bump to 3.0.1

(transplanted from 9464745385
)

.hgeol

@@ -1,8 +1,3 @@
-[patterns]
-scripts/*.in = LF
-debug/msvc/*.dat = CRLF
-unsupported/test/mpreal/*.* = CRLF
-** = native
-
-[repository]
-native = LF
+[patterns]
+**.* = native
+eigen_autoexp_part.dat = CRLF

CMakeLists.txt

@@ -64,10 +64,6 @@ set(CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake)
 
 find_package(StandardMathLibrary)
 
-
-set(EIGEN_TEST_CUSTOM_LINKER_FLAGS  "" CACHE STRING "Additional linker flags when linking unit tests.")
-set(EIGEN_TEST_CUSTOM_CXX_FLAGS     "" CACHE STRING "Additional compiler flags when compiling unit tests.")
-
 set(EIGEN_STANDARD_LIBRARIES_TO_LINK_TO "")
 
 if(NOT STANDARD_MATH_LIBRARY_FOUND)
@@ -107,8 +103,6 @@ endif()
 
 add_definitions("-DEIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS")
 
-set(EIGEN_TEST_MAX_SIZE "320" CACHE STRING "Maximal matrix/vector size, default is 320")
-
 if(CMAKE_COMPILER_IS_GNUCXX)
   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 -fexceptions -fno-check-new -fno-common -fstrict-aliasing")
   set(CMAKE_CXX_FLAGS_DEBUG "-g3")
@@ -164,7 +158,7 @@ if(CMAKE_COMPILER_IS_GNUCXX)
 
   option(EIGEN_TEST_NEON "Enable/Disable Neon in tests/examples" OFF)
   if(EIGEN_TEST_NEON)
-    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfpu=neon -mcpu=cortex-a8")
+    set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -mfloat-abi=softfp -mfpu=neon -mcpu=cortex-a8")
     message(STATUS "Enabling NEON in tests/examples")
   endif()
 
@@ -285,21 +279,9 @@ install(FILES
   )
 
 if(EIGEN_BUILD_PKGCONFIG)
-    SET(path_separator ":")
-    STRING(REPLACE ${path_separator} ";" pkg_config_libdir_search "$ENV{PKG_CONFIG_LIBDIR}")
-    message(STATUS "searching for 'pkgconfig' directory in PKG_CONFIG_LIBDIR ( $ENV{PKG_CONFIG_LIBDIR} ), ${CMAKE_INSTALL_PREFIX}/share, and ${CMAKE_INSTALL_PREFIX}/lib")
-    FIND_PATH(pkg_config_libdir pkgconfig ${pkg_config_libdir_search} ${CMAKE_INSTALL_PREFIX}/share ${CMAKE_INSTALL_PREFIX}/lib ${pkg_config_libdir_search})
-    if(pkg_config_libdir)
-        SET(pkg_config_install_dir ${pkg_config_libdir})
-        message(STATUS "found ${pkg_config_libdir}/pkgconfig" )
-    else(pkg_config_libdir)
-        SET(pkg_config_install_dir ${CMAKE_INSTALL_PREFIX}/share)
-        message(STATUS "pkgconfig not found; installing in ${pkg_config_install_dir}" )
-    endif(pkg_config_libdir)
-
     configure_file(eigen3.pc.in eigen3.pc)
     install(FILES ${CMAKE_CURRENT_BINARY_DIR}/eigen3.pc
-        DESTINATION ${pkg_config_install_dir}/pkgconfig
+        DESTINATION share/pkgconfig
         )
 endif(EIGEN_BUILD_PKGCONFIG)
 
@@ -307,9 +289,44 @@ add_subdirectory(Eigen)
 
 add_subdirectory(doc EXCLUDE_FROM_ALL)
 
-include(EigenConfigureTesting)
-# fixme, not sure this line is still needed:
+add_custom_target(buildtests)
+add_custom_target(check COMMAND "ctest")
+add_dependencies(check buildtests)
+
+# CMake/Ctest does not allow us to change the build command,
+# so we have to workaround by directly editing the generated DartConfiguration.tcl file
+# save CMAKE_MAKE_PROGRAM
+set(CMAKE_MAKE_PROGRAM_SAVE ${CMAKE_MAKE_PROGRAM})
+# and set a fake one
+set(CMAKE_MAKE_PROGRAM "@EIGEN_MAKECOMMAND_PLACEHOLDER@")
+
+include(CTest)
 enable_testing() # must be called from the root CMakeLists, see man page
+include(EigenTesting)
+ei_init_testing()
+
+# overwrite default DartConfiguration.tcl
+# The worarounds are different for each version of the MSVC IDE
+if(MSVC_IDE)
+  if(MSVC_VERSION EQUAL 1600) # MSVC 2010
+    set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests.vcxproj /p:Configuration=\${CTEST_CONFIGURATION_TYPE} \n # ")
+  else() # MSVC 2008 (TODO check MSVC 2005)
+    set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} /project buildtests")
+  endif()
+else()
+  # for make and nmake
+  set(EIGEN_MAKECOMMAND_PLACEHOLDER "${CMAKE_MAKE_PROGRAM_SAVE} buildtests")
+endif()
+
+configure_file(${CMAKE_BINARY_DIR}/DartConfiguration.tcl ${CMAKE_BINARY_DIR}/DartConfiguration.tcl)
+# restore default CMAKE_MAKE_PROGRAM
+set(CMAKE_MAKE_PROGRAM ${CMAKE_MAKE_PROGRAM_SAVE})
+# un-set temporary variables so that it is like they never existed. 
+# CMake 2.6.3 introduces the more logical unset() syntax for this.
+set(CMAKE_MAKE_PROGRAM_SAVE) 
+set(EIGEN_MAKECOMMAND_PLACEHOLDER)
+
+configure_file(${CMAKE_SOURCE_DIR}/CTestCustom.cmake.in ${CMAKE_BINARY_DIR}/CTestCustom.cmake)
 
 
 if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
@@ -318,13 +335,15 @@ else()
   add_subdirectory(test EXCLUDE_FROM_ALL)
 endif()
 
-if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
-  add_subdirectory(blas)
-  add_subdirectory(lapack)
-else()
-  add_subdirectory(blas EXCLUDE_FROM_ALL)
-  add_subdirectory(lapack EXCLUDE_FROM_ALL)
-endif()
+if(NOT MSVC)
+  if(EIGEN_LEAVE_TEST_IN_ALL_TARGET)
+    add_subdirectory(blas)
+    add_subdirectory(lapack)
+  else()
+    add_subdirectory(blas EXCLUDE_FROM_ALL)
+    add_subdirectory(lapack EXCLUDE_FROM_ALL)
+  endif()
+endif(NOT MSVC)
 
 add_subdirectory(unsupported)
 
@@ -338,13 +357,6 @@ if(EIGEN_BUILD_BTL)
   add_subdirectory(bench/btl EXCLUDE_FROM_ALL)
 endif(EIGEN_BUILD_BTL)
 
-if(TEST_REAL_CASES)
-  if(NOT WIN32)
-    add_subdirectory(bench/spbench EXCLUDE_FROM_ALL)
-    set(ENV(EIGEN_MATRIX_DIR) ${TEST_REAL_CASES})
-  endif(NOT WIN32)
-endif(TEST_REAL_CASES)
-
 ei_testing_print_summary()
 
 message(STATUS "")

COPYING.BSD

@@ -1,26 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-*/

CTestConfig.cmake

@@ -8,6 +8,6 @@ set(CTEST_PROJECT_NAME "Eigen")
 set(CTEST_NIGHTLY_START_TIME "00:00:00 UTC")
 
 set(CTEST_DROP_METHOD "http")
-set(CTEST_DROP_SITE "manao.inria.fr")
+set(CTEST_DROP_SITE "eigen.tuxfamily.org")
 set(CTEST_DROP_LOCATION "/CDash/submit.php?project=Eigen")
 set(CTEST_DROP_SITE_CDASH TRUE)

Eigen/Cholesky

@@ -5,6 +5,8 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
+namespace Eigen {
+
 /** \defgroup Cholesky_Module Cholesky module
   *
   *
@@ -22,9 +24,8 @@
 #include "src/misc/Solve.h"
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
-#ifdef EIGEN_USE_LAPACKE
-#include "src/Cholesky/LLT_MKL.h"
-#endif
+
+} // namespace Eigen
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 

Eigen/CholmodSupport

@@ -1,40 +0,0 @@
-#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H
-#define EIGEN_CHOLMODSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-  #include <cholmod.h>
-}
-
-/** \ingroup Support_modules
-  * \defgroup CholmodSupport_Module CholmodSupport module
-  *
-  * This module provides an interface to the Cholmod library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
-  * It provides the two following main factorization classes:
-  * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
-  * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial).
-  *
-  * For the sake of completeness, this module also propose the two following classes:
-  * - class CholmodSimplicialLLT
-  * - class CholmodSimplicialLDLT
-  * Note that these classes does not bring any particular advantage compared to the built-in
-  * SimplicialLLT and SimplicialLDLT factorization classes.
-  *
-  * \code
-  * #include <Eigen/CholmodSupport>
-  * \endcode
-  */
-
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
-#include "src/CholmodSupport/CholmodSupport.h"
-
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_CHOLMODSUPPORT_MODULE_H
-

Eigen/Core

@@ -34,12 +34,6 @@
 // defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization.
 #include "src/Core/util/Macros.h"
 
-#include <complex>
-
-// this include file manages BLAS and MKL related macros
-// and inclusion of their respective header files
-#include "src/Core/util/MKL_support.h"
-
 // if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into
 // account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks
 #if !EIGEN_ALIGN
@@ -142,7 +136,7 @@
 #endif
 
 // MSVC for windows mobile does not have the errno.h file
-#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
+#if !(defined(_MSC_VER) && defined(_WIN32_WCE))
 #define EIGEN_HAS_ERRNO
 #endif
 
@@ -152,6 +146,7 @@
 #include <cstddef>
 #include <cstdlib>
 #include <cmath>
+#include <complex>
 #include <cassert>
 #include <functional>
 #include <iosfwd>
@@ -172,7 +167,7 @@
   #include <intrin.h>
 #endif
 
-#if defined(_CPPUNWIND) || defined(__EXCEPTIONS)
+#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(EIGEN_NO_EXCEPTIONS)
   #define EIGEN_EXCEPTIONS
 #endif
 
@@ -180,6 +175,16 @@
   #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
+
+// defined in bits/termios.h
+#undef B0
+
 /** \brief Namespace containing all symbols from the %Eigen library. */
 namespace Eigen {
 
@@ -203,8 +208,6 @@ inline static const char *SimdInstructionSetsInUse(void) {
 #endif
 }
 
-} // end namespace Eigen
-
 #define STAGE10_FULL_EIGEN2_API             10
 #define STAGE20_RESOLVE_API_CONFLICTS       20
 #define STAGE30_FULL_EIGEN3_API             30
@@ -251,10 +254,6 @@ using std::ptrdiff_t;
   * \endcode
   */
 
-/** \defgroup Support_modules Support modules [category]
-  * Category of modules which add support for external libraries.
-  */
-
 #include "src/Core/util/Constants.h"
 #include "src/Core/util/ForwardDeclarations.h"
 #include "src/Core/util/Meta.h"
@@ -326,7 +325,7 @@ using std::ptrdiff_t;
 #include "src/Core/CommaInitializer.h"
 #include "src/Core/Flagged.h"
 #include "src/Core/ProductBase.h"
-#include "src/Core/GeneralProduct.h"
+#include "src/Core/Product.h"
 #include "src/Core/TriangularMatrix.h"
 #include "src/Core/SelfAdjointView.h"
 #include "src/Core/SolveTriangular.h"
@@ -355,20 +354,7 @@ using std::ptrdiff_t;
 #include "src/Core/ArrayBase.h"
 #include "src/Core/ArrayWrapper.h"
 
-#ifdef EIGEN_USE_BLAS
-#include "src/Core/products/GeneralMatrixMatrix_MKL.h"
-#include "src/Core/products/GeneralMatrixVector_MKL.h"
-#include "src/Core/products/GeneralMatrixMatrixTriangular_MKL.h"
-#include "src/Core/products/SelfadjointMatrixMatrix_MKL.h"
-#include "src/Core/products/SelfadjointMatrixVector_MKL.h"
-#include "src/Core/products/TriangularMatrixMatrix_MKL.h"
-#include "src/Core/products/TriangularMatrixVector_MKL.h"
-#include "src/Core/products/TriangularSolverMatrix_MKL.h"
-#endif // EIGEN_USE_BLAS
-
-#ifdef EIGEN_USE_MKL_VML
-#include "src/Core/Assign_MKL.h"
-#endif
+} // namespace Eigen
 
 #include "src/Core/GlobalFunctions.h"
 

Eigen/Eigen2Support

@@ -31,8 +31,9 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-/** \ingroup Support_modules
-  * \defgroup Eigen2Support_Module Eigen2 support module
+namespace Eigen {
+
+/** \defgroup Eigen2Support_Module Eigen2 support module
   * This module provides a couple of deprecated functions improving the compatibility with Eigen2.
   *
   * To use it, define EIGEN2_SUPPORT before including any Eigen header
@@ -55,29 +56,13 @@
 #include "src/Eigen2Support/MathFunctions.h"
 
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 // Eigen2 used to include iostream
 #include<iostream>
 
-#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
-using Eigen::Matrix##SizeSuffix##TypeSuffix; \
-using Eigen::Vector##SizeSuffix##TypeSuffix; \
-using Eigen::RowVector##SizeSuffix##TypeSuffix;
-
-#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
-
-#define EIGEN_USING_MATRIX_TYPEDEFS \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \
-EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd)
-
 #define USING_PART_OF_NAMESPACE_EIGEN \
 EIGEN_USING_MATRIX_TYPEDEFS \
 using Eigen::Matrix; \

Eigen/Eigenvalues

@@ -9,7 +9,8 @@
 #include "Jacobi"
 #include "Householder"
 #include "LU"
-#include "Geometry"
+
+namespace Eigen {
 
 /** \defgroup Eigenvalues_Module Eigenvalues module
   *
@@ -34,11 +35,8 @@
 #include "src/Eigenvalues/ComplexSchur.h"
 #include "src/Eigenvalues/ComplexEigenSolver.h"
 #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
-#ifdef EIGEN_USE_LAPACKE
-#include "src/Eigenvalues/RealSchur_MKL.h"
-#include "src/Eigenvalues/ComplexSchur_MKL.h"
-#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h"
-#endif
+
+} // namespace Eigen
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 

Eigen/Geometry

@@ -13,6 +13,8 @@
 #define M_PI 3.14159265358979323846
 #endif
 
+namespace Eigen {
+
 /** \defgroup Geometry_Module Geometry module
   *
   *
@@ -56,6 +58,8 @@
 #include "src/Eigen2Support/Geometry/All.h"
 #endif
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_GEOMETRY_MODULE_H

Eigen/Householder

@@ -5,6 +5,8 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
+namespace Eigen {
+
 /** \defgroup Householder_Module Householder module
   * This module provides Householder transformations.
   *
@@ -17,6 +19,8 @@
 #include "src/Householder/HouseholderSequence.h"
 #include "src/Householder/BlockHouseholder.h"
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_HOUSEHOLDER_MODULE_H

Eigen/IterativeLinearSolvers

@@ -1,40 +0,0 @@
-#ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
-#define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H
-
-#include "SparseCore"
-#include "OrderingMethods"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \ingroup Sparse_modules
-  * \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module
-  *
-  * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse.
-  * Those solvers are accessible via the following classes:
-  *  - ConjugateGradient for selfadjoint (hermitian) matrices,
-  *  - BiCGSTAB for general square matrices.
-  *
-  * These iterative solvers are associated with some preconditioners:
-  *  - IdentityPreconditioner - not really useful
-  *  - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices.
-  *  - IncompleteILUT - incomplete LU factorization with dual thresholding
-  *
-  * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport.
-  *
-  * \code
-  * #include <Eigen/IterativeLinearSolvers>
-  * \endcode
-  */
-
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
-#include "src/IterativeLinearSolvers/IterativeSolverBase.h"
-#include "src/IterativeLinearSolvers/BasicPreconditioners.h"
-#include "src/IterativeLinearSolvers/ConjugateGradient.h"
-#include "src/IterativeLinearSolvers/BiCGSTAB.h"
-#include "src/IterativeLinearSolvers/IncompleteLUT.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H

Eigen/Jacobi

@@ -5,6 +5,8 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
+namespace Eigen {
+
 /** \defgroup Jacobi_Module Jacobi module
   * This module provides Jacobi and Givens rotations.
   *
@@ -19,6 +21,8 @@
 
 #include "src/Jacobi/Jacobi.h"
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_JACOBI_MODULE_H

Eigen/LU

@@ -5,6 +5,8 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
+namespace Eigen {
+
 /** \defgroup LU_Module LU module
   * This module includes %LU decomposition and related notions such as matrix inversion and determinant.
   * This module defines the following MatrixBase methods:
@@ -21,9 +23,6 @@
 #include "src/misc/Image.h"
 #include "src/LU/FullPivLU.h"
 #include "src/LU/PartialPivLU.h"
-#ifdef EIGEN_USE_LAPACKE
-#include "src/LU/PartialPivLU_MKL.h"
-#endif
 #include "src/LU/Determinant.h"
 #include "src/LU/Inverse.h"
 
@@ -35,6 +34,8 @@
   #include "src/Eigen2Support/LU.h"
 #endif
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_LU_MODULE_H

Eigen/LeastSquares

@@ -15,6 +15,8 @@
 #include "Eigenvalues"
 #include "Geometry"
 
+namespace Eigen {
+
 /** \defgroup LeastSquares_Module LeastSquares module
   * This module provides linear regression and related features.
   *
@@ -25,6 +27,8 @@
 
 #include "src/Eigen2Support/LeastSquares.h"
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN2_SUPPORT

Eigen/OrderingMethods

@@ -1,23 +0,0 @@
-#ifndef EIGEN_ORDERINGMETHODS_MODULE_H
-#define EIGEN_ORDERINGMETHODS_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \ingroup Sparse_modules
-  * \defgroup OrderingMethods_Module OrderingMethods module
-  *
-  * This module is currently for internal use only.
-  *
-  *
-  * \code
-  * #include <Eigen/OrderingMethods>
-  * \endcode
-  */
-
-#include "src/OrderingMethods/Amd.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_ORDERINGMETHODS_MODULE_H

Eigen/PaStiXSupport

@@ -1,34 +0,0 @@
-#ifndef EIGEN_PASTIXSUPPORT_MODULE_H
-#define EIGEN_PASTIXSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include <complex.h>
-extern "C" {
-#include <pastix_nompi.h>
-#include <pastix.h>
-}
-
-#ifdef complex
-#undef complex
-#endif
-
-/** \ingroup Support_modules
-  * \defgroup PaStiXSupport_Module PaStiXSupport module
-  *
-  * \code
-  * #include <Eigen/PaStiXSupport>
-  * \endcode
-  */
-
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
-#include "src/PaStiXSupport/PaStiXSupport.h"
-
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_PASTIXSUPPORT_MODULE_H

Eigen/PardisoSupport

@@ -1,26 +0,0 @@
-#ifndef EIGEN_PARDISOSUPPORT_MODULE_H
-#define EIGEN_PARDISOSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include <mkl_pardiso.h>
-
-#include <unsupported/Eigen/SparseExtra>
-
-/** \ingroup Support_modules
-  * \defgroup PardisoSupport_Module PardisoSupport module
-  *
-  * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers
-  *
-  * \code
-  * #include <Eigen/PardisoSupport>
-  * \endcode
-  */
-
-#include "src/PardisoSupport/PardisoSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_PARDISOSUPPORT_MODULE_H

Eigen/QR

@@ -9,6 +9,8 @@
 #include "Jacobi"
 #include "Householder"
 
+namespace Eigen {
+
 /** \defgroup QR_Module QR module
   *
   *
@@ -26,15 +28,13 @@
 #include "src/QR/HouseholderQR.h"
 #include "src/QR/FullPivHouseholderQR.h"
 #include "src/QR/ColPivHouseholderQR.h"
-#ifdef EIGEN_USE_LAPACKE
-#include "src/QR/HouseholderQR_MKL.h"
-#include "src/QR/ColPivHouseholderQR_MKL.h"
-#endif
 
 #ifdef EIGEN2_SUPPORT
 #include "src/Eigen2Support/QR.h"
 #endif
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #ifdef EIGEN2_SUPPORT

Eigen/SVD

@@ -7,13 +7,15 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
+namespace Eigen {
+
 /** \defgroup SVD_Module SVD module
   *
   *
   *
-  * This module provides SVD decomposition for matrices (both real and complex).
+  * This module provides SVD decomposition for (currently) real matrices.
   * This decomposition is accessible via the following MatrixBase method:
-  *  - MatrixBase::jacobiSvd()
+  *  - MatrixBase::svd()
   *
   * \code
   * #include <Eigen/SVD>
@@ -22,15 +24,14 @@
 
 #include "src/misc/Solve.h"
 #include "src/SVD/JacobiSVD.h"
-#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT)
-#include "src/SVD/JacobiSVD_MKL.h"
-#endif
 #include "src/SVD/UpperBidiagonalization.h"
 
 #ifdef EIGEN2_SUPPORT
 #include "src/Eigen2Support/SVD.h"
 #endif
 
+} // namespace Eigen
+
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_SVD_MODULE_H

Eigen/Sparse

@@ -1,23 +1,69 @@
 #ifndef EIGEN_SPARSE_MODULE_H
 #define EIGEN_SPARSE_MODULE_H
 
-/** \defgroup Sparse_modules Sparse modules
+#include "Core"
+
+#include "src/Core/util/DisableStupidWarnings.h"
+
+#include <vector>
+#include <map>
+#include <cstdlib>
+#include <cstring>
+#include <algorithm>
+
+#ifdef EIGEN2_SUPPORT
+#define EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
+#endif
+
+#ifndef EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET
+#error The sparse module API is not stable yet. To use it anyway, please define the EIGEN_YES_I_KNOW_SPARSE_MODULE_IS_NOT_STABLE_YET preprocessor token.
+#endif
+
+namespace Eigen {
+
+/** \defgroup Sparse_Module Sparse module
   *
-  * Meta-module including all related modules:
-  * - SparseCore
-  * - OrderingMethods
-  * - SparseCholesky
-  * - IterativeLinearSolvers
+  *
+  *
+  * See the \ref TutorialSparse "Sparse tutorial"
   *
   * \code
   * #include <Eigen/Sparse>
   * \endcode
   */
 
-#include "SparseCore"
-#include "OrderingMethods"
-#include "SparseCholesky"
-#include "IterativeLinearSolvers"
+/** The type used to identify a general sparse storage. */
+struct Sparse {};
+
+#include "src/Sparse/SparseUtil.h"
+#include "src/Sparse/SparseMatrixBase.h"
+#include "src/Sparse/CompressedStorage.h"
+#include "src/Sparse/AmbiVector.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/SparseBlock.h"
+#include "src/Sparse/SparseTranspose.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/SparseProduct.h"
+#include "src/Sparse/SparseSparseProduct.h"
+#include "src/Sparse/SparseDenseProduct.h"
+#include "src/Sparse/SparseDiagonalProduct.h"
+#include "src/Sparse/SparseTriangularView.h"
+#include "src/Sparse/SparseSelfAdjointView.h"
+#include "src/Sparse/TriangularSolver.h"
+#include "src/Sparse/SparseView.h"
+
+} // namespace Eigen
+
+#include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_SPARSE_MODULE_H
 

Eigen/SparseCholesky

@@ -1,30 +0,0 @@
-#ifndef EIGEN_SPARSECHOLESKY_MODULE_H
-#define EIGEN_SPARSECHOLESKY_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-/** \ingroup Sparse_modules
-  * \defgroup SparseCholesky_Module SparseCholesky module
-  *
-  * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) matrices.
-  * Those decompositions are accessible via the following classes:
-  *  - SimplicialLLt,
-  *  - SimplicialLDLt
-  *
-  * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module.
-  *
-  * \code
-  * #include <Eigen/SparseCholesky>
-  * \endcode
-  */
-
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
-#include "src/SparseCholesky/SimplicialCholesky.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SPARSECHOLESKY_MODULE_H

Eigen/SparseCore

@@ -1,66 +0,0 @@
-#ifndef EIGEN_SPARSECORE_MODULE_H
-#define EIGEN_SPARSECORE_MODULE_H
-
-#include "Core"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#include <vector>
-#include <map>
-#include <cstdlib>
-#include <cstring>
-#include <algorithm>
-
-/** \ingroup Sparse_modules
-  * \defgroup SparseCore_Module SparseCore module
-  *
-  * This module provides a sparse matrix representation, and basic associatd matrix manipulations
-  * and operations.
-  *
-  * See the \ref TutorialSparse "Sparse tutorial"
-  *
-  * \code
-  * #include <Eigen/SparseCore>
-  * \endcode
-  *
-  * This module depends on: Core.
-  */
-
-namespace Eigen {
-
-/** The type used to identify a general sparse storage. */
-struct Sparse {};
-
-}
-
-#include "src/SparseCore/SparseUtil.h"
-#include "src/SparseCore/SparseMatrixBase.h"
-#include "src/SparseCore/CompressedStorage.h"
-#include "src/SparseCore/AmbiVector.h"
-#include "src/SparseCore/SparseMatrix.h"
-#include "src/SparseCore/MappedSparseMatrix.h"
-#include "src/SparseCore/SparseVector.h"
-#include "src/SparseCore/CoreIterators.h"
-#include "src/SparseCore/SparseBlock.h"
-#include "src/SparseCore/SparseTranspose.h"
-#include "src/SparseCore/SparseCwiseUnaryOp.h"
-#include "src/SparseCore/SparseCwiseBinaryOp.h"
-#include "src/SparseCore/SparseDot.h"
-#include "src/SparseCore/SparsePermutation.h"
-#include "src/SparseCore/SparseAssign.h"
-#include "src/SparseCore/SparseRedux.h"
-#include "src/SparseCore/SparseFuzzy.h"
-#include "src/SparseCore/ConservativeSparseSparseProduct.h"
-#include "src/SparseCore/SparseSparseProductWithPruning.h"
-#include "src/SparseCore/SparseProduct.h"
-#include "src/SparseCore/SparseDenseProduct.h"
-#include "src/SparseCore/SparseDiagonalProduct.h"
-#include "src/SparseCore/SparseTriangularView.h"
-#include "src/SparseCore/SparseSelfAdjointView.h"
-#include "src/SparseCore/TriangularSolver.h"
-#include "src/SparseCore/SparseView.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SPARSECORE_MODULE_H
-

Eigen/SuperLUSupport

@@ -1,49 +0,0 @@
-#ifndef EIGEN_SUPERLUSUPPORT_MODULE_H
-#define EIGEN_SUPERLUSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-#ifdef EMPTY
-#define EIGEN_EMPTY_WAS_ALREADY_DEFINED
-#endif
-
-typedef int int_t;
-#include <slu_Cnames.h>
-#include <supermatrix.h>
-#include <slu_util.h>
-
-// slu_util.h defines a preprocessor token named EMPTY which is really polluting,
-// so we remove it in favor of a SUPERLU_EMPTY token.
-// If EMPTY was already defined then we don't undef it.
-
-#if defined(EIGEN_EMPTY_WAS_ALREADY_DEFINED)
-# undef EIGEN_EMPTY_WAS_ALREADY_DEFINED
-#elif defined(EMPTY)
-# undef EMPTY
-#endif
-
-#define SUPERLU_EMPTY (-1)
-
-namespace Eigen { struct SluMatrix; }
-
-/** \ingroup Support_modules
-  * \defgroup SuperLUSupport_Module SuperLUSupport module
-  *
-  * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting.
-  *
-  * \code
-  * #include <Eigen/SuperLUSupport>
-  * \endcode
-  */
-
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
-#include "src/SuperLUSupport/SuperLUSupport.h"
-
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_SUPERLUSUPPORT_MODULE_H

Eigen/UmfPackSupport

@@ -1,30 +0,0 @@
-#ifndef EIGEN_UMFPACKSUPPORT_MODULE_H
-#define EIGEN_UMFPACKSUPPORT_MODULE_H
-
-#include "SparseCore"
-
-#include "src/Core/util/DisableStupidWarnings.h"
-
-extern "C" {
-#include <umfpack.h>
-}
-
-/** \ingroup Support_modules
-  * \defgroup UmfPackSupport_Module UmfPackSupport module
-  *
-  *
-  *
-  *
-  * \code
-  * #include <Eigen/UmfPackSupport>
-  * \endcode
-  */
-
-#include "src/misc/Solve.h"
-#include "src/misc/SparseSolve.h"
-
-#include "src/UmfPackSupport/UmfPackSupport.h"
-
-#include "src/Core/util/ReenableStupidWarnings.h"
-
-#endif // EIGEN_UMFPACKSUPPORT_MODULE_H

Eigen/src/Cholesky/LDLT.h

@@ -1,10 +1,9 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Keir Mierle <mierle@gmail.com>
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2011 Timothy E. Holy <tim.holy@gmail.com >
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -28,21 +27,17 @@
 #ifndef EIGEN_LDLT_H
 #define EIGEN_LDLT_H
 
-namespace Eigen { 
-
 namespace internal {
 template<typename MatrixType, int UpLo> struct LDLT_Traits;
 }
 
-/** \ingroup Cholesky_Module
+/** \ingroup cholesky_Module
   *
   * \class LDLT
   *
   * \brief Robust Cholesky decomposition of a matrix with pivoting
   *
   * \param MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition
-  * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
-  *             The other triangular part won't be read.
   *
   * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite
   * matrix \f$ A \f$ such that \f$ A =  P^TLDL^*P \f$, where P is a permutation matrix, L
@@ -53,10 +48,14 @@ template<typename MatrixType, int UpLo> struct LDLT_Traits;
   * on D also stabilizes the computation.
   *
   * Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky
-  * decomposition to determine whether a system of equations has a solution.
+	* decomposition to determine whether a system of equations has a solution.
   *
   * \sa MatrixBase::ldlt(), class LLT
   */
+ /* THIS PART OF THE DOX IS CURRENTLY DISABLED BECAUSE INACCURATE BECAUSE OF BUG IN THE DECOMPOSITION CODE
+  * Note that during the decomposition, only the upper triangular part of A is considered. Therefore,
+  * the strict lower part does not have to store correct values.
+  */
 template<typename _MatrixType, int _UpLo> class LDLT
 {
   public:
@@ -99,11 +98,6 @@ template<typename _MatrixType, int _UpLo> class LDLT
         m_isInitialized(false)
     {}
 
-    /** \brief Constructor with decomposition
-      *
-      * This calculates the decomposition for the input \a matrix.
-      * \sa LDLT(Index size)
-      */
     LDLT(const MatrixType& matrix)
       : m_matrix(matrix.rows(), matrix.cols()),
         m_transpositions(matrix.rows()),
@@ -113,14 +107,6 @@ template<typename _MatrixType, int _UpLo> class LDLT
       compute(matrix);
     }
 
-    /** Clear any existing decomposition
-     * \sa rankUpdate(w,sigma)
-     */
-    void setZero()
-    {
-      m_isInitialized = false;
-    }
-
     /** \returns a view of the upper triangular matrix U */
     inline typename Traits::MatrixU matrixU() const
     {
@@ -144,14 +130,14 @@ template<typename _MatrixType, int _UpLo> class LDLT
     }
 
     /** \returns the coefficients of the diagonal matrix D */
-    inline Diagonal<const MatrixType> vectorD() const
+    inline Diagonal<const MatrixType> vectorD(void) const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
       return m_matrix.diagonal();
     }
 
     /** \returns true if the matrix is positive (semidefinite) */
-    inline bool isPositive() const
+    inline bool isPositive(void) const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
       return m_sign == 1;
@@ -172,19 +158,10 @@ template<typename _MatrixType, int _UpLo> class LDLT
     }
 
     /** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A.
-      *
-      * This function also supports in-place solves using the syntax <tt>x = decompositionObject.solve(x)</tt> .
       *
       * \note_about_checking_solutions
       *
-      * More precisely, this method solves \f$ A x = b \f$ using the decomposition \f$ A = P^T L D L^* P \f$
-      * by solving the systems \f$ P^T y_1 = b \f$, \f$ L y_2 = y_1 \f$, \f$ D y_3 = y_2 \f$, 
-      * \f$ L^* y_4 = y_3 \f$ and \f$ P x = y_4 \f$ in succession. If the matrix \f$ A \f$ is singular, then
-      * \f$ D \f$ will also be singular (all the other matrices are invertible). In that case, the
-      * least-square solution of \f$ D y_3 = y_2 \f$ is computed. This does not mean that this function
-      * computes the least-square solution of \f$ A x = b \f$ is \f$ A \f$ is singular.
-      *
-      * \sa MatrixBase::ldlt()
+      * \sa solveInPlace(), MatrixBase::ldlt()
       */
     template<typename Rhs>
     inline const internal::solve_retval<LDLT, Rhs>
@@ -210,9 +187,6 @@ template<typename _MatrixType, int _UpLo> class LDLT
 
     LDLT& compute(const MatrixType& matrix);
 
-    template <typename Derived>
-    LDLT& rankUpdate(const MatrixBase<Derived>& w,RealScalar alpha=1);
-
     /** \returns the internal LDLT decomposition matrix
       *
       * TODO: document the storage layout
@@ -228,17 +202,6 @@ template<typename _MatrixType, int _UpLo> class LDLT
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
 
-    /** \brief Reports whether previous computation was successful.
-      *
-      * \returns \c Success if computation was succesful,
-      *          \c NumericalIssue if the matrix.appears to be negative.
-      */
-    ComputationInfo info() const
-    {
-      eigen_assert(m_isInitialized && "LDLT is not initialized.");
-      return Success;
-    }
-
   protected:
 
     /** \internal
@@ -277,7 +240,7 @@ template<> struct ldlt_inplace<Lower>
       return true;
     }
 
-    RealScalar cutoff(0), biggest_in_corner;
+    RealScalar cutoff = 0, biggest_in_corner;
 
     for (Index k = 0; k < size; ++k)
     {
@@ -345,61 +308,6 @@ template<> struct ldlt_inplace<Lower>
 
     return true;
   }
-
-  // Reference for the algorithm: Davis and Hager, "Multiple Rank
-  // Modifications of a Sparse Cholesky Factorization" (Algorithm 1)
-  // Trivial rearrangements of their computations (Timothy E. Holy)
-  // allow their algorithm to work for rank-1 updates even if the
-  // original matrix is not of full rank.
-  // Here only rank-1 updates are implemented, to reduce the
-  // requirement for intermediate storage and improve accuracy
-  template<typename MatrixType, typename WDerived>
-  static bool updateInPlace(MatrixType& mat, MatrixBase<WDerived>& w, typename MatrixType::RealScalar sigma=1)
-  {
-    using internal::isfinite;
-    typedef typename MatrixType::Scalar Scalar;
-    typedef typename MatrixType::RealScalar RealScalar;
-    typedef typename MatrixType::Index Index;
-
-    const Index size = mat.rows();
-    eigen_assert(mat.cols() == size && w.size()==size);
-
-    RealScalar alpha = 1;
-
-    // Apply the update
-    for (Index j = 0; j < size; j++)
-    {
-      // Check for termination due to an original decomposition of low-rank
-      if (!isfinite(alpha))
-        break;
-
-      // Update the diagonal terms
-      RealScalar dj = real(mat.coeff(j,j));
-      Scalar wj = w.coeff(j);
-      RealScalar swj2 = sigma*abs2(wj);
-      RealScalar gamma = dj*alpha + swj2;
-
-      mat.coeffRef(j,j) += swj2/alpha;
-      alpha += swj2/dj;
-
-
-      // Update the terms of L
-      Index rs = size-j-1;
-      w.tail(rs) -= wj * mat.col(j).tail(rs);
-      if(gamma != 0)
-        mat.col(j).tail(rs) += (sigma*conj(wj)/gamma)*w.tail(rs);
-    }
-    return true;
-  }
-
-  template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
-  static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, typename MatrixType::RealScalar sigma=1)
-  {
-    // Apply the permutation to the input w
-    tmp = transpositions * w;
-
-    return ldlt_inplace<Lower>::updateInPlace(mat,tmp,sigma);
-  }
 };
 
 template<> struct ldlt_inplace<Upper>
@@ -410,29 +318,22 @@ template<> struct ldlt_inplace<Upper>
     Transpose<MatrixType> matt(mat);
     return ldlt_inplace<Lower>::unblocked(matt, transpositions, temp, sign);
   }
-
-  template<typename MatrixType, typename TranspositionType, typename Workspace, typename WType>
-  static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, typename MatrixType::RealScalar sigma=1)
-  {
-    Transpose<MatrixType> matt(mat);
-    return ldlt_inplace<Lower>::update(matt, transpositions, tmp, w.conjugate(), sigma);
-  }
 };
 
 template<typename MatrixType> struct LDLT_Traits<MatrixType,Lower>
 {
-  typedef const TriangularView<const MatrixType, UnitLower> MatrixL;
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m; }
-  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  typedef TriangularView<MatrixType, UnitLower> MatrixL;
+  typedef TriangularView<typename MatrixType::AdjointReturnType, UnitUpper> MatrixU;
+  inline static MatrixL getL(const MatrixType& m) { return m; }
+  inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
 };
 
 template<typename MatrixType> struct LDLT_Traits<MatrixType,Upper>
 {
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
-  typedef const TriangularView<const MatrixType, UnitUpper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
-  static inline MatrixU getU(const MatrixType& m) { return m; }
+  typedef TriangularView<typename MatrixType::AdjointReturnType, UnitLower> MatrixL;
+  typedef TriangularView<MatrixType, UnitUpper> MatrixU;
+  inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
+  inline static MatrixU getU(const MatrixType& m) { return m; }
 };
 
 } // end namespace internal
@@ -457,37 +358,6 @@ LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::compute(const MatrixType& a)
   return *this;
 }
 
-/** Update the LDLT decomposition:  given A = L D L^T, efficiently compute the decomposition of A + sigma w w^T.
- * \param w a vector to be incorporated into the decomposition.
- * \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column vectors. Optional; default value is +1.
- * \sa setZero()
-  */
-template<typename MatrixType, int _UpLo>
-template<typename Derived>
-LDLT<MatrixType,_UpLo>& LDLT<MatrixType,_UpLo>::rankUpdate(const MatrixBase<Derived>& w,typename NumTraits<typename MatrixType::Scalar>::Real sigma)
-{
-  const Index size = w.rows();
-  if (m_isInitialized)
-  {
-    eigen_assert(m_matrix.rows()==size);
-  }
-  else
-  {    
-    m_matrix.resize(size,size);
-    m_matrix.setZero();
-    m_transpositions.resize(size);
-    for (Index i = 0; i < size; i++)
-      m_transpositions.coeffRef(i) = i;
-    m_temporary.resize(size);
-    m_sign = sigma;
-    m_isInitialized = true;
-  }
-
-  internal::ldlt_inplace<UpLo>::update(m_matrix, m_transpositions, m_temporary, w, sigma);
-
-  return *this;
-}
-
 namespace internal {
 template<typename _MatrixType, int _UpLo, typename Rhs>
 struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
@@ -506,21 +376,7 @@ struct solve_retval<LDLT<_MatrixType,_UpLo>, Rhs>
     dec().matrixL().solveInPlace(dst);
 
     // dst = D^-1 (L^-1 P b)
-    // more precisely, use pseudo-inverse of D (see bug 241)
-    using std::abs;
-    using std::max;
-    typedef typename LDLTType::MatrixType MatrixType;
-    typedef typename LDLTType::Scalar Scalar;
-    typedef typename LDLTType::RealScalar RealScalar;
-    const Diagonal<const MatrixType> vectorD = dec().vectorD();
-    RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() * NumTraits<Scalar>::epsilon(),
-				 RealScalar(1) / NumTraits<RealScalar>::highest()); // motivated by LAPACK's xGELSS
-    for (Index i = 0; i < vectorD.size(); ++i) {
-      if(abs(vectorD(i)) > tolerance)
-	dst.row(i) /= vectorD(i);
-      else
-	dst.row(i).setZero();
-    }
+    dst = dec().vectorD().asDiagonal().inverse() * dst;
 
     // dst = L^-T (D^-1 L^-1 P b)
     dec().matrixU().solveInPlace(dst);
@@ -602,6 +458,4 @@ MatrixBase<Derived>::ldlt() const
   return LDLT<PlainObject>(derived());
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_LDLT_H

Eigen/src/Cholesky/LLT.h

@@ -25,21 +25,17 @@
 #ifndef EIGEN_LLT_H
 #define EIGEN_LLT_H
 
-namespace Eigen { 
-
 namespace internal{
 template<typename MatrixType, int UpLo> struct LLT_Traits;
 }
 
-/** \ingroup Cholesky_Module
+/** \ingroup cholesky_Module
   *
   * \class LLT
   *
   * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features
   *
   * \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition
-  * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper.
-  *             The other triangular part won't be read.
   *
   * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite
   * matrix A such that A = LL^* = U^*U, where L is lower triangular.
@@ -53,9 +49,6 @@ template<typename MatrixType, int UpLo> struct LLT_Traits;
   * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations
   * has a solution.
   *
-  * Example: \include LLT_example.cpp
-  * Output: \verbinclude LLT_example.out
-  *    
   * \sa MatrixBase::llt(), class LDLT
   */
  /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH)
@@ -185,9 +178,6 @@ template<typename _MatrixType, int _UpLo> class LLT
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
 
-    template<typename VectorType>
-    LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
-
   protected:
     /** \internal
       * Used to compute and store L
@@ -200,85 +190,16 @@ template<typename _MatrixType, int _UpLo> class LLT
 
 namespace internal {
 
-template<typename Scalar, int UpLo> struct llt_inplace;
+template<int UpLo> struct llt_inplace;
 
-template<typename MatrixType, typename VectorType>
-static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma)
+template<> struct llt_inplace<Lower>
 {
-  typedef typename MatrixType::Scalar Scalar;
-  typedef typename MatrixType::RealScalar RealScalar;
-  typedef typename MatrixType::Index Index;
-  typedef typename MatrixType::ColXpr ColXpr;
-  typedef typename internal::remove_all<ColXpr>::type ColXprCleaned;
-  typedef typename ColXprCleaned::SegmentReturnType ColXprSegment;
-  typedef Matrix<Scalar,Dynamic,1> TempVectorType;
-  typedef typename TempVectorType::SegmentReturnType TempVecSegment;
-
-  int n = mat.cols();
-  eigen_assert(mat.rows()==n && vec.size()==n);
-
-  TempVectorType temp;
-
-  if(sigma>0)
-  {
-    // This version is based on Givens rotations.
-    // It is faster than the other one below, but only works for updates,
-    // i.e., for sigma > 0
-    temp = sqrt(sigma) * vec;
-
-    for(int i=0; i<n; ++i)
-    {
-      JacobiRotation<Scalar> g;
-      g.makeGivens(mat(i,i), -temp(i), &mat(i,i));
-
-      int rs = n-i-1;
-      if(rs>0)
-      {
-        ColXprSegment x(mat.col(i).tail(rs));
-        TempVecSegment y(temp.tail(rs));
-        apply_rotation_in_the_plane(x, y, g);
-      }
-    }
-  }
-  else
-  {
-    temp = vec;
-    RealScalar beta = 1;
-    for(int j=0; j<n; ++j)
-    {
-      RealScalar Ljj = real(mat.coeff(j,j));
-      RealScalar dj = abs2(Ljj);
-      Scalar wj = temp.coeff(j);
-      RealScalar swj2 = sigma*abs2(wj);
-      RealScalar gamma = dj*beta + swj2;
-
-      RealScalar x = dj + swj2/beta;
-      if (x<=RealScalar(0))
-        return j;
-      RealScalar nLjj = sqrt(x);
-      mat.coeffRef(j,j) = nLjj;
-      beta += swj2/dj;
-
-      // Update the terms of L
-      Index rs = n-j-1;
-      if(rs)
-      {
-        temp.tail(rs) -= (wj/Ljj) * mat.col(j).tail(rs);
-        if(gamma != 0)
-          mat.col(j).tail(rs) = (nLjj/Ljj) * mat.col(j).tail(rs) + (nLjj * sigma*conj(wj)/gamma)*temp.tail(rs);
-      }
-    }
-  }
-  return -1;
-}
-
-template<typename Scalar> struct llt_inplace<Scalar, Lower>
-{
-  typedef typename NumTraits<Scalar>::Real RealScalar;
   template<typename MatrixType>
   static typename MatrixType::Index unblocked(MatrixType& mat)
   {
     typedef typename MatrixType::Index Index;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
     
     eigen_assert(mat.rows()==mat.cols());
     const Index size = mat.rows();
@@ -312,7 +233,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
 
     Index blockSize = size/8;
     blockSize = (blockSize/16)*16;
-    blockSize = (std::min)((std::max)(blockSize,Index(8)), Index(128));
+    blockSize = std::min(std::max(blockSize,Index(8)), Index(128));
 
     for (Index k=0; k<size; k+=blockSize)
     {
@@ -320,7 +241,7 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
       //       A00 |  -  |  -
       // lu  = A10 | A11 |  -
       //       A20 | A21 | A22
-      Index bs = (std::min)(blockSize, size-k);
+      Index bs = std::min(blockSize, size-k);
       Index rs = size - k - bs;
       Block<MatrixType,Dynamic,Dynamic> A11(m,k,   k,   bs,bs);
       Block<MatrixType,Dynamic,Dynamic> A21(m,k+bs,k,   rs,bs);
@@ -333,71 +254,55 @@ template<typename Scalar> struct llt_inplace<Scalar, Lower>
     }
     return -1;
   }
-
-  template<typename MatrixType, typename VectorType>
-  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
-  {
-    return Eigen::internal::llt_rank_update_lower(mat, vec, sigma);
-  }
 };
-  
-template<typename Scalar> struct llt_inplace<Scalar, Upper>
-{
-  typedef typename NumTraits<Scalar>::Real RealScalar;
 
+template<> struct llt_inplace<Upper>
+{
   template<typename MatrixType>
   static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat)
   {
     Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::unblocked(matt);
+    return llt_inplace<Lower>::unblocked(matt);
   }
   template<typename MatrixType>
   static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat)
   {
     Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::blocked(matt);
-  }
-  template<typename MatrixType, typename VectorType>
-  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma)
-  {
-    Transpose<MatrixType> matt(mat);
-    return llt_inplace<Scalar, Lower>::rankUpdate(matt, vec.conjugate(), sigma);
+    return llt_inplace<Lower>::blocked(matt);
   }
 };
 
 template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
 {
-  typedef const TriangularView<const MatrixType, Lower> MatrixL;
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m; }
-  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  typedef TriangularView<MatrixType, Lower> MatrixL;
+  typedef TriangularView<typename MatrixType::AdjointReturnType, Upper> MatrixU;
+  inline static MatrixL getL(const MatrixType& m) { return m; }
+  inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
   static bool inplace_decomposition(MatrixType& m)
-  { return llt_inplace<typename MatrixType::Scalar, Lower>::blocked(m)==-1; }
+  { return llt_inplace<Lower>::blocked(m)==-1; }
 };
 
 template<typename MatrixType> struct LLT_Traits<MatrixType,Upper>
 {
-  typedef const TriangularView<const typename MatrixType::AdjointReturnType, Lower> MatrixL;
-  typedef const TriangularView<const MatrixType, Upper> MatrixU;
-  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
-  static inline MatrixU getU(const MatrixType& m) { return m; }
+  typedef TriangularView<typename MatrixType::AdjointReturnType, Lower> MatrixL;
+  typedef TriangularView<MatrixType, Upper> MatrixU;
+  inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
+  inline static MatrixU getU(const MatrixType& m) { return m; }
   static bool inplace_decomposition(MatrixType& m)
-  { return llt_inplace<typename MatrixType::Scalar, Upper>::blocked(m)==-1; }
+  { return llt_inplace<Upper>::blocked(m)==-1; }
 };
 
 } // end namespace internal
 
 /** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix
   *
-  * \returns a reference to *this
   *
-  * Example: \include TutorialLinAlgComputeTwice.cpp
-  * Output: \verbinclude TutorialLinAlgComputeTwice.out
+  * \returns a reference to *this
   */
 template<typename MatrixType, int _UpLo>
 LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
 {
-  eigen_assert(a.rows()==a.cols());
+  assert(a.rows()==a.cols());
   const Index size = a.rows();
   m_matrix.resize(size, size);
   m_matrix = a;
@@ -409,26 +314,6 @@ LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
   return *this;
 }
 
-/** Performs a rank one update (or dowdate) of the current decomposition.
-  * If A = LL^* before the rank one update,
-  * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector
-  * of same dimension.
-  */
-template<typename _MatrixType, int _UpLo>
-template<typename VectorType>
-LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType);
-  eigen_assert(v.size()==m_matrix.cols());
-  eigen_assert(m_isInitialized);
-  if(internal::llt_inplace<typename MatrixType::Scalar, UpLo>::rankUpdate(m_matrix,v,sigma)>=0)
-    m_info = NumericalIssue;
-  else
-    m_info = Success;
-
-  return *this;
-}
-    
 namespace internal {
 template<typename _MatrixType, int UpLo, typename Rhs>
 struct solve_retval<LLT<_MatrixType, UpLo>, Rhs>
@@ -498,6 +383,4 @@ SelfAdjointView<MatrixType, UpLo>::llt() const
   return LLT<PlainObject,UpLo>(m_matrix);
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_LLT_H

Eigen/src/Cholesky/LLT_MKL.h

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

Eigen/src/CholmodSupport/CMakeLists.txt

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

Eigen/src/Core/Array.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_ARRAY_H
 #define EIGEN_ARRAY_H
 
-namespace Eigen {
-
 /** \class Array 
   * \ingroup Core_Module
   *
@@ -70,8 +68,10 @@ class Array
     friend struct internal::conservative_resize_like_impl;
 
     using Base::m_storage;
-
   public:
+    enum { NeedsToAlign = (!(Options&DontAlign))
+                          && SizeAtCompileTime!=Dynamic && ((static_cast<int>(sizeof(Scalar))*SizeAtCompileTime)%16)==0 };
+    EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
 
     using Base::base;
     using Base::coeff;
@@ -318,6 +318,5 @@ EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \
 EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \
 EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd)
 
-} // end namespace Eigen
 
 #endif // EIGEN_ARRAY_H

Eigen/src/Core/ArrayBase.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_ARRAYBASE_H
 #define EIGEN_ARRAYBASE_H
 
-namespace Eigen { 
-
 template<typename ExpressionType> class MatrixWrapper;
 
 /** \class ArrayBase
@@ -161,7 +159,7 @@ template<typename Derived> class ArrayBase
     /** \returns an \link MatrixBase Matrix \endlink expression of this array
       * \sa MatrixBase::array() */
     MatrixWrapper<Derived> matrix() { return derived(); }
-    const MatrixWrapper<const Derived> matrix() const { return derived(); }
+    const MatrixWrapper<Derived> matrix() const { return derived(); }
 
 //     template<typename Dest>
 //     inline void evalTo(Dest& dst) const { dst = matrix(); }
@@ -176,10 +174,10 @@ template<typename Derived> class ArrayBase
   protected:
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator+=(const MatrixBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
+    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator-=(const MatrixBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
+    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
 };
 
 /** replaces \c *this by \c *this - \a other.
@@ -238,6 +236,4 @@ ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_ARRAYBASE_H

Eigen/src/Core/ArrayWrapper.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_ARRAYWRAPPER_H
 #define EIGEN_ARRAYWRAPPER_H
 
-namespace Eigen { 
-
 /** \class ArrayWrapper
   * \ingroup Core_Module
   *
@@ -63,7 +61,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
 
     typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
 
-    inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
+    inline ArrayWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
 
     inline Index rows() const { return m_expression.rows(); }
     inline Index cols() const { return m_expression.cols(); }
@@ -73,7 +71,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline CoeffReturnType coeff(Index row, Index col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
@@ -88,7 +86,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline CoeffReturnType coeff(Index index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
@@ -130,14 +128,8 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     template<typename Dest>
     inline void evalTo(Dest& dst) const { dst = m_expression; }
 
-    const typename internal::remove_all<NestedExpressionType>::type& 
-    nestedExpression() const 
-    {
-      return m_expression;
-    }
-
   protected:
-    NestedExpressionType m_expression;
+    const NestedExpressionType m_expression;
 };
 
 /** \class MatrixWrapper
@@ -176,7 +168,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
 
     typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
 
-    inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
+    inline MatrixWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
 
     inline Index rows() const { return m_expression.rows(); }
     inline Index cols() const { return m_expression.cols(); }
@@ -186,7 +178,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline CoeffReturnType coeff(Index row, Index col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
@@ -201,7 +193,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
       return m_expression.derived().coeffRef(row, col);
     }
 
-    inline CoeffReturnType coeff(Index index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
@@ -240,16 +232,8 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
       m_expression.const_cast_derived().template writePacket<LoadMode>(index, x);
     }
 
-    const typename internal::remove_all<NestedExpressionType>::type& 
-    nestedExpression() const 
-    {
-      return m_expression;
-    }
-
   protected:
-    NestedExpressionType m_expression;
+    const NestedExpressionType m_expression;
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_ARRAYWRAPPER_H

Eigen/src/Core/Assign.h

@@ -27,8 +27,6 @@
 #ifndef EIGEN_ASSIGN_H
 #define EIGEN_ASSIGN_H
 
-namespace Eigen {
-
 namespace internal {
 
 /***************************************************************************
@@ -154,7 +152,7 @@ struct assign_DefaultTraversal_CompleteUnrolling
     inner = Index % Derived1::InnerSizeAtCompileTime
   };
 
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     dst.copyCoeffByOuterInner(outer, inner, src);
     assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
@@ -164,13 +162,13 @@ struct assign_DefaultTraversal_CompleteUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
+  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, int Index, int Stop>
 struct assign_DefaultTraversal_InnerUnrolling
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, int outer)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int outer)
   {
     dst.copyCoeffByOuterInner(outer, Index, src);
     assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, outer);
@@ -180,7 +178,7 @@ struct assign_DefaultTraversal_InnerUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, int) {}
+  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
 };
 
 /***********************
@@ -190,7 +188,7 @@ struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 template<typename Derived1, typename Derived2, int Index, int Stop>
 struct assign_LinearTraversal_CompleteUnrolling
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     dst.copyCoeff(Index, src);
     assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
@@ -200,7 +198,7 @@ struct assign_LinearTraversal_CompleteUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
+  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
 };
 
 /**************************
@@ -216,7 +214,7 @@ struct assign_innervec_CompleteUnrolling
     JointAlignment = assign_traits<Derived1,Derived2>::JointAlignment
   };
 
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     dst.template copyPacketByOuterInner<Derived2, Aligned, JointAlignment>(outer, inner, src);
     assign_innervec_CompleteUnrolling<Derived1, Derived2,
@@ -227,13 +225,13 @@ struct assign_innervec_CompleteUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
+  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, int Index, int Stop>
 struct assign_innervec_InnerUnrolling
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, int outer)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int outer)
   {
     dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, Index, src);
     assign_innervec_InnerUnrolling<Derived1, Derived2,
@@ -244,7 +242,7 @@ struct assign_innervec_InnerUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, int) {}
+  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
 };
 
 /***************************************************************************
@@ -253,25 +251,24 @@ struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 
 template<typename Derived1, typename Derived2,
          int Traversal = assign_traits<Derived1, Derived2>::Traversal,
-         int Unrolling = assign_traits<Derived1, Derived2>::Unrolling,
-         int Version = Specialized>
+         int Unrolling = assign_traits<Derived1, Derived2>::Unrolling>
 struct assign_impl;
 
 /************************
 *** Default traversal ***
 ************************/
 
-template<typename Derived1, typename Derived2, int Unrolling, int Version>
-struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling, Version>
+template<typename Derived1, typename Derived2, int Unrolling>
+struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling>
 {
-  static inline void run(Derived1 &, const Derived2 &) { }
+  inline static void run(Derived1 &, const Derived2 &) { }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     const Index innerSize = dst.innerSize();
     const Index outerSize = dst.outerSize();
@@ -281,21 +278,21 @@ struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
   }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
   }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     const Index outerSize = dst.outerSize();
     for(Index outer = 0; outer < outerSize; ++outer)
@@ -308,11 +305,11 @@ struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version
 *** Linear traversal ***
 ***********************/
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     const Index size = dst.size();
     for(Index i = 0; i < size; ++i)
@@ -320,10 +317,10 @@ struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
   }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
@@ -334,11 +331,11 @@ struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Versi
 *** Inner vectorization ***
 **************************/
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     const Index innerSize = dst.innerSize();
     const Index outerSize = dst.outerSize();
@@ -349,21 +346,21 @@ struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Ve
   }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling>
 {
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
   }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     const Index outerSize = dst.outerSize();
     for(Index outer = 0; outer < outerSize; ++outer)
@@ -401,11 +398,11 @@ struct unaligned_assign_impl<false>
   }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     const Index size = dst.size();
     typedef packet_traits<typename Derived1::Scalar> PacketTraits;
@@ -415,7 +412,7 @@ struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, V
       srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
     };
     const Index alignedStart = assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                             : internal::first_aligned(&dst.coeffRef(0), size);
+                             : first_aligned(&dst.coeffRef(0), size);
     const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
 
     unaligned_assign_impl<assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
@@ -429,11 +426,11 @@ struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, V
   }
 };
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
+  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
   {
     enum { size = Derived1::SizeAtCompileTime,
            packetSize = packet_traits<typename Derived1::Scalar>::size,
@@ -448,11 +445,11 @@ struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnroll
 *** Slice vectorization ***
 ***************************/
 
-template<typename Derived1, typename Derived2, int Version>
-struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Version>
+template<typename Derived1, typename Derived2>
+struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     typedef packet_traits<typename Derived1::Scalar> PacketTraits;
     enum {
@@ -466,7 +463,7 @@ struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Ve
     const Index outerSize = dst.outerSize();
     const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
     Index alignedStart = ((!alignable) || assign_traits<Derived1,Derived2>::DstIsAligned) ? 0
-                       : internal::first_aligned(&dst.coeffRef(0,0), innerSize);
+                       : first_aligned(&dst.coeffRef(0,0), innerSize);
 
     for(Index outer = 0; outer < outerSize; ++outer)
     {
@@ -534,19 +531,19 @@ struct assign_selector;
 
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,false,false> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
+  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
 };
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,true,false> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
+  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
 };
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,false,true> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
+  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
 };
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,true,true> {
-  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
+  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
 };
 
 } // end namespace internal
@@ -593,6 +590,4 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_ASSIGN_H

Eigen/src/Core/Assign_MKL.h

@@ -1,221 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   MKL VML support for coefficient-wise unary Eigen expressions like a=b.sin()
- ********************************************************************************
-*/
-
-#ifndef EIGEN_ASSIGN_VML_H
-#define EIGEN_ASSIGN_VML_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template<typename Op> struct vml_call
-{ enum { IsSupported = 0 }; };
-
-template<typename Dst, typename Src, typename UnaryOp>
-class vml_assign_traits
-{
-  private:
-    enum {
-      DstHasDirectAccess = Dst::Flags & DirectAccessBit,
-      SrcHasDirectAccess = Src::Flags & DirectAccessBit,
-
-      StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)),
-      InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime)
-                : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime)
-                : int(Dst::RowsAtCompileTime),
-      InnerMaxSize  = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime)
-                    : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime)
-                    : int(Dst::MaxRowsAtCompileTime),
-      MaxSizeAtCompileTime = Dst::SizeAtCompileTime,
-
-      MightEnableVml =  vml_call<UnaryOp>::IsSupported && StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess
-                     && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1,
-      MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit),
-      VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize,
-      LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD,
-      MayEnableVml = MightEnableVml && LargeEnough,
-      MayLinearize = MayEnableVml && MightLinearize
-    };
-  public:
-    enum {
-      Traversal = MayLinearize ? LinearVectorizedTraversal
-                : MayEnableVml ? InnerVectorizedTraversal
-                : DefaultTraversal
-    };
-};
-
-template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling,
-         int VmlTraversal = vml_assign_traits<Derived1, Derived2, UnaryOp>::Traversal >
-struct vml_assign_impl
-  : assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>
-{
-};
-
-template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
-struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, InnerVectorizedTraversal>
-{
-  typedef typename Derived1::Scalar Scalar;
-  typedef typename Derived1::Index Index;
-  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
-  {
-    // in case we want to (or have to) skip VML at runtime we can call:
-    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
-    const Index innerSize = dst.innerSize();
-    const Index outerSize = dst.outerSize();
-    for(Index outer = 0; outer < outerSize; ++outer) {
-      const Scalar *src_ptr = src.IsRowMajor ?  &(src.nestedExpression().coeffRef(outer,0)) :
-                                                &(src.nestedExpression().coeffRef(0, outer));
-      Scalar *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer));
-      vml_call<UnaryOp>::run(src.functor(), innerSize, src_ptr, dst_ptr );
-    }
-  }
-};
-
-template<typename Derived1, typename Derived2, typename UnaryOp, int Traversal, int Unrolling>
-struct vml_assign_impl<Derived1, Derived2, UnaryOp, Traversal, Unrolling, LinearVectorizedTraversal>
-{
-  static inline void run(Derived1& dst, const CwiseUnaryOp<UnaryOp, Derived2>& src)
-  {
-    // in case we want to (or have to) skip VML at runtime we can call:
-    // assign_impl<Derived1,Eigen::CwiseUnaryOp<UnaryOp, Derived2>,Traversal,Unrolling,BuiltIn>::run(dst,src);
-    vml_call<UnaryOp>::run(src.functor(), dst.size(), src.nestedExpression().data(), dst.data() );
-  }
-};
-
-// Macroses
-
-#define EIGEN_MKL_VML_SPECIALIZE_ASSIGN(TRAVERSAL,UNROLLING) \
-  template<typename Derived1, typename Derived2, typename UnaryOp> \
-  struct assign_impl<Derived1, Eigen::CwiseUnaryOp<UnaryOp, Derived2>, TRAVERSAL, UNROLLING, Specialized>  {  \
-    static inline void run(Derived1 &dst, const Eigen::CwiseUnaryOp<UnaryOp, Derived2> &src) { \
-      vml_assign_impl<Derived1,Derived2,UnaryOp,TRAVERSAL,UNROLLING>::run(dst, src); \
-    } \
-  };
-
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,InnerUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,InnerUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,CompleteUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,NoUnrolling)
-EIGEN_MKL_VML_SPECIALIZE_ASSIGN(SliceVectorizedTraversal,NoUnrolling)
-
-
-#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1)
-#define  EIGEN_MKL_VML_MODE VML_HA
-#else
-#define  EIGEN_MKL_VML_MODE VML_LA
-#endif
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)     \
-  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
-    enum { IsSupported = 1 };                                                    \
-    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
-                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
-      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst);                           \
-    }                                                                            \
-  };
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)  \
-  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
-    enum { IsSupported = 1 };                                                    \
-    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& /*func*/,        \
-                            int size, const EIGENTYPE* src, EIGENTYPE* dst) {    \
-      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
-      VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst, vmlMode);                  \
-    }                                                                            \
-  };
-
-#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE)       \
-  template<> struct vml_call< scalar_##EIGENOP##_op<EIGENTYPE> > {               \
-    enum { IsSupported = 1 };                                                    \
-    static inline void run( const scalar_##EIGENOP##_op<EIGENTYPE>& func,        \
-                          int size, const EIGENTYPE* src, EIGENTYPE* dst) {      \
-      EIGENTYPE exponent = func.m_exponent;                                      \
-      MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE;                                    \
-      VMLOP(&size, (const VMLTYPE*)src, (const VMLTYPE*)&exponent,               \
-                        (VMLTYPE*)dst, &vmlMode);                                \
-    }                                                                            \
-  };
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                   \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vs##VMLOP, float, float)             \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vd##VMLOP, double, double)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)                \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vc##VMLOP, scomplex, MKL_Complex8)   \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vz##VMLOP, dcomplex, MKL_Complex16)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP)                        \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP)                         \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP)
-
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vms##VMLOP, float, float)         \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmd##VMLOP, double, double)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)             \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmc##VMLOP, scomplex, MKL_Complex8)  \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmz##VMLOP, dcomplex, MKL_Complex16)
-
-#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(EIGENOP, VMLOP)                     \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP)                      \
-  EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP)
-
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sin,  Sin)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos,  Cos)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan,  Tan)
-//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs,  Abs)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp,  Exp)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log,  Ln)
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sqrt, Sqrt)
-
-EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr)
-
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8)
-EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16)
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_ASSIGN_VML_H

Eigen/src/Core/BandMatrix.h

@@ -25,10 +25,9 @@
 #ifndef EIGEN_BANDMATRIX_H
 #define EIGEN_BANDMATRIX_H
 
-namespace Eigen { 
-
 namespace internal {
 
+
 template<typename Derived>
 class BandMatrixBase : public EigenBase<Derived>
 {
@@ -88,7 +87,7 @@ class BandMatrixBase : public EigenBase<Derived>
       if (i<=supers())
       {
         start = supers()-i;
-        len = (std::min)(rows(),std::max<Index>(0,coeffs().rows() - (supers()-i)));
+        len = std::min(rows(),std::max<Index>(0,coeffs().rows() - (supers()-i)));
       }
       else if (i>=rows()-subs())
         len = std::max<Index>(0,coeffs().rows() - (i + 1 - rows() + subs()));
@@ -97,11 +96,11 @@ class BandMatrixBase : public EigenBase<Derived>
 
     /** \returns a vector expression of the main diagonal */
     inline Block<CoefficientsType,1,SizeAtCompileTime> diagonal()
-    { return Block<CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
+    { return Block<CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,std::min(rows(),cols())); }
 
     /** \returns a vector expression of the main diagonal (const version) */
     inline const Block<const CoefficientsType,1,SizeAtCompileTime> diagonal() const
-    { return Block<const CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,(std::min)(rows(),cols())); }
+    { return Block<const CoefficientsType,1,SizeAtCompileTime>(coeffs(),supers(),0,1,std::min(rows(),cols())); }
 
     template<int Index> struct DiagonalIntReturnType {
       enum {
@@ -123,13 +122,13 @@ class BandMatrixBase : public EigenBase<Derived>
     /** \returns a vector expression of the \a N -th sub or super diagonal */
     template<int N> inline typename DiagonalIntReturnType<N>::Type diagonal()
     {
-      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
+      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, std::max(0,N), 1, diagonalLength(N));
     }
 
     /** \returns a vector expression of the \a N -th sub or super diagonal */
     template<int N> inline const typename DiagonalIntReturnType<N>::Type diagonal() const
     {
-      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N));
+      return typename DiagonalIntReturnType<N>::BuildType(coeffs(), supers()-N, std::max(0,N), 1, diagonalLength(N));
     }
 
     /** \returns a vector expression of the \a i -th sub or super diagonal */
@@ -167,7 +166,7 @@ class BandMatrixBase : public EigenBase<Derived>
   protected:
 
     inline Index diagonalLength(Index i) const
-    { return i<0 ? (std::min)(cols(),rows()+i) : (std::min)(rows(),cols()-i); }
+    { return i<0 ? std::min(cols(),rows()+i) : std::min(rows(),cols()-i); }
 };
 
 /**
@@ -285,7 +284,6 @@ class BandMatrixWrapper : public BandMatrixBase<BandMatrixWrapper<_CoefficientsT
       : m_coeffs(coeffs),
         m_rows(rows), m_supers(supers), m_subs(subs)
     {
-      EIGEN_UNUSED_VARIABLE(cols);
       //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows());
     }
 
@@ -344,6 +342,4 @@ class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_BANDMATRIX_H

Eigen/src/Core/Block.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_BLOCK_H
 #define EIGEN_BLOCK_H
 
-namespace Eigen { 
-
 /** \class Block
   * \ingroup Core_Module
   *
@@ -96,7 +94,7 @@ struct traits<Block<XprType, BlockRows, BlockCols, InnerPanel, HasDirectAccess>
     MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits<Scalar>::size) == 0)
                        && (InnerStrideAtCompileTime == 1)
                         ? PacketAccessBit : 0,
-    MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) == 0)) ? AlignedBit : 0,
+    MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && ((OuterStrideAtCompileTime % packet_traits<Scalar>::size) == 0)) ? AlignedBit : 0,
     FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1) ? LinearAccessBit : 0,
     FlagsLvalueBit = is_lvalue<XprType>::value ? LvalueBit : 0,
     FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0,
@@ -244,21 +242,6 @@ template<typename XprType, int BlockRows, int BlockCols, bool InnerPanel, bool H
     inline Index outerStride() const;
     #endif
 
-    const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const 
-    { 
-      return m_xpr; 
-    }
-      
-    Index startRow() const 
-    { 
-      return m_startRow.value(); 
-    }
-      
-    Index startCol() const 
-    { 
-      return m_startCol.value(); 
-    }
-
   protected:
 
     const typename XprType::Nested m_xpr;
@@ -321,11 +304,6 @@ class Block<XprType,BlockRows,BlockCols, InnerPanel,true>
       init();
     }
 
-    const typename internal::remove_all<typename XprType::Nested>::type& nestedExpression() const 
-    { 
-      return m_xpr; 
-    }
-      
     /** \sa MapBase::innerStride() */
     inline Index innerStride() const
     {
@@ -363,10 +341,9 @@ class Block<XprType,BlockRows,BlockCols, InnerPanel,true>
                     : m_xpr.innerStride();
     }
 
-    typename XprType::Nested m_xpr;
-    Index m_outerStride;
+    const typename XprType::Nested m_xpr;
+    int m_outerStride;
 };
 
-} // end namespace Eigen
 
 #endif // EIGEN_BLOCK_H

Eigen/src/Core/BooleanRedux.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_ALLANDANY_H
 #define EIGEN_ALLANDANY_H
 
-namespace Eigen { 
-
 namespace internal {
 
 template<typename Derived, int UnrollCount>
@@ -37,7 +35,7 @@ struct all_unroller
     row = (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
-  static inline bool run(const Derived &mat)
+  inline static bool run(const Derived &mat)
   {
     return all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col);
   }
@@ -46,13 +44,13 @@ struct all_unroller
 template<typename Derived>
 struct all_unroller<Derived, 1>
 {
-  static inline bool run(const Derived &mat) { return mat.coeff(0, 0); }
+  inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
 };
 
 template<typename Derived>
 struct all_unroller<Derived, Dynamic>
 {
-  static inline bool run(const Derived &) { return false; }
+  inline static bool run(const Derived &) { return false; }
 };
 
 template<typename Derived, int UnrollCount>
@@ -63,7 +61,7 @@ struct any_unroller
     row = (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
-  static inline bool run(const Derived &mat)
+  inline static bool run(const Derived &mat)
   {
     return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
   }
@@ -72,13 +70,13 @@ struct any_unroller
 template<typename Derived>
 struct any_unroller<Derived, 1>
 {
-  static inline bool run(const Derived &mat) { return mat.coeff(0, 0); }
+  inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
 };
 
 template<typename Derived>
 struct any_unroller<Derived, Dynamic>
 {
-  static inline bool run(const Derived &) { return false; }
+  inline static bool run(const Derived &) { return false; }
 };
 
 } // end namespace internal
@@ -148,6 +146,4 @@ inline typename DenseBase<Derived>::Index DenseBase<Derived>::count() const
   return derived().template cast<bool>().template cast<Index>().sum();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_ALLANDANY_H

Eigen/src/Core/CommaInitializer.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_COMMAINITIALIZER_H
 #define EIGEN_COMMAINITIALIZER_H
 
-namespace Eigen { 
-
 /** \class CommaInitializer
   * \ingroup Core_Module
   *
@@ -149,6 +147,4 @@ DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
   return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_COMMAINITIALIZER_H

Eigen/src/Core/CwiseBinaryOp.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_CWISE_BINARY_OP_H
 #define EIGEN_CWISE_BINARY_OP_H
 
-namespace Eigen {
-
 /** \class CwiseBinaryOp
   * \ingroup Core_Module
   *
@@ -169,8 +167,8 @@ class CwiseBinaryOp : internal::no_assignment_operator,
     const BinaryOp& functor() const { return m_functor; }
 
   protected:
-    LhsNested m_lhs;
-    RhsNested m_rhs;
+    const LhsNested m_lhs;
+    const RhsNested m_rhs;
     const BinaryOp m_functor;
 };
 
@@ -239,6 +237,4 @@ MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_CWISE_BINARY_OP_H

Eigen/src/Core/CwiseNullaryOp.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_CWISE_NULLARY_OP_H
 #define EIGEN_CWISE_NULLARY_OP_H
 
-namespace Eigen {
-
 /** \class CwiseNullaryOp
   * \ingroup Core_Module
   *
@@ -103,9 +101,6 @@ class CwiseNullaryOp : internal::no_assignment_operator,
       return m_functor.packetOp(index);
     }
 
-    /** \returns the functor representing the nullary operation */
-    const NullaryOp& functor() const { return m_functor; }
-
   protected:
     const internal::variable_if_dynamic<Index, RowsAtCompileTime> m_rows;
     const internal::variable_if_dynamic<Index, ColsAtCompileTime> m_cols;
@@ -243,8 +238,6 @@ DenseBase<Derived>::Constant(const Scalar& value)
   * assumed to be a(0), a(1), ..., a(size). This assumption allows for better vectorization
   * and yields faster code than the random access version.
   *
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
-  *
   * \only_for_vectors
   *
   * Example: \include DenseBase_LinSpaced_seq.cpp
@@ -277,7 +270,6 @@ DenseBase<Derived>::LinSpaced(Sequential_t, const Scalar& low, const Scalar& hig
   * \brief Sets a linearly space vector.
   *
   * The function generates 'size' equally spaced values in the closed interval [low,high].
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
   *
   * \only_for_vectors
   *
@@ -389,7 +381,6 @@ PlainObjectBase<Derived>::setConstant(Index rows, Index cols, const Scalar& valu
   * \brief Sets a linearly space vector.
   *
   * The function generates 'size' equally spaced values in the closed interval [low,high].
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
   *
   * \only_for_vectors
   *
@@ -405,23 +396,6 @@ EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(Index size, const
   return derived() = Derived::NullaryExpr(size, internal::linspaced_op<Scalar,false>(low,high,size));
 }
 
-/**
-  * \brief Sets a linearly space vector.
-  *
-  * The function fill *this with equally spaced values in the closed interval [low,high].
-  * When size is set to 1, a vector of length 1 containing 'high' is returned.
-  *
-  * \only_for_vectors
-  *
-  * \sa setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp
-  */
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived& DenseBase<Derived>::setLinSpaced(const Scalar& low, const Scalar& high)
-{
-  EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-  return setLinSpaced(size(), low, high);
-}
-
 // zero:
 
 /** \returns an expression of a zero matrix.
@@ -768,7 +742,7 @@ struct setIdentity_impl<Derived, true>
   static EIGEN_STRONG_INLINE Derived& run(Derived& m)
   {
     m.setZero();
-    const Index size = (std::min)(m.rows(), m.cols());
+    const Index size = std::min(m.rows(), m.cols());
     for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1);
     return m;
   }
@@ -874,6 +848,4 @@ template<typename Derived>
 EIGEN_STRONG_INLINE const typename MatrixBase<Derived>::BasisReturnType MatrixBase<Derived>::UnitW()
 { return Derived::Unit(3); }
 
-} // end namespace Eigen
-
 #endif // EIGEN_CWISE_NULLARY_OP_H

Eigen/src/Core/CwiseUnaryOp.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_CWISE_UNARY_OP_H
 #define EIGEN_CWISE_UNARY_OP_H
 
-namespace Eigen { 
-
 /** \class CwiseUnaryOp
   * \ingroup Core_Module
   *
@@ -97,7 +95,7 @@ class CwiseUnaryOp : internal::no_assignment_operator,
     nestedExpression() { return m_xpr.const_cast_derived(); }
 
   protected:
-    typename XprType::Nested m_xpr;
+    const typename XprType::Nested m_xpr;
     const UnaryOp m_functor;
 };
 
@@ -136,6 +134,4 @@ class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
     }
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_CWISE_UNARY_OP_H

Eigen/src/Core/CwiseUnaryView.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_CWISE_UNARY_VIEW_H
 #define EIGEN_CWISE_UNARY_VIEW_H
 
-namespace Eigen {
-
 /** \class CwiseUnaryView
   * \ingroup Core_Module
   *
@@ -99,7 +97,7 @@ class CwiseUnaryView : internal::no_assignment_operator,
 
   protected:
     // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC
-    typename internal::nested<MatrixType>::type m_matrix;
+    const typename internal::nested<MatrixType>::type m_matrix;
     ViewOp m_functor;
 };
 
@@ -145,6 +143,6 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
     }
 };
 
-} // end namespace Eigen
+
 
 #endif // EIGEN_CWISE_UNARY_VIEW_H

Eigen/src/Core/DenseBase.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_DENSEBASE_H
 #define EIGEN_DENSEBASE_H
 
-namespace Eigen {
-
 /** \class DenseBase
   * \ingroup Core_Module
   *
@@ -171,8 +169,8 @@ template<typename Derived> class DenseBase
 
       IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */
 
-      InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime)
-                             : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime),
+      InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? SizeAtCompileTime
+                             : int(IsRowMajor) ? ColsAtCompileTime : RowsAtCompileTime,
 
       CoeffReadCost = internal::traits<Derived>::CoeffReadCost,
         /**< This is a rough measure of how expensive it is to read one coefficient from
@@ -378,13 +376,12 @@ template<typename Derived> class DenseBase
     inline Derived& operator*=(const Scalar& other);
     inline Derived& operator/=(const Scalar& other);
 
-    typedef typename internal::add_const_on_value_type<typename internal::eval<Derived>::type>::type EvalReturnType;
     /** \returns the matrix or vector obtained by evaluating this expression.
       *
       * Notice that in the case of a plain matrix or vector (not an expression) this function just returns
       * a const reference, in order to avoid a useless copy.
       */
-    EIGEN_STRONG_INLINE EvalReturnType eval() const
+    EIGEN_STRONG_INLINE const typename internal::eval<Derived>::type eval() const
     {
       // Even though MSVC does not honor strong inlining when the return type
       // is a dynamic matrix, we desperately need strong inlining for fixed
@@ -543,6 +540,4 @@ template<typename Derived> class DenseBase
     template<typename OtherDerived> explicit DenseBase(const DenseBase<OtherDerived>&);
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_DENSEBASE_H

Eigen/src/Core/DenseCoeffsBase.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_DENSECOEFFSBASE_H
 #define EIGEN_DENSECOEFFSBASE_H
 
-namespace Eigen {
-
 namespace internal {
 template<typename T> struct add_const_on_value_type_if_arithmetic
 {
@@ -712,16 +710,16 @@ namespace internal {
 template<typename Derived, bool JustReturnZero>
 struct first_aligned_impl
 {
-  static inline typename Derived::Index run(const Derived&)
+  inline static typename Derived::Index run(const Derived&)
   { return 0; }
 };
 
 template<typename Derived>
 struct first_aligned_impl<Derived, false>
 {
-  static inline typename Derived::Index run(const Derived& m)
+  inline static typename Derived::Index run(const Derived& m)
   {
-    return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
+    return first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
   }
 };
 
@@ -731,7 +729,7 @@ struct first_aligned_impl<Derived, false>
   * documentation.
   */
 template<typename Derived>
-static inline typename Derived::Index first_aligned(const Derived& m)
+inline static typename Derived::Index first_aligned(const Derived& m)
 {
   return first_aligned_impl
           <Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>
@@ -764,6 +762,4 @@ struct outer_stride_at_compile_time<Derived, false>
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_DENSECOEFFSBASE_H

Eigen/src/Core/DenseStorage.h

@@ -33,8 +33,6 @@
   #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
 #endif
 
-namespace Eigen {
-
 namespace internal {
 
 struct constructor_without_unaligned_array_assert {};
@@ -106,8 +104,8 @@ template<typename T, int Size, int _Rows, int _Cols, int _Options> class DenseSt
       : m_data(internal::constructor_without_unaligned_array_assert()) {}
     inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
     inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); }
-    static inline DenseIndex rows(void) {return _Rows;}
-    static inline DenseIndex cols(void) {return _Cols;}
+    inline static DenseIndex rows(void) {return _Rows;}
+    inline static DenseIndex cols(void) {return _Cols;}
     inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
     inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
     inline const T *data() const { return m_data.array; }
@@ -122,24 +120,14 @@ template<typename T, int _Rows, int _Cols, int _Options> class DenseStorage<T, 0
     inline DenseStorage(internal::constructor_without_unaligned_array_assert) {}
     inline DenseStorage(DenseIndex,DenseIndex,DenseIndex) {}
     inline void swap(DenseStorage& ) {}
-    static inline DenseIndex rows(void) {return _Rows;}
-    static inline DenseIndex cols(void) {return _Cols;}
+    inline static DenseIndex rows(void) {return _Rows;}
+    inline static DenseIndex cols(void) {return _Cols;}
     inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
     inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
     inline const T *data() const { return 0; }
     inline T *data() { return 0; }
 };
 
-// more specializations for null matrices; these are necessary to resolve ambiguities
-template<typename T, int _Options> class DenseStorage<T, 0, Dynamic, Dynamic, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
-template<typename T, int _Rows, int _Options> class DenseStorage<T, 0, _Rows, Dynamic, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
-template<typename T, int _Cols, int _Options> class DenseStorage<T, 0, Dynamic, _Cols, _Options>
-: public DenseStorage<T, 0, 0, 0, _Options> { };
-
 // dynamic-size matrix with fixed-size storage
 template<typename T, int Size, int _Options> class DenseStorage<T, Size, Dynamic, Dynamic, _Options>
 {
@@ -253,7 +241,7 @@ template<typename T, int _Rows, int _Options> class DenseStorage<T, Dynamic, _Ro
     { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN }
     inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Rows*m_cols); }
     inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); }
-    static inline DenseIndex rows(void) {return _Rows;}
+    inline static DenseIndex rows(void) {return _Rows;}
     inline DenseIndex cols(void) const {return m_cols;}
     inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols)
     {
@@ -290,7 +278,7 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
     inline ~DenseStorage() { internal::conditional_aligned_delete_auto<T,(_Options&DontAlign)==0>(m_data, _Cols*m_rows); }
     inline void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); }
     inline DenseIndex rows(void) const {return m_rows;}
-    static inline DenseIndex cols(void) {return _Cols;}
+    inline static DenseIndex cols(void) {return _Cols;}
     inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
@@ -313,6 +301,4 @@ template<typename T, int _Cols, int _Options> class DenseStorage<T, Dynamic, Dyn
     inline T *data() { return m_data; }
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_MATRIX_H

Eigen/src/Core/Diagonal.h

@@ -2,7 +2,6 @@
 // for linear algebra.
 //
 // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -26,8 +25,6 @@
 #ifndef EIGEN_DIAGONAL_H
 #define EIGEN_DIAGONAL_H
 
-namespace Eigen { 
-
 /** \class Diagonal
   * \ingroup Core_Module
   *
@@ -90,7 +87,7 @@ template<typename MatrixType, int DiagIndex> class Diagonal
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal)
 
     inline Index rows() const
-    { return m_index.value()<0 ? (std::min)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min)(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
+    { return m_index.value()<0 ? std::min(m_matrix.cols(),m_matrix.rows()+m_index.value()) : std::min(m_matrix.rows(),m_matrix.cols()-m_index.value()); }
 
     inline Index cols() const { return 1; }
 
@@ -104,15 +101,6 @@ template<typename MatrixType, int DiagIndex> class Diagonal
       return 0;
     }
 
-    typedef typename internal::conditional<
-                       internal::is_lvalue<MatrixType>::value,
-                       Scalar,
-                       const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
-
-    inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
-    inline const Scalar* data() const { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); }
-
     inline Scalar& coeffRef(Index row, Index)
     {
       EIGEN_STATIC_ASSERT_LVALUE(MatrixType)
@@ -145,19 +133,8 @@ template<typename MatrixType, int DiagIndex> class Diagonal
       return m_matrix.coeff(index+rowOffset(), index+colOffset());
     }
 
-    const typename internal::remove_all<typename MatrixType::Nested>::type& 
-    nestedExpression() const 
-    {
-      return m_matrix;
-    }
-
-    int index() const
-    {
-      return m_index.value();
-    }
-
   protected:
-    typename MatrixType::Nested m_matrix;
+    const typename MatrixType::Nested m_matrix;
     const internal::variable_if_dynamic<Index, DiagIndex> m_index;
 
   private:
@@ -247,6 +224,4 @@ MatrixBase<Derived>::diagonal() const
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_DIAGONAL_H

Eigen/src/Core/DiagonalMatrix.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_DIAGONALMATRIX_H
 #define EIGEN_DIAGONALMATRIX_H
 
-namespace Eigen { 
-
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 template<typename Derived>
 class DiagonalBase : public EigenBase<Derived>
@@ -74,7 +72,7 @@ class DiagonalBase : public EigenBase<Derived>
     const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
     operator*(const MatrixBase<MatrixDerived> &matrix) const;
 
-    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
+    inline const DiagonalWrapper<CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
     inverse() const
     {
       return diagonal().cwiseInverse();
@@ -253,13 +251,13 @@ class DiagonalWrapper
     #endif
 
     /** Constructor from expression of diagonal coefficients to wrap. */
-    inline DiagonalWrapper(DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
+    inline DiagonalWrapper(const DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
 
     /** \returns a const reference to the wrapped expression of diagonal coefficients. */
     const DiagonalVectorType& diagonal() const { return m_diagonal; }
 
   protected:
-    typename DiagonalVectorType::Nested m_diagonal;
+    const typename DiagonalVectorType::Nested m_diagonal;
 };
 
 /** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients
@@ -305,6 +303,4 @@ bool MatrixBase<Derived>::isDiagonal(RealScalar prec) const
   return true;
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_DIAGONALMATRIX_H

Eigen/src/Core/DiagonalProduct.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_DIAGONALPRODUCT_H
 #define EIGEN_DIAGONALPRODUCT_H
 
-namespace Eigen { 
-
 namespace internal {
 template<typename MatrixType, typename DiagonalType, int ProductOrder>
 struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
@@ -109,8 +107,8 @@ class DiagonalProduct : internal::no_assignment_operator,
                      m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
     }
 
-    typename MatrixType::Nested m_matrix;
-    typename DiagonalType::Nested m_diagonal;
+    const typename MatrixType::Nested m_matrix;
+    const typename DiagonalType::Nested m_diagonal;
 };
 
 /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
@@ -133,6 +131,5 @@ DiagonalBase<DiagonalDerived>::operator*(const MatrixBase<MatrixDerived> &matrix
   return DiagonalProduct<MatrixDerived, DiagonalDerived, OnTheLeft>(matrix.derived(), derived());
 }
 
-} // end namespace Eigen
 
 #endif // EIGEN_DIAGONALPRODUCT_H

Eigen/src/Core/Dot.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_DOT_H
 #define EIGEN_DOT_H
 
-namespace Eigen { 
-
 namespace internal {
 
 // helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot
@@ -118,9 +116,7 @@ MatrixBase<Derived>::eigen2_dot(const MatrixBase<OtherDerived>& other) const
 
 //---------- implementation of L2 norm and related functions ----------
 
-/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm.
-  * In both cases, it consists in the sum of the square of all the matrix entries.
-  * For vectors, this is also equals to the dot product of \c *this with itself.
+/** \returns the squared \em l2 norm of *this, i.e., for vectors, the dot product of *this with itself.
   *
   * \sa dot(), norm()
   */
@@ -130,9 +126,7 @@ EIGEN_STRONG_INLINE typename NumTraits<typename internal::traits<Derived>::Scala
   return internal::real((*this).cwiseAbs2().sum());
 }
 
-/** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm.
-  * In both cases, it consists in the square root of the sum of the square of all the matrix entries.
-  * For vectors, this is also equals to the square root of the dot product of \c *this with itself.
+/** \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()
   */
@@ -178,7 +172,7 @@ template<typename Derived, int p>
 struct lpNorm_selector
 {
   typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
-  static inline RealScalar run(const MatrixBase<Derived>& m)
+  inline static RealScalar run(const MatrixBase<Derived>& m)
   {
     return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
   }
@@ -187,7 +181,7 @@ struct lpNorm_selector
 template<typename Derived>
 struct lpNorm_selector<Derived, 1>
 {
-  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.cwiseAbs().sum();
   }
@@ -196,7 +190,7 @@ struct lpNorm_selector<Derived, 1>
 template<typename Derived>
 struct lpNorm_selector<Derived, 2>
 {
-  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.norm();
   }
@@ -205,7 +199,7 @@ struct lpNorm_selector<Derived, 2>
 template<typename Derived>
 struct lpNorm_selector<Derived, Infinity>
 {
-  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.cwiseAbs().maxCoeff();
   }
@@ -271,6 +265,4 @@ bool MatrixBase<Derived>::isUnitary(RealScalar prec) const
   return true;
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_DOT_H

Eigen/src/Core/EigenBase.h

@@ -26,7 +26,6 @@
 #ifndef EIGEN_EIGENBASE_H
 #define EIGEN_EIGENBASE_H
 
-namespace Eigen {
 
 /** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T).
   *
@@ -170,6 +169,4 @@ inline void MatrixBase<Derived>::applyOnTheLeft(const EigenBase<OtherDerived> &o
   other.derived().applyThisOnTheLeft(derived());
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_EIGENBASE_H

Eigen/src/Core/Flagged.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_FLAGGED_H
 #define EIGEN_FLAGGED_H
 
-namespace Eigen { 
-
 /** \class Flagged
   * \ingroup Core_Module
   *
@@ -150,6 +148,4 @@ DenseBase<Derived>::flagged() const
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_FLAGGED_H

Eigen/src/Core/ForceAlignedAccess.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_FORCEALIGNEDACCESS_H
 #define EIGEN_FORCEALIGNEDACCESS_H
 
-namespace Eigen {
-
 /** \class ForceAlignedAccess
   * \ingroup Core_Module
   *
@@ -156,6 +154,4 @@ MatrixBase<Derived>::forceAlignedAccessIf()
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_FORCEALIGNEDACCESS_H

Eigen/src/Core/Functors.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_FUNCTORS_H
 #define EIGEN_FUNCTORS_H
 
-namespace Eigen {
-
 namespace internal {
 
 // associative functors:
@@ -118,7 +116,7 @@ struct functor_traits<scalar_conj_product_op<LhsScalar,RhsScalar> > {
   */
 template<typename Scalar> struct scalar_min_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::min; return (min)(a, b); }
+  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::min; return min(a, b); }
   template<typename Packet>
   EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
   { return internal::pmin(a,b); }
@@ -141,7 +139,7 @@ struct functor_traits<scalar_min_op<Scalar> > {
   */
 template<typename Scalar> struct scalar_max_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::max; return (max)(a, b); }
+  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::max; return max(a, b); }
   template<typename Packet>
   EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const
   { return internal::pmax(a,b); }
@@ -169,8 +167,8 @@ template<typename Scalar> struct scalar_hypot_op {
   {
     using std::max;
     using std::min;
-    Scalar p = (max)(_x, _y);
-    Scalar q = (min)(_x, _y);
+    Scalar p = max(_x, _y);
+    Scalar q = min(_x, _y);
     Scalar qp = q/p;
     return p * sqrt(Scalar(1) + qp*qp);
   }
@@ -180,18 +178,6 @@ struct functor_traits<scalar_hypot_op<Scalar> > {
   enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess=0 };
 };
 
-/** \internal
-  * \brief Template functor to compute the pow of two scalars
-  */
-template<typename Scalar, typename OtherScalar> struct scalar_binary_pow_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_binary_pow_op)
-  inline Scalar operator() (const Scalar& a, const OtherScalar& b) const { return internal::pow(a, b); }
-};
-template<typename Scalar, typename OtherScalar>
-struct functor_traits<scalar_binary_pow_op<Scalar,OtherScalar> > {
-  enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false };
-};
-
 // other binary functors:
 
 /** \internal
@@ -234,38 +220,6 @@ struct functor_traits<scalar_quotient_op<Scalar> > {
   };
 };
 
-/** \internal
-  * \brief Template functor to compute the and of two booleans
-  *
-  * \sa class CwiseBinaryOp, ArrayBase::operator&&
-  */
-struct scalar_boolean_and_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op)
-  EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; }
-};
-template<> struct functor_traits<scalar_boolean_and_op> {
-  enum {
-    Cost = NumTraits<bool>::AddCost,
-    PacketAccess = false
-  };
-};
-
-/** \internal
-  * \brief Template functor to compute the or of two booleans
-  *
-  * \sa class CwiseBinaryOp, ArrayBase::operator||
-  */
-struct scalar_boolean_or_op {
-  EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op)
-  EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; }
-};
-template<> struct functor_traits<scalar_boolean_or_op> {
-  enum {
-    Cost = NumTraits<bool>::AddCost,
-    PacketAccess = false
-  };
-};
-
 // unary functors:
 
 /** \internal
@@ -630,7 +584,7 @@ template <typename Scalar, bool RandomAccess> struct functor_traits< linspaced_o
 template <typename Scalar, bool RandomAccess> struct linspaced_op
 {
   typedef typename packet_traits<Scalar>::type Packet;
-  linspaced_op(Scalar low, Scalar high, int num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/(num_steps-1))) {}
+  linspaced_op(Scalar low, Scalar high, int num_steps) : impl(low, (high-low)/(num_steps-1)) {}
 
   template<typename Index>
   EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }
@@ -827,20 +781,6 @@ template<typename Scalar>
 struct functor_traits<scalar_pow_op<Scalar> >
 { enum { Cost = 5 * NumTraits<Scalar>::MulCost, PacketAccess = false }; };
 
-/** \internal
-  * \brief Template functor to compute the quotient between a scalar and array entries.
-  * \sa class CwiseUnaryOp, Cwise::inverse()
-  */
-template<typename Scalar>
-struct scalar_inverse_mult_op {
-  scalar_inverse_mult_op(const Scalar& other) : m_other(other) {}
-  inline Scalar operator() (const Scalar& a) const { return m_other / a; }
-  template<typename Packet>
-  inline const Packet packetOp(const Packet& a) const
-  { return internal::pdiv(pset1<Packet>(m_other),a); }
-  Scalar m_other;
-};
-
 /** \internal
   * \brief Template functor to compute the inverse of a scalar
   * \sa class CwiseUnaryOp, Cwise::inverse()
@@ -999,6 +939,4 @@ struct functor_traits<std::binary_compose<T0,T1,T2> >
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_FUNCTORS_H

Eigen/src/Core/Fuzzy.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_FUZZY_H
 #define EIGEN_FUZZY_H
 
-namespace Eigen { 
-
 namespace internal
 {
 
@@ -37,9 +35,9 @@ struct isApprox_selector
   static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
   {
     using std::min;
-    typename internal::nested<Derived,2>::type nested(x);
-    typename internal::nested<OtherDerived,2>::type otherNested(y);
-    return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
+    const typename internal::nested<Derived,2>::type nested(x);
+    const typename internal::nested<OtherDerived,2>::type otherNested(y);
+    return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * min(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum());
   }
 };
 
@@ -160,6 +158,4 @@ bool DenseBase<Derived>::isMuchSmallerThan(
   return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_FUZZY_H

Eigen/src/Core/GeneralProduct.h

@@ -1,628 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
-//
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_GENERAL_PRODUCT_H
-#define EIGEN_GENERAL_PRODUCT_H
-
-namespace Eigen { 
-
-/** \class GeneralProduct
-  * \ingroup Core_Module
-  *
-  * \brief Expression of the product of two general matrices or vectors
-  *
-  * \param LhsNested the type used to store the left-hand side
-  * \param RhsNested the type used to store the right-hand side
-  * \param ProductMode the type of the product
-  *
-  * This class represents an expression of the product of two general matrices.
-  * We call a general matrix, a dense matrix with full storage. For instance,
-  * This excludes triangular, selfadjoint, and sparse matrices.
-  * It is the return type of the operator* between general matrices. Its template
-  * arguments are determined automatically by ProductReturnType. Therefore,
-  * GeneralProduct should never be used direclty. To determine the result type of a
-  * function which involves a matrix product, use ProductReturnType::Type.
-  *
-  * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
-  */
-template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
-class GeneralProduct;
-
-enum {
-  Large = 2,
-  Small = 3
-};
-
-namespace internal {
-
-template<int Rows, int Cols, int Depth> struct product_type_selector;
-
-template<int Size, int MaxSize> struct product_size_category
-{
-  enum { is_large = MaxSize == Dynamic ||
-                    Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
-         value = is_large  ? Large
-               : Size == 1 ? 1
-                           : Small
-  };
-};
-
-template<typename Lhs, typename Rhs> struct product_type
-{
-  typedef typename remove_all<Lhs>::type _Lhs;
-  typedef typename remove_all<Rhs>::type _Rhs;
-  enum {
-    MaxRows  = _Lhs::MaxRowsAtCompileTime,
-    Rows  = _Lhs::RowsAtCompileTime,
-    MaxCols  = _Rhs::MaxColsAtCompileTime,
-    Cols  = _Rhs::ColsAtCompileTime,
-    MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
-                                           _Rhs::MaxRowsAtCompileTime),
-    Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
-                                        _Rhs::RowsAtCompileTime),
-    LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
-  };
-
-  // the splitting into different lines of code here, introducing the _select enums and the typedef below,
-  // is to work around an internal compiler error with gcc 4.1 and 4.2.
-private:
-  enum {
-    rows_select = product_size_category<Rows,MaxRows>::value,
-    cols_select = product_size_category<Cols,MaxCols>::value,
-    depth_select = product_size_category<Depth,MaxDepth>::value
-  };
-  typedef product_type_selector<rows_select, cols_select, depth_select> selector;
-
-public:
-  enum {
-    value = selector::ret
-  };
-#ifdef EIGEN_DEBUG_PRODUCT
-  static void debug()
-  {
-      EIGEN_DEBUG_VAR(Rows);
-      EIGEN_DEBUG_VAR(Cols);
-      EIGEN_DEBUG_VAR(Depth);
-      EIGEN_DEBUG_VAR(rows_select);
-      EIGEN_DEBUG_VAR(cols_select);
-      EIGEN_DEBUG_VAR(depth_select);
-      EIGEN_DEBUG_VAR(value);
-  }
-#endif
-};
-
-
-/* The following allows to select the kind of product at compile time
- * based on the three dimensions of the product.
- * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
-// FIXME I'm not sure the current mapping is the ideal one.
-template<int M, int N>  struct product_type_selector<M,N,1>              { enum { ret = OuterProduct }; };
-template<int Depth>     struct product_type_selector<1,    1,    Depth>  { enum { ret = InnerProduct }; };
-template<>              struct product_type_selector<1,    1,    1>      { enum { ret = InnerProduct }; };
-template<>              struct product_type_selector<Small,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<1,    Small,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small, Large, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
-template<>              struct product_type_selector<Large, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
-template<>              struct product_type_selector<1,    Large,Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<1,    Large,Large>  { enum { ret = GemvProduct }; };
-template<>              struct product_type_selector<1,    Small,Large>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Large,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Large,1,    Large>  { enum { ret = GemvProduct }; };
-template<>              struct product_type_selector<Small,1,    Large>  { enum { ret = CoeffBasedProductMode }; };
-template<>              struct product_type_selector<Small,Small,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Small,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Small,Large,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Large,Large>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Small,Small>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Small,Large,Small>  { enum { ret = GemmProduct }; };
-template<>              struct product_type_selector<Large,Large,Small>  { enum { ret = GemmProduct }; };
-
-} // end namespace internal
-
-/** \class ProductReturnType
-  * \ingroup Core_Module
-  *
-  * \brief Helper class to get the correct and optimized returned type of operator*
-  *
-  * \param Lhs the type of the left-hand side
-  * \param Rhs the type of the right-hand side
-  * \param ProductMode the type of the product (determined automatically by internal::product_mode)
-  *
-  * This class defines the typename Type representing the optimized product expression
-  * between two matrix expressions. In practice, using ProductReturnType<Lhs,Rhs>::Type
-  * is the recommended way to define the result type of a function returning an expression
-  * which involve a matrix product. The class Product should never be
-  * used directly.
-  *
-  * \sa class Product, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
-  */
-template<typename Lhs, typename Rhs, int ProductType>
-struct ProductReturnType
-{
-  // TODO use the nested type to reduce instanciations ????
-//   typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
-//   typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
-
-  typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
-};
-
-template<typename Lhs, typename Rhs>
-struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
-{
-  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
-  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
-  typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
-};
-
-template<typename Lhs, typename Rhs>
-struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
-{
-  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
-  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
-  typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
-};
-
-// this is a workaround for sun CC
-template<typename Lhs, typename Rhs>
-struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
-{};
-
-/***********************************************************************
-*  Implementation of Inner Vector Vector Product
-***********************************************************************/
-
-// FIXME : maybe the "inner product" could return a Scalar
-// instead of a 1x1 matrix ??
-// Pro: more natural for the user
-// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
-// product ends up to a row-vector times col-vector product... To tackle this use
-// case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
-
-namespace internal {
-
-template<typename Lhs, typename Rhs>
-struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
- : traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
-{};
-
-}
-
-template<typename Lhs, typename Rhs>
-class GeneralProduct<Lhs, Rhs, InnerProduct>
-  : internal::no_assignment_operator,
-    public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
-{
-    typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
-  public:
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs)
-    {
-      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-
-      Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
-    }
-
-    /** Convertion to scalar */
-    operator const typename Base::Scalar() const {
-      return Base::coeff(0,0);
-    }
-};
-
-/***********************************************************************
-*  Implementation of Outer Vector Vector Product
-***********************************************************************/
-
-namespace internal {
-template<int StorageOrder> struct outer_product_selector;
-
-template<typename Lhs, typename Rhs>
-struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
- : traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
-{};
-
-}
-
-template<typename Lhs, typename Rhs>
-class GeneralProduct<Lhs, Rhs, OuterProduct>
-  : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
-{
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
-
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {
-      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
-        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-    }
-
-    template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
-    {
-      internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha);
-    }
-};
-
-namespace internal {
-
-template<> struct outer_product_selector<ColMajor> {
-  template<typename ProductType, typename Dest>
-  static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
-    typedef typename Dest::Index Index;
-    // FIXME make sure lhs is sequentially stored
-    // FIXME not very good if rhs is real and lhs complex while alpha is real too
-    const Index cols = dest.cols();
-    for (Index j=0; j<cols; ++j)
-      dest.col(j) += (alpha * prod.rhs().coeff(j)) * prod.lhs();
-  }
-};
-
-template<> struct outer_product_selector<RowMajor> {
-  template<typename ProductType, typename Dest>
-  static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
-    typedef typename Dest::Index Index;
-    // FIXME make sure rhs is sequentially stored
-    // FIXME not very good if lhs is real and rhs complex while alpha is real too
-    const Index rows = dest.rows();
-    for (Index i=0; i<rows; ++i)
-      dest.row(i) += (alpha * prod.lhs().coeff(i)) * prod.rhs();
-  }
-};
-
-} // end namespace internal
-
-/***********************************************************************
-*  Implementation of General Matrix Vector Product
-***********************************************************************/
-
-/*  According to the shape/flags of the matrix we have to distinghish 3 different cases:
- *   1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
- *   2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
- *   3 - all other cases are handled using a simple loop along the outer-storage direction.
- *  Therefore we need a lower level meta selector.
- *  Furthermore, if the matrix is the rhs, then the product has to be transposed.
- */
-namespace internal {
-
-template<typename Lhs, typename Rhs>
-struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
- : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
-{};
-
-template<int Side, int StorageOrder, bool BlasCompatible>
-struct gemv_selector;
-
-} // end namespace internal
-
-template<typename Lhs, typename Rhs>
-class GeneralProduct<Lhs, Rhs, GemvProduct>
-  : public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
-{
-  public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
-
-    typedef typename Lhs::Scalar LhsScalar;
-    typedef typename Rhs::Scalar RhsScalar;
-
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
-    {
-//       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
-//         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-    }
-
-    enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
-    typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
-
-    template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
-    {
-      eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
-      internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
-                       bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
-    }
-};
-
-namespace internal {
-
-// The vector is on the left => transposition
-template<int StorageOrder, bool BlasCompatible>
-struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
-  {
-    Transpose<Dest> destT(dest);
-    enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
-    gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
-      ::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
-        (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
-  }
-};
-
-template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
-
-template<typename Scalar,int Size,int MaxSize>
-struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
-{
-  EIGEN_STRONG_INLINE  Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
-};
-
-template<typename Scalar,int Size>
-struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
-{
-  EIGEN_STRONG_INLINE Scalar* data() { return 0; }
-};
-
-template<typename Scalar,int Size,int MaxSize>
-struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
-{
-  #if EIGEN_ALIGN_STATICALLY
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
-  EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
-  #else
-  // Some architectures cannot align on the stack,
-  // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
-  enum {
-    ForceAlignment  = internal::packet_traits<Scalar>::Vectorizable,
-    PacketSize      = internal::packet_traits<Scalar>::size
-  };
-  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
-  EIGEN_STRONG_INLINE Scalar* data() {
-    return ForceAlignment
-            ? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
-            : m_data.array;
-  }
-  #endif
-};
-
-template<> struct gemv_selector<OnTheRight,ColMajor,true>
-{
-  template<typename ProductType, typename Dest>
-  static inline void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
-  {
-    typedef typename ProductType::Index Index;
-    typedef typename ProductType::LhsScalar   LhsScalar;
-    typedef typename ProductType::RhsScalar   RhsScalar;
-    typedef typename ProductType::Scalar      ResScalar;
-    typedef typename ProductType::RealScalar  RealScalar;
-    typedef typename ProductType::ActualLhsType ActualLhsType;
-    typedef typename ProductType::ActualRhsType ActualRhsType;
-    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
-    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
-    typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
-
-    ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
-    ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
-                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
-
-    enum {
-      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
-      // on, the other hand it is good for the cache to pack the vector anyways...
-      EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
-      ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
-      MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
-    };
-
-    gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
-
-    bool alphaIsCompatible = (!ComplexByReal) || (imag(actualAlpha)==RealScalar(0));
-    bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
-    
-    RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
-
-    ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
-                                                  evalToDest ? dest.data() : static_dest.data());
-    
-    if(!evalToDest)
-    {
-      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      int size = dest.size();
-      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      #endif
-      if(!alphaIsCompatible)
-      {
-        MappedDest(actualDestPtr, dest.size()).setZero();
-        compatibleAlpha = RhsScalar(1);
-      }
-      else
-        MappedDest(actualDestPtr, dest.size()) = dest;
-    }
-
-    general_matrix_vector_product
-      <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
-        actualLhs.rows(), actualLhs.cols(),
-        actualLhs.data(), actualLhs.outerStride(),
-        actualRhs.data(), actualRhs.innerStride(),
-        actualDestPtr, 1,
-        compatibleAlpha);
-
-    if (!evalToDest)
-    {
-      if(!alphaIsCompatible)
-        dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
-      else
-        dest = MappedDest(actualDestPtr, dest.size());
-    }
-  }
-};
-
-template<> struct gemv_selector<OnTheRight,RowMajor,true>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
-  {
-    typedef typename ProductType::LhsScalar LhsScalar;
-    typedef typename ProductType::RhsScalar RhsScalar;
-    typedef typename ProductType::Scalar    ResScalar;
-    typedef typename ProductType::Index Index;
-    typedef typename ProductType::ActualLhsType ActualLhsType;
-    typedef typename ProductType::ActualRhsType ActualRhsType;
-    typedef typename ProductType::_ActualRhsType _ActualRhsType;
-    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
-    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
-
-    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
-    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
-
-    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
-                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
-
-    enum {
-      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
-      // on, the other hand it is good for the cache to pack the vector anyways...
-      DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
-    };
-
-    gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
-
-    ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
-        DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
-
-    if(!DirectlyUseRhs)
-    {
-      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      int size = actualRhs.size();
-      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
-      #endif
-      Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
-    }
-
-    general_matrix_vector_product
-      <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
-        actualLhs.rows(), actualLhs.cols(),
-        actualLhs.data(), actualLhs.outerStride(),
-        actualRhsPtr, 1,
-        dest.data(), dest.innerStride(),
-        actualAlpha);
-  }
-};
-
-template<> struct gemv_selector<OnTheRight,ColMajor,false>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
-  {
-    typedef typename Dest::Index Index;
-    // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
-    const Index size = prod.rhs().rows();
-    for(Index k=0; k<size; ++k)
-      dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
-  }
-};
-
-template<> struct gemv_selector<OnTheRight,RowMajor,false>
-{
-  template<typename ProductType, typename Dest>
-  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
-  {
-    typedef typename Dest::Index Index;
-    // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
-    const Index rows = prod.rows();
-    for(Index i=0; i<rows; ++i)
-      dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
-  }
-};
-
-} // end namespace internal
-
-/***************************************************************************
-* Implementation of matrix base methods
-***************************************************************************/
-
-/** \returns the matrix product of \c *this and \a other.
-  *
-  * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
-  *
-  * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
-  */
-template<typename Derived>
-template<typename OtherDerived>
-inline const typename ProductReturnType<Derived, OtherDerived>::Type
-MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
-{
-  // A note regarding the function declaration: In MSVC, this function will sometimes
-  // not be inlined since DenseStorage is an unwindable object for dynamic
-  // matrices and product types are holding a member to store the result.
-  // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
-  enum {
-    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
-                   || OtherDerived::RowsAtCompileTime==Dynamic
-                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
-    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
-    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
-  };
-  // note to the lost user:
-  //    * for a dot product use: v1.dot(v2)
-  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
-    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
-    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
-  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
-#ifdef EIGEN_DEBUG_PRODUCT
-  internal::product_type<Derived,OtherDerived>::debug();
-#endif
-  return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
-}
-
-/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
-  *
-  * The returned product will behave like any other expressions: the coefficients of the product will be
-  * computed once at a time as requested. This might be useful in some extremely rare cases when only
-  * a small and no coherent fraction of the result's coefficients have to be computed.
-  *
-  * \warning This version of the matrix product can be much much slower. So use it only if you know
-  * what you are doing and that you measured a true speed improvement.
-  *
-  * \sa operator*(const MatrixBase&)
-  */
-template<typename Derived>
-template<typename OtherDerived>
-const typename LazyProductReturnType<Derived,OtherDerived>::Type
-MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
-{
-  enum {
-    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
-                   || OtherDerived::RowsAtCompileTime==Dynamic
-                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
-    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
-    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
-  };
-  // note to the lost user:
-  //    * for a dot product use: v1.dot(v2)
-  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
-    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
-  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
-    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
-  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
-
-  return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
-}
-
-} // end namespace Eigen
-
-#endif // EIGEN_PRODUCT_H

Eigen/src/Core/GenericPacketMath.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_GENERIC_PACKET_MATH_H
 #define EIGEN_GENERIC_PACKET_MATH_H
 
-namespace Eigen {
-
 namespace internal {
 
 /** \internal
@@ -136,12 +134,12 @@ pdiv(const Packet& a,
 /** \internal \returns the min of \a a and \a b  (coeff-wise) */
 template<typename Packet> inline Packet
 pmin(const Packet& a,
-        const Packet& b) { using std::min; return (min)(a, b); }
+        const Packet& b) { using std::min; return min(a, b); }
 
 /** \internal \returns the max of \a a and \a b  (coeff-wise) */
 template<typename Packet> inline Packet
 pmax(const Packet& a,
-        const Packet& b) { using std::max; return (max)(a, b); }
+        const Packet& b) { using std::max; return max(a, b); }
 
 /** \internal \returns the absolute value of \a a */
 template<typename Packet> inline Packet
@@ -314,7 +312,7 @@ template<int Offset,typename PacketType>
 struct palign_impl
 {
   // by default data are aligned, so there is nothing to be done :)
-  static inline void run(PacketType&, const PacketType&) {}
+  inline static void run(PacketType&, const PacketType&) {}
 };
 
 /** \internal update \a first using the concatenation of the \a Offset last elements
@@ -337,7 +335,5 @@ template<> inline std::complex<double> pmul(const std::complex<double>& a, const
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_GENERIC_PACKET_MATH_H
 

Eigen/src/Core/GlobalFunctions.h

@@ -66,36 +66,13 @@ namespace std
 
   template<typename Derived>
   inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_pow_op<typename Derived::Scalar>, const Derived>
-  pow(const Eigen::ArrayBase<Derived>& x, const typename Derived::Scalar& exponent) {
-    return x.derived().pow(exponent);
-  }
-
-  template<typename Derived>
-  inline const Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>
-  pow(const Eigen::ArrayBase<Derived>& x, const Eigen::ArrayBase<Derived>& exponents) 
-  {
-    return Eigen::CwiseBinaryOp<Eigen::internal::scalar_binary_pow_op<typename Derived::Scalar, typename Derived::Scalar>, const Derived, const Derived>(
-      x.derived(),
-      exponents.derived()
-    );
+  pow(const Eigen::ArrayBase<Derived>& x, const typename Derived::Scalar& exponent) { \
+    return x.derived().pow(exponent); \
   }
 }
 
 namespace Eigen
 {
-  /**
-  * \brief Component-wise division of a scalar by array elements.
-  **/
-  template <typename Derived>
-  inline const Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>
-    operator/(typename Derived::Scalar s, const Eigen::ArrayBase<Derived>& a)
-  {
-    return Eigen::CwiseUnaryOp<Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>, const Derived>(
-      a.derived(),
-      Eigen::internal::scalar_inverse_mult_op<typename Derived::Scalar>(s)  
-    );
-  }
-
   namespace internal
   {
     EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op)

Eigen/src/Core/IO.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_IO_H
 #define EIGEN_IO_H
 
-namespace Eigen { 
-
 enum { DontAlignCols = 1 };
 enum { StreamPrecision = -1,
        FullPrecision = -2 };
@@ -173,7 +171,7 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
     return s;
   }
   
-  typename Derived::Nested m = _m;
+  const typename Derived::Nested m = _m;
   typedef typename Derived::Scalar Scalar;
   typedef typename Derived::Index Index;
 
@@ -259,6 +257,4 @@ std::ostream & operator <<
   return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT);
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_IO_H

Eigen/src/Core/Map.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_MAP_H
 #define EIGEN_MAP_H
 
-namespace Eigen { 
-
 /** \class Map
   * \ingroup Core_Module
   *
@@ -36,7 +34,7 @@ namespace Eigen {
   * \tparam PlainObjectType the equivalent matrix type of the mapped data
   * \tparam MapOptions specifies whether the pointer is \c #Aligned, or \c #Unaligned.
   *                The default is \c #Unaligned.
-  * \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout
+  * \tparam StrideType optionnally specifies strides. By default, Map assumes the memory layout
   *                   of an ordinary, contiguous array. This can be overridden by specifying strides.
   *                   The type passed here must be a specialization of the Stride template, see examples below.
   *
@@ -74,9 +72,9 @@ namespace Eigen {
   * Example: \include Map_placement_new.cpp
   * Output: \verbinclude Map_placement_new.out
   *
-  * This class is the return type of PlainObjectBase::Map() but can also be used directly.
+  * This class is the return type of Matrix::Map() but can also be used directly.
   *
-  * \sa PlainObjectBase::Map(), \ref TopicStorageOrders
+  * \sa Matrix::Map(), \ref TopicStorageOrders
   */
 
 namespace internal {
@@ -104,7 +102,7 @@ struct traits<Map<PlainObjectType, MapOptions, StrideType> >
                            || HasNoOuterStride
                            || ( OuterStrideAtCompileTime!=Dynamic
                            && ((static_cast<int>(sizeof(Scalar))*OuterStrideAtCompileTime)%16)==0 ) ),
-    Flags0 = TraitsBase::Flags & (~NestByRefBit),
+    Flags0 = TraitsBase::Flags,
     Flags1 = IsAligned ? (int(Flags0) | AlignedBit) : (int(Flags0) & ~AlignedBit),
     Flags2 = (bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime))
            ? int(Flags1) : int(Flags1 & ~LinearAccessBit),
@@ -122,6 +120,7 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
   public:
 
     typedef MapBase<Map> Base;
+
     EIGEN_DENSE_PUBLIC_INTERFACE(Map)
 
     typedef typename Base::PointerType PointerType;
@@ -182,6 +181,7 @@ template<typename PlainObjectType, int MapOptions, typename StrideType> class Ma
       PlainObjectType::Base::_check_template_params();
     }
 
+
     EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map)
 
   protected:
@@ -202,6 +202,4 @@ inline Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
   this->_set_noalias(Eigen::Map<const Matrix>(data));
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_MAP_H

Eigen/src/Core/MapBase.h

@@ -30,7 +30,6 @@
       EIGEN_STATIC_ASSERT((int(internal::traits<Derived>::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \
                           YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT)
 
-namespace Eigen { 
 
 /** \class MapBase
   * \ingroup Core_Module
@@ -171,8 +170,8 @@ template<typename Derived> class MapBase<Derived, ReadOnlyAccessors>
       EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(internal::traits<Derived>::Flags&PacketAccessBit,
                                         internal::inner_stride_at_compile_time<Derived>::ret==1),
                           PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1);
-      eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::Flags&AlignedBit, (size_t(m_data) % 16) == 0)
-                   && "data is not aligned");
+      eigen_assert(EIGEN_IMPLIES(internal::traits<Derived>::Flags&AlignedBit, (size_t(m_data) % (sizeof(Scalar)*internal::packet_traits<Scalar>::size)) == 0)
+        && "data is not aligned");
     }
 
     PointerType m_data;
@@ -252,6 +251,5 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
     using Base::Base::operator=;
 };
 
-} // end namespace Eigen
 
 #endif // EIGEN_MAPBASE_H

Eigen/src/Core/MathFunctions.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_MATHFUNCTIONS_H
 #define EIGEN_MATHFUNCTIONS_H
 
-namespace Eigen {
-
 namespace internal {
 
 /** \internal \struct global_math_functions_filtering_base
@@ -311,7 +309,8 @@ struct abs2_impl<std::complex<RealScalar> >
 {
   static inline RealScalar run(const std::complex<RealScalar>& x)
   {
-    return real(x)*real(x) + imag(x)*imag(x);
+    using std::norm;
+    return norm(x);
   }
 };
 
@@ -379,8 +378,8 @@ struct hypot_impl
     using std::min;
     RealScalar _x = abs(x);
     RealScalar _y = abs(y);
-    RealScalar p = (max)(_x, _y);
-    RealScalar q = (min)(_x, _y);
+    RealScalar p = max(_x, _y);
+    RealScalar q = min(_x, _y);
     RealScalar qp = q/p;
     return p * sqrt(RealScalar(1) + qp*qp);
   }
@@ -554,7 +553,7 @@ struct pow_default_impl<Scalar, true>
 {
   static inline Scalar run(Scalar x, Scalar y)
   {
-    Scalar res(1);
+    Scalar res = 1;
     eigen_assert(!NumTraits<Scalar>::IsSigned || y >= 0);
     if(y & 1) res *= x;
     y >>= 1;
@@ -738,7 +737,7 @@ struct scalar_fuzzy_default_impl<Scalar, false, false>
   static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec)
   {
     using std::min;
-    return abs(x - y) <= (min)(abs(x), abs(y)) * prec;
+    return abs(x - y) <= min(abs(x), abs(y)) * prec;
   }
   static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar& prec)
   {
@@ -777,7 +776,7 @@ struct scalar_fuzzy_default_impl<Scalar, true, false>
   static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec)
   {
     using std::min;
-    return abs2(x - y) <= (min)(abs2(x), abs2(y)) * prec * prec;
+    return abs2(x - y) <= min(abs2(x), abs2(y)) * prec * prec;
   }
 };
 
@@ -839,19 +838,6 @@ template<> struct scalar_fuzzy_impl<bool>
   
 };
 
-/****************************************************************************
-* Special functions                                                          *
-****************************************************************************/
-
-// std::isfinite is non standard, so let's define our own version,
-// even though it is not very efficient.
-template<typename T> bool isfinite(const T& x)
-{
-  return x<NumTraits<T>::highest() && x>NumTraits<T>::lowest();
-}
-
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_MATHFUNCTIONS_H

Eigen/src/Core/Matrix.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_MATRIX_H
 #define EIGEN_MATRIX_H
 
-namespace Eigen {
-
 /** \class Matrix
   * \ingroup Core_Module
   *
@@ -155,6 +153,10 @@ class Matrix
 
     typedef typename Base::PlainObject PlainObject;
 
+    enum { NeedsToAlign = (!(Options&DontAlign))
+                          && SizeAtCompileTime!=Dynamic && ((static_cast<int>(sizeof(Scalar))*SizeAtCompileTime)%16)==0 };
+    EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
+
     using Base::base;
     using Base::coeffRef;
 
@@ -413,8 +415,25 @@ EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
 
 #undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES
 #undef EIGEN_MAKE_TYPEDEFS
-#undef EIGEN_MAKE_FIXED_TYPEDEFS
 
-} // end namespace Eigen
+#undef EIGEN_MAKE_TYPEDEFS_LARGE
+
+#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \
+using Eigen::Matrix##SizeSuffix##TypeSuffix; \
+using Eigen::Vector##SizeSuffix##TypeSuffix; \
+using Eigen::RowVector##SizeSuffix##TypeSuffix;
+
+#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \
+
+#define EIGEN_USING_MATRIX_TYPEDEFS \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \
+EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd)
 
 #endif // EIGEN_MATRIX_H

Eigen/src/Core/MatrixBase.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_MATRIXBASE_H
 #define EIGEN_MATRIXBASE_H
 
-namespace Eigen {
-
 /** \class MatrixBase
   * \ingroup Core_Module
   *
@@ -113,7 +111,7 @@ template<typename Derived> class MatrixBase
 
     /** \returns the size of the main diagonal, which is min(rows(),cols()).
       * \sa rows(), cols(), SizeAtCompileTime. */
-    inline Index diagonalSize() const { return (std::min)(rows(),cols()); }
+    inline Index diagonalSize() const { return std::min(rows(),cols()); }
 
     /** \brief The plain matrix type corresponding to this expression.
       *
@@ -332,7 +330,7 @@ template<typename Derived> class MatrixBase
     /** \returns an \link ArrayBase Array \endlink expression of this matrix
       * \sa ArrayBase::matrix() */
     ArrayWrapper<Derived> array() { return derived(); }
-    const ArrayWrapper<const Derived> array() const { return derived(); }
+    const ArrayWrapper<Derived> array() const { return derived(); }
 
 /////////// LU module ///////////
 
@@ -467,8 +465,6 @@ template<typename Derived> class MatrixBase
     const MatrixFunctionReturnValue<Derived> sinh() const;
     const MatrixFunctionReturnValue<Derived> cos() const;
     const MatrixFunctionReturnValue<Derived> sin() const;
-    const MatrixSquareRootReturnValue<Derived> sqrt() const;
-    const MatrixLogarithmReturnValue<Derived> log() const;
 
 #ifdef EIGEN2_SUPPORT
     template<typename ProductDerived, typename Lhs, typename Rhs>
@@ -515,12 +511,10 @@ template<typename Derived> class MatrixBase
   protected:
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator+=(const ArrayBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
+    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator-=(const ArrayBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
+    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_MATRIXBASE_H

Eigen/src/Core/NestByValue.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_NESTBYVALUE_H
 #define EIGEN_NESTBYVALUE_H
 
-namespace Eigen {
-
 /** \class NestByValue
   * \ingroup Core_Module
   *
@@ -121,6 +119,4 @@ DenseBase<Derived>::nestByValue() const
   return NestByValue<Derived>(derived());
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_NESTBYVALUE_H

Eigen/src/Core/NoAlias.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_NOALIAS_H
 #define EIGEN_NOALIAS_H
 
-namespace Eigen {
-
 /** \class NoAlias
   * \ingroup Core_Module
   *
@@ -135,6 +133,4 @@ NoAlias<Derived,MatrixBase> MatrixBase<Derived>::noalias()
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_NOALIAS_H

Eigen/src/Core/NumTraits.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_NUMTRAITS_H
 #define EIGEN_NUMTRAITS_H
 
-namespace Eigen {
-
 /** \class NumTraits
   * \ingroup Core_Module
   *
@@ -83,14 +81,14 @@ template<typename T> struct GenericNumTraits
                    >::type NonInteger;
   typedef T Nested;
 
-  static inline Real epsilon() { return std::numeric_limits<T>::epsilon(); }
-  static inline Real dummy_precision()
+  inline static Real epsilon() { return std::numeric_limits<T>::epsilon(); }
+  inline static Real dummy_precision()
   {
     // make sure to override this for floating-point types
     return Real(0);
   }
-  static inline T highest() { return (std::numeric_limits<T>::max)(); }
-  static inline T lowest()  { return IsInteger ? (std::numeric_limits<T>::min)() : (-(std::numeric_limits<T>::max)()); }
+  inline static T highest() { return std::numeric_limits<T>::max(); }
+  inline static T lowest()  { return IsInteger ? std::numeric_limits<T>::min() : (-std::numeric_limits<T>::max()); }
   
 #ifdef EIGEN2_SUPPORT
   enum {
@@ -106,12 +104,12 @@ template<typename T> struct NumTraits : GenericNumTraits<T>
 template<> struct NumTraits<float>
   : GenericNumTraits<float>
 {
-  static inline float dummy_precision() { return 1e-5f; }
+  inline static float dummy_precision() { return 1e-5f; }
 };
 
 template<> struct NumTraits<double> : GenericNumTraits<double>
 {
-  static inline double dummy_precision() { return 1e-12; }
+  inline static double dummy_precision() { return 1e-12; }
 };
 
 template<> struct NumTraits<long double>
@@ -132,8 +130,8 @@ template<typename _Real> struct NumTraits<std::complex<_Real> >
     MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost
   };
 
-  static inline Real epsilon() { return NumTraits<Real>::epsilon(); }
-  static inline Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
+  inline static Real epsilon() { return NumTraits<Real>::epsilon(); }
+  inline static Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
 };
 
 template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
@@ -157,6 +155,6 @@ struct NumTraits<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
   };
 };
 
-} // end namespace Eigen
+
 
 #endif // EIGEN_NUMTRAITS_H

Eigen/src/Core/PermutationMatrix.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_PERMUTATIONMATRIX_H
 #define EIGEN_PERMUTATIONMATRIX_H
 
-namespace Eigen { 
-
 template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
 
 /** \class PermutationBase
@@ -58,8 +56,6 @@ namespace internal {
 
 template<typename PermutationType, typename MatrixType, int Side, bool Transposed=false>
 struct permut_matrix_product_retval;
-template<typename PermutationType, typename MatrixType, int Side, bool Transposed=false>
-struct permut_sparsematrix_product_retval;
 enum PermPermProduct_t {PermPermProduct};
 
 } // end namespace internal
@@ -515,7 +511,7 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
 
   protected:
 
-    typename IndicesType::Nested m_indices;
+    const typename IndicesType::Nested m_indices;
 };
 
 /** \returns the matrix with the permutation applied to the columns.
@@ -612,7 +608,7 @@ struct permut_matrix_product_retval
 
   protected:
     const PermutationType& m_permutation;
-    typename MatrixType::Nested m_matrix;
+    const typename MatrixType::Nested m_matrix;
 };
 
 /* Template partial specialization for transposed/inverse permutations */
@@ -697,6 +693,4 @@ const PermutationWrapper<const Derived> MatrixBase<Derived>::asPermutation() con
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_PERMUTATIONMATRIX_H

Eigen/src/Core/PlainObjectBase.h

@@ -32,30 +32,15 @@
 # define EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
 #endif
 
-namespace Eigen {
-
 namespace internal {
 
-template<typename Index>
-EIGEN_ALWAYS_INLINE void check_rows_cols_for_overflow(Index rows, Index cols)
-{
-  // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242
-  // we assume Index is signed
-  Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed
-  bool error = (rows < 0  || cols < 0)  ? true
-             : (rows == 0 || cols == 0) ? false
-                                        : (rows > max_index / cols);
-  if (error)
-    throw_std_bad_alloc();
-}
-
-template <typename Derived, typename OtherDerived = Derived, bool IsVector = bool(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
+template <typename Derived, typename OtherDerived = Derived, bool IsVector = static_cast<bool>(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
 
 template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct matrix_swap_impl;
 
 } // end namespace internal
 
-/** \class PlainObjectBase
+/**
   * \brief %Dense storage base class for matrices and arrays.
   *
   * This class can be extended with the help of the plugin mechanism described on the page
@@ -63,29 +48,8 @@ template<typename MatrixTypeA, typename MatrixTypeB, bool SwapPointers> struct m
   *
   * \sa \ref TopicClassHierarchy
   */
-#ifdef EIGEN_PARSED_BY_DOXYGEN
-namespace internal {
-
-// this is a warkaround to doxygen not being able to understand the inheritence logic
-// when it is hidden by the dense_xpr_base helper struct.
-template<typename Derived> struct dense_xpr_base_dispatcher_for_doxygen;// : public MatrixBase<Derived> {};
-/** This class is just a workaround for Doxygen and it does not not actually exist. */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct dense_xpr_base_dispatcher_for_doxygen<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-    : public MatrixBase<Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
-/** This class is just a workaround for Doxygen and it does not not actually exist. */
-template<typename _Scalar, int _Rows, int _Cols, int _Options, int _MaxRows, int _MaxCols>
-struct dense_xpr_base_dispatcher_for_doxygen<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> >
-    : public ArrayBase<Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> > {};
-
-} // namespace internal
-
-template<typename Derived>
-class PlainObjectBase : public internal::dense_xpr_base_dispatcher_for_doxygen<Derived>
-#else
 template<typename Derived>
 class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
-#endif
 {
   public:
     enum { Options = internal::traits<Derived>::Options };
@@ -120,12 +84,14 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     template<typename StrideType> struct StridedConstMapType { typedef Eigen::Map<const Derived, Unaligned, StrideType> type; };
     template<typename StrideType> struct StridedAlignedMapType { typedef Eigen::Map<Derived, Aligned, StrideType> type; };
     template<typename StrideType> struct StridedConstAlignedMapType { typedef Eigen::Map<const Derived, Aligned, StrideType> type; };
+    
 
   protected:
     DenseStorage<Scalar, Base::MaxSizeAtCompileTime, Base::RowsAtCompileTime, Base::ColsAtCompileTime, Options> m_storage;
 
   public:
-    enum { NeedsToAlign = SizeAtCompileTime != Dynamic && (internal::traits<Derived>::Flags & AlignedBit) != 0 };
+    enum { NeedsToAlign = (!(Options&DontAlign))
+                          && SizeAtCompileTime!=Dynamic && ((static_cast<int>(sizeof(Scalar))*SizeAtCompileTime)%16)==0 };
     EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign)
 
     Base& base() { return *static_cast<Base*>(this); }
@@ -234,13 +200,11 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
     {
       #ifdef EIGEN_INITIALIZE_MATRICES_BY_ZERO
-        internal::check_rows_cols_for_overflow(rows, cols);
         Index 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
-        internal::check_rows_cols_for_overflow(rows, cols);
         m_storage.resize(rows*cols, rows, cols);
       #endif
     }
@@ -309,7 +273,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     EIGEN_STRONG_INLINE void resizeLike(const EigenBase<OtherDerived>& _other)
     {
       const OtherDerived& other = _other.derived();
-      internal::check_rows_cols_for_overflow(other.rows(), other.cols());
       const Index othersize = other.rows()*other.cols();
       if(RowsAtCompileTime == 1)
       {
@@ -454,7 +417,6 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       : m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols())
     {
       _check_template_params();
-      internal::check_rows_cols_for_overflow(other.derived().rows(), other.derived().cols());
       Base::operator=(other.derived());
     }
 
@@ -463,71 +425,74 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       * while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned
       * \a data pointers.
       *
+      * These methods do not allow to specify strides. If you need to specify strides, you have to
+      * use the Map class directly.
+      *
       * \see class Map
       */
     //@{
-    static inline ConstMapType Map(const Scalar* data)
+    inline static ConstMapType Map(const Scalar* data)
     { return ConstMapType(data); }
-    static inline MapType Map(Scalar* data)
+    inline static MapType Map(Scalar* data)
     { return MapType(data); }
-    static inline ConstMapType Map(const Scalar* data, Index size)
+    inline static ConstMapType Map(const Scalar* data, Index size)
     { return ConstMapType(data, size); }
-    static inline MapType Map(Scalar* data, Index size)
+    inline static MapType Map(Scalar* data, Index size)
     { return MapType(data, size); }
-    static inline ConstMapType Map(const Scalar* data, Index rows, Index cols)
+    inline static ConstMapType Map(const Scalar* data, Index rows, Index cols)
     { return ConstMapType(data, rows, cols); }
-    static inline MapType Map(Scalar* data, Index rows, Index cols)
+    inline static MapType Map(Scalar* data, Index rows, Index cols)
     { return MapType(data, rows, cols); }
 
-    static inline ConstAlignedMapType MapAligned(const Scalar* data)
+    inline static ConstAlignedMapType MapAligned(const Scalar* data)
     { return ConstAlignedMapType(data); }
-    static inline AlignedMapType MapAligned(Scalar* data)
+    inline static AlignedMapType MapAligned(Scalar* data)
     { return AlignedMapType(data); }
-    static inline ConstAlignedMapType MapAligned(const Scalar* data, Index size)
+    inline static ConstAlignedMapType MapAligned(const Scalar* data, Index size)
     { return ConstAlignedMapType(data, size); }
-    static inline AlignedMapType MapAligned(Scalar* data, Index size)
+    inline static AlignedMapType MapAligned(Scalar* data, Index size)
     { return AlignedMapType(data, size); }
-    static inline ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols)
+    inline static ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols)
     { return ConstAlignedMapType(data, rows, cols); }
-    static inline AlignedMapType MapAligned(Scalar* data, Index rows, Index cols)
+    inline static AlignedMapType MapAligned(Scalar* data, Index rows, Index cols)
     { return AlignedMapType(data, rows, cols); }
 
     template<int Outer, int Inner>
-    static inline typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, const Stride<Outer, Inner>& stride)
+    inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, const Stride<Outer, Inner>& stride)
     { return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, const Stride<Outer, Inner>& stride)
+    inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, const Stride<Outer, Inner>& stride)
     { return typename StridedMapType<Stride<Outer, Inner> >::type(data, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
     { return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, size, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
     { return typename StridedMapType<Stride<Outer, Inner> >::type(data, size, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
     { return typename StridedConstMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
     { return typename StridedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
 
     template<int Outer, int Inner>
-    static inline typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, const Stride<Outer, Inner>& stride)
+    inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, const Stride<Outer, Inner>& stride)
     { return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, const Stride<Outer, Inner>& stride)
+    inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, const Stride<Outer, Inner>& stride)
     { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
     { return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, size, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
     { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, size, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
     { return typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
     template<int Outer, int Inner>
-    static inline typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
     { return typename StridedAlignedMapType<Stride<Outer, Inner> >::type(data, rows, cols, stride); }
     //@}
 
@@ -617,12 +582,8 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
     template<typename T0, typename T1>
     EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, typename internal::enable_if<Base::SizeAtCompileTime!=2,T0>::type* = 0)
     {
-      EIGEN_STATIC_ASSERT(bool(NumTraits<T0>::IsInteger) &&
-                          bool(NumTraits<T1>::IsInteger),
-                          FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED)
       eigen_assert(rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows)
              && cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols));
-      internal::check_rows_cols_for_overflow(rows, cols);      
       m_storage.resize(rows*cols,rows,cols);
       EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
     }
@@ -649,7 +610,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 
   public:
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-    static EIGEN_STRONG_INLINE void _check_template_params()
+    EIGEN_STRONG_INLINE static void _check_template_params()
     {
       EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (Options&RowMajor)==RowMajor)
                         && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (Options&RowMajor)==0)
@@ -680,15 +641,14 @@ struct internal::conservative_resize_like_impl
     if ( ( Derived::IsRowMajor && _this.cols() == cols) || // row-major and we change only the number of rows
          (!Derived::IsRowMajor && _this.rows() == rows) )  // column-major and we change only the number of columns
     {
-      internal::check_rows_cols_for_overflow(rows, cols);
       _this.derived().m_storage.conservativeResize(rows*cols,rows,cols);
     }
     else
     {
       // The storage order does not allow us to use reallocation.
       typename Derived::PlainObject tmp(rows,cols);
-      const Index common_rows = (std::min)(rows, _this.rows());
-      const Index common_cols = (std::min)(cols, _this.cols());
+      const Index common_rows = std::min(rows, _this.rows());
+      const Index common_cols = std::min(cols, _this.cols());
       tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
       _this.derived().swap(tmp);
     }
@@ -721,8 +681,8 @@ struct internal::conservative_resize_like_impl
     {
       // The storage order does not allow us to use reallocation.
       typename Derived::PlainObject tmp(other);
-      const Index common_rows = (std::min)(tmp.rows(), _this.rows());
-      const Index common_cols = (std::min)(tmp.cols(), _this.cols());
+      const Index common_rows = std::min(tmp.rows(), _this.rows());
+      const Index common_cols = std::min(tmp.cols(), _this.cols());
       tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols);
       _this.derived().swap(tmp);
     }
@@ -777,6 +737,4 @@ struct matrix_swap_impl<MatrixTypeA, MatrixTypeB, true>
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_DENSESTORAGEBASE_H

Eigen/src/Core/Product.h

@@ -1,7 +1,8 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -25,89 +26,600 @@
 #ifndef EIGEN_PRODUCT_H
 #define EIGEN_PRODUCT_H
 
-template<typename Lhs, typename Rhs> class Product;
-template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
-
-/** \class Product
+/** \class GeneralProduct
   * \ingroup Core_Module
   *
-  * \brief Expression of the product of two arbitrary matrices or vectors
+  * \brief Expression of the product of two general matrices or vectors
   *
-  * \param Lhs the type of the left-hand side expression
-  * \param Rhs the type of the right-hand side expression
+  * \param LhsNested the type used to store the left-hand side
+  * \param RhsNested the type used to store the right-hand side
+  * \param ProductMode the type of the product
   *
-  * This class represents an expression of the product of two arbitrary matrices.
+  * This class represents an expression of the product of two general matrices.
+  * We call a general matrix, a dense matrix with full storage. For instance,
+  * This excludes triangular, selfadjoint, and sparse matrices.
+  * It is the return type of the operator* between general matrices. Its template
+  * arguments are determined automatically by ProductReturnType. Therefore,
+  * GeneralProduct should never be used direclty. To determine the result type of a
+  * function which involves a matrix product, use ProductReturnType::Type.
   *
+  * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
   */
+template<typename Lhs, typename Rhs, int ProductType = internal::product_type<Lhs,Rhs>::value>
+class GeneralProduct;
+
+enum {
+  Large = 2,
+  Small = 3
+};
 
 namespace internal {
-template<typename Lhs, typename Rhs>
-struct traits<Product<Lhs, Rhs> >
+
+template<int Rows, int Cols, int Depth> struct product_type_selector;
+
+template<int Size, int MaxSize> struct product_size_category
 {
-  typedef MatrixXpr XprKind;
-  typedef typename remove_all<Lhs>::type LhsCleaned;
-  typedef typename remove_all<Rhs>::type RhsCleaned;
-  typedef typename scalar_product_traits<typename traits<LhsCleaned>::Scalar, typename traits<RhsCleaned>::Scalar>::ReturnType Scalar;
-  typedef typename promote_storage_type<typename traits<LhsCleaned>::StorageKind,
-                                        typename traits<RhsCleaned>::StorageKind>::ret StorageKind;
-  typedef typename promote_index_type<typename traits<LhsCleaned>::Index,
-                                      typename traits<RhsCleaned>::Index>::type Index;
-  enum {
-    RowsAtCompileTime = LhsCleaned::RowsAtCompileTime,
-    ColsAtCompileTime = RhsCleaned::ColsAtCompileTime,
-    MaxRowsAtCompileTime = LhsCleaned::MaxRowsAtCompileTime,
-    MaxColsAtCompileTime = RhsCleaned::MaxColsAtCompileTime,
-    Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0), // TODO should be no storage order
-    CoeffReadCost = 0 // TODO CoeffReadCost should not be part of the expression traits
+  enum { is_large = MaxSize == Dynamic ||
+                    Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD,
+         value = is_large  ? Large
+               : Size == 1 ? 1
+                           : Small
   };
 };
+
+template<typename Lhs, typename Rhs> struct product_type
+{
+  typedef typename remove_all<Lhs>::type _Lhs;
+  typedef typename remove_all<Rhs>::type _Rhs;
+  enum {
+    MaxRows  = _Lhs::MaxRowsAtCompileTime,
+    Rows  = _Lhs::RowsAtCompileTime,
+    MaxCols  = _Rhs::MaxColsAtCompileTime,
+    Cols  = _Rhs::ColsAtCompileTime,
+    MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime,
+                                           _Rhs::MaxRowsAtCompileTime),
+    Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime,
+                                        _Rhs::RowsAtCompileTime),
+    LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
+  };
+
+  // the splitting into different lines of code here, introducing the _select enums and the typedef below,
+  // is to work around an internal compiler error with gcc 4.1 and 4.2.
+private:
+  enum {
+    rows_select = product_size_category<Rows,MaxRows>::value,
+    cols_select = product_size_category<Cols,MaxCols>::value,
+    depth_select = product_size_category<Depth,MaxDepth>::value
+  };
+  typedef product_type_selector<rows_select, cols_select, depth_select> selector;
+
+public:
+  enum {
+    value = selector::ret
+  };
+#ifdef EIGEN_DEBUG_PRODUCT
+  static void debug()
+  {
+      EIGEN_DEBUG_VAR(Rows);
+      EIGEN_DEBUG_VAR(Cols);
+      EIGEN_DEBUG_VAR(Depth);
+      EIGEN_DEBUG_VAR(rows_select);
+      EIGEN_DEBUG_VAR(cols_select);
+      EIGEN_DEBUG_VAR(depth_select);
+      EIGEN_DEBUG_VAR(value);
+  }
+#endif
+};
+
+
+/* The following allows to select the kind of product at compile time
+ * based on the three dimensions of the product.
+ * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */
+// FIXME I'm not sure the current mapping is the ideal one.
+template<int M, int N>  struct product_type_selector<M,N,1>              { enum { ret = OuterProduct }; };
+template<int Depth>     struct product_type_selector<1,    1,    Depth>  { enum { ret = InnerProduct }; };
+template<>              struct product_type_selector<1,    1,    1>      { enum { ret = InnerProduct }; };
+template<>              struct product_type_selector<Small,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<1,    Small,Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small,Small,Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small, Large, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
+template<>              struct product_type_selector<Large, Small, 1>    { enum { ret = LazyCoeffBasedProductMode }; };
+template<>              struct product_type_selector<1,    Large,Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<1,    Large,Large>  { enum { ret = GemvProduct }; };
+template<>              struct product_type_selector<1,    Small,Large>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Large,1,    Small>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Large,1,    Large>  { enum { ret = GemvProduct }; };
+template<>              struct product_type_selector<Small,1,    Large>  { enum { ret = CoeffBasedProductMode }; };
+template<>              struct product_type_selector<Small,Small,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Small,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Small,Large,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Large,Large>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Small,Small>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Small,Large,Small>  { enum { ret = GemmProduct }; };
+template<>              struct product_type_selector<Large,Large,Small>  { enum { ret = GemmProduct }; };
+
 } // end namespace internal
 
+/** \class ProductReturnType
+  * \ingroup Core_Module
+  *
+  * \brief Helper class to get the correct and optimized returned type of operator*
+  *
+  * \param Lhs the type of the left-hand side
+  * \param Rhs the type of the right-hand side
+  * \param ProductMode the type of the product (determined automatically by internal::product_mode)
+  *
+  * This class defines the typename Type representing the optimized product expression
+  * between two matrix expressions. In practice, using ProductReturnType<Lhs,Rhs>::Type
+  * is the recommended way to define the result type of a function returning an expression
+  * which involve a matrix product. The class Product should never be
+  * used directly.
+  *
+  * \sa class Product, MatrixBase::operator*(const MatrixBase<OtherDerived>&)
+  */
+template<typename Lhs, typename Rhs, int ProductType>
+struct ProductReturnType
+{
+  // TODO use the nested type to reduce instanciations ????
+//   typedef typename internal::nested<Lhs,Rhs::ColsAtCompileTime>::type LhsNested;
+//   typedef typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type RhsNested;
+
+  typedef GeneralProduct<Lhs/*Nested*/, Rhs/*Nested*/, ProductType> Type;
+};
 
 template<typename Lhs, typename Rhs>
-class Product : public ProductImpl<Lhs,Rhs,typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
-                                                                            typename internal::traits<Rhs>::StorageKind>::ret>
+struct ProductReturnType<Lhs,Rhs,CoeffBasedProductMode>
 {
+  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
+  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
+  typedef CoeffBasedProduct<LhsNested, RhsNested, EvalBeforeAssigningBit | EvalBeforeNestingBit> Type;
+};
+
+template<typename Lhs, typename Rhs>
+struct ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
+{
+  typedef typename internal::nested<Lhs, Rhs::ColsAtCompileTime, typename internal::plain_matrix_type<Lhs>::type >::type LhsNested;
+  typedef typename internal::nested<Rhs, Lhs::RowsAtCompileTime, typename internal::plain_matrix_type<Rhs>::type >::type RhsNested;
+  typedef CoeffBasedProduct<LhsNested, RhsNested, NestByRefBit> Type;
+};
+
+// this is a workaround for sun CC
+template<typename Lhs, typename Rhs>
+struct LazyProductReturnType : public ProductReturnType<Lhs,Rhs,LazyCoeffBasedProductMode>
+{};
+
+/***********************************************************************
+*  Implementation of Inner Vector Vector Product
+***********************************************************************/
+
+// FIXME : maybe the "inner product" could return a Scalar
+// instead of a 1x1 matrix ??
+// Pro: more natural for the user
+// Cons: this could be a problem if in a meta unrolled algorithm a matrix-matrix
+// product ends up to a row-vector times col-vector product... To tackle this use
+// case, we could have a specialization for Block<MatrixType,1,1> with: operator=(Scalar x);
+
+namespace internal {
+
+template<typename Lhs, typename Rhs>
+struct traits<GeneralProduct<Lhs,Rhs,InnerProduct> >
+ : traits<Matrix<typename scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> >
+{};
+
+}
+
+template<typename Lhs, typename Rhs>
+class GeneralProduct<Lhs, Rhs, InnerProduct>
+  : internal::no_assignment_operator,
+    public Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1>
+{
+    typedef Matrix<typename internal::scalar_product_traits<typename Lhs::Scalar, typename Rhs::Scalar>::ReturnType,1,1> Base;
   public:
-    
-    typedef typename ProductImpl<
-        Lhs, Rhs,
-        typename internal::promote_storage_type<typename Lhs::StorageKind,
-                                                typename Rhs::StorageKind>::ret>::Base Base;
-    EIGEN_GENERIC_PUBLIC_INTERFACE(Product)
-
-    typedef typename Lhs::Nested LhsNested;
-    typedef typename Rhs::Nested RhsNested;
-    typedef typename internal::remove_all<LhsNested>::type LhsNestedCleaned;
-    typedef typename internal::remove_all<RhsNested>::type RhsNestedCleaned;
-
-    Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs)
+    GeneralProduct(const Lhs& lhs, const Rhs& rhs)
     {
-      eigen_assert(lhs.cols() == rhs.rows()
-        && "invalid matrix product"
-        && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
+      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
+        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+
+      Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum();
     }
 
-    inline Index rows() const { return m_lhs.rows(); }
-    inline Index cols() const { return m_rhs.cols(); }
-
-    const LhsNestedCleaned& lhs() const { return m_lhs; }
-    const RhsNestedCleaned& rhs() const { return m_rhs; }
-
-  protected:
-
-    const LhsNested m_lhs;
-    const RhsNested m_rhs;
+    /** Convertion to scalar */
+    operator const typename Base::Scalar() const {
+      return Base::coeff(0,0);
+    }
 };
 
+/***********************************************************************
+*  Implementation of Outer Vector Vector Product
+***********************************************************************/
+
+namespace internal {
+template<int StorageOrder> struct outer_product_selector;
+
 template<typename Lhs, typename Rhs>
-class ProductImpl<Lhs,Rhs,Dense> : public internal::dense_xpr_base<Product<Lhs,Rhs> >::type
-{
-    typedef Product<Lhs, Rhs> Derived;
-  public:
+struct traits<GeneralProduct<Lhs,Rhs,OuterProduct> >
+ : traits<ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs> >
+{};
 
-    typedef typename internal::dense_xpr_base<Product<Lhs, Rhs> >::type Base;
-    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
+}
+
+template<typename Lhs, typename Rhs>
+class GeneralProduct<Lhs, Rhs, OuterProduct>
+  : public ProductBase<GeneralProduct<Lhs,Rhs,OuterProduct>, Lhs, Rhs>
+{
+  public:
+    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
+
+    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+    {
+      EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::RealScalar, typename Rhs::RealScalar>::value),
+        YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+    }
+
+    template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
+    {
+      internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha);
+    }
 };
 
+namespace internal {
+
+template<> struct outer_product_selector<ColMajor> {
+  template<typename ProductType, typename Dest>
+  static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
+    typedef typename Dest::Index Index;
+    // FIXME make sure lhs is sequentially stored
+    // FIXME not very good if rhs is real and lhs complex while alpha is real too
+    const Index cols = dest.cols();
+    for (Index j=0; j<cols; ++j)
+      dest.col(j) += (alpha * prod.rhs().coeff(j)) * prod.lhs();
+  }
+};
+
+template<> struct outer_product_selector<RowMajor> {
+  template<typename ProductType, typename Dest>
+  static EIGEN_DONT_INLINE void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha) {
+    typedef typename Dest::Index Index;
+    // FIXME make sure rhs is sequentially stored
+    // FIXME not very good if lhs is real and rhs complex while alpha is real too
+    const Index rows = dest.rows();
+    for (Index i=0; i<rows; ++i)
+      dest.row(i) += (alpha * prod.lhs().coeff(i)) * prod.rhs();
+  }
+};
+
+} // end namespace internal
+
+/***********************************************************************
+*  Implementation of General Matrix Vector Product
+***********************************************************************/
+
+/*  According to the shape/flags of the matrix we have to distinghish 3 different cases:
+ *   1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine
+ *   2 - the matrix is row-major, BLAS compatible and N is large => call fast BLAS-like rowmajor routine
+ *   3 - all other cases are handled using a simple loop along the outer-storage direction.
+ *  Therefore we need a lower level meta selector.
+ *  Furthermore, if the matrix is the rhs, then the product has to be transposed.
+ */
+namespace internal {
+
+template<typename Lhs, typename Rhs>
+struct traits<GeneralProduct<Lhs,Rhs,GemvProduct> >
+ : traits<ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs> >
+{};
+
+template<int Side, int StorageOrder, bool BlasCompatible>
+struct gemv_selector;
+
+} // end namespace internal
+
+template<typename Lhs, typename Rhs>
+class GeneralProduct<Lhs, Rhs, GemvProduct>
+  : public ProductBase<GeneralProduct<Lhs,Rhs,GemvProduct>, Lhs, Rhs>
+{
+  public:
+    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
+
+    typedef typename Lhs::Scalar LhsScalar;
+    typedef typename Rhs::Scalar RhsScalar;
+
+    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+    {
+//       EIGEN_STATIC_ASSERT((internal::is_same<typename Lhs::Scalar, typename Rhs::Scalar>::value),
+//         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
+    }
+
+    enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight };
+    typedef typename internal::conditional<int(Side)==OnTheRight,_LhsNested,_RhsNested>::type MatrixType;
+
+    template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
+    {
+      eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols());
+      internal::gemv_selector<Side,(int(MatrixType::Flags)&RowMajorBit) ? RowMajor : ColMajor,
+                       bool(internal::blas_traits<MatrixType>::HasUsableDirectAccess)>::run(*this, dst, alpha);
+    }
+};
+
+namespace internal {
+
+// The vector is on the left => transposition
+template<int StorageOrder, bool BlasCompatible>
+struct gemv_selector<OnTheLeft,StorageOrder,BlasCompatible>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
+  {
+    Transpose<Dest> destT(dest);
+    enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor };
+    gemv_selector<OnTheRight,OtherStorageOrder,BlasCompatible>
+      ::run(GeneralProduct<Transpose<const typename ProductType::_RhsNested>,Transpose<const typename ProductType::_LhsNested>, GemvProduct>
+        (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha);
+  }
+};
+
+template<typename Scalar,int Size,int MaxSize,bool Cond> struct gemv_static_vector_if;
+
+template<typename Scalar,int Size,int MaxSize>
+struct gemv_static_vector_if<Scalar,Size,MaxSize,false>
+{
+  EIGEN_STRONG_INLINE  Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; }
+};
+
+template<typename Scalar,int Size>
+struct gemv_static_vector_if<Scalar,Size,Dynamic,true>
+{
+  EIGEN_STRONG_INLINE Scalar* data() { return 0; }
+};
+
+template<typename Scalar,int Size,int MaxSize>
+struct gemv_static_vector_if<Scalar,Size,MaxSize,true>
+{
+  #if EIGEN_ALIGN_STATICALLY
+  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize),0> m_data;
+  EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; }
+  #else
+  // Some architectures cannot align on the stack,
+  // => let's manually enforce alignment by allocating more data and return the address of the first aligned element.
+  enum {
+    ForceAlignment  = internal::packet_traits<Scalar>::Vectorizable,
+    PacketSize      = internal::packet_traits<Scalar>::size
+  };
+  internal::plain_array<Scalar,EIGEN_SIZE_MIN_PREFER_FIXED(Size,MaxSize)+(ForceAlignment?PacketSize:0),0> m_data;
+  EIGEN_STRONG_INLINE Scalar* data() {
+    return ForceAlignment
+            ? reinterpret_cast<Scalar*>((reinterpret_cast<size_t>(m_data.array) & ~(size_t(15))) + 16)
+            : m_data.array;
+  }
+  #endif
+};
+
+template<> struct gemv_selector<OnTheRight,ColMajor,true>
+{
+  template<typename ProductType, typename Dest>
+  static inline void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
+  {
+    typedef typename ProductType::Index Index;
+    typedef typename ProductType::LhsScalar   LhsScalar;
+    typedef typename ProductType::RhsScalar   RhsScalar;
+    typedef typename ProductType::Scalar      ResScalar;
+    typedef typename ProductType::RealScalar  RealScalar;
+    typedef typename ProductType::ActualLhsType ActualLhsType;
+    typedef typename ProductType::ActualRhsType ActualRhsType;
+    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
+    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
+    typedef Map<Matrix<ResScalar,Dynamic,1>, Aligned> MappedDest;
+
+    const ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs());
+    const ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs());
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
+                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
+
+    enum {
+      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
+      // on, the other hand it is good for the cache to pack the vector anyways...
+      EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1,
+      ComplexByReal = (NumTraits<LhsScalar>::IsComplex) && (!NumTraits<RhsScalar>::IsComplex),
+      MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal
+    };
+
+    gemv_static_vector_if<ResScalar,Dest::SizeAtCompileTime,Dest::MaxSizeAtCompileTime,MightCannotUseDest> static_dest;
+
+    // this is written like this (i.e., with a ?:) to workaround an ICE with ICC 12
+    bool alphaIsCompatible = (!ComplexByReal) ? true : (imag(actualAlpha)==RealScalar(0));
+    bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible;
+    
+    RhsScalar compatibleAlpha = get_factor<ResScalar,RhsScalar>::run(actualAlpha);
+
+    ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(),
+                                                  evalToDest ? dest.data() : static_dest.data());
+    
+    if(!evalToDest)
+    {
+      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      int size = dest.size();
+      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      #endif
+      if(!alphaIsCompatible)
+      {
+        MappedDest(actualDestPtr, dest.size()).setZero();
+        compatibleAlpha = RhsScalar(1);
+      }
+      else
+        MappedDest(actualDestPtr, dest.size()) = dest;
+    }
+
+    general_matrix_vector_product
+      <Index,LhsScalar,ColMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
+        actualLhs.rows(), actualLhs.cols(),
+        &actualLhs.coeffRef(0,0), actualLhs.outerStride(),
+        actualRhs.data(), actualRhs.innerStride(),
+        actualDestPtr, 1,
+        compatibleAlpha);
+
+    if (!evalToDest)
+    {
+      if(!alphaIsCompatible)
+        dest += actualAlpha * MappedDest(actualDestPtr, dest.size());
+      else
+        dest = MappedDest(actualDestPtr, dest.size());
+    }
+  }
+};
+
+template<> struct gemv_selector<OnTheRight,RowMajor,true>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
+  {
+    typedef typename ProductType::LhsScalar LhsScalar;
+    typedef typename ProductType::RhsScalar RhsScalar;
+    typedef typename ProductType::Scalar    ResScalar;
+    typedef typename ProductType::Index Index;
+    typedef typename ProductType::ActualLhsType ActualLhsType;
+    typedef typename ProductType::ActualRhsType ActualRhsType;
+    typedef typename ProductType::_ActualRhsType _ActualRhsType;
+    typedef typename ProductType::LhsBlasTraits LhsBlasTraits;
+    typedef typename ProductType::RhsBlasTraits RhsBlasTraits;
+
+    typename add_const<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
+    typename add_const<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
+
+    ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
+                                  * RhsBlasTraits::extractScalarFactor(prod.rhs());
+
+    enum {
+      // FIXME find a way to allow an inner stride on the result if packet_traits<Scalar>::size==1
+      // on, the other hand it is good for the cache to pack the vector anyways...
+      DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1
+    };
+
+    gemv_static_vector_if<RhsScalar,_ActualRhsType::SizeAtCompileTime,_ActualRhsType::MaxSizeAtCompileTime,!DirectlyUseRhs> static_rhs;
+
+    ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(),
+        DirectlyUseRhs ? const_cast<RhsScalar*>(actualRhs.data()) : static_rhs.data());
+
+    if(!DirectlyUseRhs)
+    {
+      #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      int size = actualRhs.size();
+      EIGEN_DENSE_STORAGE_CTOR_PLUGIN
+      #endif
+      Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
+    }
+
+    general_matrix_vector_product
+      <Index,LhsScalar,RowMajor,LhsBlasTraits::NeedToConjugate,RhsScalar,RhsBlasTraits::NeedToConjugate>::run(
+        actualLhs.rows(), actualLhs.cols(),
+        &actualLhs.coeffRef(0,0), actualLhs.outerStride(),
+        actualRhsPtr, 1,
+        &dest.coeffRef(0,0), dest.innerStride(),
+        actualAlpha);
+  }
+};
+
+template<> struct gemv_selector<OnTheRight,ColMajor,false>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
+  {
+    typedef typename Dest::Index Index;
+    // TODO makes sure dest is sequentially stored in memory, otherwise use a temp
+    const Index size = prod.rhs().rows();
+    for(Index k=0; k<size; ++k)
+      dest += (alpha*prod.rhs().coeff(k)) * prod.lhs().col(k);
+  }
+};
+
+template<> struct gemv_selector<OnTheRight,RowMajor,false>
+{
+  template<typename ProductType, typename Dest>
+  static void run(const ProductType& prod, Dest& dest, typename ProductType::Scalar alpha)
+  {
+    typedef typename Dest::Index Index;
+    // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp
+    const Index rows = prod.rows();
+    for(Index i=0; i<rows; ++i)
+      dest.coeffRef(i) += alpha * (prod.lhs().row(i).cwiseProduct(prod.rhs().transpose())).sum();
+  }
+};
+
+} // end namespace internal
+
+/***************************************************************************
+* Implementation of matrix base methods
+***************************************************************************/
+
+/** \returns the matrix product of \c *this and \a other.
+  *
+  * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*().
+  *
+  * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*()
+  */
+template<typename Derived>
+template<typename OtherDerived>
+inline const typename ProductReturnType<Derived,OtherDerived>::Type
+MatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) const
+{
+  // A note regarding the function declaration: In MSVC, this function will sometimes
+  // not be inlined since DenseStorage is an unwindable object for dynamic
+  // matrices and product types are holding a member to store the result.
+  // Thus it does not help tagging this function with EIGEN_STRONG_INLINE.
+  enum {
+    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
+                   || OtherDerived::RowsAtCompileTime==Dynamic
+                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
+    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
+    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
+  };
+  // note to the lost user:
+  //    * for a dot product use: v1.dot(v2)
+  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
+    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
+    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
+  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
+#ifdef EIGEN_DEBUG_PRODUCT
+  internal::product_type<Derived,OtherDerived>::debug();
+#endif
+  return typename ProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+}
+
+/** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation.
+  *
+  * The returned product will behave like any other expressions: the coefficients of the product will be
+  * computed once at a time as requested. This might be useful in some extremely rare cases when only
+  * a small and no coherent fraction of the result's coefficients have to be computed.
+  *
+  * \warning This version of the matrix product can be much much slower. So use it only if you know
+  * what you are doing and that you measured a true speed improvement.
+  *
+  * \sa operator*(const MatrixBase&)
+  */
+template<typename Derived>
+template<typename OtherDerived>
+const typename LazyProductReturnType<Derived,OtherDerived>::Type
+MatrixBase<Derived>::lazyProduct(const MatrixBase<OtherDerived> &other) const
+{
+  enum {
+    ProductIsValid =  Derived::ColsAtCompileTime==Dynamic
+                   || OtherDerived::RowsAtCompileTime==Dynamic
+                   || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime),
+    AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime,
+    SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived)
+  };
+  // note to the lost user:
+  //    * for a dot product use: v1.dot(v2)
+  //    * for a coeff-wise product use: v1.cwiseProduct(v2)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes),
+    INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS)
+  EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors),
+    INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION)
+  EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
+
+  return typename LazyProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+}
+
 #endif // EIGEN_PRODUCT_H

Eigen/src/Core/ProductBase.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_PRODUCTBASE_H
 #define EIGEN_PRODUCTBASE_H
 
-namespace Eigen { 
-
 /** \class ProductBase
   * \ingroup Core_Module
   *
@@ -117,10 +115,10 @@ class ProductBase : public MatrixBase<Derived>
     inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,Scalar(1)); }
 
     template<typename Dest>
-    inline void addTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(1)); }
+    inline void addTo(Dest& dst) const { scaleAndAddTo(dst,1); }
 
     template<typename Dest>
-    inline void subTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(-1)); }
+    inline void subTo(Dest& dst) const { scaleAndAddTo(dst,-1); }
 
     template<typename Dest>
     inline void scaleAndAddTo(Dest& dst,Scalar alpha) const { derived().scaleAndAddTo(dst,alpha); }
@@ -154,8 +152,7 @@ class ProductBase : public MatrixBase<Derived>
 #else
       EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
       eigen_assert(this->rows() == 1 && this->cols() == 1);
-      Matrix<Scalar,1,1> result = *this;
-      return result.coeff(row,col);
+      return derived().coeff(row,col);
 #endif
     }
 
@@ -163,8 +160,7 @@ class ProductBase : public MatrixBase<Derived>
     {
       EIGEN_STATIC_ASSERT_SIZE_1x1(Derived)
       eigen_assert(this->rows() == 1 && this->cols() == 1);
-      Matrix<Scalar,1,1> result = *this;
-      return result.coeff(i);
+      return derived().coeff(i);
     }
 
     const Scalar& coeffRef(Index row, Index col) const
@@ -183,8 +179,8 @@ class ProductBase : public MatrixBase<Derived>
 
   protected:
 
-    LhsNested m_lhs;
-    RhsNested m_rhs;
+    const LhsNested m_lhs;
+    const RhsNested m_rhs;
 
     mutable PlainObject m_result;
 };
@@ -260,16 +256,16 @@ class ScaledProduct
     : Base(prod.lhs(),prod.rhs()), m_prod(prod), m_alpha(x) {}
 
     template<typename Dest>
-    inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst, Scalar(1)); }
+    inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,m_alpha); }
 
     template<typename Dest>
-    inline void addTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(1)); }
+    inline void addTo(Dest& dst) const { scaleAndAddTo(dst,m_alpha); }
 
     template<typename Dest>
-    inline void subTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(-1)); }
+    inline void subTo(Dest& dst) const { scaleAndAddTo(dst,-m_alpha); }
 
     template<typename Dest>
-    inline void scaleAndAddTo(Dest& dst,Scalar alpha) const { m_prod.derived().scaleAndAddTo(dst,alpha * m_alpha); }
+    inline void scaleAndAddTo(Dest& dst,Scalar alpha) const { m_prod.derived().scaleAndAddTo(dst,alpha); }
 
     const Scalar& alpha() const { return m_alpha; }
     
@@ -288,6 +284,5 @@ Derived& MatrixBase<Derived>::lazyAssign(const ProductBase<ProductDerived, Lhs,R
   return derived();
 }
 
-} // end namespace Eigen
 
 #endif // EIGEN_PRODUCTBASE_H

Eigen/src/Core/Random.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_RANDOM_H
 #define EIGEN_RANDOM_H
 
-namespace Eigen { 
-
 namespace internal {
 
 template<typename Scalar> struct scalar_random_op {
@@ -162,6 +160,4 @@ PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
   return setRandom();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_RANDOM_H

Eigen/src/Core/Redux.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_REDUX_H
 #define EIGEN_REDUX_H
 
-namespace Eigen { 
-
 namespace internal {
 
 // TODO
@@ -97,7 +95,7 @@ struct redux_novec_unroller
 
   typedef typename Derived::Scalar Scalar;
 
-  static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func)
+  EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func& func)
   {
     return func(redux_novec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
                 redux_novec_unroller<Func, Derived, Start+HalfLength, Length-HalfLength>::run(mat,func));
@@ -114,7 +112,7 @@ struct redux_novec_unroller<Func, Derived, Start, 1>
 
   typedef typename Derived::Scalar Scalar;
 
-  static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func&)
+  EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func&)
   {
     return mat.coeffByOuterInner(outer, inner);
   }
@@ -127,7 +125,7 @@ template<typename Func, typename Derived, int Start>
 struct redux_novec_unroller<Func, Derived, Start, 0>
 {
   typedef typename Derived::Scalar Scalar;
-  static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); }
+  EIGEN_STRONG_INLINE static Scalar run(const Derived&, const Func&) { return Scalar(); }
 };
 
 /*** vectorization ***/
@@ -143,7 +141,7 @@ struct redux_vec_unroller
   typedef typename Derived::Scalar Scalar;
   typedef typename packet_traits<Scalar>::type PacketScalar;
 
-  static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func& func)
+  EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func& func)
   {
     return func.packetOp(
             redux_vec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
@@ -164,7 +162,7 @@ struct redux_vec_unroller<Func, Derived, Start, 1>
   typedef typename Derived::Scalar Scalar;
   typedef typename packet_traits<Scalar>::type PacketScalar;
 
-  static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func&)
+  EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func&)
   {
     return mat.template packetByOuterInner<alignment>(outer, inner);
   }
@@ -216,33 +214,20 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, NoUnrolling>
     const Index size = mat.size();
     eigen_assert(size && "you are using an empty matrix");
     const Index packetSize = packet_traits<Scalar>::size;
-    const Index alignedStart = internal::first_aligned(mat);
+    const Index alignedStart = first_aligned(mat);
     enum {
       alignment = bool(Derived::Flags & DirectAccessBit) || bool(Derived::Flags & AlignedBit)
                 ? Aligned : Unaligned
     };
-    const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize);
-    const Index alignedSize = ((size-alignedStart)/(packetSize))*(packetSize);
-    const Index alignedEnd2 = alignedStart + alignedSize2;
-    const Index alignedEnd  = alignedStart + alignedSize;
+    const Index alignedSize = ((size-alignedStart)/packetSize)*packetSize;
+    const Index alignedEnd = alignedStart + alignedSize;
     Scalar res;
     if(alignedSize)
     {
-      PacketScalar packet_res0 = mat.template packet<alignment>(alignedStart);
-      if(alignedSize>packetSize) // we have at least two packets to partly unroll the loop
-      {
-        PacketScalar packet_res1 = mat.template packet<alignment>(alignedStart+packetSize);
-        for(Index index = alignedStart + 2*packetSize; index < alignedEnd2; index += 2*packetSize)
-        {
-          packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(index));
-          packet_res1 = func.packetOp(packet_res1, mat.template packet<alignment>(index+packetSize));
-        }
-
-        packet_res0 = func.packetOp(packet_res0,packet_res1);
-        if(alignedEnd>alignedEnd2)
-          packet_res0 = func.packetOp(packet_res0, mat.template packet<alignment>(alignedEnd2));
-      }
-      res = func.predux(packet_res0);
+      PacketScalar packet_res = mat.template packet<alignment>(alignedStart);
+      for(Index index = alignedStart + packetSize; index < alignedEnd; index += packetSize)
+        packet_res = func.packetOp(packet_res, mat.template packet<alignment>(index));
+      res = func.predux(packet_res);
 
       for(Index index = 0; index < alignedStart; ++index)
         res = func(res,mat.coeff(index));
@@ -311,7 +296,7 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
     Size = Derived::SizeAtCompileTime,
     VectorizedSize = (Size / PacketSize) * PacketSize
   };
-  static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func)
+  EIGEN_STRONG_INLINE static Scalar run(const Derived& mat, const Func& func)
   {
     eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix");
     Scalar res = func.predux(redux_vec_unroller<Func, Derived, 0, Size / PacketSize>::run(mat,func));
@@ -416,6 +401,4 @@ MatrixBase<Derived>::trace() const
   return derived().diagonal().sum();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_REDUX_H

Eigen/src/Core/Replicate.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_REPLICATE_H
 #define EIGEN_REPLICATE_H
 
-namespace Eigen { 
-
 /**
   * \class Replicate
   * \ingroup Core_Module
@@ -50,10 +48,7 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
   typedef typename MatrixType::Scalar Scalar;
   typedef typename traits<MatrixType>::StorageKind StorageKind;
   typedef typename traits<MatrixType>::XprKind XprKind;
-  enum {
-    Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor
-  };
-  typedef typename nested<MatrixType,Factor>::type MatrixTypeNested;
+  typedef typename nested<MatrixType>::type MatrixTypeNested;
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   enum {
     RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic
@@ -77,8 +72,6 @@ struct traits<Replicate<MatrixType,RowFactor,ColFactor> >
 template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
   : public internal::dense_xpr_base< Replicate<MatrixType,RowFactor,ColFactor> >::type
 {
-    typedef typename internal::traits<Replicate>::MatrixTypeNested MatrixTypeNested;
-    typedef typename internal::traits<Replicate>::_MatrixTypeNested _MatrixTypeNested;
   public:
 
     typedef typename internal::dense_xpr_base<Replicate>::type Base;
@@ -94,7 +87,7 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
     }
 
     template<typename OriginalMatrixType>
-    inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
+    inline Replicate(const OriginalMatrixType& matrix, int rowFactor, int colFactor)
       : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
     {
       EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
@@ -129,13 +122,9 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
       return m_matrix.template packet<LoadMode>(actual_row, actual_col);
     }
 
-    const _MatrixTypeNested& nestedExpression() const
-    { 
-      return m_matrix; 
-    }
 
   protected:
-    MatrixTypeNested m_matrix;
+    const typename MatrixType::Nested m_matrix;
     const internal::variable_if_dynamic<Index, RowFactor> m_rowFactor;
     const internal::variable_if_dynamic<Index, ColFactor> m_colFactor;
 };
@@ -187,6 +176,4 @@ VectorwiseOp<ExpressionType,Direction>::replicate(Index factor) const
           (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_REPLICATE_H

Eigen/src/Core/ReturnByValue.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_RETURNBYVALUE_H
 #define EIGEN_RETURNBYVALUE_H
 
-namespace Eigen {
-
 /** \class ReturnByValue
   * \ingroup Core_Module
   *
@@ -98,6 +96,4 @@ Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_RETURNBYVALUE_H

Eigen/src/Core/Reverse.h

@@ -27,8 +27,6 @@
 #ifndef EIGEN_REVERSE_H
 #define EIGEN_REVERSE_H
 
-namespace Eigen { 
-
 /** \class Reverse
   * \ingroup Core_Module
   *
@@ -185,14 +183,8 @@ template<typename MatrixType, int Direction> class Reverse
       m_matrix.const_cast_derived().template writePacket<LoadMode>(m_matrix.size() - index - PacketSize, internal::preverse(x));
     }
 
-    const typename internal::remove_all<typename MatrixType::Nested>::type& 
-    nestedExpression() const 
-    {
-      return m_matrix;
-    }
-
   protected:
-    typename MatrixType::Nested m_matrix;
+    const typename MatrixType::Nested m_matrix;
 };
 
 /** \returns an expression of the reverse of *this.
@@ -234,6 +226,5 @@ inline void DenseBase<Derived>::reverseInPlace()
   derived() = derived().reverse().eval();
 }
 
-} // end namespace Eigen
 
 #endif // EIGEN_REVERSE_H

Eigen/src/Core/Select.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_SELECT_H
 #define EIGEN_SELECT_H
 
-namespace Eigen { 
-
 /** \class Select
   * \ingroup Core_Module
   *
@@ -103,25 +101,10 @@ class Select : internal::no_assignment_operator,
         return m_else.coeff(i);
     }
 
-    const ConditionMatrixType& conditionMatrix() const
-    {
-      return m_condition;
-    }
-
-    const ThenMatrixType& thenMatrix() const
-    {
-      return m_then;
-    }
-
-    const ElseMatrixType& elseMatrix() const
-    {
-      return m_else;
-    }
-
   protected:
-    typename ConditionMatrixType::Nested m_condition;
-    typename ThenMatrixType::Nested m_then;
-    typename ElseMatrixType::Nested m_else;
+    const typename ConditionMatrixType::Nested m_condition;
+    const typename ThenMatrixType::Nested m_then;
+    const typename ElseMatrixType::Nested m_else;
 };
 
 
@@ -172,6 +155,4 @@ DenseBase<Derived>::select(typename ElseDerived::Scalar thenScalar,
     derived(), ElseDerived::Constant(rows(),cols(),thenScalar), elseMatrix.derived());
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_SELECT_H

Eigen/src/Core/SelfAdjointView.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_SELFADJOINTMATRIX_H
 #define EIGEN_SELFADJOINTMATRIX_H
 
-namespace Eigen { 
-
 /** \class SelfAdjointView
   * \ingroup Core_Module
   *
@@ -84,7 +82,7 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
     };
     typedef typename MatrixType::PlainObject PlainObject;
 
-    inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
+    inline SelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
     {}
 
     inline Index rows() const { return m_matrix.rows(); }
@@ -201,7 +199,7 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
     #endif
 
   protected:
-    MatrixTypeNested m_matrix;
+    const MatrixTypeNested m_matrix;
 };
 
 
@@ -224,7 +222,7 @@ struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), U
     row = (UnrollCount-1) % Derived1::RowsAtCompileTime
   };
 
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount-1, ClearOpposite>::run(dst, src);
 
@@ -238,7 +236,7 @@ struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), U
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, 0, ClearOpposite>
 {
-  static inline void run(Derived1 &, const Derived2 &) {}
+  inline static void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
@@ -249,7 +247,7 @@ struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), U
     row = (UnrollCount-1) % Derived1::RowsAtCompileTime
   };
 
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount-1, ClearOpposite>::run(dst, src);
 
@@ -263,14 +261,14 @@ struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), U
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, 0, ClearOpposite>
 {
-  static inline void run(Derived1 &, const Derived2 &) {}
+  inline static void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -287,7 +285,7 @@ struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Upper, Dyn
 template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, SelfAdjoint|Lower, Dynamic, ClearOpposite>
 {
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
   typedef typename Derived1::Index Index;
     for(Index i = 0; i < dst.rows(); ++i)
@@ -324,6 +322,4 @@ MatrixBase<Derived>::selfadjointView()
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_SELFADJOINTMATRIX_H

Eigen/src/Core/SelfCwiseBinaryOp.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_SELFCWISEBINARYOP_H
 #define EIGEN_SELFCWISEBINARYOP_H
 
-namespace Eigen { 
-
 /** \class SelfCwiseBinaryOp
   * \ingroup Core_Module
   *
@@ -165,16 +163,6 @@ template<typename BinaryOp, typename Lhs, typename Rhs> class SelfCwiseBinaryOp
       return Base::operator=(rhs);
     }
 
-    Lhs& expression() const 
-    { 
-      return m_matrix;
-    }
-
-    const BinaryOp& functor() const 
-    { 
-      return m_functor;
-    }
-
   protected:
     Lhs& m_matrix;
     const BinaryOp& m_functor;
@@ -204,6 +192,4 @@ inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_SELFCWISEBINARYOP_H

Eigen/src/Core/SolveTriangular.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_SOLVETRIANGULAR_H
 #define EIGEN_SOLVETRIANGULAR_H
 
-namespace Eigen { 
-
 namespace internal {
 
 // Forward declarations:
@@ -102,7 +100,7 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
   typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
   static void run(const Lhs& lhs, Rhs& rhs)
   {
-    typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsProductTraits::extract(lhs);
+    const ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
     triangular_solve_matrix<Scalar,Index,Side,Mode,LhsProductTraits::NeedToConjugate,(int(Lhs::Flags) & RowMajorBit) ? RowMajor : ColMajor,
                                (Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor>
       ::run(lhs.rows(), Side==OnTheLeft? rhs.cols() : rhs.rows(), &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.outerStride());
@@ -179,8 +177,10 @@ template<int Side, typename OtherDerived>
 void TriangularView<MatrixType,Mode>::solveInPlace(const MatrixBase<OtherDerived>& _other) const
 {
   OtherDerived& other = _other.const_cast_derived();
-  eigen_assert( cols() == rows() && ((Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols())) );
-  eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
+  eigen_assert(cols() == rows());
+  eigen_assert( (Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols()) );
+  eigen_assert(!(Mode & ZeroDiag));
+  eigen_assert(Mode & (Upper|Lower));
 
   enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit  && OtherDerived::IsVectorAtCompileTime };
   typedef typename internal::conditional<copy,
@@ -255,11 +255,9 @@ template<int Side, typename TriangularType, typename Rhs> struct triangular_solv
 
   protected:
     const TriangularType& m_triangularMatrix;
-    typename Rhs::Nested m_rhs;
+    const typename Rhs::Nested m_rhs;
 };
 
 } // namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_SOLVETRIANGULAR_H

Eigen/src/Core/StableNorm.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_STABLENORM_H
 #define EIGEN_STABLENORM_H
 
-namespace Eigen { 
-
 namespace internal {
 template<typename ExpressionType, typename Scalar>
 inline void stable_norm_kernel(const ExpressionType& bl, Scalar& ssq, Scalar& scale, Scalar& invScale)
@@ -60,9 +58,9 @@ MatrixBase<Derived>::stableNorm() const
 {
   using std::min;
   const Index blockSize = 4096;
-  RealScalar scale(0);
-  RealScalar invScale(1);
-  RealScalar ssq(0); // sum of square
+  RealScalar scale = 0;
+  RealScalar invScale = 1;
+  RealScalar ssq = 0; // sum of square
   enum {
     Alignment = (int(Flags)&DirectAccessBit) || (int(Flags)&AlignedBit) ? 1 : 0
   };
@@ -71,7 +69,7 @@ MatrixBase<Derived>::stableNorm() const
   if (bi>0)
     internal::stable_norm_kernel(this->head(bi), ssq, scale, invScale);
   for (; bi<n; bi+=blockSize)
-    internal::stable_norm_kernel(this->segment(bi,(min)(blockSize, n - bi)).template forceAlignedAccessIf<Alignment>(), ssq, scale, invScale);
+    internal::stable_norm_kernel(this->segment(bi,min(blockSize, n - bi)).template forceAlignedAccessIf<Alignment>(), ssq, scale, invScale);
   return scale * internal::sqrt(ssq);
 }
 
@@ -105,12 +103,12 @@ MatrixBase<Derived>::blueNorm() const
     // For portability, the PORT subprograms "ilmaeh" and "rlmach"
     // are used. For any specific computer, each of the assignment
     // statements can be replaced
-    nbig  = (std::numeric_limits<Index>::max)();            // largest integer
+    nbig  = std::numeric_limits<Index>::max();            // largest integer
     ibeta = std::numeric_limits<RealScalar>::radix;         // base for floating-point numbers
     it    = std::numeric_limits<RealScalar>::digits;        // number of base-beta digits in mantissa
     iemin = std::numeric_limits<RealScalar>::min_exponent;  // minimum exponent
     iemax = std::numeric_limits<RealScalar>::max_exponent;  // maximum exponent
-    rbig  = (std::numeric_limits<RealScalar>::max)();         // largest floating-point number
+    rbig  = std::numeric_limits<RealScalar>::max();         // largest floating-point number
 
     iexp  = -((1-iemin)/2);
     b1    = RealScalar(pow(RealScalar(ibeta),RealScalar(iexp)));  // lower boundary of midrange
@@ -169,8 +167,8 @@ MatrixBase<Derived>::blueNorm() const
   }
   else
     return internal::sqrt(amed);
-  asml = (min)(abig, amed);
-  abig = (max)(abig, amed);
+  asml = min(abig, amed);
+  abig = max(abig, amed);
   if(asml <= abig*relerr)
     return abig;
   else
@@ -189,6 +187,4 @@ MatrixBase<Derived>::hypotNorm() const
   return this->cwiseAbs().redux(internal::scalar_hypot_op<RealScalar>());
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_STABLENORM_H

Eigen/src/Core/Stride.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_STRIDE_H
 #define EIGEN_STRIDE_H
 
-namespace Eigen { 
-
 /** \class Stride
   * \ingroup Core_Module
   *
@@ -118,6 +116,4 @@ class OuterStride : public Stride<Value, 0>
     OuterStride(Index v) : Base(v,0) {}
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_STRIDE_H

Eigen/src/Core/Swap.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_SWAP_H
 #define EIGEN_SWAP_H
 
-namespace Eigen { 
-
 /** \class SwapWrapper
   * \ingroup Core_Module
   *
@@ -54,15 +52,6 @@ template<typename ExpressionType> class SwapWrapper
     inline Index cols() const { return m_expression.cols(); }
     inline Index outerStride() const { return m_expression.outerStride(); }
     inline Index innerStride() const { return m_expression.innerStride(); }
-    
-    typedef typename internal::conditional<
-                       internal::is_lvalue<ExpressionType>::value,
-                       Scalar,
-                       const Scalar
-                     >::type ScalarWithConstIfNotLvalue;
-                     
-    inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
-    inline const Scalar* data() const { return m_expression.data(); }
 
     inline Scalar& coeffRef(Index row, Index col)
     {
@@ -130,12 +119,8 @@ template<typename ExpressionType> class SwapWrapper
       _other.template writePacket<LoadMode>(index, tmp);
     }
 
-    ExpressionType& expression() const { return m_expression; }
-
   protected:
     ExpressionType& m_expression;
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_SWAP_H

Eigen/src/Core/Transpose.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_TRANSPOSE_H
 #define EIGEN_TRANSPOSE_H
 
-namespace Eigen { 
-
 /** \class Transpose
   * \ingroup Core_Module
   *
@@ -93,7 +91,7 @@ template<typename MatrixType> class Transpose
     nestedExpression() { return m_matrix.const_cast_derived(); }
 
   protected:
-    typename MatrixType::Nested m_matrix;
+    const typename MatrixType::Nested m_matrix;
 };
 
 namespace internal {
@@ -154,12 +152,12 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
       return derived().nestedExpression().coeffRef(index);
     }
 
-    inline CoeffReturnType coeff(Index row, Index col) const
+    inline const CoeffReturnType coeff(Index row, Index col) const
     {
       return derived().nestedExpression().coeff(col, row);
     }
 
-    inline CoeffReturnType coeff(Index index) const
+    inline const CoeffReturnType coeff(Index index) const
     {
       return derived().nestedExpression().coeff(index);
     }
@@ -352,14 +350,15 @@ struct blas_traits<SelfCwiseBinaryOp<BinOp,NestedXpr,Rhs> >
 template<bool DestIsTransposed, typename OtherDerived>
 struct check_transpose_aliasing_compile_time_selector
 {
-  enum { ret = bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed };
+  enum { ret = blas_traits<OtherDerived>::IsTransposed != DestIsTransposed
+  };
 };
 
 template<bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB>
 struct check_transpose_aliasing_compile_time_selector<DestIsTransposed,CwiseBinaryOp<BinOp,DerivedA,DerivedB> >
 {
-  enum { ret =    bool(blas_traits<DerivedA>::IsTransposed) != DestIsTransposed
-               || bool(blas_traits<DerivedB>::IsTransposed) != DestIsTransposed
+  enum { ret =    blas_traits<DerivedA>::IsTransposed != DestIsTransposed
+               || blas_traits<DerivedB>::IsTransposed != DestIsTransposed
   };
 };
 
@@ -368,7 +367,7 @@ struct check_transpose_aliasing_run_time_selector
 {
   static bool run(const Scalar* dest, const OtherDerived& src)
   {
-    return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src));
+    return (blas_traits<OtherDerived>::IsTransposed != DestIsTransposed) && (dest!=0 && dest==(Scalar*)extract_data(src));
   }
 };
 
@@ -424,6 +423,4 @@ void DenseBase<Derived>::checkTransposeAliasing(const OtherDerived& other) const
 }
 #endif
 
-} // end namespace Eigen
-
 #endif // EIGEN_TRANSPOSE_H

Eigen/src/Core/Transpositions.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_TRANSPOSITIONS_H
 #define EIGEN_TRANSPOSITIONS_H
 
-namespace Eigen { 
-
 /** \class Transpositions
   * \ingroup Core_Module
   *
@@ -406,7 +404,7 @@ struct transposition_matrix_product_retval
 
   protected:
     const TranspositionType& m_transpositions;
-    typename MatrixType::Nested m_matrix;
+    const typename MatrixType::Nested m_matrix;
 };
 
 } // end namespace internal
@@ -446,6 +444,4 @@ class Transpose<TranspositionsBase<TranspositionsDerived> >
     const TranspositionType& m_transpositions;
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_TRANSPOSITIONS_H

Eigen/src/Core/TriangularMatrix.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_TRIANGULARMATRIX_H
 #define EIGEN_TRIANGULARMATRIX_H
 
-namespace Eigen { 
-
 namespace internal {
   
 template<int Side, typename TriangularType, typename Rhs> struct triangular_solve_retval;
@@ -113,7 +111,6 @@ template<typename Derived> class TriangularBase : public EigenBase<Derived>
       EIGEN_ONLY_USED_FOR_DEBUG(col);
       eigen_assert(col>=0 && col<cols() && row>=0 && row<rows());
       const int mode = int(Mode) & ~SelfAdjoint;
-      EIGEN_ONLY_USED_FOR_DEBUG(mode);
       eigen_assert((mode==Upper && col>=row)
                 || (mode==Lower && col<=row)
                 || ((mode==StrictlyUpper || mode==UnitUpper) && col>row)
@@ -275,8 +272,11 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     inline const TriangularView<MatrixConjugateReturnType,Mode> conjugate() const
     { return m_matrix.conjugate(); }
 
+    /** \sa MatrixBase::adjoint() */
+    inline TriangularView<typename MatrixType::AdjointReturnType,TransposeMode> adjoint()
+    { return m_matrix.adjoint(); }
     /** \sa MatrixBase::adjoint() const */
-    inline const TriangularView<const typename MatrixType::AdjointReturnType,TransposeMode> adjoint() const
+    inline const TriangularView<typename MatrixType::AdjointReturnType,TransposeMode> adjoint() const
     { return m_matrix.adjoint(); }
 
     /** \sa MatrixBase::transpose() */
@@ -287,13 +287,11 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     }
     /** \sa MatrixBase::transpose() const */
     inline const TriangularView<Transpose<MatrixType>,TransposeMode> transpose() const
-    {
-      return m_matrix.transpose();
-    }
+    { return m_matrix.transpose(); }
 
     /** Efficient triangular matrix times vector/matrix product */
     template<typename OtherDerived>
-    TriangularProduct<Mode,true,MatrixType,false,OtherDerived, OtherDerived::IsVectorAtCompileTime>
+    TriangularProduct<Mode,true,MatrixType,false,OtherDerived,OtherDerived::IsVectorAtCompileTime>
     operator*(const MatrixBase<OtherDerived>& rhs) const
     {
       return TriangularProduct
@@ -376,8 +374,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     template<typename OtherDerived>
     void swap(MatrixBase<OtherDerived> const & other)
     {
-      SwapWrapper<MatrixType> swaper(const_cast<MatrixType&>(m_matrix));
-      TriangularView<SwapWrapper<MatrixType>,Mode>(swaper).lazyAssign(other.derived());
+      TriangularView<SwapWrapper<MatrixType>,Mode>(const_cast<MatrixType&>(m_matrix)).lazyAssign(other.derived());
     }
 
     Scalar determinant() const
@@ -435,7 +432,7 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     template<typename ProductDerived, typename Lhs, typename Rhs>
     EIGEN_STRONG_INLINE TriangularView& assignProduct(const ProductBase<ProductDerived, Lhs,Rhs>& prod, const Scalar& alpha);
 
-    MatrixTypeNested m_matrix;
+    const MatrixTypeNested m_matrix;
 };
 
 /***************************************************************************
@@ -454,7 +451,7 @@ struct triangular_assignment_selector
   
   typedef typename Derived1::Scalar Scalar;
 
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     triangular_assignment_selector<Derived1, Derived2, Mode, UnrollCount-1, ClearOpposite>::run(dst, src);
 
@@ -482,7 +479,7 @@ struct triangular_assignment_selector
 template<typename Derived1, typename Derived2, unsigned int Mode, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, Mode, 0, ClearOpposite>
 {
-  static inline void run(Derived1 &, const Derived2 &) {}
+  inline static void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, bool ClearOpposite>
@@ -490,11 +487,11 @@ struct triangular_assignment_selector<Derived1, Derived2, Upper, Dynamic, ClearO
 {
   typedef typename Derived1::Index Index;
   typedef typename Derived1::Scalar Scalar;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
-      Index maxi = (std::min)(j, dst.rows()-1);
+      Index maxi = std::min(j, dst.rows()-1);
       for(Index i = 0; i <= maxi; ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
@@ -508,13 +505,13 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, Lower, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
       for(Index i = j; i < dst.rows(); ++i)
         dst.copyCoeff(i, j, src);
-      Index maxi = (std::min)(j, dst.rows());
+      Index maxi = std::min(j, dst.rows());
       if (ClearOpposite)
         for(Index i = 0; i < maxi; ++i)
           dst.coeffRef(i, j) = static_cast<typename Derived1::Scalar>(0);
@@ -526,11 +523,11 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
-      Index maxi = (std::min)(j, dst.rows());
+      Index maxi = std::min(j, dst.rows());
       for(Index i = 0; i < maxi; ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
@@ -544,13 +541,13 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, StrictlyLower, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
       for(Index i = j+1; i < dst.rows(); ++i)
         dst.copyCoeff(i, j, src);
-      Index maxi = (std::min)(j, dst.rows()-1);
+      Index maxi = std::min(j, dst.rows()-1);
       if (ClearOpposite)
         for(Index i = 0; i <= maxi; ++i)
           dst.coeffRef(i, j) = static_cast<typename Derived1::Scalar>(0);
@@ -562,11 +559,11 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, UnitUpper, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
-      Index maxi = (std::min)(j, dst.rows());
+      Index maxi = std::min(j, dst.rows());
       for(Index i = 0; i < maxi; ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
@@ -582,11 +579,11 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, UnitLower, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  static inline void run(Derived1 &dst, const Derived2 &src)
+  inline static void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
-      Index maxi = (std::min)(j, dst.rows());
+      Index maxi = std::min(j, dst.rows());
       for(Index i = maxi+1; i < dst.rows(); ++i)
         dst.copyCoeff(i, j, src);
       if (ClearOpposite)
@@ -798,7 +795,7 @@ bool MatrixBase<Derived>::isUpperTriangular(RealScalar prec) const
   RealScalar maxAbsOnUpperPart = static_cast<RealScalar>(-1);
   for(Index j = 0; j < cols(); ++j)
   {
-    Index maxi = (std::min)(j, rows()-1);
+    Index maxi = std::min(j, rows()-1);
     for(Index i = 0; i <= maxi; ++i)
     {
       RealScalar absValue = internal::abs(coeff(i,j));
@@ -830,13 +827,11 @@ bool MatrixBase<Derived>::isLowerTriangular(RealScalar prec) const
   RealScalar threshold = maxAbsOnLowerPart * prec;
   for(Index j = 1; j < cols(); ++j)
   {
-    Index maxi = (std::min)(j, rows()-1);
+    Index maxi = std::min(j, rows()-1);
     for(Index i = 0; i < maxi; ++i)
       if(internal::abs(coeff(i, j)) > threshold) return false;
   }
   return true;
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_TRIANGULARMATRIX_H

Eigen/src/Core/VectorBlock.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_VECTORBLOCK_H
 #define EIGEN_VECTORBLOCK_H
 
-namespace Eigen { 
-
 /** \class VectorBlock
   * \ingroup Core_Module
   *
@@ -294,6 +292,5 @@ DenseBase<Derived>::tail() const
   return typename ConstFixedSegmentReturnType<Size>::Type(derived(), size() - Size);
 }
 
-} // end namespace Eigen
 
 #endif // EIGEN_VECTORBLOCK_H

Eigen/src/Core/VectorwiseOp.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_PARTIAL_REDUX_H
 #define EIGEN_PARTIAL_REDUX_H
 
-namespace Eigen { 
-
 /** \class PartialReduxExpr
   * \ingroup Core_Module
   *
@@ -112,7 +110,7 @@ class PartialReduxExpr : internal::no_assignment_operator,
     }
 
   protected:
-    MatrixTypeNested m_matrix;
+    const MatrixTypeNested m_matrix;
     const MemberOp m_functor;
 };
 
@@ -239,10 +237,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     typename ExtendedType<OtherDerived>::Type
     extendedTo(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Vertical, OtherDerived::MaxColsAtCompileTime==1),
-                          YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED)
-      EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(Direction==Horizontal, OtherDerived::MaxRowsAtCompileTime==1),
-                          YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED)
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived);
       return typename ExtendedType<OtherDerived>::Type
                       (other.derived(),
                        Direction==Vertical   ? 1 : m_matrix.rows(),
@@ -423,9 +418,10 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     ExpressionType& operator=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
       //eigen_assert((m_matrix.isNull()) == (other.isNull())); FIXME
-      return const_cast<ExpressionType&>(m_matrix = extendedTo(other.derived()));
+      for(Index j=0; j<subVectors(); ++j)
+        subVector(j) = other;
+      return const_cast<ExpressionType&>(m_matrix);
     }
 
     /** Adds the vector \a other to each subvector of \c *this */
@@ -433,8 +429,9 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     ExpressionType& operator+=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
-      return const_cast<ExpressionType&>(m_matrix += extendedTo(other.derived()));
+      for(Index j=0; j<subVectors(); ++j)
+        subVector(j) += other.derived();
+      return const_cast<ExpressionType&>(m_matrix);
     }
 
     /** Substracts the vector \a other to each subvector of \c *this */
@@ -442,29 +439,8 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     ExpressionType& operator-=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
-      return const_cast<ExpressionType&>(m_matrix -= extendedTo(other.derived()));
-    }
-
-    /** Multiples each subvector of \c *this by the vector \a other */
-    template<typename OtherDerived>
-    ExpressionType& operator*=(const DenseBase<OtherDerived>& other)
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
-      m_matrix *= extendedTo(other.derived());
-      return const_cast<ExpressionType&>(m_matrix);
-    }
-
-    /** Divides each subvector of \c *this by the vector \a other */
-    template<typename OtherDerived>
-    ExpressionType& operator/=(const DenseBase<OtherDerived>& other)
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
-      m_matrix /= extendedTo(other.derived());
+      for(Index j=0; j<subVectors(); ++j)
+        subVector(j) -= other.derived();
       return const_cast<ExpressionType&>(m_matrix);
     }
 
@@ -475,8 +451,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
                   const typename ExtendedType<OtherDerived>::Type>
     operator+(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived);
       return m_matrix + extendedTo(other.derived());
     }
 
@@ -487,39 +462,10 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
                   const typename ExtendedType<OtherDerived>::Type>
     operator-(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
+      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived);
       return m_matrix - extendedTo(other.derived());
     }
 
-    /** Returns the expression where each subvector is the product of the vector \a other
-      * by the corresponding subvector of \c *this */
-    template<typename OtherDerived> EIGEN_STRONG_INLINE
-    CwiseBinaryOp<internal::scalar_product_op<Scalar>,
-                  const ExpressionTypeNestedCleaned,
-                  const typename ExtendedType<OtherDerived>::Type>
-    operator*(const DenseBase<OtherDerived>& other) const
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
-      return m_matrix * extendedTo(other.derived());
-    }
-
-    /** Returns the expression where each subvector is the quotient of the corresponding
-      * subvector of \c *this by the vector \a other */
-    template<typename OtherDerived>
-    CwiseBinaryOp<internal::scalar_quotient_op<Scalar>,
-                  const ExpressionTypeNestedCleaned,
-                  const typename ExtendedType<OtherDerived>::Type>
-    operator/(const DenseBase<OtherDerived>& other) const
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      EIGEN_STATIC_ASSERT_ARRAYXPR(ExpressionType)
-      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
-      return m_matrix / extendedTo(other.derived());
-    }
-
 /////////// Geometry module ///////////
 
     #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS
@@ -563,7 +509,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
   * Example: \include MatrixBase_colwise.cpp
   * Output: \verbinclude MatrixBase_colwise.out
   *
-  * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
+  * \sa rowwise(), class VectorwiseOp
   */
 template<typename Derived>
 inline const typename DenseBase<Derived>::ConstColwiseReturnType
@@ -574,7 +520,7 @@ DenseBase<Derived>::colwise() const
 
 /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
   *
-  * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
+  * \sa rowwise(), class VectorwiseOp
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::ColwiseReturnType
@@ -588,7 +534,7 @@ DenseBase<Derived>::colwise()
   * Example: \include MatrixBase_rowwise.cpp
   * Output: \verbinclude MatrixBase_rowwise.out
   *
-  * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
+  * \sa colwise(), class VectorwiseOp
   */
 template<typename Derived>
 inline const typename DenseBase<Derived>::ConstRowwiseReturnType
@@ -599,7 +545,7 @@ DenseBase<Derived>::rowwise() const
 
 /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
   *
-  * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
+  * \sa colwise(), class VectorwiseOp
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::RowwiseReturnType
@@ -608,6 +554,4 @@ DenseBase<Derived>::rowwise()
   return derived();
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_PARTIAL_REDUX_H

Eigen/src/Core/Visitor.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_VISITOR_H
 #define EIGEN_VISITOR_H
 
-namespace Eigen { 
-
 namespace internal {
 
 template<typename Visitor, typename Derived, int UnrollCount>
@@ -37,7 +35,7 @@ struct visitor_impl
     row = (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
-  static inline void run(const Derived &mat, Visitor& visitor)
+  inline static void run(const Derived &mat, Visitor& visitor)
   {
     visitor_impl<Visitor, Derived, UnrollCount-1>::run(mat, visitor);
     visitor(mat.coeff(row, col), row, col);
@@ -47,7 +45,7 @@ struct visitor_impl
 template<typename Visitor, typename Derived>
 struct visitor_impl<Visitor, Derived, 1>
 {
-  static inline void run(const Derived &mat, Visitor& visitor)
+  inline static void run(const Derived &mat, Visitor& visitor)
   {
     return visitor.init(mat.coeff(0, 0), 0, 0);
   }
@@ -57,7 +55,7 @@ template<typename Visitor, typename Derived>
 struct visitor_impl<Visitor, Derived, Dynamic>
 {
   typedef typename Derived::Index Index;
-  static inline void run(const Derived& mat, Visitor& visitor)
+  inline static void run(const Derived& mat, Visitor& visitor)
   {
     visitor.init(mat.coeff(0,0), 0, 0);
     for(Index i = 1; i < mat.rows(); ++i)
@@ -247,6 +245,4 @@ DenseBase<Derived>::maxCoeff(IndexType* index) const
   return maxVisitor.res;
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_VISITOR_H

Eigen/src/Core/arch/AltiVec/Complex.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_COMPLEX_ALTIVEC_H
 #define EIGEN_COMPLEX_ALTIVEC_H
 
-namespace Eigen {
-
 namespace internal {
 
 static Packet4ui  p4ui_CONJ_XOR = vec_mergeh((Packet4ui)p4i_ZERO, (Packet4ui)p4f_ZERO_);//{ 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
@@ -170,7 +168,7 @@ template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet2cf>(const P
 template<int Offset>
 struct palign_impl<Offset,Packet2cf>
 {
-  static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second)
+  EIGEN_STRONG_INLINE static void run(Packet2cf& first, const Packet2cf& second)
   {
     if (Offset==1)
     {
@@ -227,6 +225,4 @@ template<> EIGEN_STRONG_INLINE Packet2cf pcplxflip<Packet2cf>(const Packet2cf& x
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_COMPLEX_ALTIVEC_H

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

@@ -25,8 +25,6 @@
 #ifndef EIGEN_PACKET_MATH_ALTIVEC_H
 #define EIGEN_PACKET_MATH_ALTIVEC_H
 
-namespace Eigen {
-
 namespace internal {
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
@@ -489,7 +487,7 @@ template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
 template<int Offset>
 struct palign_impl<Offset,Packet4f>
 {
-  static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
+  EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second)
   {
     if (Offset!=0)
       first = vec_sld(first, second, Offset*4);
@@ -499,7 +497,7 @@ struct palign_impl<Offset,Packet4f>
 template<int Offset>
 struct palign_impl<Offset,Packet4i>
 {
-  static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
+  EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second)
   {
     if (Offset!=0)
       first = vec_sld(first, second, Offset*4);
@@ -508,6 +506,4 @@ struct palign_impl<Offset,Packet4i>
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_PACKET_MATH_ALTIVEC_H

Eigen/src/Core/arch/NEON/Complex.h

@@ -25,12 +25,10 @@
 #ifndef EIGEN_COMPLEX_NEON_H
 #define EIGEN_COMPLEX_NEON_H
 
-namespace Eigen {
-
 namespace internal {
 
-static uint32x4_t p4ui_CONJ_XOR = EIGEN_INIT_NEON_PACKET4(0x00000000, 0x80000000, 0x00000000, 0x80000000);
-static uint32x2_t p2ui_CONJ_XOR = EIGEN_INIT_NEON_PACKET2(0x00000000, 0x80000000);
+static uint32x4_t p4ui_CONJ_XOR = { 0x00000000, 0x80000000, 0x00000000, 0x80000000 };
+static uint32x2_t p2ui_CONJ_XOR = { 0x00000000, 0x80000000 };
 
 //---------- float ----------
 struct Packet2cf
@@ -269,6 +267,4 @@ template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, con
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_COMPLEX_NEON_H

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

@@ -27,8 +27,6 @@
 #ifndef EIGEN_PACKET_MATH_NEON_H
 #define EIGEN_PACKET_MATH_NEON_H
 
-namespace Eigen {
-
 namespace internal {
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
@@ -54,16 +52,6 @@ typedef uint32x4_t  Packet4ui;
 #define _EIGEN_DECLARE_CONST_Packet4i(NAME,X) \
   const Packet4i p4i_##NAME = pset1<Packet4i>(X)
 
-#if defined(__llvm__) && !defined(__clang__)
-  //Special treatment for Apple's llvm-gcc, its NEON packet types are unions
-  #define EIGEN_INIT_NEON_PACKET2(X, Y)       {{X, Y}}
-  #define EIGEN_INIT_NEON_PACKET4(X, Y, Z, W) {{X, Y, Z, W}}
-#else
-  //Default initializer for packets
-  #define EIGEN_INIT_NEON_PACKET2(X, Y)       {X, Y}
-  #define EIGEN_INIT_NEON_PACKET4(X, Y, Z, W) {X, Y, Z, W}
-#endif
-    
 #ifndef __pld
 #define __pld(x) asm volatile ( "   pld [%[addr]]\n" :: [addr] "r" (x) : "cc" );
 #endif
@@ -96,7 +84,7 @@ template<> struct packet_traits<int>    : default_packet_traits
   };
 };
 
-#if EIGEN_GNUC_AT_MOST(4,4) && !defined(__llvm__)
+#if EIGEN_GNUC_AT_MOST(4,4)
 // workaround gcc 4.2, 4.3 and 4.4 compilatin issue
 EIGEN_STRONG_INLINE float32x4_t vld1q_f32(const float* x) { return ::vld1q_f32((const float32_t*)x); }
 EIGEN_STRONG_INLINE float32x2_t vld1_f32 (const float* x) { return ::vld1_f32 ((const float32_t*)x); }
@@ -112,12 +100,12 @@ template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from)   {
 
 template<> EIGEN_STRONG_INLINE Packet4f plset<float>(const float& a)
 {
-  Packet4f countdown = EIGEN_INIT_NEON_PACKET4(0, 1, 2, 3);
+  Packet4f countdown = { 0, 1, 2, 3 };
   return vaddq_f32(pset1<Packet4f>(a), countdown);
 }
 template<> EIGEN_STRONG_INLINE Packet4i plset<int>(const int& a)
 {
-  Packet4i countdown = EIGEN_INIT_NEON_PACKET4(0, 1, 2, 3);
+  Packet4i countdown = { 0, 1, 2, 3 };
   return vaddq_s32(pset1<Packet4i>(a), countdown);
 }
 
@@ -160,8 +148,7 @@ template<> EIGEN_STRONG_INLINE Packet4i pdiv<Packet4i>(const Packet4i& /*a*/, co
 }
 
 // for some weird raisons, it has to be overloaded for packet of integers
-template<> EIGEN_STRONG_INLINE Packet4f pmadd(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return vmlaq_f32(c,a,b); }
-template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return vmlaq_s32(c,a,b); }
+template<> EIGEN_STRONG_INLINE Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return padd(pmul(a,b), c); }
 
 template<> EIGEN_STRONG_INLINE Packet4f pmin<Packet4f>(const Packet4f& a, const Packet4f& b) { return vminq_f32(a,b); }
 template<> EIGEN_STRONG_INLINE Packet4i pmin<Packet4i>(const Packet4i& a, const Packet4i& b) { return vminq_s32(a,b); }
@@ -408,32 +395,26 @@ template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
   return s[0];
 }
 
-// this PALIGN_NEON business is to work around a bug in LLVM Clang 3.0 causing incorrect compilation errors,
-// see bug 347 and this LLVM bug: http://llvm.org/bugs/show_bug.cgi?id=11074
-#define PALIGN_NEON(Offset,Type,Command) \
-template<>\
-struct palign_impl<Offset,Type>\
-{\
-    EIGEN_STRONG_INLINE static void run(Type& first, const Type& second)\
-    {\
-        if (Offset!=0)\
-            first = Command(first, second, Offset);\
-    }\
-};\
+template<int Offset>
+struct palign_impl<Offset,Packet4f>
+{
+  EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second)
+  {
+    if (Offset!=0)
+      first = vextq_f32(first, second, Offset);
+  }
+};
 
-PALIGN_NEON(0,Packet4f,vextq_f32)
-PALIGN_NEON(1,Packet4f,vextq_f32)
-PALIGN_NEON(2,Packet4f,vextq_f32)
-PALIGN_NEON(3,Packet4f,vextq_f32)
-PALIGN_NEON(0,Packet4i,vextq_s32)
-PALIGN_NEON(1,Packet4i,vextq_s32)
-PALIGN_NEON(2,Packet4i,vextq_s32)
-PALIGN_NEON(3,Packet4i,vextq_s32)
-    
-#undef PALIGN_NEON
+template<int Offset>
+struct palign_impl<Offset,Packet4i>
+{
+  EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second)
+  {
+    if (Offset!=0)
+      first = vextq_s32(first, second, Offset);
+  }
+};
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_PACKET_MATH_NEON_H

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

@@ -25,8 +25,6 @@
 #ifndef EIGEN_COMPLEX_SSE_H
 #define EIGEN_COMPLEX_SSE_H
 
-namespace Eigen {
-
 namespace internal {
 
 //---------- float ----------
@@ -104,7 +102,7 @@ template<> EIGEN_STRONG_INLINE Packet2cf pset1<Packet2cf>(const std::complex<flo
   Packet2cf res;
   #if EIGEN_GNUC_AT_MOST(4,2)
   // workaround annoying "may be used uninitialized in this function" warning with gcc 4.2
-  res.v = _mm_loadl_pi(_mm_set1_ps(0.0f), reinterpret_cast<const __m64*>(&from));
+  res.v = _mm_loadl_pi(_mm_set1_ps(0.0f), (const __m64*)&from);
   #else
   res.v = _mm_loadl_pi(res.v, (const __m64*)&from);
   #endif
@@ -153,7 +151,7 @@ template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet2cf>(const P
 template<int Offset>
 struct palign_impl<Offset,Packet2cf>
 {
-  static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second)
+  EIGEN_STRONG_INLINE static void run(Packet2cf& first, const Packet2cf& second)
   {
     if (Offset==1)
     {
@@ -352,7 +350,7 @@ template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet1cd>(const
 template<int Offset>
 struct palign_impl<Offset,Packet1cd>
 {
-  static EIGEN_STRONG_INLINE void run(Packet1cd& /*first*/, const Packet1cd& /*second*/)
+  EIGEN_STRONG_INLINE static void run(Packet1cd& /*first*/, const Packet1cd& /*second*/)
   {
     // FIXME is it sure we never have to align a Packet1cd?
     // Even though a std::complex<double> has 16 bytes, it is not necessarily aligned on a 16 bytes boundary...
@@ -446,6 +444,4 @@ EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_COMPLEX_SSE_H

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

@@ -30,8 +30,6 @@
 #ifndef EIGEN_MATH_FUNCTIONS_SSE_H
 #define EIGEN_MATH_FUNCTIONS_SSE_H
 
-namespace Eigen {
-
 namespace internal {
 
 template<> EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_UNUSED
@@ -394,6 +392,4 @@ Packet4f psqrt<Packet4f>(const Packet4f& _x)
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_MATH_FUNCTIONS_SSE_H

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

@@ -25,8 +25,6 @@
 #ifndef EIGEN_PACKET_MATH_SSE_H
 #define EIGEN_PACKET_MATH_SSE_H
 
-namespace Eigen {
-
 namespace internal {
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
@@ -112,18 +110,9 @@ template<> struct unpacket_traits<Packet4f> { typedef float  type; enum {size=4}
 template<> struct unpacket_traits<Packet2d> { typedef double type; enum {size=2}; };
 template<> struct unpacket_traits<Packet4i> { typedef int    type; enum {size=4}; };
 
-#if defined(_MSC_VER) && (_MSC_VER==1500)
-// Workaround MSVC 9 internal compiler error.
-// TODO: It has been detected with win64 builds (amd64), so let's check whether it also happens in 32bits+SSE mode
-// TODO: let's check whether there does not exist a better fix, like adding a pset0() function. (it crashed on pset1(0)).
-template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&  from) { return _mm_set_ps(from,from,from,from); }
-template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double& from) { return _mm_set_pd(from,from); }
-template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from) { return _mm_set_epi32(from,from,from,from); }
-#else
 template<> EIGEN_STRONG_INLINE Packet4f pset1<Packet4f>(const float&  from) { return _mm_set1_ps(from); }
 template<> EIGEN_STRONG_INLINE Packet2d pset1<Packet2d>(const double& from) { return _mm_set1_pd(from); }
 template<> EIGEN_STRONG_INLINE Packet4i pset1<Packet4i>(const int&    from) { return _mm_set1_epi32(from); }
-#endif
 
 template<> EIGEN_STRONG_INLINE Packet4f plset<float>(const float& a) { return _mm_add_ps(pset1<Packet4f>(a), _mm_set_ps(3,2,1,0)); }
 template<> EIGEN_STRONG_INLINE Packet2d plset<double>(const double& a) { return _mm_add_pd(pset1<Packet2d>(a),_mm_set_pd(1,0)); }
@@ -293,7 +282,7 @@ template<> EIGEN_STRONG_INLINE Packet4i ploadu<Packet4i>(const int* from)
 
 template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float*   from)
 {
-  return vec4f_swizzle1(_mm_castpd_ps(_mm_load_sd(reinterpret_cast<const double*>(from))), 0, 0, 1, 1);
+  return vec4f_swizzle1(_mm_castpd_ps(_mm_load_sd((const double*)from)), 0, 0, 1, 1);
 }
 template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double*  from)
 { return pset1<Packet2d>(from[0]); }
@@ -313,8 +302,8 @@ template<> EIGEN_STRONG_INLINE void pstoreu<double>(double* to, const Packet2d&
   _mm_storel_pd((to), from);
   _mm_storeh_pd((to+1), from);
 }
-template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*  to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast<double*>(to), _mm_castps_pd(from)); }
-template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*      to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu(reinterpret_cast<double*>(to), _mm_castsi128_pd(from)); }
+template<> EIGEN_STRONG_INLINE void pstoreu<float>(float*  to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, _mm_castps_pd(from)); }
+template<> EIGEN_STRONG_INLINE void pstoreu<int>(int*      to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE pstoreu((double*)to, _mm_castsi128_pd(from)); }
 
 // some compilers might be tempted to perform multiple moves instead of using a vector path.
 template<> EIGEN_STRONG_INLINE void pstore1<Packet4f>(float* to, const float& a)
@@ -552,7 +541,7 @@ template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
 template<int Offset>
 struct palign_impl<Offset,Packet4f>
 {
-  static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
+  EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second)
   {
     if (Offset!=0)
       first = _mm_castsi128_ps(_mm_alignr_epi8(_mm_castps_si128(second), _mm_castps_si128(first), Offset*4));
@@ -562,7 +551,7 @@ struct palign_impl<Offset,Packet4f>
 template<int Offset>
 struct palign_impl<Offset,Packet4i>
 {
-  static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
+  EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second)
   {
     if (Offset!=0)
       first = _mm_alignr_epi8(second,first, Offset*4);
@@ -572,7 +561,7 @@ struct palign_impl<Offset,Packet4i>
 template<int Offset>
 struct palign_impl<Offset,Packet2d>
 {
-  static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second)
+  EIGEN_STRONG_INLINE static void run(Packet2d& first, const Packet2d& second)
   {
     if (Offset==1)
       first = _mm_castsi128_pd(_mm_alignr_epi8(_mm_castpd_si128(second), _mm_castpd_si128(first), 8));
@@ -583,7 +572,7 @@ struct palign_impl<Offset,Packet2d>
 template<int Offset>
 struct palign_impl<Offset,Packet4f>
 {
-  static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
+  EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second)
   {
     if (Offset==1)
     {
@@ -606,7 +595,7 @@ struct palign_impl<Offset,Packet4f>
 template<int Offset>
 struct palign_impl<Offset,Packet4i>
 {
-  static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
+  EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second)
   {
     if (Offset==1)
     {
@@ -629,7 +618,7 @@ struct palign_impl<Offset,Packet4i>
 template<int Offset>
 struct palign_impl<Offset,Packet2d>
 {
-  static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second)
+  EIGEN_STRONG_INLINE static void run(Packet2d& first, const Packet2d& second)
   {
     if (Offset==1)
     {
@@ -642,6 +631,4 @@ struct palign_impl<Offset,Packet2d>
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_PACKET_MATH_SSE_H

Eigen/src/Core/products/CoeffBasedProduct.h

@@ -26,8 +26,6 @@
 #ifndef EIGEN_COEFFBASED_PRODUCT_H
 #define EIGEN_COEFFBASED_PRODUCT_H
 
-namespace Eigen { 
-
 namespace internal {
 
 /*********************************************************************************
@@ -226,8 +224,8 @@ class CoeffBasedProduct
     { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this).diagonal(index); }
 
   protected:
-    typename internal::add_const_on_value_type<LhsNested>::type m_lhs;
-    typename internal::add_const_on_value_type<RhsNested>::type m_rhs;
+    const LhsNested m_lhs;
+    const RhsNested m_rhs;
 
     mutable PlainObject m_result;
 };
@@ -254,7 +252,7 @@ template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<DefaultTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     product_coeff_impl<DefaultTraversal, UnrollingIndex-1, Lhs, Rhs, RetScalar>::run(row, col, lhs, rhs, res);
     res += lhs.coeff(row, UnrollingIndex) * rhs.coeff(UnrollingIndex, col);
@@ -265,7 +263,7 @@ template<typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     res = lhs.coeff(row, 0) * rhs.coeff(0, col);
   }
@@ -275,7 +273,7 @@ template<typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<DefaultTraversal, Dynamic, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res)
   {
     eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
     res = lhs.coeff(row, 0) * rhs.coeff(0, col);
@@ -293,7 +291,7 @@ struct product_coeff_vectorized_unroller
 {
   typedef typename Lhs::Index Index;
   enum { PacketSize = packet_traits<typename Lhs::Scalar>::size };
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
   {
     product_coeff_vectorized_unroller<UnrollingIndex-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
     pres = padd(pres, pmul( lhs.template packet<Aligned>(row, UnrollingIndex) , rhs.template packet<Aligned>(UnrollingIndex, col) ));
@@ -304,7 +302,7 @@ template<typename Lhs, typename Rhs, typename Packet>
 struct product_coeff_vectorized_unroller<0, Lhs, Rhs, Packet>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
   {
     pres = pmul(lhs.template packet<Aligned>(row, 0) , rhs.template packet<Aligned>(0, col));
   }
@@ -316,7 +314,7 @@ struct product_coeff_impl<InnerVectorizedTraversal, UnrollingIndex, Lhs, Rhs, Re
   typedef typename Lhs::PacketScalar Packet;
   typedef typename Lhs::Index Index;
   enum { PacketSize = packet_traits<typename Lhs::Scalar>::size };
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     Packet pres;
     product_coeff_vectorized_unroller<UnrollingIndex+1-PacketSize, Lhs, Rhs, Packet>::run(row, col, lhs, rhs, pres);
@@ -329,7 +327,7 @@ template<typename Lhs, typename Rhs, int LhsRows = Lhs::RowsAtCompileTime, int R
 struct product_coeff_vectorized_dyn_selector
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.row(row).transpose().cwiseProduct(rhs.col(col)).sum();
   }
@@ -341,7 +339,7 @@ template<typename Lhs, typename Rhs, int RhsCols>
 struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,RhsCols>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.transpose().cwiseProduct(rhs.col(col)).sum();
   }
@@ -351,7 +349,7 @@ template<typename Lhs, typename Rhs, int LhsRows>
 struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,LhsRows,1>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.row(row).transpose().cwiseProduct(rhs).sum();
   }
@@ -361,7 +359,7 @@ template<typename Lhs, typename Rhs>
 struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,1>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.transpose().cwiseProduct(rhs).sum();
   }
@@ -371,7 +369,7 @@ template<typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<InnerVectorizedTraversal, Dynamic, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     product_coeff_vectorized_dyn_selector<Lhs,Rhs>::run(row, col, lhs, rhs, res);
   }
@@ -385,7 +383,7 @@ template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int Lo
 struct product_packet_impl<RowMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
   {
     product_packet_impl<RowMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
     res =  pmadd(pset1<Packet>(lhs.coeff(row, UnrollingIndex)), rhs.template packet<LoadMode>(UnrollingIndex, col), res);
@@ -396,7 +394,7 @@ template<int UnrollingIndex, typename Lhs, typename Rhs, typename Packet, int Lo
 struct product_packet_impl<ColMajor, UnrollingIndex, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
   {
     product_packet_impl<ColMajor, UnrollingIndex-1, Lhs, Rhs, Packet, LoadMode>::run(row, col, lhs, rhs, res);
     res =  pmadd(lhs.template packet<LoadMode>(row, UnrollingIndex), pset1<Packet>(rhs.coeff(UnrollingIndex, col)), res);
@@ -407,7 +405,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
   {
     res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
   }
@@ -417,7 +415,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
   {
     res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
   }
@@ -427,7 +425,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
   {
     eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
     res = pmul(pset1<Packet>(lhs.coeff(row, 0)),rhs.template packet<LoadMode>(0, col));
@@ -440,7 +438,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
+  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
   {
     eigen_assert(lhs.cols()>0 && "you are using a non initialized matrix");
     res = pmul(lhs.template packet<LoadMode>(row, 0), pset1<Packet>(rhs.coeff(0, col)));
@@ -451,6 +449,4 @@ struct product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
 
 } // end namespace internal
 
-} // end namespace Eigen
-
 #endif // EIGEN_COEFFBASED_PRODUCT_H

Eigen/src/Core/products/GeneralBlockPanelKernel.h

@@ -25,25 +25,24 @@
 #ifndef EIGEN_GENERAL_BLOCK_PANEL_H
 #define EIGEN_GENERAL_BLOCK_PANEL_H
 
-namespace Eigen { 
-
 namespace internal {
 
 template<typename _LhsScalar, typename _RhsScalar, bool _ConjLhs=false, bool _ConjRhs=false>
 class gebp_traits;
 
-
-/** \internal \returns b if a<=0, and returns a otherwise. */
-inline std::ptrdiff_t manage_caching_sizes_helper(std::ptrdiff_t a, std::ptrdiff_t b)
-{
-  return a<=0 ? b : a;
-}
-
 /** \internal */
 inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1=0, std::ptrdiff_t* l2=0)
 {
-  static std::ptrdiff_t m_l1CacheSize = manage_caching_sizes_helper(queryL1CacheSize(),8 * 1024);
-  static std::ptrdiff_t m_l2CacheSize = manage_caching_sizes_helper(queryTopLevelCacheSize(),1*1024*1024);
+  static std::ptrdiff_t m_l1CacheSize = 0;
+  static std::ptrdiff_t m_l2CacheSize = 0;
+  if(m_l1CacheSize==0)
+  {
+    m_l1CacheSize = queryL1CacheSize();
+    m_l2CacheSize = queryTopLevelCacheSize();
+
+    if(m_l1CacheSize<=0) m_l1CacheSize = 8 * 1024;
+    if(m_l2CacheSize<=0) m_l2CacheSize = 1 * 1024 * 1024;
+  }
 
   if(action==SetAction)
   {
@@ -82,7 +81,6 @@ inline void manage_caching_sizes(Action action, std::ptrdiff_t* l1=0, std::ptrdi
 template<typename LhsScalar, typename RhsScalar, int KcFactor>
 void computeProductBlockingSizes(std::ptrdiff_t& k, std::ptrdiff_t& m, std::ptrdiff_t& n)
 {
-  EIGEN_UNUSED_VARIABLE(n);
   // Explanations:
   // Let's recall the product algorithms form kc x nc horizontal panels B' on the rhs and
   // mc x kc blocks A' on the lhs. A' has to fit into L2 cache. Moreover, B' is processed
@@ -104,6 +102,7 @@ void computeProductBlockingSizes(std::ptrdiff_t& k, std::ptrdiff_t& m, std::ptrd
   k = std::min<std::ptrdiff_t>(k, l1/kdiv);
   std::ptrdiff_t _m = k>0 ? l2/(4 * sizeof(LhsScalar) * k) : 0;
   if(_m<m) m = _m & mr_mask;
+  n = n;
 }
 
 template<typename LhsScalar, typename RhsScalar>
@@ -119,14 +118,14 @@ inline void computeProductBlockingSizes(std::ptrdiff_t& k, std::ptrdiff_t& m, st
   // FIXME (a bit overkill maybe ?)
 
   template<typename CJ, typename A, typename B, typename C, typename T> struct gebp_madd_selector {
-    EIGEN_ALWAYS_INLINE static void run(const CJ& cj, A& a, B& b, C& c, T& /*t*/)
+    EIGEN_STRONG_INLINE EIGEN_ALWAYS_INLINE_ATTRIB static void run(const CJ& cj, A& a, B& b, C& c, T& /*t*/)
     {
       c = cj.pmadd(a,b,c);
     }
   };
 
   template<typename CJ, typename T> struct gebp_madd_selector<CJ,T,T,T,T> {
-    EIGEN_ALWAYS_INLINE static void run(const CJ& cj, T& a, T& b, T& c, T& t)
+    EIGEN_STRONG_INLINE EIGEN_ALWAYS_INLINE_ATTRIB static void run(const CJ& cj, T& a, T& b, T& c, T& t)
     {
       t = b; t = cj.pmul(a,t); c = padd(c,t);
     }
@@ -537,7 +536,7 @@ struct gebp_kernel
     ResPacketSize = Traits::ResPacketSize
   };
 
-  EIGEN_DONT_INLINE EIGEN_FLATTEN_ATTRIB
+  EIGEN_FLATTEN_ATTRIB
   void operator()(ResScalar* res, Index resStride, const LhsScalar* blockA, const RhsScalar* blockB, Index rows, Index depth, Index cols, ResScalar alpha,
                   Index strideA=-1, Index strideB=-1, Index offsetA=0, Index offsetB=0, RhsScalar* unpackedB = 0)
   {
@@ -599,64 +598,64 @@ struct gebp_kernel
           if(nr==2)
           {
             LhsPacket A0, A1;
-            RhsPacket B_0;
+            RhsPacket B0;
             RhsPacket T0;
             
 EIGEN_ASM_COMMENT("mybegin2");
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
+            traits.loadRhs(&blB[1*RhsProgress], B0);
+            traits.madd(A0,B0,C1,T0);
+            traits.madd(A1,B0,C5,B0);
 
             traits.loadLhs(&blA[2*LhsProgress], A0);
             traits.loadLhs(&blA[3*LhsProgress], A1);
-            traits.loadRhs(&blB[2*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[3*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
+            traits.loadRhs(&blB[2*RhsProgress], B0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
+            traits.loadRhs(&blB[3*RhsProgress], B0);
+            traits.madd(A0,B0,C1,T0);
+            traits.madd(A1,B0,C5,B0);
 
             traits.loadLhs(&blA[4*LhsProgress], A0);
             traits.loadLhs(&blA[5*LhsProgress], A1);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[5*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
+            traits.loadRhs(&blB[4*RhsProgress], B0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
+            traits.loadRhs(&blB[5*RhsProgress], B0);
+            traits.madd(A0,B0,C1,T0);
+            traits.madd(A1,B0,C5,B0);
 
             traits.loadLhs(&blA[6*LhsProgress], A0);
             traits.loadLhs(&blA[7*LhsProgress], A1);
-            traits.loadRhs(&blB[6*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[7*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
+            traits.loadRhs(&blB[6*RhsProgress], B0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
+            traits.loadRhs(&blB[7*RhsProgress], B0);
+            traits.madd(A0,B0,C1,T0);
+            traits.madd(A1,B0,C5,B0);
 EIGEN_ASM_COMMENT("myend");
           }
           else
           {
 EIGEN_ASM_COMMENT("mybegin4");
             LhsPacket A0, A1;
-            RhsPacket B_0, B1, B2, B3;
+            RhsPacket B0, B1, B2, B3;
             RhsPacket T0;
             
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
 
-            traits.madd(A0,B_0,C0,T0);
+            traits.madd(A0,B0,C0,T0);
             traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.madd(A1,B_0,C4,B_0);
+            traits.madd(A1,B0,C4,B0);
             traits.loadRhs(&blB[3*RhsProgress], B3);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
+            traits.loadRhs(&blB[4*RhsProgress], B0);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.loadRhs(&blB[5*RhsProgress], B1);
@@ -668,9 +667,9 @@ EIGEN_ASM_COMMENT("mybegin4");
             traits.madd(A1,B3,C7,B3);
             traits.loadLhs(&blA[3*LhsProgress], A1);
             traits.loadRhs(&blB[7*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[8*RhsProgress], B_0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
+            traits.loadRhs(&blB[8*RhsProgress], B0);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.loadRhs(&blB[9*RhsProgress], B1);
@@ -683,9 +682,9 @@ EIGEN_ASM_COMMENT("mybegin4");
             traits.loadLhs(&blA[5*LhsProgress], A1);
             traits.loadRhs(&blB[11*RhsProgress], B3);
 
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[12*RhsProgress], B_0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
+            traits.loadRhs(&blB[12*RhsProgress], B0);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.loadRhs(&blB[13*RhsProgress], B1);
@@ -697,8 +696,8 @@ EIGEN_ASM_COMMENT("mybegin4");
             traits.madd(A1,B3,C7,B3);
             traits.loadLhs(&blA[7*LhsProgress], A1);
             traits.loadRhs(&blB[15*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.madd(A0,B2,C2,T0);
@@ -716,32 +715,32 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsPacket A0, A1;
-            RhsPacket B_0;
+            RhsPacket B0;
             RhsPacket T0;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
-            traits.madd(A0,B_0,C0,T0);
-            traits.madd(A1,B_0,C4,B_0);
-            traits.loadRhs(&blB[1*RhsProgress], B_0);
-            traits.madd(A0,B_0,C1,T0);
-            traits.madd(A1,B_0,C5,B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.madd(A0,B0,C0,T0);
+            traits.madd(A1,B0,C4,B0);
+            traits.loadRhs(&blB[1*RhsProgress], B0);
+            traits.madd(A0,B0,C1,T0);
+            traits.madd(A1,B0,C5,B0);
           }
           else
           {
             LhsPacket A0, A1;
-            RhsPacket B_0, B1, B2, B3;
+            RhsPacket B0, B1, B2, B3;
             RhsPacket T0;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
 
-            traits.madd(A0,B_0,C0,T0);
+            traits.madd(A0,B0,C0,T0);
             traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.madd(A1,B_0,C4,B_0);
+            traits.madd(A1,B0,C4,B0);
             traits.loadRhs(&blB[3*RhsProgress], B3);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
@@ -828,42 +827,42 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsPacket A0;
-            RhsPacket B_0, B1;
+            RhsPacket B0, B1;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[2*RhsProgress], B_0);
+            traits.madd(A0,B0,C0,B0);
+            traits.loadRhs(&blB[2*RhsProgress], B0);
             traits.madd(A0,B1,C1,B1);
             traits.loadLhs(&blA[1*LhsProgress], A0);
             traits.loadRhs(&blB[3*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
+            traits.madd(A0,B0,C0,B0);
+            traits.loadRhs(&blB[4*RhsProgress], B0);
             traits.madd(A0,B1,C1,B1);
             traits.loadLhs(&blA[2*LhsProgress], A0);
             traits.loadRhs(&blB[5*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[6*RhsProgress], B_0);
+            traits.madd(A0,B0,C0,B0);
+            traits.loadRhs(&blB[6*RhsProgress], B0);
             traits.madd(A0,B1,C1,B1);
             traits.loadLhs(&blA[3*LhsProgress], A0);
             traits.loadRhs(&blB[7*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
+            traits.madd(A0,B0,C0,B0);
             traits.madd(A0,B1,C1,B1);
           }
           else
           {
             LhsPacket A0;
-            RhsPacket B_0, B1, B2, B3;
+            RhsPacket B0, B1, B2, B3;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
 
-            traits.madd(A0,B_0,C0,B_0);
+            traits.madd(A0,B0,C0,B0);
             traits.loadRhs(&blB[2*RhsProgress], B2);
             traits.loadRhs(&blB[3*RhsProgress], B3);
-            traits.loadRhs(&blB[4*RhsProgress], B_0);
+            traits.loadRhs(&blB[4*RhsProgress], B0);
             traits.madd(A0,B1,C1,B1);
             traits.loadRhs(&blB[5*RhsProgress], B1);
             traits.madd(A0,B2,C2,B2);
@@ -871,8 +870,8 @@ EIGEN_ASM_COMMENT("mybegin4");
             traits.madd(A0,B3,C3,B3);
             traits.loadLhs(&blA[1*LhsProgress], A0);
             traits.loadRhs(&blB[7*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[8*RhsProgress], B_0);
+            traits.madd(A0,B0,C0,B0);
+            traits.loadRhs(&blB[8*RhsProgress], B0);
             traits.madd(A0,B1,C1,B1);
             traits.loadRhs(&blB[9*RhsProgress], B1);
             traits.madd(A0,B2,C2,B2);
@@ -881,8 +880,8 @@ EIGEN_ASM_COMMENT("mybegin4");
             traits.loadLhs(&blA[2*LhsProgress], A0);
             traits.loadRhs(&blB[11*RhsProgress], B3);
 
-            traits.madd(A0,B_0,C0,B_0);
-            traits.loadRhs(&blB[12*RhsProgress], B_0);
+            traits.madd(A0,B0,C0,B0);
+            traits.loadRhs(&blB[12*RhsProgress], B0);
             traits.madd(A0,B1,C1,B1);
             traits.loadRhs(&blB[13*RhsProgress], B1);
             traits.madd(A0,B2,C2,B2);
@@ -891,7 +890,7 @@ EIGEN_ASM_COMMENT("mybegin4");
 
             traits.loadLhs(&blA[3*LhsProgress], A0);
             traits.loadRhs(&blB[15*RhsProgress], B3);
-            traits.madd(A0,B_0,C0,B_0);
+            traits.madd(A0,B0,C0,B0);
             traits.madd(A0,B1,C1,B1);
             traits.madd(A0,B2,C2,B2);
             traits.madd(A0,B3,C3,B3);
@@ -906,26 +905,26 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsPacket A0;
-            RhsPacket B_0, B1;
+            RhsPacket B0, B1;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
-            traits.madd(A0,B_0,C0,B_0);
+            traits.madd(A0,B0,C0,B0);
             traits.madd(A0,B1,C1,B1);
           }
           else
           {
             LhsPacket A0;
-            RhsPacket B_0, B1, B2, B3;
+            RhsPacket B0, B1, B2, B3;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B_0);
+            traits.loadRhs(&blB[0*RhsProgress], B0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
             traits.loadRhs(&blB[2*RhsProgress], B2);
             traits.loadRhs(&blB[3*RhsProgress], B3);
 
-            traits.madd(A0,B_0,C0,B_0);
+            traits.madd(A0,B0,C0,B0);
             traits.madd(A0,B1,C1,B1);
             traits.madd(A0,B2,C2,B2);
             traits.madd(A0,B3,C3,B3);
@@ -972,26 +971,26 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsScalar A0;
-            RhsScalar B_0, B1;
+            RhsScalar B0, B1;
 
             A0 = blA[k];
-            B_0 = blB[0];
+            B0 = blB[0];
             B1 = blB[1];
-            MADD(cj,A0,B_0,C0,B_0);
+            MADD(cj,A0,B0,C0,B0);
             MADD(cj,A0,B1,C1,B1);
           }
           else
           {
             LhsScalar A0;
-            RhsScalar B_0, B1, B2, B3;
+            RhsScalar B0, B1, B2, B3;
 
             A0 = blA[k];
-            B_0 = blB[0];
+            B0 = blB[0];
             B1 = blB[1];
             B2 = blB[2];
             B3 = blB[3];
 
-            MADD(cj,A0,B_0,C0,B_0);
+            MADD(cj,A0,B0,C0,B0);
             MADD(cj,A0,B1,C1,B1);
             MADD(cj,A0,B2,C2,B2);
             MADD(cj,A0,B3,C3,B3);
@@ -1028,14 +1027,14 @@ EIGEN_ASM_COMMENT("mybegin4");
         for(Index k=0; k<depth; k++)
         {
           LhsPacket A0, A1;
-          RhsPacket B_0;
+          RhsPacket B0;
           RhsPacket T0;
 
           traits.loadLhs(&blA[0*LhsProgress], A0);
           traits.loadLhs(&blA[1*LhsProgress], A1);
-          traits.loadRhs(&blB[0*RhsProgress], B_0);
-          traits.madd(A0,B_0,C0,T0);
-          traits.madd(A1,B_0,C4,B_0);
+          traits.loadRhs(&blB[0*RhsProgress], B0);
+          traits.madd(A0,B0,C0,T0);
+          traits.madd(A1,B0,C4,B0);
 
           blB += RhsProgress;
           blA += 2*LhsProgress;
@@ -1067,10 +1066,10 @@ EIGEN_ASM_COMMENT("mybegin4");
         for(Index k=0; k<depth; k++)
         {
           LhsPacket A0;
-          RhsPacket B_0;
+          RhsPacket B0;
           traits.loadLhs(blA, A0);
-          traits.loadRhs(blB, B_0);
-          traits.madd(A0, B_0, C0, B_0);
+          traits.loadRhs(blB, B0);
+          traits.madd(A0, B0, C0, B0);
           blB += RhsProgress;
           blA += LhsProgress;
         }
@@ -1092,8 +1091,8 @@ EIGEN_ASM_COMMENT("mybegin4");
         for(Index k=0; k<depth; k++)
         {
           LhsScalar A0 = blA[k];
-          RhsScalar B_0 = blB[k];
-          MADD(cj, A0, B_0, C0, B_0);
+          RhsScalar B0 = blB[k];
+          MADD(cj, A0, B0, C0, B0);
         }
         res[(j2+0)*resStride + i] += alpha*C0;
       }
@@ -1104,7 +1103,7 @@ EIGEN_ASM_COMMENT("mybegin4");
 #undef CJMADD
 
 // pack a block of the lhs
-// The traversal is as follow (mr==4):
+// The travesal is as follow (mr==4):
 //   0  4  8 12 ...
 //   1  5  9 13 ...
 //   2  6 10 14 ...
@@ -1120,15 +1119,11 @@ EIGEN_ASM_COMMENT("mybegin4");
 template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder, bool Conjugate, bool PanelMode>
 struct gemm_pack_lhs
 {
-  EIGEN_DONT_INLINE void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows,
+  void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows,
                   Index stride=0, Index offset=0)
   {
-    typedef typename packet_traits<Scalar>::type Packet;
-    enum { PacketSize = packet_traits<Scalar>::size };
-
-    EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK LHS");
+//     enum { PacketSize = packet_traits<Scalar>::size };
     eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
-    eigen_assert( (StorageOrder==RowMajor) || ((Pack1%PacketSize)==0 && Pack1<=4*PacketSize) );
     conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
     const_blas_data_mapper<Scalar, Index, StorageOrder> lhs(_lhs,lhsStride);
     Index count = 0;
@@ -1136,44 +1131,9 @@ struct gemm_pack_lhs
     for(Index i=0; i<peeled_mc; i+=Pack1)
     {
       if(PanelMode) count += Pack1 * offset;
-
-      if(StorageOrder==ColMajor)
-      {
-        for(Index k=0; k<depth; k++)
-        {
-          Packet A, B, C, D;
-          if(Pack1>=1*PacketSize) A = ploadu<Packet>(&lhs(i+0*PacketSize, k));
-          if(Pack1>=2*PacketSize) B = ploadu<Packet>(&lhs(i+1*PacketSize, k));
-          if(Pack1>=3*PacketSize) C = ploadu<Packet>(&lhs(i+2*PacketSize, k));
-          if(Pack1>=4*PacketSize) D = ploadu<Packet>(&lhs(i+3*PacketSize, k));
-          if(Pack1>=1*PacketSize) { pstore(blockA+count, cj.pconj(A)); count+=PacketSize; }
-          if(Pack1>=2*PacketSize) { pstore(blockA+count, cj.pconj(B)); count+=PacketSize; }
-          if(Pack1>=3*PacketSize) { pstore(blockA+count, cj.pconj(C)); count+=PacketSize; }
-          if(Pack1>=4*PacketSize) { pstore(blockA+count, cj.pconj(D)); count+=PacketSize; }
-        }
-      }
-      else
-      {
-        for(Index k=0; k<depth; k++)
-        {
-          // TODO add a vectorized transpose here
-          Index w=0;
-          for(; w<Pack1-3; w+=4)
-          {
-            Scalar a(cj(lhs(i+w+0, k))),
-                   b(cj(lhs(i+w+1, k))),
-                   c(cj(lhs(i+w+2, k))),
-                   d(cj(lhs(i+w+3, k)));
-            blockA[count++] = a;
-            blockA[count++] = b;
-            blockA[count++] = c;
-            blockA[count++] = d;
-          }
-          if(Pack1%4)
-            for(;w<Pack1;++w)
-              blockA[count++] = cj(lhs(i+w, k));
-        }
-      }
+      for(Index k=0; k<depth; k++)
+        for(Index w=0; w<Pack1; w++)
+          blockA[count++] = cj(lhs(i+w, k));
       if(PanelMode) count += Pack1 * (stride-offset-depth);
     }
     if(rows-peeled_mc>=Pack2)
@@ -1207,10 +1167,9 @@ struct gemm_pack_rhs<Scalar, Index, nr, ColMajor, Conjugate, PanelMode>
 {
   typedef typename packet_traits<Scalar>::type Packet;
   enum { PacketSize = packet_traits<Scalar>::size };
-  EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
+  void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
                   Index stride=0, Index offset=0)
   {
-    EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS COLMAJOR");
     eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
     conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
     Index packet_cols = (cols/nr) * nr;
@@ -1255,10 +1214,9 @@ template<typename Scalar, typename Index, int nr, bool Conjugate, bool PanelMode
 struct gemm_pack_rhs<Scalar, Index, nr, RowMajor, Conjugate, PanelMode>
 {
   enum { PacketSize = packet_traits<Scalar>::size };
-  EIGEN_DONT_INLINE void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
+  void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
                   Index stride=0, Index offset=0)
   {
-    EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS ROWMAJOR");
     eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
     conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
     Index packet_cols = (cols/nr) * nr;
@@ -1324,6 +1282,4 @@ inline void setCpuCacheSizes(std::ptrdiff_t l1, std::ptrdiff_t l2)
   internal::manage_caching_sizes(SetAction, &l1, &l2);
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_GENERAL_BLOCK_PANEL_H

Eigen/src/Core/products/GeneralMatrixMatrix.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_GENERAL_MATRIX_MATRIX_H
 #define EIGEN_GENERAL_MATRIX_MATRIX_H
 
-namespace Eigen { 
-
 namespace internal {
 
 template<typename _LhsScalar, typename _RhsScalar> class level3_blocking;
@@ -80,7 +78,7 @@ static void run(Index rows, Index cols, Index depth,
   typedef gebp_traits<LhsScalar,RhsScalar> Traits;
 
   Index kc = blocking.kc();                 // cache block size along the K direction
-  Index mc = (std::min)(rows,blocking.mc());  // cache block size along the M direction
+  Index mc = std::min(rows,blocking.mc());  // cache block size along the M direction
   //Index nc = blocking.nc(); // cache block size along the N direction
 
   gemm_pack_lhs<LhsScalar, Index, Traits::mr, Traits::LhsProgress, LhsStorageOrder> pack_lhs;
@@ -105,7 +103,7 @@ static void run(Index rows, Index cols, Index depth,
     // For each horizontal panel of the rhs, and corresponding vertical panel of the lhs...
     for(Index k=0; k<depth; k+=kc)
     {
-      const Index actual_kc = (std::min)(k+kc,depth)-k; // => rows of B', and cols of the A'
+      const Index actual_kc = std::min(k+kc,depth)-k; // => rows of B', and cols of the A'
 
       // In order to reduce the chance that a thread has to wait for the other,
       // let's start by packing A'.
@@ -142,7 +140,7 @@ static void run(Index rows, Index cols, Index depth,
       // Then keep going as usual with the remaining A'
       for(Index i=mc; i<rows; i+=mc)
       {
-        const Index actual_mc = (std::min)(i+mc,rows)-i;
+        const Index actual_mc = std::min(i+mc,rows)-i;
 
         // pack A_i,k to A'
         pack_lhs(blockA, &lhs(i,k), lhsStride, actual_kc, actual_mc);
@@ -176,7 +174,7 @@ static void run(Index rows, Index cols, Index depth,
     // (==GEMM_VAR1)
     for(Index k2=0; k2<depth; k2+=kc)
     {
-      const Index actual_kc = (std::min)(k2+kc,depth)-k2;
+      const Index actual_kc = std::min(k2+kc,depth)-k2;
 
       // OK, here we have selected one horizontal panel of rhs and one vertical panel of lhs.
       // => Pack rhs's panel into a sequential chunk of memory (L2 caching)
@@ -189,7 +187,7 @@ static void run(Index rows, Index cols, Index depth,
       // (==GEPP_VAR1)
       for(Index i2=0; i2<rows; i2+=mc)
       {
-        const Index actual_mc = (std::min)(i2+mc,rows)-i2;
+        const Index actual_mc = std::min(i2+mc,rows)-i2;
 
         // We pack the lhs's block into a sequential chunk of memory (L1 caching)
         // Note that this block will be read a very high number of times, which is equal to the number of
@@ -414,8 +412,8 @@ class GeneralProduct<Lhs, Rhs, GemmProduct>
     {
       eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
 
-      typename internal::add_const_on_value_type<ActualLhsType>::type lhs = LhsBlasTraits::extract(m_lhs);
-      typename internal::add_const_on_value_type<ActualRhsType>::type rhs = RhsBlasTraits::extract(m_rhs);
+      const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
+      const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
 
       Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                                  * RhsBlasTraits::extractScalarFactor(m_rhs);
@@ -438,6 +436,4 @@ class GeneralProduct<Lhs, Rhs, GemmProduct>
     }
 };
 
-} // end namespace Eigen
-
 #endif // EIGEN_GENERAL_MATRIX_MATRIX_H

Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h

@@ -25,8 +25,6 @@
 #ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H
 #define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H
 
-namespace Eigen { 
-
 namespace internal {
 
 /**********************************************************************
@@ -44,14 +42,14 @@ struct tribb_kernel;
 template <typename Index,
           typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
           typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs,
-                              int ResStorageOrder, int  UpLo, int Version = Specialized>
+                              int ResStorageOrder, int  UpLo>
 struct general_matrix_matrix_triangular_product;
 
 // as usual if the result is row major => we transpose the product
 template <typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
-                          typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int  UpLo, int Version>
-struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor,UpLo,Version>
-{
+                          typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int  UpLo>
+struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor,UpLo>
+{  
   typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   static EIGEN_STRONG_INLINE void run(Index size, Index depth,const LhsScalar* lhs, Index lhsStride,
                                       const RhsScalar* rhs, Index rhsStride, ResScalar* res, Index resStride, ResScalar alpha)
@@ -65,8 +63,8 @@ struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,
 };
 
 template <typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
-                          typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int  UpLo, int Version>
-struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor,UpLo,Version>
+                          typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs, int  UpLo>
+struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor,UpLo>
 {
   typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   static EIGEN_STRONG_INLINE void run(Index size, Index depth,const LhsScalar* _lhs, Index lhsStride,
@@ -98,14 +96,14 @@ struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,
 
     for(Index k2=0; k2<depth; k2+=kc)
     {
-      const Index actual_kc = (std::min)(k2+kc,depth)-k2;
+      const Index actual_kc = std::min(k2+kc,depth)-k2;
 
       // note that the actual rhs is the transpose/adjoint of mat
       pack_rhs(blockB, &rhs(k2,0), rhsStride, actual_kc, size);
 
       for(Index i2=0; i2<size; i2+=mc)
       {
-        const Index actual_mc = (std::min)(i2+mc,size)-i2;
+        const Index actual_mc = std::min(i2+mc,size)-i2;
 
         pack_lhs(blockA, &lhs(i2, k2), lhsStride, actual_kc, actual_mc);
 
@@ -114,7 +112,7 @@ struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,
         //  2 - the actual_mc x actual_mc symmetric block => processed with a special kernel
         //  3 - after the diagonal => processed with gebp or skipped
         if (UpLo==Lower)
-          gebp(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, (std::min)(size,i2), alpha,
+          gebp(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, std::min(size,i2), alpha,
                -1, -1, 0, 0, allocatedBlockB);
 
         sybb(res+resStride*i2 + i2, resStride, blockA, blockB + actual_kc*i2, actual_mc, actual_kc, alpha, allocatedBlockB);
@@ -122,7 +120,7 @@ struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,
         if (UpLo==Upper)
         {
           Index j2 = i2+actual_mc;
-          gebp(res+resStride*j2+i2, resStride, blockA, blockB+actual_kc*j2, actual_mc, actual_kc, (std::max)(Index(0), size-j2), alpha,
+          gebp(res+resStride*j2+i2, resStride, blockA, blockB+actual_kc*j2, actual_mc, actual_kc, std::max(Index(0), size-j2), alpha,
                -1, -1, 0, 0, allocatedBlockB);
         }
       }
@@ -203,13 +201,13 @@ TriangularView<MatrixType,UpLo>& TriangularView<MatrixType,UpLo>::assignProduct(
   typedef internal::blas_traits<Lhs> LhsBlasTraits;
   typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhs;
   typedef typename internal::remove_all<ActualLhs>::type _ActualLhs;
-  typename internal::add_const_on_value_type<ActualLhs>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
+  const ActualLhs actualLhs = LhsBlasTraits::extract(prod.lhs());
   
   typedef typename internal::remove_all<typename ProductDerived::RhsNested>::type Rhs;
   typedef internal::blas_traits<Rhs> RhsBlasTraits;
   typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhs;
   typedef typename internal::remove_all<ActualRhs>::type _ActualRhs;
-  typename internal::add_const_on_value_type<ActualRhs>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
+  const ActualRhs actualRhs = RhsBlasTraits::extract(prod.rhs());
 
   typename ProductDerived::Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs().derived()) * RhsBlasTraits::extractScalarFactor(prod.rhs().derived());
 
@@ -224,6 +222,4 @@ TriangularView<MatrixType,UpLo>& TriangularView<MatrixType,UpLo>::assignProduct(
   return *this;
 }
 
-} // end namespace Eigen
-
 #endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H

Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h

@@ -1,146 +0,0 @@
-/*
- Copyright (c) 2011, Intel Corporation. All rights reserved.
-
- Redistribution and use in source and binary forms, with or without modification,
- are permitted provided that the following conditions are met:
-
- * Redistributions of source code must retain the above copyright notice, this
-   list of conditions and the following disclaimer.
- * Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
- * Neither the name of Intel Corporation nor the names of its contributors may
-   be used to endorse or promote products derived from this software without
-   specific prior written permission.
-
- THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
- ********************************************************************************
- *   Content : Eigen bindings to Intel(R) MKL
- *   Level 3 BLAS SYRK/HERK implementation.
- ********************************************************************************
-*/
-
-#ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H
-#define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H
-
-namespace Eigen { 
-
-namespace internal {
-
-template <typename Index, typename Scalar, int AStorageOrder, bool ConjugateA, int ResStorageOrder, int  UpLo>
-struct general_matrix_matrix_rankupdate :
-       general_matrix_matrix_triangular_product<
-         Index,Scalar,AStorageOrder,ConjugateA,Scalar,AStorageOrder,ConjugateA,ResStorageOrder,UpLo,BuiltIn> {};
-
-
-// try to go to BLAS specialization
-#define EIGEN_MKL_RANKUPDATE_SPECIALIZE(Scalar) \
-template <typename Index, int LhsStorageOrder, bool ConjugateLhs, \
-                          int RhsStorageOrder, bool ConjugateRhs, int  UpLo> \
-struct general_matrix_matrix_triangular_product<Index,Scalar,LhsStorageOrder,ConjugateLhs, \
-               Scalar,RhsStorageOrder,ConjugateRhs,ColMajor,UpLo,Specialized> { \
-  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const Scalar* lhs, Index lhsStride, \
-                          const Scalar* rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha) \
-  { \
-    if (lhs==rhs) { \
-      general_matrix_matrix_rankupdate<Index,Scalar,LhsStorageOrder,ConjugateLhs,ColMajor,UpLo> \
-      ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha); \
-    } else { \
-      general_matrix_matrix_triangular_product<Index, \
-        Scalar, LhsStorageOrder, ConjugateLhs, \
-        Scalar, RhsStorageOrder, ConjugateRhs, \
-        ColMajor, UpLo, BuiltIn> \
-      ::run(size,depth,lhs,lhsStride,rhs,rhsStride,res,resStride,alpha); \
-    } \
-  } \
-};
-
-EIGEN_MKL_RANKUPDATE_SPECIALIZE(double)
-//EIGEN_MKL_RANKUPDATE_SPECIALIZE(dcomplex)
-EIGEN_MKL_RANKUPDATE_SPECIALIZE(float)
-//EIGEN_MKL_RANKUPDATE_SPECIALIZE(scomplex)
-
-// SYRK for float/double
-#define EIGEN_MKL_RANKUPDATE_R(EIGTYPE, MKLTYPE, MKLFUNC) \
-template <typename Index, int AStorageOrder, bool ConjugateA, int  UpLo> \
-struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,ColMajor,UpLo> { \
-  enum { \
-    IsLower = (UpLo&Lower) == Lower, \
-    LowUp = IsLower ? Lower : Upper, \
-    conjA = ((AStorageOrder==ColMajor) && ConjugateA) ? 1 : 0 \
-  }; \
-  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \
-                          const EIGTYPE* rhs, Index rhsStride, EIGTYPE* res, Index resStride, EIGTYPE alpha) \
-  { \
-  /* typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs;*/ \
-\
-   MKL_INT lda=lhsStride, ldc=resStride, n=size, k=depth; \
-   char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'T':'N'; \
-   MKLTYPE alpha_, beta_; \
-\
-/* Set alpha_ & beta_ */ \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
-   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
-   MKLFUNC(&uplo, &trans, &n, &k, &alpha_, lhs, &lda, &beta_, res, &ldc); \
-  } \
-};
-
-// HERK for complex data
-#define EIGEN_MKL_RANKUPDATE_C(EIGTYPE, MKLTYPE, RTYPE, MKLFUNC) \
-template <typename Index, int AStorageOrder, bool ConjugateA, int  UpLo> \
-struct general_matrix_matrix_rankupdate<Index,EIGTYPE,AStorageOrder,ConjugateA,ColMajor,UpLo> { \
-  enum { \
-    IsLower = (UpLo&Lower) == Lower, \
-    LowUp = IsLower ? Lower : Upper, \
-    conjA = (((AStorageOrder==ColMajor) && ConjugateA) || ((AStorageOrder==RowMajor) && !ConjugateA)) ? 1 : 0 \
-  }; \
-  static EIGEN_STRONG_INLINE void run(Index size, Index depth,const EIGTYPE* lhs, Index lhsStride, \
-                          const EIGTYPE* rhs, Index rhsStride, EIGTYPE* res, Index resStride, EIGTYPE alpha) \
-  { \
-   typedef Matrix<EIGTYPE, Dynamic, Dynamic, AStorageOrder> MatrixType; \
-\
-   MKL_INT lda=lhsStride, ldc=resStride, n=size, k=depth; \
-   char uplo=(IsLower) ? 'L' : 'U', trans=(AStorageOrder==RowMajor) ? 'C':'N'; \
-   RTYPE alpha_, beta_; \
-   const EIGTYPE* a_ptr; \
-\
-/* Set alpha_ & beta_ */ \
-/*   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); */\
-/*   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1));*/ \
-   alpha_ = alpha.real(); \
-   beta_ = 1.0; \
-/* Copy with conjugation in some cases*/ \
-   MatrixType a; \
-   if (conjA) { \
-     Map<const MatrixType, 0, OuterStride<> > mapA(lhs,n,k,OuterStride<>(lhsStride)); \
-     a = mapA.conjugate(); \
-     lda = a.outerStride(); \
-     a_ptr = a.data(); \
-   } else a_ptr=lhs; \
-   MKLFUNC(&uplo, &trans, &n, &k, &alpha_, (MKLTYPE*)a_ptr, &lda, &beta_, (MKLTYPE*)res, &ldc); \
-  } \
-};
-
-
-EIGEN_MKL_RANKUPDATE_R(double, double, dsyrk)
-EIGEN_MKL_RANKUPDATE_R(float,  float,  ssyrk)
-
-//EIGEN_MKL_RANKUPDATE_C(dcomplex, MKL_Complex16, double, zherk)
-//EIGEN_MKL_RANKUPDATE_C(scomplex, MKL_Complex8,  double, cherk)
-
-
-} // end namespace internal
-
-} // end namespace Eigen
-
-#endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_MKL_H