bump

conditional jump. This makes Part considered an "expensive" xpr
 that must be evaluated in operations such as Product.
This fixes bug #80.

.hgignore

@@ -0,0 +1,24 @@
+syntax: glob
+qrc_*cxx
+*.orig
+*.pyc
+*.diff
+diff
+*.save
+*.old
+*.gmo
+*.qm
+core
+core.*
+*.bak
+*~
+build
+*.moc.*
+*.moc
+ui_*
+CMakeCache.txt
+tags
+.*.swp
+activity.png
+*.out
+*.php*

CMakeLists.txt

@@ -1,22 +1,15 @@
 project(Eigen)
-set(EIGEN_VERSION_NUMBER "2.0-beta5")
-
-#if the svnversion program is absent, this will leave the SVN_REVISION string empty,
-#but won't stop CMake.
-execute_process(COMMAND svnversion -n ${CMAKE_SOURCE_DIR}
-                OUTPUT_VARIABLE EIGEN_SVNVERSION_OUTPUT)
-
-#we only want EIGEN_SVN_REVISION if it is an actual revision number, not a string like "exported"
-string(REGEX MATCH "^[0-9]+.*" EIGEN_SVN_REVISION "${EIGEN_SVNVERSION_OUTPUT}")
-
-if(EIGEN_SVN_REVISION)
-  set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER} (SVN revision ${EIGEN_SVN_REVISION})")
-else(EIGEN_SVN_REVISION)
-  set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER}")
-endif(EIGEN_SVN_REVISION)
-
 cmake_minimum_required(VERSION 2.6.2)
 
+set(INCLUDE_INSTALL_DIR
+    "${CMAKE_INSTALL_PREFIX}/include/eigen2"
+    CACHE PATH
+    "The directory where we install the header files"
+    FORCE)
+
+set(EIGEN_VERSION_NUMBER "2.0.11")
+set(EIGEN_VERSION "${EIGEN_VERSION_NUMBER}")
+
 set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
 
 option(EIGEN_BUILD_TESTS "Build tests" OFF)
@@ -25,6 +18,9 @@ if(NOT WIN32)
   option(EIGEN_BUILD_LIB "Build the binary shared library" OFF)
 endif(NOT WIN32)
 option(EIGEN_BUILD_BTL "Build benchmark suite" OFF)
+if(NOT WIN32)
+  option(EIGEN_BUILD_PKGCONFIG "Build pkg-config .pc file for Eigen" ON)
+endif(NOT WIN32)
 
 if(EIGEN_BUILD_LIB)
   option(EIGEN_TEST_LIB "Build the unit tests using the library (disable -pedantic)" OFF)
@@ -34,7 +30,12 @@ set(CMAKE_INCLUDE_CURRENT_DIR ON)
 
 if(CMAKE_COMPILER_IS_GNUCXX)
   if(CMAKE_SYSTEM_NAME MATCHES Linux)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wnon-virtual-dtor -Wno-long-long -ansi -Wundef -Wcast-align -Wchar-subscripts -Wall -W -Wpointer-arith -Wwrite-strings -Wformat-security -Wextra -fno-exceptions -fno-check-new -fno-common -fstrict-aliasing")
+    include(CheckCXXCompilerFlag)
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wnon-virtual-dtor -Wno-long-long -ansi -Wundef -Wcast-align -Wchar-subscripts -Wall -W -Wpointer-arith -Wwrite-strings -Wformat-security -fno-exceptions -fno-check-new -fno-common -fstrict-aliasing")
+    check_cxx_compiler_flag("-Wextra" has_wextra)
+    if(has_wextra)
+      set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Wextra")
+    endif()
     if(NOT EIGEN_TEST_LIB)
       set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -pedantic")
     endif(NOT EIGEN_TEST_LIB)
@@ -76,11 +77,26 @@ if(MSVC)
   endif(EIGEN_TEST_SSE2)
 endif(MSVC)
 
+option(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION "Disable explicit vectorization in tests/examples" OFF)
+if(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
+  add_definitions(-DEIGEN_DONT_VECTORIZE=1)
+  message("Disabling vectorization in tests/examples")
+endif(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
+
 include_directories(${CMAKE_CURRENT_SOURCE_DIR} ${CMAKE_CURRENT_BINARY_DIR})
 
+if(EIGEN_BUILD_PKGCONFIG)
+    configure_file(eigen2.pc.in eigen2.pc) # uses INCLUDE_INSTALL_DIR
+    install(FILES ${CMAKE_CURRENT_BINARY_DIR}/eigen2.pc
+        DESTINATION share/pkgconfig
+        )
+endif(EIGEN_BUILD_PKGCONFIG)
+
 add_subdirectory(Eigen)
+add_subdirectory(unsupported)
 
 if(EIGEN_BUILD_TESTS)
+  include(CTest)
   add_subdirectory(test)
 endif(EIGEN_BUILD_TESTS)
 

CTestConfig.cmake

@@ -0,0 +1,13 @@
+## This file should be placed in the root directory of your project.
+## Then modify the CMakeLists.txt file in the root directory of your
+## project to incorporate the testing dashboard.
+## # The following are required to uses Dart and the Cdash dashboard
+##   ENABLE_TESTING()
+##   INCLUDE(CTest)
+set(CTEST_PROJECT_NAME "Eigen 2.0")
+set(CTEST_NIGHTLY_START_TIME "06:00:00 UTC")
+
+set(CTEST_DROP_METHOD "http")
+set(CTEST_DROP_SITE "eigen.tuxfamily.org")
+set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen+2.0")
+set(CTEST_DROP_SITE_CDASH TRUE)

Eigen/Array

@@ -7,7 +7,7 @@
 
 namespace Eigen {
 
-/** \defgroup Array Array module
+/** \defgroup Array_Module Array module
   * This module provides several handy features to manipulate matrices as simple array of values.
   * In addition to listed classes, it defines various methods of the Cwise interface
   * (accessible from MatrixBase::cwise()), including:
@@ -26,7 +26,7 @@ namespace Eigen {
 
 #include "src/Array/CwiseOperators.h"
 #include "src/Array/Functors.h"
-#include "src/Array/AllAndAny.h"
+#include "src/Array/BooleanRedux.h"
 #include "src/Array/Select.h"
 #include "src/Array/PartialRedux.h"
 #include "src/Array/Random.h"

Eigen/CMakeLists.txt

@@ -1,4 +1,6 @@
-set(Eigen_HEADERS Core LU Cholesky QR Geometry Sparse Array SVD Regression LeastSquares)
+set(Eigen_HEADERS Core LU Cholesky QR Geometry
+                  Sparse Array SVD LeastSquares
+                  QtAlignedMalloc StdVector NewStdVector)
 
 if(EIGEN_BUILD_LIB)
     set(Eigen_SRCS
@@ -20,12 +22,6 @@ if(CMAKE_COMPILER_IS_GNUCXX)
     set(CMAKE_CXX_FLAGS_RELWITHDEBINFO "${CMAKE_CXX_FLAGS_RELWITHDEBINFO} -g1 -O2")
 endif(CMAKE_COMPILER_IS_GNUCXX)
 
-set(INCLUDE_INSTALL_DIR
-    "${CMAKE_INSTALL_PREFIX}/include/eigen2"
-    CACHE PATH
-    "The directory where we install the header files"
-    FORCE)
-
 install(FILES
   ${Eigen_HEADERS}
   DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen

Eigen/Cholesky

@@ -17,6 +17,9 @@
 namespace Eigen {
 
 /** \defgroup Cholesky_Module Cholesky module
+  *
+  * \nonstableyet
+  *
   * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices.
   * Those decompositions are accessible via the following MatrixBase methods:
   *  - MatrixBase::llt(),
@@ -31,14 +34,12 @@ namespace Eigen {
 #include "src/Array/Functors.h"
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
-#include "src/Cholesky/Cholesky.h"
-#include "src/Cholesky/CholeskyWithoutSquareRoot.h"
 
 } // namespace Eigen
 
 #define EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(MATRIXTYPE,PREFIX) \
-  PREFIX template class Cholesky<MATRIXTYPE>; \
-  PREFIX template class CholeskyWithoutSquareRoot<MATRIXTYPE>
+  PREFIX template class LLT<MATRIXTYPE>; \
+  PREFIX template class LDLT<MATRIXTYPE>
 
 #define EIGEN_CHOLESKY_MODULE_INSTANTIATE(PREFIX) \
   EIGEN_CHOLESKY_MODULE_INSTANTIATE_TYPE(Matrix2f,PREFIX); \

Eigen/Core

@@ -3,13 +3,14 @@
 
 // first thing Eigen does: prevent MSVC from committing suicide
 #include "src/Core/util/DisableMSVCWarnings.h"
+
 #ifdef _MSC_VER
+  #include <malloc.h> // for _aligned_malloc -- need it regardless of whether vectorization is enabled
   #if (_MSC_VER >= 1500) // 2008 or later
-    // Remember that usage of defined() in a #define is undefined by the standard
-    #ifdef _M_IX86_FP
-      #if _M_IX86_FP >= 2
-        #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
-      #endif
+    // Remember that usage of defined() in a #define is undefined by the standard.
+    // a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP.
+    #if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(_M_X64)
+      #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER
     #endif   
   #endif
 #endif
@@ -57,10 +58,7 @@
 #include <iostream>
 #include <cstring>
 #include <string>
-
-#if defined(EIGEN_SSE2_ON_MSVC_2008_OR_LATER) && defined(EIGEN_VECTORIZE)
-  #include <malloc.h> // for _aligned_malloc
-#endif
+#include <limits>
 
 #if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(EIGEN_NO_EXCEPTIONS)
   #define EIGEN_EXCEPTIONS
@@ -70,6 +68,13 @@
   #include <new>
 #endif
 
+// this needs to be done after all possible windows C header includes and before any Eigen source includes
+// (system C++ includes are supposed to be able to deal with this already):
+// windows.h defines min and max macros which would make Eigen fail to compile.
+#if defined(min) || defined(max)
+#error The preprocessor symbols 'min' or 'max' are defined. If you are compiling on Windows, do #define NOMINMAX to prevent windows.h from defining these symbols.
+#endif
+
 namespace Eigen {
 
 /** \defgroup Core_Module Core module

Eigen/Dense

@@ -0,0 +1,8 @@
+#include "Core"
+#include "Array"
+#include "LU"
+#include "Cholesky"
+#include "QR"
+#include "SVD"
+#include "Geometry"
+#include "LeastSquares"

Eigen/Eigen

@@ -0,0 +1,2 @@
+#include "Dense"
+#include "Sparse"

Eigen/Geometry

@@ -14,7 +14,10 @@
 
 namespace Eigen {
 
-/** \defgroup GeometryModule Geometry module
+/** \defgroup Geometry_Module Geometry module
+  *
+  * \nonstableyet
+  *
   * This module provides support for:
   *  - fixed-size homogeneous transformations
   *  - translation, scaling, 2D and 3D rotations

Eigen/LeastSquares

@@ -5,21 +5,20 @@
 
 #include "src/Core/util/DisableMSVCWarnings.h"
 
-#include "LU"
 #include "QR"
 #include "Geometry"
 
 namespace Eigen {
 
-/** \defgroup Regression_Module Regression module
+/** \defgroup LeastSquares_Module LeastSquares module
   * This module provides linear regression and related features.
   *
   * \code
-  * #include <Eigen/Regression>
+  * #include <Eigen/LeastSquares>
   * \endcode
   */
 
-#include "src/Regression/Regression.h"
+#include "src/LeastSquares/LeastSquares.h"
 
 } // namespace Eigen
 

Eigen/NewStdVector

@@ -0,0 +1,168 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
+//
+// 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_STDVECTOR_MODULE_H
+#define EIGEN_STDVECTOR_MODULE_H
+
+#include "Core"
+#include <vector>
+
+namespace Eigen {
+
+// This one is needed to prevent reimplementing the whole std::vector.
+template <class T>
+class aligned_allocator_indirection : public aligned_allocator<T>
+{
+public:
+  typedef size_t    size_type;
+  typedef ptrdiff_t difference_type;
+  typedef T*        pointer;
+  typedef const T*  const_pointer;
+  typedef T&        reference;
+  typedef const T&  const_reference;
+  typedef T         value_type;
+
+  template<class U>
+  struct rebind
+  {
+    typedef aligned_allocator_indirection<U> other;
+  };
+
+  aligned_allocator_indirection() throw() {}
+  aligned_allocator_indirection(const aligned_allocator_indirection& ) throw() : aligned_allocator<T>() {}
+  aligned_allocator_indirection(const aligned_allocator<T>& ) throw() {}
+  template<class U>
+  aligned_allocator_indirection(const aligned_allocator_indirection<U>& ) throw() {}
+  template<class U>
+  aligned_allocator_indirection(const aligned_allocator<U>& ) throw() {}
+  ~aligned_allocator_indirection() throw() {}
+};
+
+#ifdef _MSC_VER
+
+  // sometimes, MSVC detects, at compile time, that the argument x
+  // in std::vector::resize(size_t s,T x) won't be aligned and generate an error
+  // even if this function is never called. Whence this little wrapper.
+  #define EIGEN_WORKAROUND_MSVC_STD_VECTOR(T) Eigen::ei_workaround_msvc_std_vector<T>
+  template<typename T> struct ei_workaround_msvc_std_vector : public T
+  {
+    inline ei_workaround_msvc_std_vector() : T() {}
+    inline ei_workaround_msvc_std_vector(const T& other) : T(other) {}
+    inline operator T& () { return *static_cast<T*>(this); }
+    inline operator const T& () const { return *static_cast<const T*>(this); }
+    template<typename OtherT>
+    inline T& operator=(const OtherT& other)
+    { T::operator=(other); return *this; }
+    inline ei_workaround_msvc_std_vector& operator=(const ei_workaround_msvc_std_vector& other)
+    { T::operator=(other); return *this; }
+  };
+
+#else
+
+  #define EIGEN_WORKAROUND_MSVC_STD_VECTOR(T) T
+
+#endif
+
+}
+
+namespace std {
+
+#define EIGEN_STD_VECTOR_SPECIALIZATION_BODY \
+  public:  \
+    typedef T value_type; \
+    typedef typename vector_base::allocator_type allocator_type; \
+    typedef typename vector_base::size_type size_type;  \
+    typedef typename vector_base::iterator iterator;  \
+    typedef typename vector_base::const_iterator const_iterator;  \
+    explicit vector(const allocator_type& a = allocator_type()) : vector_base(a) {}  \
+    template<typename InputIterator> \
+    vector(InputIterator first, InputIterator last, const allocator_type& a = allocator_type()) \
+    : vector_base(first, last, a) {} \
+    vector(const vector& c) : vector_base(c) {}  \
+    explicit vector(size_type num, const value_type& val = value_type()) : vector_base(num, val) {} \
+    vector(iterator start, iterator end) : vector_base(start, end) {}  \
+    vector& operator=(const vector& x) {  \
+      vector_base::operator=(x);  \
+      return *this;  \
+    }
+
+template<typename T>
+class vector<T,Eigen::aligned_allocator<T> >
+  : public vector<EIGEN_WORKAROUND_MSVC_STD_VECTOR(T),
+                  Eigen::aligned_allocator_indirection<EIGEN_WORKAROUND_MSVC_STD_VECTOR(T)> >
+{
+  typedef vector<EIGEN_WORKAROUND_MSVC_STD_VECTOR(T),
+                 Eigen::aligned_allocator_indirection<EIGEN_WORKAROUND_MSVC_STD_VECTOR(T)> > vector_base;
+  EIGEN_STD_VECTOR_SPECIALIZATION_BODY
+
+  void resize(size_type new_size)
+  { resize(new_size, T()); }
+
+#if defined(_VECTOR_)
+  // workaround MSVC std::vector implementation
+  void resize(size_type new_size, const value_type& x)
+  {
+    if (vector_base::size() < new_size)
+      vector_base::_Insert_n(vector_base::end(), new_size - vector_base::size(), x);
+    else if (new_size < vector_base::size())
+      vector_base::erase(vector_base::begin() + new_size, vector_base::end());
+  }
+  void push_back(const value_type& x)
+  { vector_base::push_back(x); } 
+  using vector_base::insert;  
+  iterator insert(const_iterator position, const value_type& x)
+  { return vector_base::insert(position,x); }
+  void insert(const_iterator position, size_type new_size, const value_type& x)
+  { vector_base::insert(position, new_size, x); }
+#elif defined(_GLIBCXX_VECTOR) && EIGEN_GNUC_AT_LEAST(4,2)
+  // workaround GCC std::vector implementation
+  void resize(size_type new_size, const value_type& x)
+  {
+    if (new_size < vector_base::size())
+      vector_base::_M_erase_at_end(this->_M_impl._M_start + new_size);
+    else
+      vector_base::insert(vector_base::end(), new_size - vector_base::size(), x);
+  }
+#elif defined(_GLIBCXX_VECTOR) && (!EIGEN_GNUC_AT_LEAST(4,1))
+  // Note that before gcc-4.1 we already have: std::vector::resize(size_type,const T&),
+  // no no need to workaround !
+  using vector_base::resize;
+#else
+  // either GCC 4.1 or non-GCC
+  // default implementation which should always work.
+  void resize(size_type new_size, const value_type& x)
+  {
+    if (new_size < vector_base::size())
+      vector_base::erase(vector_base::begin() + new_size, vector_base::end());
+    else if (new_size > vector_base::size())
+      vector_base::insert(vector_base::end(), new_size - vector_base::size(), x);
+  }
+#endif
+
+};
+
+}
+
+#endif // EIGEN_STDVECTOR_MODULE_H

Eigen/QR

@@ -19,6 +19,9 @@
 namespace Eigen {
 
 /** \defgroup QR_Module QR module
+  *
+  * \nonstableyet
+  *
   * This module mainly provides QR decomposition and an eigen value solver.
   * This module also provides some MatrixBase methods, including:
   *  - MatrixBase::qr(),

Eigen/QtAlignedMalloc

@@ -0,0 +1,49 @@
+#ifndef EIGEN_QTMALLOC_MODULE_H
+#define EIGEN_QTMALLOC_MODULE_H
+
+#if (!EIGEN_MALLOC_ALREADY_ALIGNED)
+
+#ifdef QVECTOR_H
+#error You must include <Eigen/QtAlignedMalloc> before <QtCore/QVector>.
+#endif                                           
+
+#ifdef Q_DECL_IMPORT
+  #define Q_DECL_IMPORT_ORIG Q_DECL_IMPORT
+  #undef Q_DECL_IMPORT
+  #define Q_DECL_IMPORT
+#else
+  #define Q_DECL_IMPORT
+#endif
+
+#include "Core"
+
+#include <QtCore/QVector>
+
+inline void *qMalloc(size_t size)
+{
+  return Eigen::ei_aligned_malloc(size);
+}
+
+inline void qFree(void *ptr)
+{
+  Eigen::ei_aligned_free(ptr);
+}
+
+inline void *qRealloc(void *ptr, size_t size)
+{
+  void* newPtr = Eigen::ei_aligned_malloc(size);
+  memcpy(newPtr, ptr, size);
+  Eigen::ei_aligned_free(ptr);
+  return newPtr;
+}
+
+#endif
+
+#ifdef Q_DECL_IMPORT_ORIG
+  #define Q_DECL_IMPORT Q_DECL_IMPORT_ORIG
+  #undef Q_DECL_IMPORT_ORIG
+#else
+  #undef Q_DECL_IMPORT
+#endif
+
+#endif // EIGEN_QTMALLOC_MODULE_H

Eigen/Regression

@@ -1,5 +0,0 @@
-#ifdef __GNUC__
-#warning "The Eigen/Regression header file has been renamed to Eigen/LeastSquares. The old name is deprecated, please update your code."
-#endif
-
-#include "LeastSquares"

Eigen/SVD

@@ -8,6 +8,9 @@
 namespace Eigen {
 
 /** \defgroup SVD_Module SVD module
+  *
+  * \nonstableyet
+  *
   * This module provides SVD decomposition for (currently) real matrices.
   * This decomposition is accessible via the following MatrixBase method:
   *  - MatrixBase::svd()

Eigen/Sparse

@@ -22,7 +22,6 @@
 #endif
 
 #ifdef EIGEN_TAUCS_SUPPORT
-
   // taucs.h declares a lot of mess
   #define isnan
   #define finite
@@ -40,7 +39,9 @@
   #ifdef max
     #undef max
   #endif
-
+  #ifdef complex
+    #undef complex
+  #endif
 #endif
 
 #ifdef EIGEN_SUPERLU_SUPPORT
@@ -70,16 +71,39 @@
 
 namespace Eigen {
 
+/** \defgroup Sparse_Module Sparse module
+  *
+  * \nonstableyet
+  *
+  * See the \ref TutorialSparse "Sparse tutorial"
+  *
+  * \code
+  * #include <Eigen/QR>
+  * \endcode
+  */
+
 #include "src/Sparse/SparseUtil.h"
 #include "src/Sparse/SparseMatrixBase.h"
-#include "src/Sparse/SparseArray.h"
+#include "src/Sparse/CompressedStorage.h"
 #include "src/Sparse/AmbiVector.h"
 #include "src/Sparse/RandomSetter.h"
 #include "src/Sparse/SparseBlock.h"
 #include "src/Sparse/SparseMatrix.h"
+#include "src/Sparse/DynamicSparseMatrix.h"
+#include "src/Sparse/MappedSparseMatrix.h"
 #include "src/Sparse/SparseVector.h"
 #include "src/Sparse/CoreIterators.h"
+#include "src/Sparse/SparseTranspose.h"
+#include "src/Sparse/SparseCwise.h"
+#include "src/Sparse/SparseCwiseUnaryOp.h"
+#include "src/Sparse/SparseCwiseBinaryOp.h"
+#include "src/Sparse/SparseDot.h"
+#include "src/Sparse/SparseAssign.h"
+#include "src/Sparse/SparseRedux.h"
+#include "src/Sparse/SparseFuzzy.h"
+#include "src/Sparse/SparseFlagged.h"
 #include "src/Sparse/SparseProduct.h"
+#include "src/Sparse/SparseDiagonalProduct.h"
 #include "src/Sparse/TriangularSolver.h"
 #include "src/Sparse/SparseLLT.h"
 #include "src/Sparse/SparseLDLT.h"

Eigen/StdVector

@@ -0,0 +1,147 @@
+#ifdef EIGEN_USE_NEW_STDVECTOR
+#include "NewStdVector"
+#else
+
+#ifndef EIGEN_STDVECTOR_MODULE_H
+#define EIGEN_STDVECTOR_MODULE_H
+
+#if defined(_GLIBCXX_VECTOR) || defined(_VECTOR_)
+#error you must include <Eigen/StdVector> before <vector>. Also note that <Eigen/Sparse> includes <vector>, so it must be included after <Eigen/StdVector> too.
+#endif                                                    
+
+#ifndef EIGEN_GNUC_AT_LEAST
+#ifdef __GNUC__
+  #define EIGEN_GNUC_AT_LEAST(x,y) ((__GNUC__>=x && __GNUC_MINOR__>=y) || __GNUC__>x)
+#else
+  #define EIGEN_GNUC_AT_LEAST(x,y) 0
+#endif
+#endif
+
+#define vector std_vector
+#include <vector>        
+#undef vector
+
+namespace Eigen {
+
+template<typename T> class aligned_allocator;
+
+// meta programming to determine if a class has a given member
+struct ei_does_not_have_aligned_operator_new_marker_sizeof {int a[1];};
+struct ei_has_aligned_operator_new_marker_sizeof {int a[2];};
+
+template<typename ClassType>
+struct ei_has_aligned_operator_new {
+    template<typename T>
+    static ei_has_aligned_operator_new_marker_sizeof
+    test(T const *, typename T::ei_operator_new_marker_type const * = 0);
+    static ei_does_not_have_aligned_operator_new_marker_sizeof
+    test(...);
+
+    // note that the following indirection is needed for gcc-3.3
+    enum {ret =  sizeof(test(static_cast<ClassType*>(0))) 
+              == sizeof(ei_has_aligned_operator_new_marker_sizeof) };
+};
+
+#ifdef _MSC_VER
+  
+  // sometimes, MSVC detects, at compile time, that the argument x
+  // in std::vector::resize(size_t s,T x) won't be aligned and generate an error
+  // even if this function is never called. Whence this little wrapper.
+  #define _EIGEN_WORKAROUND_MSVC_STD_VECTOR(T) Eigen::ei_workaround_msvc_std_vector<T>
+  template<typename T> struct ei_workaround_msvc_std_vector : public T
+  {
+    inline ei_workaround_msvc_std_vector() : T() {}
+    inline ei_workaround_msvc_std_vector(const T& other) : T(other) {}
+    inline operator T& () { return *static_cast<T*>(this); }
+    inline operator const T& () const { return *static_cast<const T*>(this); }
+    template<typename OtherT>
+    inline T& operator=(const OtherT& other)
+    { T::operator=(other); return *this; }
+    inline ei_workaround_msvc_std_vector& operator=(const ei_workaround_msvc_std_vector& other)
+    { T::operator=(other); return *this; }
+  };
+
+#else
+
+  #define _EIGEN_WORKAROUND_MSVC_STD_VECTOR(T) T
+
+#endif
+
+}
+
+namespace std {
+
+#define EIGEN_STD_VECTOR_SPECIALIZATION_BODY \
+  public:  \
+    typedef T value_type; \
+    typedef typename vector_base::allocator_type allocator_type; \
+    typedef typename vector_base::size_type size_type;  \
+    typedef typename vector_base::iterator iterator;  \
+    explicit vector(const allocator_type& __a = allocator_type()) : vector_base(__a) {}  \
+    vector(const vector& c) : vector_base(c) {}  \
+    vector(size_type num, const value_type& val = value_type()) : vector_base(num, val) {} \
+    vector(iterator start, iterator end) : vector_base(start, end) {}  \
+    vector& operator=(const vector& __x) {  \
+      vector_base::operator=(__x);  \
+      return *this;  \
+    }
+
+template<typename T,
+         typename AllocT = std::allocator<T>,
+         bool HasAlignedNew = Eigen::ei_has_aligned_operator_new<T>::ret>
+class vector : public std::std_vector<T,AllocT>
+{
+  typedef std_vector<T, AllocT> vector_base;
+  EIGEN_STD_VECTOR_SPECIALIZATION_BODY
+};
+
+template<typename T,typename DummyAlloc>
+class vector<T,DummyAlloc,true>
+  : public std::std_vector<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T),
+                           Eigen::aligned_allocator<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T)> >          
+{
+  typedef std_vector<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T),
+                     Eigen::aligned_allocator<_EIGEN_WORKAROUND_MSVC_STD_VECTOR(T)> > vector_base;
+  EIGEN_STD_VECTOR_SPECIALIZATION_BODY
+
+  void resize(size_type __new_size)
+  { resize(__new_size, T()); }     
+
+  #if defined(_VECTOR_)
+  // workaround MSVC std::vector implementation
+  void resize(size_type __new_size, const value_type& __x)                 
+  {                                                              
+    if (vector_base::size() < __new_size)                                 
+      vector_base::_Insert_n(vector_base::end(), __new_size - vector_base::size(), __x);
+    else if (__new_size < vector_base::size())
+      vector_base::erase(vector_base::begin() + __new_size, vector_base::end());
+  }
+  #elif defined(_GLIBCXX_VECTOR) && EIGEN_GNUC_AT_LEAST(4,2)
+  // workaround GCC std::vector implementation
+  void resize(size_type __new_size, const value_type& __x)
+  {                                              
+    if (__new_size < vector_base::size())               
+      vector_base::_M_erase_at_end(this->_M_impl._M_start + __new_size);
+    else                       
+      vector_base::insert(vector_base::end(), __new_size - vector_base::size(), __x); 
+  }                                                              
+  #elif defined(_GLIBCXX_VECTOR) && EIGEN_GNUC_AT_LEAST(4,1)
+  void resize(size_type __new_size, const value_type& __x)
+  {
+    if (__new_size < vector_base::size())
+      vector_base::erase(vector_base::begin() + __new_size, vector_base::end());
+    else
+      vector_base::insert(vector_base::end(), __new_size - vector_base::size(), __x);
+  }
+  #else
+  // Before gcc-4.1 we already have: std::vector::resize(size_type,const T&),
+  // so no need for a workaround !
+  using vector_base::resize;
+  #endif  
+};
+
+}
+
+#endif // EIGEN_STDVECTOR_MODULE_H
+
+#endif // EIGEN_USE_NEW_STDVECTOR

Eigen/src/Array/BooleanRedux.h

@@ -89,7 +89,7 @@ struct ei_any_unroller<Derived, Dynamic>
   * \sa MatrixBase::any(), Cwise::operator<()
   */
 template<typename Derived>
-inline bool MatrixBase<Derived>::all(void) const
+inline bool MatrixBase<Derived>::all() const
 {
   const bool unroll = SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost)
                       <= EIGEN_UNROLLING_LIMIT;
@@ -113,7 +113,7 @@ inline bool MatrixBase<Derived>::all(void) const
   * \sa MatrixBase::all()
   */
 template<typename Derived>
-inline bool MatrixBase<Derived>::any(void) const
+inline bool MatrixBase<Derived>::any() const
 {
   const bool unroll = SizeAtCompileTime * (CoeffReadCost + NumTraits<Scalar>::AddCost)
                       <= EIGEN_UNROLLING_LIMIT;
@@ -130,4 +130,16 @@ inline bool MatrixBase<Derived>::any(void) const
   }
 }
 
+/** \array_module
+  * 
+  * \returns the number of coefficients which evaluate to true
+  *
+  * \sa MatrixBase::all(), MatrixBase::any()
+  */
+template<typename Derived>
+inline int MatrixBase<Derived>::count() const
+{
+  return this->cast<bool>().cast<int>().sum();
+}
+
 #endif // EIGEN_ALLANDANY_H

Eigen/src/Array/Functors.h

@@ -43,6 +43,8 @@ struct ei_scalar_add_op {
   inline const PacketScalar packetOp(const PacketScalar& a) const
   { return ei_padd(a, ei_pset1(m_other)); }
   const Scalar m_other;
+private:
+  ei_scalar_add_op& operator=(const ei_scalar_add_op&);
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_add_op<Scalar> >
@@ -138,6 +140,8 @@ struct ei_scalar_pow_op {
   inline ei_scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {}
   inline Scalar operator() (const Scalar& a) const { return ei_pow(a, m_exponent); }
   const Scalar m_exponent;
+private:
+  ei_scalar_pow_op& operator=(const ei_scalar_pow_op&);
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_pow_op<Scalar> >
@@ -200,7 +204,6 @@ template<typename Scalar>
 struct ei_functor_traits<ei_scalar_cube_op<Scalar> >
 { enum { Cost = 2*NumTraits<Scalar>::MulCost, PacketAccess = int(ei_packet_traits<Scalar>::size)>1 }; };
 
-
 // default ei_functor_traits for STL functors:
 
 template<typename T>

Eigen/src/Array/PartialRedux.h

@@ -61,7 +61,11 @@ struct ei_traits<PartialReduxExpr<MatrixType, MemberOp, Direction> >
     Flags = (unsigned int)_MatrixTypeNested::Flags & HereditaryBits,
     TraversalSize = Direction==Vertical ? RowsAtCompileTime : ColsAtCompileTime
   };
+  #if EIGEN_GNUC_AT_LEAST(3,4)
   typedef typename MemberOp::template Cost<InputScalar,int(TraversalSize)> CostOpType;
+  #else
+  typedef typename MemberOp::template Cost<InputScalar,TraversalSize> CostOpType;
+  #endif
   enum {
     CoeffReadCost = TraversalSize * ei_traits<_MatrixTypeNested>::CoeffReadCost + int(CostOpType::value)
   };
@@ -104,7 +108,7 @@ class PartialReduxExpr : ei_no_assignment_operator,
     { enum { value = COST }; };                                     \
     template<typename Derived>                                      \
     inline ResultType operator()(const MatrixBase<Derived>& mat) const     \
-    { return mat.MEMBER(); }                                        \
+    { return mat.MEMBER(); } \
   }
 
 EIGEN_MEMBER_FUNCTOR(squaredNorm, Size * NumTraits<Scalar>::MulCost + (Size-1)*NumTraits<Scalar>::AddCost);
@@ -114,6 +118,7 @@ EIGEN_MEMBER_FUNCTOR(minCoeff, (Size-1)*NumTraits<Scalar>::AddCost);
 EIGEN_MEMBER_FUNCTOR(maxCoeff, (Size-1)*NumTraits<Scalar>::AddCost);
 EIGEN_MEMBER_FUNCTOR(all, (Size-1)*NumTraits<Scalar>::AddCost);
 EIGEN_MEMBER_FUNCTOR(any, (Size-1)*NumTraits<Scalar>::AddCost);
+EIGEN_MEMBER_FUNCTOR(count, (Size-1)*NumTraits<Scalar>::AddCost);
 
 /** \internal */
 template <typename BinaryOp, typename Scalar>
@@ -128,6 +133,8 @@ struct ei_member_redux {
   inline result_type operator()(const MatrixBase<Derived>& mat) const
   { return mat.redux(m_functor); }
   const BinaryOp m_functor;
+private:
+  ei_member_redux& operator=(const ei_member_redux&);
 };
 
 /** \array_module \ingroup Array
@@ -173,7 +180,7 @@ template<typename ExpressionType, int Direction> class PartialRedux
     };
 
     typedef typename ExpressionType::PlainMatrixType CrossReturnType;
-
+    
     inline PartialRedux(const ExpressionType& matrix) : m_matrix(matrix) {}
 
     /** \internal */
@@ -246,6 +253,16 @@ template<typename ExpressionType, int Direction> class PartialRedux
       * \sa MatrixBase::any() */
     const typename ReturnType<ei_member_any>::Type any() const
     { return _expression(); }
+    
+    /** \returns a row (or column) vector expression representing
+      * the number of \c true coefficients of each respective column (or row).
+      *
+      * Example: \include PartialRedux_count.cpp
+      * Output: \verbinclude PartialRedux_count.out
+      *
+      * \sa MatrixBase::count() */
+    const PartialReduxExpr<ExpressionType, ei_member_count<int>, Direction> count() const
+    { return _expression(); }
 
     /** \returns a 3x3 matrix expression of the cross product
       * of each column or row of the referenced expression with the \a other vector.
@@ -275,6 +292,9 @@ template<typename ExpressionType, int Direction> class PartialRedux
 
   protected:
     ExpressionTypeNested m_matrix;
+
+  private:
+    PartialRedux& operator=(const PartialRedux&);
 };
 
 /** \array_module

Eigen/src/Array/Random.h

@@ -110,7 +110,7 @@ MatrixBase<Derived>::Random()
   * Example: \include MatrixBase_setRandom.cpp
   * Output: \verbinclude MatrixBase_setRandom.out
   *
-  * \sa class CwiseNullaryOp, MatrixBase::setRandom(int,int)
+  * \sa class CwiseNullaryOp, setRandom(int), setRandom(int,int)
   */
 template<typename Derived>
 inline Derived& MatrixBase<Derived>::setRandom()
@@ -118,4 +118,39 @@ inline Derived& MatrixBase<Derived>::setRandom()
   return *this = Random(rows(), cols());
 }
 
+/** Resizes to the given \a size, and sets all coefficients in this expression to random values.
+  *
+  * \only_for_vectors
+  *
+  * Example: \include Matrix_setRandom_int.cpp
+  * Output: \verbinclude Matrix_setRandom_int.out
+  *
+  * \sa MatrixBase::setRandom(), setRandom(int,int), class CwiseNullaryOp, MatrixBase::Random()
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setRandom(int size)
+{
+  resize(size);
+  return setRandom();
+}
+
+/** Resizes to the given size, and sets all coefficients in this expression to random values.
+  *
+  * \param rows the new number of rows
+  * \param cols the new number of columns
+  *
+  * Example: \include Matrix_setRandom_int_int.cpp
+  * Output: \verbinclude Matrix_setRandom_int_int.out
+  *
+  * \sa MatrixBase::setRandom(), setRandom(int), class CwiseNullaryOp, MatrixBase::Random()
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setRandom(int rows, int cols)
+{
+  resize(rows, cols);
+  return setRandom();
+}
+
 #endif // EIGEN_RANDOM_H

Eigen/src/Array/Select.h

@@ -45,15 +45,18 @@ template<typename ConditionMatrixType, typename ThenMatrixType, typename ElseMat
 struct ei_traits<Select<ConditionMatrixType, ThenMatrixType, ElseMatrixType> >
 {
   typedef typename ei_traits<ThenMatrixType>::Scalar Scalar;
+  typedef typename ConditionMatrixType::Nested ConditionMatrixNested;
+  typedef typename ThenMatrixType::Nested ThenMatrixNested;
+  typedef typename ElseMatrixType::Nested ElseMatrixNested;
   enum {
     RowsAtCompileTime = ConditionMatrixType::RowsAtCompileTime,
     ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime,
     MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime,
     MaxColsAtCompileTime = ConditionMatrixType::MaxColsAtCompileTime,
     Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & HereditaryBits,
-    CoeffReadCost = ei_traits<ConditionMatrixType>::CoeffReadCost
-                  + EIGEN_ENUM_MAX(ei_traits<ThenMatrixType>::CoeffReadCost,
-                                   ei_traits<ElseMatrixType>::CoeffReadCost)
+	CoeffReadCost = ei_traits<typename ei_cleantype<ConditionMatrixNested>::type>::CoeffReadCost
+	+ EIGEN_ENUM_MAX(ei_traits<typename ei_cleantype<ThenMatrixNested>::type>::CoeffReadCost,
+	                 ei_traits<typename ei_cleantype<ElseMatrixNested>::type>::CoeffReadCost)
   };
 };
 
@@ -105,6 +108,9 @@ class Select : ei_no_assignment_operator,
   * \returns a matrix where each coefficient (i,j) is equal to \a thenMatrix(i,j)
   * if \c *this(i,j), and \a elseMatrix(i,j) otherwise.
   *
+  * Example: \include MatrixBase_select.cpp
+  * Output: \verbinclude MatrixBase_select.out
+  *
   * \sa class Select
   */
 template<typename Derived>

Eigen/src/CMakeLists.txt

@@ -5,5 +5,5 @@ ADD_SUBDIRECTORY(SVD)
 ADD_SUBDIRECTORY(Cholesky)
 ADD_SUBDIRECTORY(Array)
 ADD_SUBDIRECTORY(Geometry)
-ADD_SUBDIRECTORY(Regression)
+ADD_SUBDIRECTORY(LeastSquares)
 ADD_SUBDIRECTORY(Sparse)

Eigen/src/Cholesky/Cholesky.h

@@ -1,165 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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_CHOLESKY_H
-#define EIGEN_CHOLESKY_H
-
-/** \ingroup Cholesky_Module
-  *
-  * \class Cholesky
-  *
-  * \deprecated this class has been renamed LLT
-  */
-template<typename MatrixType> class Cholesky
-{
-  private:
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
-
-    enum {
-      PacketSize = ei_packet_traits<Scalar>::size,
-      AlignmentMask = int(PacketSize)-1
-    };
-
-  public:
-
-    Cholesky(const MatrixType& matrix)
-      : m_matrix(matrix.rows(), matrix.cols())
-    {
-      compute(matrix);
-    }
-
-		/** \deprecated */
-    inline Part<MatrixType, LowerTriangular> matrixL(void) const { return m_matrix; }
-
-    /** \deprecated */
-    inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
-
-    template<typename Derived>
-    EIGEN_DEPRECATED typename MatrixBase<Derived>::PlainMatrixType_ColMajor solve(const MatrixBase<Derived> &b) const;
-
-    template<typename RhsDerived, typename ResDerived>
-    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
-
-    template<typename Derived>
-    bool solveInPlace(MatrixBase<Derived> &bAndX) const;
-
-    void compute(const MatrixType& matrix);
-
-  protected:
-    /** \internal
-      * Used to compute and store L
-      * The strict upper part is not used and even not initialized.
-      */
-    MatrixType m_matrix;
-    bool m_isPositiveDefinite;
-};
-
-/** \deprecated */
-template<typename MatrixType>
-void Cholesky<MatrixType>::compute(const MatrixType& a)
-{
-  assert(a.rows()==a.cols());
-  const int size = a.rows();
-  m_matrix.resize(size, size);
-  const RealScalar eps = ei_sqrt(precision<Scalar>());
-
-  RealScalar x;
-  x = ei_real(a.coeff(0,0));
-  m_isPositiveDefinite = x > eps && ei_isMuchSmallerThan(ei_imag(a.coeff(0,0)), RealScalar(1));
-  m_matrix.coeffRef(0,0) = ei_sqrt(x);
-  m_matrix.col(0).end(size-1) = a.row(0).end(size-1).adjoint() / ei_real(m_matrix.coeff(0,0));
-  for (int j = 1; j < size; ++j)
-  {
-    Scalar tmp = ei_real(a.coeff(j,j)) - m_matrix.row(j).start(j).squaredNorm();
-    x = ei_real(tmp);
-    if (x < eps || (!ei_isMuchSmallerThan(ei_imag(tmp), RealScalar(1))))
-    {
-      m_isPositiveDefinite = false;
-      return;
-    }
-    m_matrix.coeffRef(j,j) = x = ei_sqrt(x);
-
-    int endSize = size-j-1;
-    if (endSize>0) {
-      // Note that when all matrix columns have good alignment, then the following
-      // product is guaranteed to be optimal with respect to alignment.
-      m_matrix.col(j).end(endSize) =
-        (m_matrix.block(j+1, 0, endSize, j) * m_matrix.row(j).start(j).adjoint()).lazy();
-
-      // FIXME could use a.col instead of a.row
-      m_matrix.col(j).end(endSize) = (a.row(j).end(endSize).adjoint()
-        - m_matrix.col(j).end(endSize) ) / x;
-    }
-  }
-}
-
-/** \deprecated */
-template<typename MatrixType>
-template<typename Derived>
-typename MatrixBase<Derived>::PlainMatrixType_ColMajor Cholesky<MatrixType>::solve(const MatrixBase<Derived> &b) const
-{
-  const int size = m_matrix.rows();
-  ei_assert(size==b.rows());
-  typename MatrixBase<Derived>::PlainMatrixType_ColMajor x(b);
-  solveInPlace(x);
-  return x;
-}
-
-/** \deprecated */
-template<typename MatrixType>
-template<typename RhsDerived, typename ResDerived>
-bool Cholesky<MatrixType>::solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const
-{
-  const int size = m_matrix.rows();
-  ei_assert(size==b.rows() && "Cholesky::solve(): invalid number of rows of the right hand side matrix b");
-  return solveInPlace((*result) = b);
-}
-
-/** \deprecated */
-template<typename MatrixType>
-template<typename Derived>
-bool Cholesky<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
-{
-  const int size = m_matrix.rows();
-  ei_assert(size==bAndX.rows());
-  if (!m_isPositiveDefinite)
-    return false;
-  matrixL().solveTriangularInPlace(bAndX);
-  m_matrix.adjoint().template part<UpperTriangular>().solveTriangularInPlace(bAndX);
-  return true;
-}
-
-/** \cholesky_module
-  * \deprecated has been renamed llt()
-  */
-template<typename Derived>
-inline const Cholesky<typename MatrixBase<Derived>::PlainMatrixType>
-MatrixBase<Derived>::cholesky() const
-{
-  return Cholesky<PlainMatrixType>(derived());
-}
-
-#endif // EIGEN_CHOLESKY_H

Eigen/src/Cholesky/CholeskyWithoutSquareRoot.h

@@ -1,184 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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_CHOLESKY_WITHOUT_SQUARE_ROOT_H
-#define EIGEN_CHOLESKY_WITHOUT_SQUARE_ROOT_H
-
-/** \deprecated \ingroup Cholesky_Module
-  *
-  * \class CholeskyWithoutSquareRoot
-  *
-  * \deprecated this class has been renamed LDLT
-  */
-template<typename MatrixType> class CholeskyWithoutSquareRoot
-{
-  public:
-
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar;
-    typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
-
-    CholeskyWithoutSquareRoot(const MatrixType& matrix)
-      : m_matrix(matrix.rows(), matrix.cols())
-    {
-      compute(matrix);
-    }
-
-    /** \returns the lower triangular matrix L */
-    inline Part<MatrixType, UnitLowerTriangular> matrixL(void) const { return m_matrix; }
-
-    /** \returns the coefficients of the diagonal matrix D */
-    inline DiagonalCoeffs<MatrixType> vectorD(void) const { return m_matrix.diagonal(); }
-
-    /** \returns true if the matrix is positive definite */
-    inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
-
-    template<typename Derived>
-    EIGEN_DEPRECATED typename Derived::Eval solve(const MatrixBase<Derived> &b) const;
-
-    template<typename RhsDerived, typename ResDerived>
-    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
-
-		template<typename Derived>
-    bool solveInPlace(MatrixBase<Derived> &bAndX) const;
-
-    void compute(const MatrixType& matrix);
-
-  protected:
-    /** \internal
-      * Used to compute and store the cholesky decomposition A = L D L^* = U^* D U.
-      * The strict upper part is used during the decomposition, the strict lower
-      * part correspond to the coefficients of L (its diagonal is equal to 1 and
-      * is not stored), and the diagonal entries correspond to D.
-      */
-    MatrixType m_matrix;
-
-    bool m_isPositiveDefinite;
-};
-
-/** \deprecated */
-template<typename MatrixType>
-void CholeskyWithoutSquareRoot<MatrixType>::compute(const MatrixType& a)
-{
-  assert(a.rows()==a.cols());
-  const int size = a.rows();
-  m_matrix.resize(size, size);
-  m_isPositiveDefinite = true;
-  const RealScalar eps = ei_sqrt(precision<Scalar>());
-
-  if (size<=1)
-  {
-    m_matrix = a;
-    return;
-  }
-
-  // Let's preallocate a temporay vector to evaluate the matrix-vector product into it.
-  // Unlike the standard Cholesky decomposition, here we cannot evaluate it to the destination
-  // matrix because it a sub-row which is not compatible suitable for efficient packet evaluation.
-  // (at least if we assume the matrix is col-major)
-  Matrix<Scalar,MatrixType::RowsAtCompileTime,1> _temporary(size);
-
-  // Note that, in this algorithm the rows of the strict upper part of m_matrix is used to store
-  // column vector, thus the strange .conjugate() and .transpose()...
-
-  m_matrix.row(0) = a.row(0).conjugate();
-  m_matrix.col(0).end(size-1) = m_matrix.row(0).end(size-1) / m_matrix.coeff(0,0);
-  for (int j = 1; j < size; ++j)
-  {
-    RealScalar tmp = ei_real(a.coeff(j,j) - (m_matrix.row(j).start(j) * m_matrix.col(j).start(j).conjugate()).coeff(0,0));
-    m_matrix.coeffRef(j,j) = tmp;
-
-    if (tmp < eps)
-    {
-      m_isPositiveDefinite = false;
-      return;
-    }
-
-    int endSize = size-j-1;
-    if (endSize>0)
-    {
-      _temporary.end(endSize) = ( m_matrix.block(j+1,0, endSize, j)
-                                  * m_matrix.col(j).start(j).conjugate() ).lazy();
-
-      m_matrix.row(j).end(endSize) = a.row(j).end(endSize).conjugate()
-                                   - _temporary.end(endSize).transpose();
-
-      m_matrix.col(j).end(endSize) = m_matrix.row(j).end(endSize) / tmp;
-    }
-  }
-}
-
-/** \deprecated */
-template<typename MatrixType>
-template<typename Derived>
-typename Derived::Eval CholeskyWithoutSquareRoot<MatrixType>::solve(const MatrixBase<Derived> &b) const
-{
-  const int size = m_matrix.rows();
-  ei_assert(size==b.rows());
-
-  return m_matrix.adjoint().template part<UnitUpperTriangular>()
-    .solveTriangular(
-      (  m_matrix.cwise().inverse().template part<Diagonal>()
-       * matrixL().solveTriangular(b))
-     );
-}
-
-/** \deprecated */
-template<typename MatrixType>
-template<typename RhsDerived, typename ResDerived>
-bool CholeskyWithoutSquareRoot<MatrixType>
-::solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const
-{
-  const int size = m_matrix.rows();
-  ei_assert(size==b.rows() && "Cholesky::solve(): invalid number of rows of the right hand side matrix b");
-  *result = b;
-  return solveInPlace(*result);
-}
-
-/** \deprecated */
-template<typename MatrixType>
-template<typename Derived>
-bool CholeskyWithoutSquareRoot<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
-{
-  const int size = m_matrix.rows();
-  ei_assert(size==bAndX.rows());
-  if (!m_isPositiveDefinite)
-    return false;
-  matrixL().solveTriangularInPlace(bAndX);
-  bAndX = (m_matrix.cwise().inverse().template part<Diagonal>() * bAndX).lazy();
-  m_matrix.adjoint().template part<UnitUpperTriangular>().solveTriangularInPlace(bAndX);
-  return true;
-}
-
-/** \cholesky_module
-  * \deprecated has been renamed ldlt()
-  */
-template<typename Derived>
-inline const CholeskyWithoutSquareRoot<typename MatrixBase<Derived>::PlainMatrixType>
-MatrixBase<Derived>::choleskyNoSqrt() const
-{
-  return derived();
-}
-
-#endif // EIGEN_CHOLESKY_WITHOUT_SQUARE_ROOT_H

Eigen/src/Cholesky/LDLT.h

@@ -68,8 +68,8 @@ template<typename MatrixType> class LDLT
     /** \returns true if the matrix is positive definite */
     inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
 
-    template<typename RhsDerived, typename ResDerived>
-    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
+    template<typename RhsDerived, typename ResultType>
+    bool solve(const MatrixBase<RhsDerived> &b, ResultType *result) const;
 
     template<typename Derived>
     bool solveInPlace(MatrixBase<Derived> &bAndX) const;
@@ -152,9 +152,9 @@ void LDLT<MatrixType>::compute(const MatrixType& a)
   * \sa LDLT::solveInPlace(), MatrixBase::ldlt()
   */
 template<typename MatrixType>
-template<typename RhsDerived, typename ResDerived>
+template<typename RhsDerived, typename ResultType>
 bool LDLT<MatrixType>
-::solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const
+::solve(const MatrixBase<RhsDerived> &b, ResultType *result) const
 {
   const int size = m_matrix.rows();
   ei_assert(size==b.rows() && "LLT::solve(): invalid number of rows of the right hand side matrix b");

Eigen/src/Cholesky/LLT.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>
 //
@@ -41,11 +41,16 @@
   * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other
   * situations like generalised eigen problems with hermitian matrices.
   *
-  * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
-  * the strict lower part does not have to store correct values.
+  * Remember that Cholesky decompositions are not rank-revealing. This LLT decomposition is only stable on positive definite matrices,
+  * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations
+  * has a solution.
   *
   * \sa MatrixBase::llt(), class LDLT
   */
+ /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH)
+  * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
+  * the strict lower part does not have to store correct values.
+  */
 template<typename MatrixType> class LLT
 {
   private:
@@ -60,20 +65,33 @@ template<typename MatrixType> class LLT
 
   public:
 
+    /** 
+    * \brief Default Constructor.
+    *
+    * The default constructor is useful in cases in which the user intends to
+    * perform decompositions via LLT::compute(const MatrixType&).
+    */
+    LLT() : m_matrix(), m_isInitialized(false) {}
+
     LLT(const MatrixType& matrix)
-      : m_matrix(matrix.rows(), matrix.cols())
+      : m_matrix(matrix.rows(), matrix.cols()),
+        m_isInitialized(false)
     {
       compute(matrix);
     }
 
     /** \returns the lower triangular matrix L */
-    inline Part<MatrixType, LowerTriangular> matrixL(void) const { return m_matrix; }
+    inline Part<MatrixType, LowerTriangular> matrixL(void) const 
+    { 
+      ei_assert(m_isInitialized && "LLT is not initialized.");
+      return m_matrix; 
+    }
+    
+    /** \deprecated */
+    inline bool isPositiveDefinite(void) const { return m_isInitialized && m_isPositiveDefinite; }
 
-    /** \returns true if the matrix is positive definite */
-    inline bool isPositiveDefinite(void) const { return m_isPositiveDefinite; }
-
-    template<typename RhsDerived, typename ResDerived>
-    bool solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const;
+    template<typename RhsDerived, typename ResultType>
+    bool solve(const MatrixBase<RhsDerived> &b, ResultType *result) const;
 
     template<typename Derived>
     bool solveInPlace(MatrixBase<Derived> &bAndX) const;
@@ -86,6 +104,7 @@ template<typename MatrixType> class LLT
       * The strict upper part is not used and even not initialized.
       */
     MatrixType m_matrix;
+    bool m_isInitialized;
     bool m_isPositiveDefinite;
 };
 
@@ -95,24 +114,34 @@ template<typename MatrixType>
 void LLT<MatrixType>::compute(const MatrixType& a)
 {
   assert(a.rows()==a.cols());
+  m_isPositiveDefinite = true;
   const int size = a.rows();
   m_matrix.resize(size, size);
-  const RealScalar eps = ei_sqrt(precision<Scalar>());
-
+  // The biggest overall is the point of reference to which further diagonals
+  // are compared; if any diagonal is negligible compared
+  // to the largest overall, the algorithm bails.  This cutoff is suggested
+  // in "Analysis of the Cholesky Decomposition of a Semi-definite Matrix" by
+  // Nicholas J. Higham. Also see "Accuracy and Stability of Numerical
+  // Algorithms" page 217, also by Higham.
+  const RealScalar cutoff = machine_epsilon<Scalar>() * size * a.diagonal().cwise().abs().maxCoeff();
   RealScalar x;
   x = ei_real(a.coeff(0,0));
-  m_isPositiveDefinite = x > eps && ei_isMuchSmallerThan(ei_imag(a.coeff(0,0)), RealScalar(1));
   m_matrix.coeffRef(0,0) = ei_sqrt(x);
+  if(size==1)
+  {
+    m_isInitialized = true;
+    return;
+  }
   m_matrix.col(0).end(size-1) = a.row(0).end(size-1).adjoint() / ei_real(m_matrix.coeff(0,0));
   for (int j = 1; j < size; ++j)
   {
-    Scalar tmp = ei_real(a.coeff(j,j)) - m_matrix.row(j).start(j).squaredNorm();
-    x = ei_real(tmp);
-    if (x < eps || (!ei_isMuchSmallerThan(ei_imag(tmp), RealScalar(1))))
+    x = ei_real(a.coeff(j,j)) - m_matrix.row(j).start(j).squaredNorm();
+    if (x < cutoff)
     {
       m_isPositiveDefinite = false;
-      return;
+      continue;
     }
+
     m_matrix.coeffRef(j,j) = x = ei_sqrt(x);
 
     int endSize = size-j-1;
@@ -127,12 +156,14 @@ void LLT<MatrixType>::compute(const MatrixType& a)
         - m_matrix.col(j).end(endSize) ) / x;
     }
   }
+
+  m_isInitialized = true;
 }
 
 /** Computes the solution x of \f$ A x = b \f$ using the current decomposition of A.
   * The result is stored in \a result
   *
-  * \returns true in case of success, false otherwise.
+  * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD.
   *
   * In other words, it computes \f$ b = A^{-1} b \f$ with
   * \f$ {L^{*}}^{-1} L^{-1} b \f$ from right to left.
@@ -143,9 +174,10 @@ void LLT<MatrixType>::compute(const MatrixType& a)
   * \sa LLT::solveInPlace(), MatrixBase::llt()
   */
 template<typename MatrixType>
-template<typename RhsDerived, typename ResDerived>
-bool LLT<MatrixType>::solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDerived> *result) const
+template<typename RhsDerived, typename ResultType>
+bool LLT<MatrixType>::solve(const MatrixBase<RhsDerived> &b, ResultType *result) const
 {
+  ei_assert(m_isInitialized && "LLT is not initialized.");
   const int size = m_matrix.rows();
   ei_assert(size==b.rows() && "LLT::solve(): invalid number of rows of the right hand side matrix b");
   return solveInPlace((*result) = b);
@@ -155,6 +187,8 @@ bool LLT<MatrixType>::solve(const MatrixBase<RhsDerived> &b, MatrixBase<ResDeriv
   *
   * \param bAndX represents both the right-hand side matrix b and result x.
   *
+  * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD.
+  *
   * This version avoids a copy when the right hand side matrix b is not
   * needed anymore.
   *
@@ -164,10 +198,9 @@ template<typename MatrixType>
 template<typename Derived>
 bool LLT<MatrixType>::solveInPlace(MatrixBase<Derived> &bAndX) const
 {
+  ei_assert(m_isInitialized && "LLT is not initialized.");
   const int size = m_matrix.rows();
   ei_assert(size==bAndX.rows());
-  if (!m_isPositiveDefinite)
-    return false;
   matrixL().solveTriangularInPlace(bAndX);
   m_matrix.adjoint().template part<UpperTriangular>().solveTriangularInPlace(bAndX);
   return true;

Eigen/src/Core/Assign.h

@@ -353,7 +353,7 @@ struct ei_assign_impl<Derived1, Derived2, SliceVectorization, NoUnrolling>
     const int outerSize = dst.outerSize();
     const int alignedStep = (packetSize - dst.stride() % packetSize) & packetAlignedMask;
     int alignedStart = ei_assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                     : ei_alignmentOffset(&dst.coeffRef(0), innerSize);
+                     : ei_alignmentOffset(&dst.coeffRef(0,0), innerSize);
 
     for(int i = 0; i < outerSize; ++i)
     {
@@ -401,6 +401,8 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>
   ::lazyAssign(const MatrixBase<OtherDerived>& other)
 {
   EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived)
+  EIGEN_STATIC_ASSERT((ei_is_same_type<typename Derived::Scalar, typename OtherDerived::Scalar>::ret),
+    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
   ei_assert(rows() == other.rows() && cols() == other.cols());
   ei_assign_impl<Derived, OtherDerived>::run(derived(),other.derived());
   return derived();
@@ -437,8 +439,6 @@ template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>
   ::operator=(const MatrixBase<OtherDerived>& other)
 {
-  EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename OtherDerived::Scalar>::ret),
-    YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
   return ei_assign_selector<Derived,OtherDerived>::run(derived(), other.derived());
 }
 

Eigen/src/Core/Block.h

@@ -61,27 +61,28 @@
   *
   * \sa MatrixBase::block(int,int,int,int), MatrixBase::block(int,int), class VectorBlock
   */
+
 template<typename MatrixType, int BlockRows, int BlockCols, int _PacketAccess, int _DirectAccessStatus>
 struct ei_traits<Block<MatrixType, BlockRows, BlockCols, _PacketAccess, _DirectAccessStatus> >
 {
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::Nested MatrixTypeNested;
+  typedef typename ei_traits<MatrixType>::Scalar Scalar;
+  typedef typename ei_nested<MatrixType>::type MatrixTypeNested;
   typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
   enum{
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime == 1 ? 1 : BlockRows,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime == 1 ? 1 : BlockCols,
+    RowsAtCompileTime = ei_traits<MatrixType>::RowsAtCompileTime == 1 ? 1 : BlockRows,
+    ColsAtCompileTime = ei_traits<MatrixType>::ColsAtCompileTime == 1 ? 1 : BlockCols,
     MaxRowsAtCompileTime = RowsAtCompileTime == 1 ? 1
-      : (BlockRows==Dynamic ? MatrixType::MaxRowsAtCompileTime : BlockRows),
+      : (BlockRows==Dynamic ? int(ei_traits<MatrixType>::MaxRowsAtCompileTime) : BlockRows),
     MaxColsAtCompileTime = ColsAtCompileTime == 1 ? 1
-      : (BlockCols==Dynamic ? MatrixType::MaxColsAtCompileTime : BlockCols),
-    RowMajor = int(MatrixType::Flags)&RowMajorBit,
-    InnerSize = RowMajor ? ColsAtCompileTime : RowsAtCompileTime,
-    InnerMaxSize = RowMajor ? MaxColsAtCompileTime : MaxRowsAtCompileTime,
+      : (BlockCols==Dynamic ? int(ei_traits<MatrixType>::MaxColsAtCompileTime) : BlockCols),
+    RowMajor = int(ei_traits<MatrixType>::Flags)&RowMajorBit,
+    InnerSize = RowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
+    InnerMaxSize = RowMajor ? int(MaxColsAtCompileTime) : int(MaxRowsAtCompileTime),
     MaskPacketAccessBit = (InnerMaxSize == Dynamic || (InnerSize >= ei_packet_traits<Scalar>::size))
                         ? PacketAccessBit : 0,
     FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1) ? LinearAccessBit : 0,
-    Flags = (MatrixType::Flags & (HereditaryBits | MaskPacketAccessBit | DirectAccessBit)) | FlagsLinearAccessBit,
-    CoeffReadCost = MatrixType::CoeffReadCost,
+    Flags = (ei_traits<MatrixType>::Flags & (HereditaryBits | MaskPacketAccessBit | DirectAccessBit)) | FlagsLinearAccessBit,
+    CoeffReadCost = ei_traits<MatrixType>::CoeffReadCost,
     PacketAccess = _PacketAccess
   };
   typedef typename ei_meta_if<int(PacketAccess)==ForceAligned,
@@ -122,7 +123,7 @@ template<typename MatrixType, int BlockRows, int BlockCols, int PacketAccess, in
       : m_matrix(matrix), m_startRow(startRow), m_startCol(startCol),
         m_blockRows(matrix.rows()), m_blockCols(matrix.cols())
     {
-      EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && RowsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
+      EIGEN_STATIC_ASSERT(RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic,THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE)
       ei_assert(startRow >= 0 && BlockRows >= 1 && startRow + BlockRows <= matrix.rows()
           && startCol >= 0 && BlockCols >= 1 && startCol + BlockCols <= matrix.cols());
     }
@@ -146,8 +147,6 @@ template<typename MatrixType, int BlockRows, int BlockCols, int PacketAccess, in
     inline int rows() const { return m_blockRows.value(); }
     inline int cols() const { return m_blockCols.value(); }
 
-    inline int stride(void) const { return m_matrix.stride(); }
-
     inline Scalar& coeffRef(int row, int col)
     {
       return m_matrix.const_cast_derived()
@@ -223,15 +222,13 @@ class Block<MatrixType,BlockRows,BlockCols,PacketAccess,HasDirectAccess>
 
     class InnerIterator;
     typedef typename ei_traits<Block>::AlignedDerivedType AlignedDerivedType;
+    friend class Block<MatrixType,BlockRows,BlockCols,PacketAccess==int(AsRequested)?ForceAligned:AsRequested,HasDirectAccess>;
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block)
 
-    AlignedDerivedType forceAligned()
+    AlignedDerivedType _convertToForceAligned()
     {
-      if (PacketAccess==ForceAligned)
-        return *this;
-      else
-        return Block<MatrixType,BlockRows,BlockCols,ForceAligned,HasDirectAccess>
+      return Block<MatrixType,BlockRows,BlockCols,ForceAligned,HasDirectAccess>
                     (m_matrix, Base::m_data, Base::m_rows.value(), Base::m_cols.value());
     }
 
@@ -456,7 +453,7 @@ MatrixBase<Derived>::end(int size) const
   * \only_for_vectors
   *
   * The template parameter \a Size is the number of coefficients in the block
-  * 
+  *
   * \param start the index of the first element of the sub-vector
   *
   * Example: \include MatrixBase_template_int_segment.cpp

Eigen/src/Core/CacheFriendlyProduct.h

@@ -81,7 +81,7 @@ static void ei_cache_friendly_product(
     MaxBlockRows_ClampingMask = 0xFFFFF8,
     #endif
     // maximal size of the blocks fitted in L2 cache
-    MaxL2BlockSize = ei_L2_block_traits<EIGEN_TUNE_FOR_L2_CACHE_SIZE,Scalar>::width
+    MaxL2BlockSize = ei_L2_block_traits<EIGEN_TUNE_FOR_CPU_CACHE_SIZE,Scalar>::width
   };
 
   const bool resIsAligned = (PacketSize==1) || (((resStride%PacketSize) == 0) && (size_t(res)%16==0));
@@ -95,9 +95,9 @@ static void ei_cache_friendly_product(
   const bool needRhsCopy = (PacketSize>1) && ((rhsStride%PacketSize!=0) || (size_t(rhs)%16!=0));
   Scalar* EIGEN_RESTRICT block = 0;
   const int allocBlockSize = l2BlockRows*size;
-  block = ei_aligned_stack_alloc(Scalar, allocBlockSize);
+  block = ei_aligned_stack_new(Scalar, allocBlockSize);
   Scalar* EIGEN_RESTRICT rhsCopy
-    = ei_aligned_stack_alloc(Scalar, l2BlockSizeAligned*l2BlockSizeAligned);
+    = ei_aligned_stack_new(Scalar, l2BlockSizeAligned*l2BlockSizeAligned);
 
   // loops on each L2 cache friendly blocks of the result
   for(int l2i=0; l2i<rows; l2i+=l2BlockRows)
@@ -180,7 +180,7 @@ static void ei_cache_friendly_product(
         {
           int offsetblock = l2k * (l2blockRowEnd-l2i) + (l1i-l2i)*(l2blockSizeEnd-l2k) - l2k*MaxBlockRows;
           const Scalar* EIGEN_RESTRICT localB = &block[offsetblock];
-          
+
           for(int l1j=l2j; l1j<l2blockColEnd; l1j+=1)
           {
             const Scalar* EIGEN_RESTRICT rhsColumn;
@@ -338,8 +338,8 @@ static void ei_cache_friendly_product(
     }
   }
 
-  ei_aligned_stack_free(block, Scalar, allocBlockSize);
-  ei_aligned_stack_free(rhsCopy, Scalar, l2BlockSizeAligned*l2BlockSizeAligned);
+  ei_aligned_stack_delete(Scalar, block, allocBlockSize);
+  ei_aligned_stack_delete(Scalar, rhsCopy, l2BlockSizeAligned*l2BlockSizeAligned);
 }
 
 #endif // EIGEN_EXTERN_INSTANTIATIONS
@@ -361,13 +361,14 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_colmajor_times_vector(
   #ifdef _EIGEN_ACCUMULATE_PACKETS
   #error _EIGEN_ACCUMULATE_PACKETS has already been defined
   #endif
-
-  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2,OFFSET) \
-    ei_pstore(&res[j OFFSET], \
-      ei_padd(ei_pload(&res[j OFFSET]), \
+  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) \
+    ei_pstore(&res[j], \
+      ei_padd(ei_pload(&res[j]), \
         ei_padd( \
-          ei_padd(ei_pmul(ptmp0,ei_pload ## A0(&lhs0[j OFFSET])),ei_pmul(ptmp1,ei_pload ## A13(&lhs1[j OFFSET]))), \
-          ei_padd(ei_pmul(ptmp2,ei_pload ## A2(&lhs2[j OFFSET])),ei_pmul(ptmp3,ei_pload ## A13(&lhs3[j OFFSET]))) )))
+          ei_padd(ei_pmul(ptmp0,EIGEN_CAT(ei_ploa , A0)(&lhs0[j])), \
+                  ei_pmul(ptmp1,EIGEN_CAT(ei_ploa , A13)(&lhs1[j]))), \
+          ei_padd(ei_pmul(ptmp2,EIGEN_CAT(ei_ploa , A2)(&lhs2[j])), \
+                  ei_pmul(ptmp3,EIGEN_CAT(ei_ploa , A13)(&lhs3[j]))) )))
 
   typedef typename ei_packet_traits<Scalar>::type Packet;
   const int PacketSize = sizeof(Packet)/sizeof(Scalar);
@@ -397,7 +398,7 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_colmajor_times_vector(
   if (PacketSize>1)
   {
     ei_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(Packet)==0 || size<PacketSize);
-    
+
     while (skipColumns<PacketSize &&
            alignedStart != ((lhsAlignmentOffset + alignmentStep*skipColumns)%PacketSize))
       ++skipColumns;
@@ -418,7 +419,7 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_colmajor_times_vector(
 
   int offset1 = (FirstAligned && alignmentStep==1?3:1);
   int offset3 = (FirstAligned && alignmentStep==1?1:3);
-  
+
   int columnBound = ((rhs.size()-skipColumns)/columnsAtOnce)*columnsAtOnce + skipColumns;
   for (int i=skipColumns; i<columnBound; i+=columnsAtOnce)
   {
@@ -442,11 +443,11 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_colmajor_times_vector(
         {
           case AllAligned:
             for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(,,,);
+              _EIGEN_ACCUMULATE_PACKETS(d,d,d);
             break;
           case EvenAligned:
             for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(,u,,);
+              _EIGEN_ACCUMULATE_PACKETS(d,du,d);
             break;
           case FirstAligned:
             if(peels>1)
@@ -482,11 +483,11 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_colmajor_times_vector(
               }
             }
             for (int j = peeledSize; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(,u,u,);
+              _EIGEN_ACCUMULATE_PACKETS(d,du,du);
             break;
           default:
             for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(u,u,u,);
+              _EIGEN_ACCUMULATE_PACKETS(du,du,du);
             break;
         }
       }
@@ -494,7 +495,7 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_colmajor_times_vector(
 
     /* process remaining coeffs (or all if there is no explicit vectorization) */
     for (int j=alignedSize; j<size; ++j)
-	  res[j] += ei_pfirst(ptmp0)*lhs0[j] + ei_pfirst(ptmp1)*lhs1[j] + ei_pfirst(ptmp2)*lhs2[j] + ei_pfirst(ptmp3)*lhs3[j];
+      res[j] += ei_pfirst(ptmp0)*lhs0[j] + ei_pfirst(ptmp1)*lhs1[j] + ei_pfirst(ptmp2)*lhs2[j] + ei_pfirst(ptmp3)*lhs3[j];
   }
 
   // process remaining first and last columns (at most columnsAtOnce-1)
@@ -550,12 +551,12 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
   #error _EIGEN_ACCUMULATE_PACKETS has already been defined
   #endif
 
-  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2,OFFSET) {\
+  #define _EIGEN_ACCUMULATE_PACKETS(A0,A13,A2) {\
     Packet b = ei_pload(&rhs[j]); \
-    ptmp0 = ei_pmadd(b, ei_pload##A0 (&lhs0[j]), ptmp0); \
-    ptmp1 = ei_pmadd(b, ei_pload##A13(&lhs1[j]), ptmp1); \
-    ptmp2 = ei_pmadd(b, ei_pload##A2 (&lhs2[j]), ptmp2); \
-    ptmp3 = ei_pmadd(b, ei_pload##A13(&lhs3[j]), ptmp3); }
+    ptmp0 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A0) (&lhs0[j]), ptmp0); \
+    ptmp1 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A13)(&lhs1[j]), ptmp1); \
+    ptmp2 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A2) (&lhs2[j]), ptmp2); \
+    ptmp3 = ei_pmadd(b, EIGEN_CAT(ei_ploa,A13)(&lhs3[j]), ptmp3); }
 
   typedef typename ei_packet_traits<Scalar>::type Packet;
   const int PacketSize = sizeof(Packet)/sizeof(Scalar);
@@ -580,13 +581,13 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
 
   // we cannot assume the first element is aligned because of sub-matrices
   const int lhsAlignmentOffset = ei_alignmentOffset(lhs,size);
-  
+
   // find how many rows do we have to skip to be aligned with rhs (if possible)
   int skipRows = 0;
   if (PacketSize>1)
   {
     ei_internal_assert(size_t(lhs+lhsAlignmentOffset)%sizeof(Packet)==0  || size<PacketSize);
-    
+
     while (skipRows<PacketSize &&
            alignedStart != ((lhsAlignmentOffset + alignmentStep*skipRows)%PacketSize))
       ++skipRows;
@@ -607,7 +608,7 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
 
   int offset1 = (FirstAligned && alignmentStep==1?3:1);
   int offset3 = (FirstAligned && alignmentStep==1?1:3);
-  
+
   int rowBound = ((res.size()-skipRows)/rowsAtOnce)*rowsAtOnce + skipRows;
   for (int i=skipRows; i<rowBound; i+=rowsAtOnce)
   {
@@ -621,7 +622,7 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
     {
       /* explicit vectorization */
       Packet ptmp0 = ei_pset1(Scalar(0)), ptmp1 = ei_pset1(Scalar(0)), ptmp2 = ei_pset1(Scalar(0)), ptmp3 = ei_pset1(Scalar(0));
-      
+
       // process initial unaligned coeffs
       // FIXME this loop get vectorized by the compiler !
       for (int j=0; j<alignedStart; ++j)
@@ -636,11 +637,11 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
         {
           case AllAligned:
             for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(,,,);
+              _EIGEN_ACCUMULATE_PACKETS(d,d,d);
             break;
           case EvenAligned:
             for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(,u,,);
+              _EIGEN_ACCUMULATE_PACKETS(d,du,d);
             break;
           case FirstAligned:
             if (peels>1)
@@ -679,11 +680,11 @@ static EIGEN_DONT_INLINE void ei_cache_friendly_product_rowmajor_times_vector(
               }
             }
             for (int j = peeledSize; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(,u,u,);
+              _EIGEN_ACCUMULATE_PACKETS(d,du,du);
             break;
           default:
             for (int j = alignedStart; j<alignedSize; j+=PacketSize)
-              _EIGEN_ACCUMULATE_PACKETS(u,u,u,);
+              _EIGEN_ACCUMULATE_PACKETS(du,du,du);
             break;
         }
         tmp0 += ei_predux(ptmp0);

Eigen/src/Core/Coeffs.h

@@ -313,6 +313,8 @@ EIGEN_STRONG_INLINE void MatrixBase<Derived>::writePacket
   derived().template writePacket<StoreMode>(index,x);
 }
 
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+
 /** \internal Copies the coefficient at position (row,col) of other into *this.
   *
   * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code
@@ -377,4 +379,6 @@ EIGEN_STRONG_INLINE void MatrixBase<Derived>::copyPacket(int index, const Matrix
     other.derived().template packet<LoadMode>(index));
 }
 
+#endif
+
 #endif // EIGEN_COEFFS_H

Eigen/src/Core/CommaInitializer.h

@@ -116,6 +116,9 @@ struct CommaInitializer
   int m_row;              // current row id
   int m_col;              // current col id
   int m_currentBlockRows; // current block height
+
+private:
+  CommaInitializer& operator=(const CommaInitializer&);
 };
 
 /** \anchor MatrixBaseCommaInitRef

Eigen/src/Core/Cwise.h

@@ -128,6 +128,12 @@ template<typename ExpressionType> class Cwise
 
     ExpressionType& operator-=(const Scalar& scalar);
 
+    template<typename OtherDerived>
+    inline ExpressionType& operator*=(const MatrixBase<OtherDerived> &other);
+
+    template<typename OtherDerived>
+    inline ExpressionType& operator/=(const MatrixBase<OtherDerived> &other);
+
     template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)
     operator<(const MatrixBase<OtherDerived>& other) const;
 
@@ -165,8 +171,16 @@ template<typename ExpressionType> class Cwise
     const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)
     operator!=(Scalar s) const;
 
+    // allow to extend Cwise outside Eigen
+    #ifdef EIGEN_CWISE_PLUGIN
+    #include EIGEN_CWISE_PLUGIN
+    #endif
+
   protected:
     ExpressionTypeNested m_matrix;
+
+  private:
+    Cwise& operator=(const Cwise&);
 };
 
 /** \returns a Cwise wrapper of *this providing additional coefficient-wise operations

Eigen/src/Core/CwiseBinaryOp.h

@@ -86,14 +86,12 @@ class CwiseBinaryOp : ei_no_assignment_operator,
     typedef typename ei_traits<CwiseBinaryOp>::LhsNested LhsNested;
     typedef typename ei_traits<CwiseBinaryOp>::RhsNested RhsNested;
 
-    class InnerIterator;
-
     EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
       : m_lhs(lhs), m_rhs(rhs), m_functor(func)
     {
       // we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor
       // that would take two operands of different types. If there were such an example, then this check should be
-      // moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as 
+      // moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as
       // currently they take only one typename Scalar template parameter.
       // It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths.
       // So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
@@ -224,6 +222,34 @@ Cwise<ExpressionType>::operator/(const MatrixBase<OtherDerived> &other) const
   return EIGEN_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)(_expression(), other.derived());
 }
 
+/** Replaces this expression by its coefficient-wise product with \a other.
+  *
+  * Example: \include Cwise_times_equal.cpp
+  * Output: \verbinclude Cwise_times_equal.out
+  *
+  * \sa operator*(), operator/=()
+  */
+template<typename ExpressionType>
+template<typename OtherDerived>
+inline ExpressionType& Cwise<ExpressionType>::operator*=(const MatrixBase<OtherDerived> &other)
+{
+  return m_matrix.const_cast_derived() = *this * other;
+}
+
+/** Replaces this expression by its coefficient-wise quotient by \a other.
+  *
+  * Example: \include Cwise_slash_equal.cpp
+  * Output: \verbinclude Cwise_slash_equal.out
+  *
+  * \sa operator/(), operator*=()
+  */
+template<typename ExpressionType>
+template<typename OtherDerived>
+inline ExpressionType& Cwise<ExpressionType>::operator/=(const MatrixBase<OtherDerived> &other)
+{
+  return m_matrix.const_cast_derived() = *this / other;
+}
+
 /** \returns an expression of the coefficient-wise min of *this and \a other
   *
   * Example: \include Cwise_min.cpp

Eigen/src/Core/CwiseNullaryOp.h

@@ -41,14 +41,9 @@
   * \sa class CwiseUnaryOp, class CwiseBinaryOp, MatrixBase::NullaryExpr()
   */
 template<typename NullaryOp, typename MatrixType>
-struct ei_traits<CwiseNullaryOp<NullaryOp, MatrixType> >
+struct ei_traits<CwiseNullaryOp<NullaryOp, MatrixType> > : ei_traits<MatrixType>
 {
-  typedef typename ei_traits<MatrixType>::Scalar Scalar;
   enum {
-    RowsAtCompileTime = ei_traits<MatrixType>::RowsAtCompileTime,
-    ColsAtCompileTime = ei_traits<MatrixType>::ColsAtCompileTime,
-    MaxRowsAtCompileTime = ei_traits<MatrixType>::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = ei_traits<MatrixType>::MaxColsAtCompileTime,
     Flags = (ei_traits<MatrixType>::Flags
       & (  HereditaryBits
          | (ei_functor_has_linear_access<NullaryOp>::ret ? LinearAccessBit : 0)
@@ -151,6 +146,7 @@ template<typename CustomNullaryOp>
 EIGEN_STRONG_INLINE const CwiseNullaryOp<CustomNullaryOp, Derived>
 MatrixBase<Derived>::NullaryExpr(int size, const CustomNullaryOp& func)
 {
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
   ei_assert(IsVectorAtCompileTime);
   if(RowsAtCompileTime == 1) return CwiseNullaryOp<CustomNullaryOp, Derived>(1, size, func);
   else return CwiseNullaryOp<CustomNullaryOp, Derived>(size, 1, func);
@@ -232,6 +228,7 @@ MatrixBase<Derived>::Constant(const Scalar& value)
   return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, ei_scalar_constant_op<Scalar>(value));
 }
 
+/** \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
 template<typename Derived>
 bool MatrixBase<Derived>::isApproxToConstant
 (const Scalar& value, RealScalar prec) const
@@ -243,9 +240,29 @@ bool MatrixBase<Derived>::isApproxToConstant
   return true;
 }
 
+/** This is just an alias for isApproxToConstant().
+  *
+  * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */
+template<typename Derived>
+bool MatrixBase<Derived>::isConstant
+(const Scalar& value, RealScalar prec) const
+{
+  return isApproxToConstant(value, prec);
+}
+
+/** Alias for setConstant(): sets all coefficients in this expression to \a value.
+  *
+  * \sa setConstant(), Constant(), class CwiseNullaryOp
+  */
+template<typename Derived>
+EIGEN_STRONG_INLINE void MatrixBase<Derived>::fill(const Scalar& value)
+{
+  setConstant(value);
+}
+
 /** Sets all coefficients in this expression to \a value.
   *
-  * \sa class CwiseNullaryOp, Zero(), Ones()
+  * \sa fill(), setConstant(int,const Scalar&), setConstant(int,int,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes()
   */
 template<typename Derived>
 EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setConstant(const Scalar& value)
@@ -253,6 +270,42 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setConstant(const Scalar& valu
   return derived() = Constant(rows(), cols(), value);
 }
 
+/** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value.
+  *
+  * \only_for_vectors
+  *
+  * Example: \include Matrix_set_int.cpp
+  * Output: \verbinclude Matrix_setConstant_int.out
+  *
+  * \sa MatrixBase::setConstant(const Scalar&), setConstant(int,int,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setConstant(int size, const Scalar& value)
+{
+  resize(size);
+  return setConstant(value);
+}
+
+/** Resizes to the given size, and sets all coefficients in this expression to the given \a value.
+  *
+  * \param rows the new number of rows
+  * \param cols the new number of columns
+  *
+  * Example: \include Matrix_setConstant_int_int.cpp
+  * Output: \verbinclude Matrix_setConstant_int_int.out
+  *
+  * \sa MatrixBase::setConstant(const Scalar&), setConstant(int,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&)
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setConstant(int rows, int cols, const Scalar& value)
+{
+  resize(rows, cols);
+  return setConstant(value);
+}
+
+
 // zero:
 
 /** \returns an expression of a zero matrix.
@@ -349,6 +402,41 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setZero()
   return setConstant(Scalar(0));
 }
 
+/** Resizes to the given \a size, and sets all coefficients in this expression to zero.
+  *
+  * \only_for_vectors
+  *
+  * Example: \include Matrix_setZero_int.cpp
+  * Output: \verbinclude Matrix_setZero_int.out
+  *
+  * \sa MatrixBase::setZero(), setZero(int,int), class CwiseNullaryOp, MatrixBase::Zero()
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setZero(int size)
+{
+  resize(size);
+  return setConstant(Scalar(0));
+}
+
+/** Resizes to the given size, and sets all coefficients in this expression to zero.
+  *
+  * \param rows the new number of rows
+  * \param cols the new number of columns
+  *
+  * Example: \include Matrix_setZero_int_int.cpp
+  * Output: \verbinclude Matrix_setZero_int_int.out
+  *
+  * \sa MatrixBase::setZero(), setZero(int), class CwiseNullaryOp, MatrixBase::Zero()
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setZero(int rows, int cols)
+{
+  resize(rows, cols);
+  return setConstant(Scalar(0));
+}
+
 // ones:
 
 /** \returns an expression of a matrix where all coefficients equal one.
@@ -442,6 +530,41 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setOnes()
   return setConstant(Scalar(1));
 }
 
+/** Resizes to the given \a size, and sets all coefficients in this expression to one.
+  *
+  * \only_for_vectors
+  *
+  * Example: \include Matrix_setOnes_int.cpp
+  * Output: \verbinclude Matrix_setOnes_int.out
+  *
+  * \sa MatrixBase::setOnes(), setOnes(int,int), class CwiseNullaryOp, MatrixBase::Ones()
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setOnes(int size)
+{
+  resize(size);
+  return setConstant(Scalar(1));
+}
+
+/** Resizes to the given size, and sets all coefficients in this expression to one.
+  *
+  * \param rows the new number of rows
+  * \param cols the new number of columns
+  *
+  * Example: \include Matrix_setOnes_int_int.cpp
+  * Output: \verbinclude Matrix_setOnes_int_int.out
+  *
+  * \sa MatrixBase::setOnes(), setOnes(int), class CwiseNullaryOp, MatrixBase::Ones()
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setOnes(int rows, int cols)
+{
+  resize(rows, cols);
+  return setConstant(Scalar(1));
+}
+
 // Identity:
 
 /** \returns an expression of the identity matrix (not necessarily square).
@@ -551,6 +674,24 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::setIdentity()
   return ei_setIdentity_impl<Derived>::run(derived());
 }
 
+/** Resizes to the given size, and writes the identity expression (not necessarily square) into *this.
+  *
+  * \param rows the new number of rows
+  * \param cols the new number of columns
+  *
+  * Example: \include Matrix_setIdentity_int_int.cpp
+  * Output: \verbinclude Matrix_setIdentity_int_int.out
+  *
+  * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity()
+  */
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+EIGEN_STRONG_INLINE Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>&
+Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::setIdentity(int rows, int cols)
+{
+  resize(rows, cols);
+  return setIdentity();
+}
+
 /** \returns an expression of the i-th unit (basis) vector.
   *
   * \only_for_vectors

Eigen/src/Core/CwiseUnaryOp.h

@@ -41,6 +41,7 @@
   */
 template<typename UnaryOp, typename MatrixType>
 struct ei_traits<CwiseUnaryOp<UnaryOp, MatrixType> >
+ : ei_traits<MatrixType>
 {
   typedef typename ei_result_of<
                      UnaryOp(typename MatrixType::Scalar)
@@ -48,16 +49,10 @@ struct ei_traits<CwiseUnaryOp<UnaryOp, MatrixType> >
   typedef typename MatrixType::Nested MatrixTypeNested;
   typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
-    MatrixTypeCoeffReadCost = _MatrixTypeNested::CoeffReadCost,
-    MatrixTypeFlags = _MatrixTypeNested::Flags,
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
-    Flags = (MatrixTypeFlags & (
+    Flags = (_MatrixTypeNested::Flags & (
       HereditaryBits | LinearAccessBit | AlignedBit
       | (ei_functor_traits<UnaryOp>::PacketAccess ? PacketAccessBit : 0))),
-    CoeffReadCost = MatrixTypeCoeffReadCost + ei_functor_traits<UnaryOp>::Cost
+    CoeffReadCost = _MatrixTypeNested::CoeffReadCost + ei_functor_traits<UnaryOp>::Cost
   };
 };
 
@@ -69,8 +64,6 @@ class CwiseUnaryOp : ei_no_assignment_operator,
 
     EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp)
 
-    class InnerIterator;
-
     inline CwiseUnaryOp(const MatrixType& mat, const UnaryOp& func = UnaryOp())
       : m_matrix(mat), m_functor(func) {}
 

Eigen/src/Core/DiagonalMatrix.h

@@ -26,6 +26,7 @@
 #define EIGEN_DIAGONALMATRIX_H
 
 /** \class DiagonalMatrix
+  * \nonstableyet 
   *
   * \brief Expression of a diagonal matrix
   *
@@ -61,6 +62,7 @@ class DiagonalMatrix : ei_no_assignment_operator,
   public:
 
     EIGEN_GENERIC_PUBLIC_INTERFACE(DiagonalMatrix)
+    typedef CoeffsVectorType _CoeffsVectorType;
 
     // needed to evaluate a DiagonalMatrix<Xpr> to a DiagonalMatrix<NestByValue<Vector> >
     template<typename OtherCoeffsVectorType>
@@ -91,7 +93,8 @@ class DiagonalMatrix : ei_no_assignment_operator,
     const typename CoeffsVectorType::Nested m_coeffs;
 };
 
-/** \returns an expression of a diagonal matrix with *this as vector of diagonal coefficients
+/** \nonstableyet 
+  * \returns an expression of a diagonal matrix with *this as vector of diagonal coefficients
   *
   * \only_for_vectors
   *
@@ -109,7 +112,8 @@ MatrixBase<Derived>::asDiagonal() const
   return derived();
 }
 
-/** \returns true if *this is approximately equal to a diagonal matrix,
+/** \nonstableyet 
+  * \returns true if *this is approximately equal to a diagonal matrix,
   *          within the precision given by \a prec.
   *
   * Example: \include MatrixBase_isDiagonal.cpp

Eigen/src/Core/DiagonalProduct.h

@@ -73,7 +73,7 @@ struct ei_traits<Product<LhsNested, RhsNested, DiagonalProduct> >
     RemovedBits = ~((RhsFlags & RowMajorBit) && (!CanVectorizeLhs) ? 0 : RowMajorBit),
 
     Flags = ((unsigned int)(LhsFlags | RhsFlags) & HereditaryBits & RemovedBits)
-          | (CanVectorizeLhs || CanVectorizeRhs ? PacketAccessBit : 0),
+          | (((CanVectorizeLhs&&RhsIsDiagonal) || (CanVectorizeRhs&&LhsIsDiagonal)) ? PacketAccessBit : 0),
 
     CoeffReadCost = NumTraits<Scalar>::MulCost + _LhsNested::CoeffReadCost + _RhsNested::CoeffReadCost
   };
@@ -114,12 +114,10 @@ template<typename LhsNested, typename RhsNested> class Product<LhsNested, RhsNes
     {
       if (RhsIsDiagonal)
       {
-        ei_assert((_LhsNested::Flags&RowMajorBit)==0);
         return ei_pmul(m_lhs.template packet<LoadMode>(row, col), ei_pset1(m_rhs.coeff(col, col)));
       }
       else
       {
-        ei_assert(_RhsNested::Flags&RowMajorBit);
         return ei_pmul(ei_pset1(m_lhs.coeff(row, row)), m_rhs.template packet<LoadMode>(row, col));
       }
     }

Eigen/src/Core/Dot.h

@@ -258,53 +258,28 @@ template<typename OtherDerived>
 typename ei_traits<Derived>::Scalar
 MatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
 {
-  typedef typename Derived::Nested Nested;
-  typedef typename OtherDerived::Nested OtherNested;
-  typedef typename ei_unref<Nested>::type _Nested;
-  typedef typename ei_unref<OtherNested>::type _OtherNested;
-
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(_Nested)
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(_OtherNested)
-  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(_Nested,_OtherNested)
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
+  EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived)
   EIGEN_STATIC_ASSERT((ei_is_same_type<Scalar, typename OtherDerived::Scalar>::ret),
     YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
   ei_assert(size() == other.size());
 
-  return ei_dot_impl<_Nested, _OtherNested>::run(derived(), other.derived());
+  return ei_dot_impl<Derived, OtherDerived>::run(derived(), other.derived());
 }
 
-/** \returns the squared norm of *this, i.e. the dot product of *this with itself.
-  *
-  * \note This is \em not the \em l2 norm, but its square.
-  *
-  * \deprecated Use squaredNorm() instead. This norm2() function is kept only for compatibility and will be removed in Eigen 2.0.
-  *
-  * \only_for_vectors
-  *
-  * \sa dot(), norm()
-  */
-template<typename Derived>
-EIGEN_DEPRECATED inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<Derived>::norm2() const
-{
-  return ei_real(dot(*this));
-}
-
-/** \returns the squared norm of *this, i.e. the dot product of *this with itself.
-  *
-  * \only_for_vectors
+/** \returns the squared \em l2 norm of *this, i.e., for vectors, the dot product of *this with itself.
   *
   * \sa dot(), norm()
   */
 template<typename Derived>
 inline typename NumTraits<typename ei_traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
 {
-  return ei_real(dot(*this));
+  return ei_real((*this).cwise().abs2().sum());
 }
 
-/** \returns the \em l2 norm of *this, i.e. the square root of the dot product of *this with itself.
-  *
-  * \only_for_vectors
+/** \returns the \em l2 norm of *this, i.e., for vectors, the square root of the dot product of *this with itself.
   *
   * \sa dot(), squaredNorm()
   */

Eigen/src/Core/Flagged.h

@@ -40,18 +40,9 @@
   * \sa MatrixBase::flagged()
   */
 template<typename ExpressionType, unsigned int Added, unsigned int Removed>
-struct ei_traits<Flagged<ExpressionType, Added, Removed> >
+struct ei_traits<Flagged<ExpressionType, Added, Removed> > : ei_traits<ExpressionType>
 {
-  typedef typename ExpressionType::Scalar Scalar;
-
-  enum {
-    RowsAtCompileTime = ExpressionType::RowsAtCompileTime,
-    ColsAtCompileTime = ExpressionType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = ExpressionType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = ExpressionType::MaxColsAtCompileTime,
-    Flags = (ExpressionType::Flags | Added) & ~Removed,
-    CoeffReadCost = ExpressionType::CoeffReadCost
-  };
+  enum { Flags = (ExpressionType::Flags | Added) & ~Removed };
 };
 
 template<typename ExpressionType, unsigned int Added, unsigned int Removed> class Flagged
@@ -118,6 +109,9 @@ template<typename ExpressionType, unsigned int Added, unsigned int Removed> clas
 
   protected:
     ExpressionTypeNested m_matrix;
+
+private:
+  Flagged& operator=(const Flagged&);
 };
 
 /** \returns an expression of *this with added flags

Eigen/src/Core/Functors.h

@@ -279,6 +279,8 @@ struct ei_scalar_multiple_op {
   EIGEN_STRONG_INLINE const PacketScalar packetOp(const PacketScalar& a) const
   { return ei_pmul(a, ei_pset1(m_other)); }
   const Scalar m_other;
+private:
+  ei_scalar_multiple_op& operator=(const ei_scalar_multiple_op&);
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_multiple_op<Scalar> >
@@ -294,6 +296,8 @@ struct ei_scalar_quotient1_impl {
   EIGEN_STRONG_INLINE const PacketScalar packetOp(const PacketScalar& a) const
   { return ei_pmul(a, ei_pset1(m_other)); }
   const Scalar m_other;
+private:
+  ei_scalar_quotient1_impl& operator=(const ei_scalar_quotient1_impl&);
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_quotient1_impl<Scalar,true> >
@@ -306,6 +310,8 @@ struct ei_scalar_quotient1_impl<Scalar,false> {
   EIGEN_STRONG_INLINE ei_scalar_quotient1_impl(const Scalar& other) : m_other(other) {}
   EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; }
   const Scalar m_other;
+private:
+  ei_scalar_quotient1_impl& operator=(const ei_scalar_quotient1_impl&);
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_quotient1_impl<Scalar,false> >
@@ -323,6 +329,8 @@ template<typename Scalar>
 struct ei_scalar_quotient1_op : ei_scalar_quotient1_impl<Scalar, NumTraits<Scalar>::HasFloatingPoint > {
   EIGEN_STRONG_INLINE ei_scalar_quotient1_op(const Scalar& other)
     : ei_scalar_quotient1_impl<Scalar, NumTraits<Scalar>::HasFloatingPoint >(other) {}
+private:
+  ei_scalar_quotient1_op& operator=(const ei_scalar_quotient1_op&);
 };
 
 // nullary functors
@@ -335,6 +343,8 @@ struct ei_scalar_constant_op {
   EIGEN_STRONG_INLINE const Scalar operator() (int, int = 0) const { return m_other; }
   EIGEN_STRONG_INLINE const PacketScalar packetOp() const { return ei_pset1(m_other); }
   const Scalar m_other;
+private:
+  ei_scalar_constant_op& operator=(const ei_scalar_constant_op&);
 };
 template<typename Scalar>
 struct ei_functor_traits<ei_scalar_constant_op<Scalar> >
@@ -348,6 +358,12 @@ template<typename Scalar>
 struct ei_functor_traits<ei_scalar_identity_op<Scalar> >
 { enum { Cost = NumTraits<Scalar>::AddCost, PacketAccess = false, IsRepeatable = true }; };
 
+// allow to add new functors and specializations of ei_functor_traits from outside Eigen.
+// this macro is really needed because ei_functor_traits must be specialized after it is declared but before it is used...
+#ifdef EIGEN_FUNCTORS_PLUGIN
+#include EIGEN_FUNCTORS_PLUGIN
+#endif
+
 // all functors allow linear access, except ei_scalar_identity_op. So we fix here a quick meta
 // to indicate whether a functor allows linear access, just always answering 'yes' except for
 // ei_scalar_identity_op.

Eigen/src/Core/Map.h

@@ -66,12 +66,9 @@ template<typename MatrixType, int PacketAccess> class Map
 
     inline int stride() const { return this->innerSize(); }
 
-    AlignedDerivedType forceAligned()
+    AlignedDerivedType _convertToForceAligned()
     {
-      if (PacketAccess==ForceAligned)
-        return *this;
-      else
-        return Map<MatrixType,ForceAligned>(Base::m_data, Base::m_rows.value(), Base::m_cols.value());
+      return Map<MatrixType,ForceAligned>(Base::m_data, Base::m_rows.value(), Base::m_cols.value());
     }
 
     inline Map(const Scalar* data) : Base(data) {}
@@ -85,7 +82,7 @@ template<typename MatrixType, int PacketAccess> class Map
       EIGEN_ONLY_USED_FOR_DEBUG(rows);
       EIGEN_ONLY_USED_FOR_DEBUG(cols);
       ei_assert(rows == this->rows());
-      ei_assert(rows == this->cols());
+      ei_assert(cols == this->cols());
     }
 
     inline void resize(int size)
@@ -102,17 +99,13 @@ template<typename MatrixType, int PacketAccess> class Map
   * Only for fixed-size matrices and vectors.
   * \param data The array of data to copy
   *
-  * For dynamic-size matrices and vectors, see the variants taking additional int parameters
-  * for the dimensions.
-  *
-  * \sa Matrix(const Scalar *, int), Matrix(const Scalar *, int, int),
-  * Matrix::Map(const Scalar *)
+  * \sa Matrix::Map(const Scalar *)
   */
 template<typename _Scalar, int _Rows, int _Cols, int _StorageOrder, int _MaxRows, int _MaxCols>
 inline Matrix<_Scalar, _Rows, _Cols, _StorageOrder, _MaxRows, _MaxCols>
   ::Matrix(const Scalar *data)
 {
-  *this = Eigen::Map<Matrix>(data);
+  _set_noalias(Eigen::Map<Matrix>(data));
 }
 
 #endif // EIGEN_MAP_H

Eigen/src/Core/MapBase.h

@@ -63,10 +63,22 @@ template<typename Derived> class MapBase
     inline int cols() const { return m_cols.value(); }
 
     inline int stride() const { return derived().stride(); }
+    inline const Scalar* data() const { return m_data; }
+
+    template<bool IsForceAligned,typename Dummy> struct force_aligned_impl {
+      static AlignedDerivedType run(MapBase& a) { return a.derived(); }
+    };
+
+    template<typename Dummy> struct force_aligned_impl<false,Dummy> {
+      static AlignedDerivedType run(MapBase& a) { return a.derived()._convertToForceAligned(); }
+    };
 
     /** \returns an expression equivalent to \c *this but having the \c PacketAccess constant
       * set to \c ForceAligned. Must be reimplemented by the derived class. */
-    AlignedDerivedType forceAligned() { return derived().forceAligned(); }
+    AlignedDerivedType forceAligned()
+    {
+      return force_aligned_impl<int(PacketAccess)==int(ForceAligned),Derived>::run(*this);
+    }
 
     inline const Scalar& coeff(int row, int col) const
     {
@@ -95,7 +107,11 @@ template<typename Derived> class MapBase
 
     inline Scalar& coeffRef(int index)
     {
-      return *const_cast<Scalar*>(m_data + index);
+      ei_assert(Derived::IsVectorAtCompileTime || (ei_traits<Derived>::Flags & LinearAccessBit));
+      if ( ((RowsAtCompileTime == 1) == IsRowMajor) )
+        return const_cast<Scalar*>(m_data)[index];
+      else
+        return const_cast<Scalar*>(m_data)[index*stride()];
     }
 
     template<int LoadMode>
@@ -150,6 +166,19 @@ template<typename Derived> class MapBase
                   && cols > 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)));
     }
 
+    Derived& operator=(const MapBase& other)
+    {
+      return Base::operator=(other);
+    }
+
+    template<typename OtherDerived>
+    Derived& operator=(const MatrixBase<OtherDerived>& other)
+    {
+      return Base::operator=(other);
+    }
+    
+    using Base::operator*=;
+
     template<typename OtherDerived>
     Derived& operator+=(const MatrixBase<OtherDerived>& other)
     { return derived() = forceAligned() + other; }

Eigen/src/Core/MathFunctions.h

@@ -26,6 +26,7 @@
 #define EIGEN_MATHFUNCTIONS_H
 
 template<typename T> inline typename NumTraits<T>::Real precision();
+template<typename T> inline typename NumTraits<T>::Real machine_epsilon();
 template<typename T> inline T ei_random(T a, T b);
 template<typename T> inline T ei_random();
 template<typename T> inline T ei_random_amplitude()
@@ -34,11 +35,22 @@ template<typename T> inline T ei_random_amplitude()
   else return static_cast<T>(10);
 }
 
+template<typename T> inline T ei_hypot(T x, T y)
+{
+  T _x = ei_abs(x);
+  T _y = ei_abs(y);
+  T p = std::max(_x, _y);
+  T q = std::min(_x, _y);
+  T qp = q/p;
+  return p * ei_sqrt(T(1) + qp*qp);
+}
+
 /**************
 ***   int   ***
 **************/
 
 template<> inline int precision<int>() { return 0; }
+template<> inline int machine_epsilon<int>() { return 0; }
 inline int ei_real(int x)  { return x; }
 inline int ei_imag(int)    { return 0; }
 inline int ei_conj(int x)  { return x; }
@@ -49,12 +61,8 @@ inline int ei_exp(int)  { ei_assert(false); return 0; }
 inline int ei_log(int)  { ei_assert(false); return 0; }
 inline int ei_sin(int)  { ei_assert(false); return 0; }
 inline int ei_cos(int)  { ei_assert(false); return 0; }
-
-#if EIGEN_GNUC_AT_LEAST(4,3)
-inline int ei_pow(int x, int y) { return int(std::pow(x, y)); }
-#else
+inline int ei_atan2(int, int)  { ei_assert(false); return 0; }
 inline int ei_pow(int x, int y) { return int(std::pow(double(x), y)); }
-#endif
 
 template<> inline int ei_random(int a, int b)
 {
@@ -83,6 +91,7 @@ inline bool ei_isApproxOrLessThan(int a, int b, int = precision<int>())
 **************/
 
 template<> inline float precision<float>() { return 1e-5f; }
+template<> inline float machine_epsilon<float>() { return 1.192e-07f; }
 inline float ei_real(float x)  { return x; }
 inline float ei_imag(float)    { return 0.f; }
 inline float ei_conj(float x)  { return x; }
@@ -93,6 +102,7 @@ inline float ei_exp(float x)   { return std::exp(x); }
 inline float ei_log(float x)   { return std::log(x); }
 inline float ei_sin(float x)   { return std::sin(x); }
 inline float ei_cos(float x)   { return std::cos(x); }
+inline float ei_atan2(float y, float x) { return std::atan2(y,x); }
 inline float ei_pow(float x, float y)  { return std::pow(x, y); }
 
 template<> inline float ei_random(float a, float b)
@@ -128,6 +138,8 @@ inline bool ei_isApproxOrLessThan(float a, float b, float prec = precision<float
 **************/
 
 template<> inline double precision<double>() { return 1e-11; }
+template<> inline double machine_epsilon<double>() { return 2.220e-16; }
+
 inline double ei_real(double x)  { return x; }
 inline double ei_imag(double)    { return 0.; }
 inline double ei_conj(double x)  { return x; }
@@ -138,7 +150,8 @@ inline double ei_exp(double x)   { return std::exp(x); }
 inline double ei_log(double x)   { return std::log(x); }
 inline double ei_sin(double x)   { return std::sin(x); }
 inline double ei_cos(double x)   { return std::cos(x); }
-inline double ei_pow(double x, double y)  { return std::pow(x, y); }
+inline double ei_atan2(double y, double x) { return std::atan2(y,x); }
+inline double ei_pow(double x, double y) { return std::pow(x, y); }
 
 template<> inline double ei_random(double a, double b)
 {
@@ -173,6 +186,7 @@ inline bool ei_isApproxOrLessThan(double a, double b, double prec = precision<do
 *********************/
 
 template<> inline float precision<std::complex<float> >() { return precision<float>(); }
+template<> inline float machine_epsilon<std::complex<float> >() { return machine_epsilon<float>(); }
 inline float ei_real(const std::complex<float>& x) { return std::real(x); }
 inline float ei_imag(const std::complex<float>& x) { return std::imag(x); }
 inline std::complex<float> ei_conj(const std::complex<float>& x) { return std::conj(x); }
@@ -181,6 +195,7 @@ inline float ei_abs2(const std::complex<float>& x) { return std::norm(x); }
 inline std::complex<float> ei_exp(std::complex<float> x)  { return std::exp(x); }
 inline std::complex<float> ei_sin(std::complex<float> x)  { return std::sin(x); }
 inline std::complex<float> ei_cos(std::complex<float> x)  { return std::cos(x); }
+inline std::complex<float> ei_atan2(std::complex<float>, std::complex<float> )  { ei_assert(false); return 0; }
 
 template<> inline std::complex<float> ei_random()
 {
@@ -206,6 +221,7 @@ inline bool ei_isApprox(const std::complex<float>& a, const std::complex<float>&
 **********************/
 
 template<> inline double precision<std::complex<double> >() { return precision<double>(); }
+template<> inline double machine_epsilon<std::complex<double> >() { return machine_epsilon<double>(); }
 inline double ei_real(const std::complex<double>& x) { return std::real(x); }
 inline double ei_imag(const std::complex<double>& x) { return std::imag(x); }
 inline std::complex<double> ei_conj(const std::complex<double>& x) { return std::conj(x); }
@@ -214,6 +230,7 @@ inline double ei_abs2(const std::complex<double>& x) { return std::norm(x); }
 inline std::complex<double> ei_exp(std::complex<double> x)  { return std::exp(x); }
 inline std::complex<double> ei_sin(std::complex<double> x)  { return std::sin(x); }
 inline std::complex<double> ei_cos(std::complex<double> x)  { return std::cos(x); }
+inline std::complex<double> ei_atan2(std::complex<double>, std::complex<double>)  { ei_assert(false); return 0; }
 
 template<> inline std::complex<double> ei_random()
 {
@@ -240,6 +257,7 @@ inline bool ei_isApprox(const std::complex<double>& a, const std::complex<double
 ******************/
 
 template<> inline long double precision<long double>() { return precision<double>(); }
+template<> inline long double machine_epsilon<long double>() { return 1.084e-19l; }
 inline long double ei_real(long double x)  { return x; }
 inline long double ei_imag(long double)    { return 0.; }
 inline long double ei_conj(long double x)  { return x; }
@@ -250,6 +268,7 @@ inline long double ei_exp(long double x)   { return std::exp(x); }
 inline long double ei_log(long double x)   { return std::log(x); }
 inline long double ei_sin(long double x)   { return std::sin(x); }
 inline long double ei_cos(long double x)   { return std::cos(x); }
+inline long double ei_atan2(long double y, long double x) { return std::atan2(y,x); }
 inline long double ei_pow(long double x, long double y)  { return std::pow(x, y); }
 
 template<> inline long double ei_random(long double a, long double b)

Eigen/src/Core/Matrix.h

@@ -25,6 +25,12 @@
 #ifndef EIGEN_MATRIX_H
 #define EIGEN_MATRIX_H
 
+#ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
+# define EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED for(int i=0;i<base().size();++i) coeffRef(i)=Scalar(0);
+#else
+# define EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
+#endif
+
 /** \class Matrix
   *
   * \brief The matrix class, also used for vectors and row-vectors
@@ -40,8 +46,8 @@
   * \param _Cols Number of columns, or \b Dynamic
   *
   * The remaining template parameters are optional -- in most cases you don't have to worry about them.
-  * \param _Options A combination of either \b Matrix_RowMajor or \b Matrix_ColMajor, and of either
-  *                 \b Matrix_AutoAlign or \b Matrix_DontAlign.
+  * \param _Options A combination of either \b RowMajor or \b ColMajor, and of either
+  *                 \b AutoAlign or \b DontAlign.
   *                 The former controls storage order, and defaults to column-major. The latter controls alignment, which is required
   *                 for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size.
   * \param _MaxRows Maximum number of rows. Defaults to \a _Rows (\ref maxrows "note").
@@ -99,6 +105,7 @@
   * when the exact numbers of rows and columns are not known are compile-time, but it is known at compile-time that they cannot
   * exceed a certain value. This happens when taking dynamic-size blocks inside fixed-size matrices: in this case _MaxRows and _MaxCols
   * are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.</dd>
+  * </dl>
   *
   * \see MatrixBase for the majority of the API methods for matrices
   */
@@ -112,8 +119,7 @@ struct ei_traits<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
     MaxRowsAtCompileTime = _MaxRows,
     MaxColsAtCompileTime = _MaxCols,
     Flags = ei_compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret,
-    CoeffReadCost = NumTraits<Scalar>::ReadCost,
-    SupportedAccessPatterns = RandomAccessPattern
+    CoeffReadCost = NumTraits<Scalar>::ReadCost
   };
 };
 
@@ -133,33 +139,12 @@ class Matrix
     ei_matrix_storage<Scalar, MaxSizeAtCompileTime, RowsAtCompileTime, ColsAtCompileTime, Options> m_storage;
 
   public:
-    enum { NeedsToAlign = (Options&Matrix_AutoAlign) == Matrix_AutoAlign
+    enum { NeedsToAlign = (Options&AutoAlign) == AutoAlign
                           && SizeAtCompileTime!=Dynamic && ((sizeof(Scalar)*SizeAtCompileTime)%16)==0 };
-    typedef typename ei_meta_if<NeedsToAlign, ei_byte_forcing_aligned_malloc, char>::ret ByteAlignedAsNeeded;
-    void *operator new(size_t size) throw()
-    {
-      return ei_aligned_malloc<ByteAlignedAsNeeded>(size);
-    }
-
-    void *operator new(size_t, void *ptr) throw()
-    {
-      return static_cast<void*>(ptr);
-    }
-
-    void *operator new[](size_t size) throw()
-    {
-      return ei_aligned_malloc<ByteAlignedAsNeeded>(size);
-    }
-
-    void *operator new[](size_t, void *ptr) throw()
-    {
-      return static_cast<void*>(ptr);
-    }
-
-    void operator delete(void * ptr) { ei_aligned_free(static_cast<ByteAlignedAsNeeded *>(ptr), 0); }
-    void operator delete[](void * ptr) { ei_aligned_free(static_cast<ByteAlignedAsNeeded *>(ptr), 0); }
-
-  public:
+    EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
+    
+    Base& base() { return *static_cast<Base*>(this); }
+    const Base& base() const { return *static_cast<const Base*>(this); }
 
     EIGEN_STRONG_INLINE int rows() const { return m_storage.rows(); }
     EIGEN_STRONG_INLINE int cols() const { return m_storage.cols(); }
@@ -249,13 +234,18 @@ class Matrix
       */
     inline void resize(int rows, int cols)
     {
-      ei_assert(rows > 0
-          && (MaxRowsAtCompileTime == Dynamic || MaxRowsAtCompileTime >= rows)
-          && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
-          && cols > 0
-          && (MaxColsAtCompileTime == Dynamic || MaxColsAtCompileTime >= cols)
-          && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
-      m_storage.resize(rows * cols, rows, cols);
+      ei_assert((MaxRowsAtCompileTime == Dynamic || MaxRowsAtCompileTime >= rows)
+             && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
+             && (MaxColsAtCompileTime == Dynamic || MaxColsAtCompileTime >= cols)
+             && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
+      #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
+        int size = rows*cols;
+        bool size_changed = size != this->size();
+        m_storage.resize(size, rows, cols);
+        if(size_changed) EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
+      #else
+        m_storage.resize(rows*cols, rows, cols);
+      #endif
     }
 
     /** Resizes \c *this to a vector of length \a size
@@ -264,57 +254,33 @@ class Matrix
       */
     inline void resize(int size)
     {
-      ei_assert(size>0 && "a vector cannot be resized to 0 length");
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
+      ei_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == size);
+      #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
+        bool size_changed = size != this->size();
+      #endif
       if(RowsAtCompileTime == 1)
         m_storage.resize(size, 1, size);
       else
         m_storage.resize(size, size, 1);
-    }
-
-    /** Copies the value of the expression \a other into \c *this.
-      *
-      * \warning Note that the sizes of \c *this and \a other must match.
-      * If you want automatic resizing, then you must use the function set().
-      *
-      * As a special exception, copying a row-vector into a vector (and conversely)
-      * is allowed.
-      *
-      * \sa set()
-      */
-    template<typename OtherDerived>
-    EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase<OtherDerived>& other)
-    {
-      ei_assert(m_storage.data()!=0 && "you cannot use operator= with a non initialized matrix (instead use set()");
-      return Base::operator=(other.derived());
+      #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
+        if(size_changed) EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
+      #endif
     }
 
     /** Copies the value of the expression \a other into \c *this with automatic resizing.
       *
-      * This function is the same than the assignment operator = excepted that \c *this might
-      * be resized to match the dimensions of \a other.
+      * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
+      * it will be initialized.
       *
       * Note that copying a row-vector into a vector (and conversely) is allowed.
       * The resizing, if any, is then done in the appropriate way so that row-vectors
       * remain row-vectors and vectors remain vectors.
-      *
-      * \sa operator=()
       */
     template<typename OtherDerived>
-    inline Matrix& set(const MatrixBase<OtherDerived>& other)
+    EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase<OtherDerived>& other)
     {
-      if(RowsAtCompileTime == 1)
-      {
-        ei_assert(other.isVector());
-        resize(1, other.size());
-      }
-      else if(ColsAtCompileTime == 1)
-      {
-        ei_assert(other.isVector());
-        resize(other.size(), 1);
-      }
-      else resize(other.rows(), other.cols());
-      return Base::operator=(other.derived());
+      return _set(other);
     }
 
     /** This is a special case of the templated operator=. Its purpose is to
@@ -322,7 +288,7 @@ class Matrix
       */
     EIGEN_STRONG_INLINE Matrix& operator=(const Matrix& other)
     {
-      return operator=<Matrix>(other);
+      return _set(other);
     }
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATOR(Matrix, +=)
@@ -334,32 +300,25 @@ class Matrix
       *
       * For fixed-size matrices, does nothing.
       *
-      * For dynamic-size matrices, creates an empty matrix of size null.
-      * \warning while creating such an \em null matrix is allowed, it \b cannot
-      * \b be \b used before having being resized or initialized with the function set().
-      * In particular, initializing a null matrix with operator = is not supported.
-      * Finally, this constructor is the unique way to create null matrices: resizing
+      * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix
+      * is called a null matrix. This constructor is the unique way to create null matrices: resizing
       * a matrix to 0 is not supported.
-      * Here are some examples:
-      * \code
-      * MatrixXf r = MatrixXf::Random(3,4); // create a random matrix of floats
-      * MatrixXf m1, m2;  // creates two null matrices of float
       *
-      * m1 = r;           // illegal (raise an assertion)
-      * r = m1;           // illegal (raise an assertion)
-      * m1 = m2;          // illegal (raise an assertion)
-      * m1.set(r);        // OK
-      * m2.resize(3,4);
-      * m2 = r;           // OK
-      * \endcode
-      *
-      * \sa resize(int,int), set()
+      * \sa resize(int,int)
       */
     EIGEN_STRONG_INLINE explicit Matrix() : m_storage()
     {
-      ei_assert(RowsAtCompileTime > 0 && ColsAtCompileTime > 0);
+      _check_template_params();
+      EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
     }
 
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal */
+    Matrix(ei_constructor_without_unaligned_array_assert)
+      : m_storage(ei_constructor_without_unaligned_array_assert())
+    {EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED}
+#endif
+
     /** Constructs a vector or row-vector with given dimension. \only_for_vectors
       *
       * Note that this is only useful for dynamic-size vectors. For fixed-size vectors,
@@ -369,9 +328,11 @@ class Matrix
     EIGEN_STRONG_INLINE explicit Matrix(int dim)
       : m_storage(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim)
     {
+      _check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix)
       ei_assert(dim > 0);
       ei_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim);
+      EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
     }
 
     /** This constructor has two very different behaviors, depending on the type of *this.
@@ -386,6 +347,7 @@ class Matrix
       */
     EIGEN_STRONG_INLINE Matrix(int x, int y) : m_storage(x*y, x, y)
     {
+      _check_template_params();
       if((RowsAtCompileTime == 1 && ColsAtCompileTime == 2)
       || (RowsAtCompileTime == 2 && ColsAtCompileTime == 1))
       {
@@ -396,11 +358,13 @@ class Matrix
       {
         ei_assert(x > 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == x)
                && y > 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == y));
+        EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
       }
     }
     /** constructs an initialized 2D vector with given coefficients */
     EIGEN_STRONG_INLINE Matrix(const float& x, const float& y)
     {
+      _check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 2)
       m_storage.data()[0] = x;
       m_storage.data()[1] = y;
@@ -408,6 +372,7 @@ class Matrix
     /** constructs an initialized 2D vector with given coefficients */
     EIGEN_STRONG_INLINE Matrix(const double& x, const double& y)
     {
+      _check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 2)
       m_storage.data()[0] = x;
       m_storage.data()[1] = y;
@@ -415,6 +380,7 @@ class Matrix
     /** constructs an initialized 3D vector with given coefficients */
     EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z)
     {
+      _check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 3)
       m_storage.data()[0] = x;
       m_storage.data()[1] = y;
@@ -423,6 +389,7 @@ class Matrix
     /** constructs an initialized 4D vector with given coefficients */
     EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w)
     {
+      _check_template_params();
       EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 4)
       m_storage.data()[0] = x;
       m_storage.data()[1] = y;
@@ -437,14 +404,15 @@ class Matrix
     EIGEN_STRONG_INLINE Matrix(const MatrixBase<OtherDerived>& other)
              : m_storage(other.rows() * other.cols(), other.rows(), other.cols())
     {
-      ei_assign_selector<Matrix,OtherDerived,false>::run(*this, other.derived());
-      //Base::operator=(other.derived());
+      _check_template_params();
+      _set_noalias(other);
     }
     /** Copy constructor */
     EIGEN_STRONG_INLINE Matrix(const Matrix& other)
             : Base(), m_storage(other.rows() * other.cols(), other.rows(), other.cols())
     {
-      Base::lazyAssign(other);
+      _check_template_params();
+      _set_noalias(other);
     }
     /** Destructor */
     inline ~Matrix() {}
@@ -452,18 +420,14 @@ class Matrix
     /** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the
       * data pointers.
       */
-    inline void swap(Matrix& other)
-    {
-      if (Base::SizeAtCompileTime==Dynamic)
-        m_storage.swap(other.m_storage);
-      else
-        this->Base::swap(other);
-    }
+    template<typename OtherDerived>
+    void swap(const MatrixBase<OtherDerived>& other);
 
     /** \name Map
-      * These are convenience functions returning Map objects. The Map() static functions return unaligned Map objects,
-      * while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned
-      * \a data pointers.
+      * These are convenience functions returning Map objects.
+      *
+      * \warning Do not use MapAligned in the Eigen 2.0. Mapping aligned arrays will be fully
+      * supported in Eigen 3.0 (already implemented in the development branch)
       *
       * \see class Map
       */
@@ -495,6 +459,25 @@ class Matrix
     { return AlignedMapType(data, rows, cols); }
     //@}
 
+    using Base::setConstant;
+    Matrix& setConstant(int size, const Scalar& value);
+    Matrix& setConstant(int rows, int cols, const Scalar& value);
+
+    using Base::setZero;
+    Matrix& setZero(int size);
+    Matrix& setZero(int rows, int cols);
+
+    using Base::setOnes;
+    Matrix& setOnes(int size);
+    Matrix& setOnes(int rows, int cols);
+
+    using Base::setRandom;
+    Matrix& setRandom(int size);
+    Matrix& setRandom(int rows, int cols);
+
+    using Base::setIdentity;
+    Matrix& setIdentity(int rows, int cols);
+
 /////////// Geometry module ///////////
 
     template<typename OtherDerived>
@@ -506,8 +489,113 @@ class Matrix
     #ifdef EIGEN_MATRIX_PLUGIN
     #include EIGEN_MATRIX_PLUGIN
     #endif
+
+  private:
+    /** \internal Resizes *this in preparation for assigning \a other to it.
+      * Takes care of doing all the checking that's needed.
+      *
+      * Note that copying a row-vector into a vector (and conversely) is allowed.
+      * The resizing, if any, is then done in the appropriate way so that row-vectors
+      * remain row-vectors and vectors remain vectors.
+      */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE void _resize_to_match(const MatrixBase<OtherDerived>& other)
+    {
+      if(RowsAtCompileTime == 1)
+      {
+        ei_assert(other.isVector());
+        resize(1, other.size());
+      }
+      else if(ColsAtCompileTime == 1)
+      {
+        ei_assert(other.isVector());
+        resize(other.size(), 1);
+      }
+      else resize(other.rows(), other.cols());
+    }
+
+    /** \internal Copies the value of the expression \a other into \c *this with automatic resizing.
+      *
+      * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized),
+      * it will be initialized.
+      *
+      * Note that copying a row-vector into a vector (and conversely) is allowed.
+      * The resizing, if any, is then done in the appropriate way so that row-vectors
+      * remain row-vectors and vectors remain vectors.
+      *
+      * \sa operator=(const MatrixBase<OtherDerived>&), _set_noalias()
+      */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Matrix& _set(const MatrixBase<OtherDerived>& other)
+    {
+      // this enum introduced to fix compilation with gcc 3.3
+      enum { cond = int(OtherDerived::Flags) & EvalBeforeAssigningBit };
+      _set_selector(other.derived(), typename ei_meta_if<bool(cond), ei_meta_true, ei_meta_false>::ret());
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const ei_meta_true&) { _set_noalias(other.eval()); }
+
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const ei_meta_false&) { _set_noalias(other); }
+
+    /** \internal Like _set() but additionally makes the assumption that no aliasing effect can happen (which
+      * is the case when creating a new matrix) so one can enforce lazy evaluation.
+      *
+      * \sa operator=(const MatrixBase<OtherDerived>&), _set()
+      */
+    template<typename OtherDerived>
+    EIGEN_STRONG_INLINE Matrix& _set_noalias(const MatrixBase<OtherDerived>& other)
+    {
+      _resize_to_match(other);
+      // the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because
+      // it wouldn't allow to copy a row-vector into a column-vector.
+      return ei_assign_selector<Matrix,OtherDerived,false>::run(*this, other.derived());
+    }
+
+    static EIGEN_STRONG_INLINE void _check_template_params()
+    {
+        EIGEN_STATIC_ASSERT((_Rows > 0
+                        && _Cols > 0
+                        && _MaxRows <= _Rows
+                        && _MaxCols <= _Cols
+                        && (_Options & (AutoAlign|RowMajor)) == _Options),
+          INVALID_MATRIX_TEMPLATE_PARAMETERS)
+    }
+    
+    template<typename MatrixType, typename OtherDerived, bool IsSameType, bool IsDynamicSize>
+    friend struct ei_matrix_swap_impl;
 };
 
+template<typename MatrixType, typename OtherDerived,
+         bool IsSameType = ei_is_same_type<MatrixType, OtherDerived>::ret,
+         bool IsDynamicSize = MatrixType::SizeAtCompileTime==Dynamic>
+struct ei_matrix_swap_impl
+{
+  static inline void run(MatrixType& matrix, MatrixBase<OtherDerived>& other)
+  {
+    matrix.base().swap(other);
+  }
+};
+
+template<typename MatrixType, typename OtherDerived>
+struct ei_matrix_swap_impl<MatrixType, OtherDerived, true, true>
+{
+  static inline void run(MatrixType& matrix, MatrixBase<OtherDerived>& other)
+  {
+    matrix.m_storage.swap(other.derived().m_storage);
+  }
+};
+
+template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
+template<typename OtherDerived>
+inline void Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::swap(const MatrixBase<OtherDerived>& other)
+{
+  ei_matrix_swap_impl<Matrix, OtherDerived>::run(*this, *const_cast<MatrixBase<OtherDerived>*>(&other));
+}
+
+
 /** \defgroup matrixtypedefs Global matrix typedefs
   *
   * \ingroup Core_Module

Eigen/src/Core/MatrixBase.h

@@ -136,12 +136,6 @@ template<typename Derived> class MatrixBase
           */
     };
 
-    /** Default constructor. Just checks at compile-time for self-consistency of the flags. */
-    MatrixBase()
-    {
-      ei_assert(ei_are_flags_consistent<Flags>::ret);
-    }
-
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** This is the "real scalar" type; if the \a Scalar type is already real numbers
       * (e.g. int, float or double) then \a RealScalar is just the same as \a Scalar. If
@@ -165,7 +159,7 @@ template<typename Derived> class MatrixBase
     inline int size() const { return rows() * cols(); }
     /** \returns the number of nonzero coefficients which is in practice the number
       * of stored coefficients. */
-    inline int nonZeros() const { return derived.nonZeros(); }
+    inline int nonZeros() const { return size(); }
     /** \returns true if either the number of rows or the number of columns is equal to 1.
       * In other words, this function returns
       * \code rows()==1 || cols()==1 \endcode
@@ -229,10 +223,6 @@ template<typename Derived> class MatrixBase
     template<typename OtherDerived>
     Derived& operator=(const MatrixBase<OtherDerived>& other);
 
-    /** Copies \a other into *this without evaluating other. \returns a reference to *this. */
-    template<typename OtherDerived>
-    Derived& lazyAssign(const MatrixBase<OtherDerived>& other);
-
     /** Special case of the template operator=, in order to prevent the compiler
       * from generating a default operator= (issue hit with g++ 4.1)
       */
@@ -241,6 +231,11 @@ template<typename Derived> class MatrixBase
       return this->operator=<Derived>(other);
     }
 
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** Copies \a other into *this without evaluating other. \returns a reference to *this. */
+    template<typename OtherDerived>
+    Derived& lazyAssign(const MatrixBase<OtherDerived>& other);
+
     /** Overloaded for cache friendly product evaluation */
     template<typename Lhs, typename Rhs>
     Derived& lazyAssign(const Product<Lhs,Rhs,CacheFriendlyProduct>& product);
@@ -249,10 +244,7 @@ template<typename Derived> class MatrixBase
     template<typename OtherDerived>
     Derived& lazyAssign(const Flagged<OtherDerived, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit>& other)
     { return lazyAssign(other._expression()); }
-
-    /** Overloaded for sparse product evaluation */
-    template<typename Derived1, typename Derived2>
-    Derived& lazyAssign(const Product<Derived1,Derived2,SparseProduct>& product);
+#endif // not EIGEN_PARSED_BY_DOXYGEN
 
     CommaInitializer<Derived> operator<< (const Scalar& s);
 
@@ -346,13 +338,12 @@ template<typename Derived> class MatrixBase
 		solveTriangular(const MatrixBase<OtherDerived>& other) const;
 
     template<typename OtherDerived>
-    void solveTriangularInPlace(MatrixBase<OtherDerived>& other) const;
+    void solveTriangularInPlace(const MatrixBase<OtherDerived>& other) const;
 
 
     template<typename OtherDerived>
     Scalar dot(const MatrixBase<OtherDerived>& other) const;
     RealScalar squaredNorm() const;
-    RealScalar norm2() const;
     RealScalar norm()  const;
     const PlainMatrixType normalized() const;
     void normalize();
@@ -448,6 +439,7 @@ template<typename Derived> class MatrixBase
 
     const DiagonalMatrix<Derived> asDiagonal() const;
 
+    void fill(const Scalar& value);
     Derived& setConstant(const Scalar& value);
     Derived& setZero();
     Derived& setOnes();
@@ -465,6 +457,7 @@ template<typename Derived> class MatrixBase
                            RealScalar prec = precision<Scalar>()) const;
 
     bool isApproxToConstant(const Scalar& value, RealScalar prec = precision<Scalar>()) const;
+    bool isConstant(const Scalar& value, RealScalar prec = precision<Scalar>()) const;
     bool isZero(RealScalar prec = precision<Scalar>()) const;
     bool isOnes(RealScalar prec = precision<Scalar>()) const;
     bool isIdentity(RealScalar prec = precision<Scalar>()) const;
@@ -533,8 +526,11 @@ template<typename Derived> class MatrixBase
     typename ei_traits<Derived>::Scalar minCoeff() const;
     typename ei_traits<Derived>::Scalar maxCoeff() const;
 
-    typename ei_traits<Derived>::Scalar minCoeff(int* row, int* col = 0) const;
-    typename ei_traits<Derived>::Scalar maxCoeff(int* row, int* col = 0) const;
+    typename ei_traits<Derived>::Scalar minCoeff(int* row, int* col) const;
+    typename ei_traits<Derived>::Scalar maxCoeff(int* row, int* col) const;
+
+    typename ei_traits<Derived>::Scalar minCoeff(int* index) const;
+    typename ei_traits<Derived>::Scalar maxCoeff(int* index) const;
 
     template<typename BinaryOp>
     typename ei_result_of<BinaryOp(typename ei_traits<Derived>::Scalar)>::type
@@ -559,6 +555,7 @@ template<typename Derived> class MatrixBase
 
     bool all(void) const;
     bool any(void) const;
+    int count() const;
 
     const PartialRedux<Derived,Horizontal> rowwise() const;
     const PartialRedux<Derived,Vertical> colwise() const;
@@ -593,9 +590,6 @@ template<typename Derived> class MatrixBase
 
     const LLT<PlainMatrixType>  llt() const;
     const LDLT<PlainMatrixType> ldlt() const;
-    // deprecated:
-    const Cholesky<PlainMatrixType> cholesky() const;
-    const CholeskyWithoutSquareRoot<PlainMatrixType> choleskyNoSqrt() const;
 
 /////////// QR module ///////////
 
@@ -615,9 +609,36 @@ template<typename Derived> class MatrixBase
     PlainMatrixType unitOrthogonal(void) const;
     Matrix<Scalar,3,1> eulerAngles(int a0, int a1, int a2) const;
 
+/////////// Sparse module ///////////
+
+    // dense = spasre * dense
+    template<typename Derived1, typename Derived2>
+    Derived& lazyAssign(const SparseProduct<Derived1,Derived2,SparseTimeDenseProduct>& product);
+    // dense = dense * spasre
+    template<typename Derived1, typename Derived2>
+    Derived& lazyAssign(const SparseProduct<Derived1,Derived2,DenseTimeSparseProduct>& product);
+
     #ifdef EIGEN_MATRIXBASE_PLUGIN
     #include EIGEN_MATRIXBASE_PLUGIN
     #endif
+
+  protected:
+    /** Default constructor. Do nothing. */
+    MatrixBase()
+    {
+      /* Just checks for self-consistency of the flags.
+       * Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down
+       */
+#ifdef EIGEN_INTERNAL_DEBUGGING
+      EIGEN_STATIC_ASSERT(ei_are_flags_consistent<Flags>::ret,
+                          INVALID_MATRIXBASE_TEMPLATE_PARAMETERS)
+#endif
+    }
+
+  private:
+    explicit MatrixBase(int);
+    MatrixBase(int,int);
+    template<typename OtherDerived> explicit MatrixBase(const MatrixBase<OtherDerived>&);
 };
 
 #endif // EIGEN_MATRIXBASE_H

Eigen/src/Core/MatrixStorage.h

@@ -2,7 +2,7 @@
 // for linear algebra. Eigen itself is part of the KDE project.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -26,25 +26,33 @@
 #ifndef EIGEN_MATRIXSTORAGE_H
 #define EIGEN_MATRIXSTORAGE_H
 
+struct ei_constructor_without_unaligned_array_assert {};
+
 /** \internal
   * Static array automatically aligned if the total byte size is a multiple of 16 and the matrix options require auto alignment
   */
 template <typename T, int Size, int MatrixOptions,
-          bool Align = (MatrixOptions&Matrix_AutoAlign) && (((Size*sizeof(T))&0xf)==0)
+          bool Align = (MatrixOptions&AutoAlign) && (((Size*sizeof(T))&0xf)==0)
 > struct ei_matrix_array
 {
   EIGEN_ALIGN_128 T array[Size];
 
   ei_matrix_array()
   {
+    #ifndef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
     ei_assert((reinterpret_cast<size_t>(array) & 0xf) == 0
-              && "this assertion is explained here: http://eigen.tuxfamily.org/api/UnalignedArrayAssert.html  **** READ THIS WEB PAGE !!! ****");
+              && "this assertion is explained here: http://eigen.tuxfamily.org/dox/UnalignedArrayAssert.html  **** READ THIS WEB PAGE !!! ****");
+    #endif
   }
+
+  ei_matrix_array(ei_constructor_without_unaligned_array_assert) {}
 };
 
 template <typename T, int Size, int MatrixOptions> struct ei_matrix_array<T,Size,MatrixOptions,false>
 {
   T array[Size];
+  ei_matrix_array() {}
+  ei_matrix_array(ei_constructor_without_unaligned_array_assert) {}
 };
 
 /** \internal
@@ -66,6 +74,8 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class ei_matr
     ei_matrix_array<T,Size,_Options> m_data;
   public:
     inline explicit ei_matrix_storage() {}
+    inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
+      : m_data(ei_constructor_without_unaligned_array_assert()) {}
     inline ei_matrix_storage(int,int,int) {}
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); }
     inline static int rows(void) {return _Rows;}
@@ -83,6 +93,8 @@ template<typename T, int Size, int _Options> class ei_matrix_storage<T, Size, Dy
     int m_cols;
   public:
     inline explicit ei_matrix_storage() : m_rows(0), m_cols(0) {}
+    inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
+      : m_data(ei_constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {}
     inline ei_matrix_storage(int, int rows, int cols) : m_rows(rows), m_cols(cols) {}
     inline ~ei_matrix_storage() {}
     inline void swap(ei_matrix_storage& other)
@@ -105,6 +117,8 @@ template<typename T, int Size, int _Cols, int _Options> class ei_matrix_storage<
     int m_rows;
   public:
     inline explicit ei_matrix_storage() : m_rows(0) {}
+    inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
+      : m_data(ei_constructor_without_unaligned_array_assert()), m_rows(0) {}
     inline ei_matrix_storage(int, int rows, int) : m_rows(rows) {}
     inline ~ei_matrix_storage() {}
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
@@ -125,6 +139,8 @@ template<typename T, int Size, int _Rows, int _Options> class ei_matrix_storage<
     int m_cols;
   public:
     inline explicit ei_matrix_storage() : m_cols(0) {}
+    inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
+      : m_data(ei_constructor_without_unaligned_array_assert()), m_cols(0) {}
     inline ei_matrix_storage(int, int, int cols) : m_cols(cols) {}
     inline ~ei_matrix_storage() {}
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
@@ -146,9 +162,11 @@ template<typename T, int _Options> class ei_matrix_storage<T, Dynamic, Dynamic,
     int m_cols;
   public:
     inline explicit ei_matrix_storage() : m_data(0), m_rows(0), m_cols(0) {}
+    inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert)
+       : m_data(0), m_rows(0), m_cols(0) {}
     inline ei_matrix_storage(int size, int rows, int cols)
-      : m_data(ei_aligned_malloc<T>(size)), m_rows(rows), m_cols(cols) {}
-    inline ~ei_matrix_storage() { ei_aligned_free(m_data, m_rows*m_cols); }
+      : m_data(ei_aligned_new<T>(size)), m_rows(rows), m_cols(cols) {}
+    inline ~ei_matrix_storage() { ei_aligned_delete(m_data, m_rows*m_cols); }
     inline void swap(ei_matrix_storage& other)
     { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); }
     inline int rows(void) const {return m_rows;}
@@ -157,8 +175,11 @@ template<typename T, int _Options> class ei_matrix_storage<T, Dynamic, Dynamic,
     {
       if(size != m_rows*m_cols)
       {
-        ei_aligned_free(m_data, m_rows*m_cols);
-        m_data = ei_aligned_malloc<T>(size);
+        ei_aligned_delete(m_data, m_rows*m_cols);
+        if (size)
+          m_data = ei_aligned_new<T>(size);
+        else
+          m_data = 0;
       }
       m_rows = rows;
       m_cols = cols;
@@ -174,8 +195,9 @@ template<typename T, int _Rows, int _Options> class ei_matrix_storage<T, Dynamic
     int m_cols;
   public:
     inline explicit ei_matrix_storage() : m_data(0), m_cols(0) {}
-    inline ei_matrix_storage(int size, int, int cols) : m_data(ei_aligned_malloc<T>(size)), m_cols(cols) {}
-    inline ~ei_matrix_storage() { ei_aligned_free(m_data, _Rows*m_cols); }
+    inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {}
+    inline ei_matrix_storage(int size, int, int cols) : m_data(ei_aligned_new<T>(size)), m_cols(cols) {}
+    inline ~ei_matrix_storage() { ei_aligned_delete(m_data, _Rows*m_cols); }
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
     inline static int rows(void) {return _Rows;}
     inline int cols(void) const {return m_cols;}
@@ -183,8 +205,11 @@ template<typename T, int _Rows, int _Options> class ei_matrix_storage<T, Dynamic
     {
       if(size != _Rows*m_cols)
       {
-        ei_aligned_free(m_data, _Rows*m_cols);
-        m_data = ei_aligned_malloc<T>(size);
+        ei_aligned_delete(m_data, _Rows*m_cols);
+        if (size)
+          m_data = ei_aligned_new<T>(size);
+        else
+          m_data = 0;
       }
       m_cols = cols;
     }
@@ -199,8 +224,9 @@ template<typename T, int _Cols, int _Options> class ei_matrix_storage<T, Dynamic
     int m_rows;
   public:
     inline explicit ei_matrix_storage() : m_data(0), m_rows(0) {}
-    inline ei_matrix_storage(int size, int rows, int) : m_data(ei_aligned_malloc<T>(size)), m_rows(rows) {}
-    inline ~ei_matrix_storage() { ei_aligned_free(m_data, _Cols*m_rows); }
+    inline ei_matrix_storage(ei_constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {}
+    inline ei_matrix_storage(int size, int rows, int) : m_data(ei_aligned_new<T>(size)), m_rows(rows) {}
+    inline ~ei_matrix_storage() { ei_aligned_delete(m_data, _Cols*m_rows); }
     inline void swap(ei_matrix_storage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
     inline int rows(void) const {return m_rows;}
     inline static int cols(void) {return _Cols;}
@@ -208,8 +234,11 @@ template<typename T, int _Cols, int _Options> class ei_matrix_storage<T, Dynamic
     {
       if(size != m_rows*_Cols)
       {
-        ei_aligned_free(m_data, _Cols*m_rows);
-        m_data = ei_aligned_malloc<T>(size);
+        ei_aligned_delete(m_data, _Cols*m_rows);
+        if (size)
+          m_data = ei_aligned_new<T>(size);
+        else
+          m_data = 0;
       }
       m_rows = rows;
     }

Eigen/src/Core/Minor.h

@@ -25,7 +25,8 @@
 #ifndef EIGEN_MINOR_H
 #define EIGEN_MINOR_H
 
-/** \class Minor
+/** \nonstableyet 
+  * \class Minor
   *
   * \brief Expression of a minor
   *
@@ -92,7 +93,8 @@ template<typename MatrixType> class Minor
     const int m_row, m_col;
 };
 
-/** \return an expression of the (\a row, \a col)-minor of *this,
+/** \nonstableyet 
+  * \return an expression of the (\a row, \a col)-minor of *this,
   * i.e. an expression constructed from *this by removing the specified
   * row and column.
   *
@@ -108,7 +110,8 @@ MatrixBase<Derived>::minor(int row, int col)
   return Minor<Derived>(derived(), row, col);
 }
 
-/** This is the const version of minor(). */
+/** \nonstableyet 
+  * This is the const version of minor(). */
 template<typename Derived>
 inline const Minor<Derived>
 MatrixBase<Derived>::minor(int row, int col) const

Eigen/src/Core/NestByValue.h

@@ -38,18 +38,8 @@
   * \sa MatrixBase::nestByValue()
   */
 template<typename ExpressionType>
-struct ei_traits<NestByValue<ExpressionType> >
-{
-  typedef typename ExpressionType::Scalar Scalar;
-  enum {
-    RowsAtCompileTime = ExpressionType::RowsAtCompileTime,
-    ColsAtCompileTime = ExpressionType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = ExpressionType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = ExpressionType::MaxColsAtCompileTime,
-    Flags = ExpressionType::Flags,
-    CoeffReadCost = ExpressionType::CoeffReadCost
-  };
-};
+struct ei_traits<NestByValue<ExpressionType> > : public ei_traits<ExpressionType>
+{};
 
 template<typename ExpressionType> class NestByValue
   : public MatrixBase<NestByValue<ExpressionType> >
@@ -110,6 +100,9 @@ template<typename ExpressionType> class NestByValue
 
   protected:
     const ExpressionType m_expression;
+
+  private:
+    NestByValue& operator=(const NestByValue&);
 };
 
 /** \returns an expression of the temporary version of *this.

Eigen/src/Core/Part.h

@@ -26,7 +26,8 @@
 #ifndef EIGEN_PART_H
 #define EIGEN_PART_H
 
-/** \class Part
+/** \nonstableyet
+  * \class Part
   *
   * \brief Expression of a triangular matrix extracted from a given matrix
   *
@@ -43,18 +44,13 @@
   * \sa MatrixBase::part()
   */
 template<typename MatrixType, unsigned int Mode>
-struct ei_traits<Part<MatrixType, Mode> >
+struct ei_traits<Part<MatrixType, Mode> > : ei_traits<MatrixType>
 {
-  typedef typename MatrixType::Scalar Scalar;
   typedef typename ei_nested<MatrixType>::type MatrixTypeNested;
   typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
-    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
-    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
-    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
     Flags = (_MatrixTypeNested::Flags & (HereditaryBits) & (~(PacketAccessBit | DirectAccessBit | LinearAccessBit))) | Mode,
-    CoeffReadCost = _MatrixTypeNested::CoeffReadCost
+    CoeffReadCost = _MatrixTypeNested::CoeffReadCost + ConditionalJumpCost
   };
 };
 
@@ -121,18 +117,21 @@ template<typename MatrixType, unsigned int Mode> class Part
     const Block<Part, RowsAtCompileTime, 1> col(int i) { return Base::col(i); }
     const Block<Part, RowsAtCompileTime, 1> col(int i) const { return Base::col(i); }
 
-    template<typename OtherDerived/*, int OtherMode*/>
+    template<typename OtherDerived>
     void swap(const MatrixBase<OtherDerived>& other)
     {
-      Part<SwapWrapper<MatrixType>,Mode>(SwapWrapper<MatrixType>(const_cast<MatrixType&>(m_matrix))).lazyAssign(other.derived());
+      Part<SwapWrapper<MatrixType>,Mode>(const_cast<MatrixType&>(m_matrix)).lazyAssign(other.derived());
     }
 
   protected:
-
     const typename MatrixType::Nested m_matrix;
+
+  private:
+    Part& operator=(const Part&);
 };
 
-/** \returns an expression of a triangular matrix extracted from the current matrix
+/** \nonstableyet
+  * \returns an expression of a triangular matrix extracted from the current matrix
   *
   * The parameter \a Mode can have the following values: \c UpperTriangular, \c StrictlyUpperTriangular, \c UnitUpperTriangular,
   * \c LowerTriangular, \c StrictlyLowerTriangular, \c UnitLowerTriangular.
@@ -283,7 +282,8 @@ void Part<MatrixType, Mode>::lazyAssign(const Other& other)
     >::run(m_matrix.const_cast_derived(), other.derived());
 }
 
-/** \returns a lvalue pseudo-expression allowing to perform special operations on \c *this.
+/** \nonstableyet
+  * \returns a lvalue pseudo-expression allowing to perform special operations on \c *this.
   *
   * The \a Mode parameter can have the following values: \c UpperTriangular, \c StrictlyUpperTriangular, \c LowerTriangular,
   * \c StrictlyLowerTriangular, \c SelfAdjoint.

Eigen/src/Core/Product.h

@@ -79,7 +79,6 @@ struct ProductReturnType<Lhs,Rhs,CacheFriendlyProduct>
  *    - NormalProduct
  *    - CacheFriendlyProduct
  *    - DiagonalProduct
- *    - SparseProduct
  */
 template<typename Lhs, typename Rhs> struct ei_product_mode
 {
@@ -87,8 +86,6 @@ template<typename Lhs, typename Rhs> struct ei_product_mode
 
     value = ((Rhs::Flags&Diagonal)==Diagonal) || ((Lhs::Flags&Diagonal)==Diagonal)
           ? DiagonalProduct
-          : (Rhs::Flags & Lhs::Flags & SparseBit)
-          ? SparseProduct
           : Lhs::MaxColsAtCompileTime == Dynamic
             && ( Lhs::MaxRowsAtCompileTime == Dynamic
               || Rhs::MaxColsAtCompileTime == Dynamic )
@@ -302,7 +299,7 @@ template<typename OtherDerived>
 inline Derived &
 MatrixBase<Derived>::operator*=(const MatrixBase<OtherDerived> &other)
 {
-  return *this = *this * other;
+  return derived() = derived() * other.derived();
 }
 
 /***************************************************************************
@@ -573,7 +570,7 @@ struct ei_cache_friendly_product_selector<ProductType,LhsRows,ColMajor,HasDirect
        _res = &res.coeffRef(0);
     else
     {
-      _res = ei_aligned_stack_alloc(Scalar,res.size());
+      _res = ei_aligned_stack_new(Scalar,res.size());
       Map<Matrix<Scalar,DestDerived::RowsAtCompileTime,1> >(_res, res.size()) = res;
     }
     ei_cache_friendly_product_colmajor_times_vector(res.size(),
@@ -583,7 +580,7 @@ struct ei_cache_friendly_product_selector<ProductType,LhsRows,ColMajor,HasDirect
     if (!EvalToRes)
     {
       res = Map<Matrix<Scalar,DestDerived::SizeAtCompileTime,1> >(_res, res.size());
-      ei_aligned_stack_free(_res, Scalar, res.size());
+      ei_aligned_stack_delete(Scalar, _res, res.size());
     }
   }
 };
@@ -619,7 +616,7 @@ struct ei_cache_friendly_product_selector<ProductType,1,LhsOrder,LhsAccess,RhsCo
        _res = &res.coeffRef(0);
     else
     {
-      _res = ei_aligned_stack_alloc(Scalar, res.size());
+      _res = ei_aligned_stack_new(Scalar, res.size());
       Map<Matrix<Scalar,DestDerived::SizeAtCompileTime,1> >(_res, res.size()) = res;
     }
     ei_cache_friendly_product_colmajor_times_vector(res.size(),
@@ -629,7 +626,7 @@ struct ei_cache_friendly_product_selector<ProductType,1,LhsOrder,LhsAccess,RhsCo
     if (!EvalToRes)
     {
       res = Map<Matrix<Scalar,DestDerived::SizeAtCompileTime,1> >(_res, res.size());
-      ei_aligned_stack_free(_res, Scalar, res.size());
+      ei_aligned_stack_delete(Scalar, _res, res.size());
     }
   }
 };
@@ -652,13 +649,13 @@ struct ei_cache_friendly_product_selector<ProductType,LhsRows,RowMajor,HasDirect
        _rhs = &product.rhs().const_cast_derived().coeffRef(0);
     else
     {
-      _rhs = ei_aligned_stack_alloc(Scalar, product.rhs().size());
+      _rhs = ei_aligned_stack_new(Scalar, product.rhs().size());
       Map<Matrix<Scalar,Rhs::SizeAtCompileTime,1> >(_rhs, product.rhs().size()) = product.rhs();
     }
     ei_cache_friendly_product_rowmajor_times_vector(&product.lhs().const_cast_derived().coeffRef(0,0), product.lhs().stride(),
                                                     _rhs, product.rhs().size(), res);
 
-    if (!UseRhsDirectly) ei_aligned_stack_free(_rhs, Scalar, product.rhs().size());
+    if (!UseRhsDirectly) ei_aligned_stack_delete(Scalar, _rhs, product.rhs().size());
   }
 };
 
@@ -680,13 +677,13 @@ struct ei_cache_friendly_product_selector<ProductType,1,LhsOrder,LhsAccess,RhsCo
        _lhs = &product.lhs().const_cast_derived().coeffRef(0);
     else
     {
-      _lhs = ei_aligned_stack_alloc(Scalar, product.lhs().size());
+      _lhs = ei_aligned_stack_new(Scalar, product.lhs().size());
       Map<Matrix<Scalar,Lhs::SizeAtCompileTime,1> >(_lhs, product.lhs().size()) = product.lhs();
     }
     ei_cache_friendly_product_rowmajor_times_vector(&product.rhs().const_cast_derived().coeffRef(0,0), product.rhs().stride(),
                                                     _lhs, product.lhs().size(), res);
 
-    if(!UseLhsDirectly) ei_aligned_stack_free(_lhs, Scalar, product.lhs().size());
+    if(!UseLhsDirectly) ei_aligned_stack_delete(Scalar, _lhs, product.lhs().size());
   }
 };
 
@@ -765,7 +762,7 @@ inline void Product<Lhs,Rhs,ProductMode>::_cacheFriendlyEvalAndAdd(DestDerived&
     rows(), cols(), lhs.cols(),
     _LhsCopy::Flags&RowMajorBit, (const Scalar*)&(lhs.const_cast_derived().coeffRef(0,0)), lhs.stride(),
     _RhsCopy::Flags&RowMajorBit, (const Scalar*)&(rhs.const_cast_derived().coeffRef(0,0)), rhs.stride(),
-    Flags&RowMajorBit, (Scalar*)&(res.coeffRef(0,0)), res.stride()
+    DestDerived::Flags&RowMajorBit, (Scalar*)&(res.coeffRef(0,0)), res.stride()
   );
 }
 

Eigen/src/Core/SolveTriangular.h

@@ -221,13 +221,19 @@ struct ei_solve_triangular_selector<Lhs,Rhs,UpLo,ColMajor|IsDense>
 };
 
 /** "in-place" version of MatrixBase::solveTriangular() where the result is written in \a other
+  *
+  * \nonstableyet
+  *
+  * The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here.
+  * This function will const_cast it, so constness isn't honored here.
   *
   * See MatrixBase:solveTriangular() for the details.
   */
 template<typename Derived>
 template<typename OtherDerived>
-void MatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other) const
+void MatrixBase<Derived>::solveTriangularInPlace(const MatrixBase<OtherDerived>& _other) const
 {
+  MatrixBase<OtherDerived>& other = _other.const_cast_derived();
   ei_assert(derived().cols() == derived().rows());
   ei_assert(derived().cols() == other.rows());
   ei_assert(!(Flags & ZeroDiagBit));
@@ -246,6 +252,8 @@ void MatrixBase<Derived>::solveTriangularInPlace(MatrixBase<OtherDerived>& other
 }
 
 /** \returns the product of the inverse of \c *this with \a other, \a *this being triangular.
+  *
+  * \nonstableyet
   *
   * This function computes the inverse-matrix matrix product inverse(\c *this) * \a other.
   * The matrix \c *this must be triangular and invertible (i.e., all the coefficients of the

Eigen/src/Core/Sum.h

@@ -42,7 +42,6 @@ public:
   enum {
     Vectorization = (int(Derived::Flags)&ActualPacketAccessBit)
                  && (int(Derived::Flags)&LinearAccessBit)
-                 && (int(Derived::SizeAtCompileTime)>2*PacketSize)
                   ? LinearVectorization
                   : NoVectorization
   };
@@ -101,18 +100,13 @@ struct ei_sum_novec_unroller<Derived, Start, 1>
 };
 
 /*** vectorization ***/
-
-template<typename Derived, int Index, int Stop,
-         bool LastPacket = (Stop-Index == ei_packet_traits<typename Derived::Scalar>::size)>
+  
+template<typename Derived, int Start, int Length>
 struct ei_sum_vec_unroller
 {
   enum {
-    row = int(Derived::Flags)&RowMajorBit
-        ? Index / int(Derived::ColsAtCompileTime)
-        : Index % Derived::RowsAtCompileTime,
-    col = int(Derived::Flags)&RowMajorBit
-        ? Index % int(Derived::ColsAtCompileTime)
-        : Index / Derived::RowsAtCompileTime
+    PacketSize = ei_packet_traits<typename Derived::Scalar>::size,
+    HalfLength = Length/2
   };
 
   typedef typename Derived::Scalar Scalar;
@@ -121,22 +115,22 @@ struct ei_sum_vec_unroller
   inline static PacketScalar run(const Derived &mat)
   {
     return ei_padd(
-      mat.template packet<Aligned>(row, col),
-      ei_sum_vec_unroller<Derived, Index+ei_packet_traits<typename Derived::Scalar>::size, Stop>::run(mat)
-    );
+            ei_sum_vec_unroller<Derived, Start, HalfLength>::run(mat),
+            ei_sum_vec_unroller<Derived, Start+HalfLength, Length-HalfLength>::run(mat) );
   }
 };
 
-template<typename Derived, int Index, int Stop>
-struct ei_sum_vec_unroller<Derived, Index, Stop, true>
+template<typename Derived, int Start>
+struct ei_sum_vec_unroller<Derived, Start, 1>
 {
   enum {
+    index = Start * ei_packet_traits<typename Derived::Scalar>::size,
     row = int(Derived::Flags)&RowMajorBit
-        ? Index / int(Derived::ColsAtCompileTime)
-        : Index % Derived::RowsAtCompileTime,
+        ? index / int(Derived::ColsAtCompileTime)
+        : index % Derived::RowsAtCompileTime,
     col = int(Derived::Flags)&RowMajorBit
-        ? Index % int(Derived::ColsAtCompileTime)
-        : Index / Derived::RowsAtCompileTime,
+        ? index % int(Derived::ColsAtCompileTime)
+        : index / Derived::RowsAtCompileTime,
     alignment = (Derived::Flags & AlignedBit) ? Aligned : Unaligned
   };
 
@@ -231,11 +225,18 @@ template<typename Derived>
 struct ei_sum_impl<Derived, LinearVectorization, CompleteUnrolling>
 {
   typedef typename Derived::Scalar Scalar;
+  typedef typename ei_packet_traits<Scalar>::type PacketScalar;
+  enum {
+    PacketSize = ei_packet_traits<Scalar>::size,
+    Size = Derived::SizeAtCompileTime,
+    VectorizationSize = (Size / PacketSize) * PacketSize
+  };
   static Scalar run(const Derived& mat)
   {
-    return ei_predux(
-      ei_sum_vec_unroller<Derived, 0, Derived::SizeAtCompileTime>::run(mat)
-    );
+    Scalar res = ei_predux(ei_sum_vec_unroller<Derived, 0, Size / PacketSize>::run(mat));
+    if (VectorizationSize != Size)
+      res += ei_sum_novec_unroller<Derived, VectorizationSize, Size-VectorizationSize>::run(mat);
+    return res;
   }
 };
 

Eigen/src/Core/Swap.h

@@ -117,6 +117,9 @@ template<typename ExpressionType> class SwapWrapper
 
   protected:
     ExpressionType& m_expression;
+
+  private:
+    SwapWrapper& operator=(const SwapWrapper&);
 };
 
 /** swaps *this with the expression \a other.

Eigen/src/Core/Transpose.h

@@ -63,15 +63,12 @@ template<typename MatrixType> class Transpose
 
     EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
 
-    class InnerIterator;
-
     inline Transpose(const MatrixType& matrix) : m_matrix(matrix) {}
 
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)
 
     inline int rows() const { return m_matrix.cols(); }
     inline int cols() const { return m_matrix.rows(); }
-    inline int nonZeros() const { return m_matrix.nonZeros(); }
     inline int stride(void) const { return m_matrix.stride(); }
 
     inline Scalar& coeffRef(int row, int col)
@@ -127,7 +124,20 @@ template<typename MatrixType> class Transpose
   * Example: \include MatrixBase_transpose.cpp
   * Output: \verbinclude MatrixBase_transpose.out
   *
-  * \sa adjoint(), class DiagonalCoeffs */
+  * \warning If you want to replace a matrix by its own transpose, do \b NOT do this:
+  * \code
+  * m = m.transpose(); // bug!!! caused by aliasing effect
+  * \endcode
+  * Instead, use the transposeInPlace() method:
+  * \code
+  * m.transposeInPlace();
+  * \endcode
+  * which gives Eigen good opportunities for optimization, or alternatively you can also do:
+  * \code
+  * m = m.transpose().eval();
+  * \endcode
+  *
+  * \sa transposeInPlace(), adjoint() */
 template<typename Derived>
 inline Transpose<Derived>
 MatrixBase<Derived>::transpose()
@@ -135,7 +145,11 @@ MatrixBase<Derived>::transpose()
   return derived();
 }
 
-/** This is the const version of transpose(). \sa adjoint() */
+/** This is the const version of transpose().
+  *
+  * Make sure you read the warning for transpose() !
+  *
+  * \sa transposeInPlace(), adjoint() */
 template<typename Derived>
 inline const Transpose<Derived>
 MatrixBase<Derived>::transpose() const
@@ -148,6 +162,15 @@ MatrixBase<Derived>::transpose() const
   * Example: \include MatrixBase_adjoint.cpp
   * Output: \verbinclude MatrixBase_adjoint.out
   *
+  * \warning If you want to replace a matrix by its own adjoint, do \b NOT do this:
+  * \code
+  * m = m.adjoint(); // bug!!! caused by aliasing effect
+  * \endcode
+  * Instead, do:
+  * \code
+  * m = m.adjoint().eval();
+  * \endcode
+  *
   * \sa transpose(), conjugate(), class Transpose, class ei_scalar_conjugate_op */
 template<typename Derived>
 inline const typename MatrixBase<Derived>::AdjointReturnType
@@ -177,7 +200,7 @@ struct ei_inplace_transpose_selector<MatrixType,false> { // non square matrix
     if (m.rows()==m.cols())
       m.template part<StrictlyUpperTriangular>().swap(m.transpose());
     else
-      m.set(m.transpose().eval());
+      m = m.transpose().eval();
   }
 };
 
@@ -185,10 +208,10 @@ struct ei_inplace_transpose_selector<MatrixType,false> { // non square matrix
   *
   * In most cases it is probably better to simply use the transposed expression
   * of a matrix. However, when transposing the matrix data itself is really needed,
-  * then this "in-place" version is probably the right choice because it provides 
+  * then this "in-place" version is probably the right choice because it provides
   * the following additional features:
   *  - less error prone: doing the same operation with .transpose() requires special care:
-  *    \code m.set(m.transpose().eval()); \endcode
+  *    \code m = m.transpose().eval(); \endcode
   *  - no temporary object is created (currently only for squared matrices)
   *  - it allows future optimizations (cache friendliness, etc.)
   *

Eigen/src/Core/Visitor.h

@@ -164,7 +164,7 @@ struct ei_functor_traits<ei_max_coeff_visitor<Scalar> > {
 /** \returns the minimum of all coefficients of *this
   * and puts in *row and *col its location.
   *
-  * \sa MatrixBase::maxCoeff(int*,int*), MatrixBase::visitor(), MatrixBase::minCoeff()
+  * \sa MatrixBase::minCoeff(int*), MatrixBase::maxCoeff(int*,int*), MatrixBase::visitor(), MatrixBase::minCoeff()
   */
 template<typename Derived>
 typename ei_traits<Derived>::Scalar
@@ -177,6 +177,22 @@ MatrixBase<Derived>::minCoeff(int* row, int* col) const
   return minVisitor.res;
 }
 
+/** \returns the minimum of all coefficients of *this
+  * and puts in *index its location.
+  *
+  * \sa MatrixBase::minCoeff(int*,int*), MatrixBase::maxCoeff(int*,int*), MatrixBase::visitor(), MatrixBase::minCoeff()
+  */
+template<typename Derived>
+typename ei_traits<Derived>::Scalar
+MatrixBase<Derived>::minCoeff(int* index) const
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  ei_min_coeff_visitor<Scalar> minVisitor;
+  this->visit(minVisitor);
+  *index = (RowsAtCompileTime==1) ? minVisitor.col : minVisitor.row;
+  return minVisitor.res;
+}
+
 /** \returns the maximum of all coefficients of *this
   * and puts in *row and *col its location.
   *
@@ -193,5 +209,20 @@ MatrixBase<Derived>::maxCoeff(int* row, int* col) const
   return maxVisitor.res;
 }
 
+/** \returns the maximum of all coefficients of *this
+  * and puts in *index its location.
+  *
+  * \sa MatrixBase::maxCoeff(int*,int*), MatrixBase::minCoeff(int*,int*), MatrixBase::visitor(), MatrixBase::maxCoeff()
+  */
+template<typename Derived>
+typename ei_traits<Derived>::Scalar
+MatrixBase<Derived>::maxCoeff(int* index) const
+{
+  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
+  ei_max_coeff_visitor<Scalar> maxVisitor;
+  this->visit(maxVisitor);
+  *index = (RowsAtCompileTime==1) ? maxVisitor.col : maxVisitor.row;
+  return maxVisitor.res;
+}
 
 #endif // EIGEN_VISITOR_H

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

@@ -37,6 +37,10 @@ template<> struct ei_unpacket_traits<__m128>  { typedef float  type; enum {size=
 template<> struct ei_unpacket_traits<__m128d> { typedef double type; enum {size=2}; };
 template<> struct ei_unpacket_traits<__m128i> { typedef int    type; enum {size=4}; };
 
+template<> EIGEN_STRONG_INLINE __m128  ei_pset1<float>(const float&  from) { return _mm_set1_ps(from); }
+template<> EIGEN_STRONG_INLINE __m128d ei_pset1<double>(const double& from) { return _mm_set1_pd(from); }
+template<> EIGEN_STRONG_INLINE __m128i ei_pset1<int>(const int&    from) { return _mm_set1_epi32(from); }
+
 template<> EIGEN_STRONG_INLINE __m128  ei_padd<__m128>(const __m128&  a, const __m128&  b) { return _mm_add_ps(a,b); }
 template<> EIGEN_STRONG_INLINE __m128d ei_padd<__m128d>(const __m128d& a, const __m128d& b) { return _mm_add_pd(a,b); }
 template<> EIGEN_STRONG_INLINE __m128i ei_padd<__m128i>(const __m128i& a, const __m128i& b) { return _mm_add_epi32(a,b); }
@@ -63,7 +67,7 @@ template<> EIGEN_STRONG_INLINE __m128  ei_pdiv<__m128>(const __m128&  a, const _
 template<> EIGEN_STRONG_INLINE __m128d ei_pdiv<__m128d>(const __m128d& a, const __m128d& b) { return _mm_div_pd(a,b); }
 template<> EIGEN_STRONG_INLINE __m128i ei_pdiv<__m128i>(const __m128i& /*a*/, const __m128i& /*b*/)
 { ei_assert(false && "packet integer division are not supported by SSE");
-  __m128i dummy;
+  __m128i dummy = ei_pset1<int>(0);
   return dummy;
 }
 
@@ -102,10 +106,6 @@ template<> EIGEN_STRONG_INLINE __m128  ei_ploadu<float>(const float*   from) { r
 template<> EIGEN_STRONG_INLINE __m128d ei_ploadu<double>(const double*  from) { return _mm_loadu_pd(from); }
 template<> EIGEN_STRONG_INLINE __m128i ei_ploadu<int>(const int* from) { return _mm_loadu_si128(reinterpret_cast<const __m128i*>(from)); }
 
-template<> EIGEN_STRONG_INLINE __m128  ei_pset1<float>(const float&  from) { return _mm_set1_ps(from); }
-template<> EIGEN_STRONG_INLINE __m128d ei_pset1<double>(const double& from) { return _mm_set1_pd(from); }
-template<> EIGEN_STRONG_INLINE __m128i ei_pset1<int>(const int&    from) { return _mm_set1_epi32(from); }
-
 template<> EIGEN_STRONG_INLINE void ei_pstore<float>(float*  to, const __m128&  from) { _mm_store_ps(to, from); }
 template<> EIGEN_STRONG_INLINE void ei_pstore<double>(double* to, const __m128d& from) { _mm_store_pd(to, from); }
 template<> EIGEN_STRONG_INLINE void ei_pstore<int>(int*    to, const __m128i& from) { _mm_store_si128(reinterpret_cast<__m128i*>(to), from); }
@@ -114,9 +114,22 @@ template<> EIGEN_STRONG_INLINE void ei_pstoreu<float>(float*  to, const __m128&
 template<> EIGEN_STRONG_INLINE void ei_pstoreu<double>(double* to, const __m128d& from) { _mm_storeu_pd(to, from); }
 template<> EIGEN_STRONG_INLINE void ei_pstoreu<int>(int*    to, const __m128i& from) { _mm_storeu_si128(reinterpret_cast<__m128i*>(to), from); }
 
+#if defined(_MSC_VER) && (_MSC_VER <= 1500) && defined(_WIN64)
+// The temporary variable fixes an internal compilation error.
+// Direct of the struct members fixed bug #62.
+template<> EIGEN_STRONG_INLINE float  ei_pfirst<__m128>(const __m128& a) { return a.m128_f32[0]; }
+template<> EIGEN_STRONG_INLINE double ei_pfirst<__m128d>(const __m128d& a) { return a.m128d_f64[0]; }
+template<> EIGEN_STRONG_INLINE int    ei_pfirst<__m128i>(const __m128i& a) { int x = _mm_cvtsi128_si32(a); return x; }
+#elif defined(_MSC_VER) && (_MSC_VER <= 1500)
+// The temporary variable fixes an internal compilation error.
+template<> EIGEN_STRONG_INLINE float  ei_pfirst<__m128>(const __m128& a) { float x = _mm_cvtss_f32(a); return x; }
+template<> EIGEN_STRONG_INLINE double ei_pfirst<__m128d>(const __m128d& a) { double x = _mm_cvtsd_f64(a); return x; }
+template<> EIGEN_STRONG_INLINE int    ei_pfirst<__m128i>(const __m128i& a) { int x = _mm_cvtsi128_si32(a); return x; }
+#else
 template<> EIGEN_STRONG_INLINE float  ei_pfirst<__m128>(const __m128&  a) { return _mm_cvtss_f32(a); }
 template<> EIGEN_STRONG_INLINE double ei_pfirst<__m128d>(const __m128d& a) { return _mm_cvtsd_f64(a); }
 template<> EIGEN_STRONG_INLINE int    ei_pfirst<__m128i>(const __m128i& a) { return _mm_cvtsi128_si32(a); }
+#endif
 
 #ifdef __SSE3__
 // TODO implement SSE2 versions as well as integer versions
@@ -308,4 +321,7 @@ struct ei_palign_impl<Offset,__m128d>
 };
 #endif
 
+#define ei_vec4f_swizzle1(v,p,q,r,s) \
+  (_mm_castsi128_ps(_mm_shuffle_epi32( _mm_castps_si128(v), ((s)<<6|(r)<<4|(q)<<2|(p)))))
+
 #endif // EIGEN_PACKET_MATH_SSE_H

Eigen/src/Core/util/Constants.h

@@ -201,7 +201,7 @@ enum { ForceAligned, AsRequested };
 enum { ConditionalJumpCost = 5 };
 enum CornerType { TopLeft, TopRight, BottomLeft, BottomRight };
 enum DirectionType { Vertical, Horizontal };
-enum ProductEvaluationMode { NormalProduct, CacheFriendlyProduct, DiagonalProduct, SparseProduct };
+enum ProductEvaluationMode { NormalProduct, CacheFriendlyProduct, DiagonalProduct, SparseTimeSparseProduct, SparseTimeDenseProduct, DenseTimeSparseProduct };
 
 enum {
   /** \internal Equivalent to a slice vectorization for fixed-size matrices having good alignment
@@ -223,15 +223,13 @@ enum {
 };
 
 enum {
-  Matrix_ColMajor = 0,
-  Matrix_RowMajor = 0x1,  // it is only a coincidence that this is equal to RowMajorBit -- don't rely on that
+  ColMajor = 0,
+  RowMajor = 0x1,  // it is only a coincidence that this is equal to RowMajorBit -- don't rely on that
   /** \internal Don't require alignment for the matrix itself (the array of coefficients, if dynamically allocated, may still be
                 requested to be aligned) */
-  ColMajor = Matrix_ColMajor, // deprecated
-  RowMajor = Matrix_RowMajor, // deprecated
-  Matrix_DontAlign = 0,
-  /** \internal Align the matrix itself */
-  Matrix_AutoAlign = 0x2
+  DontAlign = 0,
+  /** \internal Align the matrix itself if it is vectorizable fixed-size */
+  AutoAlign = 0x2
 };
 
 enum {
@@ -241,9 +239,16 @@ enum {
   HasDirectAccess = DirectAccessBit
 };
 
-const int FullyCoherentAccessPattern  = 0x1;
-const int InnerCoherentAccessPattern  = 0x2 | FullyCoherentAccessPattern;
-const int OuterCoherentAccessPattern  = 0x4 | InnerCoherentAccessPattern;
-const int RandomAccessPattern         = 0x8 | OuterCoherentAccessPattern;
+const int EiArch_Generic = 0x0;
+const int EiArch_SSE     = 0x1;
+const int EiArch_AltiVec = 0x2;
+
+#if defined EIGEN_VECTORIZE_SSE
+  const int EiArch = EiArch_SSE;
+#elif defined EIGEN_VECTORIZE_ALTIVEC
+  const int EiArch = EiArch_AltiVec;
+#else
+  const int EiArch = EiArch_Generic;
+#endif
 
 #endif // EIGEN_CONSTANTS_H

Eigen/src/Core/util/DisableMSVCWarnings.h

@@ -1,9 +1,5 @@
-#ifndef EIGEN_DISABLEMSVCWARNINGS_H
-#define EIGEN_DISABLEMSVCWARNINGS_H
 
 #ifdef _MSC_VER
   #pragma warning( push )
-  #pragma warning( disable : 4181 4244 4127 4211 )
+  #pragma warning( disable : 4181 4244 4127 4211 4717 )
 #endif
-
-#endif // EIGEN_DISABLEMSVCWARNINGS_H

Eigen/src/Core/util/EnableMSVCWarnings.h

@@ -1,8 +1,4 @@
-#ifndef EIGEN_ENABLEMSVCWARNINGS_H
-#define EIGEN_ENABLEMSVCWARNINGS_H
 
 #ifdef _MSC_VER
   #pragma warning( pop )
 #endif
-
-#endif // EIGEN_ENABLEMSVCWARNINGS_H

Eigen/src/Core/util/ForwardDeclarations.h

@@ -29,7 +29,7 @@ template<typename T> struct ei_traits;
 template<typename T> struct NumTraits;
 
 template<typename _Scalar, int _Rows, int _Cols,
-         int _Options = EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION | Matrix_AutoAlign,
+         int _Options = EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION | AutoAlign,
          int _MaxRows = _Rows, int _MaxCols = _Cols> class Matrix;
 
 template<typename ExpressionType, unsigned int Added, unsigned int Removed> class Flagged;
@@ -106,9 +106,6 @@ template<typename MatrixType> class QR;
 template<typename MatrixType> class SVD;
 template<typename MatrixType> class LLT;
 template<typename MatrixType> class LDLT;
-// deprecated:
-template<typename MatrixType> class Cholesky;
-template<typename MatrixType> class CholeskyWithoutSquareRoot;
 
 // Geometry module:
 template<typename Derived, int _Dim> class RotationBase;
@@ -122,4 +119,7 @@ template <typename _Scalar, int _AmbientDim> class Hyperplane;
 template<typename Scalar,int Dim> class Translation;
 template<typename Scalar,int Dim> class Scaling;
 
+// Sparse module:
+template<typename Lhs, typename Rhs, int ProductMode> class SparseProduct;
+
 #endif // EIGEN_FORWARDDECLARATIONS_H

Eigen/src/Core/util/Macros.h

@@ -30,16 +30,52 @@
 
 #define EIGEN_WORLD_VERSION 2
 #define EIGEN_MAJOR_VERSION 0
-#define EIGEN_MINOR_VERSION 0
+#define EIGEN_MINOR_VERSION 11
 
 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
                                       (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
                                                                  EIGEN_MINOR_VERSION>=z))))
 
-#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
-#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION Matrix_RowMajor
+// 16 byte alignment is only useful for vectorization. Since it affects the ABI, we need to enable 16 byte alignment on all
+// platforms where vectorization might be enabled. In theory we could always enable alignment, but it can be a cause of problems
+// on some platforms, so we just disable it in certain common platform (compiler+architecture combinations) to avoid these problems.
+#if defined(__GNUC__) && !(defined(__i386__) || defined(__x86_64__) || defined(__powerpc__) || defined(__ppc__) || defined(__ia64__))
+#define EIGEN_GCC_AND_ARCH_DOESNT_WANT_ALIGNMENT 1
 #else
-#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION Matrix_ColMajor
+#define EIGEN_GCC_AND_ARCH_DOESNT_WANT_ALIGNMENT 0
+#endif
+
+#if defined(__GNUC__) && (__GNUC__ <= 3)
+#define EIGEN_GCC3_OR_OLDER 1
+#else
+#define EIGEN_GCC3_OR_OLDER 0
+#endif
+
+// FIXME vectorization + alignment is completely disabled with sun studio
+#if !EIGEN_GCC_AND_ARCH_DOESNT_WANT_ALIGNMENT && !EIGEN_GCC3_OR_OLDER && !defined(__SUNPRO_CC)
+  #define EIGEN_ARCH_WANTS_ALIGNMENT 1
+#else
+  #define EIGEN_ARCH_WANTS_ALIGNMENT 0
+#endif
+
+// EIGEN_ALIGN is the true test whether we want to align or not. It takes into account both the user choice to explicitly disable
+// alignment (EIGEN_DONT_ALIGN) and the architecture config (EIGEN_ARCH_WANTS_ALIGNMENT). Henceforth, only EIGEN_ALIGN should be used.
+#if EIGEN_ARCH_WANTS_ALIGNMENT && !defined(EIGEN_DONT_ALIGN)
+  #define EIGEN_ALIGN 1
+#else
+  #define EIGEN_ALIGN 0
+  #ifdef EIGEN_VECTORIZE
+    #error "Vectorization enabled, but our platform checks say that we don't do 16 byte alignment on this platform. If you added vectorization for another architecture, you also need to edit this platform check."
+  #endif
+  #ifndef EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
+    #define EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT
+  #endif
+#endif
+
+#ifdef EIGEN_DEFAULT_TO_ROW_MAJOR
+#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION RowMajor
+#else
+#define EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION ColMajor
 #endif
 
 /** \internal  Defines the maximal loop size to enable meta unrolling of loops.
@@ -50,10 +86,18 @@
 #define EIGEN_UNROLLING_LIMIT 100
 #endif
 
-/** \internal Define the maximal size in Bytes of L2 blocks.
-  * The current value is set to generate blocks of 256x256 for float */
-#ifndef EIGEN_TUNE_FOR_L2_CACHE_SIZE
-#define EIGEN_TUNE_FOR_L2_CACHE_SIZE (sizeof(float)*256*256)
+/** \internal Define the maximal size in Bytes of blocks fitting in CPU cache.
+  * The current value is set to generate blocks of 256x256 for float
+  *
+  * Typically for a single-threaded application you would set that to 25% of the size of your CPU caches in bytes
+  */
+#ifndef EIGEN_TUNE_FOR_CPU_CACHE_SIZE
+#define EIGEN_TUNE_FOR_CPU_CACHE_SIZE (sizeof(float)*256*256)
+#endif
+
+// FIXME this should go away quickly
+#ifdef EIGEN_TUNE_FOR_L2_CACHE_SIZE
+#error EIGEN_TUNE_FOR_L2_CACHE_SIZE is now called EIGEN_TUNE_FOR_CPU_CACHE_SIZE.
 #endif
 
 #define USING_PART_OF_NAMESPACE_EIGEN \
@@ -139,18 +183,25 @@ using Eigen::ei_cos;
  * If we made alignment depend on whether or not EIGEN_VECTORIZE is defined, it would be impossible to link
  * vectorized and non-vectorized code.
  */
-#if (defined __GNUC__)
+#if !EIGEN_ALIGN
+#define EIGEN_ALIGN_128
+#elif (defined __GNUC__)
 #define EIGEN_ALIGN_128 __attribute__((aligned(16)))
 #elif (defined _MSC_VER)
 #define EIGEN_ALIGN_128 __declspec(align(16))
 #else
-#define EIGEN_ALIGN_128
+#error Please tell me what is the equivalent of __attribute__((aligned(16))) for your compiler
 #endif
 
-#define EIGEN_RESTRICT __restrict
+#ifdef EIGEN_DONT_USE_RESTRICT_KEYWORD
+  #define EIGEN_RESTRICT
+#endif
+#ifndef EIGEN_RESTRICT
+  #define EIGEN_RESTRICT __restrict
+#endif
 
 #ifndef EIGEN_STACK_ALLOCATION_LIMIT
-#define EIGEN_STACK_ALLOCATION_LIMIT 16000000
+#define EIGEN_STACK_ALLOCATION_LIMIT 1000000
 #endif
 
 #ifndef EIGEN_DEFAULT_IO_FORMAT
@@ -165,18 +216,18 @@ using Eigen::ei_cos;
 template<typename OtherDerived> \
 EIGEN_STRONG_INLINE Derived& operator Op(const Eigen::MatrixBase<OtherDerived>& other) \
 { \
-  return Eigen::MatrixBase<Derived>::operator Op(other.derived()); \
+  return Base::operator Op(other.derived()); \
 } \
 EIGEN_STRONG_INLINE Derived& operator Op(const Derived& other) \
 { \
-  return Eigen::MatrixBase<Derived>::operator Op(other); \
+  return Base::operator Op(other); \
 }
 
 #define EIGEN_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, Op) \
 template<typename Other> \
 EIGEN_STRONG_INLINE Derived& operator Op(const Other& scalar) \
 { \
-  return Eigen::MatrixBase<Derived>::operator Op(scalar); \
+  return Base::operator Op(scalar); \
 }
 
 #define EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Derived) \
@@ -208,4 +259,15 @@ _EIGEN_GENERIC_PUBLIC_INTERFACE(Derived, Eigen::MatrixBase<Derived>)
 #define EIGEN_ENUM_MIN(a,b) (((int)a <= (int)b) ? (int)a : (int)b)
 #define EIGEN_ENUM_MAX(a,b) (((int)a >= (int)b) ? (int)a : (int)b)
 
+// just an empty macro !
+#define EIGEN_EMPTY
+
+// concatenate two tokens
+#define EIGEN_CAT2(a,b) a ## b
+#define EIGEN_CAT(a,b) EIGEN_CAT2(a,b)
+
+// convert a token to a string
+#define EIGEN_MAKESTRING2(a) #a
+#define EIGEN_MAKESTRING(a) EIGEN_MAKESTRING2(a)
+
 #endif // EIGEN_MACROS_H

Eigen/src/Core/util/Memory.h

@@ -1,8 +1,9 @@
 // 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) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2009 Kenneth Riddile <kfriddile@yahoo.com>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -26,108 +27,236 @@
 #ifndef EIGEN_MEMORY_H
 #define EIGEN_MEMORY_H
 
-#ifdef __linux
-// it seems we cannot assume posix_memalign is defined in the stdlib header
-extern "C" int posix_memalign (void **, size_t, size_t) throw ();
+// FreeBSD 6 seems to have 16-byte aligned malloc
+// See http://svn.freebsd.org/viewvc/base/stable/6/lib/libc/stdlib/malloc.c?view=markup
+// FreeBSD 7 seems to have 16-byte aligned malloc except on ARM and MIPS architectures
+// See http://svn.freebsd.org/viewvc/base/stable/7/lib/libc/stdlib/malloc.c?view=markup
+#if defined(__FreeBSD__) && !defined(__arm__) && !defined(__mips__)
+#define EIGEN_FREEBSD_MALLOC_ALREADY_ALIGNED 1
+#else
+#define EIGEN_FREEBSD_MALLOC_ALREADY_ALIGNED 0
 #endif
 
-struct ei_byte_forcing_aligned_malloc
-{
-  unsigned char c; // sizeof must be 1.
-};
-template<typename T> struct ei_force_aligned_malloc { enum { ret = 0 }; };
-template<> struct ei_force_aligned_malloc<ei_byte_forcing_aligned_malloc> { enum { ret = 1 }; };
+#if defined(__APPLE__) || defined(_WIN64) || EIGEN_FREEBSD_MALLOC_ALREADY_ALIGNED
+  #define EIGEN_MALLOC_ALREADY_ALIGNED 1
+#else
+  #define EIGEN_MALLOC_ALREADY_ALIGNED 0
+#endif
 
-/** \internal allocates \a size * sizeof(\a T) bytes. If vectorization is enabled and T is such that a packet
-  * containts more than one T, then the returned pointer is guaranteed to have 16 bytes alignment.
-  * On allocation error, the returned pointer is undefined, but if exceptions are enabled then a std::bad_alloc is thrown.
+#if ((defined _GNU_SOURCE) || ((defined _XOPEN_SOURCE) && (_XOPEN_SOURCE >= 600))) && (defined _POSIX_ADVISORY_INFO) && (_POSIX_ADVISORY_INFO > 0)
+  #define EIGEN_HAS_POSIX_MEMALIGN 1
+#else
+  #define EIGEN_HAS_POSIX_MEMALIGN 0
+#endif
+
+#ifdef EIGEN_VECTORIZE_SSE
+  #define EIGEN_HAS_MM_MALLOC 1
+#else
+  #define EIGEN_HAS_MM_MALLOC 0
+#endif
+
+/** \internal like malloc, but the returned pointer is guaranteed to be 16-byte aligned.
+  * Fast, but wastes 16 additional bytes of memory.
+  * Does not throw any exception.
   */
-template<typename T>
-inline T* ei_aligned_malloc(size_t size)
+inline void* ei_handmade_aligned_malloc(size_t size)
 {
-  if(ei_packet_traits<T>::size>1 || ei_force_aligned_malloc<T>::ret)
-  {
-    void *void_result;
-    #ifdef __linux
-      #ifdef EIGEN_EXCEPTIONS
-        const int failed =
-      #endif
-      posix_memalign(&void_result, 16, size*sizeof(T));
-    #else
-      #ifdef _MSC_VER
-        void_result = _aligned_malloc(size*sizeof(T), 16);
-      #elif defined(__APPLE__)
-        void_result = malloc(size*sizeof(T)); // Apple's malloc() already returns aligned ptrs
-      #else
-        void_result = _mm_malloc(size*sizeof(T), 16);
-      #endif
-      #ifdef EIGEN_EXCEPTIONS
-        const int failed = (void_result == 0);
-      #endif
-    #endif
-    #ifdef EIGEN_EXCEPTIONS
-      if(failed)
-        throw std::bad_alloc();
-    #endif
-    // if the user uses Eigen on some fancy scalar type such as multiple-precision numbers,
-    // and this type has a custom operator new, then we want to honor this operator new!
-    // so when we use C functions to allocate memory, we must be careful to call manually the constructor using
-    // the special placement-new syntax.
-    return new(void_result) T[size];
-  }
-  else
-    return new T[size]; // here we really want a new, not a malloc. Justification: if the user uses Eigen on
-      // some fancy scalar type such as multiple-precision numbers, and this type has a custom operator new,
-      // then we want to honor this operator new! Anyway this type won't have vectorization so the vectorizing path
-      // is irrelevant here. Yes, we should say somewhere in the docs that if the user uses a custom scalar type then
-      // he can't have both vectorization and a custom operator new on his scalar type.
+  void *original = malloc(size+16);
+  void *aligned = reinterpret_cast<void*>((reinterpret_cast<size_t>(original) & ~(size_t(15))) + 16);
+  *(reinterpret_cast<void**>(aligned) - 1) = original;
+  return aligned;
+}
+
+/** \internal frees memory allocated with ei_handmade_aligned_malloc */
+inline void ei_handmade_aligned_free(void *ptr)
+{
+  if(ptr)
+    free(*(reinterpret_cast<void**>(ptr) - 1));
+}
+
+/** \internal allocates \a size bytes. The returned pointer is guaranteed to have 16 bytes alignment.
+  * On allocation error, the returned pointer is null, and if exceptions are enabled then a std::bad_alloc is thrown.
+  */
+inline void* ei_aligned_malloc(size_t size)
+{
+  #ifdef EIGEN_NO_MALLOC
+    ei_assert(false && "heap allocation is forbidden (EIGEN_NO_MALLOC is defined)");
+  #endif
+
+  void *result;  
+  #if !EIGEN_ALIGN
+    result = malloc(size);
+  #elif EIGEN_MALLOC_ALREADY_ALIGNED
+    result = malloc(size);
+  #elif EIGEN_HAS_POSIX_MEMALIGN
+    if(posix_memalign(&result, 16, size)) result = 0;
+  #elif EIGEN_HAS_MM_MALLOC
+    result = _mm_malloc(size, 16);
+  #elif (defined _MSC_VER)
+    result = _aligned_malloc(size, 16);
+  #else
+    result = ei_handmade_aligned_malloc(size);
+  #endif
+    
+  #ifdef EIGEN_EXCEPTIONS
+    if(result == 0)
+      throw std::bad_alloc();
+  #endif
+  return result;
+}
+
+/** allocates \a size bytes. If Align is true, then the returned ptr is 16-byte-aligned.
+  * On allocation error, the returned pointer is null, and if exceptions are enabled then a std::bad_alloc is thrown.
+  */
+template<bool Align> inline void* ei_conditional_aligned_malloc(size_t size)
+{
+  return ei_aligned_malloc(size);
+}
+
+template<> inline void* ei_conditional_aligned_malloc<false>(size_t size)
+{
+  #ifdef EIGEN_NO_MALLOC
+    ei_assert(false && "heap allocation is forbidden (EIGEN_NO_MALLOC is defined)");
+  #endif
+
+  void *result = malloc(size);
+  #ifdef EIGEN_EXCEPTIONS
+    if(!result) throw std::bad_alloc();
+  #endif
+  return result;
+}
+
+/** \internal construct the elements of an array.
+  * The \a size parameter tells on how many objects to call the constructor of T.
+  */
+template<typename T> inline T* ei_construct_elements_of_array(T *ptr, size_t size)
+{
+  for (size_t i=0; i < size; ++i) ::new (ptr + i) T;
+  return ptr;
+}
+
+/** allocates \a size objects of type T. The returned pointer is guaranteed to have 16 bytes alignment.
+  * On allocation error, the returned pointer is undefined, but if exceptions are enabled then a std::bad_alloc is thrown.
+  * The default constructor of T is called.
+  */
+template<typename T> inline T* ei_aligned_new(size_t size)
+{
+  T *result = reinterpret_cast<T*>(ei_aligned_malloc(sizeof(T)*size));
+  return ei_construct_elements_of_array(result, size);
+}
+
+template<typename T, bool Align> inline T* ei_conditional_aligned_new(size_t size)
+{
+  T *result = reinterpret_cast<T*>(ei_conditional_aligned_malloc<Align>(sizeof(T)*size));
+  return ei_construct_elements_of_array(result, size);
 }
 
 /** \internal free memory allocated with ei_aligned_malloc
-  * The \a size parameter is used to determine on how many elements to call the destructor. If you don't
-  * want any destructor to be called, just pass 0.
   */
-template<typename T>
-inline void ei_aligned_free(T* ptr, size_t size)
+inline void ei_aligned_free(void *ptr)
 {
-    if (ei_packet_traits<T>::size>1 || ei_force_aligned_malloc<T>::ret)
-    {
-      // need to call manually the dtor in case T is some user-defined fancy numeric type.
-      // always destruct an array starting from the end.
-      while(size) ptr[--size].~T();
-      #if defined(__linux)
-        free(ptr);
-      #elif defined(__APPLE__)
-        free(ptr);
-      #elif defined(_MSC_VER)
-        _aligned_free(ptr);
-      #else
-        _mm_free(ptr);
-      #endif
-    }
-    else
-      delete[] ptr;
+  #if !EIGEN_ALIGN
+    free(ptr);
+  #elif EIGEN_MALLOC_ALREADY_ALIGNED
+    free(ptr);
+  #elif EIGEN_HAS_POSIX_MEMALIGN
+    free(ptr);
+  #elif EIGEN_HAS_MM_MALLOC
+    _mm_free(ptr);
+  #elif defined(_MSC_VER)
+    _aligned_free(ptr);
+  #else
+    ei_handmade_aligned_free(ptr);
+  #endif
 }
 
-/** \internal \returns the number of elements which have to be skipped such that data are 16 bytes aligned */
-template<typename Scalar>
-inline static int ei_alignmentOffset(const Scalar* ptr, int maxOffset)
+/** \internal free memory allocated with ei_conditional_aligned_malloc
+  */
+template<bool Align> inline void ei_conditional_aligned_free(void *ptr)
+{
+  ei_aligned_free(ptr);
+}
+
+template<> inline void ei_conditional_aligned_free<false>(void *ptr)
+{
+  free(ptr);
+}
+
+/** \internal destruct the elements of an array.
+  * The \a size parameters tells on how many objects to call the destructor of T.
+  */
+template<typename T> inline void ei_destruct_elements_of_array(T *ptr, size_t size)
+{
+  // always destruct an array starting from the end.
+  while(size) ptr[--size].~T();
+}
+
+/** \internal delete objects constructed with ei_aligned_new
+  * The \a size parameters tells on how many objects to call the destructor of T.
+  */
+template<typename T> inline void ei_aligned_delete(T *ptr, size_t size)
+{
+  ei_destruct_elements_of_array<T>(ptr, size);
+  ei_aligned_free(ptr);
+}
+
+/** \internal delete objects constructed with ei_conditional_aligned_new
+  * The \a size parameters tells on how many objects to call the destructor of T.
+  */
+template<typename T, bool Align> inline void ei_conditional_aligned_delete(T *ptr, size_t size)
+{
+  ei_destruct_elements_of_array<T>(ptr, size);
+  ei_conditional_aligned_free<Align>(ptr);
+}
+
+/** \internal \returns the index of the first element of the array that is well aligned for vectorization.
+  *
+  * \param array the address of the start of the array
+  * \param size the size of the array
+  *
+  * \note If no element of the array is well aligned, the size of the array is returned. Typically,
+  * for example with SSE, "well aligned" means 16-byte-aligned. If vectorization is disabled or if the
+  * packet size for the given scalar type is 1, then everything is considered well-aligned.
+  *
+  * \note If the scalar type is vectorizable, we rely on the following assumptions: sizeof(Scalar) is a
+  * power of 2, the packet size in bytes is also a power of 2, and is a multiple of sizeof(Scalar). On the
+  * other hand, we do not assume that the array address is a multiple of sizeof(Scalar), as that fails for
+  * example with Scalar=double on certain 32-bit platforms, see bug #79.
+  *
+  * There is also the variant ei_first_aligned(const MatrixBase&, Integer) defined in Coeffs.h.
+  */
+template<typename Scalar, typename Integer>
+inline static Integer ei_alignmentOffset(const Scalar* array, Integer size)
 {
   typedef typename ei_packet_traits<Scalar>::type Packet;
-  const int PacketSize = ei_packet_traits<Scalar>::size;
-  const int PacketAlignedMask = PacketSize-1;
-  const bool Vectorized = PacketSize>1;
-  return Vectorized
-          ? std::min<int>( (PacketSize - (int((size_t(ptr)/sizeof(Scalar))) & PacketAlignedMask))
-                           & PacketAlignedMask, maxOffset)
-          : 0;
+  enum { PacketSize = ei_packet_traits<Scalar>::size,
+         PacketAlignedMask = PacketSize-1
+  };
+  
+  if(PacketSize==1)
+  {
+    // Either there is no vectorization, or a packet consists of exactly 1 scalar so that all elements
+    // of the array have the same aligment.
+    return 0;
+  }
+  else if(size_t(array) & (sizeof(Scalar)-1))
+  {
+    // There is vectorization for this scalar type, but the array is not aligned to the size of a single scalar.
+    // Consequently, no element of the array is well aligned.
+    return size;
+  }
+  else
+  {
+    return std::min<Integer>( (PacketSize - (Integer((size_t(array)/sizeof(Scalar))) & PacketAlignedMask))
+                           & PacketAlignedMask, size);
+  }
 }
 
 /** \internal
-  * ei_aligned_stack_alloc(TYPE,SIZE) allocates an aligned buffer of sizeof(TYPE)*SIZE bytes
-  * on the stack if sizeof(TYPE)*SIZE is smaller than EIGEN_STACK_ALLOCATION_LIMIT.
+  * ei_aligned_stack_alloc(SIZE) allocates an aligned buffer of SIZE bytes
+  * on the stack if SIZE is smaller than EIGEN_STACK_ALLOCATION_LIMIT.
   * Otherwise the memory is allocated on the heap.
-  * Data allocated with ei_aligned_stack_alloc \b must be freed by calling ei_aligned_stack_free(PTR,TYPE,SIZE).
+  * Data allocated with ei_aligned_stack_alloc \b must be freed by calling ei_aligned_stack_free(PTR,SIZE).
   * \code
   * float * data = ei_aligned_stack_alloc(float,array.size());
   * // ...
@@ -135,122 +264,153 @@ inline static int ei_alignmentOffset(const Scalar* ptr, int maxOffset)
   * \endcode
   */
 #ifdef __linux__
-  #define ei_aligned_stack_alloc(TYPE,SIZE) ((sizeof(TYPE)*(SIZE)>EIGEN_STACK_ALLOCATION_LIMIT) \
-                                    ? ei_aligned_malloc<TYPE>(SIZE) \
-                                    : (TYPE*)alloca(sizeof(TYPE)*(SIZE)))
-  #define ei_aligned_stack_free(PTR,TYPE,SIZE) if (sizeof(TYPE)*SIZE>EIGEN_STACK_ALLOCATION_LIMIT) ei_aligned_free(PTR,SIZE)
+  #define ei_aligned_stack_alloc(SIZE) (SIZE<=EIGEN_STACK_ALLOCATION_LIMIT) \
+                                    ? alloca(SIZE) \
+                                    : ei_aligned_malloc(SIZE)
+  #define ei_aligned_stack_free(PTR,SIZE) if(SIZE>EIGEN_STACK_ALLOCATION_LIMIT) ei_aligned_free(PTR)
 #else
-  #define ei_aligned_stack_alloc(TYPE,SIZE) ei_aligned_malloc<TYPE>(SIZE)
-  #define ei_aligned_stack_free(PTR,TYPE,SIZE) ei_aligned_free(PTR,SIZE)
+  #define ei_aligned_stack_alloc(SIZE) ei_aligned_malloc(SIZE)
+  #define ei_aligned_stack_free(PTR,SIZE) ei_aligned_free(PTR)
 #endif
 
-/** \class WithAlignedOperatorNew
-  *
-  * \brief Enforces instances of inherited classes to be 16 bytes aligned when allocated with operator new
-  *
-  * When Eigen's explicit vectorization is enabled, Eigen assumes that some fixed sizes types are aligned
-  * on a 16 bytes boundary. Those include all Matrix types having a sizeof multiple of 16 bytes, e.g.:
-  *  - Vector2d, Vector4f, Vector4i, Vector4d,
-  *  - Matrix2d, Matrix4f, Matrix4i, Matrix4d,
-  *  - etc.
-  * When an object is statically allocated, the compiler will automatically and always enforces 16 bytes
-  * alignment of the data when needed. However some troubles might appear when data are dynamically allocated.
-  * Let's pick an example:
-  * \code
-  * struct Foo {
-  *   char dummy;
-  *   Vector4f some_vector;
-  * };
-  * Foo obj1;                           // static allocation
-  * obj1.some_vector = Vector4f(..);    // =>   OK
-  *
-  * Foo *pObj2 = new Foo;               // dynamic allocation
-  * pObj2->some_vector = Vector4f(..);  // =>  !! might segfault !!
-  * \endcode
-  * Here, the problem is that operator new is not aware of the compile time alignment requirement of the
-  * type Vector4f (and hence of the type Foo). Therefore "new Foo" does not necessarily returns a 16 bytes
-  * aligned pointer. The purpose of the class WithAlignedOperatorNew is exactly to overcome this issue by
-  * overloading the operator new to return aligned data when the vectorization is enabled.
-  * Here is a similar safe example:
-  * \code
-  * struct Foo : public WithAlignedOperatorNew {
-  *   char dummy;
-  *   Vector4f some_vector;
-  * };
-  * Foo *pObj2 = new Foo;               // dynamic allocation
-  * pObj2->some_vector = Vector4f(..);  // =>  SAFE !
-  * \endcode
-  *
-  * \sa class ei_new_allocator
-  */
-struct WithAlignedOperatorNew
+#define ei_aligned_stack_new(TYPE,SIZE) ei_construct_elements_of_array(reinterpret_cast<TYPE*>(ei_aligned_stack_alloc(sizeof(TYPE)*SIZE)), SIZE)
+#define ei_aligned_stack_delete(TYPE,PTR,SIZE) do {ei_destruct_elements_of_array<TYPE>(PTR, SIZE); \
+                                                   ei_aligned_stack_free(PTR,sizeof(TYPE)*SIZE);} while(0)
+
+
+#if EIGEN_ALIGN
+  #ifdef EIGEN_EXCEPTIONS
+    #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
+      void* operator new(size_t size, const std::nothrow_t&) throw() { \
+        try { return Eigen::ei_conditional_aligned_malloc<NeedsToAlign>(size); } \
+        catch (...) { return 0; } \
+        return 0; \
+      }
+  #else
+    #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
+      void* operator new(size_t size, const std::nothrow_t&) throw() { \
+        return Eigen::ei_conditional_aligned_malloc<NeedsToAlign>(size); \
+      }
+  #endif
+
+  #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign) \
+      void *operator new(size_t size) { \
+        return Eigen::ei_conditional_aligned_malloc<NeedsToAlign>(size); \
+      } \
+      void *operator new[](size_t size) { \
+        return Eigen::ei_conditional_aligned_malloc<NeedsToAlign>(size); \
+      } \
+      void operator delete(void * ptr) throw() { Eigen::ei_conditional_aligned_free<NeedsToAlign>(ptr); } \
+      void operator delete[](void * ptr) throw() { Eigen::ei_conditional_aligned_free<NeedsToAlign>(ptr); } \
+      /* in-place new and delete. since (at least afaik) there is no actual   */ \
+      /* memory allocated we can safely let the default implementation handle */ \
+      /* this particular case. */ \
+      static void *operator new(size_t size, void *ptr) { return ::operator new(size,ptr); } \
+      void operator delete(void * memory, void *ptr) throw() { return ::operator delete(memory,ptr); } \
+      /* nothrow-new (returns zero instead of std::bad_alloc) */ \
+      EIGEN_MAKE_ALIGNED_OPERATOR_NEW_NOTHROW(NeedsToAlign) \
+      void operator delete(void *ptr, const std::nothrow_t&) throw() { \
+        Eigen::ei_conditional_aligned_free<NeedsToAlign>(ptr); \
+      } \
+      typedef void ei_operator_new_marker_type;
+#else
+  #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
+#endif
+
+#define EIGEN_MAKE_ALIGNED_OPERATOR_NEW EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(true)
+#define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(Scalar,Size) \
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(((Size)!=Eigen::Dynamic) && ((sizeof(Scalar)*(Size))%16==0))
+
+
+/** \class aligned_allocator
+*
+* \brief stl compatible allocator to use with with 16 byte aligned types
+*
+* Example:
+* \code
+* // Matrix4f requires 16 bytes alignment:
+* std::map< int, Matrix4f, std::less<int>, aligned_allocator<Matrix4f> > my_map_mat4;
+* // Vector3f does not require 16 bytes alignment, no need to use Eigen's allocator:
+* std::map< int, Vector3f > my_map_vec3;
+* \endcode
+*
+*/
+template<class T>
+class aligned_allocator
 {
-  void *operator new(size_t size) throw()
-  {
-    return ei_aligned_malloc<ei_byte_forcing_aligned_malloc>(size);
-  }
-
-  void *operator new[](size_t size) throw()
-  {
-    return ei_aligned_malloc<ei_byte_forcing_aligned_malloc>(size);
-  }
-
-  void operator delete(void * ptr) { ei_aligned_free(static_cast<ei_byte_forcing_aligned_malloc *>(ptr), 0); }
-  void operator delete[](void * ptr) { ei_aligned_free(static_cast<ei_byte_forcing_aligned_malloc *>(ptr), 0); }
-};
-
-template<typename T, int SizeAtCompileTime,
-         bool NeedsToAlign = (SizeAtCompileTime!=Dynamic) && ((sizeof(T)*SizeAtCompileTime)%16==0)>
-struct ei_with_aligned_operator_new : public WithAlignedOperatorNew {};
-
-template<typename T, int SizeAtCompileTime>
-struct ei_with_aligned_operator_new<T,SizeAtCompileTime,false> {};
-
-/** \class ei_new_allocator
-  *
-  * \brief stl compatible allocator to use with with fixed-size vector and matrix types
-  *
-  * STL allocator simply wrapping operators new[] and delete[]. Unlike GCC's default new_allocator,
-  * ei_new_allocator call operator new on the type \a T and not the general new operator ignoring
-  * overloaded version of operator new.
-  *
-  * Example:
-  * \code
-  * // Vector4f requires 16 bytes alignment:
-  * std::vector<Vector4f,ei_new_allocator<Vector4f> > dataVec4;
-  * // Vector3f does not require 16 bytes alignment, no need to use Eigen's allocator:
-  * std::vector<Vector3f> dataVec3;
-  *
-  * struct Foo : WithAlignedOperatorNew {
-  *   char dummy;
-  *   Vector4f some_vector;
-  * };
-  * std::vector<Foo,ei_new_allocator<Foo> > dataFoo;
-  * \endcode
-  *
-  * \sa class WithAlignedOperatorNew
-  */
-template<typename T> class ei_new_allocator
-{
-  public:
-    typedef T         value_type;
+public:
+    typedef size_t    size_type;
+    typedef ptrdiff_t difference_type;
     typedef T*        pointer;
     typedef const T*  const_pointer;
     typedef T&        reference;
     typedef const T&  const_reference;
+    typedef T         value_type;
 
-    template<typename OtherType>
+    template<class U>
     struct rebind
-    { typedef ei_new_allocator<OtherType> other; };
+    {
+        typedef aligned_allocator<U> other;
+    };
 
-    T* address(T& ref) const { return &ref; }
-    const T* address(const T& ref) const { return &ref; }
-    T* allocate(size_t size, const void* = 0) { return new T[size]; }
-    void deallocate(T* ptr, size_t) { delete[] ptr; }
-    size_t max_size() const { return size_t(-1) / sizeof(T); }
-    // FIXME I'm note sure about this construction...
-    void construct(T* ptr, const T& refObj) { ::new(ptr) T(refObj); }
-    void destroy(T* ptr) { ptr->~T(); }
+    pointer address( reference value ) const
+    {
+        return &value;
+    }
+
+    const_pointer address( const_reference value ) const
+    {
+        return &value;
+    }
+
+    aligned_allocator() throw()
+    {
+    }
+
+    aligned_allocator( const aligned_allocator& ) throw()
+    {
+    }
+
+    template<class U>
+    aligned_allocator( const aligned_allocator<U>& ) throw()
+    {
+    }
+
+    ~aligned_allocator() throw()
+    {
+    }
+
+    size_type max_size() const throw()
+    {
+        return std::numeric_limits<size_type>::max();
+    }
+
+    pointer allocate( size_type num, const_pointer* hint = 0 )
+    {
+        static_cast<void>( hint ); // suppress unused variable warning
+        return static_cast<pointer>( ei_aligned_malloc( num * sizeof(T) ) );
+    }
+
+    void construct( pointer p, const T& value )
+    {
+        ::new( p ) T( value );
+    }
+
+    void destroy( pointer p )
+    {
+        p->~T();
+    }
+
+    void deallocate( pointer p, size_type /*num*/ )
+    {
+        ei_aligned_free( p );
+    }
+    
+    bool operator!=(const aligned_allocator<T>& other) const
+    { return false; }
+    
+    bool operator==(const aligned_allocator<T>& other) const
+    { return true; }
 };
 
 #endif // EIGEN_MEMORY_H

Eigen/src/Core/util/StaticAssert.h

@@ -71,7 +71,12 @@
         INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS,
         INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION,
         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY,
-        THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES
+        THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES,
+        THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES,
+        INVALID_MATRIX_TEMPLATE_PARAMETERS,
+        INVALID_MATRIXBASE_TEMPLATE_PARAMETERS,
+        BOTH_MATRICES_MUST_HAVE_THE_SAME_STORAGE_ORDER,
+        THIS_METHOD_IS_ONLY_FOR_DIAGONAL_MATRIX
       };
     };
 

Eigen/src/Core/util/XprHelper.h

@@ -37,6 +37,10 @@
 //classes inheriting ei_no_assignment_operator don't generate a default operator=.
 class ei_no_assignment_operator
 {
+#if EIGEN_GCC3_OR_OLDER
+  protected:
+    void nevermind_this_is_just_to_work_around_a_stupid_gcc3_warning();
+#endif
   private:
     ei_no_assignment_operator& operator=(const ei_no_assignment_operator&);
 };
@@ -89,11 +93,11 @@ template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxC
 class ei_compute_matrix_flags
 {
     enum {
-      row_major_bit = Options&Matrix_RowMajor ? RowMajorBit : 0,
+      row_major_bit = Options&RowMajor ? RowMajorBit : 0,
       inner_max_size = row_major_bit ? MaxCols : MaxRows,
       is_big = inner_max_size == Dynamic,
       is_packet_size_multiple = (Cols*Rows) % ei_packet_traits<Scalar>::size == 0,
-      aligned_bit = ((Options&Matrix_AutoAlign) && (is_big || is_packet_size_multiple)) ? AlignedBit : 0,
+      aligned_bit = ((Options&AutoAlign) && (is_big || is_packet_size_multiple)) ? AlignedBit : 0,
       packet_access_bit = ei_packet_traits<Scalar>::size > 1 && aligned_bit ? PacketAccessBit : 0
     };
 
@@ -117,7 +121,7 @@ template<typename T> struct ei_eval<T,IsDense>
   typedef Matrix<typename ei_traits<T>::Scalar,
                 ei_traits<T>::RowsAtCompileTime,
                 ei_traits<T>::ColsAtCompileTime,
-                Matrix_AutoAlign | (ei_traits<T>::Flags&RowMajorBit ? Matrix_RowMajor : Matrix_ColMajor),
+                AutoAlign | (ei_traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor),
                 ei_traits<T>::MaxRowsAtCompileTime,
                 ei_traits<T>::MaxColsAtCompileTime
           > type;
@@ -138,7 +142,7 @@ template<typename T> struct ei_plain_matrix_type
   typedef Matrix<typename ei_traits<T>::Scalar,
                 ei_traits<T>::RowsAtCompileTime,
                 ei_traits<T>::ColsAtCompileTime,
-                Matrix_AutoAlign | (ei_traits<T>::Flags&RowMajorBit ? Matrix_RowMajor : Matrix_ColMajor),
+                AutoAlign | (ei_traits<T>::Flags&RowMajorBit ? RowMajor : ColMajor),
                 ei_traits<T>::MaxRowsAtCompileTime,
                 ei_traits<T>::MaxColsAtCompileTime
           > type;
@@ -151,7 +155,7 @@ template<typename T> struct ei_plain_matrix_type_column_major
   typedef Matrix<typename ei_traits<T>::Scalar,
                 ei_traits<T>::RowsAtCompileTime,
                 ei_traits<T>::ColsAtCompileTime,
-                Matrix_AutoAlign | Matrix_ColMajor,
+                AutoAlign | ColMajor,
                 ei_traits<T>::MaxRowsAtCompileTime,
                 ei_traits<T>::MaxColsAtCompileTime
           > type;

Eigen/src/Geometry/AlignedBox.h

@@ -25,7 +25,7 @@
 #ifndef EIGEN_ALIGNEDBOX_H
 #define EIGEN_ALIGNEDBOX_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   * \nonstableyet
   *
   * \class AlignedBox
@@ -39,10 +39,9 @@
   */
 template <typename _Scalar, int _AmbientDim>
 class AlignedBox
-  : public ei_with_aligned_operator_new<_Scalar,_AmbientDim==Dynamic ? Dynamic : _AmbientDim+1>
 {
 public:
-
+EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim==Dynamic ? Dynamic : _AmbientDim+1)
   enum { AmbientDimAtCompileTime = _AmbientDim };
   typedef _Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;

Eigen/src/Geometry/AngleAxis.h

@@ -25,7 +25,7 @@
 #ifndef EIGEN_ANGLEAXIS_H
 #define EIGEN_ANGLEAXIS_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class AngleAxis
   *
@@ -147,7 +147,7 @@ public:
   inline explicit AngleAxis(const AngleAxis<OtherScalarType>& other)
   {
     m_axis = other.axis().template cast<Scalar>();
-    m_angle = other.angle();
+    m_angle = Scalar(other.angle());
   }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
@@ -158,10 +158,10 @@ public:
   { return m_axis.isApprox(other.m_axis, prec) && ei_isApprox(m_angle,other.m_angle, prec); }
 };
 
-/** \ingroup GeometryModule
+/** \ingroup Geometry_Module
   * single precision angle-axis type */
 typedef AngleAxis<float> AngleAxisf;
-/** \ingroup GeometryModule
+/** \ingroup Geometry_Module
   * double precision angle-axis type */
 typedef AngleAxis<double> AngleAxisd;
 

Eigen/src/Geometry/EulerAngles.h

@@ -25,7 +25,7 @@
 #ifndef EIGEN_EULERANGLES_H
 #define EIGEN_EULERANGLES_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   * \nonstableyet
   *
   * \returns the Euler-angles of the rotation matrix \c *this using the convention defined by the triplet (\a a0,\a a1,\a a2)
@@ -60,31 +60,31 @@ MatrixBase<Derived>::eulerAngles(int a0, int a1, int a2) const
   if (a0==a2)
   {
     Scalar s = Vector2(coeff(j,i) , coeff(k,i)).norm();
-    res[1] = std::atan2(s, coeff(i,i));
+    res[1] = ei_atan2(s, coeff(i,i));
     if (s > epsilon)
     {
-      res[0] = std::atan2(coeff(j,i), coeff(k,i));
-      res[2] = std::atan2(coeff(i,j),-coeff(i,k));
+      res[0] = ei_atan2(coeff(j,i), coeff(k,i));
+      res[2] = ei_atan2(coeff(i,j),-coeff(i,k));
     }
     else
     {
       res[0] = Scalar(0);
-      res[2] = (coeff(i,i)>0?1:-1)*std::atan2(-coeff(k,j), coeff(j,j));
+      res[2] = (coeff(i,i)>0?1:-1)*ei_atan2(-coeff(k,j), coeff(j,j));
     }
   }
   else
   {
     Scalar c = Vector2(coeff(i,i) , coeff(i,j)).norm();
-    res[1] = std::atan2(-coeff(i,k), c);
+    res[1] = ei_atan2(-coeff(i,k), c);
     if (c > epsilon)
     {
-      res[0] = std::atan2(coeff(j,k), coeff(k,k));
-      res[2] = std::atan2(coeff(i,j), coeff(i,i));
+      res[0] = ei_atan2(coeff(j,k), coeff(k,k));
+      res[2] = ei_atan2(coeff(i,j), coeff(i,i));
     }
     else
     {
       res[0] = Scalar(0);
-      res[2] = (coeff(i,k)>0?1:-1)*std::atan2(-coeff(k,j), coeff(j,j));
+      res[2] = (coeff(i,k)>0?1:-1)*ei_atan2(-coeff(k,j), coeff(j,j));
     }
   }
   if (!odd)

Eigen/src/Geometry/Hyperplane.h

@@ -26,7 +26,7 @@
 #ifndef EIGEN_HYPERPLANE_H
 #define EIGEN_HYPERPLANE_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class Hyperplane
   *
@@ -45,17 +45,16 @@
   */
 template <typename _Scalar, int _AmbientDim>
 class Hyperplane
-  : public ei_with_aligned_operator_new<_Scalar,_AmbientDim==Dynamic ? Dynamic : _AmbientDim+1>
 {
 public:
-
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim==Dynamic ? Dynamic : _AmbientDim+1)
   enum { AmbientDimAtCompileTime = _AmbientDim };
   typedef _Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef Matrix<Scalar,AmbientDimAtCompileTime,1> VectorType;
-  typedef Matrix<Scalar,AmbientDimAtCompileTime==Dynamic
+  typedef Matrix<Scalar,int(AmbientDimAtCompileTime)==Dynamic
                         ? Dynamic
-                        : AmbientDimAtCompileTime+1,1> Coefficients;
+                        : int(AmbientDimAtCompileTime)+1,1> Coefficients;
   typedef Block<Coefficients,AmbientDimAtCompileTime,1> NormalReturnType;
 
   /** Default constructor without initialization */

Eigen/src/Geometry/ParametrizedLine.h

@@ -26,7 +26,7 @@
 #ifndef EIGEN_PARAMETRIZEDLINE_H
 #define EIGEN_PARAMETRIZEDLINE_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class ParametrizedLine
   *
@@ -41,10 +41,9 @@
   */
 template <typename _Scalar, int _AmbientDim>
 class ParametrizedLine
-  : public ei_with_aligned_operator_new<_Scalar,_AmbientDim>
 {
 public:
-
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
   enum { AmbientDimAtCompileTime = _AmbientDim };
   typedef _Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;

Eigen/src/Geometry/Quaternion.h

@@ -30,7 +30,7 @@ template<typename Other,
          int OtherCols=Other::ColsAtCompileTime>
 struct ei_quaternion_assign_impl;
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class Quaternion
   *
@@ -59,19 +59,19 @@ template<typename _Scalar> struct ei_traits<Quaternion<_Scalar> >
 
 template<typename _Scalar>
 class Quaternion : public RotationBase<Quaternion<_Scalar>,3>
-  , public ei_with_aligned_operator_new<_Scalar,4>
 {
   typedef RotationBase<Quaternion<_Scalar>,3> Base;
-  typedef Matrix<_Scalar, 4, 1> Coefficients;
-  Coefficients m_coeffs;
 
 public:
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,4)
 
   using Base::operator*;
 
   /** the scalar type of the coefficients */
   typedef _Scalar Scalar;
 
+  /** the type of the Coefficients 4-vector */
+  typedef Matrix<Scalar, 4, 1> Coefficients;
   /** the type of a 3D vector */
   typedef Matrix<Scalar,3,1> Vector3;
   /** the equivalent rotation matrix type */
@@ -109,9 +109,8 @@ public:
   /** \returns a vector expression of the coefficients (x,y,z,w) */
   inline Coefficients& coeffs() { return m_coeffs; }
 
-  /** Default constructor and initializing an identity quaternion. */
-  inline Quaternion()
-  { m_coeffs << 0, 0, 0, 1; }
+  /** Default constructor leaving the quaternion uninitialized. */
+  inline Quaternion() {}
 
   /** Constructs and initializes the quaternion \f$ w+xi+yj+zk \f$ from
     * its four coefficients \a w, \a x, \a y and \a z.
@@ -149,7 +148,7 @@ public:
 
   /** \sa Quaternion::Identity(), MatrixBase::setIdentity()
     */
-  inline Quaternion& setIdentity() { m_coeffs << 1, 0, 0, 0; return *this; }
+  inline Quaternion& setIdentity() { m_coeffs << 0, 0, 0, 1; return *this; }
 
   /** \returns the squared norm of the quaternion's coefficients
     * \sa Quaternion::norm(), MatrixBase::squaredNorm()
@@ -214,26 +213,56 @@ public:
   bool isApprox(const Quaternion& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
   { return m_coeffs.isApprox(other.m_coeffs, prec); }
 
+protected:
+  Coefficients m_coeffs;
 };
 
-/** \ingroup GeometryModule
+/** \ingroup Geometry_Module
   * single precision quaternion type */
 typedef Quaternion<float> Quaternionf;
-/** \ingroup GeometryModule
+/** \ingroup Geometry_Module
   * double precision quaternion type */
 typedef Quaternion<double> Quaterniond;
 
+// Generic Quaternion * Quaternion product
+template<int Arch,typename Scalar> inline Quaternion<Scalar>
+ei_quaternion_product(const Quaternion<Scalar>& a, const Quaternion<Scalar>& b)
+{
+  return Quaternion<Scalar>
+  (
+    a.w() * b.w() - a.x() * b.x() - a.y() * b.y() - a.z() * b.z(),
+    a.w() * b.x() + a.x() * b.w() + a.y() * b.z() - a.z() * b.y(),
+    a.w() * b.y() + a.y() * b.w() + a.z() * b.x() - a.x() * b.z(),
+    a.w() * b.z() + a.z() * b.w() + a.x() * b.y() - a.y() * b.x()
+  );
+}
+
+#ifdef EIGEN_VECTORIZE_SSE
+template<> inline Quaternion<float>
+ei_quaternion_product<EiArch_SSE,float>(const Quaternion<float>& _a, const Quaternion<float>& _b)
+{
+  const __m128 mask = _mm_castsi128_ps(_mm_setr_epi32(0,0,0,0x80000000));
+  Quaternion<float> res;
+  __m128 a = _a.coeffs().packet<Aligned>(0);
+  __m128 b = _b.coeffs().packet<Aligned>(0);
+  __m128 flip1 = _mm_xor_ps(_mm_mul_ps(ei_vec4f_swizzle1(a,1,2,0,2),
+                                       ei_vec4f_swizzle1(b,2,0,1,2)),mask);
+  __m128 flip2 = _mm_xor_ps(_mm_mul_ps(ei_vec4f_swizzle1(a,3,3,3,1),
+                                       ei_vec4f_swizzle1(b,0,1,2,1)),mask);
+  ei_pstore(&res.x(),
+            _mm_add_ps(_mm_sub_ps(_mm_mul_ps(a,ei_vec4f_swizzle1(b,3,3,3,3)),
+                                  _mm_mul_ps(ei_vec4f_swizzle1(a,2,0,1,0),
+                                             ei_vec4f_swizzle1(b,1,2,0,0))),
+                       _mm_add_ps(flip1,flip2)));
+  return res;
+}
+#endif
+
 /** \returns the concatenation of two rotations as a quaternion-quaternion product */
 template <typename Scalar>
 inline Quaternion<Scalar> Quaternion<Scalar>::operator* (const Quaternion& other) const
 {
-  return Quaternion
-  (
-    this->w() * other.w() - this->x() * other.x() - this->y() * other.y() - this->z() * other.z(),
-    this->w() * other.x() + this->x() * other.w() + this->y() * other.z() - this->z() * other.y(),
-    this->w() * other.y() + this->y() * other.w() + this->z() * other.x() - this->x() * other.z(),
-    this->w() * other.z() + this->z() * other.w() + this->x() * other.y() - this->y() * other.x()
-  );
+  return ei_quaternion_product<EiArch>(*this,other);
 }
 
 /** \sa operator*(Quaternion) */
@@ -345,7 +374,6 @@ inline Quaternion<Scalar>& Quaternion<Scalar>::setFromTwoVectors(const MatrixBas
 {
   Vector3 v0 = a.normalized();
   Vector3 v1 = b.normalized();
-  Vector3 axis = v0.cross(v1);
   Scalar c = v0.dot(v1);
 
   // if dot == 1, vectors are the same
@@ -353,8 +381,18 @@ inline Quaternion<Scalar>& Quaternion<Scalar>::setFromTwoVectors(const MatrixBas
   {
     // set to identity
     this->w() = 1; this->vec().setZero();
+    return *this;
   }
-  Scalar s = ei_sqrt((1+c)*2);
+  // if dot == -1, vectors are opposites
+  if (ei_isApprox(c,Scalar(-1)))
+  {
+    this->vec() = v0.unitOrthogonal();
+    this->w() = 0;
+    return *this;
+  }
+
+  Vector3 axis = v0.cross(v1);
+  Scalar s = ei_sqrt((Scalar(1)+c)*Scalar(2));
   Scalar invs = Scalar(1)/s;
   this->vec() = axis * invs;
   this->w() = s * Scalar(0.5);
@@ -412,22 +450,31 @@ inline Scalar Quaternion<Scalar>::angularDistance(const Quaternion& other) const
 template <typename Scalar>
 Quaternion<Scalar> Quaternion<Scalar>::slerp(Scalar t, const Quaternion& other) const
 {
-  static const Scalar one = Scalar(1) - precision<Scalar>();
+  static const Scalar one = Scalar(1) - machine_epsilon<Scalar>();
   Scalar d = this->dot(other);
   Scalar absD = ei_abs(d);
+
+  Scalar scale0;
+  Scalar scale1;
+
   if (absD>=one)
-    return *this;
+  {
+    scale0 = Scalar(1) - t;
+    scale1 = t;
+  }
+  else
+  {
+    // theta is the angle between the 2 quaternions
+    Scalar theta = std::acos(absD);
+    Scalar sinTheta = ei_sin(theta);
 
-  // theta is the angle between the 2 quaternions
-  Scalar theta = std::acos(absD);
-  Scalar sinTheta = ei_sin(theta);
+    scale0 = ei_sin( ( Scalar(1) - t ) * theta) / sinTheta;
+    scale1 = ei_sin( ( t * theta) ) / sinTheta;
+    if (d<0)
+      scale1 = -scale1;
+  }
 
-  Scalar scale0 = ei_sin( ( Scalar(1) - t ) * theta) / sinTheta;
-  Scalar scale1 = ei_sin( ( t * theta) ) / sinTheta;
-  if (d<0)
-    scale1 = -scale1;
-
-  return Quaternion(scale0 * m_coeffs + scale1 * other.m_coeffs);
+  return Quaternion<Scalar>(scale0 * coeffs() + scale1 * other.coeffs());
 }
 
 // set from a rotation matrix
@@ -459,7 +506,7 @@ struct ei_quaternion_assign_impl<Other,3,3>
       int j = (i+1)%3;
       int k = (j+1)%3;
 
-      t = ei_sqrt(mat.coeff(i,i)-mat.coeff(j,j)-mat.coeff(k,k) + 1.0);
+      t = ei_sqrt(mat.coeff(i,i)-mat.coeff(j,j)-mat.coeff(k,k) + Scalar(1.0));
       q.coeffs().coeffRef(i) = Scalar(0.5) * t;
       t = Scalar(0.5)/t;
       q.w() = (mat.coeff(k,j)-mat.coeff(j,k))*t;

Eigen/src/Geometry/Rotation2D.h

@@ -25,7 +25,7 @@
 #ifndef EIGEN_ROTATION2D_H
 #define EIGEN_ROTATION2D_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class Rotation2D
   *
@@ -85,7 +85,7 @@ public:
 
   /** Concatenates two rotations */
   inline Rotation2D& operator*=(const Rotation2D& other)
-  { return m_angle += other.m_angle; }
+  { return m_angle += other.m_angle; return *this; }
 
   /** Applies the rotation to a 2D vector */
   Vector2 operator* (const Vector2& vec) const
@@ -114,7 +114,7 @@ public:
   template<typename OtherScalarType>
   inline explicit Rotation2D(const Rotation2D<OtherScalarType>& other)
   {
-    m_angle = other.angle();
+    m_angle = Scalar(other.angle());
   }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
@@ -125,10 +125,10 @@ public:
   { return ei_isApprox(m_angle,other.m_angle, prec); }
 };
 
-/** \ingroup GeometryModule
+/** \ingroup Geometry_Module
   * single precision 2D rotation type */
 typedef Rotation2D<float> Rotation2Df;
-/** \ingroup GeometryModule
+/** \ingroup Geometry_Module
   * double precision 2D rotation type */
 typedef Rotation2D<double> Rotation2Dd;
 

Eigen/src/Geometry/Scaling.h

@@ -25,7 +25,7 @@
 #ifndef EIGEN_SCALING_H
 #define EIGEN_SCALING_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class Scaling
   *
@@ -41,9 +41,9 @@
   */
 template<typename _Scalar, int _Dim>
 class Scaling
-  : public ei_with_aligned_operator_new<_Scalar,_Dim>
 {
 public:
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim)
   /** dimension of the space */
   enum { Dim = _Dim };
   /** the scalar type of the coefficients */
@@ -118,7 +118,7 @@ public:
 
   /** \returns the inverse scaling */
   inline Scaling inverse() const
-  { return Scaling(coeffs.cwise().inverse()); }
+  { return Scaling(coeffs().cwise().inverse()); }
 
   inline Scaling& operator=(const Scaling& other)
   {
@@ -149,7 +149,7 @@ public:
 
 };
 
-/** \addtogroup GeometryModule */
+/** \addtogroup Geometry_Module */
 //@{
 typedef Scaling<float, 2> Scaling2f;
 typedef Scaling<double,2> Scaling2d;

Eigen/src/Geometry/Transform.h

@@ -2,6 +2,7 @@
 // for linear algebra. Eigen itself is part of the KDE project.
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -42,7 +43,7 @@ template< typename Other,
           int OtherCols=Other::ColsAtCompileTime>
 struct ei_transform_product_impl;
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class Transform
   *
@@ -61,10 +62,9 @@ struct ei_transform_product_impl;
   */
 template<typename _Scalar, int _Dim>
 class Transform
-  : public ei_with_aligned_operator_new<_Scalar,_Dim==Dynamic ? Dynamic : (_Dim+1)*(_Dim+1)>
 {
 public:
-
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim==Dynamic ? Dynamic : (_Dim+1)*(_Dim+1))
   enum {
     Dim = _Dim,     ///< space dimension in which the transformation holds
     HDim = _Dim+1   ///< size of a respective homogeneous vector
@@ -96,7 +96,9 @@ public:
   inline Transform() { }
 
   inline Transform(const Transform& other)
-  { m_matrix = other.m_matrix; }
+  {
+    m_matrix = other.m_matrix;
+  }
 
   inline explicit Transform(const TranslationType& t) { *this = t; }
   inline explicit Transform(const ScalingType& s) { *this = s; }
@@ -196,6 +198,10 @@ public:
 
   /** \sa MatrixBase::setIdentity() */
   void setIdentity() { m_matrix.setIdentity(); }
+  static const typename MatrixType::IdentityReturnType Identity()
+  {
+    return MatrixType::Identity();
+  }
 
   template<typename OtherDerived>
   inline Transform& scale(const MatrixBase<OtherDerived> &other);
@@ -243,8 +249,11 @@ public:
   template<typename Derived>
   inline Transform operator*(const RotationBase<Derived,Dim>& r) const;
 
-  EIGEN_DEPRECATED LinearMatrixType extractRotation(TransformTraits traits = Affine) const { return rotation(traits); }
-  LinearMatrixType rotation(TransformTraits traits = Affine) const;
+  LinearMatrixType rotation() const;
+  template<typename RotationMatrixType, typename ScalingMatrixType>
+  void computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const;
+  template<typename ScalingMatrixType, typename RotationMatrixType>
+  void computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const;
 
   template<typename PositionDerived, typename OrientationType, typename ScaleDerived>
   Transform& fromPositionOrientationScale(const MatrixBase<PositionDerived> &position,
@@ -278,17 +287,21 @@ public:
   bool isApprox(const Transform& other, typename NumTraits<Scalar>::Real prec = precision<Scalar>()) const
   { return m_matrix.isApprox(other.m_matrix, prec); }
 
+  #ifdef EIGEN_TRANSFORM_PLUGIN
+  #include EIGEN_TRANSFORM_PLUGIN
+  #endif
+
 protected:
 
 };
 
-/** \ingroup GeometryModule */
+/** \ingroup Geometry_Module */
 typedef Transform<float,2> Transform2f;
-/** \ingroup GeometryModule */
+/** \ingroup Geometry_Module */
 typedef Transform<float,3> Transform3f;
-/** \ingroup GeometryModule */
+/** \ingroup Geometry_Module */
 typedef Transform<double,2> Transform2d;
-/** \ingroup GeometryModule */
+/** \ingroup Geometry_Module */
 typedef Transform<double,3> Transform3d;
 
 /**************************
@@ -330,9 +343,9 @@ template<typename Scalar, int Dim>
 QMatrix Transform<Scalar,Dim>::toQMatrix(void) const
 {
   EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  return QMatrix(other.coeffRef(0,0), other.coeffRef(1,0),
-                 other.coeffRef(0,1), other.coeffRef(1,1),
-                 other.coeffRef(0,2), other.coeffRef(1,2));
+  return QMatrix(m_matrix.coeff(0,0), m_matrix.coeff(1,0),
+                 m_matrix.coeff(0,1), m_matrix.coeff(1,1),
+                 m_matrix.coeff(0,2), m_matrix.coeff(1,2));
 }
 
 /** Initialises \c *this from a QTransform assuming the dimension is 2.
@@ -364,12 +377,12 @@ Transform<Scalar,Dim>& Transform<Scalar,Dim>::operator=(const QTransform& other)
   * This function is available only if the token EIGEN_QT_SUPPORT is defined.
   */
 template<typename Scalar, int Dim>
-QMatrix Transform<Scalar,Dim>::toQTransform(void) const
+QTransform Transform<Scalar,Dim>::toQTransform(void) const
 {
   EIGEN_STATIC_ASSERT(Dim==2, YOU_MADE_A_PROGRAMMING_MISTAKE)
-  return QTransform(other.coeffRef(0,0), other.coeffRef(1,0), other.coeffRef(2,0)
-                    other.coeffRef(0,1), other.coeffRef(1,1), other.coeffRef(2,1)
-                    other.coeffRef(0,2), other.coeffRef(1,2), other.coeffRef(2,2);
+  return QTransform(m_matrix.coeff(0,0), m_matrix.coeff(1,0), m_matrix.coeff(2,0),
+                    m_matrix.coeff(0,1), m_matrix.coeff(1,1), m_matrix.coeff(2,1),
+                    m_matrix.coeff(0,2), m_matrix.coeff(1,2), m_matrix.coeff(2,2));
 }
 #endif
 
@@ -586,47 +599,61 @@ inline Transform<Scalar,Dim> Transform<Scalar,Dim>::operator*(const RotationBase
   return res;
 }
 
-/***************************
-*** Specialial functions ***
-***************************/
+/************************
+*** Special functions ***
+************************/
 
 /** \returns the rotation part of the transformation
+  * \nonstableyet
   *
-  * \param traits allows to optimize the extraction process when the transformion
-  * is known to be not a general aafine transformation. The possible values are:
-  *  - Affine which use a QR decomposition (default),
-  *  - Isometry which simply returns the linear part !
+  * \svd_module
   *
-  * \warning this function consider the scaling is positive
-  *
-  * \warning to use this method in the general case (traits==GenericAffine), you need
-  * to include the QR module.
-  *
-  * \sa inverse(), class QR
+  * \sa computeRotationScaling(), computeScalingRotation(), class SVD
   */
 template<typename Scalar, int Dim>
 typename Transform<Scalar,Dim>::LinearMatrixType
-Transform<Scalar,Dim>::rotation(TransformTraits traits) const
+Transform<Scalar,Dim>::rotation() const
 {
-  ei_assert(traits!=Projective && "you cannot extract a rotation from a non affine transformation");
-  if (traits == Affine)
-  {
-    // FIXME maybe QR should be fixed to return a R matrix with a positive diagonal ??
-    QR<LinearMatrixType> qr(linear());
-    LinearMatrixType matQ = qr.matrixQ();
-    LinearMatrixType matR = qr.matrixR();
-    for (int i=0 ; i<Dim; ++i)
-      if (matR.coeff(i,i)<0)
-        matQ.col(i) = -matQ.col(i);
-    return matQ;
-  }
-  else if (traits == Isometry) // though that's stupid let's handle it !
-    return linear();
-  else
-  {
-    ei_assert("invalid traits value in Transform::extractRotation()");
-    return LinearMatrixType();
-  }
+  LinearMatrixType result;
+  computeRotationScaling(&result, (LinearMatrixType*)0);
+  return result;
+}
+
+
+/** decomposes the linear part of the transformation as a product rotation x scaling, the scaling being
+  * not necessarily positive.
+  *
+  * If either pointer is zero, the corresponding computation is skipped.
+  *
+  * \nonstableyet
+  *
+  * \svd_module
+  *
+  * \sa computeScalingRotation(), rotation(), class SVD
+  */
+template<typename Scalar, int Dim>
+template<typename RotationMatrixType, typename ScalingMatrixType>
+void Transform<Scalar,Dim>::computeRotationScaling(RotationMatrixType *rotation, ScalingMatrixType *scaling) const
+{
+  linear().svd().computeRotationScaling(rotation, scaling);
+}
+
+/** decomposes the linear part of the transformation as a product rotation x scaling, the scaling being
+  * not necessarily positive.
+  *
+  * If either pointer is zero, the corresponding computation is skipped.
+  *
+  * \nonstableyet
+  *
+  * \svd_module
+  *
+  * \sa computeRotationScaling(), rotation(), class SVD
+  */
+template<typename Scalar, int Dim>
+template<typename ScalingMatrixType, typename RotationMatrixType>
+void Transform<Scalar,Dim>::computeScalingRotation(ScalingMatrixType *scaling, RotationMatrixType *rotation) const
+{
+  linear().svd().computeScalingRotation(scaling, rotation);
 }
 
 /** Convenient method to set \c *this from a position, orientation and scale
@@ -646,7 +673,9 @@ Transform<Scalar,Dim>::fromPositionOrientationScale(const MatrixBase<PositionDer
   return *this;
 }
 
-/** \returns the inverse transformation matrix according to some given knowledge
+/** \nonstableyet
+  *
+  * \returns the inverse transformation matrix according to some given knowledge
   * on \c *this.
   *
   * \param traits allows to optimize the inversion process when the transformion

Eigen/src/Geometry/Translation.h

@@ -25,7 +25,7 @@
 #ifndef EIGEN_TRANSLATION_H
 #define EIGEN_TRANSLATION_H
 
-/** \geometry_module \ingroup GeometryModule
+/** \geometry_module \ingroup Geometry_Module
   *
   * \class Translation
   *
@@ -41,9 +41,9 @@
   */
 template<typename _Scalar, int _Dim>
 class Translation
-  : public ei_with_aligned_operator_new<_Scalar,_Dim>
 {
 public:
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_Dim)
   /** dimension of the space */
   enum { Dim = _Dim };
   /** the scalar type of the coefficients */
@@ -152,7 +152,7 @@ public:
 
 };
 
-/** \addtogroup GeometryModule */
+/** \addtogroup Geometry_Module */
 //@{
 typedef Translation<float, 2> Translation2f;
 typedef Translation<double,2> Translation2d;

Eigen/src/LU/Inverse.h

@@ -29,8 +29,8 @@
 *** Part 1 : optimized implementations for fixed-size 2,3,4 cases ***
 ********************************************************************/
 
-template<typename MatrixType>
-void ei_compute_inverse_in_size2_case(const MatrixType& matrix, MatrixType* result)
+template<typename XprType, typename MatrixType>
+void ei_compute_inverse_in_size2_case(const XprType& matrix, MatrixType* result)
 {
   typedef typename MatrixType::Scalar Scalar;
   const Scalar invdet = Scalar(1) / matrix.determinant();
@@ -75,81 +75,155 @@ void ei_compute_inverse_in_size3_case(const MatrixType& matrix, MatrixType* resu
   result->coeffRef(2, 2) = matrix.minor(2,2).determinant() * invdet;
 }
 
-template<typename MatrixType>
-bool ei_compute_inverse_in_size4_case_helper(const MatrixType& matrix, MatrixType* result)
+template<typename MatrixType, typename Scalar = typename MatrixType::Scalar>
+struct ei_compute_inverse_in_size4_case
 {
-  /* Let's split M into four 2x2 blocks:
-    * (P Q)
-    * (R S)
-    * If P is invertible, with inverse denoted by P_inverse, and if
-    * (S - R*P_inverse*Q) is also invertible, then the inverse of M is
-    * (P' Q')
-    * (R' S')
-    * where
-    * S' = (S - R*P_inverse*Q)^(-1)
-    * P' = P1 + (P1*Q) * S' *(R*P_inverse)
-    * Q' = -(P_inverse*Q) * S'
-    * R' = -S' * (R*P_inverse)
-    */
-  typedef Block<MatrixType,2,2> XprBlock22;
-  typedef typename MatrixBase<XprBlock22>::PlainMatrixType Block22;
-  Block22 P_inverse;
-  if(ei_compute_inverse_in_size2_case_with_check(matrix.template block<2,2>(0,0), &P_inverse))
+  static void run(const MatrixType& matrix, MatrixType& result)
   {
-    const Block22 Q = matrix.template block<2,2>(0,2);
-    const Block22 P_inverse_times_Q = P_inverse * Q;
-    const XprBlock22 R = matrix.template block<2,2>(2,0);
-    const Block22 R_times_P_inverse = R * P_inverse;
-    const Block22 R_times_P_inverse_times_Q = R_times_P_inverse * Q;
-    const XprBlock22 S = matrix.template block<2,2>(2,2);
-    const Block22 X = S - R_times_P_inverse_times_Q;
-    Block22 Y;
-    ei_compute_inverse_in_size2_case(X, &Y);
-    result->template block<2,2>(2,2) = Y;
-    result->template block<2,2>(2,0) = - Y * R_times_P_inverse;
-    const Block22 Z = P_inverse_times_Q * Y;
-    result->template block<2,2>(0,2) = - Z;
-    result->template block<2,2>(0,0) = P_inverse + Z * R_times_P_inverse;
-    return true;
+    result.coeffRef(0,0) = matrix.minor(0,0).determinant();
+    result.coeffRef(1,0) = -matrix.minor(0,1).determinant();
+    result.coeffRef(2,0) = matrix.minor(0,2).determinant();
+    result.coeffRef(3,0) = -matrix.minor(0,3).determinant();
+    result.coeffRef(0,2) = matrix.minor(2,0).determinant();
+    result.coeffRef(1,2) = -matrix.minor(2,1).determinant();
+    result.coeffRef(2,2) = matrix.minor(2,2).determinant();
+    result.coeffRef(3,2) = -matrix.minor(2,3).determinant();
+    result.coeffRef(0,1) = -matrix.minor(1,0).determinant();
+    result.coeffRef(1,1) = matrix.minor(1,1).determinant();
+    result.coeffRef(2,1) = -matrix.minor(1,2).determinant();
+    result.coeffRef(3,1) = matrix.minor(1,3).determinant();
+    result.coeffRef(0,3) = -matrix.minor(3,0).determinant();
+    result.coeffRef(1,3) = matrix.minor(3,1).determinant();
+    result.coeffRef(2,3) = -matrix.minor(3,2).determinant();
+    result.coeffRef(3,3) = matrix.minor(3,3).determinant();
+    result /= (matrix.col(0).cwise()*result.row(0).transpose()).sum();
   }
-  else
-  {
-    return false;
-  }
-}
+};
 
+#ifdef EIGEN_VECTORIZE_SSE
+// The SSE code for the 4x4 float matrix inverse in this file comes from the file
+//   ftp://download.intel.com/design/PentiumIII/sml/24504301.pdf
+// its copyright information is:
+//   Copyright (C) 1999 Intel Corporation
+// See page ii of that document for legal stuff. Not being lawyers, we just assume
+// here that if Intel makes this document publically available, with source code
+// and detailed explanations, it's because they want their CPUs to be fed with
+// good code, and therefore they presumably don't mind us using it in Eigen.
 template<typename MatrixType>
-void ei_compute_inverse_in_size4_case(const MatrixType& matrix, MatrixType* result)
+struct ei_compute_inverse_in_size4_case<MatrixType, float>
 {
-  if(ei_compute_inverse_in_size4_case_helper(matrix, result))
+  static void run(const MatrixType& matrix, MatrixType& result)
   {
-    // good ! The topleft 2x2 block was invertible, so the 2x2 blocks approach is successful.
-    return;
+    // Variables (Streaming SIMD Extensions registers) which will contain cofactors and, later, the
+    // lines of the inverted matrix.
+    __m128 minor0, minor1, minor2, minor3;
+
+    // Variables which will contain the lines of the reference matrix and, later (after the transposition),
+    // the columns of the original matrix.
+    __m128 row0, row1, row2, row3;
+
+    // Temporary variables and the variable that will contain the matrix determinant.
+    __m128 det, tmp1;
+
+    // Matrix transposition
+    const float *src = matrix.data();
+    tmp1  = _mm_loadh_pi(_mm_castpd_ps(_mm_load_sd((double*)src)), (__m64*)(src+ 4));
+    row1  = _mm_loadh_pi(_mm_castpd_ps(_mm_load_sd((double*)(src+8))), (__m64*)(src+12));
+    row0  = _mm_shuffle_ps(tmp1, row1, 0x88);
+    row1  = _mm_shuffle_ps(row1, tmp1, 0xDD);
+    tmp1  = _mm_loadh_pi(_mm_castpd_ps(_mm_load_sd((double*)(src+ 2))), (__m64*)(src+ 6));
+    row3  = _mm_loadh_pi(_mm_castpd_ps(_mm_load_sd((double*)(src+10))), (__m64*)(src+14));
+    row2  = _mm_shuffle_ps(tmp1, row3, 0x88);
+    row3  = _mm_shuffle_ps(row3, tmp1, 0xDD);
+
+
+    // Cofactors calculation. Because in the process of cofactor computation some pairs in three-
+    // element products are repeated, it is not reasonable to load these pairs anew every time. The
+    // values in the registers with these pairs are formed using shuffle instruction. Cofactors are
+    // calculated row by row (4 elements are placed in 1 SP FP SIMD floating point register).
+
+    tmp1   = _mm_mul_ps(row2, row3);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0xB1);
+    minor0  = _mm_mul_ps(row1, tmp1);
+    minor1  = _mm_mul_ps(row0, tmp1);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0x4E);
+    minor0  = _mm_sub_ps(_mm_mul_ps(row1, tmp1), minor0);
+    minor1  = _mm_sub_ps(_mm_mul_ps(row0, tmp1), minor1);
+    minor1  = _mm_shuffle_ps(minor1, minor1, 0x4E);
+    //    -----------------------------------------------
+    tmp1   = _mm_mul_ps(row1, row2);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0xB1);
+    minor0  = _mm_add_ps(_mm_mul_ps(row3, tmp1), minor0);
+    minor3  = _mm_mul_ps(row0, tmp1);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0x4E);
+    minor0  = _mm_sub_ps(minor0, _mm_mul_ps(row3, tmp1));
+    minor3  = _mm_sub_ps(_mm_mul_ps(row0, tmp1), minor3);
+    minor3  = _mm_shuffle_ps(minor3, minor3, 0x4E);
+    //    -----------------------------------------------
+    tmp1   = _mm_mul_ps(_mm_shuffle_ps(row1, row1, 0x4E), row3);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0xB1);
+    row2   = _mm_shuffle_ps(row2, row2, 0x4E);
+    minor0  = _mm_add_ps(_mm_mul_ps(row2, tmp1), minor0);
+    minor2  = _mm_mul_ps(row0, tmp1);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0x4E);
+    minor0  = _mm_sub_ps(minor0, _mm_mul_ps(row2, tmp1));
+    minor2  = _mm_sub_ps(_mm_mul_ps(row0, tmp1), minor2);
+    minor2  = _mm_shuffle_ps(minor2, minor2, 0x4E);
+    //    -----------------------------------------------
+    tmp1   = _mm_mul_ps(row0, row1);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0xB1);
+    minor2 = _mm_add_ps(_mm_mul_ps(row3, tmp1), minor2);
+    minor3 = _mm_sub_ps(_mm_mul_ps(row2, tmp1), minor3);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0x4E);
+    minor2 = _mm_sub_ps(_mm_mul_ps(row3, tmp1), minor2);
+    minor3 = _mm_sub_ps(minor3, _mm_mul_ps(row2, tmp1));
+    //           -----------------------------------------------
+    tmp1   = _mm_mul_ps(row0, row3);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0xB1);
+    minor1 = _mm_sub_ps(minor1, _mm_mul_ps(row2, tmp1));
+    minor2 = _mm_add_ps(_mm_mul_ps(row1, tmp1), minor2);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0x4E);
+    minor1 = _mm_add_ps(_mm_mul_ps(row2, tmp1), minor1);
+    minor2 = _mm_sub_ps(minor2, _mm_mul_ps(row1, tmp1));
+    //           -----------------------------------------------
+    tmp1   = _mm_mul_ps(row0, row2);
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0xB1);
+    minor1 = _mm_add_ps(_mm_mul_ps(row3, tmp1), minor1);
+    minor3 = _mm_sub_ps(minor3, _mm_mul_ps(row1, tmp1));
+    tmp1   = _mm_shuffle_ps(tmp1, tmp1, 0x4E);
+    minor1 = _mm_sub_ps(minor1, _mm_mul_ps(row3, tmp1));
+    minor3 = _mm_add_ps(_mm_mul_ps(row1, tmp1), minor3);
+
+    // Evaluation of determinant and its reciprocal value. In the original Intel document,
+    // 1/det was evaluated using a fast rcpps command with subsequent approximation using
+    // the Newton-Raphson algorithm. Here, we go for a IEEE-compliant division instead,
+    // so as to not compromise precision at all.
+    det    = _mm_mul_ps(row0, minor0);
+    det    = _mm_add_ps(_mm_shuffle_ps(det, det, 0x4E), det);
+    det    = _mm_add_ss(_mm_shuffle_ps(det, det, 0xB1), det);
+//     tmp1= _mm_rcp_ss(det);
+//     det= _mm_sub_ss(_mm_add_ss(tmp1, tmp1), _mm_mul_ss(det, _mm_mul_ss(tmp1, tmp1)));
+    det    = _mm_div_ss(_mm_set_ss(1.0f), det); // <--- yay, one original line not copied from Intel
+    det    = _mm_shuffle_ps(det, det, 0x00);
+    // warning, Intel's variable naming is very confusing: now 'det' is 1/det !
+
+    // Multiplication of cofactors by 1/det. Storing the inverse matrix to the address in pointer src.
+    minor0 = _mm_mul_ps(det, minor0);
+    float *dst = result.data();
+    _mm_storel_pi((__m64*)(dst), minor0);
+    _mm_storeh_pi((__m64*)(dst+2), minor0);
+    minor1 = _mm_mul_ps(det, minor1);
+    _mm_storel_pi((__m64*)(dst+4), minor1);
+    _mm_storeh_pi((__m64*)(dst+6), minor1);
+    minor2 = _mm_mul_ps(det, minor2);
+    _mm_storel_pi((__m64*)(dst+ 8), minor2);
+    _mm_storeh_pi((__m64*)(dst+10), minor2);
+    minor3 = _mm_mul_ps(det, minor3);
+    _mm_storel_pi((__m64*)(dst+12), minor3);
+    _mm_storeh_pi((__m64*)(dst+14), minor3);
   }
-  else
-  {
-    // rare case: the topleft 2x2 block is not invertible (but the matrix itself is assumed to be).
-    // since this is a rare case, we don't need to optimize it. We just want to handle it with little
-    // additional code.
-    MatrixType m(matrix);
-    m.row(1).swap(m.row(2));
-    if(ei_compute_inverse_in_size4_case_helper(m, result))
-    {
-      // good, the topleft 2x2 block of m is invertible. Since m is different from matrix in that two
-      // rows were permuted, the actual inverse of matrix is derived from the inverse of m by permuting
-      // the corresponding columns.
-      result->col(1).swap(result->col(2));
-    }
-    else
-    {
-      // last possible case. Since matrix is assumed to be invertible, this last case has to work.
-      m.row(1).swap(m.row(2));
-      m.row(1).swap(m.row(3));
-      ei_compute_inverse_in_size4_case_helper(m, result);
-      result->col(1).swap(result->col(3));
-    }
-  }
-}
+};
+#endif
 
 /***********************************************
 *** Part 2 : selector and MatrixBase methods ***
@@ -198,7 +272,7 @@ struct ei_compute_inverse<MatrixType, 4>
 {
   static inline void run(const MatrixType& matrix, MatrixType* result)
   {
-    ei_compute_inverse_in_size4_case(matrix, result);
+    ei_compute_inverse_in_size4_case<MatrixType>::run(matrix, *result);
   }
 };
 

Eigen/src/LU/LU.h

@@ -42,17 +42,18 @@
   * This decomposition provides the generic approach to solving systems of linear equations, computing
   * the rank, invertibility, inverse, kernel, and determinant.
   *
+  * This LU decomposition is very stable and well tested with large matrices. Even exact rank computation
+  * works at sizes larger than 1000x1000. However there are use cases where the SVD decomposition is inherently
+  * more stable when dealing with numerically damaged input. For example, computing the kernel is more stable with
+  * SVD because the SVD can determine which singular values are negligible while LU has to work at the level of matrix
+  * coefficients that are less meaningful in this respect.
+  *
   * The data of the LU decomposition can be directly accessed through the methods matrixLU(),
-  * permutationP(), permutationQ(). Convenience methods matrixL(), matrixU() are also provided.
+  * permutationP(), permutationQ().
   *
-  * As an exemple, here is how the original matrix can be retrieved, in the square case:
-  * \include class_LU_1.cpp
-  * Output: \verbinclude class_LU_1.out
-  *
-  * When the matrix is not square, matrixL() is no longer very useful: if one needs it, one has
-  * to construct the L matrix by hand, as shown in this example:
-  * \include class_LU_2.cpp
-  * Output: \verbinclude class_LU_2.out
+  * As an exemple, here is how the original matrix can be retrieved:
+  * \include class_LU.cpp
+  * Output: \verbinclude class_LU.out
   *
   * \sa MatrixBase::lu(), MatrixBase::determinant(), MatrixBase::inverse(), MatrixBase::computeInverse()
   */
@@ -108,26 +109,6 @@ template<typename MatrixType> class LU
       return m_lu;
     }
 
-    /** \returns an expression of the unit-lower-triangular part of the LU matrix. In the square case,
-      *          this is the L matrix. In the non-square, actually obtaining the L matrix takes some
-      *          more care, see the documentation of class LU.
-      *
-      * \sa matrixLU(), matrixU()
-      */
-    inline const Part<MatrixType, UnitLowerTriangular> matrixL() const
-    {
-      return m_lu;
-    }
-
-    /** \returns an expression of the U matrix, i.e. the upper-triangular part of the LU matrix.
-      *
-      * \sa matrixLU(), matrixL()
-      */
-    inline const Part<MatrixType, UpperTriangular> matrixU() const
-    {
-      return m_lu;
-    }
-
     /** \returns a vector of integers, whose size is the number of rows of the matrix being decomposed,
       * representing the P permutation i.e. the permutation of the rows. For its precise meaning,
       * see the examples given in the documentation of class LU.
@@ -342,6 +323,7 @@ template<typename MatrixType> class LU
     IntRowVectorType m_q;
     int m_det_pq;
     int m_rank;
+    RealScalar m_precision;
 };
 
 template<typename MatrixType>
@@ -354,22 +336,41 @@ LU<MatrixType>::LU(const MatrixType& matrix)
   const int size = matrix.diagonal().size();
   const int rows = matrix.rows();
   const int cols = matrix.cols();
+  
+  // this formula comes from experimenting (see "LU precision tuning" thread on the list)
+  // and turns out to be identical to Higham's formula used already in LDLt.
+  m_precision = machine_epsilon<Scalar>() * size;
 
   IntColVectorType rows_transpositions(matrix.rows());
   IntRowVectorType cols_transpositions(matrix.cols());
   int number_of_transpositions = 0;
 
   RealScalar biggest = RealScalar(0);
+  m_rank = size;
   for(int k = 0; k < size; ++k)
   {
     int row_of_biggest_in_corner, col_of_biggest_in_corner;
     RealScalar biggest_in_corner;
 
     biggest_in_corner = m_lu.corner(Eigen::BottomRight, rows-k, cols-k)
-                  .cwise().abs()
-                  .maxCoeff(&row_of_biggest_in_corner, &col_of_biggest_in_corner);
+                        .cwise().abs()
+                        .maxCoeff(&row_of_biggest_in_corner, &col_of_biggest_in_corner);
     row_of_biggest_in_corner += k;
     col_of_biggest_in_corner += k;
+    if(k==0) biggest = biggest_in_corner;
+
+    // if the corner is negligible, then we have less than full rank, and we can finish early
+    if(ei_isMuchSmallerThan(biggest_in_corner, biggest, m_precision))
+    {
+      m_rank = k;
+      for(int i = k; i < size; i++)
+      {
+        rows_transpositions.coeffRef(i) = i;
+        cols_transpositions.coeffRef(i) = i;
+      }
+      break;
+    }
+
     rows_transpositions.coeffRef(k) = row_of_biggest_in_corner;
     cols_transpositions.coeffRef(k) = col_of_biggest_in_corner;
     if(k != row_of_biggest_in_corner) {
@@ -380,12 +381,8 @@ LU<MatrixType>::LU(const MatrixType& matrix)
       m_lu.col(k).swap(m_lu.col(col_of_biggest_in_corner));
       ++number_of_transpositions;
     }
-
-    if(k==0) biggest = biggest_in_corner;
-    const Scalar lu_k_k = m_lu.coeff(k,k);
-    if(ei_isMuchSmallerThan(lu_k_k, biggest)) continue;
     if(k<rows-1)
-      m_lu.col(k).end(rows-k-1) /= lu_k_k;
+      m_lu.col(k).end(rows-k-1) /= m_lu.coeff(k,k);
     if(k<size-1)
       for(int col = k + 1; col < cols; ++col)
         m_lu.col(col).end(rows-k-1) -= m_lu.col(k).end(rows-k-1) * m_lu.coeff(k,col);
@@ -400,10 +397,6 @@ LU<MatrixType>::LU(const MatrixType& matrix)
     std::swap(m_q.coeffRef(k), m_q.coeffRef(cols_transpositions.coeff(k)));
 
   m_det_pq = (number_of_transpositions%2) ? -1 : 1;
-
-  for(m_rank = 0; m_rank < size; ++m_rank)
-    if(ei_isMuchSmallerThan(m_lu.diagonal().coeff(m_rank), m_lu.diagonal().coeff(0)))
-      break;
 }
 
 template<typename MatrixType>
@@ -444,8 +437,7 @@ void LU<MatrixType>::computeKernel(KernelMatrixType *result) const
       .template marked<UpperTriangular>()
       .solveTriangularInPlace(y);
 
-  for(int i = 0; i < m_rank; ++i)
-    result->row(m_q.coeff(i)) = y.row(i);
+  for(int i = 0; i < m_rank; ++i) result->row(m_q.coeff(i)) = y.row(i);
   for(int i = m_rank; i < cols; ++i) result->row(m_q.coeff(i)).setZero();
   for(int k = 0; k < dimker; ++k) result->coeffRef(m_q.coeff(m_rank+k), k) = Scalar(1);
 }
@@ -489,13 +481,13 @@ bool LU<MatrixType>::solve(
    * So we proceed as follows:
    * Step 1: compute c = Pb.
    * Step 2: replace c by the solution x to Lx = c. Exists because L is invertible.
-   * Step 3: compute d such that Ud = c. Check if such d really exists.
-   * Step 4: result = Qd;
+   * Step 3: replace c by the solution x to Ux = c. Check if a solution really exists.
+   * Step 4: result = Qc;
    */
 
-  const int rows = m_lu.rows();
+  const int rows = m_lu.rows(), cols = m_lu.cols();
   ei_assert(b.rows() == rows);
-  const int smalldim = std::min(rows, m_lu.cols());
+  const int smalldim = std::min(rows, cols);
 
   typename OtherDerived::PlainMatrixType c(b.rows(), b.cols());
 
@@ -503,36 +495,32 @@ bool LU<MatrixType>::solve(
   for(int i = 0; i < rows; ++i) c.row(m_p.coeff(i)) = b.row(i);
 
   // Step 2
-  Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime,
-         MatrixType::Options,
-         MatrixType::MaxRowsAtCompileTime,
-         MatrixType::MaxRowsAtCompileTime> l(rows, rows);
-  l.setZero();
-  l.corner(Eigen::TopLeft,rows,smalldim)
-    = m_lu.corner(Eigen::TopLeft,rows,smalldim);
-  l.template marked<UnitLowerTriangular>().solveTriangularInPlace(c);
+  m_lu.corner(Eigen::TopLeft,smalldim,smalldim).template marked<UnitLowerTriangular>()
+    .solveTriangularInPlace(
+      c.corner(Eigen::TopLeft, smalldim, c.cols()));
+  if(rows>cols)
+  {
+    c.corner(Eigen::BottomLeft, rows-cols, c.cols())
+      -= m_lu.corner(Eigen::BottomLeft, rows-cols, cols) * c.corner(Eigen::TopLeft, cols, c.cols());
+  }
 
   // Step 3
   if(!isSurjective())
   {
     // is c is in the image of U ?
-    RealScalar biggest_in_c = c.corner(TopLeft, m_rank, c.cols()).cwise().abs().maxCoeff();
+    RealScalar biggest_in_c = m_rank>0 ? c.corner(TopLeft, m_rank, c.cols()).cwise().abs().maxCoeff() : 0;
     for(int col = 0; col < c.cols(); ++col)
       for(int row = m_rank; row < c.rows(); ++row)
-        if(!ei_isMuchSmallerThan(c.coeff(row,col), biggest_in_c))
+        if(!ei_isMuchSmallerThan(c.coeff(row,col), biggest_in_c, m_precision))
           return false;
   }
-  Matrix<Scalar, Dynamic, OtherDerived::ColsAtCompileTime,
-         MatrixType::Options,
-         MatrixType::MaxRowsAtCompileTime, OtherDerived::MaxColsAtCompileTime>
-    d(c.corner(TopLeft, m_rank, c.cols()));
   m_lu.corner(TopLeft, m_rank, m_rank)
       .template marked<UpperTriangular>()
-      .solveTriangularInPlace(d);
+      .solveTriangularInPlace(c.corner(TopLeft, m_rank, c.cols()));
 
   // Step 4
   result->resize(m_lu.cols(), b.cols());
-  for(int i = 0; i < m_rank; ++i) result->row(m_q.coeff(i)) = d.row(i);
+  for(int i = 0; i < m_rank; ++i) result->row(m_q.coeff(i)) = c.row(i);
   for(int i = m_rank; i < m_lu.cols(); ++i) result->row(m_q.coeff(i)).setZero();
   return true;
 }

Eigen/src/LeastSquares/CMakeLists.txt

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

Eigen/src/LeastSquares/LeastSquares.h

@@ -1,7 +1,7 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra. Eigen itself is part of the KDE project.
 //
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -22,12 +22,12 @@
 // License and a copy of the GNU General Public License along with
 // Eigen. If not, see <http://www.gnu.org/licenses/>.
 
-#ifndef EIGEN_REGRESSION_H
-#define EIGEN_REGRESSION_H
+#ifndef EIGEN_LEASTSQUARES_H
+#define EIGEN_LEASTSQUARES_H
 
-/** \ingroup Regression_Module
+/** \ingroup LeastSquares_Module
   *
-  * \regression_module
+  * \leastsquares_module
   *
   * For a set of points, this function tries to express
   * one of the coords as a linear (affine) function of the other coords.
@@ -57,7 +57,7 @@
     Vector3d coeffs; // will store the coefficients a, b, c
     linearRegression(
       5,
-      points,
+      &points,
       &coeffs,
       1 // the coord to express as a function of
         // the other ones. 0 means x, 1 means y, 2 means z.
@@ -80,11 +80,11 @@
                   This vector must be of the same type and size as the
                   data points. The meaning of its coords is as follows.
                   For brevity, let \f$n=Size\f$,
-                  \f$r_i=retCoefficients[i]\f$,
+                  \f$r_i=result[i]\f$,
                   and \f$f=funcOfOthers\f$. Denote by
                   \f$x_0,\ldots,x_{n-1}\f$
                   the n coordinates in the n-dimensional space.
-                  Then the result equation is:
+                  Then the resulting equation is:
                   \f[ x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1}
                    + r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n. \f]
   * @param funcOfOthers Determines which coord to express as a function of the
@@ -101,36 +101,20 @@ void linearRegression(int numPoints,
                       int funcOfOthers )
 {
   typedef typename VectorType::Scalar Scalar;
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType)
-  ei_assert(numPoints >= 1);
-  int size = points[0]->size();
-  ei_assert(funcOfOthers >= 0 && funcOfOthers < size);
+  typedef Hyperplane<Scalar, VectorType::SizeAtCompileTime> HyperplaneType;
+  const int size = points[0]->size();
   result->resize(size);
-
-  Matrix<Scalar, Dynamic, VectorType::SizeAtCompileTime,
-         Dynamic, VectorType::MaxSizeAtCompileTime, RowMajorBit>
-    m(numPoints, size);
-  if(funcOfOthers>0)
-    for(int i = 0; i < numPoints; ++i)
-      m.row(i).start(funcOfOthers) = points[i]->start(funcOfOthers);
-  if(funcOfOthers<size-1)
-    for(int i = 0; i < numPoints; ++i)
-      m.row(i).block(funcOfOthers, size-funcOfOthers-1)
-        = points[i]->end(size-funcOfOthers-1);
-  for(int i = 0; i < numPoints; ++i)
-    m.row(i).coeffRef(size-1) = Scalar(1);
-
-  VectorType v(size);
-  v.setZero();
-  for(int i = 0; i < numPoints; ++i)
-    v += m.row(i).adjoint() * points[i]->coeff(funcOfOthers);
-
-  ei_assert((m.adjoint()*m).lu().solve(v, result));
+  HyperplaneType h(size);
+  fitHyperplane(numPoints, points, &h);
+  for(int i = 0; i < funcOfOthers; i++)
+    result->coeffRef(i) = - h.coeffs()[i] / h.coeffs()[funcOfOthers];
+  for(int i = funcOfOthers; i < size; i++)
+    result->coeffRef(i) = - h.coeffs()[i+1] / h.coeffs()[funcOfOthers];
 }
 
-/** \ingroup Regression_Module
+/** \ingroup LeastSquares_Module
   *
-  * \regression_module
+  * \leastsquares_module
   *
   * This function is quite similar to linearRegression(), so we refer to the
   * documentation of this function and only list here the differences.
@@ -195,4 +179,4 @@ void fitHyperplane(int numPoints,
 }
 
 
-#endif // EIGEN_REGRESSION_H
+#endif // EIGEN_LEASTSQUARES_H

Eigen/src/QR/EigenSolver.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>
 //
@@ -53,9 +53,18 @@ template<typename _MatrixType> class EigenSolver
     typedef Matrix<RealScalar, MatrixType::ColsAtCompileTime, 1> RealVectorType;
     typedef Matrix<RealScalar, Dynamic, 1> RealVectorTypeX;
 
+    /** 
+    * \brief Default Constructor.
+    *
+    * The default constructor is useful in cases in which the user intends to
+    * perform decompositions via EigenSolver::compute(const MatrixType&).
+    */
+    EigenSolver() : m_eivec(), m_eivalues(), m_isInitialized(false) {}
+
     EigenSolver(const MatrixType& matrix)
       : m_eivec(matrix.rows(), matrix.cols()),
-        m_eivalues(matrix.cols())
+        m_eivalues(matrix.cols()),
+        m_isInitialized(false)
     {
       compute(matrix);
     }
@@ -94,12 +103,20 @@ template<typename _MatrixType> class EigenSolver
       *
       * \sa pseudoEigenvalueMatrix()
       */
-    const MatrixType& pseudoEigenvectors() const { return m_eivec; }
+    const MatrixType& pseudoEigenvectors() const 
+    { 
+      ei_assert(m_isInitialized && "EigenSolver is not initialized.");
+      return m_eivec; 
+    }
 
     MatrixType pseudoEigenvalueMatrix() const;
 
     /** \returns the eigenvalues as a column vector */
-    EigenvalueType eigenvalues() const { return m_eivalues; }
+    EigenvalueType eigenvalues() const 
+    { 
+      ei_assert(m_isInitialized && "EigenSolver is not initialized.");
+      return m_eivalues; 
+    }
 
     void compute(const MatrixType& matrix);
 
@@ -111,6 +128,7 @@ template<typename _MatrixType> class EigenSolver
   protected:
     MatrixType m_eivec;
     EigenvalueType m_eivalues;
+    bool m_isInitialized;
 };
 
 /** \returns the real block diagonal matrix D of the eigenvalues.
@@ -120,6 +138,7 @@ template<typename _MatrixType> class EigenSolver
 template<typename MatrixType>
 MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
 {
+  ei_assert(m_isInitialized && "EigenSolver is not initialized.");
   int n = m_eivec.cols();
   MatrixType matD = MatrixType::Zero(n,n);
   for (int i=0; i<n; ++i)
@@ -143,6 +162,7 @@ MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
 template<typename MatrixType>
 typename EigenSolver<MatrixType>::EigenvectorType EigenSolver<MatrixType>::eigenvectors(void) const
 {
+  ei_assert(m_isInitialized && "EigenSolver is not initialized.");
   int n = m_eivec.cols();
   EigenvectorType matV(n,n);
   for (int j=0; j<n; ++j)
@@ -183,6 +203,8 @@ void EigenSolver<MatrixType>::compute(const MatrixType& matrix)
 
   // Reduce Hessenberg to real Schur form.
   hqr2(matH);
+
+  m_isInitialized = true;
 }
 
 // Nonsymmetric reduction to Hessenberg form.
@@ -282,7 +304,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
   int n = nn-1;
   int low = 0;
   int high = nn-1;
-  Scalar eps = pow(2.0,-52.0);
+  Scalar eps = ei_pow(Scalar(2),ei_is_same_type<Scalar,float>::ret ? Scalar(-23) : Scalar(-52));
   Scalar exshift = 0.0;
   Scalar p=0,q=0,r=0,s=0,z=0,t,w,x,y;
 
@@ -328,7 +350,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
     else if (l == n-1) // Two roots found
     {
       w = matH.coeff(n,n-1) * matH.coeff(n-1,n);
-      p = (matH.coeff(n-1,n-1) - matH.coeff(n,n)) / 2.0;
+      p = (matH.coeff(n-1,n-1) - matH.coeff(n,n)) * Scalar(0.5);
       q = p * p + w;
       z = ei_sqrt(ei_abs(q));
       matH.coeffRef(n,n) = matH.coeff(n,n) + exshift;
@@ -405,25 +427,25 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
         for (int i = low; i <= n; ++i)
           matH.coeffRef(i,i) -= x;
         s = ei_abs(matH.coeff(n,n-1)) + ei_abs(matH.coeff(n-1,n-2));
-        x = y = 0.75 * s;
-        w = -0.4375 * s * s;
+        x = y = Scalar(0.75) * s;
+        w = Scalar(-0.4375) * s * s;
       }
 
       // MATLAB's new ad hoc shift
       if (iter == 30)
       {
-        s = (y - x) / 2.0;
+        s = Scalar((y - x) / 2.0);
         s = s * s + w;
         if (s > 0)
         {
           s = ei_sqrt(s);
           if (y < x)
             s = -s;
-          s = x - w / ((y - x) / 2.0 + s);
+          s = Scalar(x - w / ((y - x) / 2.0 + s));
           for (int i = low; i <= n; ++i)
             matH.coeffRef(i,i) -= s;
           exshift += s;
-          x = y = w = 0.964;
+          x = y = w = Scalar(0.964);
         }
       }
 
@@ -469,7 +491,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
         if (k != m) {
           p = matH.coeff(k,k-1);
           q = matH.coeff(k+1,k-1);
-          r = (notlast ? matH.coeff(k+2,k-1) : 0.0);
+          r = notlast ? matH.coeff(k+2,k-1) : Scalar(0);
           x = ei_abs(p) + ei_abs(q) + ei_abs(r);
           if (x != 0.0)
           {
@@ -647,7 +669,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
             x = matH.coeff(i,i+1);
             y = matH.coeff(i+1,i);
             vr = (m_eivalues.coeff(i).real() - p) * (m_eivalues.coeff(i).real() - p) + m_eivalues.coeff(i).imag() * m_eivalues.coeff(i).imag() - q * q;
-            vi = (m_eivalues.coeff(i).real() - p) * 2.0 * q;
+            vi = (m_eivalues.coeff(i).real() - p) * Scalar(2) * q;
             if ((vr == 0.0) && (vi == 0.0))
               vr = eps * norm * (ei_abs(w) + ei_abs(q) + ei_abs(x) + ei_abs(y) + ei_abs(z));
 

Eigen/src/QR/QR.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>
 //
@@ -49,43 +49,163 @@ template<typename MatrixType> class QR
     typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> MatrixTypeR;
     typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, 1> VectorType;
 
+    /** 
+    * \brief Default Constructor.
+    *
+    * The default constructor is useful in cases in which the user intends to
+    * perform decompositions via QR::compute(const MatrixType&).
+    */
+    QR() : m_qr(), m_hCoeffs(), m_isInitialized(false) {}
+
     QR(const MatrixType& matrix)
       : m_qr(matrix.rows(), matrix.cols()),
-        m_hCoeffs(matrix.cols())
+        m_hCoeffs(matrix.cols()),
+        m_isInitialized(false)
     {
-      _compute(matrix);
+      compute(matrix);
+    }
+    
+    /** \deprecated use isInjective()
+      * \returns whether or not the matrix is of full rank
+      *
+      * \note Since the rank is computed only once, i.e. the first time it is needed, this
+      *       method almost does not perform any further computation.
+      */
+    EIGEN_DEPRECATED bool isFullRank() const 
+    { 
+      ei_assert(m_isInitialized && "QR is not initialized.");
+      return rank() == m_qr.cols(); 
+    }
+    
+    /** \returns the rank of the matrix of which *this is the QR decomposition.
+      *
+      * \note Since the rank is computed only once, i.e. the first time it is needed, this
+      *       method almost does not perform any further computation.
+      */
+    int rank() const;
+    
+    /** \returns the dimension of the kernel of the matrix of which *this is the QR decomposition.
+      *
+      * \note Since the rank is computed only once, i.e. the first time it is needed, this
+      *       method almost does not perform any further computation.
+      */
+    inline int dimensionOfKernel() const
+    {
+      ei_assert(m_isInitialized && "QR is not initialized.");
+      return m_qr.cols() - rank();
+    }
+    
+    /** \returns true if the matrix of which *this is the QR decomposition represents an injective
+      *          linear map, i.e. has trivial kernel; false otherwise.
+      *
+      * \note Since the rank is computed only once, i.e. the first time it is needed, this
+      *       method almost does not perform any further computation.
+      */
+    inline bool isInjective() const
+    {
+      ei_assert(m_isInitialized && "QR is not initialized.");
+      return rank() == m_qr.cols();
+    }
+    
+    /** \returns true if the matrix of which *this is the QR decomposition represents a surjective
+      *          linear map; false otherwise.
+      *
+      * \note Since the rank is computed only once, i.e. the first time it is needed, this
+      *       method almost does not perform any further computation.
+      */
+    inline bool isSurjective() const
+    {
+      ei_assert(m_isInitialized && "QR is not initialized.");
+      return rank() == m_qr.rows();
     }
 
-    /** \returns whether or not the matrix is of full rank */
-    bool isFullRank() const { return ei_isMuchSmallerThan(m_hCoeffs.cwise().abs().minCoeff(), Scalar(1)); }
-
+    /** \returns true if the matrix of which *this is the QR decomposition is invertible.
+      *
+      * \note Since the rank is computed only once, i.e. the first time it is needed, this
+      *       method almost does not perform any further computation.
+      */
+    inline bool isInvertible() const
+    {
+      ei_assert(m_isInitialized && "QR is not initialized.");
+      return isInjective() && isSurjective();
+    }
+    
     /** \returns a read-only expression of the matrix R of the actual the QR decomposition */
     const Part<NestByValue<MatrixRBlockType>, UpperTriangular>
     matrixR(void) const
     {
+      ei_assert(m_isInitialized && "QR is not initialized.");
       int cols = m_qr.cols();
       return MatrixRBlockType(m_qr, 0, 0, cols, cols).nestByValue().template part<UpperTriangular>();
     }
 
+    /** This method finds a solution x to the equation Ax=b, where A is the matrix of which
+      * *this is the QR decomposition, if any exists.
+      *
+      * \param b the right-hand-side of the equation to solve.
+      *
+      * \param result a pointer to the vector/matrix in which to store the solution, if any exists.
+      *          Resized if necessary, so that result->rows()==A.cols() and result->cols()==b.cols().
+      *          If no solution exists, *result is left with undefined coefficients.
+      *
+      * \returns true if any solution exists, false if no solution exists.
+      *
+      * \note If there exist more than one solution, this method will arbitrarily choose one.
+      *       If you need a complete analysis of the space of solutions, take the one solution obtained
+      *       by this method and add to it elements of the kernel, as determined by kernel().
+      *
+      * \note The case where b is a matrix is not yet implemented. Also, this
+      *       code is space inefficient.
+      *
+      * Example: \include QR_solve.cpp
+      * Output: \verbinclude QR_solve.out
+      *
+      * \sa MatrixBase::solveTriangular(), kernel(), computeKernel(), inverse(), computeInverse()
+      */
+    template<typename OtherDerived, typename ResultType>
+    bool solve(const MatrixBase<OtherDerived>& b, ResultType *result) const;
+
     MatrixType matrixQ(void) const;
 
-  private:
-
-    void _compute(const MatrixType& matrix);
+    void compute(const MatrixType& matrix);
 
   protected:
     MatrixType m_qr;
     VectorType m_hCoeffs;
+    mutable int m_rank;
+    mutable bool m_rankIsUptodate;
+    bool m_isInitialized;
 };
 
+/** \returns the rank of the matrix of which *this is the QR decomposition. */
+template<typename MatrixType>
+int QR<MatrixType>::rank() const
+{
+  ei_assert(m_isInitialized && "QR is not initialized.");
+  if (!m_rankIsUptodate)
+  {
+    RealScalar maxCoeff = m_qr.diagonal().cwise().abs().maxCoeff();
+    int n = m_qr.cols();
+    m_rank = 0;
+    while(m_rank<n && !ei_isMuchSmallerThan(m_qr.diagonal().coeff(m_rank), maxCoeff))
+      ++m_rank;
+    m_rankIsUptodate = true;
+  }
+  return m_rank;
+}
+
 #ifndef EIGEN_HIDE_HEAVY_CODE
 
 template<typename MatrixType>
-void QR<MatrixType>::_compute(const MatrixType& matrix)
-{
+void QR<MatrixType>::compute(const MatrixType& matrix)
+{ 
+  m_rankIsUptodate = false;
   m_qr = matrix;
+  m_hCoeffs.resize(matrix.cols());
+
   int rows = matrix.rows();
   int cols = matrix.cols();
+  RealScalar eps2 = precision<RealScalar>()*precision<RealScalar>();
 
   for (int k = 0; k < cols; ++k)
   {
@@ -110,7 +230,8 @@ void QR<MatrixType>::_compute(const MatrixType& matrix)
         m_hCoeffs.coeffRef(k) = 0;
       }
     }
-    else if ( (!ei_isMuchSmallerThan(beta=m_qr.col(k).end(remainingSize-1).squaredNorm(),static_cast<Scalar>(1))) || ei_imag(v0)==0 )
+    else if ((beta=m_qr.col(k).end(remainingSize-1).squaredNorm())>eps2)
+    // FIXME what about ei_imag(v0) ??
     {
       // form k-th Householder vector
       beta = ei_sqrt(ei_abs2(v0)+beta);
@@ -136,12 +257,46 @@ void QR<MatrixType>::_compute(const MatrixType& matrix)
       m_hCoeffs.coeffRef(k) = 0;
     }
   }
+  m_isInitialized = true;
+}
+
+template<typename MatrixType>
+template<typename OtherDerived, typename ResultType>
+bool QR<MatrixType>::solve(
+  const MatrixBase<OtherDerived>& b,
+  ResultType *result
+) const
+{
+  ei_assert(m_isInitialized && "QR is not initialized.");
+  const int rows = m_qr.rows();
+  ei_assert(b.rows() == rows);
+  result->resize(rows, b.cols());
+  
+  // TODO(keir): There is almost certainly a faster way to multiply by
+  // Q^T without explicitly forming matrixQ(). Investigate.
+  *result = matrixQ().transpose()*b;
+  
+  if(!isSurjective())
+  {
+    // is result is in the image of R ?
+    RealScalar biggest_in_res = result->corner(TopLeft, m_rank, result->cols()).cwise().abs().maxCoeff();
+    for(int col = 0; col < result->cols(); ++col)
+      for(int row = m_rank; row < result->rows(); ++row)
+        if(!ei_isMuchSmallerThan(result->coeff(row,col), biggest_in_res))
+          return false;
+  }
+  m_qr.corner(TopLeft, m_rank, m_rank)
+      .template marked<UpperTriangular>()
+      .solveTriangularInPlace(result->corner(TopLeft, m_rank, result->cols()));
+
+  return true;
 }
 
 /** \returns the matrix Q */
 template<typename MatrixType>
-MatrixType QR<MatrixType>::matrixQ(void) const
+MatrixType QR<MatrixType>::matrixQ() const
 {
+  ei_assert(m_isInitialized && "QR is not initialized.");
   // compute the product Q_0 Q_1 ... Q_n-1,
   // where Q_k is the k-th Householder transformation I - h_k v_k v_k'
   // and v_k is the k-th Householder vector [1,m_qr(k+1,k), m_qr(k+2,k), ...]

Eigen/src/QR/SelfAdjointEigenSolver.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>
 //
@@ -52,8 +52,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
     typedef Tridiagonalization<MatrixType> TridiagonalizationType;
 
     SelfAdjointEigenSolver()
-        : m_eivec(Size, Size),
-          m_eivalues(Size)
+        : m_eivec(int(Size), int(Size)),
+          m_eivalues(int(Size))
     {
       ei_assert(Size!=Dynamic);
     }
@@ -189,6 +189,14 @@ void SelfAdjointEigenSolver<MatrixType>::compute(const MatrixType& matrix, bool
   assert(matrix.cols() == matrix.rows());
   int n = matrix.cols();
   m_eivalues.resize(n,1);
+
+  if(n==1)
+  {
+    m_eivalues.coeffRef(0,0) = ei_real(matrix.coeff(0,0));
+    m_eivec.setOnes();
+    return;
+  }
+
   m_eivec = matrix;
 
   // FIXME, should tridiag be a local variable of this function or an attribute of SelfAdjointEigenSolver ?
@@ -334,7 +342,7 @@ MatrixBase<Derived>::operatorNorm() const
 template<typename RealScalar, typename Scalar>
 static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, int start, int end, Scalar* matrixQ, int n)
 {
-  RealScalar td = (diag[end-1] - diag[end])*0.5;
+  RealScalar td = (diag[end-1] - diag[end])*RealScalar(0.5);
   RealScalar e2 = ei_abs2(subdiag[end-1]);
   RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * ei_sqrt(td*td + e2));
   RealScalar x = diag[start] - mu;
@@ -357,10 +365,12 @@ static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, int st
       subdiag[k - 1] = c * subdiag[k-1] - s * z;
 
     x = subdiag[k];
-    z = -s * subdiag[k+1];
 
     if (k < end - 1)
+    {
+      z = -s * subdiag[k+1];
       subdiag[k + 1] = c * subdiag[k+1];
+    }
 
     // apply the givens rotation to the unit matrix Q = Q * G
     // G only modifies the two columns k and k+1

Eigen/src/QR/Tridiagonalization.h

@@ -201,6 +201,7 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType&
     // squared norm of the vector v skipping the first element
     RealScalar v1norm2 = matA.col(i).end(n-(i+2)).squaredNorm();
 
+    // FIXME comparing against 1
     if (ei_isMuchSmallerThan(v1norm2,static_cast<Scalar>(1)))
     {
       hCoeffs.coeffRef(i) = 0.;
@@ -331,7 +332,8 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType&
     if (ei_real(v0)>=0.)
       beta = -beta;
     matA.col(i).coeffRef(i+1) = beta;
-    hCoeffs.coeffRef(i) = (beta - v0) / beta;
+    if(ei_isMuchSmallerThan(beta, Scalar(1))) hCoeffs.coeffRef(i) = Scalar(0);
+    else hCoeffs.coeffRef(i) = (beta - v0) / beta;
   }
   else
   {

Eigen/src/Regression/CMakeLists.txt

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

Eigen/src/SVD/SVD.h

@@ -61,6 +61,8 @@ template<typename MatrixType> class SVD
 
   public:
 
+    SVD() {} // a user who relied on compiler-generated default compiler reported problems with MSVC in 2.0.7
+    
     SVD(const MatrixType& matrix)
       : m_matU(matrix.rows(), std::min(matrix.rows(), matrix.cols())),
         m_matV(matrix.cols(),matrix.cols()),
@@ -79,6 +81,15 @@ template<typename MatrixType> class SVD
     void compute(const MatrixType& matrix);
     SVD& sort();
 
+    template<typename UnitaryType, typename PositiveType>
+    void computeUnitaryPositive(UnitaryType *unitary, PositiveType *positive) const;
+    template<typename PositiveType, typename UnitaryType>
+    void computePositiveUnitary(PositiveType *positive, UnitaryType *unitary) const;
+    template<typename RotationType, typename ScalingType>
+    void computeRotationScaling(RotationType *unitary, ScalingType *positive) const;
+    template<typename ScalingType, typename RotationType>
+    void computeScalingRotation(ScalingType *positive, RotationType *unitary) const;
+
   protected:
     /** \internal */
     MatrixUType m_matU;
@@ -98,6 +109,8 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
   const int m = matrix.rows();
   const int n = matrix.cols();
   const int nu = std::min(m,n);
+  ei_assert(m>=n && "In Eigen 2.0, SVD only works for MxN matrices with M>=N. Sorry!");
+  ei_assert(m>1 && "In Eigen 2.0, SVD doesn't work on 1x1 matrices");
 
   m_matU.resize(m, nu);
   m_matU.setZero();
@@ -208,7 +221,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
           m_matU.col(j).end(m-k) += t * m_matU.col(k).end(m-k);
         }
         m_matU.col(k).end(m-k) = - m_matU.col(k).end(m-k);
-        m_matU(k,k) = 1.0 + m_matU(k,k);
+        m_matU(k,k) = Scalar(1) + m_matU(k,k);
         if (k-1>0)
           m_matU.col(k).start(k-1).setZero();
       }
@@ -242,7 +255,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
   // Main iteration loop for the singular values.
   int pp = p-1;
   int iter = 0;
-  Scalar eps(pow(2.0,-52.0));
+  Scalar eps = ei_pow(Scalar(2),ei_is_same_type<Scalar,float>::ret ? Scalar(-23) : Scalar(-52));
   while (p > 0)
   {
     int k=0;
@@ -260,7 +273,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
     //              s(k), ..., s(p) are not negligible (qr step).
     // kase = 4     if e(p-1) is negligible (convergence).
 
-    for (k = p-2; k >= -1; k--)
+    for (k = p-2; k >= -1; --k)
     {
       if (k == -1)
           break;
@@ -277,11 +290,11 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
     else
     {
       int ks;
-      for (ks = p-1; ks >= k; ks--)
+      for (ks = p-1; ks >= k; --ks)
       {
         if (ks == k)
           break;
-        Scalar t( (ks != p ? ei_abs(e[ks]) : 0.) + (ks != k+1 ? ei_abs(e[ks-1]) : 0.));
+        Scalar t = (ks != p ? ei_abs(e[ks]) : Scalar(0)) + (ks != k+1 ? ei_abs(e[ks-1]) : Scalar(0));
         if (ei_abs(m_sigma[ks]) <= eps*t)
         {
           m_sigma[ks] = 0.0;
@@ -313,9 +326,9 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
       {
         Scalar f(e[p-2]);
         e[p-2] = 0.0;
-        for (j = p-2; j >= k; j--)
+        for (j = p-2; j >= k; --j)
         {
-          Scalar t(hypot(m_sigma[j],f));
+          Scalar t(ei_hypot(m_sigma[j],f));
           Scalar cs(m_sigma[j]/t);
           Scalar sn(f/t);
           m_sigma[j] = t;
@@ -344,7 +357,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
         e[k-1] = 0.0;
         for (j = k; j < p; ++j)
         {
-          Scalar t(hypot(m_sigma[j],f));
+          Scalar t(ei_hypot(m_sigma[j],f));
           Scalar cs( m_sigma[j]/t);
           Scalar sn(f/t);
           m_sigma[j] = t;
@@ -375,7 +388,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
         Scalar epm1 = e[p-2]/scale;
         Scalar sk = m_sigma[k]/scale;
         Scalar ek = e[k]/scale;
-        Scalar b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/2.0;
+        Scalar b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/Scalar(2);
         Scalar c = (sp*epm1)*(sp*epm1);
         Scalar shift = 0.0;
         if ((b != 0.0) || (c != 0.0))
@@ -392,7 +405,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
 
         for (j = k; j < p-1; ++j)
         {
-          Scalar t = hypot(f,g);
+          Scalar t = ei_hypot(f,g);
           Scalar cs = f/t;
           Scalar sn = g/t;
           if (j != k)
@@ -410,7 +423,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
               m_matV(i,j) = t;
             }
           }
-          t = hypot(f,g);
+          t = ei_hypot(f,g);
           cs = f/t;
           sn = g/t;
           m_sigma[j] = t;
@@ -439,7 +452,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
         // Make the singular values positive.
         if (m_sigma[k] <= 0.0)
         {
-          m_sigma[k] = (m_sigma[k] < 0.0 ? -m_sigma[k] : 0.0);
+          m_sigma[k] = m_sigma[k] < Scalar(0) ? -m_sigma[k] : Scalar(0);
           if (wantv)
             m_matV.col(k).start(pp+1) = -m_matV.col(k).start(pp+1);
         }
@@ -534,6 +547,95 @@ bool SVD<MatrixType>::solve(const MatrixBase<OtherDerived> &b, ResultType* resul
   return true;
 }
 
+/** Computes the polar decomposition of the matrix, as a product unitary x positive.
+  *
+  * If either pointer is zero, the corresponding computation is skipped.
+  *
+  * Only for square matrices.
+  *
+  * \sa computePositiveUnitary(), computeRotationScaling()
+  */
+template<typename MatrixType>
+template<typename UnitaryType, typename PositiveType>
+void SVD<MatrixType>::computeUnitaryPositive(UnitaryType *unitary,
+                                             PositiveType *positive) const
+{
+  ei_assert(m_matU.cols() == m_matV.cols() && "Polar decomposition is only for square matrices");
+  if(unitary) *unitary = m_matU * m_matV.adjoint();
+  if(positive) *positive = m_matV * m_sigma.asDiagonal() * m_matV.adjoint();
+}
+
+/** Computes the polar decomposition of the matrix, as a product positive x unitary.
+  *
+  * If either pointer is zero, the corresponding computation is skipped.
+  *
+  * Only for square matrices.
+  *
+  * \sa computeUnitaryPositive(), computeRotationScaling()
+  */
+template<typename MatrixType>
+template<typename UnitaryType, typename PositiveType>
+void SVD<MatrixType>::computePositiveUnitary(UnitaryType *positive,
+                                             PositiveType *unitary) const
+{
+  ei_assert(m_matU.rows() == m_matV.rows() && "Polar decomposition is only for square matrices");
+  if(unitary) *unitary = m_matU * m_matV.adjoint();
+  if(positive) *positive = m_matU * m_sigma.asDiagonal() * m_matU.adjoint();
+}
+
+/** decomposes the matrix as a product rotation x scaling, the scaling being
+  * not necessarily positive.
+  *
+  * If either pointer is zero, the corresponding computation is skipped.
+  *
+  * This method requires the Geometry module.
+  *
+  * \sa computeScalingRotation(), computeUnitaryPositive()
+  */
+template<typename MatrixType>
+template<typename RotationType, typename ScalingType>
+void SVD<MatrixType>::computeRotationScaling(RotationType *rotation, ScalingType *scaling) const
+{
+  ei_assert(m_matU.rows() == m_matV.rows() && "Polar decomposition is only for square matrices");
+  Scalar x = (m_matU * m_matV.adjoint()).determinant(); // so x has absolute value 1
+  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> sv(m_sigma);
+  sv.coeffRef(0) *= x;
+  if(scaling) scaling->lazyAssign(m_matV * sv.asDiagonal() * m_matV.adjoint());
+  if(rotation)
+  {
+    MatrixType m(m_matU);
+    m.col(0) /= x;
+    rotation->lazyAssign(m * m_matV.adjoint());
+  }
+}
+
+/** decomposes the matrix as a product scaling x rotation, the scaling being
+  * not necessarily positive.
+  *
+  * If either pointer is zero, the corresponding computation is skipped.
+  *
+  * This method requires the Geometry module.
+  *
+  * \sa computeRotationScaling(), computeUnitaryPositive()
+  */
+template<typename MatrixType>
+template<typename ScalingType, typename RotationType>
+void SVD<MatrixType>::computeScalingRotation(ScalingType *scaling, RotationType *rotation) const
+{
+  ei_assert(m_matU.rows() == m_matV.rows() && "Polar decomposition is only for square matrices");
+  Scalar x = (m_matU * m_matV.adjoint()).determinant(); // so x has absolute value 1
+  Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> sv(m_sigma);
+  sv.coeffRef(0) *= x;
+  if(scaling) scaling->lazyAssign(m_matU * sv.asDiagonal() * m_matU.adjoint());
+  if(rotation)
+  {
+    MatrixType m(m_matU);
+    m.col(0) /= x;
+    rotation->lazyAssign(m * m_matV.adjoint());
+  }
+}
+
+
 /** \svd_module
   * \returns the SVD decomposition of \c *this
   */

Eigen/src/Sparse/AmbiVector.h

@@ -99,6 +99,8 @@ template<typename _Scalar> class AmbiVector
       allocSize = allocSize/sizeof(Scalar) + (allocSize%sizeof(Scalar)>0?1:0);
       Scalar* newBuffer = new Scalar[allocSize];
       memcpy(newBuffer,  m_buffer,  copyElements * sizeof(ListEl));
+      delete[] m_buffer;
+      m_buffer = newBuffer;
     }
 
   protected:
@@ -238,8 +240,11 @@ Scalar& AmbiVector<Scalar>::coeffRef(int i)
       else
       {
         if (m_llSize>=m_allocatedElements)
+        {
           reallocateSparse();
-        ei_internal_assert(m_llSize<m_size && "internal error: overflow in sparse mode");
+          llElements = reinterpret_cast<ListEl*>(m_buffer);
+        }
+        ei_internal_assert(m_llSize<m_allocatedElements && "internal error: overflow in sparse mode");
         // let's insert a new coefficient
         ListEl& el = llElements[m_llSize];
         el.value = Scalar(0);
@@ -365,6 +370,9 @@ class AmbiVector<_Scalar>::Iterator
     int m_cachedIndex;          // current coordinate
     Scalar m_cachedValue;       // current value
     bool m_isDense;             // mode of the vector
+
+  private:
+    Iterator& operator=(const Iterator&);
 };
 
 

Eigen/src/Sparse/CMakeLists.txt

@@ -2,5 +2,5 @@ FILE(GLOB Eigen_Sparse_SRCS "*.h")
 
 INSTALL(FILES 
   ${Eigen_Sparse_SRCS}
-  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Sparse
+  DESTINATION ${INCLUDE_INSTALL_DIR}/Eigen/src/Sparse COMPONENT Devel
   )

Eigen/src/Sparse/CholmodSupport.h

@@ -1,7 +1,7 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra. Eigen itself is part of the KDE project.
 //
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -54,16 +54,17 @@ void ei_cholmod_configure_matrix(CholmodType& mat)
   }
 }
 
-template<typename Scalar, int Flags>
-cholmod_sparse SparseMatrix<Scalar,Flags>::asCholmodMatrix()
+template<typename Derived>
+cholmod_sparse SparseMatrixBase<Derived>::asCholmodMatrix()
 {
+  typedef typename Derived::Scalar Scalar;
   cholmod_sparse res;
   res.nzmax   = nonZeros();
   res.nrow    = rows();;
   res.ncol    = cols();
-  res.p       = _outerIndexPtr();
-  res.i       = _innerIndexPtr();
-  res.x       = _valuePtr();
+  res.p       = derived()._outerIndexPtr();
+  res.i       = derived()._innerIndexPtr();
+  res.x       = derived()._valuePtr();
   res.xtype = CHOLMOD_REAL;
   res.itype = CHOLMOD_INT;
   res.sorted = 1;
@@ -73,11 +74,11 @@ cholmod_sparse SparseMatrix<Scalar,Flags>::asCholmodMatrix()
 
   ei_cholmod_configure_matrix<Scalar>(res);
 
-  if (Flags & SelfAdjoint)
+  if (Derived::Flags & SelfAdjoint)
   {
-    if (Flags & UpperTriangular)
+    if (Derived::Flags & UpperTriangular)
       res.stype = 1;
-    else if (Flags & LowerTriangular)
+    else if (Derived::Flags & LowerTriangular)
       res.stype = -1;
     else
       res.stype = 0;
@@ -108,19 +109,14 @@ cholmod_dense ei_cholmod_map_eigen_to_dense(MatrixBase<Derived>& mat)
 }
 
 template<typename Scalar, int Flags>
-SparseMatrix<Scalar,Flags> SparseMatrix<Scalar,Flags>::Map(cholmod_sparse& cm)
+MappedSparseMatrix<Scalar,Flags>::MappedSparseMatrix(cholmod_sparse& cm)
 {
-  SparseMatrix res;
-  res.m_innerSize = cm.nrow;
-  res.m_outerSize = cm.ncol;
-  res.m_outerIndex = reinterpret_cast<int*>(cm.p);
-  SparseArray<Scalar> data = SparseArray<Scalar>::Map(
-                                reinterpret_cast<int*>(cm.i),
-                                reinterpret_cast<Scalar*>(cm.x),
-                                res.m_outerIndex[cm.ncol]);
-  res.m_data.swap(data);
-  res.markAsRValue();
-  return res;
+  m_innerSize = cm.nrow;
+  m_outerSize = cm.ncol;
+  m_outerIndex = reinterpret_cast<int*>(cm.p);
+  m_innerIndices = reinterpret_cast<int*>(cm.i);
+  m_values = reinterpret_cast<Scalar*>(cm.x);
+  m_nnz = m_outerIndex[cm.ncol];
 }
 
 template<typename MatrixType>
@@ -128,8 +124,8 @@ class SparseLLT<MatrixType,Cholmod> : public SparseLLT<MatrixType>
 {
   protected:
     typedef SparseLLT<MatrixType> Base;
-    using typename Base::Scalar;
-    using Base::RealScalar;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::RealScalar RealScalar;
     using Base::MatrixLIsDirty;
     using Base::SupernodalFactorIsDirty;
     using Base::m_flags;
@@ -210,7 +206,7 @@ SparseLLT<MatrixType,Cholmod>::matrixL() const
     ei_assert(!(m_status & SupernodalFactorIsDirty));
 
     cholmod_sparse* cmRes = cholmod_factor_to_sparse(m_cholmodFactor, &m_cholmod);
-    const_cast<typename Base::CholMatrixType&>(m_matrix) = Base::CholMatrixType::Map(*cmRes);
+    const_cast<typename Base::CholMatrixType&>(m_matrix) = MappedSparseMatrix<Scalar>(*cmRes);
     free(cmRes);
 
     m_status = (m_status & ~MatrixLIsDirty);

Eigen/src/Sparse/CompressedStorage.h

@@ -0,0 +1,230 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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_COMPRESSED_STORAGE_H
+#define EIGEN_COMPRESSED_STORAGE_H
+
+/** Stores a sparse set of values as a list of values and a list of indices.
+  *
+  */
+template<typename Scalar>
+class CompressedStorage
+{
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+  public:
+    CompressedStorage()
+      : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
+    {}
+
+    CompressedStorage(size_t size)
+      : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
+    {
+      resize(size);
+    }
+
+    CompressedStorage(const CompressedStorage& other)
+      : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
+    {
+      *this = other;
+    }
+
+    CompressedStorage& operator=(const CompressedStorage& other)
+    {
+      resize(other.size());
+      memcpy(m_values, other.m_values, m_size * sizeof(Scalar));
+      memcpy(m_indices, other.m_indices, m_size * sizeof(int));
+      return *this;
+    }
+
+    void swap(CompressedStorage& other)
+    {
+      std::swap(m_values, other.m_values);
+      std::swap(m_indices, other.m_indices);
+      std::swap(m_size, other.m_size);
+      std::swap(m_allocatedSize, other.m_allocatedSize);
+    }
+
+    ~CompressedStorage()
+    {
+      delete[] m_values;
+      delete[] m_indices;
+    }
+
+    void reserve(size_t size)
+    {
+      size_t newAllocatedSize = m_size + size;
+      if (newAllocatedSize > m_allocatedSize)
+        reallocate(newAllocatedSize);
+    }
+
+    void squeeze()
+    {
+      if (m_allocatedSize>m_size)
+        reallocate(m_size);
+    }
+
+    void resize(size_t size, float reserveSizeFactor = 0)
+    {
+      if (m_allocatedSize<size)
+        reallocate(size + size_t(reserveSizeFactor*size));
+      m_size = size;
+    }
+
+    void append(const Scalar& v, int i)
+    {
+      int id = m_size;
+      resize(m_size+1, 1);
+      m_values[id] = v;
+      m_indices[id] = i;
+    }
+
+    inline size_t size() const { return m_size; }
+    inline size_t allocatedSize() const { return m_allocatedSize; }
+    inline void clear() { m_size = 0; }
+
+    inline Scalar& value(size_t i) { return m_values[i]; }
+    inline const Scalar& value(size_t i) const { return m_values[i]; }
+
+    inline int& index(size_t i) { return m_indices[i]; }
+    inline const int& index(size_t i) const { return m_indices[i]; }
+
+    static CompressedStorage Map(int* indices, Scalar* values, size_t size)
+    {
+      CompressedStorage res;
+      res.m_indices = indices;
+      res.m_values = values;
+      res.m_allocatedSize = res.m_size = size;
+      return res;
+    }
+    
+    /** \returns the largest \c k such that for all \c j in [0,k) index[\c j]\<\a key */
+    inline int searchLowerIndex(int key) const
+    {
+      return searchLowerIndex(0, m_size, key);
+    }
+    
+    /** \returns the largest \c k in [start,end) such that for all \c j in [start,k) index[\c j]\<\a key */
+    inline int searchLowerIndex(size_t start, size_t end, int key) const
+    {
+      while(end>start)
+      {
+        size_t mid = (end+start)>>1;
+        if (m_indices[mid]<key)
+          start = mid+1;
+        else
+          end = mid;
+      }
+      return start;
+    }
+    
+    /** \returns the stored value at index \a key
+      * If the value does not exist, then the value \a defaultValue is returned without any insertion. */
+    inline Scalar at(int key, Scalar defaultValue = Scalar(0)) const
+    {
+      if (m_size==0)
+        return defaultValue;
+      else if (key==m_indices[m_size-1])
+        return m_values[m_size-1];
+      // ^^  optimization: let's first check if it is the last coefficient
+      // (very common in high level algorithms)
+      const size_t id = searchLowerIndex(0,m_size-1,key);
+      return ((id<m_size) && (m_indices[id]==key)) ? m_values[id] : defaultValue;
+    }
+    
+    /** Like at(), but the search is performed in the range [start,end) */
+    inline Scalar atInRange(size_t start, size_t end, int key, Scalar defaultValue = Scalar(0)) const
+    {
+      if (start==end)
+        return Scalar(0);
+      else if (end>start && key==m_indices[end-1])
+        return m_values[end-1];
+      // ^^  optimization: let's first check if it is the last coefficient
+      // (very common in high level algorithms)
+      const size_t id = searchLowerIndex(start,end-1,key);
+      return ((id<end) && (m_indices[id]==key)) ? m_values[id] : defaultValue;
+    }
+    
+    /** \returns a reference to the value at index \a key
+      * If the value does not exist, then the value \a defaultValue is inserted
+      * such that the keys are sorted. */
+    inline Scalar& atWithInsertion(int key, Scalar defaultValue = Scalar(0))
+    {
+      size_t id = searchLowerIndex(0,m_size,key);
+      if (id>=m_size || m_indices[id]!=key)
+      {
+        resize(m_size+1,1);
+        for (size_t j=m_size-1; j>id; --j)
+        {
+          m_indices[j] = m_indices[j-1];
+          m_values[j] = m_values[j-1];
+        }
+        m_indices[id] = key;
+        m_values[id] = defaultValue;
+      }
+      return m_values[id];
+    }
+    
+    void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
+    {
+      size_t k = 0;
+      size_t n = size();
+      for (size_t i=0; i<n; ++i)
+      {
+        if (!ei_isMuchSmallerThan(value(i), reference, epsilon))
+        {
+          value(k) = value(i);
+          index(k) = index(i);
+          ++k;
+        }
+      }
+      resize(k,0);
+    }
+
+  protected:
+
+    inline void reallocate(size_t size)
+    {
+      Scalar* newValues  = new Scalar[size];
+      int* newIndices = new int[size];
+      size_t copySize = std::min(size, m_size);
+      // copy
+      memcpy(newValues,  m_values,  copySize * sizeof(Scalar));
+      memcpy(newIndices, m_indices, copySize * sizeof(int));
+      // delete old stuff
+      delete[] m_values;
+      delete[] m_indices;
+      m_values = newValues;
+      m_indices = newIndices;
+      m_allocatedSize = size;
+    }
+
+  protected:
+    Scalar* m_values;
+    int* m_indices;
+    size_t m_size;
+    size_t m_allocatedSize;
+
+};
+
+#endif // EIGEN_COMPRESSED_STORAGE_H

Eigen/src/Sparse/CoreIterators.h

@@ -28,216 +28,41 @@
 /* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
  */
 
-template<typename Derived>
-class MatrixBase<Derived>::InnerIterator
+/** \class InnerIterator
+  * \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression
+  *
+  * todo
+  */
+
+// generic version for dense matrix and expressions
+template<typename Derived> class MatrixBase<Derived>::InnerIterator
 {
     typedef typename Derived::Scalar Scalar;
+    enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit };
   public:
-    InnerIterator(const Derived& mat, int outer)
-      : m_matrix(mat), m_inner(0), m_outer(outer), m_end(mat.rows())
+    EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, int outer)
+      : m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.rows())
     {}
 
-    Scalar value() const
+    EIGEN_STRONG_INLINE Scalar value() const
     {
-      return (Derived::Flags&RowMajorBit) ? m_matrix.coeff(m_outer, m_inner)
-                                          : m_matrix.coeff(m_inner, m_outer);
+      return (IsRowMajor) ? m_expression.coeff(m_outer, m_inner)
+                          : m_expression.coeff(m_inner, m_outer);
     }
 
-    InnerIterator& operator++() { m_inner++; return *this; }
+    EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; }
 
-    int index() const { return m_inner; }
+    EIGEN_STRONG_INLINE int index() const { return m_inner; }
+    inline int row() const { return IsRowMajor ? m_outer : index(); }
+    inline int col() const { return IsRowMajor ? index() : m_outer; }
 
-    operator bool() const { return m_inner < m_end && m_inner>=0; }
+    EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; }
 
   protected:
-    const Derived& m_matrix;
+    const Derived& m_expression;
     int m_inner;
     const int m_outer;
     const int m_end;
 };
 
-template<typename MatrixType>
-class Transpose<MatrixType>::InnerIterator : public MatrixType::InnerIterator
-{
-  public:
-
-    InnerIterator(const Transpose& trans, int outer)
-      : MatrixType::InnerIterator(trans.m_matrix, outer)
-    {}
-};
-
-template<typename MatrixType, int BlockRows, int BlockCols, int PacketAccess, int _DirectAccessStatus>
-class Block<MatrixType, BlockRows, BlockCols, PacketAccess, _DirectAccessStatus>::InnerIterator
-{
-    typedef typename Block::Scalar Scalar;
-    typedef typename ei_traits<Block>::_MatrixTypeNested _MatrixTypeNested;
-    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
-  public:
-
-    InnerIterator(const Block& block, int outer)
-      : m_iter(block.m_matrix,(Block::Flags&RowMajor) ? block.m_startRow.value() + outer : block.m_startCol.value() + outer),
-        m_start( (Block::Flags&RowMajor) ? block.m_startCol.value() : block.m_startRow.value()),
-        m_end(m_start + ((Block::Flags&RowMajor) ? block.m_blockCols.value() : block.m_blockRows.value())),
-        m_offset( (Block::Flags&RowMajor) ? block.m_startCol.value() : block.m_startRow.value())
-    {
-      while (m_iter.index()>=0 && m_iter.index()<m_start)
-        ++m_iter;
-    }
-
-    InnerIterator& operator++()
-    {
-      ++m_iter;
-      return *this;
-    }
-
-    Scalar value() const { return m_iter.value(); }
-
-    int index() const { return m_iter.index() - m_offset; }
-
-    operator bool() const { return m_iter && m_iter.index()<m_end; }
-
-  protected:
-    MatrixTypeIterator m_iter;
-    int m_start;
-    int m_end;
-    int m_offset;
-}; 
-
-template<typename MatrixType, int BlockRows, int BlockCols, int PacketAccess>
-class Block<MatrixType, BlockRows, BlockCols, PacketAccess, IsSparse>::InnerIterator
-{
-    typedef typename Block::Scalar Scalar;
-    typedef typename ei_traits<Block>::_MatrixTypeNested _MatrixTypeNested;
-    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
-  public:
-
-    InnerIterator(const Block& block, int outer)
-      : m_iter(block.m_matrix,(Block::Flags&RowMajor) ? block.m_startRow.value() + outer : block.m_startCol.value() + outer),
-        m_start( (Block::Flags&RowMajor) ? block.m_startCol.value() : block.m_startRow.value()),
-        m_end(m_start + ((Block::Flags&RowMajor) ? block.m_blockCols.value() : block.m_blockRows.value())),
-        m_offset( (Block::Flags&RowMajor) ? block.m_startCol.value() : block.m_startRow.value())
-    {
-      while (m_iter.index()>=0 && m_iter.index()<m_start)
-        ++m_iter;
-    }
-
-    InnerIterator& operator++()
-    {
-      ++m_iter;
-      return *this;
-    }
-
-    Scalar value() const { return m_iter.value(); }
-
-    int index() const { return m_iter.index() - m_offset; }
-
-    operator bool() const { return m_iter && m_iter.index()<m_end; }
-
-  protected:
-    MatrixTypeIterator m_iter;
-    int m_start;
-    int m_end;
-    int m_offset;
-};
-
-template<typename UnaryOp, typename MatrixType>
-class CwiseUnaryOp<UnaryOp,MatrixType>::InnerIterator
-{
-    typedef typename CwiseUnaryOp::Scalar Scalar;
-    typedef typename ei_traits<CwiseUnaryOp>::_MatrixTypeNested _MatrixTypeNested;
-    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
-  public:
-
-    InnerIterator(const CwiseUnaryOp& unaryOp, int outer)
-      : m_iter(unaryOp.m_matrix,outer), m_functor(unaryOp.m_functor), m_id(-1)
-    {
-      this->operator++();
-    }
-
-    InnerIterator& operator++()
-    {
-      if (m_iter)
-      {
-        m_id = m_iter.index();
-        m_value = m_functor(m_iter.value());
-        ++m_iter;
-      }
-      else
-      {
-        m_id = -1;
-      }
-      return *this;
-    }
-
-    Scalar value() const { return m_value; }
-
-    int index() const { return m_id; }
-
-    operator bool() const { return m_id>=0; }
-
-  protected:
-    MatrixTypeIterator m_iter;
-    const UnaryOp& m_functor;
-    Scalar m_value;
-    int m_id;
-};
-
-template<typename BinaryOp, typename Lhs, typename Rhs>
-class CwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator
-{
-    typedef typename CwiseBinaryOp::Scalar Scalar;
-    typedef typename ei_traits<CwiseBinaryOp>::_LhsNested _LhsNested;
-    typedef typename _LhsNested::InnerIterator LhsIterator;
-    typedef typename ei_traits<CwiseBinaryOp>::_RhsNested _RhsNested;
-    typedef typename _RhsNested::InnerIterator RhsIterator;
-  public:
-
-    InnerIterator(const CwiseBinaryOp& binOp, int outer)
-      : m_lhsIter(binOp.m_lhs,outer), m_rhsIter(binOp.m_rhs,outer), m_functor(binOp.m_functor), m_id(-1)
-    {
-      this->operator++();
-    }
-
-    InnerIterator& operator++()
-    {
-      if (m_lhsIter && m_rhsIter && (m_lhsIter.index() == m_rhsIter.index()))
-      {
-        m_id = m_lhsIter.index();
-        m_value = m_functor(m_lhsIter.value(), m_rhsIter.value());
-        ++m_lhsIter;
-        ++m_rhsIter;
-      }
-      else if (m_lhsIter && (!m_rhsIter || (m_lhsIter.index() < m_rhsIter.index())))
-      {
-        m_id = m_lhsIter.index();
-        m_value = m_functor(m_lhsIter.value(), Scalar(0));
-        ++m_lhsIter;
-      }
-      else if (m_rhsIter && (!m_lhsIter || (m_lhsIter.index() > m_rhsIter.index())))
-      {
-        m_id = m_rhsIter.index();
-        m_value = m_functor(Scalar(0), m_rhsIter.value());
-        ++m_rhsIter;
-      }
-      else
-      {
-        m_id = -1;
-      }
-      return *this;
-    }
-
-    Scalar value() const { return m_value; }
-
-    int index() const { return m_id; }
-
-    operator bool() const { return m_id>=0; }
-
-  protected:
-    LhsIterator m_lhsIter;
-    RhsIterator m_rhsIter;
-    const BinaryOp& m_functor;
-    Scalar m_value;
-    int m_id;
-};
-
 #endif // EIGEN_COREITERATORS_H

Eigen/src/Sparse/DynamicSparseMatrix.h

@@ -0,0 +1,299 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.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_DYNAMIC_SPARSEMATRIX_H
+#define EIGEN_DYNAMIC_SPARSEMATRIX_H
+
+/** \class DynamicSparseMatrix
+  *
+  * \brief A sparse matrix class designed for matrix assembly purpose
+  *
+  * \param _Scalar the scalar type, i.e. the type of the coefficients
+  *
+  * Unlike SparseMatrix, this class provides a much higher degree of flexibility. In particular, it allows
+  * random read/write accesses in log(rho*outer_size) where \c rho is the probability that a coefficient is
+  * nonzero and outer_size is the number of columns if the matrix is column-major and the number of rows
+  * otherwise.
+  * 
+  * Internally, the data are stored as a std::vector of compressed vector. The performances of random writes might
+  * decrease as the number of nonzeros per inner-vector increase. In practice, we observed very good performance
+  * till about 100 nonzeros/vector, and the performance remains relatively good till 500 nonzeros/vectors.
+  *
+  * \see SparseMatrix
+  */
+template<typename _Scalar, int _Flags>
+struct ei_traits<DynamicSparseMatrix<_Scalar, _Flags> >
+{
+  typedef _Scalar Scalar;
+  enum {
+    RowsAtCompileTime = Dynamic,
+    ColsAtCompileTime = Dynamic,
+    MaxRowsAtCompileTime = Dynamic,
+    MaxColsAtCompileTime = Dynamic,
+    Flags = SparseBit | _Flags,
+    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    SupportedAccessPatterns = OuterRandomAccessPattern
+  };
+};
+
+template<typename _Scalar, int _Flags>
+class DynamicSparseMatrix
+  : public SparseMatrixBase<DynamicSparseMatrix<_Scalar, _Flags> >
+{
+  public:
+    EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(DynamicSparseMatrix)
+    // FIXME: why are these operator already alvailable ???
+    // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, +=)
+    // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, -=)
+    typedef MappedSparseMatrix<Scalar,Flags> Map;
+
+  protected:
+
+    enum { IsRowMajor = Base::IsRowMajor };
+    typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
+
+    int m_innerSize;
+    std::vector<CompressedStorage<Scalar> > m_data;
+
+  public:
+  
+    inline int rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
+    inline int cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
+    inline int innerSize() const { return m_innerSize; }
+    inline int outerSize() const { return m_data.size(); }
+    inline int innerNonZeros(int j) const { return m_data[j].size(); }
+    
+    std::vector<CompressedStorage<Scalar> >& _data() { return m_data; }
+    const std::vector<CompressedStorage<Scalar> >& _data() const { return m_data; }
+
+    /** \returns the coefficient value at given position \a row, \a col
+      * This operation involes a log(rho*outer_size) binary search.
+      */
+    inline Scalar coeff(int row, int col) const
+    {
+      const int outer = IsRowMajor ? row : col;
+      const int inner = IsRowMajor ? col : row;
+      return m_data[outer].at(inner);
+    }
+
+    /** \returns a reference to the coefficient value at given position \a row, \a col
+      * This operation involes a log(rho*outer_size) binary search. If the coefficient does not
+      * exist yet, then a sorted insertion into a sequential buffer is performed.
+      */
+    inline Scalar& coeffRef(int row, int col)
+    {
+      const int outer = IsRowMajor ? row : col;
+      const int inner = IsRowMajor ? col : row;
+      return m_data[outer].atWithInsertion(inner);
+    }
+
+    class InnerIterator;
+
+    inline void setZero()
+    {
+      for (int j=0; j<outerSize(); ++j)
+        m_data[j].clear();
+    }
+
+    /** \returns the number of non zero coefficients */
+    inline int nonZeros() const
+    {
+      int res = 0;
+      for (int j=0; j<outerSize(); ++j)
+        res += m_data[j].size();
+      return res;
+    }
+
+    /** Set the matrix to zero and reserve the memory for \a reserveSize nonzero coefficients. */
+    inline void startFill(int reserveSize = 1000)
+    {
+      if (outerSize()>0)
+      {
+        int reserveSizePerVector = std::max(reserveSize/outerSize(),4);
+        for (int j=0; j<outerSize(); ++j)
+        {
+          m_data[j].clear();
+          m_data[j].reserve(reserveSizePerVector);
+        }
+      }
+    }
+
+    /** inserts a nonzero coefficient at given coordinates \a row, \a col and returns its reference assuming that:
+      *  1 - the coefficient does not exist yet
+      *  2 - this the coefficient with greater inner coordinate for the given outer coordinate.
+      * In other words, assuming \c *this is column-major, then there must not exists any nonzero coefficient of coordinates
+      * \c i \c x \a col such that \c i >= \a row. Otherwise the matrix is invalid.
+      * 
+      * \see fillrand(), coeffRef()
+      */
+    inline Scalar& fill(int row, int col)
+    {
+      const int outer = IsRowMajor ? row : col;
+      const int inner = IsRowMajor ? col : row;
+      ei_assert(outer<int(m_data.size()) && inner<m_innerSize);
+      ei_assert((m_data[outer].size()==0) || (m_data[outer].index(m_data[outer].size()-1)<inner));
+      m_data[outer].append(0, inner);
+      return m_data[outer].value(m_data[outer].size()-1);
+    }
+
+    /** Like fill() but with random inner coordinates.
+      * Compared to the generic coeffRef(), the unique limitation is that we assume
+      * the coefficient does not exist yet.
+      */
+    inline Scalar& fillrand(int row, int col)
+    {
+      const int outer = IsRowMajor ? row : col;
+      const int inner = IsRowMajor ? col : row;
+      
+      int startId = 0;
+      int id = m_data[outer].size() - 1;
+      m_data[outer].resize(id+2,1);
+
+      while ( (id >= startId) && (m_data[outer].index(id) > inner) )
+      {
+        m_data[outer].index(id+1) = m_data[outer].index(id);
+        m_data[outer].value(id+1) = m_data[outer].value(id);
+        --id;
+      }
+      m_data[outer].index(id+1) = inner;
+      m_data[outer].value(id+1) = 0;
+      return m_data[outer].value(id+1);
+    }
+
+    /** Does nothing. Provided for compatibility with SparseMatrix. */
+    inline void endFill() {}
+    
+    void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
+    {
+      for (int j=0; j<outerSize(); ++j)
+        m_data[j].prune(reference,epsilon);
+    }
+
+    /** Resize the matrix without preserving the data (the matrix is set to zero)
+      */
+    void resize(int rows, int cols)
+    {
+      const int outerSize = IsRowMajor ? rows : cols;
+      m_innerSize = IsRowMajor ? cols : rows;
+      setZero();
+      if (int(m_data.size()) != outerSize)
+      {
+        m_data.resize(outerSize);
+      }
+    }
+    
+    void resizeAndKeepData(int rows, int cols)
+    {
+      const int outerSize = IsRowMajor ? rows : cols;
+      const int innerSize = IsRowMajor ? cols : rows;
+      if (m_innerSize>innerSize)
+      {
+        // remove all coefficients with innerCoord>=innerSize
+        // TODO
+        std::cerr << "not implemented yet\n";
+        exit(2);
+      }
+      if (m_data.size() != outerSize)
+      {
+        m_data.resize(outerSize);
+      }
+    }
+
+    inline DynamicSparseMatrix()
+      : m_innerSize(0), m_data(0)
+    {
+      ei_assert(innerSize()==0 && outerSize()==0);
+    }
+
+    inline DynamicSparseMatrix(int rows, int cols)
+      : m_innerSize(0)
+    {
+      resize(rows, cols);
+    }
+
+    template<typename OtherDerived>
+    inline DynamicSparseMatrix(const SparseMatrixBase<OtherDerived>& other)
+      : m_innerSize(0)
+    {
+      *this = other.derived();
+    }
+
+    inline DynamicSparseMatrix(const DynamicSparseMatrix& other)
+      : Base(), m_innerSize(0)
+    {
+      *this = other.derived();
+    }
+
+    inline void swap(DynamicSparseMatrix& other)
+    {
+      //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
+      std::swap(m_innerSize, other.m_innerSize);
+      //std::swap(m_outerSize, other.m_outerSize);
+      m_data.swap(other.m_data);
+    }
+
+    inline DynamicSparseMatrix& operator=(const DynamicSparseMatrix& other)
+    {
+      if (other.isRValue())
+      {
+        swap(other.const_cast_derived());
+      }
+      else
+      {
+        resize(other.rows(), other.cols());
+        m_data = other.m_data;
+      }
+      return *this;
+    }
+
+    template<typename OtherDerived>
+    inline DynamicSparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other)
+    {
+      return SparseMatrixBase<DynamicSparseMatrix>::operator=(other.derived());
+    }
+
+    /** Destructor */
+    inline ~DynamicSparseMatrix() {}
+};
+
+template<typename Scalar, int _Flags>
+class DynamicSparseMatrix<Scalar,_Flags>::InnerIterator : public SparseVector<Scalar,_Flags>::InnerIterator
+{
+    typedef typename SparseVector<Scalar,_Flags>::InnerIterator Base;
+  public:
+    InnerIterator(const DynamicSparseMatrix& mat, int outer)
+      : Base(mat.m_data[outer]), m_outer(outer)
+    {}
+    
+    inline int row() const { return IsRowMajor ? m_outer : Base::index(); }
+    inline int col() const { return IsRowMajor ? Base::index() : m_outer; }
+
+  protected:
+    const int m_outer;
+
+  private:
+    InnerIterator& operator=(const InnerIterator&);
+};
+
+#endif // EIGEN_DYNAMIC_SPARSEMATRIX_H

Eigen/src/Sparse/MappedSparseMatrix.h

@@ -0,0 +1,175 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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_MAPPED_SPARSEMATRIX_H
+#define EIGEN_MAPPED_SPARSEMATRIX_H
+
+/** \class MappedSparseMatrix
+  *
+  * \brief Sparse matrix
+  *
+  * \param _Scalar the scalar type, i.e. the type of the coefficients
+  *
+  * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
+  *
+  */
+template<typename _Scalar, int _Flags>
+struct ei_traits<MappedSparseMatrix<_Scalar, _Flags> > : ei_traits<SparseMatrix<_Scalar, _Flags> >
+{};
+
+template<typename _Scalar, int _Flags>
+class MappedSparseMatrix
+  : public SparseMatrixBase<MappedSparseMatrix<_Scalar, _Flags> >
+{
+  public:
+    EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(MappedSparseMatrix)
+
+  protected:
+    enum { IsRowMajor = Base::IsRowMajor };
+
+    int m_outerSize;
+    int m_innerSize;
+    int m_nnz;
+    int* m_outerIndex;
+    int* m_innerIndices;
+    Scalar* m_values;
+
+  public:
+
+    inline int rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
+    inline int cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
+    inline int innerSize() const { return m_innerSize; }
+    inline int outerSize() const { return m_outerSize; }
+    inline int innerNonZeros(int j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
+
+    //----------------------------------------
+    // direct access interface
+    inline const Scalar* _valuePtr() const { return m_values; }
+    inline Scalar* _valuePtr() { return m_values; }
+
+    inline const int* _innerIndexPtr() const { return m_innerIndices; }
+    inline int* _innerIndexPtr() { return m_innerIndices; }
+
+    inline const int* _outerIndexPtr() const { return m_outerIndex; }
+    inline int* _outerIndexPtr() { return m_outerIndex; }
+    //----------------------------------------
+
+    inline Scalar coeff(int row, int col) const
+    {
+      const int outer = RowMajor ? row : col;
+      const int inner = RowMajor ? col : row;
+
+      int start = m_outerIndex[outer];
+      int end = m_outerIndex[outer+1];
+      if (start==end)
+        return Scalar(0);
+      else if (end>0 && inner==m_innerIndices[end-1])
+        return m_values[end-1];
+      // ^^  optimization: let's first check if it is the last coefficient
+      // (very common in high level algorithms)
+
+      const int* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end-1],inner);
+      const int id = r-&m_innerIndices[0];
+      return ((*r==inner) && (id<end)) ? m_values[id] : Scalar(0);
+    }
+
+    inline Scalar& coeffRef(int row, int col)
+    {
+      const int outer = RowMajor ? row : col;
+      const int inner = RowMajor ? col : row;
+
+      int start = m_outerIndex[outer];
+      int end = m_outerIndex[outer+1];
+      ei_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
+      ei_assert(end>start && "coeffRef cannot be called on a zero coefficient");
+      int* r = std::lower_bound(&m_innerIndices[start],&m_innerIndices[end],inner);
+      const int id = r-&m_innerIndices[0];
+      ei_assert((*r==inner) && (id<end) && "coeffRef cannot be called on a zero coefficient");
+      return m_values[id];
+    }
+
+    class InnerIterator;
+
+    /** \returns the number of non zero coefficients */
+    inline int nonZeros() const  { return m_nnz; }
+
+    inline MappedSparseMatrix(int rows, int cols, int nnz, int* outerIndexPtr, int* innerIndexPtr, Scalar* valuePtr)
+      : m_outerSize(IsRowMajor?rows:cols), m_innerSize(IsRowMajor?cols:rows), m_nnz(nnz), m_outerIndex(outerIndexPtr),
+        m_innerIndices(innerIndexPtr), m_values(valuePtr)
+    {}
+
+    #ifdef EIGEN_TAUCS_SUPPORT
+    explicit MappedSparseMatrix(taucs_ccs_matrix& taucsMatrix);
+    #endif
+
+    #ifdef EIGEN_CHOLMOD_SUPPORT
+    explicit MappedSparseMatrix(cholmod_sparse& cholmodMatrix);
+    #endif
+
+    #ifdef EIGEN_SUPERLU_SUPPORT
+    explicit MappedSparseMatrix(SluMatrix& sluMatrix);
+    #endif
+
+    /** Empty destructor */
+    inline ~MappedSparseMatrix() {}
+};
+
+template<typename Scalar, int _Flags>
+class MappedSparseMatrix<Scalar,_Flags>::InnerIterator
+{
+  public:
+    InnerIterator(const MappedSparseMatrix& mat, int outer)
+      : m_matrix(mat),
+        m_outer(outer),
+        m_id(mat._outerIndexPtr()[outer]),
+        m_start(m_id),
+        m_end(mat._outerIndexPtr()[outer+1])
+    {}
+
+    template<unsigned int Added, unsigned int Removed>
+    InnerIterator(const Flagged<MappedSparseMatrix,Added,Removed>& mat, int outer)
+      : m_matrix(mat._expression()), m_id(m_matrix._outerIndexPtr()[outer]),
+        m_start(m_id), m_end(m_matrix._outerIndexPtr()[outer+1])
+    {}
+
+    inline InnerIterator& operator++() { m_id++; return *this; }
+
+    inline Scalar value() const { return m_matrix._valuePtr()[m_id]; }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix._valuePtr()[m_id]); }
+
+    inline int index() const { return m_matrix._innerIndexPtr()[m_id]; }
+    inline int row() const { return IsRowMajor ? m_outer : index(); }
+    inline int col() const { return IsRowMajor ? index() : m_outer; }
+
+    inline operator bool() const { return (m_id < m_end) && (m_id>=m_start); }
+
+  protected:
+    const MappedSparseMatrix& m_matrix;
+    const int m_outer;
+    int m_id;
+    const int m_start;
+    const int m_end;
+};
+
+#endif // EIGEN_MAPPED_SPARSEMATRIX_H

Eigen/src/Sparse/RandomSetter.h

@@ -25,6 +25,10 @@
 #ifndef EIGEN_RANDOMSETTER_H
 #define EIGEN_RANDOMSETTER_H
 
+/** Represents a std::map
+  *
+  * \see RandomSetter
+  */
 template<typename Scalar> struct StdMapTraits
 {
   typedef int KeyType;
@@ -36,20 +40,40 @@ template<typename Scalar> struct StdMapTraits
   static void setInvalidKey(Type&, const KeyType&) {}
 };
 
-#ifdef _HASH_MAP
-template<typename Scalar> struct GnuHashMapTraits
+#ifdef EIGEN_UNORDERED_MAP_SUPPORT
+/** Represents a std::unordered_map
+  *
+  * To use it you need to both define EIGEN_UNORDERED_MAP_SUPPORT and include the unordered_map header file
+  * yourself making sure that unordered_map is defined in the std namespace.
+  * 
+  * For instance, with current version of gcc you can either enable C++0x standard (-std=c++0x) or do:
+  * \code
+  * #include <tr1/unordered_map>
+  * #define EIGEN_UNORDERED_MAP_SUPPORT
+  * namespace std {
+  *   using std::tr1::unordered_map;
+  * }
+  * \endcode
+  *
+  * \see RandomSetter
+  */
+template<typename Scalar> struct StdUnorderedMapTraits
 {
   typedef int KeyType;
-  typedef __gnu_cxx::hash_map<KeyType,Scalar> Type;
+  typedef std::unordered_map<KeyType,Scalar> Type;
   enum {
     IsSorted = 0
   };
 
   static void setInvalidKey(Type&, const KeyType&) {}
 };
-#endif
+#endif // EIGEN_UNORDERED_MAP_SUPPORT
 
 #ifdef _DENSE_HASH_MAP_H_
+/** Represents a google::dense_hash_map
+  *
+  * \see RandomSetter
+  */
 template<typename Scalar> struct GoogleDenseHashMapTraits
 {
   typedef int KeyType;
@@ -64,6 +88,10 @@ template<typename Scalar> struct GoogleDenseHashMapTraits
 #endif
 
 #ifdef _SPARSE_HASH_MAP_H_
+/** Represents a google::sparse_hash_map
+  *
+  * \see RandomSetter
+  */
 template<typename Scalar> struct GoogleSparseHashMapTraits
 {
   typedef int KeyType;
@@ -78,7 +106,19 @@ template<typename Scalar> struct GoogleSparseHashMapTraits
 
 /** \class RandomSetter
   *
-  * Typical usage:
+  * \brief The RandomSetter is a wrapper object allowing to set/update a sparse matrix with random access
+  *
+  * \param SparseMatrixType the type of the sparse matrix we are updating
+  * \param MapTraits a traits class representing the map implementation used for the temporary sparse storage.
+  *                  Its default value depends on the system.
+  * \param OuterPacketBits defines the number of rows (or columns) manage by a single map object
+  *                        as a power of two exponent.
+  *
+  * This class temporarily represents a sparse matrix object using a generic map implementation allowing for
+  * efficient random access. The conversion from the compressed representation to a hash_map object is performed
+  * in the RandomSetter constructor, while the sparse matrix is updated back at destruction time. This strategy
+  * suggest the use of nested blocks as in this example:
+  *
   * \code
   * SparseMatrix<double> m(rows,cols);
   * {
@@ -91,11 +131,28 @@ template<typename Scalar> struct GoogleSparseHashMapTraits
   * // and m is ready to use.
   * \endcode
   *
-  * \note for performance and memory consumption reasons it is highly recommended to use
-  * Google's hash library. To do so you have two options:
-  *  - include <google/dense_hash_map> yourself \b before Eigen/Sparse header
+  * Since hash_map objects are not fully sorted, representing a full matrix as a single hash_map would
+  * involve a big and costly sort to update the compressed matrix back. To overcome this issue, a RandomSetter
+  * use multiple hash_map, each representing 2^OuterPacketBits columns or rows according to the storage order.
+  * To reach optimal performance, this value should be adjusted according to the average number of nonzeros
+  * per rows/columns.
+  *
+  * The possible values for the template parameter MapTraits are:
+  *  - \b StdMapTraits: corresponds to std::map. (does not perform very well)
+  *  - \b GnuHashMapTraits: corresponds to __gnu_cxx::hash_map (available only with GCC)
+  *  - \b GoogleDenseHashMapTraits: corresponds to google::dense_hash_map (best efficiency, reasonable memory consumption)
+  *  - \b GoogleSparseHashMapTraits: corresponds to google::sparse_hash_map (best memory consumption, relatively good performance)
+  *
+  * The default map implementation depends on the availability, and the preferred order is:
+  * GoogleSparseHashMapTraits, GnuHashMapTraits, and finally StdMapTraits.
+  *
+  * For performance and memory consumption reasons it is highly recommended to use one of
+  * the Google's hash_map implementation. To enable the support for them, you have two options:
+  *  - \#include <google/dense_hash_map> yourself \b before Eigen/Sparse header
   *  - define EIGEN_GOOGLEHASH_SUPPORT
   * In the later case the inclusion of <google/dense_hash_map> is made for you.
+  * 
+  * \see http://code.google.com/p/google-sparsehash/
   */
 template<typename SparseMatrixType,
          template <typename T> class MapTraits =
@@ -121,11 +178,19 @@ class RandomSetter
     enum {
       SwapStorage = 1 - MapTraits<ScalarWrapper>::IsSorted,
       TargetRowMajor = (SparseMatrixType::Flags & RowMajorBit) ? 1 : 0,
-      SetterRowMajor = SwapStorage ? 1-TargetRowMajor : TargetRowMajor
+      SetterRowMajor = SwapStorage ? 1-TargetRowMajor : TargetRowMajor,
+      IsUpperTriangular = SparseMatrixType::Flags & UpperTriangularBit,
+      IsLowerTriangular = SparseMatrixType::Flags & LowerTriangularBit
     };
 
   public:
 
+    /** Constructs a random setter object from the sparse matrix \a target
+      *
+      * Note that the initial value of \a target are imported. If you want to re-set
+      * a sparse matrix from scratch, then you must set it to zero first using the
+      * setZero() function.
+      */
     inline RandomSetter(SparseMatrixType& target)
       : mp_target(&target)
     {
@@ -153,6 +218,7 @@ class RandomSetter
           (*this)(TargetRowMajor?j:it.index(), TargetRowMajor?it.index():j) = it.value();
     }
 
+    /** Destructor updating back the sparse matrix target */
     ~RandomSetter()
     {
       KeyType keyBitsMask = (1<<m_keyBitsOffset)-1;
@@ -226,8 +292,11 @@ class RandomSetter
       delete[] m_hashmaps;
     }
 
+    /** \returns a reference to the coefficient at given coordinates \a row, \a col */
     Scalar& operator() (int row, int col)
     {
+      ei_assert(((!IsUpperTriangular) || (row<=col)) && "Invalid access to an upper triangular matrix");
+      ei_assert(((!IsLowerTriangular) || (col<=row)) && "Invalid access to an upper triangular matrix");
       const int outer = SetterRowMajor ? row : col;
       const int inner = SetterRowMajor ? col : row;
       const int outerMajor = outer >> OuterPacketBits; // index of the packet/map
@@ -236,7 +305,11 @@ class RandomSetter
       return m_hashmaps[outerMajor][key].value;
     }
 
-    // might be slow
+    /** \returns the number of non zero coefficients 
+      *
+      * \note According to the underlying map/hash_map implementation,
+      * this function might be quite expensive.
+      */
     int nonZeros() const
     {
       int nz = 0;

Eigen/src/Sparse/SparseArray.h

@@ -1,144 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra. Eigen itself is part of the KDE project.
-//
-// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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_SPARSE_ARRAY_H
-#define EIGEN_SPARSE_ARRAY_H
-
-/** Stores a sparse set of values as a list of values and a list of indices.
-  *
-  */
-template<typename Scalar>
-class SparseArray
-{
-  public:
-    SparseArray()
-      : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
-    {}
-
-    SparseArray(int size)
-      : m_values(0), m_indices(0), m_size(0), m_allocatedSize(0)
-    {
-      resize(size);
-    }
-
-    SparseArray(const SparseArray& other)
-    {
-      *this = other;
-    }
-
-    SparseArray& operator=(const SparseArray& other)
-    {
-      resize(other.size());
-      memcpy(m_values, other.m_values, m_size * sizeof(Scalar));
-      memcpy(m_indices, other.m_indices, m_size * sizeof(int));
-      return *this;
-    }
-
-    void swap(SparseArray& other)
-    {
-      std::swap(m_values, other.m_values);
-      std::swap(m_indices, other.m_indices);
-      std::swap(m_size, other.m_size);
-      std::swap(m_allocatedSize, other.m_allocatedSize);
-    }
-
-    ~SparseArray()
-    {
-      delete[] m_values;
-      delete[] m_indices;
-    }
-
-    void reserve(int size)
-    {
-      int newAllocatedSize = m_size + size;
-      if (newAllocatedSize > m_allocatedSize)
-        reallocate(newAllocatedSize);
-    }
-
-    void squeeze()
-    {
-      if (m_allocatedSize>m_size)
-        reallocate(m_size);
-    }
-
-    void resize(int size, int reserveSizeFactor = 0)
-    {
-      if (m_allocatedSize<size)
-        reallocate(size + reserveSizeFactor*size);
-      m_size = size;
-    }
-
-    void append(const Scalar& v, int i)
-    {
-      int id = m_size;
-      resize(m_size+1, 1);
-      m_values[id] = v;
-      m_indices[id] = i;
-    }
-
-    int size() const { return m_size; }
-    void clear() { m_size = 0; }
-
-    Scalar& value(int i) { return m_values[i]; }
-    const Scalar& value(int i) const { return m_values[i]; }
-
-    int& index(int i) { return m_indices[i]; }
-    const int& index(int i) const { return m_indices[i]; }
-
-    static SparseArray Map(int* indices, Scalar* values, int size)
-    {
-      SparseArray res;
-      res.m_indices = indices;
-      res.m_values = values;
-      res.m_allocatedSize = res.m_size = size;
-      return res;
-    }
-
-  protected:
-
-    void reallocate(int size)
-    {
-      Scalar* newValues  = new Scalar[size];
-      int* newIndices = new int[size];
-      int copySize = std::min(size, m_size);
-      // copy
-      memcpy(newValues,  m_values,  copySize * sizeof(Scalar));
-      memcpy(newIndices, m_indices, copySize * sizeof(int));
-      // delete old stuff
-      delete[] m_values;
-      delete[] m_indices;
-      m_values = newValues;
-      m_indices = newIndices;
-      m_allocatedSize = size;
-    }
-
-  protected:
-    Scalar* m_values;
-    int* m_indices;
-    int m_size;
-    int m_allocatedSize;
-
-};
-
-#endif // EIGEN_SPARSE_ARRAY_H

Eigen/src/Sparse/SparseBlock.h

@@ -23,9 +23,341 @@
 // License and a copy of the GNU General Public License along with
 // Eigen. If not, see <http://www.gnu.org/licenses/>.
 
-#ifndef EIGEN_SPARSEBLOCK_H
-#define EIGEN_SPARSEBLOCK_H
+#ifndef EIGEN_SPARSE_BLOCK_H
+#define EIGEN_SPARSE_BLOCK_H
 
+template<typename MatrixType, int Size>
+struct ei_traits<SparseInnerVectorSet<MatrixType, Size> >
+{
+  typedef typename ei_traits<MatrixType>::Scalar Scalar;
+  enum {
+    IsRowMajor = (int(MatrixType::Flags)&RowMajorBit)==RowMajorBit,
+    Flags = MatrixType::Flags,
+    RowsAtCompileTime = IsRowMajor ? Size : MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = IsRowMajor ? MatrixType::ColsAtCompileTime : Size,
+    CoeffReadCost = MatrixType::CoeffReadCost
+  };
+};
+
+template<typename MatrixType, int Size>
+class SparseInnerVectorSet : ei_no_assignment_operator,
+  public SparseMatrixBase<SparseInnerVectorSet<MatrixType, Size> >
+{
+    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
+  public:
+
+    EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseInnerVectorSet)
+    class InnerIterator: public MatrixType::InnerIterator
+    {
+      public:
+        inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
+          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer)
+        {}
+
+      private:
+        InnerIterator& operator=(const InnerIterator&);
+    };
+
+    inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
+      : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
+    {
+      ei_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
+    }
+
+    inline SparseInnerVectorSet(const MatrixType& matrix, int outer)
+      : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
+    {
+      ei_assert(Size!=Dynamic);
+      ei_assert( (outer>=0) && (outer<matrix.outerSize()) );
+    }
+
+//     template<typename OtherDerived>
+//     inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+//     {
+//       return *this;
+//     }
+
+//     template<typename Sparse>
+//     inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+//     {
+//       return *this;
+//     }
+
+    EIGEN_STRONG_INLINE int rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    EIGEN_STRONG_INLINE int cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+
+  protected:
+
+    const typename MatrixType::Nested m_matrix;
+    int m_outerStart;
+    const ei_int_if_dynamic<Size> m_outerSize;
+
+};
+
+/***************************************************************************
+* specialisation for DynamicSparseMatrix
+***************************************************************************/
+
+template<typename _Scalar, int _Options, int Size>
+class SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options>, Size>
+  : public SparseMatrixBase<SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options>, Size> >
+{
+    typedef DynamicSparseMatrix<_Scalar, _Options> MatrixType;
+    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
+  public:
+
+    EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseInnerVectorSet)
+    class InnerIterator: public MatrixType::InnerIterator
+    {
+      public:
+        inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
+          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer)
+        {}
+      private:
+        InnerIterator& operator=(const InnerIterator&);
+    };
+
+    inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
+      : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
+    {
+      ei_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
+    }
+
+    inline SparseInnerVectorSet(const MatrixType& matrix, int outer)
+      : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
+    {
+      ei_assert(Size!=Dynamic);
+      ei_assert( (outer>=0) && (outer<matrix.outerSize()) );
+    }
+
+    template<typename OtherDerived>
+    inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+    {
+      if (IsRowMajor != ((OtherDerived::Flags&RowMajorBit)==RowMajorBit))
+      {
+        // need to transpose => perform a block evaluation followed by a big swap
+        DynamicSparseMatrix<Scalar,IsRowMajor?RowMajorBit:0> aux(other);
+        *this = aux.markAsRValue();
+      }
+      else
+      {
+        // evaluate/copy vector per vector
+        for (int j=0; j<m_outerSize.value(); ++j)
+        {
+          SparseVector<Scalar,IsRowMajor ? RowMajorBit : 0> aux(other.innerVector(j));
+          m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data());
+        }
+      }
+      return *this;
+    }
+
+    inline SparseInnerVectorSet& operator=(const SparseInnerVectorSet& other)
+    {
+      return operator=<SparseInnerVectorSet>(other);
+    }
+
+//     template<typename Sparse>
+//     inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+//     {
+//       return *this;
+//     }
+
+    EIGEN_STRONG_INLINE int rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    EIGEN_STRONG_INLINE int cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+
+  protected:
+
+    const typename MatrixType::Nested m_matrix;
+    int m_outerStart;
+    const ei_int_if_dynamic<Size> m_outerSize;
+
+};
+
+
+/***************************************************************************
+* specialisation for SparseMatrix
+***************************************************************************/
+/*
+template<typename _Scalar, int _Options, int Size>
+class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options>, Size>
+  : public SparseMatrixBase<SparseInnerVectorSet<SparseMatrix<_Scalar, _Options>, Size> >
+{
+    typedef DynamicSparseMatrix<_Scalar, _Options> MatrixType;
+    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
+  public:
+
+    EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseInnerVectorSet)
+    class InnerIterator: public MatrixType::InnerIterator
+    {
+      public:
+        inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
+          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer)
+        {}
+    };
+
+    inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
+      : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
+    {
+      ei_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
+    }
+
+    inline SparseInnerVectorSet(const MatrixType& matrix, int outer)
+      : m_matrix(matrix), m_outerStart(outer)
+    {
+      ei_assert(Size==1);
+      ei_assert( (outer>=0) && (outer<matrix.outerSize()) );
+    }
+
+    template<typename OtherDerived>
+    inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+    {
+      if (IsRowMajor != ((OtherDerived::Flags&RowMajorBit)==RowMajorBit))
+      {
+        // need to transpose => perform a block evaluation followed by a big swap
+        DynamicSparseMatrix<Scalar,IsRowMajor?RowMajorBit:0> aux(other);
+        *this = aux.markAsRValue();
+      }
+      else
+      {
+        // evaluate/copy vector per vector
+        for (int j=0; j<m_outerSize.value(); ++j)
+        {
+          SparseVector<Scalar,IsRowMajor ? RowMajorBit : 0> aux(other.innerVector(j));
+          m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data());
+        }
+      }
+      return *this;
+    }
+
+    inline SparseInnerVectorSet& operator=(const SparseInnerVectorSet& other)
+    {
+      return operator=<SparseInnerVectorSet>(other);
+    }
+
+    inline const Scalar* _valuePtr() const
+    { return m_matrix._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
+    inline const int* _innerIndexPtr() const
+    { return m_matrix._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
+    inline const int* _outerIndexPtr() const { return m_matrix._outerIndexPtr() + m_outerStart; }
+
+//     template<typename Sparse>
+//     inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
+//     {
+//       return *this;
+//     }
+
+    EIGEN_STRONG_INLINE int rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
+    EIGEN_STRONG_INLINE int cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
+
+  protected:
+
+    const typename MatrixType::Nested m_matrix;
+    int m_outerStart;
+    const ei_int_if_dynamic<Size> m_outerSize;
+
+};
+*/
+//----------
+
+/** \returns the i-th row of the matrix \c *this. For row-major matrix only. */
+template<typename Derived>
+SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::row(int i)
+{
+  EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
+  return innerVector(i);
+}
+
+/** \returns the i-th row of the matrix \c *this. For row-major matrix only.
+  * (read-only version) */
+template<typename Derived>
+const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::row(int i) const
+{
+  EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
+  return innerVector(i);
+}
+
+/** \returns the i-th column of the matrix \c *this. For column-major matrix only. */
+template<typename Derived>
+SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::col(int i)
+{
+  EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  return innerVector(i);
+}
+
+/** \returns the i-th column of the matrix \c *this. For column-major matrix only.
+  * (read-only version) */
+template<typename Derived>
+const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::col(int i) const
+{
+  EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  return innerVector(i);
+}
+
+/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
+  * is col-major (resp. row-major).
+  */
+template<typename Derived>
+SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::innerVector(int outer)
+{ return SparseInnerVectorSet<Derived,1>(derived(), outer); }
+
+/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
+  * is col-major (resp. row-major). Read-only.
+  */
+template<typename Derived>
+const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::innerVector(int outer) const
+{ return SparseInnerVectorSet<Derived,1>(derived(), outer); }
+
+//----------
+
+/** \returns the i-th row of the matrix \c *this. For row-major matrix only. */
+template<typename Derived>
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(int start, int size)
+{
+  EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
+  return innerVectors(start, size);
+}
+
+/** \returns the i-th row of the matrix \c *this. For row-major matrix only.
+  * (read-only version) */
+template<typename Derived>
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(int start, int size) const
+{
+  EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
+  return innerVectors(start, size);
+}
+
+/** \returns the i-th column of the matrix \c *this. For column-major matrix only. */
+template<typename Derived>
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(int start, int size)
+{
+  EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  return innerVectors(start, size);
+}
+
+/** \returns the i-th column of the matrix \c *this. For column-major matrix only.
+  * (read-only version) */
+template<typename Derived>
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(int start, int size) const
+{
+  EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  return innerVectors(start, size);
+}
+
+/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
+  * is col-major (resp. row-major).
+  */
+template<typename Derived>
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::innerVectors(int outerStart, int outerSize)
+{ return SparseInnerVectorSet<Derived,Dynamic>(derived(), outerStart, outerSize); }
+
+/** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
+  * is col-major (resp. row-major). Read-only.
+  */
+template<typename Derived>
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::innerVectors(int outerStart, int outerSize) const
+{ return SparseInnerVectorSet<Derived,Dynamic>(derived(), outerStart, outerSize); }
+
+# if 0
 template<typename MatrixType, int BlockRows, int BlockCols, int PacketAccess>
 class Block<MatrixType,BlockRows,BlockCols,PacketAccess,IsSparse>
   : public SparseMatrixBase<Block<MatrixType,BlockRows,BlockCols,PacketAccess,IsSparse> >
@@ -117,6 +449,6 @@ public:
     const ei_int_if_dynamic<ColsAtCompileTime> m_blockCols;
 
 };
+#endif
 
-
-#endif // EIGEN_SPARSEBLOCK_H
+#endif // EIGEN_SPARSE_BLOCK_H

Eigen/src/Sparse/SparseCwise.h

@@ -0,0 +1,178 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
+// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+//
+// 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_SPARSE_CWISE_H
+#define EIGEN_SPARSE_CWISE_H
+
+/** \internal
+  * convenient macro to defined the return type of a cwise binary operation */
+#define EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(OP) \
+    CwiseBinaryOp<OP<typename ei_traits<ExpressionType>::Scalar>, ExpressionType, OtherDerived>
+
+#define EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE \
+    SparseCwiseBinaryOp< \
+      ei_scalar_product_op< \
+        typename ei_scalar_product_traits< \
+          typename ei_traits<ExpressionType>::Scalar, \
+          typename ei_traits<OtherDerived>::Scalar \
+        >::ReturnType \
+      >, \
+      ExpressionType, \
+      OtherDerived \
+    >
+
+/** \internal
+  * convenient macro to defined the return type of a cwise unary operation */
+#define EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(OP) \
+    SparseCwiseUnaryOp<OP<typename ei_traits<ExpressionType>::Scalar>, ExpressionType>
+
+/** \internal
+  * convenient macro to defined the return type of a cwise comparison to a scalar */
+/*#define EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(OP) \
+    CwiseBinaryOp<OP<typename ei_traits<ExpressionType>::Scalar>, ExpressionType, \
+        NestByValue<typename ExpressionType::ConstantReturnType> >*/
+
+template<typename ExpressionType> class SparseCwise
+{
+  public:
+
+    typedef typename ei_traits<ExpressionType>::Scalar Scalar;
+    typedef typename ei_meta_if<ei_must_nest_by_value<ExpressionType>::ret,
+        ExpressionType, const ExpressionType&>::ret ExpressionTypeNested;
+    typedef CwiseUnaryOp<ei_scalar_add_op<Scalar>, ExpressionType> ScalarAddReturnType;
+
+    inline SparseCwise(const ExpressionType& matrix) : m_matrix(matrix) {}
+
+    /** \internal */
+    inline const ExpressionType& _expression() const { return m_matrix; }
+
+    template<typename OtherDerived>
+    const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
+    operator*(const SparseMatrixBase<OtherDerived> &other) const;
+
+    template<typename OtherDerived>
+    const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
+    operator*(const MatrixBase<OtherDerived> &other) const;
+
+//     template<typename OtherDerived>
+//     const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)
+//     operator/(const SparseMatrixBase<OtherDerived> &other) const;
+//
+//     template<typename OtherDerived>
+//     const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)
+//     operator/(const MatrixBase<OtherDerived> &other) const;
+
+    template<typename OtherDerived>
+    const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)
+    min(const SparseMatrixBase<OtherDerived> &other) const;
+
+    template<typename OtherDerived>
+    const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_max_op)
+    max(const SparseMatrixBase<OtherDerived> &other) const;
+
+    const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs_op)      abs() const;
+    const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs2_op)     abs2() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_square_op)   square() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_cube_op)     cube() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_inverse_op)  inverse() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_sqrt_op)     sqrt() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_exp_op)      exp() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_log_op)      log() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_cos_op)      cos() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_sin_op)      sin() const;
+//     const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_pow_op)      pow(const Scalar& exponent) const;
+
+    template<typename OtherDerived>
+    inline ExpressionType& operator*=(const SparseMatrixBase<OtherDerived> &other);
+
+//     template<typename OtherDerived>
+//     inline ExpressionType& operator/=(const SparseMatrixBase<OtherDerived> &other);
+
+    /*
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less)
+    operator<(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::less_equal)
+    operator<=(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater)
+    operator>(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::greater_equal)
+    operator>=(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::equal_to)
+    operator==(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> const EIGEN_CWISE_BINOP_RETURN_TYPE(std::not_equal_to)
+    operator!=(const MatrixBase<OtherDerived>& other) const;
+
+    // comparisons to a scalar value
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less)
+    operator<(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::less_equal)
+    operator<=(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater)
+    operator>(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::greater_equal)
+    operator>=(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::equal_to)
+    operator==(Scalar s) const;
+
+    const EIGEN_CWISE_COMP_TO_SCALAR_RETURN_TYPE(std::not_equal_to)
+    operator!=(Scalar s) const;
+    */
+
+    // allow to extend SparseCwise outside Eigen
+    #ifdef EIGEN_SPARSE_CWISE_PLUGIN
+    #include EIGEN_SPARSE_CWISE_PLUGIN
+    #endif
+
+  protected:
+    ExpressionTypeNested m_matrix;
+
+  private:
+    SparseCwise& operator=(const SparseCwise&);
+};
+
+template<typename Derived>
+inline const SparseCwise<Derived>
+SparseMatrixBase<Derived>::cwise() const
+{
+  return derived();
+}
+
+template<typename Derived>
+inline SparseCwise<Derived>
+SparseMatrixBase<Derived>::cwise()
+{
+  return derived();
+}
+
+#endif // EIGEN_SPARSE_CWISE_H

Eigen/src/Sparse/SparseCwiseBinaryOp.h

@@ -0,0 +1,453 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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_SPARSE_CWISE_BINARY_OP_H
+#define EIGEN_SPARSE_CWISE_BINARY_OP_H
+
+// Here we have to handle 3 cases:
+//  1 - sparse op dense
+//  2 - dense op sparse
+//  3 - sparse op sparse
+// We also need to implement a 4th iterator for:
+//  4 - dense op dense
+// Finally, we also need to distinguish between the product and other operations :
+//                configuration      returned mode
+//  1 - sparse op dense    product      sparse
+//                         generic      dense
+//  2 - dense op sparse    product      sparse
+//                         generic      dense
+//  3 - sparse op sparse   product      sparse
+//                         generic      sparse
+//  4 - dense op dense     product      dense
+//                         generic      dense
+
+template<typename BinaryOp, typename Lhs, typename Rhs>
+struct ei_traits<SparseCwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
+  typedef typename ei_result_of<
+                     BinaryOp(
+                       typename Lhs::Scalar,
+                       typename Rhs::Scalar
+                     )
+                   >::type Scalar;
+  typedef typename Lhs::Nested LhsNested;
+  typedef typename Rhs::Nested RhsNested;
+  typedef typename ei_unref<LhsNested>::type _LhsNested;
+  typedef typename ei_unref<RhsNested>::type _RhsNested;
+  enum {
+    LhsCoeffReadCost = _LhsNested::CoeffReadCost,
+    RhsCoeffReadCost = _RhsNested::CoeffReadCost,
+    LhsFlags = _LhsNested::Flags,
+    RhsFlags = _RhsNested::Flags,
+    RowsAtCompileTime = Lhs::RowsAtCompileTime,
+    ColsAtCompileTime = Lhs::ColsAtCompileTime,
+    MaxRowsAtCompileTime = Lhs::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = Lhs::MaxColsAtCompileTime,
+    Flags = (int(LhsFlags) | int(RhsFlags)) & HereditaryBits,
+    CoeffReadCost = LhsCoeffReadCost + RhsCoeffReadCost + ei_functor_traits<BinaryOp>::Cost
+  };
+};
+
+template<typename BinaryOp, typename Lhs, typename Rhs>
+class SparseCwiseBinaryOp : ei_no_assignment_operator,
+  public SparseMatrixBase<SparseCwiseBinaryOp<BinaryOp, Lhs, Rhs> >
+{
+  public:
+
+    class InnerIterator;
+
+    EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseCwiseBinaryOp)
+    typedef typename ei_traits<SparseCwiseBinaryOp>::LhsNested LhsNested;
+    typedef typename ei_traits<SparseCwiseBinaryOp>::RhsNested RhsNested;
+    typedef typename ei_unref<LhsNested>::type _LhsNested;
+    typedef typename ei_unref<RhsNested>::type _RhsNested;
+
+    EIGEN_STRONG_INLINE SparseCwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
+      : m_lhs(lhs), m_rhs(rhs), m_functor(func)
+    {
+      EIGEN_STATIC_ASSERT((_LhsNested::Flags&RowMajorBit)==(_RhsNested::Flags&RowMajorBit),
+        BOTH_MATRICES_MUST_HAVE_THE_SAME_STORAGE_ORDER)
+      EIGEN_STATIC_ASSERT((ei_functor_allows_mixing_real_and_complex<BinaryOp>::ret
+                           ? int(ei_is_same_type<typename Lhs::RealScalar, typename Rhs::RealScalar>::ret)
+                           : int(ei_is_same_type<typename Lhs::Scalar, typename Rhs::Scalar>::ret)),
+        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+      // require the sizes to match
+      EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
+      ei_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
+    }
+
+    EIGEN_STRONG_INLINE int rows() const { return m_lhs.rows(); }
+    EIGEN_STRONG_INLINE int cols() const { return m_lhs.cols(); }
+
+    EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
+    EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
+    EIGEN_STRONG_INLINE const BinaryOp& functor() const { return m_functor; }
+
+  protected:
+    const LhsNested m_lhs;
+    const RhsNested m_rhs;
+    const BinaryOp m_functor;
+};
+
+template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived,
+  int _LhsStorageMode = int(Lhs::Flags) & SparseBit,
+  int _RhsStorageMode = int(Rhs::Flags) & SparseBit>
+class ei_sparse_cwise_binary_op_inner_iterator_selector;
+
+template<typename BinaryOp, typename Lhs, typename Rhs>
+class SparseCwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator
+  : public ei_sparse_cwise_binary_op_inner_iterator_selector<BinaryOp,Lhs,Rhs, typename SparseCwiseBinaryOp<BinaryOp,Lhs,Rhs>::InnerIterator>
+{
+  public:
+    typedef ei_sparse_cwise_binary_op_inner_iterator_selector<
+      BinaryOp,Lhs,Rhs, InnerIterator> Base;
+
+    EIGEN_STRONG_INLINE InnerIterator(const SparseCwiseBinaryOp& binOp, int outer)
+      : Base(binOp,outer)
+    {}
+  private:
+    InnerIterator& operator=(const InnerIterator&);
+};
+
+/***************************************************************************
+* Implementation of inner-iterators
+***************************************************************************/
+
+// template<typename T> struct ei_func_is_conjunction { enum { ret = false }; };
+// template<typename T> struct ei_func_is_conjunction<ei_scalar_product_op<T> > { enum { ret = true }; };
+
+// TODO generalize the ei_scalar_product_op specialization to all conjunctions if any !
+
+// sparse - sparse  (generic)
+template<typename BinaryOp, typename Lhs, typename Rhs, typename Derived>
+class ei_sparse_cwise_binary_op_inner_iterator_selector<BinaryOp, Lhs, Rhs, Derived, IsSparse, IsSparse>
+{
+    typedef SparseCwiseBinaryOp<BinaryOp, Lhs, Rhs> CwiseBinaryXpr;
+    typedef typename ei_traits<CwiseBinaryXpr>::Scalar Scalar;
+    typedef typename ei_traits<CwiseBinaryXpr>::_LhsNested _LhsNested;
+    typedef typename ei_traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
+    typedef typename _LhsNested::InnerIterator LhsIterator;
+    typedef typename _RhsNested::InnerIterator RhsIterator;
+  public:
+
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+      : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor())
+    {
+      this->operator++();
+    }
+
+    EIGEN_STRONG_INLINE Derived& operator++()
+    {
+      if (m_lhsIter && m_rhsIter && (m_lhsIter.index() == m_rhsIter.index()))
+      {
+        m_id = m_lhsIter.index();
+        m_value = m_functor(m_lhsIter.value(), m_rhsIter.value());
+        ++m_lhsIter;
+        ++m_rhsIter;
+      }
+      else if (m_lhsIter && (!m_rhsIter || (m_lhsIter.index() < m_rhsIter.index())))
+      {
+        m_id = m_lhsIter.index();
+        m_value = m_functor(m_lhsIter.value(), Scalar(0));
+        ++m_lhsIter;
+      }
+      else if (m_rhsIter && (!m_lhsIter || (m_lhsIter.index() > m_rhsIter.index())))
+      {
+        m_id = m_rhsIter.index();
+        m_value = m_functor(Scalar(0), m_rhsIter.value());
+        ++m_rhsIter;
+      }
+      else
+      {
+        m_id = -1;
+      }
+      return *static_cast<Derived*>(this);
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const { return m_value; }
+
+    EIGEN_STRONG_INLINE int index() const { return m_id; }
+    EIGEN_STRONG_INLINE int row() const { return m_lhsIter.row(); }
+    EIGEN_STRONG_INLINE int col() const { return m_lhsIter.col(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_id>=0; }
+
+  protected:
+    LhsIterator m_lhsIter;
+    RhsIterator m_rhsIter;
+    const BinaryOp& m_functor;
+    Scalar m_value;
+    int m_id;
+
+  private:
+    ei_sparse_cwise_binary_op_inner_iterator_selector& operator=(const ei_sparse_cwise_binary_op_inner_iterator_selector&);
+};
+
+// sparse - sparse  (product)
+template<typename T, typename Lhs, typename Rhs, typename Derived>
+class ei_sparse_cwise_binary_op_inner_iterator_selector<ei_scalar_product_op<T>, Lhs, Rhs, Derived, IsSparse, IsSparse>
+{
+    typedef ei_scalar_product_op<T> BinaryFunc;
+    typedef SparseCwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr;
+    typedef typename CwiseBinaryXpr::Scalar Scalar;
+    typedef typename ei_traits<CwiseBinaryXpr>::_LhsNested _LhsNested;
+    typedef typename _LhsNested::InnerIterator LhsIterator;
+    typedef typename ei_traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
+    typedef typename _RhsNested::InnerIterator RhsIterator;
+  public:
+
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+      : m_lhsIter(xpr.lhs(),outer), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor())
+    {
+      while (m_lhsIter && m_rhsIter && (m_lhsIter.index() != m_rhsIter.index()))
+      {
+        if (m_lhsIter.index() < m_rhsIter.index())
+          ++m_lhsIter;
+        else
+          ++m_rhsIter;
+      }
+    }
+
+    EIGEN_STRONG_INLINE Derived& operator++()
+    {
+      ++m_lhsIter;
+      ++m_rhsIter;
+      while (m_lhsIter && m_rhsIter && (m_lhsIter.index() != m_rhsIter.index()))
+      {
+        if (m_lhsIter.index() < m_rhsIter.index())
+          ++m_lhsIter;
+        else
+          ++m_rhsIter;
+      }
+      return *static_cast<Derived*>(this);
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_lhsIter.value(), m_rhsIter.value()); }
+
+    EIGEN_STRONG_INLINE int index() const { return m_lhsIter.index(); }
+    EIGEN_STRONG_INLINE int row() const { return m_lhsIter.row(); }
+    EIGEN_STRONG_INLINE int col() const { return m_lhsIter.col(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return (m_lhsIter && m_rhsIter); }
+
+  protected:
+    LhsIterator m_lhsIter;
+    RhsIterator m_rhsIter;
+    const BinaryFunc& m_functor;
+
+  private:
+    ei_sparse_cwise_binary_op_inner_iterator_selector& operator=(const ei_sparse_cwise_binary_op_inner_iterator_selector&);
+};
+
+// sparse - dense  (product)
+template<typename T, typename Lhs, typename Rhs, typename Derived>
+class ei_sparse_cwise_binary_op_inner_iterator_selector<ei_scalar_product_op<T>, Lhs, Rhs, Derived, IsSparse, IsDense>
+{
+    typedef ei_scalar_product_op<T> BinaryFunc;
+    typedef SparseCwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr;
+    typedef typename CwiseBinaryXpr::Scalar Scalar;
+    typedef typename ei_traits<CwiseBinaryXpr>::_LhsNested _LhsNested;
+    typedef typename ei_traits<CwiseBinaryXpr>::RhsNested RhsNested;
+    typedef typename _LhsNested::InnerIterator LhsIterator;
+    enum { IsRowMajor = (int(Lhs::Flags)&RowMajorBit)==RowMajorBit };
+  public:
+
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+      : m_rhs(xpr.rhs()), m_lhsIter(xpr.lhs(),outer), m_functor(xpr.functor()), m_outer(outer)
+    {}
+
+    EIGEN_STRONG_INLINE Derived& operator++()
+    {
+      ++m_lhsIter;
+      return *static_cast<Derived*>(this);
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const
+    { return m_functor(m_lhsIter.value(),
+                       m_rhs.coeff(IsRowMajor?m_outer:m_lhsIter.index(),IsRowMajor?m_lhsIter.index():m_outer)); }
+
+    EIGEN_STRONG_INLINE int index() const { return m_lhsIter.index(); }
+    EIGEN_STRONG_INLINE int row() const { return m_lhsIter.row(); }
+    EIGEN_STRONG_INLINE int col() const { return m_lhsIter.col(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter; }
+
+  protected:
+    const RhsNested m_rhs;
+    LhsIterator m_lhsIter;
+    const BinaryFunc m_functor;
+    const int m_outer;
+
+  private:
+    ei_sparse_cwise_binary_op_inner_iterator_selector& operator=(const ei_sparse_cwise_binary_op_inner_iterator_selector&);
+};
+
+// sparse - dense  (product)
+template<typename T, typename Lhs, typename Rhs, typename Derived>
+class ei_sparse_cwise_binary_op_inner_iterator_selector<ei_scalar_product_op<T>, Lhs, Rhs, Derived, IsDense, IsSparse>
+{
+    typedef ei_scalar_product_op<T> BinaryFunc;
+    typedef SparseCwiseBinaryOp<BinaryFunc, Lhs, Rhs> CwiseBinaryXpr;
+    typedef typename CwiseBinaryXpr::Scalar Scalar;
+    typedef typename ei_traits<CwiseBinaryXpr>::_RhsNested _RhsNested;
+    typedef typename _RhsNested::InnerIterator RhsIterator;
+    enum { IsRowMajor = (int(Rhs::Flags)&RowMajorBit)==RowMajorBit };
+  public:
+
+    EIGEN_STRONG_INLINE ei_sparse_cwise_binary_op_inner_iterator_selector(const CwiseBinaryXpr& xpr, int outer)
+      : m_xpr(xpr), m_rhsIter(xpr.rhs(),outer), m_functor(xpr.functor()), m_outer(outer)
+    {}
+
+    EIGEN_STRONG_INLINE Derived& operator++()
+    {
+      ++m_rhsIter;
+      return *static_cast<Derived*>(this);
+    }
+
+    EIGEN_STRONG_INLINE Scalar value() const
+    { return m_functor(m_xpr.lhs().coeff(IsRowMajor?m_outer:m_rhsIter.index(),IsRowMajor?m_rhsIter.index():m_outer), m_rhsIter.value()); }
+
+    EIGEN_STRONG_INLINE int index() const { return m_rhsIter.index(); }
+    EIGEN_STRONG_INLINE int row() const { return m_rhsIter.row(); }
+    EIGEN_STRONG_INLINE int col() const { return m_rhsIter.col(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_rhsIter; }
+
+  protected:
+    const CwiseBinaryXpr& m_xpr;
+    RhsIterator m_rhsIter;
+    const BinaryFunc& m_functor;
+    const int m_outer;
+};
+
+
+/***************************************************************************
+* Implementation of SparseMatrixBase and SparseCwise functions/operators
+***************************************************************************/
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE const SparseCwiseBinaryOp<ei_scalar_difference_op<typename ei_traits<Derived>::Scalar>,
+                                 Derived, OtherDerived>
+SparseMatrixBase<Derived>::operator-(const SparseMatrixBase<OtherDerived> &other) const
+{
+  return SparseCwiseBinaryOp<ei_scalar_difference_op<Scalar>,
+                       Derived, OtherDerived>(derived(), other.derived());
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+SparseMatrixBase<Derived>::operator-=(const SparseMatrixBase<OtherDerived> &other)
+{
+  return *this = derived() - other.derived();
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE const SparseCwiseBinaryOp<ei_scalar_sum_op<typename ei_traits<Derived>::Scalar>, Derived, OtherDerived>
+SparseMatrixBase<Derived>::operator+(const SparseMatrixBase<OtherDerived> &other) const
+{
+  return SparseCwiseBinaryOp<ei_scalar_sum_op<Scalar>, Derived, OtherDerived>(derived(), other.derived());
+}
+
+template<typename Derived>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE Derived &
+SparseMatrixBase<Derived>::operator+=(const SparseMatrixBase<OtherDerived>& other)
+{
+  return *this = derived() + other.derived();
+}
+
+template<typename ExpressionType>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
+SparseCwise<ExpressionType>::operator*(const SparseMatrixBase<OtherDerived> &other) const
+{
+  return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(_expression(), other.derived());
+}
+
+template<typename ExpressionType>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
+SparseCwise<ExpressionType>::operator*(const MatrixBase<OtherDerived> &other) const
+{
+  return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(_expression(), other.derived());
+}
+
+// template<typename ExpressionType>
+// template<typename OtherDerived>
+// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)
+// SparseCwise<ExpressionType>::operator/(const SparseMatrixBase<OtherDerived> &other) const
+// {
+//   return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)(_expression(), other.derived());
+// }
+//
+// template<typename ExpressionType>
+// template<typename OtherDerived>
+// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)
+// SparseCwise<ExpressionType>::operator/(const MatrixBase<OtherDerived> &other) const
+// {
+//   return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_quotient_op)(_expression(), other.derived());
+// }
+
+template<typename ExpressionType>
+template<typename OtherDerived>
+inline ExpressionType& SparseCwise<ExpressionType>::operator*=(const SparseMatrixBase<OtherDerived> &other)
+{
+  return m_matrix.const_cast_derived() = _expression() * other.derived();
+}
+
+// template<typename ExpressionType>
+// template<typename OtherDerived>
+// inline ExpressionType& SparseCwise<ExpressionType>::operator/=(const SparseMatrixBase<OtherDerived> &other)
+// {
+//   return m_matrix.const_cast_derived() = *this / other;
+// }
+
+template<typename ExpressionType>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)
+SparseCwise<ExpressionType>::min(const SparseMatrixBase<OtherDerived> &other) const
+{
+  return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_min_op)(_expression(), other.derived());
+}
+
+template<typename ExpressionType>
+template<typename OtherDerived>
+EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_max_op)
+SparseCwise<ExpressionType>::max(const SparseMatrixBase<OtherDerived> &other) const
+{
+  return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(ei_scalar_max_op)(_expression(), other.derived());
+}
+
+// template<typename Derived>
+// template<typename CustomBinaryOp, typename OtherDerived>
+// EIGEN_STRONG_INLINE const CwiseBinaryOp<CustomBinaryOp, Derived, OtherDerived>
+// SparseMatrixBase<Derived>::binaryExpr(const SparseMatrixBase<OtherDerived> &other, const CustomBinaryOp& func) const
+// {
+//   return CwiseBinaryOp<CustomBinaryOp, Derived, OtherDerived>(derived(), other.derived(), func);
+// }
+
+#endif // EIGEN_SPARSE_CWISE_BINARY_OP_H

Eigen/src/Sparse/SparseCwiseUnaryOp.h

@@ -0,0 +1,186 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2008 Gael Guennebaud <g.gael@free.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_SPARSE_CWISE_UNARY_OP_H
+#define EIGEN_SPARSE_CWISE_UNARY_OP_H
+
+template<typename UnaryOp, typename MatrixType>
+struct ei_traits<SparseCwiseUnaryOp<UnaryOp, MatrixType> > : ei_traits<MatrixType>
+{
+  typedef typename ei_result_of<
+                     UnaryOp(typename MatrixType::Scalar)
+                   >::type Scalar;
+  typedef typename MatrixType::Nested MatrixTypeNested;
+  typedef typename ei_unref<MatrixTypeNested>::type _MatrixTypeNested;
+  enum {
+    CoeffReadCost = _MatrixTypeNested::CoeffReadCost + ei_functor_traits<UnaryOp>::Cost
+  };
+};
+
+template<typename UnaryOp, typename MatrixType>
+class SparseCwiseUnaryOp : ei_no_assignment_operator,
+  public SparseMatrixBase<SparseCwiseUnaryOp<UnaryOp, MatrixType> >
+{
+  public:
+
+    class InnerIterator;
+//     typedef typename ei_unref<LhsNested>::type _LhsNested;
+
+    EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseCwiseUnaryOp)
+
+    inline SparseCwiseUnaryOp(const MatrixType& mat, const UnaryOp& func = UnaryOp())
+      : m_matrix(mat), m_functor(func) {}
+
+    EIGEN_STRONG_INLINE int rows() const { return m_matrix.rows(); }
+    EIGEN_STRONG_INLINE int cols() const { return m_matrix.cols(); }
+
+//     EIGEN_STRONG_INLINE const typename MatrixType::Nested& _matrix() const { return m_matrix; }
+//     EIGEN_STRONG_INLINE const UnaryOp& _functor() const { return m_functor; }
+
+  protected:
+    const typename MatrixType::Nested m_matrix;
+    const UnaryOp m_functor;
+};
+
+
+template<typename UnaryOp, typename MatrixType>
+class SparseCwiseUnaryOp<UnaryOp,MatrixType>::InnerIterator
+{
+    typedef typename SparseCwiseUnaryOp::Scalar Scalar;
+    typedef typename ei_traits<SparseCwiseUnaryOp>::_MatrixTypeNested _MatrixTypeNested;
+    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const SparseCwiseUnaryOp& unaryOp, int outer)
+      : m_iter(unaryOp.m_matrix,outer), m_functor(unaryOp.m_functor)
+    {}
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    { ++m_iter; return *this; }
+
+    EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_iter.value()); }
+
+    EIGEN_STRONG_INLINE int index() const { return m_iter.index(); }
+    EIGEN_STRONG_INLINE int row() const { return m_iter.row(); }
+    EIGEN_STRONG_INLINE int col() const { return m_iter.col(); }
+
+    EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
+
+  protected:
+    MatrixTypeIterator m_iter;
+    const UnaryOp m_functor;
+
+  private:
+    InnerIterator& operator=(const InnerIterator&);
+};
+
+template<typename Derived>
+template<typename CustomUnaryOp>
+EIGEN_STRONG_INLINE const SparseCwiseUnaryOp<CustomUnaryOp, Derived>
+SparseMatrixBase<Derived>::unaryExpr(const CustomUnaryOp& func) const
+{
+  return SparseCwiseUnaryOp<CustomUnaryOp, Derived>(derived(), func);
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE const SparseCwiseUnaryOp<ei_scalar_opposite_op<typename ei_traits<Derived>::Scalar>,Derived>
+SparseMatrixBase<Derived>::operator-() const
+{
+  return derived();
+}
+
+template<typename ExpressionType>
+EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs_op)
+SparseCwise<ExpressionType>::abs() const
+{
+  return _expression();
+}
+
+template<typename ExpressionType>
+EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_UNOP_RETURN_TYPE(ei_scalar_abs2_op)
+SparseCwise<ExpressionType>::abs2() const
+{
+  return _expression();
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE typename SparseMatrixBase<Derived>::ConjugateReturnType
+SparseMatrixBase<Derived>::conjugate() const
+{
+  return ConjugateReturnType(derived());
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE const typename SparseMatrixBase<Derived>::RealReturnType
+SparseMatrixBase<Derived>::real() const { return derived(); }
+
+template<typename Derived>
+EIGEN_STRONG_INLINE const typename SparseMatrixBase<Derived>::ImagReturnType
+SparseMatrixBase<Derived>::imag() const { return derived(); }
+
+template<typename Derived>
+template<typename NewType>
+EIGEN_STRONG_INLINE const SparseCwiseUnaryOp<ei_scalar_cast_op<typename ei_traits<Derived>::Scalar, NewType>, Derived>
+SparseMatrixBase<Derived>::cast() const
+{
+  return derived();
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE const SparseCwiseUnaryOp<ei_scalar_multiple_op<typename ei_traits<Derived>::Scalar>, Derived>
+SparseMatrixBase<Derived>::operator*(const Scalar& scalar) const
+{
+  return SparseCwiseUnaryOp<ei_scalar_multiple_op<Scalar>, Derived>
+    (derived(), ei_scalar_multiple_op<Scalar>(scalar));
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE const SparseCwiseUnaryOp<ei_scalar_quotient1_op<typename ei_traits<Derived>::Scalar>, Derived>
+SparseMatrixBase<Derived>::operator/(const Scalar& scalar) const
+{
+  return SparseCwiseUnaryOp<ei_scalar_quotient1_op<Scalar>, Derived>
+    (derived(), ei_scalar_quotient1_op<Scalar>(scalar));
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+SparseMatrixBase<Derived>::operator*=(const Scalar& other)
+{
+  for (int j=0; j<outerSize(); ++j)
+    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
+      i.valueRef() *= other;
+  return derived();
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+SparseMatrixBase<Derived>::operator/=(const Scalar& other)
+{
+  for (int j=0; j<outerSize(); ++j)
+    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
+      i.valueRef() /= other;
+  return derived();
+}
+
+#endif // EIGEN_SPARSE_CWISE_UNARY_OP_H