= 0
   */
@@ -51,7 +52,8 @@ Packet4f plog<Packet4f>(const Packet4f& _x)
 
   Packet4i emm0;
 
-  Packet4f invalid_mask = _mm_cmple_ps(x, _mm_setzero_ps());
+  Packet4f invalid_mask = _mm_cmplt_ps(x, _mm_setzero_ps());
+  Packet4f iszero_mask = _mm_cmpeq_ps(x, _mm_setzero_ps());
 
   x = pmax(x, p4f_min_norm_pos);  /* cut off denormalized stuff */
   emm0 = _mm_srli_epi32(_mm_castps_si128(x), 23);
@@ -96,7 +98,9 @@ Packet4f plog<Packet4f>(const Packet4f& _x)
   y2 = pmul(e, p4f_cephes_log_q2);
   x = padd(x, y);
   x = padd(x, y2);
-  return _mm_or_ps(x, invalid_mask); // negative arg will be NAN
+  // negative arg will be NAN, 0 will be -INF
+  return _mm_or_ps(_mm_andnot_ps(iszero_mask, _mm_or_ps(x, invalid_mask)),
+                   _mm_and_ps(iszero_mask, p4f_minus_inf));
 }
 
 template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
@@ -370,7 +374,7 @@ Packet4f psqrt<Packet4f>(const Packet4f& _x)
   Packet4f half = pmul(_x, pset1<Packet4f>(.5f));
 
   /* select only the inverse sqrt of non-zero inputs */
-  Packet4f non_zero_mask = _mm_cmpgt_ps(_x, pset1<Packet4f>(std::numeric_limits<float>::epsilon()));
+  Packet4f non_zero_mask = _mm_cmpgt_ps(_x, pset1<Packet4f>((std::numeric_limits<float>::min)()));
   Packet4f x = _mm_and_ps(non_zero_mask, _mm_rsqrt_ps(_x));
 
   x = pmul(x, psub(pset1<Packet4f>(1.5f), pmul(half, pmul(x,x))));

Eigen/src/Core/products/GeneralBlockPanelKernel.h

@@ -69,8 +69,8 @@ inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1=0, std::ptrdi
   * - the number of scalars that fit into a packet (when vectorization is enabled).
   *
   * \sa setCpuCacheSizes */
-template<typename LhsScalar, typename RhsScalar, int KcFactor>
+template<typename LhsScalar, typename RhsScalar, int KcFactor, typename SizeType>
-void computeProductBlockingSizes(std::ptrdiff_t& k, std::ptrdiff_t& m, std::ptrdiff_t& n)
+void computeProductBlockingSizes(SizeType& k, SizeType& m, SizeType& n)
 {
   EIGEN_UNUSED_VARIABLE(n);
   // Explanations:
@@ -91,13 +91,13 @@ void computeProductBlockingSizes(std::ptrdiff_t& k, std::ptrdiff_t& m, std::ptrd
   };
 
   manage_caching_sizes(GetAction, &l1, &l2);
-  k = std::min<std::ptrdiff_t>(k, l1/kdiv);
+  k = std::min<SizeType>(k, l1/kdiv);
-  std::ptrdiff_t _m = k>0 ? l2/(4 * sizeof(LhsScalar) * k) : 0;
+  SizeType _m = k>0 ? l2/(4 * sizeof(LhsScalar) * k) : 0;
   if(_m<m) m = _m & mr_mask;
 }
 
-template<typename LhsScalar, typename RhsScalar>
+template<typename LhsScalar, typename RhsScalar, typename SizeType>
-inline void computeProductBlockingSizes(std::ptrdiff_t& k, std::ptrdiff_t& m, std::ptrdiff_t& n)
+inline void computeProductBlockingSizes(SizeType& k, SizeType& m, SizeType& n)
 {
   computeProductBlockingSizes<LhsScalar,RhsScalar,1>(k, m, n);
 }

Eigen/src/Core/products/GeneralMatrixVector.h

@@ -81,14 +81,13 @@ EIGEN_DONT_INLINE static void run(
   const Index peels = 2;
   const Index LhsPacketAlignedMask = LhsPacketSize-1;
   const Index ResPacketAlignedMask = ResPacketSize-1;
-  const Index PeelAlignedMask = ResPacketSize*peels-1;
   const Index size = rows;
   
   // How many coeffs of the result do we have to skip to be aligned.
   // Here we assume data are at least aligned on the base scalar type.
   Index alignedStart = internal::first_aligned(res,size);
   Index alignedSize = ResPacketSize>1 ? alignedStart + ((size-alignedStart) & ~ResPacketAlignedMask) : 0;
-  const Index peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
+  const Index peeledSize = alignedSize - RhsPacketSize*peels - RhsPacketSize + 1;
 
   const Index alignmentStep = LhsPacketSize>1 ? (LhsPacketSize - lhsStride % LhsPacketSize) & LhsPacketAlignedMask : 0;
   Index alignmentPattern = alignmentStep==0 ? AllAligned
@@ -177,6 +176,8 @@ EIGEN_DONT_INLINE static void run(
               _EIGEN_ACCUMULATE_PACKETS(d,du,d);
             break;
           case FirstAligned:
+          {
+            Index j = alignedStart;
             if(peels>1)
             {
               LhsPacket A00, A01, A02, A03, A10, A11, A12, A13;
@@ -186,7 +187,7 @@ EIGEN_DONT_INLINE static void run(
               A02 = pload<LhsPacket>(&lhs2[alignedStart-2]);
               A03 = pload<LhsPacket>(&lhs3[alignedStart-3]);
 
-              for (Index j = alignedStart; j<peeledSize; j+=peels*ResPacketSize)
+              for (; j<peeledSize; j+=peels*ResPacketSize)
               {
                 A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]);  palign<1>(A01,A11);
                 A12 = pload<LhsPacket>(&lhs2[j-2+LhsPacketSize]);  palign<2>(A02,A12);
@@ -210,9 +211,10 @@ EIGEN_DONT_INLINE static void run(
                 pstore(&res[j+ResPacketSize],T1);
               }
             }
-            for (Index j = peeledSize; j<alignedSize; j+=ResPacketSize)
+            for (; j<alignedSize; j+=ResPacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,du,du);
             break;
+          }
           default:
             for (Index j = alignedStart; j<alignedSize; j+=ResPacketSize)
               _EIGEN_ACCUMULATE_PACKETS(du,du,du);
@@ -332,7 +334,6 @@ EIGEN_DONT_INLINE static void run(
   const Index peels = 2;
   const Index RhsPacketAlignedMask = RhsPacketSize-1;
   const Index LhsPacketAlignedMask = LhsPacketSize-1;
-  const Index PeelAlignedMask = RhsPacketSize*peels-1;
   const Index depth = cols;
 
   // How many coeffs of the result do we have to skip to be aligned.
@@ -340,7 +341,7 @@ EIGEN_DONT_INLINE static void run(
   // if that's not the case then vectorization is discarded, see below.
   Index alignedStart = internal::first_aligned(rhs, depth);
   Index alignedSize = RhsPacketSize>1 ? alignedStart + ((depth-alignedStart) & ~RhsPacketAlignedMask) : 0;
-  const Index peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
+  const Index peeledSize = alignedSize - RhsPacketSize*peels - RhsPacketSize + 1;
 
   const Index alignmentStep = LhsPacketSize>1 ? (LhsPacketSize - lhsStride % LhsPacketSize) & LhsPacketAlignedMask : 0;
   Index alignmentPattern = alignmentStep==0 ? AllAligned
@@ -430,10 +431,12 @@ EIGEN_DONT_INLINE static void run(
               _EIGEN_ACCUMULATE_PACKETS(d,du,d);
             break;
           case FirstAligned:
+          {
+            Index j = alignedStart;
             if (peels>1)
             {
               /* Here we proccess 4 rows with with two peeled iterations to hide
-               * tghe overhead of unaligned loads. Moreover unaligned loads are handled
+               * the overhead of unaligned loads. Moreover unaligned loads are handled
                * using special shift/move operations between the two aligned packets
                * overlaping the desired unaligned packet. This is *much* more efficient
                * than basic unaligned loads.
@@ -443,7 +446,7 @@ EIGEN_DONT_INLINE static void run(
               A02 = pload<LhsPacket>(&lhs2[alignedStart-2]);
               A03 = pload<LhsPacket>(&lhs3[alignedStart-3]);
 
-              for (Index j = alignedStart; j<peeledSize; j+=peels*RhsPacketSize)
+              for (; j<peeledSize; j+=peels*RhsPacketSize)
               {
                 RhsPacket b = pload<RhsPacket>(&rhs[j]);
                 A11 = pload<LhsPacket>(&lhs1[j-1+LhsPacketSize]);  palign<1>(A01,A11);
@@ -465,9 +468,10 @@ EIGEN_DONT_INLINE static void run(
                 ptmp3 = pcj.pmadd(A13, b, ptmp3);
               }
             }
-            for (Index j = peeledSize; j<alignedSize; j+=RhsPacketSize)
+            for (; j<alignedSize; j+=RhsPacketSize)
               _EIGEN_ACCUMULATE_PACKETS(d,du,du);
             break;
+          }
           default:
             for (Index j = alignedStart; j<alignedSize; j+=RhsPacketSize)
               _EIGEN_ACCUMULATE_PACKETS(du,du,du);

Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h

@@ -57,11 +57,11 @@ template <typename Index, int Mode, \
 struct product_triangular_matrix_matrix<Scalar,Index, Mode, LhsIsTriangular, \
            LhsStorageOrder,ConjugateLhs, RhsStorageOrder,ConjugateRhs,ColMajor,Specialized> { \
   static inline void run(Index _rows, Index _cols, Index _depth, const Scalar* _lhs, Index lhsStride,\
-    const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha) { \
+    const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha, level3_blocking<Scalar,Scalar>& blocking) { \
       product_triangular_matrix_matrix_trmm<Scalar,Index,Mode, \
         LhsIsTriangular,LhsStorageOrder,ConjugateLhs, \
         RhsStorageOrder, ConjugateRhs, ColMajor>::run( \
-        _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+        _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
   } \
 };
 
@@ -96,7 +96,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
     const EIGTYPE* _lhs, Index lhsStride, \
     const EIGTYPE* _rhs, Index rhsStride, \
     EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha) \
+    EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
   { \
    Index diagSize  = (std::min)(_rows,_depth); \
    Index rows      = IsLower ? _rows : diagSize; \
@@ -115,16 +115,16 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
      /* Most likely no benefit to call TRMM or GEMM from MKL*/ \
        product_triangular_matrix_matrix<EIGTYPE,Index,Mode,true, \
        LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
-           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
      /*std::cout << "TRMM_L: A is not square! Go to Eigen TRMM implementation!\n";*/ \
      } else { \
      /* Make sense to call GEMM */ \
        Map<const MatrixLhs, 0, OuterStride<> > lhsMap(_lhs,rows,depth,OuterStride<>(lhsStride)); \
        MatrixLhs aa_tmp=lhsMap.template triangularView<Mode>(); \
        MKL_INT aStride = aa_tmp.outerStride(); \
-       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> blocking(_rows,_cols,_depth); \
+       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth); \
        general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
-       rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, blocking, 0); \
+       rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, gemm_blocking, 0); \
 \
      /*std::cout << "TRMM_L: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
      } \
@@ -210,7 +210,7 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
     const EIGTYPE* _lhs, Index lhsStride, \
     const EIGTYPE* _rhs, Index rhsStride, \
     EIGTYPE* res,        Index resStride, \
-    EIGTYPE alpha) \
+    EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
   { \
    Index diagSize  = (std::min)(_cols,_depth); \
    Index rows      = _rows; \
@@ -229,16 +229,16 @@ struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
      /* Most likely no benefit to call TRMM or GEMM from MKL*/ \
        product_triangular_matrix_matrix<EIGTYPE,Index,Mode,false, \
        LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
-           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha, blocking); \
        /*std::cout << "TRMM_R: A is not square! Go to Eigen TRMM implementation!\n";*/ \
      } else { \
      /* Make sense to call GEMM */ \
        Map<const MatrixRhs, 0, OuterStride<> > rhsMap(_rhs,depth,cols, OuterStride<>(rhsStride)); \
        MatrixRhs aa_tmp=rhsMap.template triangularView<Mode>(); \
        MKL_INT aStride = aa_tmp.outerStride(); \
-       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> blocking(_rows,_cols,_depth); \
+       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> gemm_blocking(_rows,_cols,_depth); \
        general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
-       rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, blocking, 0); \
+       rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, gemm_blocking, 0); \
 \
      /*std::cout << "TRMM_R: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
      } \

Eigen/src/Core/products/TriangularMatrixVector_MKL.h

@@ -82,11 +82,11 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
     LowUp = IsLower ? Lower : Upper \
   }; \
  static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
-                             const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+                             const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
  { \
    if (ConjLhs || IsZeroDiag) { \
      triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor,BuiltIn>::run( \
-       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
      return; \
    }\
    Index size = (std::min)(_rows,_cols); \
@@ -167,11 +167,11 @@ struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,
     LowUp = IsLower ? Lower : Upper \
   }; \
  static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
-                             const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+                             const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha) \
  { \
    if (IsZeroDiag) { \
      triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor,BuiltIn>::run( \
-       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
      return; \
    }\
    Index size = (std::min)(_rows,_cols); \

Eigen/src/Core/util/Macros.h

@@ -13,7 +13,7 @@
 
 #define EIGEN_WORLD_VERSION 3
 #define EIGEN_MAJOR_VERSION 1
-#define EIGEN_MINOR_VERSION 1
+#define EIGEN_MINOR_VERSION 4
 
 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
                                       (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \

Eigen/src/Core/util/Memory.h

@@ -88,11 +88,11 @@ inline void throw_std_bad_alloc()
 /** \internal Like malloc, but the returned pointer is guaranteed to be 16-byte aligned.
   * Fast, but wastes 16 additional bytes of memory. Does not throw any exception.
   */
-inline void* handmade_aligned_malloc(size_t size)
+inline void* handmade_aligned_malloc(std::size_t size)
 {
   void *original = std::malloc(size+16);
   if (original == 0) return 0;
-  void *aligned = reinterpret_cast<void*>((reinterpret_cast<size_t>(original) & ~(size_t(15))) + 16);
+  void *aligned = reinterpret_cast<void*>((reinterpret_cast<std::size_t>(original) & ~(std::size_t(15))) + 16);
   *(reinterpret_cast<void**>(aligned) - 1) = original;
   return aligned;
 }
@@ -108,13 +108,18 @@ inline void handmade_aligned_free(void *ptr)
   * Since we know that our handmade version is based on std::realloc
   * we can use std::realloc to implement efficient reallocation.
   */
-inline void* handmade_aligned_realloc(void* ptr, size_t size, size_t = 0)
+inline void* handmade_aligned_realloc(void* ptr, std::size_t size, std::size_t = 0)
 {
   if (ptr == 0) return handmade_aligned_malloc(size);
   void *original = *(reinterpret_cast<void**>(ptr) - 1);
+  std::ptrdiff_t previous_offset = static_cast<char *>(ptr)-static_cast<char *>(original);
   original = std::realloc(original,size+16);
   if (original == 0) return 0;
-  void *aligned = reinterpret_cast<void*>((reinterpret_cast<size_t>(original) & ~(size_t(15))) + 16);
+  void *aligned = reinterpret_cast<void*>((reinterpret_cast<std::size_t>(original) & ~(std::size_t(15))) + 16);
+  void *previous_aligned = static_cast<char *>(original)+previous_offset;
+  if(aligned!=previous_aligned)
+    std::memmove(aligned, previous_aligned, size);
+  
   *(reinterpret_cast<void**>(aligned) - 1) = original;
   return aligned;
 }
@@ -123,7 +128,7 @@ inline void* handmade_aligned_realloc(void* ptr, size_t size, size_t = 0)
 *** Implementation of generic aligned realloc (when no realloc can be used)***
 *****************************************************************************/
 
-void* aligned_malloc(size_t size);
+void* aligned_malloc(std::size_t size);
 void  aligned_free(void *ptr);
 
 /** \internal
@@ -204,7 +209,7 @@ inline void* aligned_malloc(size_t size)
     if(posix_memalign(&result, 16, size)) result = 0;
   #elif EIGEN_HAS_MM_MALLOC
     result = _mm_malloc(size, 16);
-  #elif (defined _MSC_VER)
+#elif defined(_MSC_VER) && (!defined(_WIN32_WCE))
     result = _aligned_malloc(size, 16);
   #else
     result = handmade_aligned_malloc(size);
@@ -227,7 +232,7 @@ inline void aligned_free(void *ptr)
     std::free(ptr);
   #elif EIGEN_HAS_MM_MALLOC
     _mm_free(ptr);
-  #elif defined(_MSC_VER)
+  #elif defined(_MSC_VER) && (!defined(_WIN32_WCE))
     _aligned_free(ptr);
   #else
     handmade_aligned_free(ptr);
@@ -446,7 +451,6 @@ template<typename T, bool Align> inline void conditional_aligned_delete_auto(T *
 template<typename Scalar, typename Index>
 static inline Index first_aligned(const Scalar* array, Index size)
 {
-  typedef typename packet_traits<Scalar>::type Packet;
   enum { PacketSize = packet_traits<Scalar>::size,
          PacketAlignedMask = PacketSize-1
   };
@@ -705,15 +709,6 @@ public:
         ::new( p ) T( value );
     }
 
-    // Support for c++11
-#if (__cplusplus >= 201103L)
-    template<typename... Args>
-    void  construct(pointer p, Args&&... args)
-    {
-      ::new(p) T(std::forward<Args>(args)...);
-    }
-#endif
-
     void destroy( pointer p )
     {
         p->~T();
@@ -745,7 +740,7 @@ public:
          __asm__ __volatile__ ("cpuid": "=a" (abcd[0]), "=b" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id) );
 #    endif
 #  elif defined(_MSC_VER)
-#    if (_MSC_VER > 1500)
+#    if (_MSC_VER > 1500) && ( defined(_M_IX86) || defined(_M_X64) )
 #      define EIGEN_CPUID(abcd,func,id) __cpuidex((int*)abcd,func,id)
 #    endif
 #  endif

Eigen/src/Core/util/XprHelper.h

@@ -301,9 +301,9 @@ template<typename T, int n=1, typename PlainObject = typename eval<T>::type> str
     // it's important that this value can still be squared without integer overflowing.
     DynamicAsInteger = 10000,
     ScalarReadCost = NumTraits<typename traits<T>::Scalar>::ReadCost,
-    ScalarReadCostAsInteger = ScalarReadCost == Dynamic ? DynamicAsInteger : ScalarReadCost,
+    ScalarReadCostAsInteger = ScalarReadCost == Dynamic ? int(DynamicAsInteger) : int(ScalarReadCost),
     CoeffReadCost = traits<T>::CoeffReadCost,
-    CoeffReadCostAsInteger = CoeffReadCost == Dynamic ? DynamicAsInteger : CoeffReadCost,
+    CoeffReadCostAsInteger = CoeffReadCost == Dynamic ? int(DynamicAsInteger) : int(CoeffReadCost),
     NAsInteger = n == Dynamic ? int(DynamicAsInteger) : n,
     CostEvalAsInteger   = (NAsInteger+1) * ScalarReadCostAsInteger + CoeffReadCostAsInteger,
     CostNoEvalAsInteger = NAsInteger * CoeffReadCostAsInteger

Eigen/src/Eigen2Support/SVD.h

@@ -512,8 +512,7 @@ template<typename MatrixType>
 template<typename OtherDerived, typename ResultType>
 bool SVD<MatrixType>::solve(const MatrixBase<OtherDerived> &b, ResultType* result) const
 {
-  const int rows = m_matU.rows();
+  ei_assert(b.rows() == m_matU.rows());
-  ei_assert(b.rows() == rows);
 
   Scalar maxVal = m_sigma.cwise().abs().maxCoeff();
   for (int j=0; j<b.cols(); ++j)

Eigen/src/Eigenvalues/ComplexSchur.h

@@ -336,6 +336,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
   Index iu = m_matT.cols() - 1;
   Index il;
   Index iter = 0; // number of iterations we are working on the (iu,iu) element
+  Index totalIter = 0; // number of iterations for whole matrix
 
   while(true)
   {
@@ -350,9 +351,10 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
     // if iu is zero then we are done; the whole matrix is triangularized
     if(iu==0) break;
 
-    // if we spent too many iterations on the current element, we give up
+    // if we spent too many iterations, we give up
     iter++;
-    if(iter > m_maxIterations * m_matT.cols()) break;
+    totalIter++;
+    if(totalIter > m_maxIterations * m_matT.cols()) break;
 
     // find il, the top row of the active submatrix
     il = iu-1;
@@ -382,7 +384,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
     }
   }
 
-  if(iter <= m_maxIterations * m_matT.cols()) 
+  if(totalIter <= m_maxIterations * m_matT.cols())
     m_info = Success;
   else
     m_info = NoConvergence;

Eigen/src/Eigenvalues/ComplexSchur_MKL.h

@@ -40,7 +40,7 @@ namespace Eigen {
 /** \internal Specialization for the data types supported by MKL */
 
 #define EIGEN_MKL_SCHUR_COMPLEX(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
-template<> inline\
+template<> inline \
 ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
 ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
 { \

Eigen/src/Eigenvalues/RealSchur.h

@@ -220,8 +220,9 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
   // Rows il,...,iu is the part we are working on (the active window).
   // Rows iu+1,...,end are already brought in triangular form.
   Index iu = m_matT.cols() - 1;
-  Index iter = 0; // iteration count
+  Index iter = 0;      // iteration count for current eigenvalue
-  Scalar exshift(0); // sum of exceptional shifts
+  Index totalIter = 0; // iteration count for whole matrix
+  Scalar exshift(0);   // sum of exceptional shifts
   Scalar norm = computeNormOfT();
 
   if(norm!=0)
@@ -251,14 +252,15 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
         Vector3s firstHouseholderVector(0,0,0), shiftInfo;
         computeShift(iu, iter, exshift, shiftInfo);
         iter = iter + 1;
-        if (iter > m_maxIterations * m_matT.cols()) break;
+        totalIter = totalIter + 1;
+        if (totalIter > m_maxIterations * matrix.cols()) break;
         Index im;
         initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
         performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
       }
     }
   }
-  if(iter <= m_maxIterations * m_matT.cols()) 
+  if(totalIter <= m_maxIterations * matrix.cols()) 
     m_info = Success;
   else
     m_info = NoConvergence;

Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h

@@ -743,7 +743,16 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
 //   RealScalar e2 = abs2(subdiag[end-1]);
 //   RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
   // This explain the following, somewhat more complicated, version:
-  RealScalar mu = diag[end] - (e / (td + (td>0 ? 1 : -1))) * (e / hypot(td,e));
+  RealScalar mu = diag[end];
+  if(td==0)
+    mu -= abs(e);
+  else
+  {
+    RealScalar e2 = abs2(subdiag[end-1]);
+    RealScalar h = hypot(td,e);
+    if(e2==0)  mu -= (e / (td + (td>0 ? 1 : -1))) * (e / h);
+    else       mu -= e2 / (td + (td>0 ? h : -h));
+  }
   
   RealScalar x = diag[start] - mu;
   RealScalar z = subdiag[start];

Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h

@@ -40,7 +40,7 @@ namespace Eigen {
 /** \internal Specialization for the data types supported by MKL */
 
 #define EIGEN_MKL_EIG_SELFADJ(EIGTYPE, MKLTYPE, MKLRTYPE, MKLNAME, EIGCOLROW, MKLCOLROW ) \
-template<> inline\
+template<> inline \
 SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
 SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, int options) \
 { \

Eigen/src/Geometry/AlignedBox.h

@@ -79,7 +79,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
   ~AlignedBox() {}
 
   /** \returns the dimension in which the box holds */
-  inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : Index(AmbientDimAtCompileTime); }
+  inline Index dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size() : Index(AmbientDimAtCompileTime); }
 
   /** \deprecated use isEmpty */
   inline bool isNull() const { return isEmpty(); }

Eigen/src/Geometry/Quaternion.h

@@ -193,7 +193,8 @@ public:
   *
   * \brief The quaternion class used to represent 3D orientations and rotations
   *
-  * \param _Scalar the scalar type, i.e., the type of the coefficients
+  * \tparam _Scalar the scalar type, i.e., the type of the coefficients
+  * \tparam _Options controls the memory alignement of the coeffecients. Can be \# AutoAlign or \# DontAlign. Default is AutoAlign.
   *
   * This class represents a quaternion \f$ w+xi+yj+zk \f$ that is a convenient representation of
   * orientations and rotations of objects in three dimensions. Compared to other representations
@@ -304,41 +305,29 @@ typedef Quaternion<double> Quaterniond;
 
 namespace internal {
   template<typename _Scalar, int _Options>
-  struct traits<Map<Quaternion<_Scalar>, _Options> >:
+  struct traits<Map<Quaternion<_Scalar>, _Options> > : traits<Quaternion<_Scalar, (int(_Options)&Aligned)==Aligned ? AutoAlign : DontAlign> >
-  traits<Quaternion<_Scalar, _Options> >
   {
-    typedef _Scalar Scalar;
     typedef Map<Matrix<_Scalar,4,1>, _Options> Coefficients;
-
-    typedef traits<Quaternion<_Scalar, _Options> > TraitsBase;
-    enum {
-      IsAligned = TraitsBase::IsAligned,
-
-      Flags = TraitsBase::Flags
-    };
   };
 }
 
 namespace internal {
   template<typename _Scalar, int _Options>
-  struct traits<Map<const Quaternion<_Scalar>, _Options> >:
+  struct traits<Map<const Quaternion<_Scalar>, _Options> > : traits<Quaternion<_Scalar, (int(_Options)&Aligned)==Aligned ? AutoAlign : DontAlign> >
-  traits<Quaternion<_Scalar> >
   {
-    typedef _Scalar Scalar;
     typedef Map<const Matrix<_Scalar,4,1>, _Options> Coefficients;
-
+    typedef traits<Quaternion<_Scalar, (int(_Options)&Aligned)==Aligned ? AutoAlign : DontAlign> > TraitsBase;
-    typedef traits<Quaternion<_Scalar, _Options> > TraitsBase;
     enum {
-      IsAligned = TraitsBase::IsAligned,
       Flags = TraitsBase::Flags & ~LvalueBit
     };
   };
 }
 
-/** \brief Quaternion expression mapping a constant memory buffer
+/** \ingroup Geometry_Module
+  * \brief Quaternion expression mapping a constant memory buffer
   *
-  * \param _Scalar the type of the Quaternion coefficients
+  * \tparam _Scalar the type of the Quaternion coefficients
-  * \param _Options see class Map
+  * \tparam _Options see class Map
   *
   * This is a specialization of class Map for Quaternion. This class allows to view
   * a 4 scalar memory buffer as an Eigen's Quaternion object.
@@ -371,10 +360,11 @@ class Map<const Quaternion<_Scalar>, _Options >
     const Coefficients m_coeffs;
 };
 
-/** \brief Expression of a quaternion from a memory buffer
+/** \ingroup Geometry_Module
+  * \brief Expression of a quaternion from a memory buffer
   *
-  * \param _Scalar the type of the Quaternion coefficients
+  * \tparam _Scalar the type of the Quaternion coefficients
-  * \param _Options see class Map
+  * \tparam _Options see class Map
   *
   * This is a specialization of class Map for Quaternion. This class allows to view
   * a 4 scalar memory buffer as an Eigen's  Quaternion object.

Eigen/src/LU/FullPivLU.h

@@ -577,7 +577,7 @@ struct kernel_retval<FullPivLU<_MatrixType> >
     RealScalar premultiplied_threshold = dec().maxPivot() * dec().threshold();
     Index p = 0;
     for(Index i = 0; i < dec().nonzeroPivots(); ++i)
-      if(abs(dec().matrixLU().coeff(i,i)) > premultiplied_threshold)
+      if(internal::abs(dec().matrixLU().coeff(i,i)) > premultiplied_threshold)
         pivots.coeffRef(p++) = i;
     eigen_internal_assert(p == rank());
 
@@ -645,7 +645,7 @@ struct image_retval<FullPivLU<_MatrixType> >
     RealScalar premultiplied_threshold = dec().maxPivot() * dec().threshold();
     Index p = 0;
     for(Index i = 0; i < dec().nonzeroPivots(); ++i)
-      if(abs(dec().matrixLU().coeff(i,i)) > premultiplied_threshold)
+      if(internal::abs(dec().matrixLU().coeff(i,i)) > premultiplied_threshold)
         pivots.coeffRef(p++) = i;
     eigen_internal_assert(p == rank());
 

Eigen/src/PardisoSupport/PardisoSupport.h

@@ -108,6 +108,7 @@ class PardisoImpl
     typedef Matrix<Scalar,Dynamic,1> VectorType;
     typedef Matrix<Index, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
     typedef Matrix<Index, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
+    typedef Array<Index,64,1,DontAlign> ParameterType;
     enum {
       ScalarIsComplex = NumTraits<Scalar>::IsComplex
     };
@@ -142,7 +143,7 @@ class PardisoImpl
     /** \warning for advanced usage only.
       * \returns a reference to the parameter array controlling PARDISO.
       * See the PARDISO manual to know how to use it. */
-    Array<Index,64,1>& pardisoParameterArray()
+    ParameterType& pardisoParameterArray()
     {
       return m_iparm;
     }
@@ -295,7 +296,7 @@ class PardisoImpl
     bool m_initialized, m_analysisIsOk, m_factorizationIsOk;
     Index m_type, m_msglvl;
     mutable void *m_pt[64];
-    mutable Array<Index,64,1> m_iparm;
+    mutable ParameterType m_iparm;
     mutable IntColVectorType m_perm;
     Index m_size;
     

Eigen/src/QR/ColPivHouseholderQR.h

@@ -56,6 +56,12 @@ template<typename _MatrixType> class ColPivHouseholderQR
     typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
     typedef typename internal::plain_row_type<MatrixType, RealScalar>::type RealRowVectorType;
     typedef typename HouseholderSequence<MatrixType,HCoeffsType>::ConjugateReturnType HouseholderSequenceType;
+    
+  private:
+    
+    typedef typename PermutationType::Index PermIndexType;
+    
+  public:
 
     /**
     * \brief Default Constructor.
@@ -81,7 +87,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
     ColPivHouseholderQR(Index rows, Index cols)
       : m_qr(rows, cols),
         m_hCoeffs((std::min)(rows,cols)),
-        m_colsPermutation(cols),
+        m_colsPermutation(PermIndexType(cols)),
         m_colsTranspositions(cols),
         m_temp(cols),
         m_colSqNorms(cols),
@@ -91,7 +97,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
     ColPivHouseholderQR(const MatrixType& matrix)
       : m_qr(matrix.rows(), matrix.cols()),
         m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
-        m_colsPermutation(matrix.cols()),
+        m_colsPermutation(PermIndexType(matrix.cols())),
         m_colsTranspositions(matrix.cols()),
         m_temp(matrix.cols()),
         m_colSqNorms(matrix.cols()),
@@ -436,9 +442,9 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
     m_colSqNorms.tail(cols-k-1) -= m_qr.row(k).tail(cols-k-1).cwiseAbs2();
   }
 
-  m_colsPermutation.setIdentity(cols);
+  m_colsPermutation.setIdentity(PermIndexType(cols));
-  for(Index k = 0; k < m_nonzero_pivots; ++k)
+  for(PermIndexType k = 0; k < m_nonzero_pivots; ++k)
-    m_colsPermutation.applyTranspositionOnTheRight(k, m_colsTranspositions.coeff(k));
+    m_colsPermutation.applyTranspositionOnTheRight(PermIndexType(k), PermIndexType(m_colsTranspositions.coeff(k)));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
   m_isInitialized = true;

Eigen/src/QR/ColPivHouseholderQR_MKL.h

@@ -41,7 +41,7 @@ namespace Eigen {
 /** \internal Specialization for the data types supported by MKL */
 
 #define EIGEN_MKL_QR_COLPIV(EIGTYPE, MKLTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
-template<> inline\
+template<> inline \
 ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >& \
 ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >::compute( \
               const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix) \

Eigen/src/QR/FullPivHouseholderQR.h

@@ -63,9 +63,10 @@ template<typename _MatrixType> class FullPivHouseholderQR
     typedef typename MatrixType::Index Index;
     typedef internal::FullPivHouseholderQRMatrixQReturnType<MatrixType> MatrixQReturnType;
     typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
-    typedef Matrix<Index, 1, ColsAtCompileTime, RowMajor, 1, MaxColsAtCompileTime> IntRowVectorType;
+    typedef Matrix<Index, 1,
+                   EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime,RowsAtCompileTime), RowMajor, 1,
+                   EIGEN_SIZE_MIN_PREFER_FIXED(MaxColsAtCompileTime,MaxRowsAtCompileTime)> IntDiagSizeVectorType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationType;
-    typedef typename internal::plain_col_type<MatrixType, Index>::type IntColVectorType;
     typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
     typedef typename internal::plain_col_type<MatrixType>::type ColVectorType;
 
@@ -158,7 +159,7 @@ template<typename _MatrixType> class FullPivHouseholderQR
       return m_cols_permutation;
     }
 
-    const IntColVectorType& rowsTranspositions() const
+    const IntDiagSizeVectorType& rowsTranspositions() const
     {
       eigen_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
       return m_rows_transpositions;
@@ -348,8 +349,8 @@ template<typename _MatrixType> class FullPivHouseholderQR
   protected:
     MatrixType m_qr;
     HCoeffsType m_hCoeffs;
-    IntColVectorType m_rows_transpositions;
+    IntDiagSizeVectorType m_rows_transpositions;
-    IntRowVectorType m_cols_transpositions;
+    IntDiagSizeVectorType m_cols_transpositions;
     PermutationType m_cols_permutation;
     RowVectorType m_temp;
     bool m_isInitialized, m_usePrescribedThreshold;
@@ -389,8 +390,8 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons
 
   m_precision = NumTraits<Scalar>::epsilon() * size;
 
-  m_rows_transpositions.resize(matrix.rows());
+  m_rows_transpositions.resize(size);
-  m_cols_transpositions.resize(matrix.cols());
+  m_cols_transpositions.resize(size);
   Index number_of_transpositions = 0;
 
   RealScalar biggest(0);
@@ -520,14 +521,14 @@ template<typename MatrixType> struct FullPivHouseholderQRMatrixQReturnType
 {
 public:
   typedef typename MatrixType::Index Index;
-  typedef typename internal::plain_col_type<MatrixType, Index>::type IntColVectorType;
+  typedef typename FullPivHouseholderQR<MatrixType>::IntDiagSizeVectorType IntDiagSizeVectorType;
   typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
   typedef Matrix<typename MatrixType::Scalar, 1, MatrixType::RowsAtCompileTime, RowMajor, 1,
                  MatrixType::MaxRowsAtCompileTime> WorkVectorType;
 
   FullPivHouseholderQRMatrixQReturnType(const MatrixType&       qr,
                                         const HCoeffsType&      hCoeffs,
-                                        const IntColVectorType& rowsTranspositions)
+                                        const IntDiagSizeVectorType& rowsTranspositions)
     : m_qr(qr),
       m_hCoeffs(hCoeffs),
       m_rowsTranspositions(rowsTranspositions)
@@ -566,7 +567,7 @@ public:
 protected:
   typename MatrixType::Nested m_qr;
   typename HCoeffsType::Nested m_hCoeffs;
-  typename IntColVectorType::Nested m_rowsTranspositions;
+  typename IntDiagSizeVectorType::Nested m_rowsTranspositions;
 };
 
 } // end namespace internal

Eigen/src/SVD/JacobiSVD.h

@@ -833,17 +833,13 @@ struct solve_retval<JacobiSVD<_MatrixType, QRPreconditioner>, Rhs>
     // A = U S V^*
     // So A^{-1} = V S^{-1} U^*
 
+    Matrix<Scalar, Dynamic, Rhs::ColsAtCompileTime, 0, _MatrixType::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime> tmp;
     Index diagSize = (std::min)(dec().rows(), dec().cols());
-    typename JacobiSVDType::SingularValuesType invertedSingVals(diagSize);
-
     Index nonzeroSingVals = dec().nonzeroSingularValues();
-    invertedSingVals.head(nonzeroSingVals) = dec().singularValues().head(nonzeroSingVals).array().inverse();
+    
-    invertedSingVals.tail(diagSize - nonzeroSingVals).setZero();
+    tmp.noalias() = dec().matrixU().leftCols(nonzeroSingVals).adjoint() * rhs();
-
+    tmp = dec().singularValues().head(nonzeroSingVals).asDiagonal().inverse() * tmp;
-    dst = dec().matrixV().leftCols(diagSize)
+    dst = dec().matrixV().leftCols(nonzeroSingVals) * tmp;
-        * invertedSingVals.asDiagonal()
-        * dec().matrixU().leftCols(diagSize).adjoint()
-        * rhs();
   }
 };
 } // end namespace internal

Eigen/src/SVD/JacobiSVD_MKL.h

@@ -40,7 +40,7 @@ namespace Eigen {
 /** \internal Specialization for the data types supported by MKL */
 
 #define EIGEN_MKL_SVD(EIGTYPE, MKLTYPE, MKLRTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
-template<> inline\
+template<> inline \
 JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>& \
 JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) \
 { \

Eigen/src/SparseCore/SparseDiagonalProduct.h

@@ -126,11 +126,15 @@ class sparse_diagonal_product_inner_iterator_selector
       SparseInnerVectorSet<Rhs,1>,
       typename Lhs::DiagonalVectorType>::InnerIterator Base;
     typedef typename Lhs::Index Index;
+    Index m_outer;
   public:
     inline sparse_diagonal_product_inner_iterator_selector(
               const SparseDiagonalProductType& expr, Index outer)
-      : Base(expr.rhs().innerVector(outer) .cwiseProduct(expr.lhs().diagonal()), 0)
+      : Base(expr.rhs().innerVector(outer) .cwiseProduct(expr.lhs().diagonal()), 0), m_outer(outer)
     {}
+    
+    inline Index outer() const { return m_outer; }
+    inline Index col() const { return m_outer; }
 };
 
 template<typename Lhs, typename Rhs, typename SparseDiagonalProductType>
@@ -160,11 +164,15 @@ class sparse_diagonal_product_inner_iterator_selector
       SparseInnerVectorSet<Lhs,1>,
       Transpose<const typename Rhs::DiagonalVectorType> >::InnerIterator Base;
     typedef typename Lhs::Index Index;
+    Index m_outer;
   public:
     inline sparse_diagonal_product_inner_iterator_selector(
               const SparseDiagonalProductType& expr, Index outer)
-      : Base(expr.lhs().innerVector(outer) .cwiseProduct(expr.rhs().diagonal().transpose()), 0)
+      : Base(expr.lhs().innerVector(outer) .cwiseProduct(expr.rhs().diagonal().transpose()), 0), m_outer(outer)
     {}
+    
+    inline Index outer() const { return m_outer; }
+    inline Index row() const { return m_outer; }
 };
 
 } // end namespace internal

Eigen/src/SparseCore/SparseMatrix.h

@@ -572,6 +572,16 @@ class SparseMatrix
       *this = other.derived();
     }
 
+    /** \brief Copy constructor with in-place evaluation */
+    template<typename OtherDerived>
+    SparseMatrix(const ReturnByValue<OtherDerived>& other)
+      : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
+    {
+      check_template_parameters();
+      initAssignment(other);
+      other.evalTo(*this);
+    }
+
     /** Swaps the content of two sparse matrices of the same type.
       * This is a fast operation that simply swaps the underlying pointers and parameters. */
     inline void swap(SparseMatrix& other)
@@ -613,7 +623,10 @@ class SparseMatrix
     
     template<typename OtherDerived>
     inline SparseMatrix& operator=(const ReturnByValue<OtherDerived>& other)
-    { return Base::operator=(other.derived()); }
+    {
+      initAssignment(other);
+      return Base::operator=(other.derived());
+    }
     
     template<typename OtherDerived>
     inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other)
@@ -623,7 +636,6 @@ class SparseMatrix
     template<typename OtherDerived>
     EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other)
     {
-      initAssignment(other.derived());
       const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
       if (needToTranspose)
       {
@@ -635,40 +647,45 @@ class SparseMatrix
         typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
         OtherCopy otherCopy(other.derived());
 
-        Eigen::Map<Matrix<Index, Dynamic, 1> > (m_outerIndex,outerSize()).setZero();
+        SparseMatrix dest(other.rows(),other.cols());
+        Eigen::Map<Matrix<Index, Dynamic, 1> > (dest.m_outerIndex,dest.outerSize()).setZero();
+
         // pass 1
         // FIXME the above copy could be merged with that pass
         for (Index j=0; j<otherCopy.outerSize(); ++j)
           for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
-            ++m_outerIndex[it.index()];
+            ++dest.m_outerIndex[it.index()];
 
         // prefix sum
         Index count = 0;
-        VectorXi positions(outerSize());
+        VectorXi positions(dest.outerSize());
-        for (Index j=0; j<outerSize(); ++j)
+        for (Index j=0; j<dest.outerSize(); ++j)
         {
-          Index tmp = m_outerIndex[j];
+          Index tmp = dest.m_outerIndex[j];
-          m_outerIndex[j] = count;
+          dest.m_outerIndex[j] = count;
           positions[j] = count;
           count += tmp;
         }
-        m_outerIndex[outerSize()] = count;
+        dest.m_outerIndex[dest.outerSize()] = count;
         // alloc
-        m_data.resize(count);
+        dest.m_data.resize(count);
         // pass 2
         for (Index j=0; j<otherCopy.outerSize(); ++j)
         {
           for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
           {
             Index pos = positions[it.index()]++;
-            m_data.index(pos) = j;
+            dest.m_data.index(pos) = j;
-            m_data.value(pos) = it.value();
+            dest.m_data.value(pos) = it.value();
           }
         }
+        this->swap(dest);
         return *this;
       }
       else
       {
+        if(other.isRValue())
+          initAssignment(other.derived());
         // there is no special optimization
         return Base::operator=(other.derived());
       }
@@ -888,6 +905,7 @@ protected:
         m_data.value(p) = m_data.value(p-1);
         --p;
       }
+      eigen_assert((p<=startId || m_data.index(p-1)!=inner) && "you cannot insert an element that already exist, you must call coeffRef to this end");
 
       m_innerNonZeros[outer]++;
 

Eigen/src/SparseCore/SparseSelfAdjointView.h

@@ -209,6 +209,7 @@ class SparseSelfAdjointTimeDenseProduct
 
     template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
     {
+      EIGEN_ONLY_USED_FOR_DEBUG(alpha);
       // TODO use alpha
       eigen_assert(alpha==Scalar(1) && "alpha != 1 is not implemented yet, sorry");
       typedef typename internal::remove_all<Lhs>::type _Lhs;

Eigen/src/SparseCore/SparseUtil.h

@@ -113,9 +113,10 @@ template<typename T,int Rows> struct sparse_eval<T,Rows,1> {
 
 template<typename T,int Rows,int Cols> struct sparse_eval {
     typedef typename traits<T>::Scalar _Scalar;
-    enum { _Flags = traits<T>::Flags };
+    typedef typename traits<T>::Index _Index;
+    enum { _Options = ((traits<T>::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor };
   public:
-    typedef SparseMatrix<_Scalar, _Flags> type;
+    typedef SparseMatrix<_Scalar, _Options, _Index> type;
 };
 
 template<typename T> struct sparse_eval<T,1,1> {

Eigen/src/SparseCore/SparseVector.h

@@ -202,7 +202,7 @@ class SparseVector
     }
 
     inline SparseVector(const SparseVector& other)
-      : m_size(0)
+      : SparseBase(other), m_size(0)
     {
       *this = other.derived();
     }
@@ -230,7 +230,8 @@ class SparseVector
     template<typename OtherDerived>
     inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other)
     {
-      if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
+      if ( (bool(OtherDerived::IsVectorAtCompileTime) && int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
+          || ((!bool(OtherDerived::IsVectorAtCompileTime)) && ( bool(IsColVector) ? other.cols()>1 : other.rows()>1 )))
         return assign(other.transpose());
       else
         return assign(other);

Eigen/src/SuperLUSupport/SuperLUSupport.h

@@ -496,8 +496,8 @@ class SuperLU : public SuperLUBase<_MatrixType,SuperLU<_MatrixType> >
 
     SuperLU(const MatrixType& matrix) : Base()
     {
-      Base::init();
+      init();
-      compute(matrix);
+      Base::compute(matrix);
     }
 
     ~SuperLU()
@@ -833,7 +833,7 @@ class SuperILU : public SuperLUBase<_MatrixType,SuperILU<_MatrixType> >
     SuperILU(const MatrixType& matrix) : Base()
     {
       init();
-      compute(matrix);
+      Base::compute(matrix);
     }
 
     ~SuperILU()

Eigen/src/plugins/ArrayCwiseBinaryOps.h

@@ -33,7 +33,8 @@ EIGEN_MAKE_CWISE_BINARY_OP(min,internal::scalar_min_op)
   *
   * \sa max()
   */
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const ConstantReturnType>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived,
+                                        const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> >
 (min)(const Scalar &other) const
 {
   return (min)(Derived::PlainObject::Constant(rows(), cols(), other));
@@ -52,7 +53,8 @@ EIGEN_MAKE_CWISE_BINARY_OP(max,internal::scalar_max_op)
   *
   * \sa min()
   */
-EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const ConstantReturnType>
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived,
+                                        const CwiseNullaryOp<internal::scalar_constant_op<Scalar>, PlainObject> >
 (max)(const Scalar &other) const
 {
   return (max)(Derived::PlainObject::Constant(rows(), cols(), other));

Eigen/src/plugins/ArrayCwiseUnaryOps.h

@@ -200,3 +200,4 @@ EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator<=,  std::less_equal)
 EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>,   std::greater)
 EIGEN_MAKE_SCALAR_CWISE_UNARY_OP(operator>=,  std::greater_equal)
 
+

ci/build.linux.gitlab-ci.yml

@@ -0,0 +1,30 @@
+# Base configuration for linux cross-compilation.
+.build:linux:cross:
+  extends: .common:linux:cross
+  stage: build
+  variables:
+    EIGEN_CI_BUILD_TARGET: buildtests
+  script:
+    - . ci/scripts/build.linux.script.sh
+  tags:
+    - saas-linux-2xlarge-amd64
+  rules:
+    - if: $CI_PIPELINE_SOURCE == "schedule" && $CI_PROJECT_NAMESPACE == "libeigen"
+    - if: $CI_PIPELINE_SOURCE == "web" && $CI_PROJECT_NAMESPACE == "libeigen"
+    - if: $CI_PIPELINE_SOURCE == "merge_request_event" && $CI_PROJECT_NAMESPACE == "libeigen" && $CI_MERGE_REQUEST_LABELS =~ "/all-tests/"
+  cache:
+    key: "$CI_JOB_NAME_SLUG-$CI_COMMIT_REF_SLUG-BUILD"
+    paths:
+      - ${EIGEN_CI_BUILDDIR}/
+
+build:linux:docs:
+  extends: .build:linux:cross
+  variables:
+    EIGEN_CI_TARGET_ARCH: any
+    EIGEN_CI_BUILD_TARGET: doc
+    EIGEN_CI_INSTALL: ca-certificates clang flex python3 bison graphviz
+    EIGEN_CI_C_COMPILER: clang
+    EIGEN_CI_CXX_COMPILER: clang++
+    EIGEN_CI_BEFORE_SCRIPT: ". ci/scripts/build_and_install_doxygen.sh Release_1_13_2"
+  rules:
+    - if: $CI_PIPELINE_SOURCE == "push" && $CI_PROJECT_NAMESPACE == "libeigen"

ci/common.gitlab-ci.yml

@@ -0,0 +1,24 @@
+# Base configuration for linux builds and tests.
+.common:linux:cross:
+  image: ubuntu:20.04
+  variables:
+    EIGEN_CI_TARGET_ARCH: ""
+    EIGEN_CI_ADDITIONAL_ARGS: ""
+    # If host matches target, use the following:
+    EIGEN_CI_C_COMPILER: ""
+    EIGEN_CI_CXX_COMPILER: ""
+    EIGEN_CI_INSTALL: "${EIGEN_CI_C_COMPILER} ${EIGEN_CI_CXX_COMPILER}"
+    # If host does not match the target, use the following:
+    EIGEN_CI_CROSS_TARGET_TRIPLE: ""
+    EIGEN_CI_CROSS_C_COMPILER: ${EIGEN_CI_C_COMPILER}
+    EIGEN_CI_CROSS_CXX_COMPILER: ${EIGEN_CI_CXX_COMPILER}
+    EIGEN_CI_CROSS_INSTALL: "${EIGEN_CI_CROSS_C_COMPILER} ${EIGEN_CI_CROSS_CXX_COMPILER}"
+  before_script:
+    # Call script in current shell - it sets up some environment variables.
+    - . ci/scripts/common.linux.before_script.sh
+  artifacts:
+    when: always
+    name: "$CI_JOB_NAME_SLUG-$CI_COMMIT_REF_SLUG"
+    paths:
+      - ${EIGEN_CI_BUILDDIR}/
+    expire_in: 5 days

ci/deploy.gitlab-ci.yml

@@ -0,0 +1,25 @@
+# Upload docs if pipeline succeeded.
+deploy:docs:
+  stage: deploy
+  image: busybox
+  dependencies: [ build:linux:docs ]
+  variables:
+    PAGES_PREFIX: docs-nightly
+  script:
+    - echo "Deploying site to $CI_PAGES_URL"
+    - mv ${EIGEN_CI_BUILDDIR}/doc/html public
+  pages:
+    path_prefix: $PAGES_PREFIX
+    expire_in: never
+  artifacts:
+    name: "$CI_JOB_NAME_SLUG-$CI_COMMIT_REF_SLUG"
+    paths:
+      - public
+  tags:
+    - saas-linux-small-amd64
+  rules:
+    - if: $CI_PIPELINE_SOURCE == "schedule" && $CI_PROJECT_NAMESPACE == "libeigen"
+    - if: $CI_PIPELINE_SOURCE == "web" && $CI_PROJECT_NAMESPACE == "libeigen"
+    - if: $CI_PIPELINE_SOURCE == "push" && $CI_PROJECT_NAMESPACE == "libeigen"
+      variables:
+        PAGES_PREFIX: docs-$CI_COMMIT_REF_NAME

ci/scripts/build.linux.script.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+set -x
+
+# Create and enter build directory.
+rootdir=`pwd`
+mkdir -p ${EIGEN_CI_BUILDDIR}
+cd ${EIGEN_CI_BUILDDIR}
+
+# Configure build.
+cmake -G Ninja                                                   \
+  -DCMAKE_CXX_COMPILER=${EIGEN_CI_CXX_COMPILER}                  \
+  -DCMAKE_C_COMPILER=${EIGEN_CI_C_COMPILER}                      \
+  -DCMAKE_CXX_COMPILER_TARGET=${EIGEN_CI_CXX_COMPILER_TARGET}    \
+  ${EIGEN_CI_ADDITIONAL_ARGS} ${rootdir}
+
+target=""
+if [[ ${EIGEN_CI_BUILD_TARGET} ]]; then
+  target="--target ${EIGEN_CI_BUILD_TARGET}"
+fi
+
+# Builds (particularly gcc) sometimes get killed, potentially when running
+# out of resources.  In that case, keep trying to build the remaining
+# targets (k0), then try to build again with a single thread (j1) to minimize
+# resource use.
+cmake --build . ${target} -- -k0 || cmake --build . ${target} -- -k0 -j1
+
+# Return to root directory.
+cd ${rootdir}
+
+set +x

ci/scripts/build_and_install_doxygen.sh

@@ -0,0 +1,6 @@
+git clone --depth 1 --branch $1 https://github.com/doxygen/doxygen.git
+cmake -B doxygen/.build -G Ninja                                 \
+  -DCMAKE_CXX_COMPILER=${EIGEN_CI_CXX_COMPILER}                  \
+  -DCMAKE_C_COMPILER=${EIGEN_CI_C_COMPILER}                      \
+  doxygen
+cmake --build doxygen/.build -t install

ci/scripts/common.linux.before_script.sh

@@ -0,0 +1,46 @@
+#!/bin/bash
+
+set -x
+
+echo "Running ${CI_JOB_NAME}"
+
+# Get architecture and display CI configuration.
+export ARCH=`uname -m`
+export NPROC=`nproc`
+echo "arch=$ARCH, target=${EIGEN_CI_TARGET_ARCH}"
+echo "Processors: ${NPROC}"
+echo "CI Variables:"
+export | grep EIGEN
+
+# Set noninteractive, otherwise tzdata may be installed and prompt for a
+# geographical region.
+export DEBIAN_FRONTEND=noninteractive
+apt-get update -y > /dev/null
+apt-get install -y --no-install-recommends ninja-build cmake git > /dev/null
+
+# Install required dependencies and set up compilers.
+# These are required even for testing to ensure that dynamic runtime libraries
+# are available.
+if [[ "$ARCH" == "${EIGEN_CI_TARGET_ARCH}" || "${EIGEN_CI_TARGET_ARCH}" == "any" ]]; then
+  apt-get install -y --no-install-recommends ${EIGEN_CI_INSTALL} > /dev/null;
+  export EIGEN_CI_CXX_IMPLICIT_INCLUDE_DIRECTORIES="";
+  export EIGEN_CI_CXX_COMPILER_TARGET="";
+else
+  apt-get install -y --no-install-recommends ${EIGEN_CI_CROSS_INSTALL} > /dev/null;
+  export EIGEN_CI_C_COMPILER=${EIGEN_CI_CROSS_C_COMPILER};
+  export EIGEN_CI_CXX_COMPILER=${EIGEN_CI_CROSS_CXX_COMPILER};
+  export EIGEN_CI_CXX_COMPILER_TARGET=${EIGEN_CI_CROSS_TARGET_TRIPLE};
+  # Tell the compiler where to find headers and libraries if using clang.
+  # NOTE: this breaks GCC since it messes with include path order
+  #       (https://gcc.gnu.org/bugzilla/show_bug.cgi?id=70129)
+  if [[ "${EIGEN_CI_CROSS_CXX_COMPILER}" == *"clang"* ]]; then
+    export CPLUS_INCLUDE_PATH="/usr/${EIGEN_CI_CROSS_TARGET_TRIPLE}/include";
+    export LIBRARY_PATH="/usr/${EIGEN_CI_CROSS_TARGET_TRIPLE}/lib64";
+  fi
+fi
+
+echo "Compilers: ${EIGEN_CI_C_COMPILER} ${EIGEN_CI_CXX_COMPILER}"
+
+if [ -n "$EIGEN_CI_BEFORE_SCRIPT" ]; then eval "$EIGEN_CI_BEFORE_SCRIPT"; fi
+
+set +x

cmake/FindUmfpack.cmake

@@ -19,8 +19,9 @@ find_path(UMFPACK_INCLUDES
 find_library(UMFPACK_LIBRARIES umfpack PATHS $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
 
 if(UMFPACK_LIBRARIES)
-
+  if (NOT UMFPACK_LIBDIR)
-  get_filename_component(UMFPACK_LIBDIR ${UMFPACK_LIBRARIES} PATH)
+    get_filename_component(UMFPACK_LIBDIR ${UMFPACK_LIBRARIES} PATH)
+  endif(NOT UMFPACK_LIBDIR)
 
   find_library(AMD_LIBRARY amd PATHS ${UMFPACK_LIBDIR} $ENV{UMFPACKDIR} ${LIB_INSTALL_DIR})
   if (AMD_LIBRARY)

cmake/language_support.cmake

@@ -24,6 +24,8 @@ function(workaround_9220 language language_works)
   set(text
     "project(test NONE)
     cmake_minimum_required(VERSION 2.6.0)
+    set (CMAKE_Fortran_FLAGS \"${CMAKE_Fortran_FLAGS}\")
+    set (CMAKE_EXE_LINKER_FLAGS \"${CMAKE_EXE_LINKER_FLAGS}\")
     enable_language(${language} OPTIONAL)
   ")
   file(REMOVE_RECURSE ${CMAKE_BINARY_DIR}/language_tests/${language})

debug/gdb/printers.py

@@ -51,12 +51,12 @@ class EigenMatrixPrinter:
 		template_params = m.split(',')
 		template_params = map(lambda x:x.replace(" ", ""), template_params)
 		
-		if template_params[1] == '-0x00000000000000001' or template_params[1] == '-0x000000001':
+		if template_params[1] == '-0x00000000000000001' or template_params[1] == '-0x000000001' or template_params[1] == '-1':
 			self.rows = val['m_storage']['m_rows']
 		else:
 			self.rows = int(template_params[1])
 		
-		if template_params[2] == '-0x00000000000000001' or template_params[2] == '-0x000000001':
+		if template_params[2] == '-0x00000000000000001' or template_params[2] == '-0x000000001' or template_params[2] == '-1':
 			self.cols = val['m_storage']['m_cols']
 		else:
 			self.cols = int(template_params[2])

demos/opengl/CMakeLists.txt

@@ -1,20 +1,28 @@
-find_package(Qt4 REQUIRED)
+find_package(Qt4)
-find_package(OpenGL REQUIRED)
+find_package(OpenGL)
 
-set(QT_USE_QTOPENGL TRUE)
+if(QT4_FOUND AND OPENGL_FOUND)
-include(${QT_USE_FILE})
 
-set(CMAKE_INCLUDE_CURRENT_DIR ON)
+  set(QT_USE_QTOPENGL TRUE)
+  include(${QT_USE_FILE})
 
-include_directories( ${QT_INCLUDE_DIR} )
+  set(CMAKE_INCLUDE_CURRENT_DIR ON)
 
-set(quaternion_demo_SRCS  gpuhelper.cpp icosphere.cpp camera.cpp trackball.cpp quaternion_demo.cpp)
+  include_directories( ${QT_INCLUDE_DIR} )
 
-qt4_automoc(${quaternion_demo_SRCS})
+  set(quaternion_demo_SRCS  gpuhelper.cpp icosphere.cpp camera.cpp trackball.cpp quaternion_demo.cpp)
 
-add_executable(quaternion_demo ${quaternion_demo_SRCS})
+  qt4_automoc(${quaternion_demo_SRCS})
-add_dependencies(demos quaternion_demo)
 
-target_link_libraries(quaternion_demo
+  add_executable(quaternion_demo ${quaternion_demo_SRCS})
-  ${QT_QTCORE_LIBRARY}    ${QT_QTGUI_LIBRARY}
+  add_dependencies(demos quaternion_demo)
-  ${QT_QTOPENGL_LIBRARY}  ${OPENGL_LIBRARIES} )
+
+  target_link_libraries(quaternion_demo
+    ${QT_QTCORE_LIBRARY}    ${QT_QTGUI_LIBRARY}
+    ${QT_QTOPENGL_LIBRARY}  ${OPENGL_LIBRARIES} )
+
+else()
+
+  message(STATUS "OpenGL demo disabled because Qt4 and/or OpenGL have not been found.")
+
+endif()

doc/C01_TutorialMatrixClass.dox

@@ -98,8 +98,8 @@ Matrix3f a;
 MatrixXf b;
 \endcode
 Here,
-\li \c a is a 3x3 matrix, with a static float[9] array of uninitialized coefficients,
+\li \c a is a 3-by-3 matrix, with a plain float[9] array of uninitialized coefficients,
-\li \c b is a dynamic-size matrix whose size is currently 0x0, and whose array of
+\li \c b is a dynamic-size matrix whose size is currently 0-by-0, and whose array of
 coefficients hasn't yet been allocated at all.
 
 Constructors taking sizes are also available. For matrices, the number of rows is always passed first.
@@ -216,7 +216,7 @@ The simple answer is: use fixed
 sizes for very small sizes where you can, and use dynamic sizes for larger sizes or where you have to. For small sizes,
 especially for sizes smaller than (roughly) 16, using fixed sizes is hugely beneficial
 to performance, as it allows Eigen to avoid dynamic memory allocation and to unroll
-loops. Internally, a fixed-size Eigen matrix is just a plain static array, i.e. doing
+loops. Internally, a fixed-size Eigen matrix is just a plain array, i.e. doing
 \code Matrix4f mymatrix; \endcode
 really amounts to just doing
 \code float mymatrix[16]; \endcode
@@ -231,8 +231,9 @@ member variables.
 The limitation of using fixed sizes, of course, is that this is only possible
 when you know the sizes at compile time. Also, for large enough sizes, say for sizes
 greater than (roughly) 32, the performance benefit of using fixed sizes becomes negligible.
-Worse, trying to create a very large matrix using fixed sizes could result in a stack overflow,
+Worse, trying to create a very large matrix using fixed sizes inside a function could result in a
-since Eigen will try to allocate the array as a static array, which by default goes on the stack.
+stack overflow, since Eigen will try to allocate the array automatically as a local variable, and
+this is normally done on the stack.
 Finally, depending on circumstances, Eigen can also be more aggressive trying to vectorize
 (use SIMD instructions) when dynamic sizes are used, see \ref TopicVectorization "Vectorization".
 

doc/C08_TutorialGeometry.dox

@@ -178,7 +178,7 @@ matNxN = t.linear();
 \endcode</td></tr>
 <tr><td>
 extract the rotation matrix</td><td>\code
-matNxN = t.extractRotation();
+matNxN = t.rotation();
 \endcode</td></tr>
 </table>
 

doc/C09_TutorialSparse.dox

@@ -130,7 +130,7 @@ Describing the \a buildProblem and \a save functions is out of the scope of this
 
 The SparseMatrix and SparseVector classes take three template arguments:
  * the scalar type (e.g., double)
- * the storage order (ColMajor or RowMajor, the default is RowMajor)
+ * the storage order (ColMajor or RowMajor, the default is ColMajor)
  * the inner index type (default is \c int).
 
 As for dense Matrix objects, constructors takes the size of the object.

doc/CMakeLists.txt

@@ -34,6 +34,7 @@ set(examples_targets "")
 set(snippets_targets "")
 
 add_definitions("-DEIGEN_MAKING_DOCS")
+add_custom_target(all_examples)
 
 add_subdirectory(examples)
 add_subdirectory(special_examples)
@@ -71,7 +72,8 @@ add_custom_target(doc ALL
   COMMAND doxygen
   COMMAND doxygen Doxyfile-unsupported # run doxygen twice to get proper eigen <=> unsupported cross references
   COMMAND ${CMAKE_COMMAND} -E rename html eigen-doc
-  COMMAND ${CMAKE_COMMAND} -E tar cvfz eigen-doc/eigen-doc.tgz eigen-doc/*.html eigen-doc/*.map eigen-doc/*.png eigen-doc/*.css eigen-doc/*.js eigen-doc/*.txt eigen-doc/unsupported
+  COMMAND ${CMAKE_COMMAND} -E remove eigen-doc/eigen-doc.tgz
+  COMMAND ${CMAKE_COMMAND} -E tar cvfz eigen-doc/eigen-doc.tgz eigen-doc
   COMMAND ${CMAKE_COMMAND} -E rename eigen-doc html
   WORKING_DIRECTORY ${Eigen_BINARY_DIR}/doc)
 

doc/Doxyfile.in

@@ -302,7 +302,7 @@ TYPEDEF_HIDES_STRUCT   = NO
 # Private class members and static file members will be hidden unless
 # the EXTRACT_PRIVATE and EXTRACT_STATIC tags are set to YES
 
-EXTRACT_ALL            = YES
+EXTRACT_ALL            = NO
 
 # If the EXTRACT_PRIVATE tag is set to YES all private members of a class
 # will be included in the documentation.
@@ -797,9 +797,7 @@ HTML_HEADER             = "${Eigen_BINARY_DIR}/doc/eigendoxy_header.html"
 # each generated HTML page. If it is left blank doxygen will generate a
 # standard footer.
 
-# the footer has not been customized yet, so let's use the default one
+HTML_FOOTER             = "${Eigen_BINARY_DIR}/doc/eigendoxy_footer.html"
-# ${Eigen_BINARY_DIR}/doc/eigendoxy_footer.html
-HTML_FOOTER             =
 
 # The HTML_STYLESHEET tag can be used to specify a user-defined cascading
 # style sheet that is used by each HTML page. It can be used to

doc/QuickReference.dox

@@ -55,7 +55,7 @@ All combinations are allowed: you can have a matrix with a fixed number of rows
 Matrix<double, 6, Dynamic>                  // Dynamic number of columns (heap allocation)
 Matrix<double, Dynamic, 2>                  // Dynamic number of rows (heap allocation)
 Matrix<double, Dynamic, Dynamic, RowMajor>  // Fully dynamic, row major (heap allocation)
-Matrix<double, 13, 3>                       // Fully fixed (static allocation)
+Matrix<double, 13, 3>                       // Fully fixed (usually allocated on stack)
 \endcode
 
 In most cases, you can simply use one of the convenience typedefs for \ref matrixtypedefs "matrices" and \ref arraytypedefs "arrays". Some examples:
@@ -490,7 +490,7 @@ Read-write access to sub-vectors:
 <tr><td>\code vec1.head(n)\endcode</td><td>\code vec1.head<n>()\endcode</td><td>the first \c n coeffs </td></tr>
 <tr><td>\code vec1.tail(n)\endcode</td><td>\code vec1.tail<n>()\endcode</td><td>the last \c n coeffs </td></tr>
 <tr><td>\code vec1.segment(pos,n)\endcode</td><td>\code vec1.segment<n>(pos)\endcode</td>
-    <td>the \c n coeffs in \n the range [\c pos : \c pos + \c n [</td></tr>
+    <td>the \c n coeffs in the \n range [\c pos : \c pos + \c n - 1]</td></tr>
 <tr class="alt"><td colspan="3">
 
 Read-write access to sub-matrices:</td></tr>

doc/TopicLinearAlgebraDecompositions.dox

@@ -6,7 +6,6 @@ namespace Eigen {
 \section TopicLinAlgBigTable Catalogue of decompositions offered by Eigen
 
 <table class="manual-vl">
-
     <tr>
         <th class="meta"></th>
         <th class="meta" colspan="5">Generic information, not Eigen-specific</th>

doc/eigendoxy_footer.html.in

@@ -1,5 +1,17 @@
+<hr class="footer"/>
+
+<!-- Piwik --> 
+<script type="text/javascript">
+var pkBaseURL = (("https:" == document.location.protocol) ? "https://stats.sylphide-consulting.com/piwik/" : "http://stats.sylphide-consulting.com/piwik/");
+document.write(unescape("%3Cscript src='" + pkBaseURL + "piwik.js' type='text/javascript'%3E%3C/script%3E"));
+</script><script type="text/javascript">
+try {
+var piwikTracker = Piwik.getTracker(pkBaseURL + "piwik.php", 20);
+piwikTracker.trackPageView();
+piwikTracker.enableLinkTracking();
+} catch( err ) {}
+</script><noscript><p><img src="http://stats.sylphide-consulting.com/piwik/piwik.php?idsite=20" style="border:0" alt="" /></p></noscript>
+<!-- End Piwik Tracking Code -->
 
-<hr class="footer"/><address class="footer"><small>
-<a href="http://www.doxygen.org/index.html"><img class="footer" src="$relpath$doxygen.png" alt="doxygen"/></a></small></address>
 </body>
-</html>
+</html>

doc/examples/CMakeLists.txt

@@ -1,7 +1,5 @@
 file(GLOB examples_SRCS "*.cpp")
 
-add_custom_target(all_examples)
-
 foreach(example_src ${examples_SRCS})
   get_filename_component(example ${example_src} NAME_WE)
   add_executable(${example} ${example_src})

doc/examples/QuickStart_example2_dynamic.cpp

@@ -6,10 +6,10 @@ using namespace std;
 
 int main()
 {
-  MatrixXf m = MatrixXf::Random(3,3);
+  MatrixXd m = MatrixXd::Random(3,3);
-  m = (m + MatrixXf::Constant(3,3,1.2)) * 50;
+  m = (m + MatrixXd::Constant(3,3,1.2)) * 50;
   cout << "m =" << endl << m << endl;
-  VectorXf v(3);
+  VectorXd v(3);
   v << 1, 2, 3;
   cout << "m * v =" << endl << m * v << endl;
 }

doc/examples/QuickStart_example2_fixed.cpp

@@ -6,10 +6,10 @@ using namespace std;
 
 int main()
 {
-  Matrix3f m = Matrix3f::Random();
+  Matrix3d m = Matrix3d::Random();
-  m = (m + Matrix3f::Constant(1.2)) * 50;
+  m = (m + Matrix3d::Constant(1.2)) * 50;
   cout << "m =" << endl << m << endl;
-  Vector3f v(1,2,3);
+  Vector3d v(1,2,3);
   
   cout << "m * v =" << endl << m * v << endl;
 }

doc/special_examples/CMakeLists.txt

@@ -17,4 +17,5 @@ if(QT4_FOUND)
       COMMAND Tutorial_sparse_example
       ARGS ${CMAKE_CURRENT_BINARY_DIR}/../html/Tutorial_sparse_example.jpeg
   )
+  add_dependencies(all_examples Tutorial_sparse_example)
 endif(QT4_FOUND)

scripts/eigen_gen_docs

@@ -13,7 +13,7 @@ mkdir build -p
 
 #step 2 : upload
 # (the '/' at the end of path is very important, see rsync documentation)
-rsync -az --no-p --delete build/doc/html/ $USER@ssh.tuxfamily.org:eigen/eigen.tuxfamily.org-web/htdocs/dox-devel/ || { echo "upload failed"; exit 1; }
+rsync -az --no-p --delete build/doc/html/ $USER@ssh.tuxfamily.org:eigen/eigen.tuxfamily.org-web/htdocs/dox/ || { echo "upload failed"; exit 1; }
 
 #step 3 : fix the perm
 ssh $USER@ssh.tuxfamily.org 'chmod -R g+w /home/eigen/eigen.tuxfamily.org-web/htdocs/dox-devel' || { echo "perm failed"; exit 1; }

test/array_for_matrix.cpp

@@ -42,10 +42,10 @@ template<typename MatrixType> void array_for_matrix(const MatrixType& m)
   VERIFY_IS_APPROX(m3, (m1.array() - s1).matrix());
 
   // reductions
-  VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum().sum() - m1.sum(), m1.cwiseAbs().maxCoeff());
+  VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum().sum() - m1.sum(), m1.squaredNorm());
-  VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum().sum() - m1.sum(), m1.cwiseAbs().maxCoeff());
+  VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum().sum() - m1.sum(), m1.squaredNorm());
-  VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1+m2).cwiseAbs().maxCoeff());
+  VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1+m2).squaredNorm());
-  VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum() - m2.rowwise().sum() - (m1-m2).rowwise().sum(), (m1-m2).cwiseAbs().maxCoeff());
+  VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum() - m2.rowwise().sum() - (m1-m2).rowwise().sum(), (m1-m2).squaredNorm());
   VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar>()));
 
   // vector-wise ops
@@ -168,6 +168,38 @@ template<typename MatrixType> void cwise_min_max(const MatrixType& m)
   VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1), m1.cwiseMax( maxM1));
   VERIFY_IS_APPROX(m1, m1.cwiseMax( minM1));
 
+  VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, minM1).array(), (m1.array().min)( minM1));
+  VERIFY_IS_APPROX(m1.array(), (m1.array().min)( maxM1));
+
+  VERIFY_IS_APPROX(MatrixType::Constant(rows,cols, maxM1).array(), (m1.array().max)( maxM1));
+  VERIFY_IS_APPROX(m1.array(), (m1.array().max)( minM1));
+
+}
+
+template<typename MatrixTraits> void resize(const MatrixTraits& t)
+{
+  typedef typename MatrixTraits::Index Index;
+  typedef typename MatrixTraits::Scalar Scalar;
+  typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
+  typedef Array<Scalar,Dynamic,Dynamic> Array2DType;
+  typedef Matrix<Scalar,Dynamic,1> VectorType;
+  typedef Array<Scalar,Dynamic,1> Array1DType;
+
+  Index rows = t.rows(), cols = t.cols();
+
+  MatrixType m(rows,cols);
+  VectorType v(rows);
+  Array2DType a2(rows,cols);
+  Array1DType a1(rows);
+
+  m.array().resize(rows+1,cols+1);
+  VERIFY(m.rows()==rows+1 && m.cols()==cols+1);
+  a2.matrix().resize(rows+1,cols+1);
+  VERIFY(a2.rows()==rows+1 && a2.cols()==cols+1);
+  v.array().resize(cols);
+  VERIFY(v.size()==cols);
+  a1.matrix().resize(cols);
+  VERIFY(a1.size()==cols);
 }
 
 void test_array_for_matrix()
@@ -202,4 +234,9 @@ void test_array_for_matrix()
     CALL_SUBTEST_5( lpNorm(VectorXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
     CALL_SUBTEST_4( lpNorm(VectorXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
   }
+  for(int i = 0; i < g_repeat; i++) {
+    CALL_SUBTEST_4( resize(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_5( resize(MatrixXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+    CALL_SUBTEST_6( resize(MatrixXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) );
+  }
 }

test/diagonal.cpp

@@ -56,12 +56,12 @@ template<typename MatrixType> void diagonal(const MatrixType& m)
     VERIFY_IS_APPROX(m2.template diagonal<N2>()[0], static_cast<Scalar>(6) * m1.template diagonal<N2>()[0]);
 
     m2.diagonal(N1) = 2 * m1.diagonal(N1);
-    VERIFY_IS_APPROX(m2.diagonal<N1>(), static_cast<Scalar>(2) * m1.diagonal(N1));
+    VERIFY_IS_APPROX(m2.template diagonal<N1>(), static_cast<Scalar>(2) * m1.diagonal(N1));
     m2.diagonal(N1)[0] *= 3;
     VERIFY_IS_APPROX(m2.diagonal(N1)[0], static_cast<Scalar>(6) * m1.diagonal(N1)[0]);
 
     m2.diagonal(N2) = 2 * m1.diagonal(N2);
-    VERIFY_IS_APPROX(m2.diagonal<N2>(), static_cast<Scalar>(2) * m1.diagonal(N2));
+    VERIFY_IS_APPROX(m2.template diagonal<N2>(), static_cast<Scalar>(2) * m1.diagonal(N2));
     m2.diagonal(N2)[0] *= 3;
     VERIFY_IS_APPROX(m2.diagonal(N2)[0], static_cast<Scalar>(6) * m1.diagonal(N2)[0]);
   }

test/diagonalmatrices.cpp

@@ -32,6 +32,8 @@ template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
              rv2 = RowVectorType::Random(cols);
   LeftDiagonalMatrix ldm1(v1), ldm2(v2);
   RightDiagonalMatrix rdm1(rv1), rdm2(rv2);
+  
+  Scalar s1 = internal::random<Scalar>();
 
   SquareMatrixType sq_m1 (v1.asDiagonal());
   VERIFY_IS_APPROX(sq_m1, v1.asDiagonal().toDenseMatrix());
@@ -76,6 +78,13 @@ template<typename MatrixType> void diagonalmatrices(const MatrixType& m)
   big.block(i,j,rows,cols) = big.block(i,j,rows,cols) * rv1.asDiagonal();
   VERIFY_IS_APPROX((big.block(i,j,rows,cols)) , m1 * rv1.asDiagonal() );
   
+  
+  // scalar multiple
+  VERIFY_IS_APPROX(LeftDiagonalMatrix(ldm1*s1).diagonal(), ldm1.diagonal() * s1);
+  VERIFY_IS_APPROX(LeftDiagonalMatrix(s1*ldm1).diagonal(), s1 * ldm1.diagonal());
+  
+  VERIFY_IS_APPROX(m1 * (rdm1 * s1), (m1 * rdm1) * s1);
+  VERIFY_IS_APPROX(m1 * (s1 * rdm1), (m1 * rdm1) * s1);
 }
 
 void test_diagonalmatrices()

test/geo_quaternion.cpp

@@ -171,23 +171,36 @@ template<typename Scalar, int Options> void quaternion(void)
 
 template<typename Scalar> void mapQuaternion(void){
   typedef Map<Quaternion<Scalar>, Aligned> MQuaternionA;
+  typedef Map<const Quaternion<Scalar>, Aligned> MCQuaternionA;
   typedef Map<Quaternion<Scalar> > MQuaternionUA;
   typedef Map<const Quaternion<Scalar> > MCQuaternionUA;
   typedef Quaternion<Scalar> Quaternionx;
+  typedef Matrix<Scalar,3,1> Vector3;
+  typedef AngleAxis<Scalar> AngleAxisx;
+  
+  Vector3 v0 = Vector3::Random(),
+          v1 = Vector3::Random();
+  Scalar  a = internal::random<Scalar>(-Scalar(M_PI), Scalar(M_PI));
 
   EIGEN_ALIGN16 Scalar array1[4];
   EIGEN_ALIGN16 Scalar array2[4];
   EIGEN_ALIGN16 Scalar array3[4+1];
   Scalar* array3unaligned = array3+1;
+  
+  MQuaternionA    mq1(array1);
+  MCQuaternionA   mcq1(array1);
+  MQuaternionA    mq2(array2);
+  MQuaternionUA   mq3(array3unaligned);
+  MCQuaternionUA  mcq3(array3unaligned);
 
 //  std::cerr << array1 << " " << array2 << " " << array3 << "\n";
-  MQuaternionA(array1).coeffs().setRandom();
+  mq1 = AngleAxisx(a, v0.normalized());
-  (MQuaternionA(array2)) = MQuaternionA(array1);
+  mq2 = mq1;
-  (MQuaternionUA(array3unaligned)) = MQuaternionA(array1);
+  mq3 = mq1;
 
-  Quaternionx q1 = MQuaternionA(array1);
+  Quaternionx q1 = mq1;
-  Quaternionx q2 = MQuaternionA(array2);
+  Quaternionx q2 = mq2;
-  Quaternionx q3 = MQuaternionUA(array3unaligned);
+  Quaternionx q3 = mq3;
   Quaternionx q4 = MCQuaternionUA(array3unaligned);
 
   VERIFY_IS_APPROX(q1.coeffs(), q2.coeffs());
@@ -197,6 +210,23 @@ template<typename Scalar> void mapQuaternion(void){
   if(internal::packet_traits<Scalar>::Vectorizable)
     VERIFY_RAISES_ASSERT((MQuaternionA(array3unaligned)));
   #endif
+    
+  VERIFY_IS_APPROX(mq1 * (mq1.inverse() * v1), v1);
+  VERIFY_IS_APPROX(mq1 * (mq1.conjugate() * v1), v1);
+  
+  VERIFY_IS_APPROX(mcq1 * (mcq1.inverse() * v1), v1);
+  VERIFY_IS_APPROX(mcq1 * (mcq1.conjugate() * v1), v1);
+  
+  VERIFY_IS_APPROX(mq3 * (mq3.inverse() * v1), v1);
+  VERIFY_IS_APPROX(mq3 * (mq3.conjugate() * v1), v1);
+  
+  VERIFY_IS_APPROX(mcq3 * (mcq3.inverse() * v1), v1);
+  VERIFY_IS_APPROX(mcq3 * (mcq3.conjugate() * v1), v1);
+  
+  VERIFY_IS_APPROX(mq1*mq2, q1*q2);
+  VERIFY_IS_APPROX(mq3*mq2, q3*q2);
+  VERIFY_IS_APPROX(mcq1*mq2, q1*q2);
+  VERIFY_IS_APPROX(mcq3*mq2, q3*q2);
 }
 
 template<typename Scalar> void quaternionAlignment(void){

test/nullary.cpp

@@ -91,6 +91,12 @@ void testVectorType(const VectorType& base)
   scalar.setLinSpaced(1,low,high);
   VERIFY_IS_APPROX( scalar, ScalarMatrix::Constant(high) );
   VERIFY_IS_APPROX( ScalarMatrix::LinSpaced(1,low,high), ScalarMatrix::Constant(high) );
+
+  // regression test for bug 526 (linear vectorized transversal)
+  if (size > 1) {
+    m.tail(size-1).setLinSpaced(low, high);
+    VERIFY_IS_APPROX(m(size-1), high);
+  }
 }
 
 template<typename MatrixType>

test/packetmath.cpp

@@ -40,7 +40,7 @@ template<typename Scalar> bool areApprox(const Scalar* a, const Scalar* b, int s
 {
   for (int i=0; i<size; ++i)
   {
-    if (!internal::isApprox(a[i],b[i]))
+    if (a[i]!=b[i] && !internal::isApprox(a[i],b[i]))
     {
       std::cout << "[" << Map<const Matrix<Scalar,1,Dynamic> >(a,size) << "]" << " != " << Map<const Matrix<Scalar,1,Dynamic> >(b,size) << "\n";
       return false;

test/product_extra.cpp

@@ -135,6 +135,35 @@ void zero_sized_objects()
   a*b;
 }
 
+void unaligned_objects()
+{
+  // Regression test for the bug reported here:
+  // http://forum.kde.org/viewtopic.php?f=74&t=107541
+  // Recall the matrix*vector kernel avoid unaligned loads by loading two packets and then reassemble then.
+  // There was a mistake in the computation of the valid range for fully unaligned objects: in some rare cases,
+  // memory was read outside the allocated matrix memory. Though the values were not used, this might raise segfault.
+  for(int m=450;m<460;++m)
+  {
+    for(int n=8;n<12;++n)
+    {
+      MatrixXf M(m, n);
+      VectorXf v1(n), r1(500);
+      RowVectorXf v2(m), r2(16);
+
+      M.setRandom();
+      v1.setRandom();
+      v2.setRandom();
+      for(int o=0; o<4; ++o)
+      {
+        r1.segment(o,m).noalias() = M * v1;
+        VERIFY_IS_APPROX(r1.segment(o,m), M * MatrixXf(v1));
+        r2.segment(o,n).noalias() = v2 * M;
+        VERIFY_IS_APPROX(r2.segment(o,n), MatrixXf(v2) * M);
+      }
+    }
+  }
+}
+
 void test_product_extra()
 {
   for(int i = 0; i < g_repeat; i++) {
@@ -143,6 +172,7 @@ void test_product_extra()
     CALL_SUBTEST_2( mat_mat_scalar_scalar_product() );
     CALL_SUBTEST_3( product_extra(MatrixXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
     CALL_SUBTEST_4( product_extra(MatrixXcd(internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2), internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2))) );
-    CALL_SUBTEST_5( zero_sized_objects() );
   }
+  CALL_SUBTEST_5( zero_sized_objects() );
+  CALL_SUBTEST_6( unaligned_objects() );
 }

test/sparse.h

@@ -178,5 +178,30 @@ initSparse(double density,
   }
 }
 
+template<typename Scalar> void
+initSparse(double density,
+           Matrix<Scalar,1,Dynamic>& refVec,
+           SparseVector<Scalar,RowMajor>& sparseVec,
+           std::vector<int>* zeroCoords = 0,
+           std::vector<int>* nonzeroCoords = 0)
+{
+  sparseVec.reserve(int(refVec.size()*density));
+  sparseVec.setZero();
+  for(int i=0; i<refVec.size(); i++)
+  {
+    Scalar v = (internal::random<double>(0,1) < density) ? internal::random<Scalar>() : Scalar(0);
+    if (v!=Scalar(0))
+    {
+      sparseVec.insertBack(i) = v;
+      if (nonzeroCoords)
+        nonzeroCoords->push_back(i);
+    }
+    else if (zeroCoords)
+        zeroCoords->push_back(i);
+    refVec[i] = v;
+  }
+}
+
+
 #include <unsupported/Eigen/SparseExtra>
 #endif // EIGEN_TESTSPARSE_H

test/sparse_basic.cpp

@@ -193,6 +193,12 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
     // sparse cwise* dense
     VERIFY_IS_APPROX(m3.cwiseProduct(refM4), refM3.cwiseProduct(refM4));
 //     VERIFY_IS_APPROX(m3.cwise()/refM4, refM3.cwise()/refM4);
+
+    // test aliasing
+    VERIFY_IS_APPROX((m1 = -m1), (refM1 = -refM1));
+    VERIFY_IS_APPROX((m1 = m1.transpose()), (refM1 = refM1.transpose().eval()));
+    VERIFY_IS_APPROX((m1 = -m1.transpose()), (refM1 = -refM1.transpose().eval()));
+    VERIFY_IS_APPROX((m1 += -m1), (refM1 += -refM1));
   }
 
   // test transpose

test/sparse_product.cpp

@@ -46,8 +46,10 @@ template<typename SparseMatrixType> void sparse_product()
   double density = (std::max)(8./(rows*cols), 0.01);
   typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
   typedef Matrix<Scalar,Dynamic,1> DenseVector;
-
+  typedef Matrix<Scalar,1,Dynamic> RowDenseVector;
-  Scalar s1 = internal::random<Scalar>();
+  typedef SparseVector<Scalar,0,Index> ColSpVector;
+  typedef SparseVector<Scalar,RowMajor,Index> RowSpVector;Scalar s1 = internal::random<Scalar>();
+  
   Scalar s2 = internal::random<Scalar>();
 
   // test matrix-matrix product
@@ -117,6 +119,21 @@ template<typename SparseMatrixType> void sparse_product()
     test_outer<SparseMatrixType,DenseMatrix>::run(m2,m4,refMat2,refMat4);
 
     VERIFY_IS_APPROX(m6=m6*m6, refMat6=refMat6*refMat6);
+    
+    // sparse matrix * sparse vector
+    ColSpVector cv0(cols), cv1;
+    DenseVector dcv0(cols), dcv1;
+    initSparse(2*density,dcv0, cv0);
+    
+    RowSpVector rv0(depth), rv1;
+    RowDenseVector drv0(depth), drv1(rv1);
+    initSparse(2*density,drv0, rv0);
+    
+    VERIFY_IS_APPROX(cv1=rv0*m3, dcv1=drv0*refMat3);
+    VERIFY_IS_APPROX(rv1=rv0*m3, drv1=drv0*refMat3);
+    VERIFY_IS_APPROX(cv1=m3*cv0, dcv1=refMat3*dcv0);
+    VERIFY_IS_APPROX(cv1=m3t.adjoint()*cv0, dcv1=refMat3t.adjoint()*dcv0);
+    VERIFY_IS_APPROX(rv1=m3*cv0, drv1=refMat3*dcv0);
   }
 
   // test matrix - diagonal product

test/sparse_vector.cpp

@@ -78,6 +78,17 @@ template<typename Scalar> void sparse_vector(int rows, int cols)
 
   VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm());
 
+  // test aliasing
+  VERIFY_IS_APPROX((v1 = -v1), (refV1 = -refV1));
+  VERIFY_IS_APPROX((v1 = v1.transpose()), (refV1 = refV1.transpose().eval()));
+  VERIFY_IS_APPROX((v1 += -v1), (refV1 += -refV1));
+  
+  // sparse matrix to sparse vector
+  SparseMatrixType mv1;
+  VERIFY_IS_APPROX((mv1=v1),v1);
+  VERIFY_IS_APPROX(mv1,(v1=mv1));
+  VERIFY_IS_APPROX(mv1,(v1=mv1.transpose()));
+
 }
 
 void test_sparse_vector()

unsupported/Eigen/NonLinearOptimization

@@ -1,4 +1,4 @@
-// This file is part of Eugenio, a lightweight C++ template library
+// This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2009 Thomas Capricelli <orzel@freehackers.org>

unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h

@@ -62,7 +62,9 @@ void pseudo_inverse(const CMatrix &C, CINVMatrix &CINV)
   Scalar rho, rho_1, alpha;
   d.setZero();
 
-  CINV.startFill(); // FIXME estimate the number of non-zeros
+  typedef Triplet<double> T;
+  std::vector<T> tripletList;
+    
   for (Index i = 0; i < rows; ++i)
   {
     d[i] = 1.0;
@@ -88,11 +90,12 @@ void pseudo_inverse(const CMatrix &C, CINVMatrix &CINV)
     // FIXME add a generic "prune/filter" expression for both dense and sparse object to sparse
     for (Index j=0; j<l.size(); ++j)
       if (l[j]<1e-15)
-        CINV.fill(i,j) = l[j];
+	tripletList.push_back(T(i,j,l(j)));
 
+	
     d[i] = 0.0;
   }
-  CINV.endFill();
+  CINV.setFromTriplets(tripletList.begin(), tripletList.end());
 }
 
 
@@ -107,6 +110,7 @@ template<typename TMatrix, typename CMatrix,
 void constrained_cg(const TMatrix& A, const CMatrix& C, VectorX& x,
                        const VectorB& b, const VectorF& f, IterationController &iter)
 {
+  using std::sqrt;
   typedef typename TMatrix::Scalar Scalar;
   typedef typename TMatrix::Index Index;
   typedef Matrix<Scalar,Dynamic,1>  TmpVec;

unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h

@@ -195,24 +195,24 @@ template <typename MatrixType>
 int MatrixLogarithmAtomic<MatrixType>::getPadeDegree(long double normTminusI)
 {
 #if   LDBL_MANT_DIG == 53         // double precision
-  const double maxNormForPade[] = { 1.6206284795015624e-2 /* degree = 3 */ , 5.3873532631381171e-2,
+  const long double maxNormForPade[] = { 1.6206284795015624e-2L /* degree = 3 */ , 5.3873532631381171e-2L,
-            1.1352802267628681e-1, 1.8662860613541288e-1, 2.642960831111435e-1 };
+            1.1352802267628681e-1L, 1.8662860613541288e-1L, 2.642960831111435e-1L };
 #elif LDBL_MANT_DIG <= 64         // extended precision
-  const double maxNormForPade[] = { 5.48256690357782863103e-3 /* degree = 3 */, 2.34559162387971167321e-2,
+  const long double maxNormForPade[] = { 5.48256690357782863103e-3L /* degree = 3 */, 2.34559162387971167321e-2L,
-            5.84603923897347449857e-2, 1.08486423756725170223e-1, 1.68385767881294446649e-1,
+            5.84603923897347449857e-2L, 1.08486423756725170223e-1L, 1.68385767881294446649e-1L,
-            2.32777776523703892094e-1 };
+            2.32777776523703892094e-1L };
 #elif LDBL_MANT_DIG <= 106        // double-double
-  const double maxNormForPade[] = { 8.58970550342939562202529664318890e-5 /* degree = 3 */,
+  const long double maxNormForPade[] = { 8.58970550342939562202529664318890e-5L /* degree = 3 */,
-            9.34074328446359654039446552677759e-4, 4.26117194647672175773064114582860e-3,
+            9.34074328446359654039446552677759e-4L, 4.26117194647672175773064114582860e-3L,
-            1.21546224740281848743149666560464e-2, 2.61100544998339436713088248557444e-2,
+            1.21546224740281848743149666560464e-2L, 2.61100544998339436713088248557444e-2L,
-            4.66170074627052749243018566390567e-2, 7.32585144444135027565872014932387e-2,
+            4.66170074627052749243018566390567e-2L, 7.32585144444135027565872014932387e-2L,
-            1.05026503471351080481093652651105e-1 };
+            1.05026503471351080481093652651105e-1L };
 #else                             // quadruple precision
-  const double maxNormForPade[] = { 4.7419931187193005048501568167858103e-5 /* degree = 3 */,
+  const long double maxNormForPade[] = { 4.7419931187193005048501568167858103e-5L /* degree = 3 */,
-            5.8853168473544560470387769480192666e-4, 2.9216120366601315391789493628113520e-3,
+            5.8853168473544560470387769480192666e-4L, 2.9216120366601315391789493628113520e-3L,
-            8.8415758124319434347116734705174308e-3, 1.9850836029449446668518049562565291e-2,
+            8.8415758124319434347116734705174308e-3L, 1.9850836029449446668518049562565291e-2L,
-            3.6688019729653446926585242192447447e-2, 5.9290962294020186998954055264528393e-2,
+            3.6688019729653446926585242192447447e-2L, 5.9290962294020186998954055264528393e-2L,
-            8.6998436081634343903250580992127677e-2, 1.1880960220216759245467951592883642e-1 };
+            8.6998436081634343903250580992127677e-2L, 1.1880960220216759245467951592883642e-1L };
 #endif
   for (int degree = 3; degree <= maxPadeDegree; ++degree)
     if (normTminusI <= maxNormForPade[degree - minPadeDegree])
@@ -423,8 +423,8 @@ void MatrixLogarithmAtomic<MatrixType>::computePade11(MatrixType& result, const
   * This class holds the argument to the matrix function until it is
   * assigned or evaluated for some other reason (so the argument
   * should not be changed in the meantime). It is the return type of
-  * matrixBase::matrixLogarithm() and most of the time this is the
+  * matrixBase::log() and most of the time this is the only way it
-  * only way it is used.
+  * is used.
   */
 template<typename Derived> class MatrixLogarithmReturnValue
 : public ReturnByValue<MatrixLogarithmReturnValue<Derived> >