Updated eigen to HEAD version

resources/3rdparty/eigen/.hg_archival.txt

@@ -1,4 +1,5 @@
 repo: 8a21fd850624c931e448cbcfb38168cb2717c790
-node: 43d9075b23ef596ddf396101956d06f446fc0765
-branch: 3.1
-tag: 3.1.1
+node: 5945cb388ded120eb6dd3a1dfd2766b8e83237a4
+branch: default
+latesttag: 3.1.0-rc2
+latesttagdistance: 147

resources/3rdparty/eigen/.hgtags

@@ -20,4 +20,3 @@ a810d5dbab47acfe65b3350236efdd98f67d4d8a 3.1.0-alpha1
 920fc730b5930daae0a6dbe296d60ce2e3808215 3.1.0-beta1
 8383e883ebcc6f14695ff0b5e20bb631abab43fb 3.1.0-rc1
 bf4cb8c934fa3a79f45f1e629610f0225e93e493 3.1.0-rc2
-ca142d0540d3384180c5082d24ef056bd3c354b6 3.1.0

resources/3rdparty/eigen/.krazy

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

resources/3rdparty/eigen/COPYING.LGPL

@@ -1,165 +1,502 @@
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+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!

resources/3rdparty/eigen/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:

resources/3rdparty/eigen/Eigen/Core

@@ -87,19 +87,25 @@
     // so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too.
     // notice that since these are C headers, the extern "C" is theoretically needed anyways.
     extern "C" {
-      #include <emmintrin.h>
-      #include <xmmintrin.h>
-      #ifdef  EIGEN_VECTORIZE_SSE3
-      #include <pmmintrin.h>
-      #endif
-      #ifdef EIGEN_VECTORIZE_SSSE3
-      #include <tmmintrin.h>
-      #endif
-      #ifdef EIGEN_VECTORIZE_SSE4_1
-      #include <smmintrin.h>
-      #endif
-      #ifdef EIGEN_VECTORIZE_SSE4_2
-      #include <nmmintrin.h>
+      // In theory we should only include immintrin.h and not the other *mmintrin.h header files directly.
+      // Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus:
+      #ifdef __INTEL_COMPILER
+        #include <immintrin.h>
+      #else
+        #include <emmintrin.h>
+        #include <xmmintrin.h>
+        #ifdef  EIGEN_VECTORIZE_SSE3
+        #include <pmmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSSE3
+        #include <tmmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSE4_1
+        #include <smmintrin.h>
+        #endif
+        #ifdef EIGEN_VECTORIZE_SSE4_2
+        #include <nmmintrin.h>
+        #endif
       #endif
     } // end extern "C"
   #elif defined __ALTIVEC__
@@ -297,6 +303,7 @@ using std::ptrdiff_t;
 #include "src/Core/Map.h"
 #include "src/Core/Block.h"
 #include "src/Core/VectorBlock.h"
+#include "src/Core/Ref.h"
 #include "src/Core/Transpose.h"
 #include "src/Core/DiagonalMatrix.h"
 #include "src/Core/Diagonal.h"
@@ -340,6 +347,13 @@ using std::ptrdiff_t;
 #include "src/Core/ArrayBase.h"
 #include "src/Core/ArrayWrapper.h"
 
+#ifdef EIGEN_ENABLE_EVALUATORS
+#include "src/Core/Product.h"
+#include "src/Core/CoreEvaluators.h"
+#include "src/Core/AssignEvaluator.h"
+#include "src/Core/ProductEvaluators.h"
+#endif
+
 #ifdef EIGEN_USE_BLAS
 #include "src/Core/products/GeneralMatrixMatrix_MKL.h"
 #include "src/Core/products/GeneralMatrixVector_MKL.h"

resources/3rdparty/eigen/Eigen/Eigenvalues

@@ -33,6 +33,8 @@
 #include "src/Eigenvalues/HessenbergDecomposition.h"
 #include "src/Eigenvalues/ComplexSchur.h"
 #include "src/Eigenvalues/ComplexEigenSolver.h"
+#include "src/Eigenvalues/RealQZ.h"
+#include "src/Eigenvalues/GeneralizedEigenSolver.h"
 #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
 #ifdef EIGEN_USE_LAPACKE
 #include "src/Eigenvalues/RealSchur_MKL.h"

resources/3rdparty/eigen/Eigen/MetisSupport

@@ -0,0 +1,26 @@
+#ifndef EIGEN_METISSUPPORT_MODULE_H
+#define EIGEN_METISSUPPORT_MODULE_H
+
+#include "SparseCore"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+extern "C" {
+#include <metis.h>
+}
+
+
+/** \ingroup Support_modules
+  * \defgroup MetisSupport_Module MetisSupport module
+  *
+  * \code
+  * #include <Eigen/MetisSupport>
+  * \endcode
+  */
+
+
+#include "src/MetisSupport/MetisSupport.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_METISSUPPORT_MODULE_H

resources/3rdparty/eigen/Eigen/OrderingMethods

@@ -17,7 +17,7 @@
   */
 
 #include "src/OrderingMethods/Amd.h"
-
+#include "src/OrderingMethods/Ordering.h"
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_ORDERINGMETHODS_MODULE_H

resources/3rdparty/eigen/Eigen/SparseLU

@@ -0,0 +1,17 @@
+#ifndef EIGEN_SPARSELU_MODULE_H
+#define EIGEN_SPARSELU_MODULE_H
+
+#include "SparseCore"
+
+
+/** \ingroup Sparse_modules
+  * \defgroup SparseLU_Module SparseLU module
+  *
+  */
+
+// Ordering interface
+#include "OrderingMethods"
+
+#include "src/SparseLU/SparseLU.h"
+
+#endif // EIGEN_SPARSELU_MODULE_H

resources/3rdparty/eigen/Eigen/src/Cholesky/LDLT.h

@@ -281,6 +281,13 @@ template<> struct ldlt_inplace<Lower>
         if(sign)
           *sign = real(mat.diagonal().coeff(index_of_biggest_in_corner)) > 0 ? 1 : -1;
       }
+      else 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(newSign != *sign)
+          *sign = 0;
+      }
 
       // Finish early if the matrix is not full rank.
       if(biggest_in_corner < cutoff)

resources/3rdparty/eigen/Eigen/src/CholmodSupport/CholmodSupport.h

@@ -173,6 +173,7 @@ class CholmodBase : internal::noncopyable
     CholmodBase(const MatrixType& matrix)
       : m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
     {
+      m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0);
       cholmod_start(&m_cholmod);
       compute(matrix);
     }
@@ -269,9 +270,10 @@ class CholmodBase : internal::noncopyable
     {
       eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
       cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
-      cholmod_factorize(&A, m_cholmodFactor, &m_cholmod);
+      cholmod_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, &m_cholmod);
       
-      this->m_info = Success;
+      // If the factorization failed, minor is the column at which it did. On success minor == n.
+      this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue);
       m_factorizationIsOk = true;
     }
     
@@ -286,6 +288,7 @@ class CholmodBase : internal::noncopyable
     {
       eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
       const Index size = m_cholmodFactor->n;
+      EIGEN_UNUSED_VARIABLE(size);
       eigen_assert(size==b.rows());
 
       // note: cd stands for Cholmod Dense
@@ -321,6 +324,22 @@ class CholmodBase : internal::noncopyable
     }
     #endif // EIGEN_PARSED_BY_DOXYGEN
     
+    
+    /** Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization.
+      *
+      * During the numerical factorization, an offset term is added to the diagonal coefficients:\n
+      * \c d_ii = \a offset + \c d_ii
+      *
+      * The default is \a offset=0.
+      *
+      * \returns a reference to \c *this.
+      */
+    Derived& setShift(const RealScalar& offset)
+    {
+      m_shiftOffset[0] = offset;
+      return derived();
+    }
+    
     template<typename Stream>
     void dumpMemory(Stream& s)
     {}
@@ -328,6 +347,7 @@ class CholmodBase : internal::noncopyable
   protected:
     mutable cholmod_common m_cholmod;
     cholmod_factor* m_cholmodFactor;
+    RealScalar m_shiftOffset[2];
     mutable ComputationInfo m_info;
     bool m_isInitialized;
     int m_factorizationIsOk;

resources/3rdparty/eigen/Eigen/src/Core/Array.h

@@ -142,10 +142,10 @@ class Array
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename T0, typename T1>
-    EIGEN_STRONG_INLINE Array(const T0& x, const T1& y)
+    EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1)
     {
       Base::_check_template_params();
-      this->template _init2<T0,T1>(x, y);
+      this->template _init2<T0,T1>(val0, val1);
     }
     #else
     /** constructs an uninitialized matrix with \a rows rows and \a cols columns.
@@ -155,27 +155,27 @@ class Array
       * Matrix() instead. */
     Array(Index rows, Index cols);
     /** constructs an initialized 2D vector with given coefficients */
-    Array(const Scalar& x, const Scalar& y);
+    Array(const Scalar& val0, const Scalar& val1);
     #endif
 
     /** constructs an initialized 3D vector with given coefficients */
-    EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z)
+    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2)
     {
       Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3)
-      m_storage.data()[0] = x;
-      m_storage.data()[1] = y;
-      m_storage.data()[2] = z;
+      m_storage.data()[0] = val0;
+      m_storage.data()[1] = val1;
+      m_storage.data()[2] = val2;
     }
     /** constructs an initialized 4D vector with given coefficients */
-    EIGEN_STRONG_INLINE Array(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
+    EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3)
     {
       Base::_check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4)
-      m_storage.data()[0] = x;
-      m_storage.data()[1] = y;
-      m_storage.data()[2] = z;
-      m_storage.data()[3] = w;
+      m_storage.data()[0] = val0;
+      m_storage.data()[1] = val1;
+      m_storage.data()[2] = val2;
+      m_storage.data()[3] = val3;
     }
 
     explicit Array(const Scalar *data);

resources/3rdparty/eigen/Eigen/src/Core/ArrayWrapper.h

@@ -58,19 +58,19 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline CoeffReturnType coeff(Index row, Index col) const
+    inline CoeffReturnType coeff(Index rowId, Index colId) const
     {
-      return m_expression.coeff(row, col);
+      return m_expression.coeff(rowId, colId);
     }
 
-    inline Scalar& coeffRef(Index row, Index col)
+    inline Scalar& coeffRef(Index rowId, Index colId)
     {
-      return m_expression.const_cast_derived().coeffRef(row, col);
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
     }
 
-    inline const Scalar& coeffRef(Index row, Index col) const
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
-      return m_expression.const_cast_derived().coeffRef(row, col);
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
     }
 
     inline CoeffReturnType coeff(Index index) const
@@ -89,15 +89,15 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(Index row, Index col) const
+    inline const PacketScalar packet(Index rowId, Index colId) const
     {
-      return m_expression.template packet<LoadMode>(row, col);
+      return m_expression.template packet<LoadMode>(rowId, colId);
     }
 
     template<int LoadMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
     {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
+      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
     }
 
     template<int LoadMode>
@@ -107,9 +107,9 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     }
 
     template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& val)
     {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
     }
 
     template<typename Dest>
@@ -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;
 };
@@ -161,7 +168,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
 
     typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
 
-    inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
+    inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {}
 
     inline Index rows() const { return m_expression.rows(); }
     inline Index cols() const { return m_expression.cols(); }
@@ -171,19 +178,19 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline CoeffReturnType coeff(Index row, Index col) const
+    inline CoeffReturnType coeff(Index rowId, Index colId) const
     {
-      return m_expression.coeff(row, col);
+      return m_expression.coeff(rowId, colId);
     }
 
-    inline Scalar& coeffRef(Index row, Index col)
+    inline Scalar& coeffRef(Index rowId, Index colId)
     {
-      return m_expression.const_cast_derived().coeffRef(row, col);
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
     }
 
-    inline const Scalar& coeffRef(Index row, Index col) const
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
-      return m_expression.derived().coeffRef(row, col);
+      return m_expression.derived().coeffRef(rowId, colId);
     }
 
     inline CoeffReturnType coeff(Index index) const
@@ -202,15 +209,15 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(Index row, Index col) const
+    inline const PacketScalar packet(Index rowId, Index colId) const
     {
-      return m_expression.template packet<LoadMode>(row, col);
+      return m_expression.template packet<LoadMode>(rowId, colId);
     }
 
     template<int LoadMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
     {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(row, col, x);
+      m_expression.const_cast_derived().template writePacket<LoadMode>(rowId, colId, val);
     }
 
     template<int LoadMode>
@@ -220,9 +227,9 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     }
 
     template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& val)
     {
-      m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
+      m_expression.const_cast_derived().template writePacket<LoadMode>(index, val);
     }
 
     const typename internal::remove_all<NestedExpressionType>::type& 
@@ -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;
 };

resources/3rdparty/eigen/Eigen/src/Core/AssignEvaluator.h

@@ -0,0 +1,755 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011-2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ASSIGN_EVALUATOR_H
+#define EIGEN_ASSIGN_EVALUATOR_H
+
+namespace Eigen {
+
+// This implementation is based on Assign.h
+
+namespace internal {
+  
+/***************************************************************************
+* Part 1 : the logic deciding a strategy for traversal and unrolling       *
+***************************************************************************/
+
+// copy_using_evaluator_traits is based on assign_traits
+
+template <typename Derived, typename OtherDerived>
+struct copy_using_evaluator_traits
+{
+public:
+  enum {
+    DstIsAligned = Derived::Flags & AlignedBit,
+    DstHasDirectAccess = Derived::Flags & DirectAccessBit,
+    SrcIsAligned = OtherDerived::Flags & AlignedBit,
+    JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned,
+    SrcEvalBeforeAssign = (evaluator_traits<OtherDerived>::HasEvalTo == 1)
+  };
+
+private:
+  enum {
+    InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime)
+              : int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime)
+              : int(Derived::RowsAtCompileTime),
+    InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime)
+              : int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime)
+              : int(Derived::MaxRowsAtCompileTime),
+    MaxSizeAtCompileTime = Derived::SizeAtCompileTime,
+    PacketSize = packet_traits<typename Derived::Scalar>::size
+  };
+
+  enum {
+    StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)),
+    MightVectorize = StorageOrdersAgree
+                  && (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit),
+    MayInnerVectorize  = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0
+                       && int(DstIsAligned) && int(SrcIsAligned),
+    MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit),
+    MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess
+                       && (DstIsAligned || MaxSizeAtCompileTime == Dynamic),
+      /* If the destination isn't aligned, we have to do runtime checks and we don't unroll,
+         so it's only good for large enough sizes. */
+    MaySliceVectorize  = MightVectorize && DstHasDirectAccess
+                       && (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize)
+      /* slice vectorization can be slow, so we only want it if the slices are big, which is
+         indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block
+         in a fixed-size matrix */
+  };
+
+public:
+  enum {
+    Traversal = int(SrcEvalBeforeAssign) ? int(AllAtOnceTraversal) 
+              : int(MayInnerVectorize)   ? int(InnerVectorizedTraversal)
+              : int(MayLinearVectorize)  ? int(LinearVectorizedTraversal)
+              : int(MaySliceVectorize)   ? int(SliceVectorizedTraversal)
+              : int(MayLinearize)        ? int(LinearTraversal)
+                                         : int(DefaultTraversal),
+    Vectorized = int(Traversal) == InnerVectorizedTraversal
+              || int(Traversal) == LinearVectorizedTraversal
+              || int(Traversal) == SliceVectorizedTraversal
+  };
+
+private:
+  enum {
+    UnrollingLimit      = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1),
+    MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic
+                       && int(OtherDerived::CoeffReadCost) != Dynamic
+                       && int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit),
+    MayUnrollInner      = int(InnerSize) != Dynamic
+                       && int(OtherDerived::CoeffReadCost) != Dynamic
+                       && int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit)
+  };
+
+public:
+  enum {
+    Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal))
+                ? (
+ 		    int(MayUnrollCompletely) ? int(CompleteUnrolling)
+                  : int(MayUnrollInner)      ? int(InnerUnrolling)
+                                             : int(NoUnrolling)
+                  )
+              : int(Traversal) == int(LinearVectorizedTraversal)
+                ? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling) 
+                                                                    : int(NoUnrolling) )
+              : int(Traversal) == int(LinearTraversal)
+                ? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) 
+                                              : int(NoUnrolling) )
+              : int(NoUnrolling)
+  };
+
+#ifdef EIGEN_DEBUG_ASSIGN
+  static void debug()
+  {
+    EIGEN_DEBUG_VAR(DstIsAligned)
+    EIGEN_DEBUG_VAR(SrcIsAligned)
+    EIGEN_DEBUG_VAR(JointAlignment)
+    EIGEN_DEBUG_VAR(InnerSize)
+    EIGEN_DEBUG_VAR(InnerMaxSize)
+    EIGEN_DEBUG_VAR(PacketSize)
+    EIGEN_DEBUG_VAR(StorageOrdersAgree)
+    EIGEN_DEBUG_VAR(MightVectorize)
+    EIGEN_DEBUG_VAR(MayLinearize)
+    EIGEN_DEBUG_VAR(MayInnerVectorize)
+    EIGEN_DEBUG_VAR(MayLinearVectorize)
+    EIGEN_DEBUG_VAR(MaySliceVectorize)
+    EIGEN_DEBUG_VAR(Traversal)
+    EIGEN_DEBUG_VAR(UnrollingLimit)
+    EIGEN_DEBUG_VAR(MayUnrollCompletely)
+    EIGEN_DEBUG_VAR(MayUnrollInner)
+    EIGEN_DEBUG_VAR(Unrolling)
+  }
+#endif
+};
+
+/***************************************************************************
+* Part 2 : meta-unrollers
+***************************************************************************/
+
+/************************
+*** Default traversal ***
+************************/
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Index, int Stop>
+struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling
+{
+  typedef typename DstEvaluatorType::XprType DstXprType;
+  
+  enum {
+    outer = Index / DstXprType::InnerSizeAtCompileTime,
+    inner = Index % DstXprType::InnerSizeAtCompileTime
+  };
+
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType &dstEvaluator, 
+				      SrcEvaluatorType &srcEvaluator)
+  {
+    dstEvaluator.copyCoeffByOuterInner(outer, inner, srcEvaluator);
+    copy_using_evaluator_DefaultTraversal_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, Index+1, Stop>
+      ::run(dstEvaluator, srcEvaluator);
+  }
+};
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Stop>
+struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling<DstEvaluatorType, SrcEvaluatorType, Stop, Stop>
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType&, SrcEvaluatorType&) { }
+};
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Index, int Stop>
+struct copy_using_evaluator_DefaultTraversal_InnerUnrolling
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType &dstEvaluator, 
+				      SrcEvaluatorType &srcEvaluator, 
+				      int outer)
+  {
+    dstEvaluator.copyCoeffByOuterInner(outer, Index, srcEvaluator);
+    copy_using_evaluator_DefaultTraversal_InnerUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, Index+1, Stop>
+      ::run(dstEvaluator, srcEvaluator, outer);
+  }
+};
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Stop>
+struct copy_using_evaluator_DefaultTraversal_InnerUnrolling<DstEvaluatorType, SrcEvaluatorType, Stop, Stop>
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType&, SrcEvaluatorType&, int) { }
+};
+
+/***********************
+*** Linear traversal ***
+***********************/
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Index, int Stop>
+struct copy_using_evaluator_LinearTraversal_CompleteUnrolling
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType &dstEvaluator, 
+				      SrcEvaluatorType &srcEvaluator)
+  {
+    dstEvaluator.copyCoeff(Index, srcEvaluator);
+    copy_using_evaluator_LinearTraversal_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, Index+1, Stop>
+      ::run(dstEvaluator, srcEvaluator);
+  }
+};
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Stop>
+struct copy_using_evaluator_LinearTraversal_CompleteUnrolling<DstEvaluatorType, SrcEvaluatorType, Stop, Stop>
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType&, SrcEvaluatorType&) { }
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Index, int Stop>
+struct copy_using_evaluator_innervec_CompleteUnrolling
+{
+  typedef typename DstEvaluatorType::XprType DstXprType;
+  typedef typename SrcEvaluatorType::XprType SrcXprType;
+
+  enum {
+    outer = Index / DstXprType::InnerSizeAtCompileTime,
+    inner = Index % DstXprType::InnerSizeAtCompileTime,
+    JointAlignment = copy_using_evaluator_traits<DstXprType,SrcXprType>::JointAlignment
+  };
+
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType &dstEvaluator, 
+				      SrcEvaluatorType &srcEvaluator)
+  {
+    dstEvaluator.template copyPacketByOuterInner<Aligned, JointAlignment>(outer, inner, srcEvaluator);
+    enum { NextIndex = Index + packet_traits<typename DstXprType::Scalar>::size };
+    copy_using_evaluator_innervec_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, NextIndex, Stop>
+      ::run(dstEvaluator, srcEvaluator);
+  }
+};
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Stop>
+struct copy_using_evaluator_innervec_CompleteUnrolling<DstEvaluatorType, SrcEvaluatorType, Stop, Stop>
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType&, SrcEvaluatorType&) { }
+};
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Index, int Stop>
+struct copy_using_evaluator_innervec_InnerUnrolling
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType &dstEvaluator, 
+				      SrcEvaluatorType &srcEvaluator, 
+				      int outer)
+  {
+    dstEvaluator.template copyPacketByOuterInner<Aligned, Aligned>(outer, Index, srcEvaluator);
+    typedef typename DstEvaluatorType::XprType DstXprType;
+    enum { NextIndex = Index + packet_traits<typename DstXprType::Scalar>::size };
+    copy_using_evaluator_innervec_InnerUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, NextIndex, Stop>
+      ::run(dstEvaluator, srcEvaluator, outer);
+  }
+};
+
+template<typename DstEvaluatorType, typename SrcEvaluatorType, int Stop>
+struct copy_using_evaluator_innervec_InnerUnrolling<DstEvaluatorType, SrcEvaluatorType, Stop, Stop>
+{
+  EIGEN_STRONG_INLINE static void run(DstEvaluatorType&, SrcEvaluatorType&, int) { }
+};
+
+/***************************************************************************
+* Part 3 : implementation of all cases
+***************************************************************************/
+
+// copy_using_evaluator_impl is based on assign_impl
+
+template<typename DstXprType, typename SrcXprType,
+         int Traversal = copy_using_evaluator_traits<DstXprType, SrcXprType>::Traversal,
+         int Unrolling = copy_using_evaluator_traits<DstXprType, SrcXprType>::Unrolling>
+struct copy_using_evaluator_impl;
+
+/************************
+*** Default traversal ***
+************************/
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, DefaultTraversal, NoUnrolling>
+{
+  static void run(DstXprType& dst, const SrcXprType& src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+    typedef typename DstXprType::Index Index;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    for(Index outer = 0; outer < dst.outerSize(); ++outer) {
+      for(Index inner = 0; inner < dst.innerSize(); ++inner) {
+	dstEvaluator.copyCoeffByOuterInner(outer, inner, srcEvaluator);
+      }
+    }
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, DefaultTraversal, CompleteUnrolling>
+{
+  EIGEN_STRONG_INLINE static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    copy_using_evaluator_DefaultTraversal_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, 0, DstXprType::SizeAtCompileTime>
+      ::run(dstEvaluator, srcEvaluator);
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, DefaultTraversal, InnerUnrolling>
+{
+  typedef typename DstXprType::Index Index;
+  EIGEN_STRONG_INLINE static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      copy_using_evaluator_DefaultTraversal_InnerUnrolling
+	<DstEvaluatorType, SrcEvaluatorType, 0, DstXprType::InnerSizeAtCompileTime>
+        ::run(dstEvaluator, srcEvaluator, outer);
+  }
+};
+
+/***************************
+*** Linear vectorization ***
+***************************/
+
+template <bool IsAligned = false>
+struct unaligned_copy_using_evaluator_impl
+{
+  // if IsAligned = true, then do nothing
+  template <typename SrcEvaluatorType, typename DstEvaluatorType>
+  static EIGEN_STRONG_INLINE void run(const SrcEvaluatorType&, DstEvaluatorType&, 
+				      typename SrcEvaluatorType::Index, typename SrcEvaluatorType::Index) {}
+};
+
+template <>
+struct unaligned_copy_using_evaluator_impl<false>
+{
+  // MSVC must not inline this functions. If it does, it fails to optimize the
+  // packet access path.
+#ifdef _MSC_VER
+  template <typename DstEvaluatorType, typename SrcEvaluatorType>
+  static EIGEN_DONT_INLINE void run(DstEvaluatorType &dstEvaluator, 
+				    const SrcEvaluatorType &srcEvaluator, 
+				    typename DstEvaluatorType::Index start, 
+				    typename DstEvaluatorType::Index end)
+#else
+  template <typename DstEvaluatorType, typename SrcEvaluatorType>
+  static EIGEN_STRONG_INLINE void run(DstEvaluatorType &dstEvaluator, 
+				      const SrcEvaluatorType &srcEvaluator, 
+				      typename DstEvaluatorType::Index start, 
+				      typename DstEvaluatorType::Index end)
+#endif
+  {
+    for (typename DstEvaluatorType::Index index = start; index < end; ++index)
+      dstEvaluator.copyCoeff(index, srcEvaluator);
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, LinearVectorizedTraversal, NoUnrolling>
+{
+  EIGEN_STRONG_INLINE static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+    typedef typename DstXprType::Index Index;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    const Index size = dst.size();
+    typedef packet_traits<typename DstXprType::Scalar> PacketTraits;
+    enum {
+      packetSize = PacketTraits::size,
+      dstIsAligned = int(copy_using_evaluator_traits<DstXprType,SrcXprType>::DstIsAligned),
+      dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : dstIsAligned,
+      srcAlignment = copy_using_evaluator_traits<DstXprType,SrcXprType>::JointAlignment
+    };
+    const Index alignedStart = dstIsAligned ? 0 : first_aligned(&dstEvaluator.coeffRef(0), size);
+    const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
+
+    unaligned_copy_using_evaluator_impl<dstIsAligned!=0>::run(dstEvaluator, srcEvaluator, 0, alignedStart);
+
+    for(Index index = alignedStart; index < alignedEnd; index += packetSize)
+    {
+      dstEvaluator.template copyPacket<dstAlignment, srcAlignment>(index, srcEvaluator);
+    }
+
+    unaligned_copy_using_evaluator_impl<>::run(dstEvaluator, srcEvaluator, alignedEnd, size);
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, LinearVectorizedTraversal, CompleteUnrolling>
+{
+  typedef typename DstXprType::Index Index;
+  EIGEN_STRONG_INLINE static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    enum { size = DstXprType::SizeAtCompileTime,
+           packetSize = packet_traits<typename DstXprType::Scalar>::size,
+           alignedSize = (size/packetSize)*packetSize };
+
+    copy_using_evaluator_innervec_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, 0, alignedSize>
+      ::run(dstEvaluator, srcEvaluator);
+    copy_using_evaluator_DefaultTraversal_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, alignedSize, size>
+      ::run(dstEvaluator, srcEvaluator);
+  }
+};
+
+/**************************
+*** Inner vectorization ***
+**************************/
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, InnerVectorizedTraversal, NoUnrolling>
+{
+  inline static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+    typedef typename DstXprType::Index Index;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index packetSize = packet_traits<typename DstXprType::Scalar>::size;
+    for(Index outer = 0; outer < outerSize; ++outer)
+      for(Index inner = 0; inner < innerSize; inner+=packetSize) {
+	dstEvaluator.template copyPacketByOuterInner<Aligned, Aligned>(outer, inner, srcEvaluator);
+      }
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, InnerVectorizedTraversal, CompleteUnrolling>
+{
+  EIGEN_STRONG_INLINE static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    copy_using_evaluator_innervec_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, 0, DstXprType::SizeAtCompileTime>
+      ::run(dstEvaluator, srcEvaluator);
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, InnerVectorizedTraversal, InnerUnrolling>
+{
+  typedef typename DstXprType::Index Index;
+  EIGEN_STRONG_INLINE static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    const Index outerSize = dst.outerSize();
+    for(Index outer = 0; outer < outerSize; ++outer)
+      copy_using_evaluator_innervec_InnerUnrolling
+	<DstEvaluatorType, SrcEvaluatorType, 0, DstXprType::InnerSizeAtCompileTime>
+        ::run(dstEvaluator, srcEvaluator, outer);
+  }
+};
+
+/***********************
+*** Linear traversal ***
+***********************/
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, LinearTraversal, NoUnrolling>
+{
+  inline static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+    typedef typename DstXprType::Index Index;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    const Index size = dst.size();
+    for(Index i = 0; i < size; ++i)
+      dstEvaluator.copyCoeff(i, srcEvaluator);
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, LinearTraversal, CompleteUnrolling>
+{
+  EIGEN_STRONG_INLINE static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    copy_using_evaluator_LinearTraversal_CompleteUnrolling
+      <DstEvaluatorType, SrcEvaluatorType, 0, DstXprType::SizeAtCompileTime>
+      ::run(dstEvaluator, srcEvaluator);
+  }
+};
+
+/**************************
+*** Slice vectorization ***
+***************************/
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, SliceVectorizedTraversal, NoUnrolling>
+{
+  inline static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+    typedef typename DstXprType::Index Index;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    typedef packet_traits<typename DstXprType::Scalar> PacketTraits;
+    enum {
+      packetSize = PacketTraits::size,
+      alignable = PacketTraits::AlignedOnScalar,
+      dstAlignment = alignable ? Aligned : int(copy_using_evaluator_traits<DstXprType,SrcXprType>::DstIsAligned)
+    };
+    const Index packetAlignedMask = packetSize - 1;
+    const Index innerSize = dst.innerSize();
+    const Index outerSize = dst.outerSize();
+    const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
+    Index alignedStart = ((!alignable) || copy_using_evaluator_traits<DstXprType,SrcXprType>::DstIsAligned) ? 0
+                       : first_aligned(&dstEvaluator.coeffRef(0,0), innerSize);
+
+    for(Index outer = 0; outer < outerSize; ++outer)
+    {
+      const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask);
+      // do the non-vectorizable part of the assignment
+      for(Index inner = 0; inner<alignedStart ; ++inner) {
+        dstEvaluator.copyCoeffByOuterInner(outer, inner, srcEvaluator);
+      }
+
+      // do the vectorizable part of the assignment
+      for(Index inner = alignedStart; inner<alignedEnd; inner+=packetSize) {
+        dstEvaluator.template copyPacketByOuterInner<dstAlignment, Unaligned>(outer, inner, srcEvaluator);
+      }
+
+      // do the non-vectorizable part of the assignment
+      for(Index inner = alignedEnd; inner<innerSize ; ++inner) {
+        dstEvaluator.copyCoeffByOuterInner(outer, inner, srcEvaluator);
+      }
+
+      alignedStart = std::min<Index>((alignedStart+alignedStep)%packetSize, innerSize);
+    }
+  }
+};
+
+/****************************
+*** All-at-once traversal ***
+****************************/
+
+template<typename DstXprType, typename SrcXprType>
+struct copy_using_evaluator_impl<DstXprType, SrcXprType, AllAtOnceTraversal, NoUnrolling>
+{
+  inline static void run(DstXprType &dst, const SrcXprType &src)
+  {
+    typedef typename evaluator<DstXprType>::type DstEvaluatorType;
+    typedef typename evaluator<SrcXprType>::type SrcEvaluatorType;
+    typedef typename DstXprType::Index Index;
+
+    DstEvaluatorType dstEvaluator(dst);
+    SrcEvaluatorType srcEvaluator(src);
+
+    // Evaluate rhs in temporary to prevent aliasing problems in a = a * a;
+    // TODO: Do not pass the xpr object to evalTo()
+    srcEvaluator.evalTo(dstEvaluator, dst);
+  }
+};
+
+/***************************************************************************
+* Part 4 : Entry points
+***************************************************************************/
+
+// Based on DenseBase::LazyAssign()
+
+template<typename DstXprType, template <typename> class StorageBase, typename SrcXprType>
+EIGEN_STRONG_INLINE
+const DstXprType& copy_using_evaluator(const NoAlias<DstXprType, StorageBase>& dst, 
+				       const EigenBase<SrcXprType>& src)
+{
+  return noalias_copy_using_evaluator(dst.expression(), src.derived());
+}
+
+template<typename XprType, int AssumeAliasing = evaluator_traits<XprType>::AssumeAliasing>
+struct AddEvalIfAssumingAliasing;
+
+template<typename XprType>
+struct AddEvalIfAssumingAliasing<XprType, 0>
+{
+  static const XprType& run(const XprType& xpr) 
+  {
+    return xpr;
+  }
+};
+
+template<typename XprType>
+struct AddEvalIfAssumingAliasing<XprType, 1>
+{
+  static const EvalToTemp<XprType> run(const XprType& xpr)
+  {
+    return EvalToTemp<XprType>(xpr);
+  }
+};
+
+template<typename DstXprType, typename SrcXprType>
+EIGEN_STRONG_INLINE
+const DstXprType& copy_using_evaluator(const EigenBase<DstXprType>& dst, const EigenBase<SrcXprType>& src)
+{
+  return noalias_copy_using_evaluator(dst.const_cast_derived(), 
+				      AddEvalIfAssumingAliasing<SrcXprType>::run(src.derived()));
+}
+
+template<typename DstXprType, typename SrcXprType>
+EIGEN_STRONG_INLINE
+const DstXprType& noalias_copy_using_evaluator(const PlainObjectBase<DstXprType>& dst, const EigenBase<SrcXprType>& src)
+{
+#ifdef EIGEN_DEBUG_ASSIGN
+  internal::copy_using_evaluator_traits<DstXprType, SrcXprType>::debug();
+#endif
+#ifdef EIGEN_NO_AUTOMATIC_RESIZING
+  eigen_assert((dst.size()==0 || (IsVectorAtCompileTime ? (dst.size() == src.size())
+				  : (dst.rows() == src.rows() && dst.cols() == src.cols())))
+	       && "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined");
+#else
+  dst.const_cast_derived().resizeLike(src.derived());
+#endif
+  return copy_using_evaluator_without_resizing(dst.const_cast_derived(), src.derived());
+}
+
+template<typename DstXprType, typename SrcXprType>
+EIGEN_STRONG_INLINE
+const DstXprType& noalias_copy_using_evaluator(const EigenBase<DstXprType>& dst, const EigenBase<SrcXprType>& src)
+{
+  return copy_using_evaluator_without_resizing(dst.const_cast_derived(), src.derived());
+}
+
+template<typename DstXprType, typename SrcXprType>
+const DstXprType& copy_using_evaluator_without_resizing(const DstXprType& dst, const SrcXprType& src)
+{
+#ifdef EIGEN_DEBUG_ASSIGN
+  internal::copy_using_evaluator_traits<DstXprType, SrcXprType>::debug();
+#endif
+  eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols());
+  copy_using_evaluator_impl<DstXprType, SrcXprType>::run(const_cast<DstXprType&>(dst), src);
+  return dst;
+}
+
+// Based on DenseBase::swap()
+// TODO: Chech whether we need to do something special for swapping two
+//       Arrays or Matrices.
+
+template<typename DstXprType, typename SrcXprType>
+void swap_using_evaluator(const DstXprType& dst, const SrcXprType& src)
+{
+  copy_using_evaluator(SwapWrapper<DstXprType>(const_cast<DstXprType&>(dst)), src);
+}
+
+// Based on MatrixBase::operator+= (in CwiseBinaryOp.h)
+template<typename DstXprType, typename SrcXprType>
+void add_assign_using_evaluator(const MatrixBase<DstXprType>& dst, const MatrixBase<SrcXprType>& src)
+{
+  typedef typename DstXprType::Scalar Scalar;
+  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, DstXprType, SrcXprType> tmp(dst.const_cast_derived());
+  copy_using_evaluator(tmp, src.derived());
+}
+
+// Based on ArrayBase::operator+=
+template<typename DstXprType, typename SrcXprType>
+void add_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
+{
+  typedef typename DstXprType::Scalar Scalar;
+  SelfCwiseBinaryOp<internal::scalar_sum_op<Scalar>, DstXprType, SrcXprType> tmp(dst.const_cast_derived());
+  copy_using_evaluator(tmp, src.derived());
+}
+
+// TODO: Add add_assign_using_evaluator for EigenBase ?
+
+template<typename DstXprType, typename SrcXprType>
+void subtract_assign_using_evaluator(const MatrixBase<DstXprType>& dst, const MatrixBase<SrcXprType>& src)
+{
+  typedef typename DstXprType::Scalar Scalar;
+  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, DstXprType, SrcXprType> tmp(dst.const_cast_derived());
+  copy_using_evaluator(tmp, src.derived());
+}
+
+template<typename DstXprType, typename SrcXprType>
+void subtract_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
+{
+  typedef typename DstXprType::Scalar Scalar;
+  SelfCwiseBinaryOp<internal::scalar_difference_op<Scalar>, DstXprType, SrcXprType> tmp(dst.const_cast_derived());
+  copy_using_evaluator(tmp, src.derived());
+}
+
+template<typename DstXprType, typename SrcXprType>
+void multiply_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
+{
+  typedef typename DstXprType::Scalar Scalar;
+  SelfCwiseBinaryOp<internal::scalar_product_op<Scalar>, DstXprType, SrcXprType> tmp(dst.const_cast_derived());
+  copy_using_evaluator(tmp, src.derived());
+}
+
+template<typename DstXprType, typename SrcXprType>
+void divide_assign_using_evaluator(const ArrayBase<DstXprType>& dst, const ArrayBase<SrcXprType>& src)
+{
+  typedef typename DstXprType::Scalar Scalar;
+  SelfCwiseBinaryOp<internal::scalar_quotient_op<Scalar>, DstXprType, SrcXprType> tmp(dst.const_cast_derived());
+  copy_using_evaluator(tmp, src.derived());
+}
+
+
+} // namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_ASSIGN_EVALUATOR_H

resources/3rdparty/eigen/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)

resources/3rdparty/eigen/Eigen/src/Core/Block.h

@@ -124,27 +124,27 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
 
     /** Fixed-size constructor
       */
-    inline Block(XprType& xpr, Index startRow, Index startCol)
-      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
+    inline Block(XprType& xpr, Index a_startRow, Index a_startCol)
+      : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
         m_blockRows(BlockRows), m_blockCols(BlockCols)
     {
       EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
-      eigen_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= xpr.rows()
-             && startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= xpr.cols());
+      eigen_assert(a_startRow >= 0 && BlockRows >= 1 && a_startRow + BlockRows <= xpr.rows()
+             && a_startCol >= 0 && BlockCols >= 1 && a_startCol + BlockCols <= xpr.cols());
     }
 
     /** Dynamic-size constructor
       */
     inline Block(XprType& xpr,
-          Index startRow, Index startCol,
+          Index a_startRow, Index a_startCol,
           Index blockRows, Index blockCols)
-      : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol),
+      : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol),
                           m_blockRows(blockRows), m_blockCols(blockCols)
     {
       eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows)
           && (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols));
-      eigen_assert(startRow >= 0 && blockRows >= 0 && startRow + blockRows <= xpr.rows()
-          && startCol >= 0 && blockCols >= 0 && startCol + blockCols <= xpr.cols());
+      eigen_assert(a_startRow >= 0 && blockRows >= 0 && a_startRow + blockRows <= xpr.rows()
+          && a_startCol >= 0 && blockCols >= 0 && a_startCol + blockCols <= xpr.cols());
     }
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
@@ -152,22 +152,22 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
     inline Index rows() const { return m_blockRows.value(); }
     inline Index cols() const { return m_blockCols.value(); }
 
-    inline Scalar& coeffRef(Index row, Index col)
+    inline Scalar& coeffRef(Index rowId, Index colId)
     {
       EIGEN_STATIC_ASSERT_LVALUE(XprType)
       return m_xpr.const_cast_derived()
-               .coeffRef(row + m_startRow.value(), col + m_startCol.value());
+               .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
-    inline const Scalar& coeffRef(Index row, Index col) const
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
       return m_xpr.derived()
-               .coeffRef(row + m_startRow.value(), col + m_startCol.value());
+               .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
-    EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const
+    EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const
     {
-      return m_xpr.coeff(row + m_startRow.value(), col + m_startCol.value());
+      return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
     inline Scalar& coeffRef(Index index)
@@ -193,17 +193,17 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(Index row, Index col) const
+    inline PacketScalar packet(Index rowId, Index colId) const
     {
       return m_xpr.template packet<Unaligned>
-              (row + m_startRow.value(), col + m_startCol.value());
+              (rowId + m_startRow.value(), colId + m_startCol.value());
     }
 
     template<int LoadMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& val)
     {
       m_xpr.const_cast_derived().template writePacket<Unaligned>
-              (row + m_startRow.value(), col + m_startCol.value(), x);
+              (rowId + m_startRow.value(), colId + m_startCol.value(), val);
     }
 
     template<int LoadMode>
@@ -215,11 +215,11 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
     }
 
     template<int LoadMode>
-    inline void writePacket(Index index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& val)
     {
       m_xpr.const_cast_derived().template writePacket<Unaligned>
          (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index),
-          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), x);
+          m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val);
     }
 
     #ifdef EIGEN_PARSED_BY_DOXYGEN

resources/3rdparty/eigen/Eigen/src/Core/CwiseBinaryOp.h

@@ -122,13 +122,13 @@ class CwiseBinaryOp : internal::no_assignment_operator,
     typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
     typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
 
-    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
-      : m_lhs(lhs), m_rhs(rhs), m_functor(func)
+    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
+      : m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
     {
       EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
       // require the sizes to match
       EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
-      eigen_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
+      eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
     }
 
     EIGEN_STRONG_INLINE Index rows() const {
@@ -169,17 +169,17 @@ class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
     typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
 
-    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
     {
-      return derived().functor()(derived().lhs().coeff(row, col),
-                                 derived().rhs().coeff(row, col));
+      return derived().functor()(derived().lhs().coeff(rowId, colId),
+                                 derived().rhs().coeff(rowId, colId));
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
     {
-      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(row, col),
-                                          derived().rhs().template packet<LoadMode>(row, col));
+      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
+                                          derived().rhs().template packet<LoadMode>(rowId, colId));
     }
 
     EIGEN_STRONG_INLINE const Scalar coeff(Index index) const

resources/3rdparty/eigen/Eigen/src/Core/CwiseNullaryOp.h

@@ -54,27 +54,27 @@ class CwiseNullaryOp : internal::no_assignment_operator,
     typedef typename internal::dense_xpr_base<CwiseNullaryOp>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp)
 
-    CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp())
-      : m_rows(rows), m_cols(cols), m_functor(func)
+    CwiseNullaryOp(Index nbRows, Index nbCols, const NullaryOp& func = NullaryOp())
+      : m_rows(nbRows), m_cols(nbCols), m_functor(func)
     {
-      eigen_assert(rows >= 0
-            && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-            &&  cols >= 0
-            && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
+      eigen_assert(nbRows >= 0
+            && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
+            &&  nbCols >= 0
+            && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols));
     }
 
     EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); }
     EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); }
 
-    EIGEN_STRONG_INLINE const Scalar coeff(Index rows, Index cols) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
     {
-      return m_functor(rows, cols);
+      return m_functor(rowId, colId);
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
     {
-      return m_functor.packetOp(row, col);
+      return m_functor.packetOp(rowId, colId);
     }
 
     EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
@@ -295,11 +295,11 @@ DenseBase<Derived>::LinSpaced(const Scalar& low, const Scalar& high)
 /** \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
 template<typename Derived>
 bool DenseBase<Derived>::isApproxToConstant
-(const Scalar& value, RealScalar prec) const
+(const Scalar& val, const RealScalar& prec) const
 {
   for(Index j = 0; j < cols(); ++j)
     for(Index i = 0; i < rows(); ++i)
-      if(!internal::isApprox(this->coeff(i, j), value, prec))
+      if(!internal::isApprox(this->coeff(i, j), val, prec))
         return false;
   return true;
 }
@@ -309,9 +309,9 @@ bool DenseBase<Derived>::isApproxToConstant
   * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
 template<typename Derived>
 bool DenseBase<Derived>::isConstant
-(const Scalar& value, RealScalar prec) const
+(const Scalar& val, const RealScalar& prec) const
 {
-  return isApproxToConstant(value, prec);
+  return isApproxToConstant(val, prec);
 }
 
 /** Alias for setConstant(): sets all coefficients in this expression to \a value.
@@ -319,9 +319,9 @@ bool DenseBase<Derived>::isConstant
   * \sa setConstant(), Constant(), class CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& value)
+EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& val)
 {
-  setConstant(value);
+  setConstant(val);
 }
 
 /** Sets all coefficients in this expression to \a value.
@@ -329,9 +329,9 @@ EIGEN_STRONG_INLINE void DenseBase<Derived>::fill(const Scalar& value)
   * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& value)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& val)
 {
-  return derived() = Constant(rows(), cols(), value);
+  return derived() = Constant(rows(), cols(), val);
 }
 
 /** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value.
@@ -345,10 +345,10 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setConstant(const Scalar& value
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setConstant(Index size, const Scalar& value)
+PlainObjectBase<Derived>::setConstant(Index size, const Scalar& val)
 {
   resize(size);
-  return setConstant(value);
+  return setConstant(val);
 }
 
 /** Resizes to the given size, and sets all coefficients in this expression to the given \a value.
@@ -364,10 +364,10 @@ PlainObjectBase<Derived>::setConstant(Index size, const Scalar& value)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& value)
+PlainObjectBase<Derived>::setConstant(Index nbRows, Index nbCols, const Scalar& val)
 {
-  resize(rows, cols);
-  return setConstant(value);
+  resize(nbRows, nbCols);
+  return setConstant(val);
 }
 
 /**
@@ -384,10 +384,10 @@ PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& valu
   * \sa CwiseNullaryOp
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index size, const Scalar& low, const Scalar& high)
+EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return derived() = Derived::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
+  return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op<Scalar,false>(low,high,newSize));
 }
 
 /**
@@ -425,9 +425,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low,
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Zero(Index rows, Index cols)
+DenseBase<Derived>::Zero(Index nbRows, Index nbCols)
 {
-  return Constant(rows, cols, Scalar(0));
+  return Constant(nbRows, nbCols, Scalar(0));
 }
 
 /** \returns an expression of a zero vector.
@@ -479,7 +479,7 @@ DenseBase<Derived>::Zero()
   * \sa class CwiseNullaryOp, Zero()
   */
 template<typename Derived>
-bool DenseBase<Derived>::isZero(RealScalar prec) const
+bool DenseBase<Derived>::isZero(const RealScalar& prec) const
 {
   for(Index j = 0; j < cols(); ++j)
     for(Index i = 0; i < rows(); ++i)
@@ -512,9 +512,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setZero()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setZero(Index size)
+PlainObjectBase<Derived>::setZero(Index newSize)
 {
-  resize(size);
+  resize(newSize);
   return setConstant(Scalar(0));
 }
 
@@ -530,9 +530,9 @@ PlainObjectBase<Derived>::setZero(Index size)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setZero(Index rows, Index cols)
+PlainObjectBase<Derived>::setZero(Index nbRows, Index nbCols)
 {
-  resize(rows, cols);
+  resize(nbRows, nbCols);
   return setConstant(Scalar(0));
 }
 
@@ -554,9 +554,9 @@ PlainObjectBase<Derived>::setZero(Index rows, Index cols)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(Index rows, Index cols)
+DenseBase<Derived>::Ones(Index nbRows, Index nbCols)
 {
-  return Constant(rows, cols, Scalar(1));
+  return Constant(nbRows, nbCols, Scalar(1));
 }
 
 /** \returns an expression of a vector where all coefficients equal one.
@@ -577,9 +577,9 @@ DenseBase<Derived>::Ones(Index rows, Index cols)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename DenseBase<Derived>::ConstantReturnType
-DenseBase<Derived>::Ones(Index size)
+DenseBase<Derived>::Ones(Index newSize)
 {
-  return Constant(size, Scalar(1));
+  return Constant(newSize, Scalar(1));
 }
 
 /** \returns an expression of a fixed-size matrix or vector where all coefficients equal one.
@@ -609,7 +609,7 @@ DenseBase<Derived>::Ones()
   */
 template<typename Derived>
 bool DenseBase<Derived>::isOnes
-(RealScalar prec) const
+(const RealScalar& prec) const
 {
   return isApproxToConstant(Scalar(1), prec);
 }
@@ -638,9 +638,9 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setOnes()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setOnes(Index size)
+PlainObjectBase<Derived>::setOnes(Index newSize)
 {
-  resize(size);
+  resize(newSize);
   return setConstant(Scalar(1));
 }
 
@@ -656,9 +656,9 @@ PlainObjectBase<Derived>::setOnes(Index size)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
+PlainObjectBase<Derived>::setOnes(Index nbRows, Index nbCols)
 {
-  resize(rows, cols);
+  resize(nbRows, nbCols);
   return setConstant(Scalar(1));
 }
 
@@ -680,9 +680,9 @@ PlainObjectBase<Derived>::setOnes(Index rows, Index cols)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::IdentityReturnType
-MatrixBase<Derived>::Identity(Index rows, Index cols)
+MatrixBase<Derived>::Identity(Index nbRows, Index nbCols)
 {
-  return DenseBase<Derived>::NullaryExpr(rows, cols, internal::scalar_identity_op<Scalar>());
+  return DenseBase<Derived>::NullaryExpr(nbRows, nbCols, internal::scalar_identity_op<Scalar>());
 }
 
 /** \returns an expression of the identity matrix (not necessarily square).
@@ -714,7 +714,7 @@ MatrixBase<Derived>::Identity()
   */
 template<typename Derived>
 bool MatrixBase<Derived>::isIdentity
-(RealScalar prec) const
+(const RealScalar& prec) const
 {
   for(Index j = 0; j < cols(); ++j)
   {
@@ -785,9 +785,9 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
   * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index cols)
+EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index nbRows, Index nbCols)
 {
-  derived().resize(rows, cols);
+  derived().resize(nbRows, nbCols);
   return setIdentity();
 }
 
@@ -798,10 +798,10 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity(Index rows, Index
   * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW()
   */
 template<typename Derived>
-EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index size, Index i)
+EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::Unit(Index newSize, Index i)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return BasisReturnType(SquareMatrixType::Identity(size,size), i);
+  return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i);
 }
 
 /** \returns an expression of the i-th unit (basis) vector.

resources/3rdparty/eigen/Eigen/src/Core/CwiseUnaryOp.h

@@ -98,15 +98,15 @@ class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
     typedef typename internal::dense_xpr_base<CwiseUnaryOp<UnaryOp, XprType> >::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
 
-    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
     {
-      return derived().functor()(derived().nestedExpression().coeff(row, col));
+      return derived().functor()(derived().nestedExpression().coeff(rowId, colId));
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
     {
-      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(row, col));
+      return derived().functor().packetOp(derived().nestedExpression().template packet<LoadMode>(rowId, colId));
     }
 
     EIGEN_STRONG_INLINE const Scalar coeff(Index index) const

resources/3rdparty/eigen/Eigen/src/Core/DenseBase.h

@@ -204,21 +204,21 @@ template<typename Derived> class DenseBase
       * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
       * nothing else.
       */
-    void resize(Index size)
+    void resize(Index newSize)
     {
-      EIGEN_ONLY_USED_FOR_DEBUG(size);
-      eigen_assert(size == this->size()
+      EIGEN_ONLY_USED_FOR_DEBUG(newSize);
+      eigen_assert(newSize == this->size()
                 && "DenseBase::resize() does not actually allow to resize.");
     }
     /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are
       * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does
       * nothing else.
       */
-    void resize(Index rows, Index cols)
+    void resize(Index nbRows, Index nbCols)
     {
-      EIGEN_ONLY_USED_FOR_DEBUG(rows);
-      EIGEN_ONLY_USED_FOR_DEBUG(cols);
-      eigen_assert(rows == this->rows() && cols == this->cols()
+      EIGEN_ONLY_USED_FOR_DEBUG(nbRows);
+      EIGEN_ONLY_USED_FOR_DEBUG(nbCols);
+      eigen_assert(nbRows == this->rows() && nbCols == this->cols()
                 && "DenseBase::resize() does not actually allow to resize.");
     }
 
@@ -348,17 +348,17 @@ template<typename Derived> class DenseBase
 
     template<typename OtherDerived>
     bool isApprox(const DenseBase<OtherDerived>& other,
-                  RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+                  const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
     bool isMuchSmallerThan(const RealScalar& other,
-                           RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
     template<typename OtherDerived>
     bool isMuchSmallerThan(const DenseBase<OtherDerived>& other,
-                           RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+                           const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
-    bool isApproxToConstant(const Scalar& value, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isConstant(const Scalar& value, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isZero(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isOnes(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isZero(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isOnes(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
     inline Derived& operator*=(const Scalar& other);
     inline Derived& operator/=(const Scalar& other);

resources/3rdparty/eigen/Eigen/src/Core/DenseCoeffsBase.h

@@ -427,22 +427,22 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
 
     template<int StoreMode>
     EIGEN_STRONG_INLINE void writePacket
-    (Index row, Index col, const typename internal::packet_traits<Scalar>::type& x)
+    (Index row, Index col, const typename internal::packet_traits<Scalar>::type& val)
     {
       eigen_internal_assert(row >= 0 && row < rows()
                         && col >= 0 && col < cols());
-      derived().template writePacket<StoreMode>(row,col,x);
+      derived().template writePacket<StoreMode>(row,col,val);
     }
 
 
     /** \internal */
     template<int StoreMode>
     EIGEN_STRONG_INLINE void writePacketByOuterInner
-    (Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& x)
+    (Index outer, Index inner, const typename internal::packet_traits<Scalar>::type& val)
     {
       writePacket<StoreMode>(rowIndexByOuterInner(outer, inner),
                             colIndexByOuterInner(outer, inner),
-                            x);
+                            val);
     }
 
     /** \internal
@@ -456,10 +456,10 @@ class DenseCoeffsBase<Derived, WriteAccessors> : public DenseCoeffsBase<Derived,
       */
     template<int StoreMode>
     EIGEN_STRONG_INLINE void writePacket
-    (Index index, const typename internal::packet_traits<Scalar>::type& x)
+    (Index index, const typename internal::packet_traits<Scalar>::type& val)
     {
       eigen_internal_assert(index >= 0 && index < size());
-      derived().template writePacket<StoreMode>(index,x);
+      derived().template writePacket<StoreMode>(index,val);
     }
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN

resources/3rdparty/eigen/Eigen/src/Core/DenseStorage.h

@@ -35,8 +35,16 @@ template <typename T, int Size, int MatrixOrArrayOptions,
 struct plain_array
 {
   T array[Size];
-  plain_array() {}
-  plain_array(constructor_without_unaligned_array_assert) {}
+
+  plain_array() 
+  { 
+    EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+  }
+
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+  }
 };
 
 #ifdef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
@@ -53,8 +61,17 @@ template <typename T, int Size, int MatrixOrArrayOptions>
 struct plain_array<T, Size, MatrixOrArrayOptions, 16>
 {
   EIGEN_USER_ALIGN16 T array[Size];
-  plain_array() { EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf) }
-  plain_array(constructor_without_unaligned_array_assert) {}
+
+  plain_array() 
+  { 
+    EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf);
+    EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+  }
+
+  plain_array(constructor_without_unaligned_array_assert) 
+  { 
+    EIGEN_STATIC_ASSERT(Size * sizeof(T) <= 128 * 128 * 8, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG);
+  }
 };
 
 template <typename T, int MatrixOrArrayOptions, int Alignment>
@@ -135,13 +152,13 @@ template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic
     inline explicit DenseStorage() : m_rows(0), m_cols(0) {}
     inline DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex cols) : m_rows(rows), m_cols(cols) {}
+    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {}
     inline void swap(DenseStorage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
-    inline DenseIndex rows(void) const {return m_rows;}
-    inline DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
-    inline void resize(DenseIndex, DenseIndex rows, DenseIndex cols) { m_rows = rows; m_cols = cols; }
+    inline DenseIndex rows() const {return m_rows;}
+    inline DenseIndex cols() const {return m_cols;}
+    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
+    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; }
     inline const T *data() const { return m_data.array; }
     inline T *data() { return m_data.array; }
 };
@@ -155,12 +172,12 @@ template<typename T, int Size, int _Cols, int _Options> class DenseStorage<T, Si
     inline explicit DenseStorage() : m_rows(0) {}
     inline DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex rows, DenseIndex) : m_rows(rows) {}
+    inline DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {}
     inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
     inline DenseIndex rows(void) const {return m_rows;}
     inline DenseIndex cols(void) const {return _Cols;}
-    inline void conservativeResize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
-    inline void resize(DenseIndex, DenseIndex rows, DenseIndex) { m_rows = rows; }
+    inline void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
+    inline void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; }
     inline const T *data() const { return m_data.array; }
     inline T *data() { return m_data.array; }
 };
@@ -174,12 +191,12 @@ template<typename T, int Size, int _Rows, int _Options> class DenseStorage<T, Si
     inline explicit DenseStorage() : m_cols(0) {}
     inline DenseStorage(internal::constructor_without_unaligned_array_assert)
       : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {}
-    inline DenseStorage(DenseIndex, DenseIndex, DenseIndex cols) : m_cols(cols) {}
+    inline DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {}
     inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
     inline DenseIndex rows(void) const {return _Rows;}
     inline DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
-    inline void resize(DenseIndex, DenseIndex, DenseIndex cols) { m_cols = cols; }
+    inline void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
+    inline void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; }
     inline const T *data() const { return m_data.array; }
     inline T *data() { return m_data.array; }
 };
@@ -194,21 +211,21 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
     inline explicit DenseStorage() : m_data(0), m_rows(0), m_cols(0) {}
     inline DenseStorage(internal::constructor_without_unaligned_array_assert)
        : m_data(0), m_rows(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex cols)
-      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows), m_cols(cols) 
+    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
+      : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows), m_cols(nbCols)
     { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
     inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, m_rows*m_cols); }
     inline void swap(DenseStorage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
     inline DenseIndex rows(void) const {return m_rows;}
     inline DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex cols)
+    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*m_cols);
-      m_rows = rows;
-      m_cols = cols;
+      m_rows = nbRows;
+      m_cols = nbCols;
     }
-    void resize(DenseIndex size, DenseIndex rows, DenseIndex cols)
+    void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols)
     {
       if(size != m_rows*m_cols)
       {
@@ -219,8 +236,8 @@ template<typename T, int _Options> class DenseStorage<T, Dynamic, Dynamic, Dynam
           m_data = 0;
         EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
       }
-      m_rows = rows;
-      m_cols = cols;
+      m_rows = nbRows;
+      m_cols = nbCols;
     }
     inline const T *data() const { return m_data; }
     inline T *data() { return m_data; }
@@ -234,18 +251,18 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
   public:
     inline explicit DenseStorage() : m_data(0), m_cols(0) {}
     inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex cols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(cols)
+    inline DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_cols(nbCols)
     { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
     inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
     inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
     static inline DenseIndex rows(void) {return _Rows;}
     inline DenseIndex cols(void) const {return m_cols;}
-    inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols)
+    inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, _Rows*m_cols);
-      m_cols = cols;
+      m_cols = nbCols;
     }
-    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex cols)
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols)
     {
       if(size != _Rows*m_cols)
       {
@@ -256,7 +273,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
           m_data = 0;
         EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
       }
-      m_cols = cols;
+      m_cols = nbCols;
     }
     inline const T *data() const { return m_data; }
     inline T *data() { return m_data; }
@@ -270,18 +287,18 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
   public:
     inline explicit DenseStorage() : m_data(0), m_rows(0) {}
     inline DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
-    inline DenseStorage(DenseIndex size, DenseIndex rows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(rows)
+    inline DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto<T,(_Options&DontAlign)==0>(size)), m_rows(nbRows)
     { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
     inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
     inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
     inline DenseIndex rows(void) const {return m_rows;}
     static inline DenseIndex cols(void) {return _Cols;}
-    inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex)
+    inline void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
-      m_rows = rows;
+      m_rows = nbRows;
     }
-    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex rows, DenseIndex)
+    EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex)
     {
       if(size != m_rows*_Cols)
       {
@@ -292,7 +309,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
           m_data = 0;
         EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
       }
-      m_rows = rows;
+      m_rows = nbRows;
     }
     inline const T *data() const { return m_data; }
     inline T *data() { return m_data; }

resources/3rdparty/eigen/Eigen/src/Core/Diagonal.h

@@ -41,12 +41,12 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   typedef typename MatrixType::StorageKind StorageKind;
   enum {
-    RowsAtCompileTime = (int(DiagIndex) == Dynamic || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
-    : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
-                            MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
+    RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
+                      : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                                              MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
     ColsAtCompileTime = 1,
     MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
-                         : DiagIndex == Dynamic ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
+                         : DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
                                                                               MatrixType::MaxColsAtCompileTime)
                          : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
                                                  MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
@@ -61,15 +61,16 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
 };
 }
 
-template<typename MatrixType, int DiagIndex> class Diagonal
-   : public internal::dense_xpr_base< Diagonal<MatrixType,DiagIndex> >::type
+template<typename MatrixType, int _DiagIndex> class Diagonal
+   : public internal::dense_xpr_base< Diagonal<MatrixType,_DiagIndex> >::type
 {
   public:
 
+    enum { DiagIndex = _DiagIndex };
     typedef typename internal::dense_xpr_base<Diagonal>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal)
 
-    inline Diagonal(MatrixType& matrix, Index index = DiagIndex) : m_matrix(matrix), m_index(index) {}
+    inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {}
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
 
@@ -113,20 +114,20 @@ template<typename MatrixType, int DiagIndex> class Diagonal
       return m_matrix.coeff(row+rowOffset(), row+colOffset());
     }
 
-    inline Scalar& coeffRef(Index index)
+    inline Scalar& coeffRef(Index idx)
     {
       EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
+      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
     }
 
-    inline const Scalar& coeffRef(Index index) const
+    inline const Scalar& coeffRef(Index idx) const
     {
-      return m_matrix.const_cast_derived().coeffRef(index+rowOffset(), index+colOffset());
+      return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset());
     }
 
-    inline CoeffReturnType coeff(Index index) const
+    inline CoeffReturnType coeff(Index idx) const
     {
-      return m_matrix.coeff(index+rowOffset(), index+colOffset());
+      return m_matrix.coeff(idx+rowOffset(), idx+colOffset());
     }
 
     const typename internal::remove_all<typename MatrixType::Nested>::type& 
@@ -142,7 +143,7 @@ template<typename MatrixType, int DiagIndex> class Diagonal
 
   protected:
     typename MatrixType::Nested m_matrix;
-    const internal::variable_if_dynamic<Index, DiagIndex> m_index;
+    const internal::variable_if_dynamicindex<Index, DiagIndex> m_index;
 
   private:
     // some compilers may fail to optimize std::max etc in case of compile-time constants...
@@ -189,18 +190,18 @@ MatrixBase<Derived>::diagonal() const
   *
   * \sa MatrixBase::diagonal(), class Diagonal */
 template<typename Derived>
-inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<Dynamic>::Type
+inline typename MatrixBase<Derived>::template DiagonalIndexReturnType<DynamicIndex>::Type
 MatrixBase<Derived>::diagonal(Index index)
 {
-  return typename DiagonalIndexReturnType<Dynamic>::Type(derived(), index);
+  return typename DiagonalIndexReturnType<DynamicIndex>::Type(derived(), index);
 }
 
 /** This is the const version of diagonal(Index). */
 template<typename Derived>
-inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<Dynamic>::Type
+inline typename MatrixBase<Derived>::template ConstDiagonalIndexReturnType<DynamicIndex>::Type
 MatrixBase<Derived>::diagonal(Index index) const
 {
-  return typename ConstDiagonalIndexReturnType<Dynamic>::Type(derived(), index);
+  return typename ConstDiagonalIndexReturnType<DynamicIndex>::Type(derived(), index);
 }
 
 /** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this

resources/3rdparty/eigen/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
@@ -238,7 +250,7 @@ class DiagonalWrapper
     #endif
 
     /** Constructor from expression of diagonal coefficients to wrap. */
-    inline DiagonalWrapper(DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
+    inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {}
 
     /** \returns a const reference to the wrapped expression of diagonal coefficients. */
     const DiagonalVectorType& diagonal() const { return m_diagonal; }
@@ -272,7 +284,7 @@ MatrixBase<Derived>::asDiagonal() const
   * \sa asDiagonal()
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isDiagonal(RealScalar prec) const
+bool MatrixBase<Derived>::isDiagonal(const RealScalar& prec) const
 {
   if(cols() != rows()) return false;
   RealScalar maxAbsOnDiagonal = static_cast<RealScalar>(-1);

resources/3rdparty/eigen/Eigen/src/Core/DiagonalProduct.h

@@ -103,9 +103,9 @@ class DiagonalProduct : internal::no_assignment_operator,
 template<typename Derived>
 template<typename DiagonalDerived>
 inline const DiagonalProduct<Derived, DiagonalDerived, OnTheRight>
-MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &diagonal) const
+MatrixBase<Derived>::operator*(const DiagonalBase<DiagonalDerived> &a_diagonal) const
 {
-  return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), diagonal.derived());
+  return DiagonalProduct<Derived, DiagonalDerived, OnTheRight>(derived(), a_diagonal.derived());
 }
 
 /** \returns the diagonal matrix product of \c *this by the matrix \a matrix.

resources/3rdparty/eigen/Eigen/src/Core/Dot.h

@@ -223,7 +223,7 @@ MatrixBase<Derived>::lpNorm() const
 template<typename Derived>
 template<typename OtherDerived>
 bool MatrixBase<Derived>::isOrthogonal
-(const MatrixBase<OtherDerived>& other, RealScalar prec) const
+(const MatrixBase<OtherDerived>& other, const RealScalar& prec) const
 {
   typename internal::nested<Derived,2>::type nested(derived());
   typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
@@ -242,7 +242,7 @@ bool MatrixBase<Derived>::isOrthogonal
   * Output: \verbinclude MatrixBase_isUnitary.out
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isUnitary(RealScalar prec) const
+bool MatrixBase<Derived>::isUnitary(const RealScalar& prec) const
 {
   typename Derived::Nested nested(derived());
   for(Index i = 0; i < cols(); ++i)

resources/3rdparty/eigen/Eigen/src/Core/Functors.h

@@ -204,21 +204,28 @@ struct functor_traits<scalar_difference_op<Scalar> > {
   *
   * \sa class CwiseBinaryOp, Cwise::operator/()
   */
-template<typename Scalar> struct scalar_quotient_op {
+template<typename LhsScalar,typename RhsScalar> struct scalar_quotient_op {
+  enum {
+    // TODO vectorize mixed product
+    Vectorizable = is_same<LhsScalar,RhsScalar>::value && packet_traits<LhsScalar>::HasDiv && packet_traits<RhsScalar>::HasDiv
+  };
+  typedef typename scalar_product_traits<LhsScalar,RhsScalar>::ReturnType result_type;
   EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a / b; }
+  EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a / b; }
   template<typename Packet>
   EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
   { return internal::pdiv(a,b); }
 };
-template<typename Scalar>
-struct functor_traits<scalar_quotient_op<Scalar> > {
+template<typename LhsScalar,typename RhsScalar>
+struct functor_traits<scalar_quotient_op<LhsScalar,RhsScalar> > {
   enum {
-    Cost = 2 * NumTraits<Scalar>::MulCost,
-    PacketAccess = packet_traits<Scalar>::HasDiv
+    Cost = (NumTraits<LhsScalar>::MulCost + NumTraits<RhsScalar>::MulCost), // rough estimate!
+    PacketAccess = scalar_quotient_op<LhsScalar,RhsScalar>::Vectorizable
   };
 };
 
+
+
 /** \internal
   * \brief Template functor to compute the and of two booleans
   *
@@ -447,7 +454,7 @@ 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 +485,6 @@ 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 +494,19 @@ 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 > {
-  EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other)
-    : scalar_quotient1_impl<Scalar, NumTraits<Scalar>::IsInteger >(other) {}
+struct scalar_quotient1_op {
+  typedef typename packet_traits<Scalar>::type Packet;
+  // 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
 
@@ -660,6 +645,7 @@ template<typename Scalar> struct functor_has_linear_access<scalar_identity_op<Sc
 template<typename Functor> struct functor_allows_mixing_real_and_complex { enum { ret = 0 }; };
 template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
 template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_conj_product_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
+template<typename LhsScalar,typename RhsScalar> struct functor_allows_mixing_real_and_complex<scalar_quotient_op<LhsScalar,RhsScalar> > { enum { ret = 1 }; };
 
 
 /** \internal

resources/3rdparty/eigen/Eigen/src/Core/Fuzzy.h

@@ -19,7 +19,7 @@ namespace internal
 template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
 struct isApprox_selector
 {
-  static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
+  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
   {
     using std::min;
     typename internal::nested<Derived,2>::type nested(x);
@@ -31,7 +31,7 @@ struct isApprox_selector
 template<typename Derived, typename OtherDerived>
 struct isApprox_selector<Derived, OtherDerived, true>
 {
-  static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar)
+  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&)
   {
     return x.matrix() == y.matrix();
   }
@@ -40,7 +40,7 @@ struct isApprox_selector<Derived, OtherDerived, true>
 template<typename Derived, typename OtherDerived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
 struct isMuchSmallerThan_object_selector
 {
-  static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
+  static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec)
   {
     return x.cwiseAbs2().sum() <= abs2(prec) * y.cwiseAbs2().sum();
   }
@@ -49,7 +49,7 @@ struct isMuchSmallerThan_object_selector
 template<typename Derived, typename OtherDerived>
 struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
 {
-  static bool run(const Derived& x, const OtherDerived&, typename Derived::RealScalar)
+  static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&)
   {
     return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
   }
@@ -58,7 +58,7 @@ struct isMuchSmallerThan_object_selector<Derived, OtherDerived, true>
 template<typename Derived, bool is_integer = NumTraits<typename Derived::Scalar>::IsInteger>
 struct isMuchSmallerThan_scalar_selector
 {
-  static bool run(const Derived& x, const typename Derived::RealScalar& y, typename Derived::RealScalar prec)
+  static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec)
   {
     return x.cwiseAbs2().sum() <= abs2(prec * y);
   }
@@ -67,7 +67,7 @@ struct isMuchSmallerThan_scalar_selector
 template<typename Derived>
 struct isMuchSmallerThan_scalar_selector<Derived, true>
 {
-  static bool run(const Derived& x, const typename Derived::RealScalar&, typename Derived::RealScalar)
+  static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&)
   {
     return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix();
   }
@@ -97,7 +97,7 @@ template<typename Derived>
 template<typename OtherDerived>
 bool DenseBase<Derived>::isApprox(
   const DenseBase<OtherDerived>& other,
-  RealScalar prec
+  const RealScalar& prec
 ) const
 {
   return internal::isApprox_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
@@ -119,7 +119,7 @@ bool DenseBase<Derived>::isApprox(
 template<typename Derived>
 bool DenseBase<Derived>::isMuchSmallerThan(
   const typename NumTraits<Scalar>::Real& other,
-  RealScalar prec
+  const RealScalar& prec
 ) const
 {
   return internal::isMuchSmallerThan_scalar_selector<Derived>::run(derived(), other, prec);
@@ -139,7 +139,7 @@ template<typename Derived>
 template<typename OtherDerived>
 bool DenseBase<Derived>::isMuchSmallerThan(
   const DenseBase<OtherDerived>& other,
-  RealScalar prec
+  const RealScalar& prec
 ) const
 {
   return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);

resources/3rdparty/eigen/Eigen/src/Core/GeneralProduct.h

@@ -311,7 +311,7 @@ class GeneralProduct<Lhs, Rhs, GemvProduct>
     typedef typename Lhs::Scalar LhsScalar;
     typedef typename Rhs::Scalar RhsScalar;
 
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+    GeneralProduct(const Lhs& a_lhs, const Rhs& a_rhs) : Base(a_lhs,a_rhs)
     {
 //       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
 //         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)

resources/3rdparty/eigen/Eigen/src/Core/Map.h

@@ -148,8 +148,8 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
       * \param size the size of the vector expression
       * \param stride optional Stride object, passing the strides.
       */
-    inline Map(PointerArgType data, Index size, const StrideType& stride = StrideType())
-      : Base(cast_to_pointer_type(data), size), m_stride(stride)
+    inline Map(PointerArgType dataPtr, Index a_size, const StrideType& a_stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr), a_size), m_stride(a_stride)
     {
       PlainObjectType::Base::_check_template_params();
     }
@@ -161,8 +161,8 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
       * \param cols the number of columns of the matrix expression
       * \param stride optional Stride object, passing the strides.
       */
-    inline Map(PointerArgType data, Index rows, Index cols, const StrideType& stride = StrideType())
-      : Base(cast_to_pointer_type(data), rows, cols), m_stride(stride)
+    inline Map(PointerArgType dataPtr, Index nbRows, Index nbCols, const StrideType& a_stride = StrideType())
+      : Base(cast_to_pointer_type(dataPtr), nbRows, nbCols), m_stride(a_stride)
     {
       PlainObjectType::Base::_check_template_params();
     }

resources/3rdparty/eigen/Eigen/src/Core/MapBase.h

@@ -87,9 +87,9 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
       */
     inline const Scalar* data() const { return m_data; }
 
-    inline const Scalar& coeff(Index row, Index col) const
+    inline const Scalar& coeff(Index rowId, Index colId) const
     {
-      return m_data[col * colStride() + row * rowStride()];
+      return m_data[colId * colStride() + rowId * rowStride()];
     }
 
     inline const Scalar& coeff(Index index) const
@@ -98,9 +98,9 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
       return m_data[index * innerStride()];
     }
 
-    inline const Scalar& coeffRef(Index row, Index col) const
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
-      return this->m_data[col * colStride() + row * rowStride()];
+      return this->m_data[colId * colStride() + rowId * rowStride()];
     }
 
     inline const Scalar& coeffRef(Index index) const
@@ -110,10 +110,10 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
     }
 
     template<int LoadMode>
-    inline PacketScalar packet(Index row, Index col) const
+    inline PacketScalar packet(Index rowId, Index colId) const
     {
       return internal::ploadt<PacketScalar, LoadMode>
-               (m_data + (col * colStride() + row * rowStride()));
+               (m_data + (colId * colStride() + rowId * rowStride()));
     }
 
     template<int LoadMode>
@@ -123,29 +123,29 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
       return internal::ploadt<PacketScalar, LoadMode>(m_data + index * innerStride());
     }
 
-    inline MapBase(PointerType data) : m_data(data), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
+    inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime)
     {
       EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived)
       checkSanity();
     }
 
-    inline MapBase(PointerType data, Index size)
-            : m_data(data),
-              m_rows(RowsAtCompileTime == Dynamic ? size : Index(RowsAtCompileTime)),
-              m_cols(ColsAtCompileTime == Dynamic ? size : Index(ColsAtCompileTime))
+    inline MapBase(PointerType dataPtr, Index vecSize)
+            : m_data(dataPtr),
+              m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)),
+              m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime))
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-      eigen_assert(size >= 0);
-      eigen_assert(data == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
+      eigen_assert(vecSize >= 0);
+      eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize);
       checkSanity();
     }
 
-    inline MapBase(PointerType data, Index rows, Index cols)
-            : m_data(data), m_rows(rows), m_cols(cols)
+    inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols)
+            : m_data(dataPtr), m_rows(nbRows), m_cols(nbCols)
     {
-      eigen_assert( (data == 0)
-              || (   rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-                  && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
+      eigen_assert( (dataPtr == 0)
+              || (   nbRows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows)
+                  && nbCols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols)));
       checkSanity();
     }
 
@@ -210,23 +210,23 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
     }
 
     template<int StoreMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    inline void writePacket(Index row, Index col, const PacketScalar& val)
     {
       internal::pstoret<Scalar, PacketScalar, StoreMode>
-               (this->m_data + (col * colStride() + row * rowStride()), x);
+               (this->m_data + (col * colStride() + row * rowStride()), val);
     }
 
     template<int StoreMode>
-    inline void writePacket(Index index, const PacketScalar& x)
+    inline void writePacket(Index index, const PacketScalar& val)
     {
       EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived)
       internal::pstoret<Scalar, PacketScalar, StoreMode>
-                (this->m_data + index * innerStride(), x);
+                (this->m_data + index * innerStride(), val);
     }
 
-    explicit inline MapBase(PointerType data) : Base(data) {}
-    inline MapBase(PointerType data, Index size) : Base(data, size) {}
-    inline MapBase(PointerType data, Index rows, Index cols) : Base(data, rows, cols) {}
+    explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {}
+    inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {}
+    inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {}
 
     Derived& operator=(const MapBase& other)
     {

resources/3rdparty/eigen/Eigen/src/Core/MathFunctions.h

@@ -519,6 +519,53 @@ inline EIGEN_MATHFUNC_RETVAL(atan2, Scalar) atan2(const Scalar& x, const Scalar&
   return EIGEN_MATHFUNC_IMPL(atan2, Scalar)::run(x, y);
 }
 
+/****************************************************************************
+* Implementation of atanh2                                                *
+****************************************************************************/
+
+template<typename Scalar, bool IsInteger>
+struct atanh2_default_impl
+{
+  typedef Scalar retval;
+  typedef typename NumTraits<Scalar>::Real RealScalar;
+  static inline Scalar run(const Scalar& x, const Scalar& y)
+  {
+    using std::abs;
+    using std::log;
+    using std::sqrt;
+    Scalar z = x / y;
+    if (abs(z) > sqrt(NumTraits<RealScalar>::epsilon()))
+      return RealScalar(0.5) * log((y + x) / (y - x));
+    else
+      return z + z*z*z / RealScalar(3);
+  }
+};
+
+template<typename Scalar>
+struct atanh2_default_impl<Scalar, true>
+{
+  static inline Scalar run(const Scalar&, const Scalar&)
+  {
+    EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
+    return Scalar(0);
+  }
+};
+
+template<typename Scalar>
+struct atanh2_impl : atanh2_default_impl<Scalar, NumTraits<Scalar>::IsInteger> {};
+
+template<typename Scalar>
+struct atanh2_retval
+{
+  typedef Scalar type;
+};
+
+template<typename Scalar>
+inline EIGEN_MATHFUNC_RETVAL(atanh2, Scalar) atanh2(const Scalar& x, const Scalar& y)
+{
+  return EIGEN_MATHFUNC_IMPL(atanh2, Scalar)::run(x, y);
+}
+
 /****************************************************************************
 * Implementation of pow                                                  *
 ****************************************************************************/

resources/3rdparty/eigen/Eigen/src/Core/MatrixBase.h

@@ -162,6 +162,9 @@ template<typename Derived> class MatrixBase
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     template<typename ProductDerived, typename Lhs, typename Rhs>
     Derived& lazyAssign(const ProductBase<ProductDerived, Lhs,Rhs>& other);
+
+    template<typename ProductDerived, typename Lhs, typename Rhs>
+    Derived& lazyAssign(const MatrixPowerProductBase<ProductDerived, Lhs,Rhs>& other);
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
     template<typename OtherDerived>
@@ -224,11 +227,11 @@ template<typename Derived> class MatrixBase
     // Note: The "MatrixBase::" prefixes are added to help MSVC9 to match these declarations with the later implementations.
     // On the other hand they confuse MSVC8...
     #if (defined _MSC_VER) && (_MSC_VER >= 1500) // 2008 or later
-    typename MatrixBase::template DiagonalIndexReturnType<Dynamic>::Type diagonal(Index index);
-    typename MatrixBase::template ConstDiagonalIndexReturnType<Dynamic>::Type diagonal(Index index) const;
+    typename MatrixBase::template DiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index);
+    typename MatrixBase::template ConstDiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index) const;
     #else
-    typename DiagonalIndexReturnType<Dynamic>::Type diagonal(Index index);
-    typename ConstDiagonalIndexReturnType<Dynamic>::Type diagonal(Index index) const;
+    typename DiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index);
+    typename ConstDiagonalIndexReturnType<DynamicIndex>::Type diagonal(Index index) const;
     #endif
 
     #ifdef EIGEN2_SUPPORT
@@ -237,7 +240,7 @@ 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
@@ -255,7 +258,7 @@ template<typename Derived> class MatrixBase
     template<unsigned int UpLo> typename ConstSelfAdjointViewReturnType<UpLo>::Type selfadjointView() const;
 
     const SparseView<Derived> sparseView(const Scalar& m_reference = Scalar(0),
-                                         typename NumTraits<Scalar>::Real m_epsilon = NumTraits<Scalar>::dummy_precision()) const;
+                                         const typename NumTraits<Scalar>::Real& m_epsilon = NumTraits<Scalar>::dummy_precision()) const;
     static const IdentityReturnType Identity();
     static const IdentityReturnType Identity(Index rows, Index cols);
     static const BasisReturnType Unit(Index size, Index i);
@@ -271,16 +274,16 @@ template<typename Derived> class MatrixBase
     Derived& setIdentity();
     Derived& setIdentity(Index rows, Index cols);
 
-    bool isIdentity(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isDiagonal(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isIdentity(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isDiagonal(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
-    bool isUpperTriangular(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isLowerTriangular(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isUpperTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isLowerTriangular(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
     template<typename OtherDerived>
     bool isOrthogonal(const MatrixBase<OtherDerived>& other,
-                      RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-    bool isUnitary(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
+                      const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
+    bool isUnitary(const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const;
 
     /** \returns true if each coefficients of \c *this and \a other are all exactly equal.
       * \warning When using floating point scalar values you probably should rather use a
@@ -454,6 +457,7 @@ template<typename Derived> class MatrixBase
     const MatrixFunctionReturnValue<Derived> sin() const;
     const MatrixSquareRootReturnValue<Derived> sqrt() const;
     const MatrixLogarithmReturnValue<Derived> log() const;
+    const MatrixPowerReturnValue<Derived> pow(RealScalar p) const;
 
 #ifdef EIGEN2_SUPPORT
     template<typename ProductDerived, typename Lhs, typename Rhs>

resources/3rdparty/eigen/Eigen/src/Core/NoAlias.h

@@ -82,6 +82,11 @@ class NoAlias
     { return m_expression.derived() -= CoeffBasedProduct<Lhs,Rhs,NestByRefBit>(other.lhs(), other.rhs()); }
 #endif
 
+    ExpressionType& expression() const
+    {
+      return m_expression;
+    }
+
   protected:
     ExpressionType& m_expression;
 };

resources/3rdparty/eigen/Eigen/src/Core/PermutationMatrix.h

@@ -139,9 +139,9 @@ class PermutationBase : public EigenBase<Derived>
 
     /** Resizes to given size.
       */
-    inline void resize(Index size)
+    inline void resize(Index newSize)
     {
-      indices().resize(size);
+      indices().resize(newSize);
     }
 
     /** Sets *this to be the identity permutation matrix */
@@ -153,9 +153,9 @@ class PermutationBase : public EigenBase<Derived>
 
     /** Sets *this to be the identity permutation matrix of given size.
       */
-    void setIdentity(Index size)
+    void setIdentity(Index newSize)
     {
-      resize(size);
+      resize(newSize);
       setIdentity();
     }
 
@@ -317,7 +317,7 @@ class PermutationMatrix : public PermutationBase<PermutationMatrix<SizeAtCompile
       * array's size.
       */
     template<typename Other>
-    explicit inline PermutationMatrix(const MatrixBase<Other>& indices) : m_indices(indices)
+    explicit inline PermutationMatrix(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
     {}
 
     /** Convert the Transpositions \a tr to a permutation matrix */
@@ -406,12 +406,12 @@ class Map<PermutationMatrix<SizeAtCompileTime, MaxSizeAtCompileTime, IndexType>,
     typedef typename IndicesType::Scalar Index;
     #endif
 
-    inline Map(const Index* indices)
-      : m_indices(indices)
+    inline Map(const Index* indicesPtr)
+      : m_indices(indicesPtr)
     {}
 
-    inline Map(const Index* indices, Index size)
-      : m_indices(indices,size)
+    inline Map(const Index* indicesPtr, Index size)
+      : m_indices(indicesPtr,size)
     {}
 
     /** Copies the other permutation into *this */
@@ -490,8 +490,8 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
     typedef typename Traits::IndicesType IndicesType;
     #endif
 
-    inline PermutationWrapper(const IndicesType& indices)
-      : m_indices(indices)
+    inline PermutationWrapper(const IndicesType& a_indices)
+      : m_indices(a_indices)
     {}
 
     /** const version of indices(). */

resources/3rdparty/eigen/Eigen/src/Core/PlainObjectBase.h

@@ -21,18 +21,26 @@ namespace Eigen {
 
 namespace internal {
 
-template<typename Index>
-EIGEN_ALWAYS_INLINE void check_rows_cols_for_overflow(Index rows, Index cols)
-{
-  // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
-  // we assume Index is signed
-  Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
-  bool error = (rows < 0  || cols < 0)  ? true
-             : (rows == 0 || cols == 0) ? false
-                                        : (rows > max_index / cols);
-  if (error)
-    throw_std_bad_alloc();
-}
+template<int MaxSizeAtCompileTime> struct check_rows_cols_for_overflow {
+  template<typename Index>
+  static EIGEN_ALWAYS_INLINE void run(Index, Index)
+  {
+  }
+};
+
+template<> struct check_rows_cols_for_overflow<Dynamic> {
+  template<typename Index>
+  static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols)
+  {
+    // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
+    // we assume Index is signed
+    Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
+    bool error = (rows == 0 || cols == 0) ? false
+               : (rows > max_index / cols);
+    if (error)
+      throw_std_bad_alloc();
+  }
+};
 
 template <typename Derived, typename OtherDerived = Derived, bool IsVector = bool(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
 
@@ -119,12 +127,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); }
     EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); }
 
-    EIGEN_STRONG_INLINE const Scalar& coeff(Index row, Index col) const
+    EIGEN_STRONG_INLINE const Scalar& coeff(Index rowId, Index colId) const
     {
       if(Flags & RowMajorBit)
-        return m_storage.data()[col + row * m_storage.cols()];
+        return m_storage.data()[colId + rowId * m_storage.cols()];
       else // column-major
-        return m_storage.data()[row + col * m_storage.rows()];
+        return m_storage.data()[rowId + colId * m_storage.rows()];
     }
 
     EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const
@@ -132,12 +140,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       return m_storage.data()[index];
     }
 
-    EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col)
+    EIGEN_STRONG_INLINE Scalar& coeffRef(Index rowId, Index colId)
     {
       if(Flags & RowMajorBit)
-        return m_storage.data()[col + row * m_storage.cols()];
+        return m_storage.data()[colId + rowId * m_storage.cols()];
       else // column-major
-        return m_storage.data()[row + col * m_storage.rows()];
+        return m_storage.data()[rowId + colId * m_storage.rows()];
     }
 
     EIGEN_STRONG_INLINE Scalar& coeffRef(Index index)
@@ -145,12 +153,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       return m_storage.data()[index];
     }
 
-    EIGEN_STRONG_INLINE const Scalar& coeffRef(Index row, Index col) const
+    EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const
     {
       if(Flags & RowMajorBit)
-        return m_storage.data()[col + row * m_storage.cols()];
+        return m_storage.data()[colId + rowId * m_storage.cols()];
       else // column-major
-        return m_storage.data()[row + col * m_storage.rows()];
+        return m_storage.data()[rowId + colId * m_storage.rows()];
     }
 
     EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const
@@ -160,12 +168,12 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 
     /** \internal */
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
     {
       return internal::ploadt<PacketScalar, LoadMode>
                (m_storage.data() + (Flags & RowMajorBit
-                                   ? col + row * m_storage.cols()
-                                   : row + col * m_storage.rows()));
+                                   ? colId + rowId * m_storage.cols()
+                                   : rowId + colId * m_storage.rows()));
     }
 
     /** \internal */
@@ -177,19 +185,19 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 
     /** \internal */
     template<int StoreMode>
-    EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketScalar& x)
+    EIGEN_STRONG_INLINE void writePacket(Index rowId, Index colId, const PacketScalar& val)
     {
       internal::pstoret<Scalar, PacketScalar, StoreMode>
               (m_storage.data() + (Flags & RowMajorBit
-                                   ? col + row * m_storage.cols()
-                                   : row + col * m_storage.rows()), x);
+                                   ? colId + rowId * m_storage.cols()
+                                   : rowId + colId * m_storage.rows()), val);
     }
 
     /** \internal */
     template<int StoreMode>
-    EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& x)
+    EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& val)
     {
-      internal::pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, x);
+      internal::pstoret<Scalar, PacketScalar, StoreMode>(m_storage.data() + index, val);
     }
 
     /** \returns a const pointer to the data array of this matrix */
@@ -216,17 +224,22 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t)
       */
-    EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
-    {
+    EIGEN_STRONG_INLINE void resize(Index nbRows, Index nbCols)
+    {
+      eigen_assert(   EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,nbRows==RowsAtCompileTime)
+                   && EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,nbCols==ColsAtCompileTime)
+                   && EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,nbRows<=MaxRowsAtCompileTime)
+                   && EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,nbCols<=MaxColsAtCompileTime)
+                   && nbRows>=0 && nbCols>=0 && "Invalid sizes when resizing a matrix or array.");
+      internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(nbRows, nbCols);
       #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
-        internal::check_rows_cols_for_overflow(rows, cols);
-        Index size = rows*cols;
+        Index size = nbRows*nbCols;
         bool size_changed = size != this->size();
-        m_storage.resize(size, rows, cols);
+        m_storage.resize(size, nbRows, nbCols);
         if(size_changed) EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
       #else
-        internal::check_rows_cols_for_overflow(rows, cols);
-        m_storage.resize(rows*cols, rows, cols);
+        internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(nbRows, nbCols);
+        m_storage.resize(nbRows*nbCols, nbRows, nbCols);
       #endif
     }
 
@@ -244,7 +257,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     inline void resize(Index size)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase)
-      eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
+      eigen_assert(((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime==Dynamic || size<=MaxSizeAtCompileTime)) || SizeAtCompileTime == size) && size>=0);
       #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
         bool size_changed = size != this->size();
       #endif
@@ -265,9 +278,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \sa resize(Index,Index)
       */
-    inline void resize(NoChange_t, Index cols)
+    inline void resize(NoChange_t, Index nbCols)
     {
-      resize(rows(), cols);
+      resize(rows(), nbCols);
     }
 
     /** Resizes the matrix, changing only the number of rows. For the parameter of type NoChange_t, just pass the special value \c NoChange
@@ -278,9 +291,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * \sa resize(Index,Index)
       */
-    inline void resize(Index rows, NoChange_t)
+    inline void resize(Index nbRows, NoChange_t)
     {
-      resize(rows, cols());
+      resize(nbRows, cols());
     }
 
     /** Resizes \c *this to have the same dimensions as \a other.
@@ -294,7 +307,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other)
     {
       const OtherDerived& other = _other.derived();
-      internal::check_rows_cols_for_overflow(other.rows(), other.cols());
+      internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.rows(), other.cols());
       const Index othersize = other.rows()*other.cols();
       if(RowsAtCompileTime == 1)
       {
@@ -318,9 +331,9 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       * Matrices are resized relative to the top-left element. In case values need to be 
       * appended to the matrix they will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols)
+    EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, Index nbCols)
     {
-      internal::conservative_resize_like_impl<Derived>::run(*this, rows, cols);
+      internal::conservative_resize_like_impl<Derived>::run(*this, nbRows, nbCols);
     }
 
     /** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
@@ -330,10 +343,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * In case the matrix is growing, new rows will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t)
+    EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, NoChange_t)
     {
       // Note: see the comment in conservativeResize(Index,Index)
-      conservativeResize(rows, cols());
+      conservativeResize(nbRows, cols());
     }
 
     /** Resizes the matrix to \a rows x \a cols while leaving old values untouched.
@@ -343,10 +356,10 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       *
       * In case the matrix is growing, new columns will be uninitialized.
       */
-    EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols)
+    EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index nbCols)
     {
       // Note: see the comment in conservativeResize(Index,Index)
-      conservativeResize(rows(), cols);
+      conservativeResize(rows(), nbCols);
     }
 
     /** Resizes the vector to \a size while retaining old values.
@@ -416,8 +429,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     }
 #endif
 
-    EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols)
-      : m_storage(size, rows, cols)
+    EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols)
+      : m_storage(a_size, nbRows, nbCols)
     {
 //       _check_template_params();
 //       EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
@@ -439,7 +452,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       : m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
     {
       _check_template_params();
-      internal::check_rows_cols_for_overflow(other.derived().rows(), other.derived().cols());
+      internal::check_rows_cols_for_overflow<MaxSizeAtCompileTime>::run(other.derived().rows(), other.derived().cols());
       Base::operator=(other.derived());
     }
 
@@ -600,23 +613,19 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     }
 
     template<typename T0, typename T1>
-    EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
+    EIGEN_STRONG_INLINE void _init2(Index nbRows, Index nbCols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
     {
       EIGEN_STATIC_ASSERT(bool(NumTraits<T0>::IsInteger) &&
                           bool(NumTraits<T1>::IsInteger),
                           FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
-      eigen_assert(rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-             && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
-      internal::check_rows_cols_for_overflow(rows, cols);      
-      m_storage.resize(rows*cols,rows,cols);
-      EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
+      resize(nbRows,nbCols);
     }
     template<typename T0, typename T1>
-    EIGEN_STRONG_INLINE void _init2(const Scalar& x, const Scalar& y, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
+    EIGEN_STRONG_INLINE void _init2(const Scalar& val0, const Scalar& val1, typename internal::enable_if<Base::SizeAtCompileTime==2,T0>::type* = 0)
     {
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2)
-      m_storage.data()[0] = x;
-      m_storage.data()[1] = y;
+      m_storage.data()[0] = val0;
+      m_storage.data()[1] = val1;
     }
 
     template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers>
@@ -665,7 +674,7 @@ struct internal::conservative_resize_like_impl
     if ( ( Derived::IsRowMajor && _this.cols() == cols) || // row-major and we change only the number of rows
          (!Derived::IsRowMajor && _this.rows() == rows) )  // column-major and we change only the number of columns
     {
-      internal::check_rows_cols_for_overflow(rows, cols);
+      internal::check_rows_cols_for_overflow<Derived::MaxSizeAtCompileTime>::run(rows, cols);
       _this.derived().m_storage.conservativeResize(rows*cols,rows,cols);
     }
     else

resources/3rdparty/eigen/Eigen/src/Core/Product.h

@@ -3,13 +3,15 @@
 //
 // Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
-// This Source Code Form is subject to the terms of the Mozilla Public
-// License, v. 2.0. If a copy of the MPL was not distributed with this
-// file, You can obtain one at http://mozilla.org/MPL/2.0/.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PRODUCT_H
 #define EIGEN_PRODUCT_H
 
+namespace Eigen {
+
 template<typename Lhs, typename Rhs> class Product;
 template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
 
@@ -25,25 +27,16 @@ template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
   *
   */
 
+// Use ProductReturnType to get correct traits, in particular vectorization flags
 namespace internal {
 template<typename Lhs, typename Rhs>
 struct traits<Product<Lhs, Rhs> >
-{
-  typedef MatrixXpr XprKind;
-  typedef typename remove_all<Lhs>::type LhsCleaned;
-  typedef typename remove_all<Rhs>::type RhsCleaned;
-  typedef typename scalar_product_traits<typename traits<LhsCleaned>::Scalar, typename traits<RhsCleaned>::Scalar>::ReturnType Scalar;
-  typedef typename promote_storage_type<typename traits<LhsCleaned>::StorageKind,
-                                        typename traits<RhsCleaned>::StorageKind>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<LhsCleaned>::Index,
-                                      typename traits<RhsCleaned>::Index>::type Index;
+  : traits<typename ProductReturnType<Lhs, Rhs>::Type>
+{ 
+  // We want A+B*C to be of type Product<Matrix, Sum> and not Product<Matrix, Matrix>
+  // TODO: This flag should eventually go in a separate evaluator traits class
   enum {
-    RowsAtCompileTime = LhsCleaned::RowsAtCompileTime,
-    ColsAtCompileTime = RhsCleaned::ColsAtCompileTime,
-    MaxRowsAtCompileTime = LhsCleaned::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = RhsCleaned::MaxColsAtCompileTime,
-    Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0), // TODO should be no storage order
-    CoeffReadCost = 0 // TODO CoeffReadCost should not be part of the expression traits
+    Flags = traits<typename ProductReturnType<Lhs, Rhs>::Type>::Flags & ~EvalBeforeNestingBit
   };
 };
 } // end namespace internal
@@ -95,4 +88,20 @@ class ProductImpl<Lhs,Rhs,Dense> : public internal::dense_xpr_base<Product<Lhs,R
     EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
 };
 
+/***************************************************************************
+* Implementation of matrix base methods
+***************************************************************************/
+
+
+/** \internal used to test the evaluator only
+  */
+template<typename Lhs,typename Rhs>
+const Product<Lhs,Rhs>
+prod(const Lhs& lhs, const Rhs& rhs)
+{
+  return Product<Lhs,Rhs>(lhs,rhs);
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_PRODUCT_H

resources/3rdparty/eigen/Eigen/src/Core/ProductBase.h

@@ -87,10 +87,10 @@ class ProductBase : public MatrixBase<Derived>
 
     typedef typename Base::PlainObject PlainObject;
 
-    ProductBase(const Lhs& lhs, const Rhs& rhs)
-      : m_lhs(lhs), m_rhs(rhs)
+    ProductBase(const Lhs& a_lhs, const Rhs& a_rhs)
+      : m_lhs(a_lhs), m_rhs(a_rhs)
     {
-      eigen_assert(lhs.cols() == rhs.rows()
+      eigen_assert(a_lhs.cols() == a_rhs.rows()
         && "invalid matrix product"
         && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
     }
@@ -201,7 +201,7 @@ operator*(const ProductBase<Derived,Lhs,Rhs>& prod, typename Derived::Scalar x)
 template<typename Derived,typename Lhs,typename Rhs>
 typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
                       const ScaledProduct<Derived> >::type
-operator*(const ProductBase<Derived,Lhs,Rhs>& prod, typename Derived::RealScalar x)
+operator*(const ProductBase<Derived,Lhs,Rhs>& prod, const typename Derived::RealScalar& x)
 { return ScaledProduct<Derived>(prod.derived(), x); }
 
 
@@ -213,7 +213,7 @@ operator*(typename Derived::Scalar x,const ProductBase<Derived,Lhs,Rhs>& prod)
 template<typename Derived,typename Lhs,typename Rhs>
 typename internal::enable_if<!internal::is_same<typename Derived::Scalar,typename Derived::RealScalar>::value,
                       const ScaledProduct<Derived> >::type
-operator*(typename Derived::RealScalar x,const ProductBase<Derived,Lhs,Rhs>& prod)
+operator*(const typename Derived::RealScalar& x,const ProductBase<Derived,Lhs,Rhs>& prod)
 { return ScaledProduct<Derived>(prod.derived(), x); }
 
 namespace internal {
@@ -254,7 +254,7 @@ class ScaledProduct
     inline void subTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(-1)); }
 
     template<typename Dest>
-    inline void scaleAndAddTo(Dest& dst,Scalar alpha) const { m_prod.derived().scaleAndAddTo(dst,alpha * m_alpha); }
+    inline void scaleAndAddTo(Dest& dst,Scalar a_alpha) const { m_prod.derived().scaleAndAddTo(dst,a_alpha * m_alpha); }
 
     const Scalar& alpha() const { return m_alpha; }
     

resources/3rdparty/eigen/Eigen/src/Core/ProductEvaluators.h

@@ -0,0 +1,411 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+
+#ifndef EIGEN_PRODUCTEVALUATORS_H
+#define EIGEN_PRODUCTEVALUATORS_H
+
+namespace Eigen {
+  
+namespace internal {
+  
+// We can evaluate the product either all at once, like GeneralProduct and its evalTo() function, or
+// traverse the matrix coefficient by coefficient, like CoeffBasedProduct.  Use the existing logic
+// in ProductReturnType to decide.
+
+template<typename XprType, typename ProductType>
+struct product_evaluator_dispatcher;
+
+template<typename Lhs, typename Rhs>
+struct evaluator_impl<Product<Lhs, Rhs> >
+  : product_evaluator_dispatcher<Product<Lhs, Rhs>, typename ProductReturnType<Lhs, Rhs>::Type> 
+{
+  typedef Product<Lhs, Rhs> XprType;
+  typedef product_evaluator_dispatcher<XprType, typename ProductReturnType<Lhs, Rhs>::Type> Base;
+
+  evaluator_impl(const XprType& xpr) : Base(xpr) 
+  { }
+};
+
+template<typename XprType, typename ProductType>
+struct product_evaluator_traits_dispatcher;
+
+template<typename Lhs, typename Rhs>
+struct evaluator_traits<Product<Lhs, Rhs> >
+  : product_evaluator_traits_dispatcher<Product<Lhs, Rhs>, typename ProductReturnType<Lhs, Rhs>::Type> 
+{ 
+  static const int AssumeAliasing = 1;
+};
+
+// Case 1: Evaluate all at once
+//
+// We can view the GeneralProduct class as a part of the product evaluator. 
+// Four sub-cases: InnerProduct, OuterProduct, GemmProduct and GemvProduct.
+// InnerProduct is special because GeneralProduct does not have an evalTo() method in this case.
+
+template<typename Lhs, typename Rhs>
+struct product_evaluator_traits_dispatcher<Product<Lhs, Rhs>, GeneralProduct<Lhs, Rhs, InnerProduct> > 
+{
+  static const int HasEvalTo = 0;
+};
+
+template<typename Lhs, typename Rhs>
+struct product_evaluator_dispatcher<Product<Lhs, Rhs>, GeneralProduct<Lhs, Rhs, InnerProduct> > 
+  : public evaluator<typename Product<Lhs, Rhs>::PlainObject>::type
+{
+  typedef Product<Lhs, Rhs> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  typedef typename evaluator<PlainObject>::type evaluator_base;
+
+  // TODO: Computation is too early (?)
+  product_evaluator_dispatcher(const XprType& xpr) : evaluator_base(m_result)
+  {
+    m_result.coeffRef(0,0) = (xpr.lhs().transpose().cwiseProduct(xpr.rhs())).sum();
+  }
+  
+protected:  
+  PlainObject m_result;
+};
+
+// For the other three subcases, simply call the evalTo() method of GeneralProduct
+// TODO: GeneralProduct should take evaluators, not expression objects.
+
+template<typename Lhs, typename Rhs, int ProductType>
+struct product_evaluator_traits_dispatcher<Product<Lhs, Rhs>, GeneralProduct<Lhs, Rhs, ProductType> > 
+{
+  static const int HasEvalTo = 1;
+};
+
+template<typename Lhs, typename Rhs, int ProductType>
+struct product_evaluator_dispatcher<Product<Lhs, Rhs>, GeneralProduct<Lhs, Rhs, ProductType> > 
+{
+  typedef Product<Lhs, Rhs> XprType;
+  typedef typename XprType::PlainObject PlainObject;
+  typedef typename evaluator<PlainObject>::type evaluator_base;
+  
+  product_evaluator_dispatcher(const XprType& xpr) : m_xpr(xpr)
+  { }
+  
+  template<typename DstEvaluatorType, typename DstXprType>
+  void evalTo(DstEvaluatorType /* not used */, DstXprType& dst)
+  {
+    dst.resize(m_xpr.rows(), m_xpr.cols());
+    GeneralProduct<Lhs, Rhs, ProductType>(m_xpr.lhs(), m_xpr.rhs()).evalTo(dst);
+  }
+  
+protected: 
+  const XprType& m_xpr;
+};
+
+// Case 2: Evaluate coeff by coeff
+//
+// This is mostly taken from CoeffBasedProduct.h
+// The main difference is that we add an extra argument to the etor_product_*_impl::run() function
+// for the inner dimension of the product, because evaluator object do not know their size.
+
+template<int Traversal, int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
+struct etor_product_coeff_impl;
+
+template<int StorageOrder, int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl;
+
+template<typename Lhs, typename Rhs, typename LhsNested, typename RhsNested, int Flags>
+struct product_evaluator_traits_dispatcher<Product<Lhs, Rhs>, CoeffBasedProduct<LhsNested, RhsNested, Flags> >
+{
+  static const int HasEvalTo = 0;
+};
+
+template<typename Lhs, typename Rhs, typename LhsNested, typename RhsNested, int Flags>
+struct product_evaluator_dispatcher<Product<Lhs, Rhs>, CoeffBasedProduct<LhsNested, RhsNested, Flags> >
+  : evaluator_impl_base<Product<Lhs, Rhs> >
+{
+  typedef Product<Lhs, Rhs> XprType;
+  typedef CoeffBasedProduct<LhsNested, RhsNested, Flags> CoeffBasedProductType;
+
+  product_evaluator_dispatcher(const XprType& xpr) 
+    : m_lhsImpl(xpr.lhs()), 
+      m_rhsImpl(xpr.rhs()),  
+      m_innerDim(xpr.lhs().cols())
+  { }
+
+  typedef typename XprType::Index Index;
+  typedef typename XprType::Scalar Scalar;
+  typedef typename XprType::CoeffReturnType CoeffReturnType;
+  typedef typename XprType::PacketScalar PacketScalar;
+  typedef typename XprType::PacketReturnType PacketReturnType;
+
+  // Everything below here is taken from CoeffBasedProduct.h
+
+  enum {
+    RowsAtCompileTime = traits<CoeffBasedProductType>::RowsAtCompileTime,
+    PacketSize = packet_traits<Scalar>::size,
+    InnerSize  = traits<CoeffBasedProductType>::InnerSize,
+    CoeffReadCost = traits<CoeffBasedProductType>::CoeffReadCost,
+    Unroll = CoeffReadCost != Dynamic && CoeffReadCost <= EIGEN_UNROLLING_LIMIT,
+    CanVectorizeInner = traits<CoeffBasedProductType>::CanVectorizeInner
+  };
+
+  typedef typename evaluator<Lhs>::type LhsEtorType;
+  typedef typename evaluator<Rhs>::type RhsEtorType;
+  typedef etor_product_coeff_impl<CanVectorizeInner ? InnerVectorizedTraversal : DefaultTraversal,
+                                  Unroll ? InnerSize-1 : Dynamic,
+                                  LhsEtorType, RhsEtorType, Scalar> CoeffImpl;
+
+  const CoeffReturnType coeff(Index row, Index col) const
+  {
+    Scalar res;
+    CoeffImpl::run(row, col, m_lhsImpl, m_rhsImpl, m_innerDim, res);
+    return res;
+  }
+
+  /* Allow index-based non-packet access. It is impossible though to allow index-based packed access,
+   * which is why we don't set the LinearAccessBit.
+   */
+  const CoeffReturnType coeff(Index index) const
+  {
+    Scalar res;
+    const Index row = RowsAtCompileTime == 1 ? 0 : index;
+    const Index col = RowsAtCompileTime == 1 ? index : 0;
+    CoeffImpl::run(row, col, m_lhsImpl, m_rhsImpl, m_innerDim, res);
+    return res;
+  }
+
+  template<int LoadMode>
+  const PacketReturnType packet(Index row, Index col) const
+  {
+    PacketScalar res;
+    typedef etor_product_packet_impl<Flags&RowMajorBit ? RowMajor : ColMajor,
+				     Unroll ? InnerSize-1 : Dynamic,
+				     LhsEtorType, RhsEtorType, PacketScalar, LoadMode> PacketImpl;
+    PacketImpl::run(row, col, m_lhsImpl, m_rhsImpl, m_innerDim, res);
+    return res;
+  }
+
+protected:
+  typename evaluator<Lhs>::type m_lhsImpl;
+  typename evaluator<Rhs>::type m_rhsImpl;
+
+  // TODO: Get rid of m_innerDim if known at compile time
+  Index m_innerDim;
+};
+
+/***************************************************************************
+* Normal product .coeff() implementation (with meta-unrolling)
+***************************************************************************/
+
+/**************************************
+*** Scalar path  - no vectorization ***
+**************************************/
+
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
+struct etor_product_coeff_impl<DefaultTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, RetScalar &res)
+  {
+    etor_product_coeff_impl<DefaultTraversal, UnrollingIndex-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, innerDim, res);
+    res += lhs.coeff(row, UnrollingIndex) * rhs.coeff(UnrollingIndex, col);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename RetScalar>
+struct etor_product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, RetScalar &res)
+  {
+    res = lhs.coeff(row, 0) * rhs.coeff(0, col);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename RetScalar>
+struct etor_product_coeff_impl<DefaultTraversal, Dynamic, Lhs, Rhs, RetScalar>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, RetScalar& res)
+  {
+    eigen_assert(innerDim>0 && "you are using a non initialized matrix");
+    res = lhs.coeff(row, 0) * rhs.coeff(0, col);
+    for(Index i = 1; i < innerDim; ++i)
+      res += lhs.coeff(row, i) * rhs.coeff(i, col);
+  }
+};
+
+/*******************************************
+*** Scalar path with inner vectorization ***
+*******************************************/
+
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet>
+struct etor_product_coeff_vectorized_unroller
+{
+  typedef typename Lhs::Index Index;
+  enum { PacketSize = packet_traits<typename Lhs::Scalar>::size };
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, typename Lhs::PacketScalar &pres)
+  {
+    etor_product_coeff_vectorized_unroller<UnrollingIndex-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, innerDim, pres);
+    pres = padd(pres, pmul( lhs.template packet<Aligned>(row, UnrollingIndex) , rhs.template packet<Aligned>(UnrollingIndex, col) ));
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet>
+struct etor_product_coeff_vectorized_unroller<0, Lhs, Rhs, Packet>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, typename Lhs::PacketScalar &pres)
+  {
+    pres = pmul(lhs.template packet<Aligned>(row, 0) , rhs.template packet<Aligned>(0, col));
+  }
+};
+
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
+struct etor_product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
+{
+  typedef typename Lhs::PacketScalar Packet;
+  typedef typename Lhs::Index Index;
+  enum { PacketSize = packet_traits<typename Lhs::Scalar>::size };
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, RetScalar &res)
+  {
+    Packet pres;
+    etor_product_coeff_vectorized_unroller<UnrollingIndex+1-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, innerDim, pres);
+    etor_product_coeff_impl<DefaultTraversal,UnrollingIndex,Lhs,Rhs,RetScalar>::run(row, col, lhs, rhs, innerDim, res);
+    res = predux(pres);
+  }
+};
+
+template<typename Lhs, typename Rhs, int LhsRows = Lhs::RowsAtCompileTime, int RhsCols = Rhs::ColsAtCompileTime>
+struct etor_product_coeff_vectorized_dyn_selector
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, typename Lhs::Scalar &res)
+  {
+    res = lhs.row(row).transpose().cwiseProduct(rhs.col(col)).sum();
+  }
+};
+
+// NOTE the 3 following specializations are because taking .col(0) on a vector is a bit slower
+// NOTE maybe they are now useless since we have a specialization for Block<Matrix>
+template<typename Lhs, typename Rhs, int RhsCols>
+struct etor_product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,RhsCols>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, typename Lhs::Scalar &res)
+  {
+    res = lhs.transpose().cwiseProduct(rhs.col(col)).sum();
+  }
+};
+
+template<typename Lhs, typename Rhs, int LhsRows>
+struct etor_product_coeff_vectorized_dyn_selector<Lhs,Rhs,LhsRows,1>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, typename Lhs::Scalar &res)
+  {
+    res = lhs.row(row).transpose().cwiseProduct(rhs).sum();
+  }
+};
+
+template<typename Lhs, typename Rhs>
+struct etor_product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,1>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, typename Lhs::Scalar &res)
+  {
+    res = lhs.transpose().cwiseProduct(rhs).sum();
+  }
+};
+
+template<typename Lhs, typename Rhs, typename RetScalar>
+struct etor_product_coeff_impl<InnerVectorizedTraversal, Dynamic, Lhs, Rhs, RetScalar>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, typename Lhs::Scalar &res)
+  {
+    etor_product_coeff_vectorized_dyn_selector<Lhs,Rhs>::run(row, col, lhs, rhs, innerDim, res);
+  }
+};
+
+/*******************
+*** Packet path  ***
+*******************/
+
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet &res)
+  {
+    etor_product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, innerDim, res);
+    res =  pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex)), rhs.template packet<LoadMode>(UnrollingIndex, col), res);
+  }
+};
+
+template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet &res)
+  {
+    etor_product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, innerDim, res);
+    res =  pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex), pset1<Packet>(rhs.coeff(UnrollingIndex, col)), res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, Packet &res)
+  {
+    res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index /*innerDim*/, Packet &res)
+  {
+    res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet& res)
+  {
+    eigen_assert(innerDim>0 && "you are using a non initialized matrix");
+    res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
+    for(Index i = 1; i < innerDim; ++i)
+      res =  pmadd(pset1<Packet>(lhs.coeff(row, i)), rhs.template packet<LoadMode>(i, col), res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
+struct etor_product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
+{
+  typedef typename Lhs::Index Index;
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Index innerDim, Packet& res)
+  {
+    eigen_assert(innerDim>0 && "you are using a non initialized matrix");
+    res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
+    for(Index i = 1; i < innerDim; ++i)
+      res =  pmadd(lhs.template packet<LoadMode>(row, i), pset1<Packet>(rhs.coeff(i, col)), res);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PRODUCT_EVALUATORS_H

resources/3rdparty/eigen/Eigen/src/Core/Random.h

@@ -141,9 +141,9 @@ PlainObjectBase<Derived>::setRandom(Index size)
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived&
-PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
+PlainObjectBase<Derived>::setRandom(Index nbRows, Index nbCols)
 {
-  resize(rows, cols);
+  resize(nbRows, nbCols);
   return setRandom();
 }
 

resources/3rdparty/eigen/Eigen/src/Core/Ref.h

@@ -0,0 +1,254 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_REF_H
+#define EIGEN_REF_H
+
+namespace Eigen { 
+
+template<typename Derived> class RefBase;
+template<typename PlainObjectType, int Options = 0,
+         typename StrideType = typename internal::conditional<PlainObjectType::IsVectorAtCompileTime,InnerStride<1>,OuterStride<> >::type > class Ref;
+
+/** \class Ref
+  * \ingroup Core_Module
+  *
+  * \brief A matrix or vector expression mapping an existing expressions
+  *
+  * \tparam PlainObjectType the equivalent matrix type of the mapped data
+  * \tparam Options specifies whether the pointer is \c #Aligned, or \c #Unaligned.
+  *                The default is \c #Unaligned.
+  * \tparam StrideType optionally specifies strides. By default, Ref implies a contiguous storage along the inner dimension (inner stride==1),
+  *                   but accept a variable outer stride (leading dimension).
+  *                   This can be overridden by specifying strides.
+  *                   The type passed here must be a specialization of the Stride template, see examples below.
+  *
+  * This class permits to write non template functions taking Eigen's object as parameters while limiting the number of copies.
+  * A Ref<> object can represent either a const expression or a l-value:
+  * \code
+  * // in-out argument:
+  * void foo1(Ref<VectorXf> x);
+  *
+  * // read-only const argument:
+  * void foo2(const Ref<const VectorXf>& x);
+  * \endcode
+  *
+  * In the in-out case, the input argument must satisfies the constraints of the actual Ref<> type, otherwise a compilation issue will be triggered.
+  * By default, a Ref<VectorXf> can reference any dense vector expression of float having a contiguous memory layout.
+  * Likewise, a Ref<MatrixXf> can reference any column major dense matrix expression of float whose column's elements are contiguously stored with
+  * the possibility to have a constant space inbetween each column, i.e.: the inner stride mmust be equal to 1, but the outer-stride (or leading dimension),
+  * can be greater than the number of rows.
+  *
+  * In the const case, if the input expression does not match the above requirement, then it is evaluated into a temporary before being passed to the function.
+  * Here are some examples:
+  * \code
+  * MatrixXf A;
+  * VectorXf a;
+  * foo1(a.head());             // OK
+  * foo1(A.col());              // OK
+  * foo1(A.row());              // compilation error because here innerstride!=1
+  * foo2(A.row());              // The row is copied into a contiguous temporary
+  * foo2(2*a);                  // The expression is evaluated into a temporary
+  * foo2(A.col().segment(2,4)); // No temporary
+  * \endcode
+  *
+  * The range of inputs that can be referenced without temporary can be enlarged using the last two template parameter.
+  * Here is an example accepting an innerstride!=1:
+  * \code
+  * // in-out argument:
+  * void foo3(Ref<VectorXf,0,InnerStride<> > x);
+  * foo3(A.row());              // OK
+  * \endcode
+  * The downside here is that the function foo3 might be significantly slower than foo1 because it won't be able to exploit vectorization, and will involved more
+  * expensive address computations even if the input is contiguously stored in memory. To overcome this issue, one might propose to overloads internally calling a
+  * template function, e.g.:
+  * \code
+  * // in the .h:
+  * void foo(const Ref<MatrixXf>& A);
+  * void foo(const Ref<MatrixXf,0,Stride<> >& A);
+  *
+  * // in the .cpp:
+  * template<typename TypeOfA> void foo_impl(const TypeOfA& A) {
+  *     ... // crazy code goes here
+  * }
+  * void foo(const Ref<MatrixXf>& A) { foo_impl(A); }
+  * void foo(const Ref<MatrixXf,0,Stride<> >& A) { foo_impl(A); }
+  * \endcode
+  *
+  *
+  * \sa PlainObjectBase::Map(), \ref TopicStorageOrders
+  */
+
+namespace internal {
+
+template<typename _PlainObjectType, int _Options, typename _StrideType>
+struct traits<Ref<_PlainObjectType, _Options, _StrideType> >
+  : public traits<Map<_PlainObjectType, _Options, _StrideType> >
+{
+  typedef _PlainObjectType PlainObjectType;
+  typedef _StrideType StrideType;
+  enum {
+    Options = _Options
+  };
+
+  template<typename Derived> struct match {
+    enum {
+      HasDirectAccess = internal::has_direct_access<Derived>::ret,
+      StorageOrderMatch = PlainObjectType::IsVectorAtCompileTime || ((PlainObjectType::Flags&RowMajorBit)==(Derived::Flags&RowMajorBit)),
+      InnerStrideMatch = int(StrideType::InnerStrideAtCompileTime)==int(Dynamic)
+                      || int(StrideType::InnerStrideAtCompileTime)==int(Derived::InnerStrideAtCompileTime)
+                      || (int(StrideType::InnerStrideAtCompileTime)==0 && int(Derived::InnerStrideAtCompileTime)==1),
+      OuterStrideMatch = Derived::IsVectorAtCompileTime
+                      || int(StrideType::OuterStrideAtCompileTime)==int(Dynamic) || int(StrideType::OuterStrideAtCompileTime)==int(Derived::OuterStrideAtCompileTime),
+      AlignmentMatch = (_Options!=Aligned) || ((PlainObjectType::Flags&AlignedBit)==0) || ((traits<Derived>::Flags&AlignedBit)==AlignedBit),
+      MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch
+    };
+    typedef typename internal::conditional<MatchAtCompileTime,internal::true_type,internal::false_type>::type type;
+  };
+
+};
+
+template<typename Derived>
+struct traits<RefBase<Derived> > : public traits<Derived> {};
+
+}
+
+template<typename Derived> class RefBase
+ : public MapBase<Derived>
+{
+  typedef typename internal::traits<Derived>::PlainObjectType PlainObjectType;
+  typedef typename internal::traits<Derived>::StrideType StrideType;
+
+public:
+
+  typedef MapBase<Derived> Base;
+  EIGEN_DENSE_PUBLIC_INTERFACE(RefBase)
+
+  inline Index innerStride() const
+  {
+    return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1;
+  }
+
+  inline Index outerStride() const
+  {
+    return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer()
+         : IsVectorAtCompileTime ? this->size()
+         : int(Flags)&RowMajorBit ? this->cols()
+         : this->rows();
+  }
+
+  RefBase()
+    : Base(0,RowsAtCompileTime==Dynamic?0:RowsAtCompileTime,ColsAtCompileTime==Dynamic?0:ColsAtCompileTime),
+      // Stride<> does not allow default ctor for Dynamic strides, so let' initialize it with dummy values:
+      m_stride(StrideType::OuterStrideAtCompileTime==Dynamic?0:StrideType::OuterStrideAtCompileTime,
+               StrideType::InnerStrideAtCompileTime==Dynamic?0:StrideType::InnerStrideAtCompileTime)
+  {}
+
+protected:
+
+  typedef Stride<StrideType::OuterStrideAtCompileTime,StrideType::InnerStrideAtCompileTime> StrideBase;
+
+  template<typename Expression>
+  void construct(Expression& expr)
+  {
+    if(PlainObjectType::RowsAtCompileTime==1)
+    {
+      eigen_assert(expr.rows()==1 || expr.cols()==1);
+      ::new (static_cast<Base*>(this)) Base(expr.data(), 1, expr.size());
+    }
+    else if(PlainObjectType::ColsAtCompileTime==1)
+    {
+      eigen_assert(expr.rows()==1 || expr.cols()==1);
+      ::new (static_cast<Base*>(this)) Base(expr.data(), expr.size(), 1);
+    }
+    else
+      ::new (static_cast<Base*>(this)) Base(expr.data(), expr.rows(), expr.cols());
+    ::new (&m_stride) StrideBase(StrideType::OuterStrideAtCompileTime==0?0:expr.outerStride(),
+                                 StrideType::InnerStrideAtCompileTime==0?0:expr.innerStride());
+  }
+
+  StrideBase m_stride;
+};
+
+
+template<typename PlainObjectType, int Options, typename StrideType> class Ref
+  : public RefBase<Ref<PlainObjectType, Options, StrideType> >
+{
+    typedef internal::traits<Ref> Traits;
+  public:
+
+    typedef RefBase<Ref> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
+
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename Derived>
+    inline Ref(PlainObjectBase<Derived>& expr,
+               typename internal::enable_if<bool(Traits::template match<Derived>::MatchAtCompileTime),Derived>::type* = 0)
+    {
+      Base::construct(expr);
+    }
+    template<typename Derived>
+    inline Ref(const DenseBase<Derived>& expr,
+               typename internal::enable_if<bool(internal::is_lvalue<Derived>::value&&bool(Traits::template match<Derived>::MatchAtCompileTime)),Derived>::type* = 0,
+               int = Derived::ThisConstantIsPrivateInPlainObjectBase)
+    #else
+    template<typename Derived>
+    inline Ref(DenseBase<Derived>& expr)
+    #endif
+    {
+      Base::construct(expr.const_cast_derived());
+    }
+
+    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Ref)
+
+};
+
+// this is the const ref version
+template<typename PlainObjectType, int Options, typename StrideType> class Ref<const PlainObjectType, Options, StrideType>
+  : public RefBase<Ref<const PlainObjectType, Options, StrideType> >
+{
+    typedef internal::traits<Ref> Traits;
+  public:
+
+    typedef RefBase<Ref> Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Ref)
+
+    template<typename Derived>
+    inline Ref(const DenseBase<Derived>& expr)
+    {
+//      std::cout << match_helper<Derived>::HasDirectAccess << "," << match_helper<Derived>::OuterStrideMatch << "," << match_helper<Derived>::InnerStrideMatch << "\n";
+//      std::cout << int(StrideType::OuterStrideAtCompileTime) << " - " << int(Derived::OuterStrideAtCompileTime) << "\n";
+//      std::cout << int(StrideType::InnerStrideAtCompileTime) << " - " << int(Derived::InnerStrideAtCompileTime) << "\n";
+      construct(expr.derived(), typename Traits::template match<Derived>::type());
+    }
+
+  protected:
+
+    template<typename Expression>
+    void construct(const Expression& expr,internal::true_type)
+    {
+      Base::construct(expr);
+    }
+
+    template<typename Expression>
+    void construct(const Expression& expr, internal::false_type)
+    {
+//      std::cout << "Ref: copy\n";
+      m_object = expr;
+      Base::construct(m_object);
+    }
+
+  protected:
+    PlainObjectType m_object;
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_REF_H

resources/3rdparty/eigen/Eigen/src/Core/Replicate.h

@@ -70,8 +70,8 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
     EIGEN_DENSE_PUBLIC_INTERFACE(Replicate)
 
     template<typename OriginalMatrixType>
-    inline explicit Replicate(const OriginalMatrixType& matrix)
-      : m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
+    inline explicit Replicate(const OriginalMatrixType& a_matrix)
+      : m_matrix(a_matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor)
     {
       EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
                           THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
@@ -79,8 +79,8 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
     }
 
     template<typename OriginalMatrixType>
-    inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
-      : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
+    inline Replicate(const OriginalMatrixType& a_matrix, Index rowFactor, Index colFactor)
+      : m_matrix(a_matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
     {
       EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
                           THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE)
@@ -89,27 +89,27 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
     inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); }
     inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); }
 
-    inline Scalar coeff(Index row, Index col) const
+    inline Scalar coeff(Index rowId, Index colId) const
     {
       // try to avoid using modulo; this is a pure optimization strategy
       const Index actual_row  = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
-                            : RowFactor==1 ? row
-                            : row%m_matrix.rows();
+                            : RowFactor==1 ? rowId
+                            : rowId%m_matrix.rows();
       const Index actual_col  = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
-                            : ColFactor==1 ? col
-                            : col%m_matrix.cols();
+                            : ColFactor==1 ? colId
+                            : colId%m_matrix.cols();
 
       return m_matrix.coeff(actual_row, actual_col);
     }
     template<int LoadMode>
-    inline PacketScalar packet(Index row, Index col) const
+    inline PacketScalar packet(Index rowId, Index colId) const
     {
       const Index actual_row  = internal::traits<MatrixType>::RowsAtCompileTime==1 ? 0
-                            : RowFactor==1 ? row
-                            : row%m_matrix.rows();
+                            : RowFactor==1 ? rowId
+                            : rowId%m_matrix.rows();
       const Index actual_col  = internal::traits<MatrixType>::ColsAtCompileTime==1 ? 0
-                            : ColFactor==1 ? col
-                            : col%m_matrix.cols();
+                            : ColFactor==1 ? colId
+                            : colId%m_matrix.cols();
 
       return m_matrix.template packet<LoadMode>(actual_row, actual_col);
     }

resources/3rdparty/eigen/Eigen/src/Core/Select.h

@@ -60,10 +60,10 @@ class Select : internal::no_assignment_operator,
     typedef typename internal::dense_xpr_base<Select>::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE(Select)
 
-    Select(const ConditionMatrixType& conditionMatrix,
-           const ThenMatrixType& thenMatrix,
-           const ElseMatrixType& elseMatrix)
-      : m_condition(conditionMatrix), m_then(thenMatrix), m_else(elseMatrix)
+    Select(const ConditionMatrixType& a_conditionMatrix,
+           const ThenMatrixType& a_thenMatrix,
+           const ElseMatrixType& a_elseMatrix)
+      : m_condition(a_conditionMatrix), m_then(a_thenMatrix), m_else(a_elseMatrix)
     {
       eigen_assert(m_condition.rows() == m_then.rows() && m_condition.rows() == m_else.rows());
       eigen_assert(m_condition.cols() == m_then.cols() && m_condition.cols() == m_else.cols());

resources/3rdparty/eigen/Eigen/src/Core/StableNorm.h

@@ -131,7 +131,6 @@ MatrixBase<Derived>::blueNorm() const
     abig = internal::sqrt(abig);
     if(abig > overfl)
     {
-      eigen_assert(false && "overflow");
       return rbig;
     }
     if(amed > RealScalar(0))

resources/3rdparty/eigen/Eigen/src/Core/Swap.h

@@ -49,9 +49,9 @@ template<typename ExpressionType> class SwapWrapper
     inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline Scalar& coeffRef(Index row, Index col)
+    inline Scalar& coeffRef(Index rowId, Index colId)
     {
-      return m_expression.const_cast_derived().coeffRef(row, col);
+      return m_expression.const_cast_derived().coeffRef(rowId, colId);
     }
 
     inline Scalar& coeffRef(Index index)
@@ -59,9 +59,9 @@ template<typename ExpressionType> class SwapWrapper
       return m_expression.const_cast_derived().coeffRef(index);
     }
 
-    inline Scalar& coeffRef(Index row, Index col) const
+    inline Scalar& coeffRef(Index rowId, Index colId) const
     {
-      return m_expression.coeffRef(row, col);
+      return m_expression.coeffRef(rowId, colId);
     }
 
     inline Scalar& coeffRef(Index index) const
@@ -70,14 +70,14 @@ template<typename ExpressionType> class SwapWrapper
     }
 
     template<typename OtherDerived>
-    void copyCoeff(Index row, Index col, const DenseBase<OtherDerived>& other)
+    void copyCoeff(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(row >= 0 && row < rows()
-                         && col >= 0 && col < cols());
-      Scalar tmp = m_expression.coeff(row, col);
-      m_expression.coeffRef(row, col) = _other.coeff(row, col);
-      _other.coeffRef(row, col) = tmp;
+      eigen_internal_assert(rowId >= 0 && rowId < rows()
+                         && colId >= 0 && colId < cols());
+      Scalar tmp = m_expression.coeff(rowId, colId);
+      m_expression.coeffRef(rowId, colId) = _other.coeff(rowId, colId);
+      _other.coeffRef(rowId, colId) = tmp;
     }
 
     template<typename OtherDerived>
@@ -91,16 +91,16 @@ template<typename ExpressionType> class SwapWrapper
     }
 
     template<typename OtherDerived, int StoreMode, int LoadMode>
-    void copyPacket(Index row, Index col, const DenseBase<OtherDerived>& other)
+    void copyPacket(Index rowId, Index colId, const DenseBase<OtherDerived>& other)
     {
       OtherDerived& _other = other.const_cast_derived();
-      eigen_internal_assert(row >= 0 && row < rows()
-                        && col >= 0 && col < cols());
-      Packet tmp = m_expression.template packet<StoreMode>(row, col);
-      m_expression.template writePacket<StoreMode>(row, col,
-        _other.template packet<LoadMode>(row, col)
+      eigen_internal_assert(rowId >= 0 && rowId < rows()
+                        && colId >= 0 && colId < cols());
+      Packet tmp = m_expression.template packet<StoreMode>(rowId, colId);
+      m_expression.template writePacket<StoreMode>(rowId, colId,
+        _other.template packet<LoadMode>(rowId, colId)
       );
-      _other.template writePacket<LoadMode>(row, col, tmp);
+      _other.template writePacket<LoadMode>(rowId, colId, tmp);
     }
 
     template<typename OtherDerived, int StoreMode, int LoadMode>

resources/3rdparty/eigen/Eigen/src/Core/Transpose.h

@@ -62,7 +62,7 @@ template<typename MatrixType> class Transpose
     typedef typename TransposeImpl<MatrixType,typename internal::traits<MatrixType>::StorageKind>::Base Base;
     EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
 
-    inline Transpose(MatrixType& matrix) : m_matrix(matrix) {}
+    inline Transpose(MatrixType& a_matrix) : m_matrix(a_matrix) {}
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
 
@@ -117,10 +117,10 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
     inline ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
     inline const Scalar* data() const { return derived().nestedExpression().data(); }
 
-    inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col)
+    inline ScalarWithConstIfNotLvalue& coeffRef(Index rowId, Index colId)
     {
       EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
-      return derived().nestedExpression().const_cast_derived().coeffRef(col, row);
+      return derived().nestedExpression().const_cast_derived().coeffRef(colId, rowId);
     }
 
     inline ScalarWithConstIfNotLvalue& coeffRef(Index index)
@@ -129,9 +129,9 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
       return derived().nestedExpression().const_cast_derived().coeffRef(index);
     }
 
-    inline const Scalar& coeffRef(Index row, Index col) const
+    inline const Scalar& coeffRef(Index rowId, Index colId) const
     {
-      return derived().nestedExpression().coeffRef(col, row);
+      return derived().nestedExpression().coeffRef(colId, rowId);
     }
 
     inline const Scalar& coeffRef(Index index) const
@@ -139,9 +139,9 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
       return derived().nestedExpression().coeffRef(index);
     }
 
-    inline CoeffReturnType coeff(Index row, Index col) const
+    inline CoeffReturnType coeff(Index rowId, Index colId) const
     {
-      return derived().nestedExpression().coeff(col, row);
+      return derived().nestedExpression().coeff(colId, rowId);
     }
 
     inline CoeffReturnType coeff(Index index) const
@@ -150,15 +150,15 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
     }
 
     template<int LoadMode>
-    inline const PacketScalar packet(Index row, Index col) const
+    inline const PacketScalar packet(Index rowId, Index colId) const
     {
-      return derived().nestedExpression().template packet<LoadMode>(col, row);
+      return derived().nestedExpression().template packet<LoadMode>(colId, rowId);
     }
 
     template<int LoadMode>
-    inline void writePacket(Index row, Index col, const PacketScalar& x)
+    inline void writePacket(Index rowId, Index colId, const PacketScalar& x)
     {
-      derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(col, row, x);
+      derived().nestedExpression().const_cast_derived().template writePacket<LoadMode>(colId, rowId, x);
     }
 
     template<int LoadMode>
@@ -353,7 +353,7 @@ 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 +362,8 @@ 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())))
-        || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src.rhs())));
+    return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.lhs())))
+        || ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(const Scalar*)extract_data(src.rhs())));
   }
 };
 

resources/3rdparty/eigen/Eigen/src/Core/Transpositions.h

@@ -99,9 +99,9 @@ class TranspositionsBase
     IndicesType& indices() { return derived().indices(); }
 
     /** Resizes to given size. */
-    inline void resize(int size)
+    inline void resize(int newSize)
     {
-      indices().resize(size);
+      indices().resize(newSize);
     }
 
     /** Sets \c *this to represents an identity transformation */
@@ -177,7 +177,7 @@ class Transpositions : public TranspositionsBase<Transpositions<SizeAtCompileTim
 
     /** Generic constructor from expression of the transposition indices. */
     template<typename Other>
-    explicit inline Transpositions(const MatrixBase<Other>& indices) : m_indices(indices)
+    explicit inline Transpositions(const MatrixBase<Other>& a_indices) : m_indices(a_indices)
     {}
 
     /** Copies the \a other transpositions into \c *this */
@@ -234,12 +234,12 @@ class Map<Transpositions<SizeAtCompileTime,MaxSizeAtCompileTime,IndexType>,Packe
     typedef typename Traits::IndicesType IndicesType;
     typedef typename IndicesType::Scalar Index;
 
-    inline Map(const Index* indices)
-      : m_indices(indices)
+    inline Map(const Index* indicesPtr)
+      : m_indices(indicesPtr)
     {}
 
-    inline Map(const Index* indices, Index size)
-      : m_indices(indices,size)
+    inline Map(const Index* indicesPtr, Index size)
+      : m_indices(indicesPtr,size)
     {}
 
     /** Copies the \a other transpositions into \c *this */
@@ -291,8 +291,8 @@ class TranspositionsWrapper
     typedef typename Traits::IndicesType IndicesType;
     typedef typename IndicesType::Scalar Index;
 
-    inline TranspositionsWrapper(IndicesType& indices)
-      : m_indices(indices)
+    inline TranspositionsWrapper(IndicesType& a_indices)
+      : m_indices(a_indices)
     {}
 
     /** Copies the \a other transpositions into \c *this */

resources/3rdparty/eigen/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);
     }
   }
 };
@@ -778,7 +779,7 @@ MatrixBase<Derived>::triangularView() const
   * \sa isLowerTriangular()
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
+bool MatrixBase<Derived>::isUpperTriangular(const RealScalar& prec) const
 {
   RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
   for(Index j = 0; j < cols(); ++j)
@@ -803,7 +804,7 @@ bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
   * \sa isUpperTriangular()
   */
 template<typename Derived>
-bool MatrixBase<Derived>::isLowerTriangular(RealScalar prec) const
+bool MatrixBase<Derived>::isLowerTriangular(const RealScalar& prec) const
 {
   RealScalar maxAbsOnLowerPart = static_cast<RealScalar>(-1);
   for(Index j = 0; j < cols(); ++j)

resources/3rdparty/eigen/Eigen/src/Core/VectorBlock.h

@@ -108,19 +108,19 @@ template<typename VectorType, int Size> class VectorBlock
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::SegmentReturnType
-DenseBase<Derived>::segment(Index start, Index size)
+DenseBase<Derived>::segment(Index start, Index vecSize)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return SegmentReturnType(derived(), start, size);
+  return SegmentReturnType(derived(), start, vecSize);
 }
 
 /** This is the const version of segment(Index,Index).*/
 template<typename Derived>
 inline typename DenseBase<Derived>::ConstSegmentReturnType
-DenseBase<Derived>::segment(Index start, Index size) const
+DenseBase<Derived>::segment(Index start, Index vecSize) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return ConstSegmentReturnType(derived(), start, size);
+  return ConstSegmentReturnType(derived(), start, vecSize);
 }
 
 /** \returns a dynamic-size expression of the first coefficients of *this.
@@ -140,19 +140,19 @@ DenseBase<Derived>::segment(Index start, Index size) const
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::SegmentReturnType
-DenseBase<Derived>::head(Index size)
+DenseBase<Derived>::head(Index vecsize)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return SegmentReturnType(derived(), 0, size);
+  return SegmentReturnType(derived(), 0, vecsize);
 }
 
 /** This is the const version of head(Index).*/
 template<typename Derived>
 inline typename DenseBase<Derived>::ConstSegmentReturnType
-DenseBase<Derived>::head(Index size) const
+DenseBase<Derived>::head(Index vecSize) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return ConstSegmentReturnType(derived(), 0, size);
+  return ConstSegmentReturnType(derived(), 0, vecSize);
 }
 
 /** \returns a dynamic-size expression of the last coefficients of *this.
@@ -172,19 +172,19 @@ DenseBase<Derived>::head(Index size) const
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::SegmentReturnType
-DenseBase<Derived>::tail(Index size)
+DenseBase<Derived>::tail(Index vecSize)
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return SegmentReturnType(derived(), this->size() - size, size);
+  return SegmentReturnType(derived(), this->size() - vecSize, vecSize);
 }
 
 /** This is the const version of tail(Index).*/
 template<typename Derived>
 inline typename DenseBase<Derived>::ConstSegmentReturnType
-DenseBase<Derived>::tail(Index size) const
+DenseBase<Derived>::tail(Index vecSize) const
 {
   EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return ConstSegmentReturnType(derived(), this->size() - size, size);
+  return ConstSegmentReturnType(derived(), this->size() - vecSize, vecSize);
 }
 
 /** \returns a fixed-size expression of a segment (i.e. a vector block) in \c *this

resources/3rdparty/eigen/Eigen/src/Core/Visitor.h

@@ -172,12 +172,12 @@ struct functor_traits<max_coeff_visitor<Scalar> > {
 template<typename Derived>
 template<typename IndexType>
 typename internal::traits<Derived>::Scalar
-DenseBase<Derived>::minCoeff(IndexType* row, IndexType* col) const
+DenseBase<Derived>::minCoeff(IndexType* rowId, IndexType* colId) const
 {
   internal::min_coeff_visitor<Derived> minVisitor;
   this->visit(minVisitor);
-  *row = minVisitor.row;
-  if (col) *col = minVisitor.col;
+  *rowId = minVisitor.row;
+  if (colId) *colId = minVisitor.col;
   return minVisitor.res;
 }
 
@@ -206,12 +206,12 @@ DenseBase<Derived>::minCoeff(IndexType* index) const
 template<typename Derived>
 template<typename IndexType>
 typename internal::traits<Derived>::Scalar
-DenseBase<Derived>::maxCoeff(IndexType* row, IndexType* col) const
+DenseBase<Derived>::maxCoeff(IndexType* rowPtr, IndexType* colPtr) const
 {
   internal::max_coeff_visitor<Derived> maxVisitor;
   this->visit(maxVisitor);
-  *row = maxVisitor.row;
-  if (col) *col = maxVisitor.col;
+  *rowPtr = maxVisitor.row;
+  if (colPtr) *colPtr = maxVisitor.col;
   return maxVisitor.res;
 }
 

resources/3rdparty/eigen/Eigen/src/Core/arch/NEON/PacketMath.h

@@ -237,15 +237,12 @@ template<> EIGEN_STRONG_INLINE Packet4i pabs(const Packet4i& a) { return vabsq_s
 template<> EIGEN_STRONG_INLINE float predux<Packet4f>(const Packet4f& a)
 {
   float32x2_t a_lo, a_hi, sum;
-  float s[2];
 
   a_lo = vget_low_f32(a);
   a_hi = vget_high_f32(a);
   sum = vpadd_f32(a_lo, a_hi);
   sum = vpadd_f32(sum, sum);
-  vst1_f32(s, sum);
-
-  return s[0];
+  return vget_lane_f32(sum, 0);
 }
 
 template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
@@ -271,15 +268,12 @@ template<> EIGEN_STRONG_INLINE Packet4f preduxp<Packet4f>(const Packet4f* vecs)
 template<> EIGEN_STRONG_INLINE int predux<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, sum;
-  int32_t s[2];
 
   a_lo = vget_low_s32(a);
   a_hi = vget_high_s32(a);
   sum = vpadd_s32(a_lo, a_hi);
   sum = vpadd_s32(sum, sum);
-  vst1_s32(s, sum);
-
-  return s[0];
+  return vget_lane_s32(sum, 0);
 }
 
 template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
@@ -307,7 +301,6 @@ template<> EIGEN_STRONG_INLINE Packet4i preduxp<Packet4i>(const Packet4i* vecs)
 template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
 {
   float32x2_t a_lo, a_hi, prod;
-  float s[2];
 
   // Get a_lo = |a1|a2| and a_hi = |a3|a4|
   a_lo = vget_low_f32(a);
@@ -316,14 +309,12 @@ template<> EIGEN_STRONG_INLINE float predux_mul<Packet4f>(const Packet4f& a)
   prod = vmul_f32(a_lo, a_hi);
   // Multiply prod with its swapped value |a2*a4|a1*a3|
   prod = vmul_f32(prod, vrev64_f32(prod));
-  vst1_f32(s, prod);
 
-  return s[0];
+  return vget_lane_f32(prod, 0);
 }
 template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, prod;
-  int32_t s[2];
 
   // Get a_lo = |a1|a2| and a_hi = |a3|a4|
   a_lo = vget_low_s32(a);
@@ -332,65 +323,57 @@ template<> EIGEN_STRONG_INLINE int predux_mul<Packet4i>(const Packet4i& a)
   prod = vmul_s32(a_lo, a_hi);
   // Multiply prod with its swapped value |a2*a4|a1*a3|
   prod = vmul_s32(prod, vrev64_s32(prod));
-  vst1_s32(s, prod);
 
-  return s[0];
+  return vget_lane_s32(prod, 0);
 }
 
 // min
 template<> EIGEN_STRONG_INLINE float predux_min<Packet4f>(const Packet4f& a)
 {
   float32x2_t a_lo, a_hi, min;
-  float s[2];
 
   a_lo = vget_low_f32(a);
   a_hi = vget_high_f32(a);
   min = vpmin_f32(a_lo, a_hi);
   min = vpmin_f32(min, min);
-  vst1_f32(s, min);
 
-  return s[0];
+  return vget_lane_f32(min, 0);
 }
+
 template<> EIGEN_STRONG_INLINE int predux_min<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, min;
-  int32_t s[2];
 
   a_lo = vget_low_s32(a);
   a_hi = vget_high_s32(a);
   min = vpmin_s32(a_lo, a_hi);
   min = vpmin_s32(min, min);
-  vst1_s32(s, min);
-
-  return s[0];
+  
+  return vget_lane_s32(min, 0);
 }
 
 // max
 template<> EIGEN_STRONG_INLINE float predux_max<Packet4f>(const Packet4f& a)
 {
   float32x2_t a_lo, a_hi, max;
-  float s[2];
 
   a_lo = vget_low_f32(a);
   a_hi = vget_high_f32(a);
   max = vpmax_f32(a_lo, a_hi);
   max = vpmax_f32(max, max);
-  vst1_f32(s, max);
 
-  return s[0];
+  return vget_lane_f32(max, 0);
 }
+
 template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
 {
   int32x2_t a_lo, a_hi, max;
-  int32_t s[2];
 
   a_lo = vget_low_s32(a);
   a_hi = vget_high_s32(a);
   max = vpmax_s32(a_lo, a_hi);
-  max = vpmax_s32(max, max);
-  vst1_s32(s, max);
 
-  return s[0];
+  return vget_lane_s32(max, 0);
 }
 
 // this PALIGN_NEON business is to work around a bug in LLVM Clang 3.0 causing incorrect compilation errors,

resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/MathFunctions.h

@@ -131,13 +131,16 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
   /* express exp(x) as exp(g + n*log(2)) */
   fx = pmadd(x, p4f_cephes_LOG2EF, p4f_half);
 
-  /* how to perform a floorf with SSE: just below */
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  fx = _mm_floor_ps(fx);
+#else
   emm0 = _mm_cvttps_epi32(fx);
   tmp  = _mm_cvtepi32_ps(emm0);
   /* if greater, substract 1 */
   Packet4f mask = _mm_cmpgt_ps(tmp, fx);
   mask = _mm_and_ps(mask, p4f_1);
   fx = psub(tmp, mask);
+#endif
 
   tmp = pmul(fx, p4f_cephes_exp_C1);
   Packet4f z = pmul(fx, p4f_cephes_exp_C2);
@@ -161,6 +164,79 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
   emm0 = _mm_slli_epi32(emm0, 23);
   return pmul(y, _mm_castsi128_ps(emm0));
 }
+template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
+Packet2d pexp<Packet2d>(const Packet2d& _x)
+{
+  Packet2d x = _x;
+
+  _EIGEN_DECLARE_CONST_Packet2d(1 , 1.0);
+  _EIGEN_DECLARE_CONST_Packet2d(2 , 2.0);
+  _EIGEN_DECLARE_CONST_Packet2d(half, 0.5);
+
+  _EIGEN_DECLARE_CONST_Packet2d(exp_hi,  709.437);
+  _EIGEN_DECLARE_CONST_Packet2d(exp_lo, -709.436139303);
+
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_LOG2EF, 1.4426950408889634073599);
+
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p0, 1.26177193074810590878e-4);
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p1, 3.02994407707441961300e-2);
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_p2, 9.99999999999999999910e-1);
+
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q0, 3.00198505138664455042e-6);
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q1, 2.52448340349684104192e-3);
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q2, 2.27265548208155028766e-1);
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_q3, 2.00000000000000000009e0);
+
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C1, 0.693145751953125);
+  _EIGEN_DECLARE_CONST_Packet2d(cephes_exp_C2, 1.42860682030941723212e-6);
+  static const __m128i p4i_1023_0 = _mm_setr_epi32(1023, 1023, 0, 0);
+
+  Packet2d tmp = _mm_setzero_pd(), fx;
+  Packet4i emm0;
+
+  // clamp x
+  x = pmax(pmin(x, p2d_exp_hi), p2d_exp_lo);
+  /* express exp(x) as exp(g + n*log(2)) */
+  fx = pmadd(p2d_cephes_LOG2EF, x, p2d_half);
+
+#ifdef EIGEN_VECTORIZE_SSE4_1
+  fx = _mm_floor_pd(fx);
+#else
+  emm0 = _mm_cvttpd_epi32(fx);
+  tmp  = _mm_cvtepi32_pd(emm0);
+  /* if greater, substract 1 */
+  Packet2d mask = _mm_cmpgt_pd(tmp, fx);
+  mask = _mm_and_pd(mask, p2d_1);
+  fx = psub(tmp, mask);
+#endif
+
+  tmp = pmul(fx, p2d_cephes_exp_C1);
+  Packet2d z = pmul(fx, p2d_cephes_exp_C2);
+  x = psub(x, tmp);
+  x = psub(x, z);
+
+  Packet2d x2 = pmul(x,x);
+
+  Packet2d px = p2d_cephes_exp_p0;
+  px = pmadd(px, x2, p2d_cephes_exp_p1);
+  px = pmadd(px, x2, p2d_cephes_exp_p2);
+  px = pmul (px, x);
+
+  Packet2d qx = p2d_cephes_exp_q0;
+  qx = pmadd(qx, x2, p2d_cephes_exp_q1);
+  qx = pmadd(qx, x2, p2d_cephes_exp_q2);
+  qx = pmadd(qx, x2, p2d_cephes_exp_q3);
+
+  x = pdiv(px,psub(qx,px));
+  x = pmadd(p2d_2,x,p2d_1);
+
+  // build 2^n
+  emm0 = _mm_cvttpd_epi32(fx);
+  emm0 = _mm_add_epi32(emm0, p4i_1023_0);
+  emm0 = _mm_slli_epi32(emm0, 20);
+  emm0 = _mm_shuffle_epi32(emm0, _MM_SHUFFLE(1,2,0,3));
+  return pmul(x, _mm_castsi128_pd(emm0));
+}
 
 /* evaluation of 4 sines at onces, using SSE2 intrinsics.
 

resources/3rdparty/eigen/Eigen/src/Core/arch/SSE/PacketMath.h

@@ -48,6 +48,9 @@ template<> struct is_arithmetic<__m128d> { enum { value = true }; };
 #define _EIGEN_DECLARE_CONST_Packet4f(NAME,X) \
   const Packet4f p4f_##NAME = pset1<Packet4f>(X)
 
+#define _EIGEN_DECLARE_CONST_Packet2d(NAME,X) \
+  const Packet2d p2d_##NAME = pset1<Packet2d>(X)
+
 #define _EIGEN_DECLARE_CONST_Packet4f_FROM_INT(NAME,X) \
   const Packet4f p4f_##NAME = _mm_castsi128_ps(pset1<Packet4i>(X))
 
@@ -63,7 +66,7 @@ template<> struct packet_traits<float>  : default_packet_traits
     AlignedOnScalar = 1,
     size=4,
 
-    HasDiv    = 1,
+    HasDiv  = 1,
     HasSin  = EIGEN_FAST_MATH,
     HasCos  = EIGEN_FAST_MATH,
     HasLog  = 1,
@@ -79,7 +82,8 @@ template<> struct packet_traits<double> : default_packet_traits
     AlignedOnScalar = 1,
     size=2,
 
-    HasDiv    = 1
+    HasDiv  = 1,
+    HasExp  = 1
   };
 };
 template<> struct packet_traits<int>    : default_packet_traits

resources/3rdparty/eigen/Eigen/src/Core/products/GeneralBlockPanelKernel.h

@@ -527,7 +527,7 @@ struct gebp_kernel
     ResPacketSize = Traits::ResPacketSize
   };
 
-  EIGEN_DONT_INLINE EIGEN_FLATTEN_ATTRIB
+  EIGEN_DONT_INLINE
   void operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha,
                   Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, RhsScalar* unpackedB = 0)
   {

resources/3rdparty/eigen/Eigen/src/Core/products/GeneralMatrixVector.h

@@ -81,14 +81,14 @@ 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 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 +177,8 @@ 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 +188,7 @@ 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 +212,10 @@ 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 +335,7 @@ 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 PeelAlignedMask = RhsPacketSize*peels-1;
   const Index depth = cols;
 
   // How many coeffs of the result do we have to skip to be aligned.
@@ -340,7 +343,7 @@ 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 +433,12 @@ 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 +448,7 @@ 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 +470,10 @@ 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);

resources/3rdparty/eigen/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";*/ \
      } \

resources/3rdparty/eigen/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); \

resources/3rdparty/eigen/Eigen/src/Core/util/Constants.h

@@ -13,13 +13,18 @@
 
 namespace Eigen {
 
-/** This value means that a quantity is not known at compile-time, and that instead the value is
+/** This value means that a positive quantity (e.g., a size) is not known at compile-time, and that instead the value is
   * stored in some runtime variable.
   *
   * Changing the value of Dynamic breaks the ABI, as Dynamic is often used as a template parameter for Matrix.
   */
 const int Dynamic = -1;
 
+/** This value means that a signed quantity (e.g., a signed index) is not known at compile-time, and that instead its value
+  * has to be specified at runtime.
+  */
+const int DynamicIndex = 0xffffff;
+
 /** This value means +Infinity; it is currently used only as the p parameter to MatrixBase::lpNorm<int>().
   * The value Infinity there means the L-infinity norm.
   */
@@ -227,7 +232,9 @@ enum {
     * scalar loops to handle the unaligned boundaries */
   SliceVectorizedTraversal,
   /** \internal Special case to properly handle incompatible scalar types or other defecting cases*/
-  InvalidTraversal
+  InvalidTraversal,
+  /** \internal Evaluate all entries at once */
+  AllAtOnceTraversal
 };
 
 /** \internal \ingroup enums

resources/3rdparty/eigen/Eigen/src/Core/util/ForwardDeclarations.h

@@ -154,7 +154,6 @@ template<typename LhsScalar, typename RhsScalar, bool ConjLhs=false, bool ConjRh
 template<typename Scalar> struct scalar_sum_op;
 template<typename Scalar> struct scalar_difference_op;
 template<typename LhsScalar,typename RhsScalar> struct scalar_conj_product_op;
-template<typename Scalar> struct scalar_quotient_op;
 template<typename Scalar> struct scalar_opposite_op;
 template<typename Scalar> struct scalar_conjugate_op;
 template<typename Scalar> struct scalar_real_op;
@@ -185,6 +184,7 @@ template<typename Scalar> struct scalar_identity_op;
 
 template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_product_op;
 template<typename LhsScalar,typename RhsScalar> struct scalar_multiple2_op;
+template<typename LhsScalar,typename RhsScalar=LhsScalar> struct scalar_quotient_op;
 
 } // end namespace internal
 
@@ -271,6 +271,8 @@ template<typename Derived> struct MatrixExponentialReturnValue;
 template<typename Derived> class MatrixFunctionReturnValue;
 template<typename Derived> class MatrixSquareRootReturnValue;
 template<typename Derived> class MatrixLogarithmReturnValue;
+template<typename Derived> class MatrixPowerReturnValue;
+template<typename Derived, typename Lhs, typename Rhs> class MatrixPowerProductBase;
 
 namespace internal {
 template <typename Scalar>

resources/3rdparty/eigen/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 90
 
 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
                                       (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@@ -115,12 +115,6 @@
 #define EIGEN_MAKESTRING2(a) #a
 #define EIGEN_MAKESTRING(a) EIGEN_MAKESTRING2(a)
 
-#if EIGEN_GNUC_AT_LEAST(4,1) && !defined(__clang__) && !defined(__INTEL_COMPILER)
-#define EIGEN_FLATTEN_ATTRIB __attribute__((flatten))
-#else
-#define EIGEN_FLATTEN_ATTRIB
-#endif
-
 // EIGEN_STRONG_INLINE is a stronger version of the inline, using __forceinline on MSVC,
 // but it still doesn't use GCC's always_inline. This is useful in (common) situations where MSVC needs forceinline
 // but GCC is still doing fine with just inline.
@@ -301,6 +295,12 @@
 #if defined(_MSC_VER) && (!defined(__INTEL_COMPILER))
 #define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
   using Base::operator =;
+#elif defined(__clang__) // workaround clang bug (see http://forum.kde.org/viewtopic.php?f=74&t=102653)
+#define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
+  using Base::operator =; \
+  EIGEN_STRONG_INLINE Derived& operator=(const Derived& other) { Base::operator=(other); return *this; } \
+  template <typename OtherDerived> \
+  EIGEN_STRONG_INLINE Derived& operator=(const DenseBase<OtherDerived>& other) { Base::operator=(other.derived()); return *this; }
 #else
 #define EIGEN_INHERIT_ASSIGNMENT_EQUAL_OPERATOR(Derived) \
   using Base::operator =; \

resources/3rdparty/eigen/Eigen/src/Core/util/StaticAssert.h

@@ -89,7 +89,8 @@
         YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED,
         YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED,
         THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE,
-        THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH
+        THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH,
+        OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG
       };
     };
 

resources/3rdparty/eigen/Eigen/src/Core/util/XprHelper.h

@@ -65,6 +65,27 @@ template<typename T> class variable_if_dynamic<T, Dynamic>
     void setValue(T value) { m_value = value; }
 };
 
+/** \internal like variable_if_dynamic but for DynamicIndex
+  */
+template<typename T, int Value> class variable_if_dynamicindex
+{
+  public:
+    EIGEN_EMPTY_STRUCT_CTOR(variable_if_dynamicindex)
+    explicit variable_if_dynamicindex(T v) { EIGEN_ONLY_USED_FOR_DEBUG(v); assert(v == T(Value)); }
+    static T value() { return T(Value); }
+    void setValue(T) {}
+};
+
+template<typename T> class variable_if_dynamicindex<T, DynamicIndex>
+{
+    T m_value;
+    variable_if_dynamicindex() { assert(false); }
+  public:
+    explicit variable_if_dynamicindex(T value) : m_value(value) {}
+    T value() const { return m_value; }
+    void setValue(T value) { m_value = value; }
+};
+
 template<typename T> struct functor_traits
 {
   enum
@@ -301,9 +322,9 @@ 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

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AlignedBox.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/AngleAxis.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Hyperplane.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Quaternion.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Rotation2D.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/RotationBase.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Scaling.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Transform.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>

resources/3rdparty/eigen/Eigen/src/Eigen2Support/Geometry/Translation.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/LeastSquares.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //

resources/3rdparty/eigen/Eigen/src/Eigen2Support/SVD.h

@@ -1,5 +1,5 @@
 // This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
+// for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //

resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h

@@ -3,7 +3,7 @@
 //
 // Copyright (C) 2009 Claire Maurice
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
 // 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
@@ -220,6 +220,19 @@ template<typename _MatrixType> class ComplexEigenSolver
       return m_schur.info();
     }
 
+    /** \brief Sets the maximum number of iterations allowed. */
+    ComplexEigenSolver& setMaxIterations(Index maxIters)
+    {
+      m_schur.setMaxIterations(maxIters);
+      return *this;
+    }
+
+    /** \brief Returns the maximum number of iterations. */
+    Index getMaxIterations()
+    {
+      return m_schur.getMaxIterations();
+    }
+
   protected:
     EigenvectorType m_eivec;
     EigenvalueType m_eivalues;
@@ -235,7 +248,8 @@ template<typename _MatrixType> class ComplexEigenSolver
 
 
 template<typename MatrixType>
-ComplexEigenSolver<MatrixType>& ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
+ComplexEigenSolver<MatrixType>& 
+ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
 {
   // this code is inspired from Jampack
   assert(matrix.cols() == matrix.rows());

resources/3rdparty/eigen/Eigen/src/Eigenvalues/ComplexSchur.h

@@ -3,7 +3,7 @@
 //
 // Copyright (C) 2009 Claire Maurice
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
 // 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
@@ -96,7 +96,8 @@ template<typename _MatrixType> class ComplexSchur
         m_matU(size,size),
         m_hess(size),
         m_isInitialized(false),
-        m_matUisUptodate(false)
+        m_matUisUptodate(false),
+        m_maxIters(-1)
     {}
 
     /** \brief Constructor; computes Schur decomposition of given matrix. 
@@ -109,11 +110,12 @@ template<typename _MatrixType> class ComplexSchur
       * \sa matrixT() and matrixU() for examples.
       */
     ComplexSchur(const MatrixType& matrix, bool computeU = true)
-            : m_matT(matrix.rows(),matrix.cols()),
-              m_matU(matrix.rows(),matrix.cols()),
-              m_hess(matrix.rows()),
-              m_isInitialized(false),
-              m_matUisUptodate(false)
+      : m_matT(matrix.rows(),matrix.cols()),
+        m_matU(matrix.rows(),matrix.cols()),
+        m_hess(matrix.rows()),
+        m_isInitialized(false),
+        m_matUisUptodate(false),
+        m_maxIters(-1)
     {
       compute(matrix, computeU);
     }
@@ -166,6 +168,7 @@ template<typename _MatrixType> class ComplexSchur
       * 
       * \param[in]  matrix  Square matrix whose Schur decomposition is to be computed.
       * \param[in]  computeU  If true, both T and U are computed; if false, only T is computed.
+
       * \returns    Reference to \c *this
       *
       * The Schur decomposition is computed by first reducing the
@@ -180,6 +183,8 @@ template<typename _MatrixType> class ComplexSchur
       *
       * Example: \include ComplexSchur_compute.cpp
       * Output: \verbinclude ComplexSchur_compute.out
+      *
+      * \sa compute(const MatrixType&, bool, Index)
       */
     ComplexSchur& compute(const MatrixType& matrix, bool computeU = true);
 
@@ -189,15 +194,33 @@ template<typename _MatrixType> class ComplexSchur
       */
     ComputationInfo info() const
     {
-      eigen_assert(m_isInitialized && "RealSchur is not initialized.");
+      eigen_assert(m_isInitialized && "ComplexSchur is not initialized.");
       return m_info;
     }
 
-    /** \brief Maximum number of iterations.
+    /** \brief Sets the maximum number of iterations allowed. 
       *
-      * Maximum number of iterations allowed for an eigenvalue to converge. 
+      * If not specified by the user, the maximum number of iterations is m_maxIterationsPerRow times the size
+      * of the matrix.
       */
-    static const int m_maxIterations = 30;
+    ComplexSchur& setMaxIterations(Index maxIters)
+    {
+      m_maxIters = maxIters;
+      return *this;
+    }
+
+    /** \brief Returns the maximum number of iterations. */
+    Index getMaxIterations()
+    {
+      return m_maxIters;
+    }
+
+    /** \brief Maximum number of iterations per row.
+      *
+      * If not otherwise specified, the maximum number of iterations is this number times the size of the
+      * matrix. It is currently set to 30.
+      */
+    static const int m_maxIterationsPerRow = 30;
 
   protected:
     ComplexMatrixType m_matT, m_matU;
@@ -205,6 +228,7 @@ template<typename _MatrixType> class ComplexSchur
     ComputationInfo m_info;
     bool m_isInitialized;
     bool m_matUisUptodate;
+    Index m_maxIters;
 
   private:  
     bool subdiagonalEntryIsNeglegible(Index i);
@@ -329,6 +353,10 @@ struct complex_schur_reduce_to_hessenberg<MatrixType, false>
 template<typename MatrixType>
 void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
 {  
+  Index maxIters = m_maxIters;
+  if (maxIters == -1)
+    maxIters = m_maxIterationsPerRow * m_matT.rows();
+
   // The matrix m_matT is divided in three parts. 
   // Rows 0,...,il-1 are decoupled from the rest because m_matT(il,il-1) is zero. 
   // Rows il,...,iu is the part we are working on (the active submatrix).
@@ -336,6 +364,7 @@ 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 +379,10 @@ 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 > maxIters) break;
 
     // find il, the top row of the active submatrix
     il = iu-1;
@@ -382,7 +412,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
     }
   }
 
-  if(iter <= m_maxIterations * m_matT.cols()) 
+  if(totalIter <= maxIters)
     m_info = Success;
   else
     m_info = NoConvergence;

resources/3rdparty/eigen/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) \
 { \

resources/3rdparty/eigen/Eigen/src/Eigenvalues/EigenSolver.h

@@ -2,7 +2,7 @@
 // for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
 // 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
@@ -281,6 +281,19 @@ template<typename _MatrixType> class EigenSolver
       return m_realSchur.info();
     }
 
+    /** \brief Sets the maximum number of iterations allowed. */
+    EigenSolver& setMaxIterations(Index maxIters)
+    {
+      m_realSchur.setMaxIterations(maxIters);
+      return *this;
+    }
+
+    /** \brief Returns the maximum number of iterations. */
+    Index getMaxIterations()
+    {
+      return m_realSchur.getMaxIterations();
+    }
+
   private:
     void doComputeEigenvectors();
 
@@ -348,12 +361,14 @@ typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eige
 }
 
 template<typename MatrixType>
-EigenSolver<MatrixType>& EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
+EigenSolver<MatrixType>& 
+EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
 {
   assert(matrix.cols() == matrix.rows());
 
   // Reduce to real Schur form.
   m_realSchur.compute(matrix, computeEigenvectors);
+
   if (m_realSchur.info() == Success)
   {
     m_matT = m_realSchur.matrixT();
@@ -532,7 +547,7 @@ void EigenSolver<MatrixType>::doComputeEigenvectors()
             if ((vr == 0.0) && (vi == 0.0))
               vr = eps * norm * (internal::abs(w) + internal::abs(q) + internal::abs(x) + internal::abs(y) + internal::abs(lastw));
 
-	    std::complex<Scalar> cc = cdiv(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra,vr,vi);
+            std::complex<Scalar> cc = cdiv(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra,vr,vi);
             m_matT.coeffRef(i,n-1) = internal::real(cc);
             m_matT.coeffRef(i,n) = internal::imag(cc);
             if (internal::abs(x) > (internal::abs(lastw) + internal::abs(q)))

resources/3rdparty/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h

@@ -0,0 +1,339 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_GENERALIZEDEIGENSOLVER_H
+#define EIGEN_GENERALIZEDEIGENSOLVER_H
+
+#include "./RealQZ.h"
+
+namespace Eigen { 
+
+/** \eigenvalues_module \ingroup Eigenvalues_Module
+  *
+  *
+  * \class GeneralizedEigenSolver
+  *
+  * \brief Computes the generalized eigenvalues and eigenvectors of a pair of general matrices
+  *
+  * \tparam _MatrixType the type of the matrices of which we are computing the
+  * eigen-decomposition; this is expected to be an instantiation of the Matrix
+  * class template. Currently, only real matrices are supported.
+  *
+  * The generalized eigenvalues and eigenvectors of a matrix pair \f$ A \f$ and \f$ B \f$ are scalars
+  * \f$ \lambda \f$ and vectors \f$ v \f$ such that \f$ Av = \lambda Bv \f$.  If
+  * \f$ D \f$ is a diagonal matrix with the eigenvalues on the diagonal, and
+  * \f$ V \f$ is a matrix with the eigenvectors as its columns, then \f$ A V =
+  * B V D \f$. The matrix \f$ V \f$ is almost always invertible, in which case we
+  * have \f$ A = B V D V^{-1} \f$. This is called the generalized eigen-decomposition.
+  *
+  * The generalized eigenvalues and eigenvectors of a matrix pair may be complex, even when the
+  * matrices are real. Moreover, the generalized eigenvalue might be infinite if the matrix B is
+  * singular. To workaround this difficulty, the eigenvalues are provided as a pair of complex \f$ \alpha \f$
+  * and real \f$ \beta \f$ such that: \f$ \lambda_i = \alpha_i / \beta_i \f$. If \f$ \beta_i \f$ is (nearly) zero,
+  * then one can consider the well defined left eigenvalue \f$ \mu = \beta_i / \alpha_i\f$ such that:
+  * \f$ \mu_i A v_i = B v_i \f$, or even \f$ \mu_i u_i^T A  = u_i^T B \f$ where \f$ u_i \f$ is
+  * called the left eigenvector.
+  *
+  * Call the function compute() to compute the generalized eigenvalues and eigenvectors of
+  * a given matrix pair. Alternatively, you can use the
+  * GeneralizedEigenSolver(const MatrixType&, const MatrixType&, bool) constructor which computes the
+  * eigenvalues and eigenvectors at construction time. Once the eigenvalue and
+  * eigenvectors are computed, they can be retrieved with the eigenvalues() and
+  * eigenvectors() functions.
+  *
+  * Here is an usage example of this class:
+  * Example: \include GeneralizedEigenSolver.cpp
+  * Output: \verbinclude GeneralizedEigenSolver.out
+  *
+  * \sa MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver
+  */
+template<typename _MatrixType> class GeneralizedEigenSolver
+{
+  public:
+
+    /** \brief Synonym for the template parameter \p _MatrixType. */
+    typedef _MatrixType MatrixType;
+
+    enum {
+      RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+      ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+      Options = MatrixType::Options,
+      MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+      MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+    };
+
+    /** \brief Scalar type for matrices of type #MatrixType. */
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef typename MatrixType::Index Index;
+
+    /** \brief Complex scalar type for #MatrixType. 
+      *
+      * This is \c std::complex<Scalar> if #Scalar is real (e.g.,
+      * \c float or \c double) and just \c Scalar if #Scalar is
+      * complex.
+      */
+    typedef std::complex<RealScalar> ComplexScalar;
+
+    /** \brief Type for vector of real scalar values eigenvalues as returned by betas().
+      *
+      * This is a column vector with entries of type #Scalar.
+      * The length of the vector is the size of #MatrixType.
+      */
+    typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> VectorType;
+
+    /** \brief Type for vector of complex scalar values eigenvalues as returned by betas().
+      *
+      * This is a column vector with entries of type #ComplexScalar.
+      * The length of the vector is the size of #MatrixType.
+      */
+    typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ComplexVectorType;
+
+    /** \brief Expression type for the eigenvalues as returned by eigenvalues().
+      */
+    typedef CwiseBinaryOp<internal::scalar_quotient_op<ComplexScalar,Scalar>,ComplexVectorType,VectorType> EigenvalueType;
+
+    /** \brief Type for matrix of eigenvectors as returned by eigenvectors(). 
+      *
+      * This is a square matrix with entries of type #ComplexScalar. 
+      * The size is the same as the size of #MatrixType.
+      */
+    typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, MaxColsAtCompileTime> EigenvectorsType;
+
+    /** \brief Default constructor.
+      *
+      * The default constructor is useful in cases in which the user intends to
+      * perform decompositions via EigenSolver::compute(const MatrixType&, bool).
+      *
+      * \sa compute() for an example.
+      */
+    GeneralizedEigenSolver() : m_eivec(), m_alphas(), m_betas(), m_isInitialized(false), m_realQZ(), m_matS(), m_tmp() {}
+
+    /** \brief Default constructor with memory preallocation
+      *
+      * Like the default constructor but with preallocation of the internal data
+      * according to the specified problem \a size.
+      * \sa GeneralizedEigenSolver()
+      */
+    GeneralizedEigenSolver(Index size)
+      : m_eivec(size, size),
+        m_alphas(size),
+        m_betas(size),
+        m_isInitialized(false),
+        m_eigenvectorsOk(false),
+        m_realQZ(size),
+        m_matS(size, size),
+        m_tmp(size)
+    {}
+
+    /** \brief Constructor; computes the generalized eigendecomposition of given matrix pair.
+      * 
+      * \param[in]  A  Square matrix whose eigendecomposition is to be computed.
+      * \param[in]  B  Square matrix whose eigendecomposition is to be computed.
+      * \param[in]  computeEigenvectors  If true, both the eigenvectors and the
+      *    eigenvalues are computed; if false, only the eigenvalues are computed.
+      *
+      * This constructor calls compute() to compute the generalized eigenvalues
+      * and eigenvectors.
+      *
+      * \sa compute()
+      */
+    GeneralizedEigenSolver(const MatrixType& A, const MatrixType& B, bool computeEigenvectors = true)
+      : m_eivec(A.rows(), A.cols()),
+        m_alphas(A.cols()),
+        m_betas(A.cols()),
+        m_isInitialized(false),
+        m_eigenvectorsOk(false),
+        m_realQZ(A.cols()),
+        m_matS(A.rows(), A.cols()),
+        m_tmp(A.cols())
+    {
+      compute(A, B, computeEigenvectors);
+    }
+
+    /* \brief Returns the computed generalized eigenvectors.
+      *
+      * \returns  %Matrix whose columns are the (possibly complex) eigenvectors.
+      *
+      * \pre Either the constructor 
+      * GeneralizedEigenSolver(const MatrixType&,const MatrixType&, bool) or the member function
+      * compute(const MatrixType&, const MatrixType& bool) has been called before, and
+      * \p computeEigenvectors was set to true (the default).
+      *
+      * Column \f$ k \f$ of the returned matrix is an eigenvector corresponding
+      * to eigenvalue number \f$ k \f$ as returned by eigenvalues().  The
+      * eigenvectors are normalized to have (Euclidean) norm equal to one. The
+      * matrix returned by this function is the matrix \f$ V \f$ in the
+      * generalized eigendecomposition \f$ A = B V D V^{-1} \f$, if it exists.
+      *
+      * \sa eigenvalues()
+      */
+//    EigenvectorsType eigenvectors() const;
+
+    /** \brief Returns an expression of the computed generalized eigenvalues.
+      *
+      * \returns An expression of the column vector containing the eigenvalues.
+      *
+      * It is a shortcut for \code this->alphas().cwiseQuotient(this->betas()); \endcode
+      * Not that betas might contain zeros. It is therefore not recommended to use this function,
+      * but rather directly deal with the alphas and betas vectors.
+      *
+      * \pre Either the constructor 
+      * GeneralizedEigenSolver(const MatrixType&,const MatrixType&,bool) or the member function
+      * compute(const MatrixType&,const MatrixType&,bool) has been called before.
+      *
+      * The eigenvalues are repeated according to their algebraic multiplicity,
+      * so there are as many eigenvalues as rows in the matrix. The eigenvalues 
+      * are not sorted in any particular order.
+      *
+      * \sa alphas(), betas(), eigenvectors()
+      */
+    EigenvalueType eigenvalues() const
+    {
+      eigen_assert(m_isInitialized && "GeneralizedEigenSolver is not initialized.");
+      return EigenvalueType(m_alphas,m_betas);
+    }
+
+    /** \returns A const reference to the vectors containing the alpha values
+      *
+      * This vector permits to reconstruct the j-th eigenvalues as alphas(i)/betas(j).
+      *
+      * \sa betas(), eigenvalues() */
+    ComplexVectorType alphas() const
+    {
+      eigen_assert(m_isInitialized && "GeneralizedEigenSolver is not initialized.");
+      return m_alphas;
+    }
+
+    /** \returns A const reference to the vectors containing the beta values
+      *
+      * This vector permits to reconstruct the j-th eigenvalues as alphas(i)/betas(j).
+      *
+      * \sa alphas(), eigenvalues() */
+    VectorType betas() const
+    {
+      eigen_assert(m_isInitialized && "GeneralizedEigenSolver is not initialized.");
+      return m_betas;
+    }
+
+    /** \brief Computes generalized eigendecomposition of given matrix.
+      * 
+      * \param[in]  A  Square matrix whose eigendecomposition is to be computed.
+      * \param[in]  B  Square matrix whose eigendecomposition is to be computed.
+      * \param[in]  computeEigenvectors  If true, both the eigenvectors and the
+      *    eigenvalues are computed; if false, only the eigenvalues are
+      *    computed. 
+      * \returns    Reference to \c *this
+      *
+      * This function computes the eigenvalues of the real matrix \p matrix.
+      * The eigenvalues() function can be used to retrieve them.  If 
+      * \p computeEigenvectors is true, then the eigenvectors are also computed
+      * and can be retrieved by calling eigenvectors().
+      *
+      * The matrix is first reduced to real generalized Schur form using the RealQZ
+      * class. The generalized Schur decomposition is then used to compute the eigenvalues
+      * and eigenvectors.
+      *
+      * The cost of the computation is dominated by the cost of the
+      * generalized Schur decomposition.
+      *
+      * This method reuses of the allocated data in the GeneralizedEigenSolver object.
+      */
+    GeneralizedEigenSolver& compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors = true);
+
+    ComputationInfo info() const
+    {
+      eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
+      return m_realQZ.info();
+    }
+
+    /** Sets the maximal number of iterations allowed.
+    */
+    GeneralizedEigenSolver& setMaxIterations(Index maxIters)
+    {
+      m_realQZ.setMaxIterations(maxIters);
+      return *this;
+    }
+
+  protected:
+    MatrixType m_eivec;
+    ComplexVectorType m_alphas;
+    VectorType m_betas;
+    bool m_isInitialized;
+    bool m_eigenvectorsOk;
+    RealQZ<MatrixType> m_realQZ;
+    MatrixType m_matS;
+
+    typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
+    ColumnVectorType m_tmp;
+};
+
+//template<typename MatrixType>
+//typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType GeneralizedEigenSolver<MatrixType>::eigenvectors() const
+//{
+//  eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
+//  eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
+//  Index n = m_eivec.cols();
+//  EigenvectorsType matV(n,n);
+//  // TODO
+//  return matV;
+//}
+
+template<typename MatrixType>
+GeneralizedEigenSolver<MatrixType>&
+GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors)
+{
+  eigen_assert(A.cols() == A.rows() && B.cols() == A.rows() && B.cols() == B.rows());
+
+  // Reduce to generalized real Schur form:
+  // A = Q S Z and B = Q T Z
+  m_realQZ.compute(A, B, computeEigenvectors);
+
+  if (m_realQZ.info() == Success)
+  {
+    m_matS = m_realQZ.matrixS();
+    if (computeEigenvectors)
+      m_eivec = m_realQZ.matrixZ().transpose();
+  
+    // Compute eigenvalues from matS
+    m_alphas.resize(A.cols());
+    m_betas.resize(A.cols());
+    Index i = 0;
+    while (i < A.cols())
+    {
+      if (i == A.cols() - 1 || m_matS.coeff(i+1, i) == Scalar(0))
+      {
+        m_alphas.coeffRef(i) = m_matS.coeff(i, i);
+        m_betas.coeffRef(i)  = m_realQZ.matrixT().coeff(i,i);
+        ++i;
+      }
+      else
+      {
+        Scalar p = Scalar(0.5) * (m_matS.coeff(i, i) - m_matS.coeff(i+1, i+1));
+        Scalar z = internal::sqrt(internal::abs(p * p + m_matS.coeff(i+1, i) * m_matS.coeff(i, i+1)));
+        m_alphas.coeffRef(i)   = ComplexScalar(m_matS.coeff(i+1, i+1) + p, z);
+        m_alphas.coeffRef(i+1) = ComplexScalar(m_matS.coeff(i+1, i+1) + p, -z);
+
+        m_betas.coeffRef(i)   = m_realQZ.matrixT().coeff(i,i);
+        m_betas.coeffRef(i+1) = m_realQZ.matrixT().coeff(i,i);
+        i += 2;
+      }
+    }
+  }
+
+  m_isInitialized = true;
+  m_eigenvectorsOk = false;//computeEigenvectors;
+
+  return *this;
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_GENERALIZEDEIGENSOLVER_H

resources/3rdparty/eigen/Eigen/src/Eigenvalues/RealQZ.h

@@ -0,0 +1,618 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Alexey Korepanov <kaikaikai@yandex.ru>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_REAL_QZ_H
+#define EIGEN_REAL_QZ_H
+
+namespace Eigen {
+
+  /** \eigenvalues_module \ingroup Eigenvalues_Module
+   *
+   *
+   * \class RealQZ
+   *
+   * \brief Performs a real QZ decomposition of a pair of square matrices
+   *
+   * \tparam _MatrixType the type of the matrix of which we are computing the
+   * real QZ decomposition; this is expected to be an instantiation of the
+   * Matrix class template.
+   *
+   * Given a real square matrices A and B, this class computes the real QZ
+   * decomposition: \f$ A = Q S Z \f$, \f$ B = Q T Z \f$ where Q and Z are
+   * real orthogonal matrixes, T is upper-triangular matrix, and S is upper
+   * quasi-triangular matrix. An orthogonal matrix is a matrix whose
+   * inverse is equal to its transpose, \f$ U^{-1} = U^T \f$. A quasi-triangular
+   * matrix is a block-triangular matrix whose diagonal consists of 1-by-1
+   * blocks and 2-by-2 blocks where further reduction is impossible due to
+   * complex eigenvalues. 
+   *
+   * The eigenvalues of the pencil \f$ A - z B \f$ can be obtained from
+   * 1x1 and 2x2 blocks on the diagonals of S and T.
+   *
+   * Call the function compute() to compute the real QZ decomposition of a
+   * given pair of matrices. Alternatively, you can use the 
+   * RealQZ(const MatrixType& B, const MatrixType& B, bool computeQZ)
+   * constructor which computes the real QZ decomposition at construction
+   * time. Once the decomposition is computed, you can use the matrixS(),
+   * matrixT(), matrixQ() and matrixZ() functions to retrieve the matrices
+   * S, T, Q and Z in the decomposition. If computeQZ==false, some time
+   * is saved by not computing matrices Q and Z.
+   *
+   * Example: \include RealQZ_compute.cpp
+   * Output: \include RealQZ_compute.out
+   *
+   * \note The implementation is based on the algorithm in "Matrix Computations"
+   * by Gene H. Golub and Charles F. Van Loan, and a paper "An algorithm for
+   * generalized eigenvalue problems" by C.B.Moler and G.W.Stewart.
+   *
+   * \sa class RealSchur, class ComplexSchur, class EigenSolver, class ComplexEigenSolver
+   */
+
+  template<typename _MatrixType> class RealQZ
+  {
+    public:
+      typedef _MatrixType MatrixType;
+      enum {
+        RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+        ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+        Options = MatrixType::Options,
+        MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+        MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
+      };
+      typedef typename MatrixType::Scalar Scalar;
+      typedef std::complex<typename NumTraits<Scalar>::Real> ComplexScalar;
+      typedef typename MatrixType::Index Index;
+
+      typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> EigenvalueType;
+      typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
+
+      /** \brief Default constructor.
+       *
+       * \param [in] size  Positive integer, size of the matrix whose QZ decomposition will be computed.
+       *
+       * The default constructor is useful in cases in which the user intends to
+       * perform decompositions via compute().  The \p size parameter is only
+       * used as a hint. It is not an error to give a wrong \p size, but it may
+       * impair performance.
+       *
+       * \sa compute() for an example.
+       */
+      RealQZ(Index size = RowsAtCompileTime==Dynamic ? 1 : RowsAtCompileTime) : 
+        m_S(size, size),
+        m_T(size, size),
+        m_Q(size, size),
+        m_Z(size, size),
+        m_workspace(size*2),
+        m_maxIters(400),
+        m_isInitialized(false)
+        { }
+
+      /** \brief Constructor; computes real QZ decomposition of given matrices
+       * 
+       * \param[in]  A          Matrix A.
+       * \param[in]  B          Matrix B.
+       * \param[in]  computeQZ  If false, A and Z are not computed.
+       *
+       * This constructor calls compute() to compute the QZ decomposition.
+       */
+      RealQZ(const MatrixType& A, const MatrixType& B, bool computeQZ = true) :
+        m_S(A.rows(),A.cols()),
+        m_T(A.rows(),A.cols()),
+        m_Q(A.rows(),A.cols()),
+        m_Z(A.rows(),A.cols()),
+        m_workspace(A.rows()*2),
+        m_maxIters(400),
+        m_isInitialized(false) {
+          compute(A, B, computeQZ);
+        }
+
+      /** \brief Returns matrix Q in the QZ decomposition. 
+       *
+       * \returns A const reference to the matrix Q.
+       */
+      const MatrixType& matrixQ() const {
+        eigen_assert(m_isInitialized && "RealQZ is not initialized.");
+        eigen_assert(m_computeQZ && "The matrices Q and Z have not been computed during the QZ decomposition.");
+        return m_Q;
+      }
+
+      /** \brief Returns matrix Z in the QZ decomposition. 
+       *
+       * \returns A const reference to the matrix Z.
+       */
+      const MatrixType& matrixZ() const {
+        eigen_assert(m_isInitialized && "RealQZ is not initialized.");
+        eigen_assert(m_computeQZ && "The matrices Q and Z have not been computed during the QZ decomposition.");
+        return m_Z;
+      }
+
+      /** \brief Returns matrix S in the QZ decomposition. 
+       *
+       * \returns A const reference to the matrix S.
+       */
+      const MatrixType& matrixS() const {
+        eigen_assert(m_isInitialized && "RealQZ is not initialized.");
+        return m_S;
+      }
+
+      /** \brief Returns matrix S in the QZ decomposition. 
+       *
+       * \returns A const reference to the matrix S.
+       */
+      const MatrixType& matrixT() const {
+        eigen_assert(m_isInitialized && "RealQZ is not initialized.");
+        return m_T;
+      }
+
+      /** \brief Computes QZ decomposition of given matrix. 
+       * 
+       * \param[in]  A          Matrix A.
+       * \param[in]  B          Matrix B.
+       * \param[in]  computeQZ  If false, A and Z are not computed.
+       * \returns    Reference to \c *this
+       */
+      RealQZ& compute(const MatrixType& A, const MatrixType& B, bool computeQZ = true);
+
+      /** \brief Reports whether previous computation was successful.
+       *
+       * \returns \c Success if computation was succesful, \c NoConvergence otherwise.
+       */
+      ComputationInfo info() const
+      {
+        eigen_assert(m_isInitialized && "RealQZ is not initialized.");
+        return m_info;
+      }
+
+      /** \brief Returns number of performed QR-like iterations.
+      */
+      Index iterations() const
+      {
+        eigen_assert(m_isInitialized && "RealQZ is not initialized.");
+        return m_global_iter;
+      }
+
+      /** Sets the maximal number of iterations allowed to converge to one eigenvalue
+       * or decouple the problem.
+      */
+      RealQZ& setMaxIterations(Index maxIters)
+      {
+        m_maxIters = maxIters;
+        return *this;
+      }
+
+    private:
+
+      MatrixType m_S, m_T, m_Q, m_Z;
+      Matrix<Scalar,Dynamic,1> m_workspace;
+      ComputationInfo m_info;
+      Index m_maxIters;
+      bool m_isInitialized;
+      bool m_computeQZ;
+      Scalar m_normOfT, m_normOfS;
+      Index m_global_iter;
+
+      typedef Matrix<Scalar,3,1> Vector3s;
+      typedef Matrix<Scalar,2,1> Vector2s;
+      typedef Matrix<Scalar,2,2> Matrix2s;
+      typedef JacobiRotation<Scalar> JRs;
+
+      void hessenbergTriangular();
+      void computeNorms();
+      Index findSmallSubdiagEntry(Index iu);
+      Index findSmallDiagEntry(Index f, Index l);
+      void splitOffTwoRows(Index i);
+      void pushDownZero(Index z, Index f, Index l);
+      void step(Index f, Index l, Index iter);
+
+  }; // RealQZ
+
+  /** \internal Reduces S and T to upper Hessenberg - triangular form */
+  template<typename MatrixType>
+    void RealQZ<MatrixType>::hessenbergTriangular()
+    {
+
+      const Index dim = m_S.cols();
+
+      // perform QR decomposition of T, overwrite T with R, save Q
+      HouseholderQR<MatrixType> qrT(m_T);
+      m_T = qrT.matrixQR();
+      m_T.template triangularView<StrictlyLower>().setZero();
+      m_Q = qrT.householderQ();
+      // overwrite S with Q* S
+      m_S.applyOnTheLeft(m_Q.adjoint());
+      // init Z as Identity
+      if (m_computeQZ)
+        m_Z = MatrixType::Identity(dim,dim);
+      // reduce S to upper Hessenberg with Givens rotations
+      for (Index j=0; j<=dim-3; j++) {
+        for (Index i=dim-1; i>=j+2; i--) {
+          JRs G;
+          // kill S(i,j)
+          if(m_S.coeff(i,j) != 0)
+          {
+            G.makeGivens(m_S.coeff(i-1,j), m_S.coeff(i,j), &m_S.coeffRef(i-1, j));
+            m_S.coeffRef(i,j) = Scalar(0.0);
+            m_S.rightCols(dim-j-1).applyOnTheLeft(i-1,i,G.adjoint());
+            m_T.rightCols(dim-i+1).applyOnTheLeft(i-1,i,G.adjoint());
+          }
+          // update Q
+          if (m_computeQZ)
+            m_Q.applyOnTheRight(i-1,i,G);
+          // kill T(i,i-1)
+          if(m_T.coeff(i,i-1)!=Scalar(0))
+          {
+            G.makeGivens(m_T.coeff(i,i), m_T.coeff(i,i-1), &m_T.coeffRef(i,i));
+            m_T.coeffRef(i,i-1) = Scalar(0.0);
+            m_S.applyOnTheRight(i,i-1,G);
+            m_T.topRows(i).applyOnTheRight(i,i-1,G);
+          }
+          // update Z
+          if (m_computeQZ)
+            m_Z.applyOnTheLeft(i,i-1,G.adjoint());
+        }
+      }
+    }
+
+  /** \internal Computes vector L1 norms of S and T when in Hessenberg-Triangular form already */
+  template<typename MatrixType>
+    inline void RealQZ<MatrixType>::computeNorms()
+    {
+      const Index size = m_S.cols();
+      m_normOfS = Scalar(0.0);
+      m_normOfT = Scalar(0.0);
+      for (Index j = 0; j < size; ++j)
+      {
+        m_normOfS += m_S.col(j).segment(0, (std::min)(size,j+2)).cwiseAbs().sum();
+        m_normOfT += m_T.row(j).segment(j, size - j).cwiseAbs().sum();
+      }
+    }
+
+
+  /** \internal Look for single small sub-diagonal element S(res, res-1) and return res (or 0) */
+  template<typename MatrixType>
+    inline typename MatrixType::Index RealQZ<MatrixType>::findSmallSubdiagEntry(Index iu)
+    {
+      Index res = iu;
+      while (res > 0)
+      {
+        Scalar s = internal::abs(m_S.coeff(res-1,res-1)) + internal::abs(m_S.coeff(res,res));
+        if (s == Scalar(0.0))
+          s = m_normOfS;
+        if (internal::abs(m_S.coeff(res,res-1)) < NumTraits<Scalar>::epsilon() * s)
+          break;
+        res--;
+      }
+      return res;
+    }
+
+  /** \internal Look for single small diagonal element T(res, res) for res between f and l, and return res (or f-1)  */
+  template<typename MatrixType>
+    inline typename MatrixType::Index RealQZ<MatrixType>::findSmallDiagEntry(Index f, Index l)
+    {
+      Index res = l;
+      while (res >= f) {
+        if (internal::abs(m_T.coeff(res,res)) <= NumTraits<Scalar>::epsilon() * m_normOfT)
+          break;
+        res--;
+      }
+      return res;
+    }
+
+  /** \internal decouple 2x2 diagonal block in rows i, i+1 if eigenvalues are real */
+  template<typename MatrixType>
+    inline void RealQZ<MatrixType>::splitOffTwoRows(Index i)
+    {
+      const Index dim=m_S.cols();
+      if (internal::abs(m_S.coeff(i+1,i)==Scalar(0)))
+        return;
+      Index z = findSmallDiagEntry(i,i+1);
+      if (z==i-1)
+      {
+        // block of (S T^{-1})
+        Matrix2s STi = m_T.template block<2,2>(i,i).template triangularView<Upper>().
+          template solve<OnTheRight>(m_S.template block<2,2>(i,i));
+        Scalar p = Scalar(0.5)*(STi(0,0)-STi(1,1));
+        Scalar q = p*p + STi(1,0)*STi(0,1);
+        if (q>=0) {
+          Scalar z = internal::sqrt(q);
+          // one QR-like iteration for ABi - lambda I
+          // is enough - when we know exact eigenvalue in advance,
+          // convergence is immediate
+          JRs G;
+          if (p>=0)
+            G.makeGivens(p + z, STi(1,0));
+          else
+            G.makeGivens(p - z, STi(1,0));
+          m_S.rightCols(dim-i).applyOnTheLeft(i,i+1,G.adjoint());
+          m_T.rightCols(dim-i).applyOnTheLeft(i,i+1,G.adjoint());
+          // update Q
+          if (m_computeQZ)
+            m_Q.applyOnTheRight(i,i+1,G);
+
+          G.makeGivens(m_T.coeff(i+1,i+1), m_T.coeff(i+1,i));
+          m_S.topRows(i+2).applyOnTheRight(i+1,i,G);
+          m_T.topRows(i+2).applyOnTheRight(i+1,i,G);
+          // update Z
+          if (m_computeQZ)
+            m_Z.applyOnTheLeft(i+1,i,G.adjoint());
+
+          m_S.coeffRef(i+1,i) = Scalar(0.0);
+          m_T.coeffRef(i+1,i) = Scalar(0.0);
+        }
+      }
+      else
+      {
+        pushDownZero(z,i,i+1);
+      }
+    }
+
+  /** \internal use zero in T(z,z) to zero S(l,l-1), working in block f..l */
+  template<typename MatrixType>
+    inline void RealQZ<MatrixType>::pushDownZero(Index z, Index f, Index l)
+    {
+      JRs G;
+      const Index dim = m_S.cols();
+      for (Index zz=z; zz<l; zz++)
+      {
+        // push 0 down
+        Index firstColS = zz>f ? (zz-1) : zz;
+        G.makeGivens(m_T.coeff(zz, zz+1), m_T.coeff(zz+1, zz+1));
+        m_S.rightCols(dim-firstColS).applyOnTheLeft(zz,zz+1,G.adjoint());
+        m_T.rightCols(dim-zz).applyOnTheLeft(zz,zz+1,G.adjoint());
+        m_T.coeffRef(zz+1,zz+1) = Scalar(0.0);
+        // update Q
+        if (m_computeQZ)
+          m_Q.applyOnTheRight(zz,zz+1,G);
+        // kill S(zz+1, zz-1)
+        if (zz>f)
+        {
+          G.makeGivens(m_S.coeff(zz+1, zz), m_S.coeff(zz+1,zz-1));
+          m_S.topRows(zz+2).applyOnTheRight(zz, zz-1,G);
+          m_T.topRows(zz+1).applyOnTheRight(zz, zz-1,G);
+          m_S.coeffRef(zz+1,zz-1) = Scalar(0.0);
+          // update Z
+          if (m_computeQZ)
+            m_Z.applyOnTheLeft(zz,zz-1,G.adjoint());
+        }
+      }
+      // finally kill S(l,l-1)
+      G.makeGivens(m_S.coeff(l,l), m_S.coeff(l,l-1));
+      m_S.applyOnTheRight(l,l-1,G);
+      m_T.applyOnTheRight(l,l-1,G);
+      m_S.coeffRef(l,l-1)=Scalar(0.0);
+      // update Z
+      if (m_computeQZ)
+        m_Z.applyOnTheLeft(l,l-1,G.adjoint());
+    }
+
+  /** \internal QR-like iterative step for block f..l */
+  template<typename MatrixType>
+    inline void RealQZ<MatrixType>::step(Index f, Index l, Index iter) {
+      const Index dim = m_S.cols();
+
+      // x, y, z
+      Scalar x, y, z;
+      if (iter==10)
+      {
+        // Wilkinson ad hoc shift
+        const Scalar
+          a11=m_S.coeff(f+0,f+0), a12=m_S.coeff(f+0,f+1),
+          a21=m_S.coeff(f+1,f+0), a22=m_S.coeff(f+1,f+1), a32=m_S.coeff(f+2,f+1),
+          b12=m_T.coeff(f+0,f+1),
+          b11i=Scalar(1.0)/m_T.coeff(f+0,f+0),
+          b22i=Scalar(1.0)/m_T.coeff(f+1,f+1),
+          a87=m_S.coeff(l-1,l-2),
+          a98=m_S.coeff(l-0,l-1),
+          b77i=Scalar(1.0)/m_T.coeff(l-2,l-2),
+          b88i=Scalar(1.0)/m_T.coeff(l-1,l-1);
+        Scalar ss = internal::abs(a87*b77i) + internal::abs(a98*b88i),
+               lpl = Scalar(1.5)*ss,
+               ll = ss*ss;
+        x = ll + a11*a11*b11i*b11i - lpl*a11*b11i + a12*a21*b11i*b22i
+          - a11*a21*b12*b11i*b11i*b22i;
+        y = a11*a21*b11i*b11i - lpl*a21*b11i + a21*a22*b11i*b22i 
+          - a21*a21*b12*b11i*b11i*b22i;
+        z = a21*a32*b11i*b22i;
+      }
+      else if (iter==16)
+      {
+        // another exceptional shift
+        x = m_S.coeff(f,f)/m_T.coeff(f,f)-m_S.coeff(l,l)/m_T.coeff(l,l) + m_S.coeff(l,l-1)*m_T.coeff(l-1,l) /
+          (m_T.coeff(l-1,l-1)*m_T.coeff(l,l));
+        y = m_S.coeff(f+1,f)/m_T.coeff(f,f);
+        z = 0;
+      }
+      else if (iter>23 && !(iter%8))
+      {
+        // extremely exceptional shift
+        x = internal::random<Scalar>(-1.0,1.0);
+        y = internal::random<Scalar>(-1.0,1.0);
+        z = internal::random<Scalar>(-1.0,1.0);
+      }
+      else
+      {
+        // Compute the shifts: (x,y,z,0...) = (AB^-1 - l1 I) (AB^-1 - l2 I) e1
+        // where l1 and l2 are the eigenvalues of the 2x2 matrix C = U V^-1 where
+        // U and V are 2x2 bottom right sub matrices of A and B. Thus:
+        //  = AB^-1AB^-1 + l1 l2 I - (l1+l2)(AB^-1)
+        //  = AB^-1AB^-1 + det(M) - tr(M)(AB^-1)
+        // Since we are only interested in having x, y, z with a correct ratio, we have:
+        const Scalar
+          a11 = m_S.coeff(f,f),     a12 = m_S.coeff(f,f+1),
+          a21 = m_S.coeff(f+1,f),   a22 = m_S.coeff(f+1,f+1),
+                                    a32 = m_S.coeff(f+2,f+1),
+
+          a88 = m_S.coeff(l-1,l-1), a89 = m_S.coeff(l-1,l),
+          a98 = m_S.coeff(l,l-1),   a99 = m_S.coeff(l,l),
+
+          b11 = m_T.coeff(f,f),     b12 = m_T.coeff(f,f+1),
+                                    b22 = m_T.coeff(f+1,f+1),
+
+          b88 = m_T.coeff(l-1,l-1), b89 = m_T.coeff(l-1,l),
+                                    b99 = m_T.coeff(l,l);
+
+        x = ( (a88/b88 - a11/b11)*(a99/b99 - a11/b11) - (a89/b99)*(a98/b88) + (a98/b88)*(b89/b99)*(a11/b11) ) * (b11/a21)
+          + a12/b22 - (a11/b11)*(b12/b22);
+        y = (a22/b22-a11/b11) - (a21/b11)*(b12/b22) - (a88/b88-a11/b11) - (a99/b99-a11/b11) + (a98/b88)*(b89/b99);
+        z = a32/b22;
+      }
+
+      JRs G;
+
+      for (Index k=f; k<=l-2; k++)
+      {
+        // variables for Householder reflections
+        Vector2s essential2;
+        Scalar tau, beta;
+
+        Vector3s hr(x,y,z);
+
+        // Q_k to annihilate S(k+1,k-1) and S(k+2,k-1)
+        hr.makeHouseholderInPlace(tau, beta);
+        essential2 = hr.template bottomRows<2>();
+        Index fc=(std::max)(k-1,Index(0));  // first col to update
+        m_S.template middleRows<3>(k).rightCols(dim-fc).applyHouseholderOnTheLeft(essential2, tau, m_workspace.data());
+        m_T.template middleRows<3>(k).rightCols(dim-fc).applyHouseholderOnTheLeft(essential2, tau, m_workspace.data());
+        if (m_computeQZ)
+          m_Q.template middleCols<3>(k).applyHouseholderOnTheRight(essential2, tau, m_workspace.data());
+        if (k>f)
+          m_S.coeffRef(k+2,k-1) = m_S.coeffRef(k+1,k-1) = Scalar(0.0);
+
+        // Z_{k1} to annihilate T(k+2,k+1) and T(k+2,k)
+        hr << m_T.coeff(k+2,k+2),m_T.coeff(k+2,k),m_T.coeff(k+2,k+1);
+        hr.makeHouseholderInPlace(tau, beta);
+        essential2 = hr.template bottomRows<2>();
+        {
+          Index lr = (std::min)(k+4,dim); // last row to update
+          Map<Matrix<Scalar,Dynamic,1> > tmp(m_workspace.data(),lr);
+          // S
+          tmp = m_S.template middleCols<2>(k).topRows(lr) * essential2;
+          tmp += m_S.col(k+2).head(lr);
+          m_S.col(k+2).head(lr) -= tau*tmp;
+          m_S.template middleCols<2>(k).topRows(lr) -= (tau*tmp) * essential2.adjoint();
+          // T
+          tmp = m_T.template middleCols<2>(k).topRows(lr) * essential2;
+          tmp += m_T.col(k+2).head(lr);
+          m_T.col(k+2).head(lr) -= tau*tmp;
+          m_T.template middleCols<2>(k).topRows(lr) -= (tau*tmp) * essential2.adjoint();
+        }
+        if (m_computeQZ)
+        {
+          // Z
+          Map<Matrix<Scalar,1,Dynamic> > tmp(m_workspace.data(),dim);
+          tmp = essential2.adjoint()*(m_Z.template middleRows<2>(k));
+          tmp += m_Z.row(k+2);
+          m_Z.row(k+2) -= tau*tmp;
+          m_Z.template middleRows<2>(k) -= essential2 * (tau*tmp);
+        }
+        m_T.coeffRef(k+2,k) = m_T.coeffRef(k+2,k+1) = Scalar(0.0);
+
+        // Z_{k2} to annihilate T(k+1,k)
+        G.makeGivens(m_T.coeff(k+1,k+1), m_T.coeff(k+1,k));
+        m_S.applyOnTheRight(k+1,k,G);
+        m_T.applyOnTheRight(k+1,k,G);
+        // update Z
+        if (m_computeQZ)
+          m_Z.applyOnTheLeft(k+1,k,G.adjoint());
+        m_T.coeffRef(k+1,k) = Scalar(0.0);
+
+        // update x,y,z
+        x = m_S.coeff(k+1,k);
+        y = m_S.coeff(k+2,k);
+        if (k < l-2)
+          z = m_S.coeff(k+3,k);
+      } // loop over k
+
+      // Q_{n-1} to annihilate y = S(l,l-2)
+      G.makeGivens(x,y);
+      m_S.applyOnTheLeft(l-1,l,G.adjoint());
+      m_T.applyOnTheLeft(l-1,l,G.adjoint());
+      if (m_computeQZ)
+        m_Q.applyOnTheRight(l-1,l,G);
+      m_S.coeffRef(l,l-2) = Scalar(0.0);
+
+      // Z_{n-1} to annihilate T(l,l-1)
+      G.makeGivens(m_T.coeff(l,l),m_T.coeff(l,l-1));
+      m_S.applyOnTheRight(l,l-1,G);
+      m_T.applyOnTheRight(l,l-1,G);
+      if (m_computeQZ)
+        m_Z.applyOnTheLeft(l,l-1,G.adjoint());
+      m_T.coeffRef(l,l-1) = Scalar(0.0);
+    }
+
+
+  template<typename MatrixType>
+    RealQZ<MatrixType>& RealQZ<MatrixType>::compute(const MatrixType& A_in, const MatrixType& B_in, bool computeQZ)
+    {
+
+      const Index dim = A_in.cols();
+
+      assert (A_in.rows()==dim && A_in.cols()==dim 
+          && B_in.rows()==dim && B_in.cols()==dim 
+          && "Need square matrices of the same dimension");
+
+      m_isInitialized = true;
+      m_computeQZ = computeQZ;
+      m_S = A_in; m_T = B_in;
+      m_workspace.resize(dim*2);
+      m_global_iter = 0;
+
+      // entrance point: hessenberg triangular decomposition
+      hessenbergTriangular();
+      // compute L1 vector norms of T, S into m_normOfS, m_normOfT
+      computeNorms();
+
+      Index l = dim-1, 
+            f, 
+            local_iter = 0;
+
+      while (l>0 && local_iter<m_maxIters)
+      {
+        f = findSmallSubdiagEntry(l);
+        // now rows and columns f..l (including) decouple from the rest of the problem
+        if (f>0) m_S.coeffRef(f,f-1) = Scalar(0.0);
+        if (f == l) // One root found
+        {
+          l--;
+          local_iter = 0;
+        }
+        else if (f == l-1) // Two roots found
+        {
+          splitOffTwoRows(f);
+          l -= 2;
+          local_iter = 0;
+        }
+        else // No convergence yet
+        {
+          // if there's zero on diagonal of T, we can isolate an eigenvalue with Givens rotations
+          Index z = findSmallDiagEntry(f,l);
+          if (z>=f)
+          {
+            // zero found
+            pushDownZero(z,f,l);
+          }
+          else
+          {
+            // We are sure now that S.block(f,f, l-f+1,l-f+1) is underuced upper-Hessenberg 
+            // and T.block(f,f, l-f+1,l-f+1) is invertible uper-triangular, which allows to
+            // apply a QR-like iteration to rows and columns f..l.
+            step(f,l, local_iter);
+            local_iter++;
+            m_global_iter++;
+          }
+        }
+      }
+      // check if we converged before reaching iterations limit
+      m_info = (local_iter<m_maxIters) ? Success : NoConvergence;
+      return *this;
+    } // end compute
+
+} // end namespace Eigen
+
+#endif //EIGEN_REAL_QZ

resources/3rdparty/eigen/Eigen/src/Eigenvalues/RealSchur.h

@@ -2,7 +2,7 @@
 // for linear algebra.
 //
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
+// Copyright (C) 2010,2012 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
 // 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
@@ -86,7 +86,8 @@ template<typename _MatrixType> class RealSchur
               m_workspaceVector(size),
               m_hess(size),
               m_isInitialized(false),
-              m_matUisUptodate(false)
+              m_matUisUptodate(false),
+              m_maxIters(-1)
     { }
 
     /** \brief Constructor; computes real Schur decomposition of given matrix. 
@@ -105,7 +106,8 @@ template<typename _MatrixType> class RealSchur
               m_workspaceVector(matrix.rows()),
               m_hess(matrix.rows()),
               m_isInitialized(false),
-              m_matUisUptodate(false)
+              m_matUisUptodate(false),
+              m_maxIters(-1)
     {
       compute(matrix, computeU);
     }
@@ -160,6 +162,8 @@ template<typename _MatrixType> class RealSchur
       *
       * Example: \include RealSchur_compute.cpp
       * Output: \verbinclude RealSchur_compute.out
+      *
+      * \sa compute(const MatrixType&, bool, Index)
       */
     RealSchur& compute(const MatrixType& matrix, bool computeU = true);
 
@@ -173,11 +177,29 @@ template<typename _MatrixType> class RealSchur
       return m_info;
     }
 
-    /** \brief Maximum number of iterations.
+    /** \brief Sets the maximum number of iterations allowed. 
+      *
+      * If not specified by the user, the maximum number of iterations is m_maxIterationsPerRow times the size
+      * of the matrix.
+      */
+    RealSchur& setMaxIterations(Index maxIters)
+    {
+      m_maxIters = maxIters;
+      return *this;
+    }
+
+    /** \brief Returns the maximum number of iterations. */
+    Index getMaxIterations()
+    {
+      return m_maxIters;
+    }
+
+    /** \brief Maximum number of iterations per row.
       *
-      * Maximum number of iterations allowed for an eigenvalue to converge. 
+      * If not otherwise specified, the maximum number of iterations is this number times the size of the
+      * matrix. It is currently set to 40.
       */
-    static const int m_maxIterations = 40;
+    static const int m_maxIterationsPerRow = 40;
 
   private:
     
@@ -188,6 +210,7 @@ template<typename _MatrixType> class RealSchur
     ComputationInfo m_info;
     bool m_isInitialized;
     bool m_matUisUptodate;
+    Index m_maxIters;
 
     typedef Matrix<Scalar,3,1> Vector3s;
 
@@ -204,6 +227,9 @@ template<typename MatrixType>
 RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix, bool computeU)
 {
   assert(matrix.cols() == matrix.rows());
+  Index maxIters = m_maxIters;
+  if (maxIters == -1)
+    maxIters = m_maxIterationsPerRow * matrix.rows();
 
   // Step 1. Reduce to Hessenberg form
   m_hess.compute(matrix);
@@ -220,8 +246,9 @@ 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
-  Scalar exshift(0); // sum of exceptional shifts
+  Index iter = 0;      // iteration count for current eigenvalue
+  Index totalIter = 0; // iteration count for whole matrix
+  Scalar exshift(0);   // sum of exceptional shifts
   Scalar norm = computeNormOfT();
 
   if(norm!=0)
@@ -251,14 +278,15 @@ 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 > maxIters) 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 <= maxIters)
     m_info = Success;
   else
     m_info = NoConvergence;
@@ -278,7 +306,7 @@ inline typename MatrixType::Scalar RealSchur<MatrixType>::computeNormOfT()
   //               + m_matT.bottomLeftCorner(size-1,size-1).diagonal().cwiseAbs().sum();
   Scalar norm(0);
   for (Index j = 0; j < size; ++j)
-    norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum();
+    norm += m_matT.col(j).segment(0, (std::min)(size,j+2)).cwiseAbs().sum();
   return norm;
 }
 

resources/3rdparty/eigen/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];

resources/3rdparty/eigen/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) \
 { \

resources/3rdparty/eigen/Eigen/src/Geometry/AngleAxis.h

@@ -76,7 +76,7 @@ public:
     * \warning If the \a axis vector is not normalized, then the angle-axis object
     *          represents an invalid rotation. */
   template<typename Derived>
-  inline AngleAxis(Scalar angle, const MatrixBase<Derived>& axis) : m_axis(axis), m_angle(angle) {}
+  inline AngleAxis(const Scalar& angle, const MatrixBase<Derived>& axis) : m_axis(axis), m_angle(angle) {}
   /** Constructs and initialize the angle-axis rotation from a quaternion \a q. */
   template<typename QuatDerived> inline explicit AngleAxis(const QuaternionBase<QuatDerived>& q) { *this = q; }
   /** Constructs and initialize the angle-axis rotation from a 3x3 rotation matrix. */
@@ -137,7 +137,7 @@ public:
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const AngleAxis& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+  bool isApprox(const AngleAxis& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_axis.isApprox(other.m_axis, prec) && internal::isApprox(m_angle,other.m_angle, prec); }
 };
 

resources/3rdparty/eigen/Eigen/src/Geometry/Hyperplane.h

@@ -75,7 +75,7 @@ public:
     * such that the algebraic equation of the plane is \f$ n \cdot x + d = 0 \f$.
     * \warning the vector normal is assumed to be normalized.
     */
-  inline Hyperplane(const VectorType& n, Scalar d)
+  inline Hyperplane(const VectorType& n, const Scalar& d)
     : m_coeffs(n.size()+1)
   {
     normal() = n;
@@ -256,7 +256,7 @@ public:
     *
     * \sa MatrixBase::isApprox() */
   template<int OtherOptions>
-  bool isApprox(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+  bool isApprox(const Hyperplane<Scalar,AmbientDimAtCompileTime,OtherOptions>& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_coeffs.isApprox(other.m_coeffs, prec); }
 
 protected:

resources/3rdparty/eigen/Eigen/src/Geometry/ParametrizedLine.h

@@ -93,7 +93,7 @@ public:
   VectorType projection(const VectorType& p) const
   { return origin() + direction().dot(p-origin()) * direction(); }
 
-  VectorType pointAt( Scalar t ) const;
+  VectorType pointAt(const Scalar& t) const;
   
   template <int OtherOptions>
   Scalar intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
@@ -154,7 +154,7 @@ inline ParametrizedLine<_Scalar, _AmbientDim,_Options>::ParametrizedLine(const H
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
 inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
-ParametrizedLine<_Scalar, _AmbientDim,_Options>::pointAt( _Scalar t ) const
+ParametrizedLine<_Scalar, _AmbientDim,_Options>::pointAt(const _Scalar& t) const
 {
   return origin() + (direction()*t); 
 }

resources/3rdparty/eigen/Eigen/src/Geometry/Quaternion.h

@@ -161,7 +161,7 @@ public:
     *
     * \sa MatrixBase::isApprox() */
   template<class OtherDerived>
-  bool isApprox(const QuaternionBase<OtherDerived>& other, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const
+  bool isApprox(const QuaternionBase<OtherDerived>& other, const RealScalar& prec = NumTraits<Scalar>::dummy_precision()) const
   { return coeffs().isApprox(other.coeffs(), prec); }
 
 	/** return the result vector of \a v through the rotation*/
@@ -248,7 +248,7 @@ public:
     * while internally the coefficients are stored in the following order:
     * [\c x, \c y, \c z, \c w]
     */
-  inline Quaternion(Scalar w, Scalar x, Scalar y, Scalar z) : m_coeffs(x, y, z, w){}
+  inline Quaternion(const Scalar& w, const Scalar& x, const Scalar& y, const Scalar& z) : m_coeffs(x, y, z, w){}
 
   /** Constructs and initialize a quaternion from the array data */
   inline Quaternion(const Scalar* data) : m_coeffs(data) {}

resources/3rdparty/eigen/Eigen/src/Geometry/Rotation2D.h

@@ -59,7 +59,7 @@ protected:
 public:
 
   /** Construct a 2D counter clock wise rotation from the angle \a a in radian. */
-  inline Rotation2D(Scalar a) : m_angle(a) {}
+  inline Rotation2D(const Scalar& a) : m_angle(a) {}
 
   /** \returns the rotation angle */
   inline Scalar angle() const { return m_angle; }
@@ -89,7 +89,7 @@ public:
   /** \returns the spherical interpolation between \c *this and \a other using
     * parameter \a t. It is in fact equivalent to a linear interpolation.
     */
-  inline Rotation2D slerp(Scalar t, const Rotation2D& other) const
+  inline Rotation2D slerp(const Scalar& t, const Rotation2D& other) const
   { return m_angle * (1-t) + other.angle() * t; }
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
@@ -114,7 +114,7 @@ public:
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const Rotation2D& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+  bool isApprox(const Rotation2D& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return internal::isApprox(m_angle,other.m_angle, prec); }
 };
 

resources/3rdparty/eigen/Eigen/src/Geometry/Scaling.h

@@ -99,7 +99,7 @@ public:
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const UniformScaling& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+  bool isApprox(const UniformScaling& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return internal::isApprox(m_factor, other.factor(), prec); }
 
 };
@@ -122,11 +122,11 @@ static inline UniformScaling<std::complex<RealScalar> > Scaling(const std::compl
 
 /** Constructs a 2D axis aligned scaling */
 template<typename Scalar>
-static inline DiagonalMatrix<Scalar,2> Scaling(Scalar sx, Scalar sy)
+static inline DiagonalMatrix<Scalar,2> Scaling(const Scalar& sx, const Scalar& sy)
 { return DiagonalMatrix<Scalar,2>(sx, sy); }
 /** Constructs a 3D axis aligned scaling */
 template<typename Scalar>
-static inline DiagonalMatrix<Scalar,3> Scaling(Scalar sx, Scalar sy, Scalar sz)
+static inline DiagonalMatrix<Scalar,3> Scaling(const Scalar& sx, const Scalar& sy, const Scalar& sz)
 { return DiagonalMatrix<Scalar,3>(sx, sy, sz); }
 
 /** Constructs an axis aligned scaling expression from vector expression \a coeffs

resources/3rdparty/eigen/Eigen/src/Geometry/Transform.h

@@ -506,8 +506,8 @@ public:
   template<typename OtherDerived>
   inline Transform& prescale(const MatrixBase<OtherDerived> &other);
 
-  inline Transform& scale(Scalar s);
-  inline Transform& prescale(Scalar s);
+  inline Transform& scale(const Scalar& s);
+  inline Transform& prescale(const Scalar& s);
 
   template<typename OtherDerived>
   inline Transform& translate(const MatrixBase<OtherDerived> &other);
@@ -521,8 +521,8 @@ public:
   template<typename RotationType>
   inline Transform& prerotate(const RotationType& rotation);
 
-  Transform& shear(Scalar sx, Scalar sy);
-  Transform& preshear(Scalar sx, Scalar sy);
+  Transform& shear(const Scalar& sx, const Scalar& sy);
+  Transform& preshear(const Scalar& sx, const Scalar& sy);
 
   inline Transform& operator=(const TranslationType& t);
   inline Transform& operator*=(const TranslationType& t) { return translate(t.vector()); }
@@ -584,7 +584,7 @@ public:
     * determined by \a prec.
     *
     * \sa MatrixBase::isApprox() */
-  bool isApprox(const Transform& other, typename NumTraits<Scalar>::Real prec = NumTraits<Scalar>::dummy_precision()) const
+  bool isApprox(const Transform& other, const typename NumTraits<Scalar>::Real& prec = NumTraits<Scalar>::dummy_precision()) const
   { return m_matrix.isApprox(other.m_matrix, prec); }
 
   /** Sets the last row to [0 ... 0 1]
@@ -794,7 +794,7 @@ Transform<Scalar,Dim,Mode,Options>::scale(const MatrixBase<OtherDerived> &other)
   * \sa prescale(Scalar)
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::scale(Scalar s)
+inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::scale(const Scalar& s)
 {
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
   linearExt() *= s;
@@ -821,7 +821,7 @@ Transform<Scalar,Dim,Mode,Options>::prescale(const MatrixBase<OtherDerived> &oth
   * \sa scale(Scalar)
   */
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::prescale(Scalar s)
+inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::prescale(const Scalar& s)
 {
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
   m_matrix.template topRows<Dim>() *= s;
@@ -909,7 +909,7 @@ Transform<Scalar,Dim,Mode,Options>::prerotate(const RotationType& rotation)
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 Transform<Scalar,Dim,Mode,Options>&
-Transform<Scalar,Dim,Mode,Options>::shear(Scalar sx, Scalar sy)
+Transform<Scalar,Dim,Mode,Options>::shear(const Scalar& sx, const Scalar& sy)
 {
   EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)
@@ -925,7 +925,7 @@ Transform<Scalar,Dim,Mode,Options>::shear(Scalar sx, Scalar sy)
   */
 template<typename Scalar, int Dim, int Mode, int Options>
 Transform<Scalar,Dim,Mode,Options>&
-Transform<Scalar,Dim,Mode,Options>::preshear(Scalar sx, Scalar sy)
+Transform<Scalar,Dim,Mode,Options>::preshear(const Scalar& sx, const Scalar& sy)
 {
   EIGEN_STATIC_ASSERT(int(Dim)==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
   EIGEN_STATIC_ASSERT(Mode!=int(Isometry), THIS_METHOD_IS_ONLY_FOR_SPECIFIC_TRANSFORMATIONS)

resources/3rdparty/eigen/Eigen/src/Geometry/Umeyama.h

@@ -153,16 +153,21 @@ umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, boo
     Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
   }
 
-  // Eq. (42)
-  const Scalar c = 1/src_var * svd.singularValues().dot(S);
-
-  // Eq. (41)
-  // Note that we first assign dst_mean to the destination so that there no need
-  // for a temporary.
-  Rt.col(m).head(m) = dst_mean;
-  Rt.col(m).head(m).noalias() -= c*Rt.topLeftCorner(m,m)*src_mean;
-
-  if (with_scaling) Rt.block(0,0,m,m) *= c;
+  if (with_scaling)
+  {
+    // Eq. (42)
+    const Scalar c = 1/src_var * svd.singularValues().dot(S);
+
+    // Eq. (41)
+    Rt.col(m).head(m) = dst_mean;
+    Rt.col(m).head(m).noalias() -= c*Rt.topLeftCorner(m,m)*src_mean;
+    Rt.block(0,0,m,m) *= c;
+  }
+  else
+  {
+    Rt.col(m).head(m) = dst_mean;
+    Rt.col(m).head(m).noalias() -= Rt.topLeftCorner(m,m)*src_mean;
+  }
 
   return Rt;
 }

resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h

@@ -39,10 +39,11 @@ bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
   int maxIters = iters;
 
   int n = mat.cols();
+  x = precond.solve(x);
   VectorType r  = rhs - mat * x;
   VectorType r0 = r;
   
-  RealScalar r0_sqnorm = r0.squaredNorm();
+  RealScalar r0_sqnorm = rhs.squaredNorm();
   Scalar rho    = 1;
   Scalar alpha  = 1;
   Scalar w      = 1;
@@ -223,7 +224,8 @@ public:
   template<typename Rhs,typename Dest>
   void _solve(const Rhs& b, Dest& x) const
   {
-    x.setZero();
+//     x.setZero();
+  x = b;
     _solveWithGuess(b,x);
   }
 

resources/3rdparty/eigen/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h

@@ -10,8 +10,56 @@
 #ifndef EIGEN_INCOMPLETE_LUT_H
 #define EIGEN_INCOMPLETE_LUT_H
 
+
 namespace Eigen { 
 
+namespace internal {
+    
+/**
+ * Compute a quick-sort split of a vector 
+ * On output, the vector row is permuted such that its elements satisfy
+ * abs(row(i)) >= abs(row(ncut)) if i<ncut
+ * abs(row(i)) <= abs(row(ncut)) if i>ncut 
+ * \param row The vector of values
+ * \param ind The array of index for the elements in @p row
+ * \param ncut  The number of largest elements to keep
+ **/ 
+template <typename VectorV, typename VectorI>
+int QuickSplit(VectorV &row, VectorI &ind, int ncut)
+{
+  typedef typename VectorV::RealScalar RealScalar;
+  using std::swap;
+  int mid;
+  int n = row.size(); /* length of the vector */
+  int first, last ; 
+  
+  ncut--; /* to fit the zero-based indices */
+  first = 0; 
+  last = n-1; 
+  if (ncut < first || ncut > last ) return 0;
+  
+  do {
+    mid = first; 
+    RealScalar abskey = std::abs(row(mid)); 
+    for (int j = first + 1; j <= last; j++) {
+      if ( std::abs(row(j)) > abskey) {
+        ++mid;
+        swap(row(mid), row(j));
+        swap(ind(mid), ind(j));
+      }
+    }
+    /* Interchange for the pivot element */
+    swap(row(mid), row(first));
+    swap(ind(mid), ind(first));
+    
+    if (mid > ncut) last = mid - 1;
+    else if (mid < ncut ) first = mid + 1; 
+  } while (mid != ncut );
+  
+  return 0; /* mid is equal to ncut */ 
+}
+
+}// end namespace internal
 /**
  * \brief Incomplete LU factorization with dual-threshold strategy
  * During the numerical factorization, two dropping rules are used :
@@ -126,10 +174,6 @@ class IncompleteLUT : internal::noncopyable
 
 protected:
 
-    template <typename VectorV, typename VectorI>
-    int QuickSplit(VectorV &row, VectorI &ind, int ncut);
-
-
     /** keeps off-diagonal entries; drops diagonal entries */
     struct keep_diag {
       inline bool operator() (const Index& row, const Index& col, const Scalar&) const
@@ -171,51 +215,6 @@ void IncompleteLUT<Scalar>::setFillfactor(int fillfactor)
   this->m_fillfactor = fillfactor;   
 }
 
-
-/**
- * Compute a quick-sort split of a vector 
- * On output, the vector row is permuted such that its elements satisfy
- * abs(row(i)) >= abs(row(ncut)) if i<ncut
- * abs(row(i)) <= abs(row(ncut)) if i>ncut 
- * \param row The vector of values
- * \param ind The array of index for the elements in @p row
- * \param ncut  The number of largest elements to keep
- **/ 
-template <typename Scalar>
-template <typename VectorV, typename VectorI>
-int IncompleteLUT<Scalar>::QuickSplit(VectorV &row, VectorI &ind, int ncut)
-{
-  using std::swap;
-  int mid;
-  int n = row.size(); /* length of the vector */
-  int first, last ; 
-  
-  ncut--; /* to fit the zero-based indices */
-  first = 0; 
-  last = n-1; 
-  if (ncut < first || ncut > last ) return 0;
-  
-  do {
-    mid = first; 
-    RealScalar abskey = std::abs(row(mid)); 
-    for (int j = first + 1; j <= last; j++) {
-      if ( std::abs(row(j)) > abskey) {
-        ++mid;
-        swap(row(mid), row(j));
-        swap(ind(mid), ind(j));
-      }
-    }
-    /* Interchange for the pivot element */
-    swap(row(mid), row(first));
-    swap(ind(mid), ind(first));
-    
-    if (mid > ncut) last = mid - 1;
-    else if (mid < ncut ) first = mid + 1; 
-  } while (mid != ncut );
-  
-  return 0; /* mid is equal to ncut */ 
-}
-
 template <typename Scalar>
 template<typename _MatrixType>
 void IncompleteLUT<Scalar>::analyzePattern(const _MatrixType& amat)
@@ -400,7 +399,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
     len = (std::min)(sizel, nnzL);
     typename Vector::SegmentReturnType ul(u.segment(0, sizel));
     typename VectorXi::SegmentReturnType jul(ju.segment(0, sizel));
-    QuickSplit(ul, jul, len);
+    internal::QuickSplit(ul, jul, len);
 
     // store the largest m_fill elements of the L part
     m_lu.startVec(ii);
@@ -429,7 +428,7 @@ void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
     len = (std::min)(sizeu, nnzU);
     typename Vector::SegmentReturnType uu(u.segment(ii+1, sizeu-1));
     typename VectorXi::SegmentReturnType juu(ju.segment(ii+1, sizeu-1));
-    QuickSplit(uu, juu, len);
+    internal::QuickSplit(uu, juu, len);
 
     // store the largest elements of the U part
     for(int k = ii + 1; k < ii + len; k++)

resources/3rdparty/eigen/Eigen/src/Jacobi/Jacobi.h

@@ -207,7 +207,6 @@ void JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar
 template<typename Scalar>
 void JacobiRotation<Scalar>::makeGivens(const Scalar& p, const Scalar& q, Scalar* r, internal::false_type)
 {
-
   if(q==Scalar(0))
   {
     m_c = p<Scalar(0) ? Scalar(-1) : Scalar(1);
@@ -303,6 +302,11 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
 
   Scalar* EIGEN_RESTRICT x = &_x.coeffRef(0);
   Scalar* EIGEN_RESTRICT y = &_y.coeffRef(0);
+  
+  OtherScalar c = j.c();
+  OtherScalar s = j.s();
+  if (c==OtherScalar(1) && s==OtherScalar(0))
+    return;
 
   /*** dynamic-size vectorized paths ***/
 
@@ -316,16 +320,16 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
     Index alignedStart = internal::first_aligned(y, size);
     Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize;
 
-    const Packet pc = pset1<Packet>(j.c());
-    const Packet ps = pset1<Packet>(j.s());
+    const Packet pc = pset1<Packet>(c);
+    const Packet ps = pset1<Packet>(s);
     conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
 
     for(Index i=0; i<alignedStart; ++i)
     {
       Scalar xi = x[i];
       Scalar yi = y[i];
-      x[i] =  j.c() * xi + conj(j.s()) * yi;
-      y[i] = -j.s() * xi + conj(j.c()) * yi;
+      x[i] =  c * xi + conj(s) * yi;
+      y[i] = -s * xi + conj(c) * yi;
     }
 
     Scalar* EIGEN_RESTRICT px = x + alignedStart;
@@ -372,8 +376,8 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
     {
       Scalar xi = x[i];
       Scalar yi = y[i];
-      x[i] =  j.c() * xi + conj(j.s()) * yi;
-      y[i] = -j.s() * xi + conj(j.c()) * yi;
+      x[i] =  c * xi + conj(s) * yi;
+      y[i] = -s * xi + conj(c) * yi;
     }
   }
 
@@ -382,8 +386,8 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
           (VectorX::Flags & VectorY::Flags & PacketAccessBit) &&
           (VectorX::Flags & VectorY::Flags & AlignedBit))
   {
-    const Packet pc = pset1<Packet>(j.c());
-    const Packet ps = pset1<Packet>(j.s());
+    const Packet pc = pset1<Packet>(c);
+    const Packet ps = pset1<Packet>(s);
     conj_helper<Packet,Packet,NumTraits<Scalar>::IsComplex,false> pcj;
     Scalar* EIGEN_RESTRICT px = x;
     Scalar* EIGEN_RESTRICT py = y;
@@ -405,8 +409,8 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
     {
       Scalar xi = *x;
       Scalar yi = *y;
-      *x =  j.c() * xi + conj(j.s()) * yi;
-      *y = -j.s() * xi + conj(j.c()) * yi;
+      *x =  c * xi + conj(s) * yi;
+      *y = -s * xi + conj(c) * yi;
       x += incrx;
       y += incry;
     }

resources/3rdparty/eigen/Eigen/src/MetisSupport/CMakeLists.txt

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

resources/3rdparty/eigen/Eigen/src/MetisSupport/MetisSupport.h

@@ -0,0 +1,138 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+#ifndef METIS_SUPPORT_H
+#define METIS_SUPPORT_H
+
+namespace Eigen {
+/**
+ * Get the fill-reducing ordering from the METIS package
+ * 
+ * If A is the original matrix and Ap is the permuted matrix, 
+ * the fill-reducing permutation is defined as follows :
+ * Row (column) i of A is the matperm(i) row (column) of Ap. 
+ * WARNING: As computed by METIS, this corresponds to the vector iperm (instead of perm)
+ */
+template <typename Index>
+class MetisOrdering
+{
+public:
+  typedef PermutationMatrix<Dynamic,Dynamic,Index> PermutationType;
+  typedef Matrix<Index,Dynamic,1> IndexVector; 
+  
+  template <typename MatrixType>
+  void get_symmetrized_graph(const MatrixType& A)
+  {
+    Index m = A.cols(); 
+    
+    // Get the transpose of the input matrix 
+    MatrixType At = A.transpose(); 
+    // Get the number of nonzeros elements in each row/col of At+A
+    Index TotNz = 0; 
+    IndexVector visited(m); 
+    visited.setConstant(-1); 
+    for (int j = 0; j < m; j++)
+    {
+      // Compute the union structure of of A(j,:) and At(j,:)
+      visited(j) = j; // Do not include the diagonal element
+      // Get the nonzeros in row/column j of A
+      for (typename MatrixType::InnerIterator it(A, j); it; ++it)
+      {
+        Index idx = it.index(); // Get the row index (for column major) or column index (for row major)
+        if (visited(idx) != j ) 
+        {
+          visited(idx) = j; 
+          ++TotNz; 
+        }
+      }
+      //Get the nonzeros in row/column j of At
+      for (typename MatrixType::InnerIterator it(At, j); it; ++it)
+      {
+        Index idx = it.index(); 
+        if(visited(idx) != j)
+        {
+          visited(idx) = j; 
+          ++TotNz; 
+        }
+      }
+    }
+    // Reserve place for A + At
+    m_indexPtr.resize(m+1);
+    m_innerIndices.resize(TotNz); 
+
+    // Now compute the real adjacency list of each column/row 
+    visited.setConstant(-1); 
+    Index CurNz = 0; 
+    for (int j = 0; j < m; j++)
+    {
+      m_indexPtr(j) = CurNz; 
+      
+      visited(j) = j; // Do not include the diagonal element
+      // Add the pattern of row/column j of A to A+At
+      for (typename MatrixType::InnerIterator it(A,j); it; ++it)
+      {
+        Index idx = it.index(); // Get the row index (for column major) or column index (for row major)
+        if (visited(idx) != j ) 
+        {
+          visited(idx) = j; 
+          m_innerIndices(CurNz) = idx; 
+          CurNz++; 
+        }
+      }
+      //Add the pattern of row/column j of At to A+At
+      for (typename MatrixType::InnerIterator it(At, j); it; ++it)
+      {
+        Index idx = it.index(); 
+        if(visited(idx) != j)
+        {
+          visited(idx) = j; 
+          m_innerIndices(CurNz) = idx; 
+          ++CurNz; 
+        }
+      }
+    }
+    m_indexPtr(m) = CurNz;    
+  }
+  
+  template <typename MatrixType>
+  void operator() (const MatrixType& A, PermutationType& matperm)
+  {
+     Index m = A.cols();
+     IndexVector perm(m),iperm(m); 
+    // First, symmetrize the matrix graph. 
+     get_symmetrized_graph(A); 
+     int output_error;
+     
+     // Call the fill-reducing routine from METIS 
+     output_error = METIS_NodeND(&m, m_indexPtr.data(), m_innerIndices.data(), NULL, NULL, perm.data(), iperm.data());
+     
+    if(output_error != METIS_OK) 
+    {
+      //FIXME The ordering interface should define a class of possible errors 
+     std::cerr << "ERROR WHILE CALLING THE METIS PACKAGE \n"; 
+     return; 
+    }
+    
+    // Get the fill-reducing permutation 
+    //NOTE:  If Ap is the permuted matrix then perm and iperm vectors are defined as follows 
+    // Row (column) i of Ap is the perm(i) row(column) of A, and row (column) i of A is the iperm(i) row(column) of Ap
+    
+    // To be consistent with the use of the permutation in SparseLU module, we thus keep the iperm vector 
+     matperm.resize(m);
+     for (int j = 0; j < m; j++)
+       matperm.indices()(j) = iperm(j); 
+   
+  }
+  
+  protected:
+    IndexVector m_indexPtr; // Pointer to the adjacenccy list of each row/column
+    IndexVector m_innerIndices; // Adjacency list 
+};
+
+}// end namespace eigen 
+#endif

resources/3rdparty/eigen/Eigen/src/OrderingMethods/Ordering.h

@@ -0,0 +1,158 @@
+ 
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012  Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+//
+// Eigen is free software; you can redistribute it and/or
+// modify it under the terms of the GNU Lesser General Public
+// License as published by the Free Software Foundation; either
+// version 3 of the License, or (at your option) any later version.
+//
+// Alternatively, you can redistribute it and/or
+// modify it under the terms of the GNU General Public License as
+// published by the Free Software Foundation; either version 2 of
+// the License, or (at your option) any later version.
+//
+// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
+// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
+// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
+// GNU General Public License for more details.
+//
+// You should have received a copy of the GNU Lesser General Public
+// License and a copy of the GNU General Public License along with
+// Eigen. If not, see <http://www.gnu.org/licenses/>.
+
+#ifndef EIGEN_ORDERING_H
+#define EIGEN_ORDERING_H
+
+#include "Amd.h"
+namespace Eigen {
+  
+#include "Eigen_Colamd.h"
+
+namespace internal {
+    
+    /**
+    * Get the symmetric pattern A^T+A from the input matrix A. 
+    * FIXME: The values should not be considered here
+    */
+    template<typename MatrixType> 
+    void ordering_helper_at_plus_a(const MatrixType& mat, MatrixType& symmat)
+    {
+      MatrixType C;
+      C = mat.transpose(); // NOTE: Could be  costly
+      for (int i = 0; i < C.rows(); i++) 
+      {
+          for (typename MatrixType::InnerIterator it(C, i); it; ++it)
+            it.valueRef() = 0.0;
+      }
+      symmat = C + mat; 
+    }
+    
+}
+
+/** 
+ * Get the approximate minimum degree ordering
+ * If the matrix is not structurally symmetric, an ordering of A^T+A is computed
+ * \tparam  Index The type of indices of the matrix 
+ */
+template <typename Index>
+class AMDOrdering
+{
+  public:
+    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+    
+    /** Compute the permutation vector from a sparse matrix
+     * This routine is much faster if the input matrix is column-major     
+     */
+    template <typename MatrixType>
+    void operator()(const MatrixType& mat, PermutationType& perm)
+    {
+      // Compute the symmetric pattern
+      SparseMatrix<typename MatrixType::Scalar, ColMajor, Index> symm;
+      internal::ordering_helper_at_plus_a(mat,symm); 
+    
+      // Call the AMD routine 
+      //m_mat.prune(keep_diag());
+      internal::minimum_degree_ordering(symm, perm);
+    }
+    
+    /** Compute the permutation with a selfadjoint matrix */
+    template <typename SrcType, unsigned int SrcUpLo> 
+    void operator()(const SparseSelfAdjointView<SrcType, SrcUpLo>& mat, PermutationType& perm)
+    { 
+      SparseMatrix<typename SrcType::Scalar, ColMajor, Index> C = mat;
+      
+      // Call the AMD routine 
+      // m_mat.prune(keep_diag()); //Remove the diagonal elements 
+      internal::minimum_degree_ordering(C, perm);
+    }
+};
+
+/** 
+ * Get the natural ordering
+ * 
+ *NOTE Returns an empty permutation matrix
+ * \tparam  Index The type of indices of the matrix 
+ */
+template <typename Index>
+class NaturalOrdering
+{
+  public:
+    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType;
+    
+    /** Compute the permutation vector from a column-major sparse matrix */
+    template <typename MatrixType>
+    void operator()(const MatrixType& mat, PermutationType& perm)
+    {
+      perm.resize(0); 
+    }
+    
+};
+
+/** 
+ * Get the column approximate minimum degree ordering 
+ * The matrix should be in column-major format
+ */
+template<typename Index>
+class COLAMDOrdering; 
+#include "Eigen_Colamd.h"
+
+template<typename Index>
+class COLAMDOrdering
+{
+  public:
+    typedef PermutationMatrix<Dynamic, Dynamic, Index> PermutationType; 
+    typedef Matrix<Index, Dynamic, 1> IndexVector; 
+    /** Compute the permutation vector form a sparse matrix */
+    template <typename MatrixType>
+    void operator() (const MatrixType& mat, PermutationType& perm)
+    {
+        int m = mat.rows();
+        int n = mat.cols();
+        int nnz = mat.nonZeros();
+        // Get the recommended value of Alen to be used by colamd
+        int Alen = internal::colamd_recommended(nnz, m, n); 
+        // Set the default parameters
+        double knobs [COLAMD_KNOBS]; 
+        int stats [COLAMD_STATS];
+        internal::colamd_set_defaults(knobs);
+        
+        int info;
+        IndexVector p(n+1), A(Alen); 
+        for(int i=0; i <= n; i++) p(i) = mat.outerIndexPtr()[i];
+        for(int i=0; i < nnz; i++) A(i) = mat.innerIndexPtr()[i];
+        // Call Colamd routine to compute the ordering 
+        info = internal::colamd(m, n, Alen, A.data(), p.data(), knobs, stats); 
+        eigen_assert( info && "COLAMD failed " );
+        
+        perm.resize(n);
+        for (int i = 0; i < n; i++) perm.indices()(p(i)) = i;
+        
+    }
+ 
+};
+
+} // end namespace Eigen
+#endif