Merging r50625 through r51896 from trunk into soc-2011-tomato

Merging just in case we'll want to develop some experimental stuff

408 files changed, 23349 insertions, 9358 deletions

diff --git a/extern/Eigen3/Eigen/Cholesky b/extern/Eigen3/Eigen/Cholesky
index 53f7bf911a4..f727f5d89c0 100644
--- a/extern/Eigen3/Eigen/Cholesky
+++ b/extern/Eigen3/Eigen/Cholesky
@@ -5,8 +5,6 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-namespace Eigen {
-
 /** \defgroup Cholesky_Module Cholesky module
   *
   *
@@ -24,8 +22,9 @@ namespace Eigen {
 #include "src/misc/Solve.h"
 #include "src/Cholesky/LLT.h"
 #include "src/Cholesky/LDLT.h"
-
-} // namespace Eigen
+#ifdef EIGEN_USE_LAPACKE
+#include "src/Cholesky/LLT_MKL.h"
+#endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
diff --git a/extern/Eigen3/Eigen/CholmodSupport b/extern/Eigen3/Eigen/CholmodSupport
new file mode 100644
index 00000000000..745b884e74d
--- /dev/null
+++ b/extern/Eigen3/Eigen/CholmodSupport
@@ -0,0 +1,45 @@
+#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
+  *
+  * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies.
+  * The dependencies depend on how cholmod has been compiled.
+  * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/CholmodSupport/CholmodSupport.h"
+
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_CHOLMODSUPPORT_MODULE_H
+
diff --git a/extern/Eigen3/Eigen/Core b/extern/Eigen3/Eigen/Core
index a5025e37ead..d4801702261 100644
--- a/extern/Eigen3/Eigen/Core
+++ b/extern/Eigen3/Eigen/Core
@@ -4,24 +4,9 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2007-2011 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CORE_H
 #define EIGEN_CORE_H
@@ -34,6 +19,12 @@
 // 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
@@ -136,7 +127,7 @@
 #endif
 
 // MSVC for windows mobile does not have the errno.h file
-#if !(defined(_MSC_VER) && defined(_WIN32_WCE))
+#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION)
 #define EIGEN_HAS_ERRNO
 #endif
 
@@ -146,7 +137,6 @@
 #include <cstddef>
 #include <cstdlib>
 #include <cmath>
-#include <complex>
 #include <cassert>
 #include <functional>
 #include <iosfwd>
@@ -175,9 +165,6 @@
   #include <new>
 #endif
 
-// defined in bits/termios.h
-#undef B0
-
 /** \brief Namespace containing all symbols from the %Eigen library. */
 namespace Eigen {
 
@@ -201,6 +188,8 @@ 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
@@ -247,6 +236,10 @@ 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"
@@ -318,15 +311,15 @@ using std::ptrdiff_t;
 #include "src/Core/CommaInitializer.h"
 #include "src/Core/Flagged.h"
 #include "src/Core/ProductBase.h"
-#include "src/Core/Product.h"
+#include "src/Core/GeneralProduct.h"
 #include "src/Core/TriangularMatrix.h"
 #include "src/Core/SelfAdjointView.h"
-#include "src/Core/SolveTriangular.h"
+#include "src/Core/products/GeneralBlockPanelKernel.h"
 #include "src/Core/products/Parallelizer.h"
 #include "src/Core/products/CoeffBasedProduct.h"
-#include "src/Core/products/GeneralBlockPanelKernel.h"
 #include "src/Core/products/GeneralMatrixVector.h"
 #include "src/Core/products/GeneralMatrixMatrix.h"
+#include "src/Core/SolveTriangular.h"
 #include "src/Core/products/GeneralMatrixMatrixTriangular.h"
 #include "src/Core/products/SelfadjointMatrixVector.h"
 #include "src/Core/products/SelfadjointMatrixMatrix.h"
@@ -347,7 +340,20 @@ using std::ptrdiff_t;
 #include "src/Core/ArrayBase.h"
 #include "src/Core/ArrayWrapper.h"
 
-} // namespace Eigen
+#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
 
 #include "src/Core/GlobalFunctions.h"
 
diff --git a/extern/Eigen3/Eigen/Eigen2Support b/extern/Eigen3/Eigen/Eigen2Support
index d96592a8de9..36156d29a92 100644
--- a/extern/Eigen3/Eigen/Eigen2Support
+++ b/extern/Eigen3/Eigen/Eigen2Support
@@ -3,24 +3,9 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2SUPPORT_H
 #define EIGEN2SUPPORT_H
@@ -31,9 +16,8 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-namespace Eigen {
-
-/** \defgroup Eigen2Support_Module Eigen2 support module
+/** \ingroup Support_modules
+  * \defgroup Eigen2Support_Module Eigen2 support module
   * This module provides a couple of deprecated functions improving the compatibility with Eigen2.
   *
   * To use it, define EIGEN2_SUPPORT before including any Eigen header
@@ -56,13 +40,29 @@ namespace Eigen {
 #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; \
diff --git a/extern/Eigen3/Eigen/Eigenvalues b/extern/Eigen3/Eigen/Eigenvalues
index 250c0f46652..af99ccd1fab 100644
--- a/extern/Eigen3/Eigen/Eigenvalues
+++ b/extern/Eigen3/Eigen/Eigenvalues
@@ -9,8 +9,7 @@
 #include "Jacobi"
 #include "Householder"
 #include "LU"
-
-namespace Eigen {
+#include "Geometry"
 
 /** \defgroup Eigenvalues_Module Eigenvalues module
   *
@@ -35,8 +34,11 @@ namespace Eigen {
 #include "src/Eigenvalues/ComplexSchur.h"
 #include "src/Eigenvalues/ComplexEigenSolver.h"
 #include "src/Eigenvalues/MatrixBaseEigenvalues.h"
-
-} // namespace Eigen
+#ifdef EIGEN_USE_LAPACKE
+#include "src/Eigenvalues/RealSchur_MKL.h"
+#include "src/Eigenvalues/ComplexSchur_MKL.h"
+#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h"
+#endif
 
 #include "src/Core/util/ReenableStupidWarnings.h"
 
diff --git a/extern/Eigen3/Eigen/Geometry b/extern/Eigen3/Eigen/Geometry
index 78277c0c560..efd9d4504cb 100644
--- a/extern/Eigen3/Eigen/Geometry
+++ b/extern/Eigen3/Eigen/Geometry
@@ -13,8 +13,6 @@
 #define M_PI 3.14159265358979323846
 #endif
 
-namespace Eigen {
-
 /** \defgroup Geometry_Module Geometry module
   *
   *
@@ -58,8 +56,6 @@ namespace Eigen {
 #include "src/Eigen2Support/Geometry/All.h"
 #endif
 
-} // namespace Eigen
-
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_GEOMETRY_MODULE_H
diff --git a/extern/Eigen3/Eigen/Householder b/extern/Eigen3/Eigen/Householder
index 6b86cf65c55..6e348db5c43 100644
--- a/extern/Eigen3/Eigen/Householder
+++ b/extern/Eigen3/Eigen/Householder
@@ -5,8 +5,6 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-namespace Eigen {
-
 /** \defgroup Householder_Module Householder module
   * This module provides Householder transformations.
   *
@@ -19,8 +17,6 @@ namespace Eigen {
 #include "src/Householder/HouseholderSequence.h"
 #include "src/Householder/BlockHouseholder.h"
 
-} // namespace Eigen
-
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_HOUSEHOLDER_MODULE_H
diff --git a/extern/Eigen3/Eigen/IterativeLinearSolvers b/extern/Eigen3/Eigen/IterativeLinearSolvers
new file mode 100644
index 00000000000..315c2dd1ee7
--- /dev/null
+++ b/extern/Eigen3/Eigen/IterativeLinearSolvers
@@ -0,0 +1,40 @@
+#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
diff --git a/extern/Eigen3/Eigen/Jacobi b/extern/Eigen3/Eigen/Jacobi
index afa67681379..ba8a4dc36a5 100644
--- a/extern/Eigen3/Eigen/Jacobi
+++ b/extern/Eigen3/Eigen/Jacobi
@@ -5,8 +5,6 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-namespace Eigen {
-
 /** \defgroup Jacobi_Module Jacobi module
   * This module provides Jacobi and Givens rotations.
   *
@@ -21,8 +19,6 @@ namespace Eigen {
 
 #include "src/Jacobi/Jacobi.h"
 
-} // namespace Eigen
-
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_JACOBI_MODULE_H
diff --git a/extern/Eigen3/Eigen/LU b/extern/Eigen3/Eigen/LU
index 226f88ca38a..db579550448 100644
--- a/extern/Eigen3/Eigen/LU
+++ b/extern/Eigen3/Eigen/LU
@@ -5,8 +5,6 @@
 
 #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:
@@ -23,6 +21,9 @@ namespace Eigen {
 #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"
 
@@ -34,8 +35,6 @@ namespace Eigen {
   #include "src/Eigen2Support/LU.h"
 #endif
 
-} // namespace Eigen
-
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN_LU_MODULE_H
diff --git a/extern/Eigen3/Eigen/LeastSquares b/extern/Eigen3/Eigen/LeastSquares
index 93a6302dcd9..35137c25db0 100644
--- a/extern/Eigen3/Eigen/LeastSquares
+++ b/extern/Eigen3/Eigen/LeastSquares
@@ -15,8 +15,6 @@
 #include "Eigenvalues"
 #include "Geometry"
 
-namespace Eigen {
-
 /** \defgroup LeastSquares_Module LeastSquares module
   * This module provides linear regression and related features.
   *
@@ -27,8 +25,6 @@ namespace Eigen {
 
 #include "src/Eigen2Support/LeastSquares.h"
 
-} // namespace Eigen
-
 #include "src/Core/util/ReenableStupidWarnings.h"
 
 #endif // EIGEN2_SUPPORT
diff --git a/extern/Eigen3/Eigen/OrderingMethods b/extern/Eigen3/Eigen/OrderingMethods
new file mode 100644
index 00000000000..1e2d87452e5
--- /dev/null
+++ b/extern/Eigen3/Eigen/OrderingMethods
@@ -0,0 +1,23 @@
+#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
diff --git a/extern/Eigen3/Eigen/PaStiXSupport b/extern/Eigen3/Eigen/PaStiXSupport
new file mode 100644
index 00000000000..7c616ee5eac
--- /dev/null
+++ b/extern/Eigen3/Eigen/PaStiXSupport
@@ -0,0 +1,46 @@
+#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
+  * 
+  * This module provides an interface to the <a href="http://pastix.gforge.inria.fr/">PaSTiX</a> library.
+  * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver.
+  * It provides the two following main factorization classes:
+  * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization.
+  * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization.
+  * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern).
+  * 
+  * \code
+  * #include <Eigen/PaStiXSupport>
+  * \endcode
+  *
+  * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be linked to the PaSTiX library and its dependencies.
+  * The dependencies depend on how PaSTiX has been compiled.
+  * For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/PaStiXSupport/PaStiXSupport.h"
+
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_PASTIXSUPPORT_MODULE_H
diff --git a/extern/Eigen3/Eigen/PardisoSupport b/extern/Eigen3/Eigen/PardisoSupport
new file mode 100644
index 00000000000..99330ce7a7d
--- /dev/null
+++ b/extern/Eigen3/Eigen/PardisoSupport
@@ -0,0 +1,30 @@
+#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
+  *
+  * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be linked to the MKL library and its dependencies.
+  * See this \ref TopicUsingIntelMKL "page" for more information on MKL-Eigen integration.
+  * 
+  */
+
+#include "src/PardisoSupport/PardisoSupport.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_PARDISOSUPPORT_MODULE_H
diff --git a/extern/Eigen3/Eigen/QR b/extern/Eigen3/Eigen/QR
index 97c1788ee30..ac5b0269354 100644
--- a/extern/Eigen3/Eigen/QR
+++ b/extern/Eigen3/Eigen/QR
@@ -9,8 +9,6 @@
 #include "Jacobi"
 #include "Householder"
 
-namespace Eigen {
-
 /** \defgroup QR_Module QR module
   *
   *
@@ -28,13 +26,15 @@ namespace Eigen {
 #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
diff --git a/extern/Eigen3/Eigen/SVD b/extern/Eigen3/Eigen/SVD
index 7c987a9dd36..fd310017ad1 100644
--- a/extern/Eigen3/Eigen/SVD
+++ b/extern/Eigen3/Eigen/SVD
@@ -7,8 +7,6 @@
 
 #include "src/Core/util/DisableStupidWarnings.h"
 
-namespace Eigen {
-
 /** \defgroup SVD_Module SVD module
   *
   *
@@ -24,14 +22,15 @@ namespace Eigen {
 
 #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
diff --git a/extern/Eigen3/Eigen/Sparse b/extern/Eigen3/Eigen/Sparse
index 7425b3a412a..2d1757172eb 100644
--- a/extern/Eigen3/Eigen/Sparse
+++ b/extern/Eigen3/Eigen/Sparse
@@ -1,69 +1,23 @@
 #ifndef EIGEN_SPARSE_MODULE_H
 #define EIGEN_SPARSE_MODULE_H
 
-#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
+/** \defgroup Sparse_modules Sparse modules
   *
-  *
-  *
-  * See the \ref TutorialSparse "Sparse tutorial"
+  * Meta-module including all related modules:
+  * - SparseCore
+  * - OrderingMethods
+  * - SparseCholesky
+  * - IterativeLinearSolvers
   *
   * \code
   * #include <Eigen/Sparse>
   * \endcode
   */
 
-/** 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"
+#include "SparseCore"
+#include "OrderingMethods"
+#include "SparseCholesky"
+#include "IterativeLinearSolvers"
 
 #endif // EIGEN_SPARSE_MODULE_H
 
diff --git a/extern/Eigen3/Eigen/SparseCholesky b/extern/Eigen3/Eigen/SparseCholesky
new file mode 100644
index 00000000000..5f82742f7d8
--- /dev/null
+++ b/extern/Eigen3/Eigen/SparseCholesky
@@ -0,0 +1,30 @@
+#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
diff --git a/extern/Eigen3/Eigen/SparseCore b/extern/Eigen3/Eigen/SparseCore
new file mode 100644
index 00000000000..41d28c92824
--- /dev/null
+++ b/extern/Eigen3/Eigen/SparseCore
@@ -0,0 +1,66 @@
+#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
+
diff --git a/extern/Eigen3/Eigen/StdDeque b/extern/Eigen3/Eigen/StdDeque
index a4f96232d8c..f27234778f4 100644
--- a/extern/Eigen3/Eigen/StdDeque
+++ b/extern/Eigen3/Eigen/StdDeque
@@ -4,24 +4,9 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STDDEQUE_MODULE_H
 #define EIGEN_STDDEQUE_MODULE_H
diff --git a/extern/Eigen3/Eigen/StdList b/extern/Eigen3/Eigen/StdList
index d914ded4f93..225c1e18f8e 100644
--- a/extern/Eigen3/Eigen/StdList
+++ b/extern/Eigen3/Eigen/StdList
@@ -3,24 +3,9 @@
 //
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STDLIST_MODULE_H
 #define EIGEN_STDLIST_MODULE_H
diff --git a/extern/Eigen3/Eigen/StdVector b/extern/Eigen3/Eigen/StdVector
index 3d8995e5aae..6b22627f6f6 100644
--- a/extern/Eigen3/Eigen/StdVector
+++ b/extern/Eigen3/Eigen/StdVector
@@ -4,24 +4,9 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STDVECTOR_MODULE_H
 #define EIGEN_STDVECTOR_MODULE_H
diff --git a/extern/Eigen3/Eigen/SuperLUSupport b/extern/Eigen3/Eigen/SuperLUSupport
new file mode 100644
index 00000000000..575e14fbc29
--- /dev/null
+++ b/extern/Eigen3/Eigen/SuperLUSupport
@@ -0,0 +1,59 @@
+#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
+  *
+  * This module provides an interface to the <a href="http://crd-legacy.lbl.gov/~xiaoye/SuperLU/">SuperLU</a> library.
+  * It provides the following factorization class:
+  * - class SuperLU: a supernodal sequential LU factorization.
+  * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods).
+  *
+  * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting.
+  *
+  * \code
+  * #include <Eigen/SuperLUSupport>
+  * \endcode
+  *
+  * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be linked to the superlu library and its dependencies.
+  * The dependencies depend on how superlu has been compiled.
+  * For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/SuperLUSupport/SuperLUSupport.h"
+
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_SUPERLUSUPPORT_MODULE_H
diff --git a/extern/Eigen3/Eigen/UmfPackSupport b/extern/Eigen3/Eigen/UmfPackSupport
new file mode 100644
index 00000000000..984f64a8419
--- /dev/null
+++ b/extern/Eigen3/Eigen/UmfPackSupport
@@ -0,0 +1,36 @@
+#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
+  *
+  * This module provides an interface to the UmfPack library which is part of the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">suitesparse</a> package.
+  * It provides the following factorization class:
+  * - class UmfPackLU: a multifrontal sequential LU factorization.
+  *
+  * \code
+  * #include <Eigen/UmfPackSupport>
+  * \endcode
+  *
+  * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies.
+  * The dependencies depend on how umfpack has been compiled.
+  * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task.
+  *
+  */
+
+#include "src/misc/Solve.h"
+#include "src/misc/SparseSolve.h"
+
+#include "src/UmfPackSupport/UmfPackSupport.h"
+
+#include "src/Core/util/ReenableStupidWarnings.h"
+
+#endif // EIGEN_UMFPACKSUPPORT_MODULE_H
diff --git a/extern/Eigen3/Eigen/src/Cholesky/LDLT.h b/extern/Eigen3/Eigen/src/Cholesky/LDLT.h
index a19e947a4c6..68e54b1d4ad 100644
--- a/extern/Eigen3/Eigen/src/Cholesky/LDLT.h
+++ b/extern/Eigen3/Eigen/src/Cholesky/LDLT.h
@@ -1,43 +1,33 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2008-2011 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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
@@ -48,14 +38,10 @@ 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:
@@ -98,6 +84,11 @@ 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()),
@@ -107,6 +98,14 @@ 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
     {
@@ -130,14 +129,14 @@ template<typename _MatrixType, int _UpLo> class LDLT
     }
 
     /** \returns the coefficients of the diagonal matrix D */
-    inline Diagonal<const MatrixType> vectorD(void) const
+    inline Diagonal<const MatrixType> vectorD() const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
       return m_matrix.diagonal();
     }
 
     /** \returns true if the matrix is positive (semidefinite) */
-    inline bool isPositive(void) const
+    inline bool isPositive() const
     {
       eigen_assert(m_isInitialized && "LDLT is not initialized.");
       return m_sign == 1;
@@ -196,6 +195,9 @@ 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
@@ -211,6 +213,17 @@ 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
@@ -249,7 +262,7 @@ 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)
     {
@@ -317,6 +330,61 @@ 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>
@@ -327,22 +395,29 @@ 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;
-  inline static MatrixL getL(const MatrixType& m) { return m; }
-  inline static MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixL getL(const MatrixType& m) { return m; }
+  static inline 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;
-  inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
-  inline static MatrixU getU(const MatrixType& m) { return m; }
+  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixU getU(const MatrixType& m) { return m; }
 };
 
 } // end namespace internal
@@ -367,6 +442,37 @@ 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>=0 ? 1 : -1;
+    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>
@@ -481,4 +587,6 @@ MatrixBase<Derived>::ldlt() const
   return LDLT<PlainObject>(derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_LDLT_H
diff --git a/extern/Eigen3/Eigen/src/Cholesky/LLT.h b/extern/Eigen3/Eigen/src/Cholesky/LLT.h
index 3bb76b5787f..41d14e532f1 100644
--- a/extern/Eigen3/Eigen/src/Cholesky/LLT.h
+++ b/extern/Eigen3/Eigen/src/Cholesky/LLT.h
@@ -3,39 +3,28 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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.
@@ -49,6 +38,9 @@ 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)
@@ -178,6 +170,9 @@ 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
@@ -190,16 +185,85 @@ template<typename _MatrixType, int _UpLo> class LLT
 
 namespace internal {
 
-template<int UpLo> struct llt_inplace;
+template<typename Scalar, 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)
+{
+  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<> struct llt_inplace<Lower>
+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();
@@ -254,21 +318,35 @@ template<> struct llt_inplace<Lower>
     }
     return -1;
   }
-};
 
-template<> struct llt_inplace<Upper>
+  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<typename MatrixType>
   static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat)
   {
     Transpose<MatrixType> matt(mat);
-    return llt_inplace<Lower>::unblocked(matt);
+    return llt_inplace<Scalar, Lower>::unblocked(matt);
   }
   template<typename MatrixType>
   static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat)
   {
     Transpose<MatrixType> matt(mat);
-    return llt_inplace<Lower>::blocked(matt);
+    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);
   }
 };
 
@@ -276,33 +354,35 @@ template<typename MatrixType> struct LLT_Traits<MatrixType,Lower>
 {
   typedef const TriangularView<const MatrixType, Lower> MatrixL;
   typedef const TriangularView<const 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 inline MatrixL getL(const MatrixType& m) { return m; }
+  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
   static bool inplace_decomposition(MatrixType& m)
-  { return llt_inplace<Lower>::blocked(m)==-1; }
+  { return llt_inplace<typename MatrixType::Scalar, 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;
-  inline static MatrixL getL(const MatrixType& m) { return m.adjoint(); }
-  inline static MatrixU getU(const MatrixType& m) { return m; }
+  static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); }
+  static inline MatrixU getU(const MatrixType& m) { return m; }
   static bool inplace_decomposition(MatrixType& m)
-  { return llt_inplace<Upper>::blocked(m)==-1; }
+  { return llt_inplace<typename MatrixType::Scalar, 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
   */
 template<typename MatrixType, int _UpLo>
 LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
 {
-  assert(a.rows()==a.cols());
+  eigen_assert(a.rows()==a.cols());
   const Index size = a.rows();
   m_matrix.resize(size, size);
   m_matrix = a;
@@ -314,6 +394,26 @@ 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>
@@ -383,4 +483,6 @@ SelfAdjointView<MatrixType, UpLo>::llt() const
   return LLT<PlainObject,UpLo>(m_matrix);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_LLT_H
diff --git a/extern/Eigen3/Eigen/src/Cholesky/LLT_MKL.h b/extern/Eigen3/Eigen/src/Cholesky/LLT_MKL.h
new file mode 100644
index 00000000000..64daa445cf7
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Cholesky/LLT_MKL.h
@@ -0,0 +1,102 @@
+/*
+ Copyright (c) 2011, Intel Corporation. All rights reserved.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
+ * Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+ * Neither the name of Intel Corporation nor the names of its contributors may
+   be used to endorse or promote products derived from this software without
+   specific prior written permission.
+
+ THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+ WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+ DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
+ ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+ (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+ LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
+ ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+ SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+ ********************************************************************************
+ *   Content : Eigen bindings to Intel(R) MKL
+ *     LLt decomposition based on LAPACKE_?potrf function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_LLT_MKL_H
+#define EIGEN_LLT_MKL_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+#include <iostream>
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Scalar> struct mkl_llt;
+
+#define EIGEN_MKL_LLT(EIGTYPE, MKLTYPE, MKLPREFIX) \
+template<> struct mkl_llt<EIGTYPE> \
+{ \
+  template<typename MatrixType> \
+  static inline typename MatrixType::Index potrf(MatrixType& m, char uplo) \
+  { \
+    lapack_int matrix_order; \
+    lapack_int size, lda, info, StorageOrder; \
+    EIGTYPE* a; \
+    eigen_assert(m.rows()==m.cols()); \
+    /* Set up parameters for ?potrf */ \
+    size = m.rows(); \
+    StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \
+    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
+    a = &(m.coeffRef(0,0)); \
+    lda = m.outerStride(); \
+\
+    info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \
+    info = (info==0) ? Success : NumericalIssue; \
+    return info; \
+  } \
+}; \
+template<> struct llt_inplace<EIGTYPE, Lower> \
+{ \
+  template<typename MatrixType> \
+  static typename MatrixType::Index blocked(MatrixType& m) \
+  { \
+    return mkl_llt<EIGTYPE>::potrf(m, 'L'); \
+  } \
+  template<typename MatrixType, typename VectorType> \
+  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
+  { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \
+}; \
+template<> struct llt_inplace<EIGTYPE, Upper> \
+{ \
+  template<typename MatrixType> \
+  static typename MatrixType::Index blocked(MatrixType& m) \
+  { \
+    return mkl_llt<EIGTYPE>::potrf(m, 'U'); \
+  } \
+  template<typename MatrixType, typename VectorType> \
+  static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \
+  { \
+    Transpose<MatrixType> matt(mat); \
+    return llt_inplace<EIGTYPE, Lower>::rankUpdate(matt, vec.conjugate(), sigma); \
+  } \
+};
+
+EIGEN_MKL_LLT(double, double, d)
+EIGEN_MKL_LLT(float, float, s)
+EIGEN_MKL_LLT(dcomplex, MKL_Complex16, z)
+EIGEN_MKL_LLT(scomplex, MKL_Complex8, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_LLT_MKL_H
diff --git a/extern/Eigen3/Eigen/src/CholmodSupport/CholmodSupport.h b/extern/Eigen3/Eigen/src/CholmodSupport/CholmodSupport.h
new file mode 100644
index 00000000000..37f142150ff
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/CholmodSupport/CholmodSupport.h
@@ -0,0 +1,579 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CHOLMODSUPPORT_H
+#define EIGEN_CHOLMODSUPPORT_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Scalar, typename CholmodType>
+void cholmod_configure_matrix(CholmodType& mat)
+{
+  if (internal::is_same<Scalar,float>::value)
+  {
+    mat.xtype = CHOLMOD_REAL;
+    mat.dtype = CHOLMOD_SINGLE;
+  }
+  else if (internal::is_same<Scalar,double>::value)
+  {
+    mat.xtype = CHOLMOD_REAL;
+    mat.dtype = CHOLMOD_DOUBLE;
+  }
+  else if (internal::is_same<Scalar,std::complex<float> >::value)
+  {
+    mat.xtype = CHOLMOD_COMPLEX;
+    mat.dtype = CHOLMOD_SINGLE;
+  }
+  else if (internal::is_same<Scalar,std::complex<double> >::value)
+  {
+    mat.xtype = CHOLMOD_COMPLEX;
+    mat.dtype = CHOLMOD_DOUBLE;
+  }
+  else
+  {
+    eigen_assert(false && "Scalar type not supported by CHOLMOD");
+  }
+}
+
+} // namespace internal
+
+/** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object.
+  * Note that the data are shared.
+  */
+template<typename _Scalar, int _Options, typename _Index>
+cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat)
+{
+  typedef SparseMatrix<_Scalar,_Options,_Index> MatrixType;
+  cholmod_sparse res;
+  res.nzmax   = mat.nonZeros();
+  res.nrow    = mat.rows();;
+  res.ncol    = mat.cols();
+  res.p       = mat.outerIndexPtr();
+  res.i       = mat.innerIndexPtr();
+  res.x       = mat.valuePtr();
+  res.sorted  = 1;
+  if(mat.isCompressed())
+  {
+    res.packed  = 1;
+  }
+  else
+  {
+    res.packed  = 0;
+    res.nz = mat.innerNonZeroPtr();
+  }
+
+  res.dtype   = 0;
+  res.stype   = -1;
+  
+  if (internal::is_same<_Index,int>::value)
+  {
+    res.itype = CHOLMOD_INT;
+  }
+  else
+  {
+    eigen_assert(false && "Index type different than int is not supported yet");
+  }
+
+  // setup res.xtype
+  internal::cholmod_configure_matrix<_Scalar>(res);
+  
+  res.stype = 0;
+  
+  return res;
+}
+
+template<typename _Scalar, int _Options, typename _Index>
+const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>& mat)
+{
+  cholmod_sparse res = viewAsCholmod(mat.const_cast_derived());
+  return res;
+}
+
+/** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix.
+  * The data are not copied but shared. */
+template<typename _Scalar, int _Options, typename _Index, unsigned int UpLo>
+cholmod_sparse viewAsCholmod(const SparseSelfAdjointView<SparseMatrix<_Scalar,_Options,_Index>, UpLo>& mat)
+{
+  cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived());
+  
+  if(UpLo==Upper) res.stype =  1;
+  if(UpLo==Lower) res.stype = -1;
+
+  return res;
+}
+
+/** Returns a view of the Eigen \b dense matrix \a mat as Cholmod dense matrix.
+  * The data are not copied but shared. */
+template<typename Derived>
+cholmod_dense viewAsCholmod(MatrixBase<Derived>& mat)
+{
+  EIGEN_STATIC_ASSERT((internal::traits<Derived>::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  typedef typename Derived::Scalar Scalar;
+
+  cholmod_dense res;
+  res.nrow   = mat.rows();
+  res.ncol   = mat.cols();
+  res.nzmax  = res.nrow * res.ncol;
+  res.d      = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride();
+  res.x      = mat.derived().data();
+  res.z      = 0;
+
+  internal::cholmod_configure_matrix<Scalar>(res);
+
+  return res;
+}
+
+/** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix.
+  * The data are not copied but shared. */
+template<typename Scalar, int Flags, typename Index>
+MappedSparseMatrix<Scalar,Flags,Index> viewAsEigen(cholmod_sparse& cm)
+{
+  return MappedSparseMatrix<Scalar,Flags,Index>
+         (cm.nrow, cm.ncol, reinterpret_cast<Index*>(cm.p)[cm.ncol],
+          reinterpret_cast<Index*>(cm.p), reinterpret_cast<Index*>(cm.i),reinterpret_cast<Scalar*>(cm.x) );
+}
+
+enum CholmodMode {
+  CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt
+};
+
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodBase
+  * \brief The base class for the direct Cholesky factorization of Cholmod
+  * \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
+  */
+template<typename _MatrixType, int _UpLo, typename Derived>
+class CholmodBase : internal::noncopyable
+{
+  public:
+    typedef _MatrixType MatrixType;
+    enum { UpLo = _UpLo };
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef MatrixType CholMatrixType;
+    typedef typename MatrixType::Index Index;
+
+  public:
+
+    CholmodBase()
+      : m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
+    {
+      cholmod_start(&m_cholmod);
+    }
+
+    CholmodBase(const MatrixType& matrix)
+      : m_cholmodFactor(0), m_info(Success), m_isInitialized(false)
+    {
+      cholmod_start(&m_cholmod);
+      compute(matrix);
+    }
+
+    ~CholmodBase()
+    {
+      if(m_cholmodFactor)
+        cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
+      cholmod_finish(&m_cholmod);
+    }
+    
+    inline Index cols() const { return m_cholmodFactor->n; }
+    inline Index rows() const { return m_cholmodFactor->n; }
+    
+    Derived& derived() { return *static_cast<Derived*>(this); }
+    const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    
+    /** \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 && "Decomposition is not initialized.");
+      return m_info;
+    }
+
+    /** Computes the sparse Cholesky decomposition of \a matrix */
+    Derived& compute(const MatrixType& matrix)
+    {
+      analyzePattern(matrix);
+      factorize(matrix);
+      return derived();
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<CholmodBase, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<CholmodBase, Rhs>(*this, b.derived());
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::sparse_solve_retval<CholmodBase, Rhs>
+    solve(const SparseMatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "LLT is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::sparse_solve_retval<CholmodBase, Rhs>(*this, b.derived());
+    }
+    
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      * 
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    {
+      if(m_cholmodFactor)
+      {
+        cholmod_free_factor(&m_cholmodFactor, &m_cholmod);
+        m_cholmodFactor = 0;
+      }
+      cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
+      m_cholmodFactor = cholmod_analyze(&A, &m_cholmod);
+      
+      this->m_isInitialized = true;
+      this->m_info = Success;
+      m_analysisIsOk = true;
+      m_factorizationIsOk = false;
+    }
+    
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    void factorize(const MatrixType& matrix)
+    {
+      eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
+      cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView<UpLo>());
+      cholmod_factorize(&A, m_cholmodFactor, &m_cholmod);
+      
+      this->m_info = Success;
+      m_factorizationIsOk = true;
+    }
+    
+    /** Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations.
+     *  See the Cholmod user guide for details. */
+    cholmod_common& cholmod() { return m_cholmod; }
+    
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal */
+    template<typename Rhs,typename Dest>
+    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    {
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      const Index size = m_cholmodFactor->n;
+      eigen_assert(size==b.rows());
+
+      // note: cd stands for Cholmod Dense
+      cholmod_dense b_cd = viewAsCholmod(b.const_cast_derived());
+      cholmod_dense* x_cd = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &b_cd, &m_cholmod);
+      if(!x_cd)
+      {
+        this->m_info = NumericalIssue;
+      }
+      // TODO optimize this copy by swapping when possible (be carreful with alignment, etc.)
+      dest = Matrix<Scalar,Dest::RowsAtCompileTime,Dest::ColsAtCompileTime>::Map(reinterpret_cast<Scalar*>(x_cd->x),b.rows(),b.cols());
+      cholmod_free_dense(&x_cd, &m_cholmod);
+    }
+    
+    /** \internal */
+    template<typename RhsScalar, int RhsOptions, typename RhsIndex, typename DestScalar, int DestOptions, typename DestIndex>
+    void _solve(const SparseMatrix<RhsScalar,RhsOptions,RhsIndex> &b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+    {
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      const Index size = m_cholmodFactor->n;
+      eigen_assert(size==b.rows());
+
+      // note: cs stands for Cholmod Sparse
+      cholmod_sparse b_cs = viewAsCholmod(b);
+      cholmod_sparse* x_cs = cholmod_spsolve(CHOLMOD_A, m_cholmodFactor, &b_cs, &m_cholmod);
+      if(!x_cs)
+      {
+        this->m_info = NumericalIssue;
+      }
+      // TODO optimize this copy by swapping when possible (be carreful with alignment, etc.)
+      dest = viewAsEigen<DestScalar,DestOptions,DestIndex>(*x_cs);
+      cholmod_free_sparse(&x_cs, &m_cholmod);
+    }
+    #endif // EIGEN_PARSED_BY_DOXYGEN
+    
+    template<typename Stream>
+    void dumpMemory(Stream& s)
+    {}
+    
+  protected:
+    mutable cholmod_common m_cholmod;
+    cholmod_factor* m_cholmodFactor;
+    mutable ComputationInfo m_info;
+    bool m_isInitialized;
+    int m_factorizationIsOk;
+    int m_analysisIsOk;
+};
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodSimplicialLLT
+  * \brief A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization
+  * using the Cholmod library.
+  * This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Thefore, it has little practical interest.
+  * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLLT
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodSimplicialLLT() : Base() { init(); }
+
+    CholmodSimplicialLLT(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodSimplicialLLT() {}
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 0;
+      m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+      m_cholmod.final_ll = 1;
+    }
+};
+
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodSimplicialLDLT
+  * \brief A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a simplicial LDL^T Cholesky factorization
+  * using the Cholmod library.
+  * This simplicial variant is equivalent to Eigen's built-in SimplicialLDLT class. Thefore, it has little practical interest.
+  * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLDLT
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodSimplicialLDLT() : Base() { init(); }
+
+    CholmodSimplicialLDLT(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodSimplicialLDLT() {}
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 1;
+      m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+    }
+};
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodSupernodalLLT
+  * \brief A supernodal Cholesky (LLT) factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a supernodal LL^T Cholesky factorization
+  * using the Cholmod library.
+  * This supernodal variant performs best on dense enough problems, e.g., 3D FEM, or very high order 2D FEM.
+  * The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodSupernodalLLT() : Base() { init(); }
+
+    CholmodSupernodalLLT(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodSupernodalLLT() {}
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 1;
+      m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
+    }
+};
+
+/** \ingroup CholmodSupport_Module
+  * \class CholmodDecomposition
+  * \brief A general Cholesky factorization and solver based on Cholmod
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization
+  * using the Cholmod library. The sparse matrix A must be selfajoint and positive definite. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * This variant permits to change the underlying Cholesky method at runtime.
+  * On the other hand, it does not provide access to the result of the factorization.
+  * The default is to let Cholmod automatically choose between a simplicial and supernodal factorization.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed.
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType, int _UpLo = Lower>
+class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> >
+{
+    typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base;
+    using Base::m_cholmod;
+    
+  public:
+    
+    typedef _MatrixType MatrixType;
+    
+    CholmodDecomposition() : Base() { init(); }
+
+    CholmodDecomposition(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~CholmodDecomposition() {}
+    
+    void setMode(CholmodMode mode)
+    {
+      switch(mode)
+      {
+        case CholmodAuto:
+          m_cholmod.final_asis = 1;
+          m_cholmod.supernodal = CHOLMOD_AUTO;
+          break;
+        case CholmodSimplicialLLt:
+          m_cholmod.final_asis = 0;
+          m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+          m_cholmod.final_ll = 1;
+          break;
+        case CholmodSupernodalLLt:
+          m_cholmod.final_asis = 1;
+          m_cholmod.supernodal = CHOLMOD_SUPERNODAL;
+          break;
+        case CholmodLDLt:
+          m_cholmod.final_asis = 1;
+          m_cholmod.supernodal = CHOLMOD_SIMPLICIAL;
+          break;
+        default:
+          break;
+      }
+    }
+  protected:
+    void init()
+    {
+      m_cholmod.final_asis = 1;
+      m_cholmod.supernodal = CHOLMOD_AUTO;
+    }
+};
+
+namespace internal {
+  
+template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
+struct solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+  : solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+{
+  typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+template<typename _MatrixType, int _UpLo, typename Derived, typename Rhs>
+struct sparse_solve_retval<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+  : sparse_solve_retval_base<CholmodBase<_MatrixType,_UpLo,Derived>, Rhs>
+{
+  typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CHOLMODSUPPORT_H
diff --git a/extern/Eigen3/Eigen/src/Core/Array.h b/extern/Eigen3/Eigen/src/Core/Array.h
index a11fb1b53d5..aaa38997838 100644
--- a/extern/Eigen3/Eigen/src/Core/Array.h
+++ b/extern/Eigen3/Eigen/src/Core/Array.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ARRAY_H
 #define EIGEN_ARRAY_H
 
+namespace Eigen {
+
 /** \class Array 
   * \ingroup Core_Module
   *
@@ -316,5 +303,6 @@ 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
diff --git a/extern/Eigen3/Eigen/src/Core/ArrayBase.h b/extern/Eigen3/Eigen/src/Core/ArrayBase.h
index 9399ac3d15c..004b117c933 100644
--- a/extern/Eigen3/Eigen/src/Core/ArrayBase.h
+++ b/extern/Eigen3/Eigen/src/Core/ArrayBase.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ARRAYBASE_H
 #define EIGEN_ARRAYBASE_H
 
+namespace Eigen { 
+
 template<typename ExpressionType> class MatrixWrapper;
 
 /** \class ArrayBase
@@ -159,7 +146,7 @@ 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<Derived> matrix() const { return derived(); }
+    const MatrixWrapper<const Derived> matrix() const { return derived(); }
 
 //     template<typename Dest>
 //     inline void evalTo(Dest& dst) const { dst = matrix(); }
@@ -174,10 +161,10 @@ template<typename Derived> class ArrayBase
   protected:
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator+=(const MatrixBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator-=(const MatrixBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
 };
 
 /** replaces \c *this by \c *this - \a other.
@@ -236,4 +223,6 @@ ArrayBase<Derived>::operator/=(const ArrayBase<OtherDerived>& other)
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_ARRAYBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/ArrayWrapper.h b/extern/Eigen3/Eigen/src/Core/ArrayWrapper.h
index 07f082e1edc..87af7fda937 100644
--- a/extern/Eigen3/Eigen/src/Core/ArrayWrapper.h
+++ b/extern/Eigen3/Eigen/src/Core/ArrayWrapper.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ARRAYWRAPPER_H
 #define EIGEN_ARRAYWRAPPER_H
 
+namespace Eigen { 
+
 /** \class ArrayWrapper
   * \ingroup Core_Module
   *
@@ -61,7 +48,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
 
     typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
 
-    inline ArrayWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
+    inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {}
 
     inline Index rows() const { return m_expression.rows(); }
     inline Index cols() const { return m_expression.cols(); }
@@ -71,7 +58,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
     inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline const CoeffReturnType coeff(Index row, Index col) const
+    inline CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
@@ -86,7 +73,7 @@ class ArrayWrapper : public ArrayBase<ArrayWrapper<ExpressionType> >
       return m_expression.const_cast_derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(Index index) const
+    inline CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
@@ -128,8 +115,14 @@ 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:
-    const NestedExpressionType m_expression;
+    NestedExpressionType m_expression;
 };
 
 /** \class MatrixWrapper
@@ -168,7 +161,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
 
     typedef typename internal::nested<ExpressionType>::type NestedExpressionType;
 
-    inline MatrixWrapper(const ExpressionType& matrix) : m_expression(matrix) {}
+    inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {}
 
     inline Index rows() const { return m_expression.rows(); }
     inline Index cols() const { return m_expression.cols(); }
@@ -178,7 +171,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
     inline ScalarWithConstIfNotLvalue* data() { return m_expression.data(); }
     inline const Scalar* data() const { return m_expression.data(); }
 
-    inline const CoeffReturnType coeff(Index row, Index col) const
+    inline CoeffReturnType coeff(Index row, Index col) const
     {
       return m_expression.coeff(row, col);
     }
@@ -193,7 +186,7 @@ class MatrixWrapper : public MatrixBase<MatrixWrapper<ExpressionType> >
       return m_expression.derived().coeffRef(row, col);
     }
 
-    inline const CoeffReturnType coeff(Index index) const
+    inline CoeffReturnType coeff(Index index) const
     {
       return m_expression.coeff(index);
     }
@@ -232,8 +225,16 @@ 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:
-    const NestedExpressionType m_expression;
+    NestedExpressionType m_expression;
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_ARRAYWRAPPER_H
diff --git a/extern/Eigen3/Eigen/src/Core/Assign.h b/extern/Eigen3/Eigen/src/Core/Assign.h
index 3a17152f043..cd29a88f0da 100644
--- a/extern/Eigen3/Eigen/src/Core/Assign.h
+++ b/extern/Eigen3/Eigen/src/Core/Assign.h
@@ -5,28 +5,15 @@
 // Copyright (C) 2006-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ASSIGN_H
 #define EIGEN_ASSIGN_H
 
+namespace Eigen {
+
 namespace internal {
 
 /***************************************************************************
@@ -152,7 +139,7 @@ struct assign_DefaultTraversal_CompleteUnrolling
     inner = Index % Derived1::InnerSizeAtCompileTime
   };
 
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     dst.copyCoeffByOuterInner(outer, inner, src);
     assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
@@ -162,13 +149,13 @@ struct assign_DefaultTraversal_CompleteUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, int Index, int Stop>
 struct assign_DefaultTraversal_InnerUnrolling
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int outer)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, int outer)
   {
     dst.copyCoeffByOuterInner(outer, Index, src);
     assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src, outer);
@@ -178,7 +165,7 @@ struct assign_DefaultTraversal_InnerUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, int) {}
 };
 
 /***********************
@@ -188,7 +175,7 @@ struct assign_DefaultTraversal_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 template<typename Derived1, typename Derived2, int Index, int Stop>
 struct assign_LinearTraversal_CompleteUnrolling
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     dst.copyCoeff(Index, src);
     assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Index+1, Stop>::run(dst, src);
@@ -198,7 +185,7 @@ struct assign_LinearTraversal_CompleteUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
 };
 
 /**************************
@@ -214,7 +201,7 @@ struct assign_innervec_CompleteUnrolling
     JointAlignment = assign_traits<Derived1,Derived2>::JointAlignment
   };
 
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     dst.template copyPacketByOuterInner<Derived2, Aligned, JointAlignment>(outer, inner, src);
     assign_innervec_CompleteUnrolling<Derived1, Derived2,
@@ -225,13 +212,13 @@ struct assign_innervec_CompleteUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_innervec_CompleteUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, int Index, int Stop>
 struct assign_innervec_InnerUnrolling
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src, int outer)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, int outer)
   {
     dst.template copyPacketByOuterInner<Derived2, Aligned, Aligned>(outer, Index, src);
     assign_innervec_InnerUnrolling<Derived1, Derived2,
@@ -242,7 +229,7 @@ struct assign_innervec_InnerUnrolling
 template<typename Derived1, typename Derived2, int Stop>
 struct assign_innervec_InnerUnrolling<Derived1, Derived2, Stop, Stop>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &, const Derived2 &, int) {}
+  static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, int) {}
 };
 
 /***************************************************************************
@@ -251,24 +238,25 @@ 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 Unrolling = assign_traits<Derived1, Derived2>::Unrolling,
+         int Version = Specialized>
 struct assign_impl;
 
 /************************
 *** Default traversal ***
 ************************/
 
-template<typename Derived1, typename Derived2, int Unrolling>
-struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling>
+template<typename Derived1, typename Derived2, int Unrolling, int Version>
+struct assign_impl<Derived1, Derived2, InvalidTraversal, Unrolling, Version>
 {
-  inline static void run(Derived1 &, const Derived2 &) { }
+  static inline void run(Derived1 &, const Derived2 &) { }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     const Index innerSize = dst.innerSize();
     const Index outerSize = dst.outerSize();
@@ -278,21 +266,21 @@ struct assign_impl<Derived1, Derived2, DefaultTraversal, NoUnrolling>
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, CompleteUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     assign_DefaultTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     const Index outerSize = dst.outerSize();
     for(Index outer = 0; outer < outerSize; ++outer)
@@ -305,11 +293,11 @@ struct assign_impl<Derived1, Derived2, DefaultTraversal, InnerUnrolling>
 *** Linear traversal ***
 ***********************/
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     const Index size = dst.size();
     for(Index i = 0; i < size; ++i)
@@ -317,10 +305,10 @@ struct assign_impl<Derived1, Derived2, LinearTraversal, NoUnrolling>
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     assign_LinearTraversal_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
@@ -331,11 +319,11 @@ struct assign_impl<Derived1, Derived2, LinearTraversal, CompleteUnrolling>
 *** Inner vectorization ***
 **************************/
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     const Index innerSize = dst.innerSize();
     const Index outerSize = dst.outerSize();
@@ -346,21 +334,21 @@ struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, NoUnrolling>
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, CompleteUnrolling, Version>
 {
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     assign_innervec_CompleteUnrolling<Derived1, Derived2, 0, Derived1::SizeAtCompileTime>
       ::run(dst, src);
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, InnerVectorizedTraversal, InnerUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     const Index outerSize = dst.outerSize();
     for(Index outer = 0; outer < outerSize; ++outer)
@@ -398,11 +386,11 @@ struct unaligned_assign_impl<false>
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     const Index size = dst.size();
     typedef packet_traits<typename Derived1::Scalar> PacketTraits;
@@ -412,7 +400,7 @@ struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling>
       srcAlignment = assign_traits<Derived1,Derived2>::JointAlignment
     };
     const Index alignedStart = assign_traits<Derived1,Derived2>::DstIsAligned ? 0
-                             : first_aligned(&dst.coeffRef(0), size);
+                             : internal::first_aligned(&dst.coeffRef(0), size);
     const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize;
 
     unaligned_assign_impl<assign_traits<Derived1,Derived2>::DstIsAligned!=0>::run(src,dst,0,alignedStart);
@@ -426,11 +414,11 @@ struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, NoUnrolling>
   }
 };
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  EIGEN_STRONG_INLINE static void run(Derived1 &dst, const Derived2 &src)
+  static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src)
   {
     enum { size = Derived1::SizeAtCompileTime,
            packetSize = packet_traits<typename Derived1::Scalar>::size,
@@ -445,11 +433,11 @@ struct assign_impl<Derived1, Derived2, LinearVectorizedTraversal, CompleteUnroll
 *** Slice vectorization ***
 ***************************/
 
-template<typename Derived1, typename Derived2>
-struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling>
+template<typename Derived1, typename Derived2, int Version>
+struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling, Version>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     typedef packet_traits<typename Derived1::Scalar> PacketTraits;
     enum {
@@ -463,7 +451,7 @@ struct assign_impl<Derived1, Derived2, SliceVectorizedTraversal, NoUnrolling>
     const Index outerSize = dst.outerSize();
     const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0;
     Index alignedStart = ((!alignable) || assign_traits<Derived1,Derived2>::DstIsAligned) ? 0
-                       : first_aligned(&dst.coeffRef(0,0), innerSize);
+                       : internal::first_aligned(&dst.coeffRef(0,0), innerSize);
 
     for(Index outer = 0; outer < outerSize; ++outer)
     {
@@ -531,19 +519,19 @@ struct assign_selector;
 
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,false,false> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); }
 };
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,true,false> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); }
 };
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,false,true> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); }
 };
 template<typename Derived, typename OtherDerived>
 struct assign_selector<Derived,OtherDerived,true,true> {
-  EIGEN_STRONG_INLINE static Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
+  static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); }
 };
 
 } // end namespace internal
@@ -590,4 +578,6 @@ EIGEN_STRONG_INLINE Derived& MatrixBase<Derived>::operator=(const ReturnByValue<
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_ASSIGN_H
diff --git a/extern/Eigen3/Eigen/src/Core/Assign_MKL.h b/extern/Eigen3/Eigen/src/Core/Assign_MKL.h
new file mode 100644
index 00000000000..428c6367b92
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/Assign_MKL.h
@@ -0,0 +1,224 @@
+/*
+ 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)
+
+// The vm*powx functions are not avaibale in the windows version of MKL.
+#ifdef _WIN32
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8)
+EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16)
+#endif
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_ASSIGN_VML_H
diff --git a/extern/Eigen3/Eigen/src/Core/BandMatrix.h b/extern/Eigen3/Eigen/src/Core/BandMatrix.h
index 2570d7b559f..ffd7fe8b301 100644
--- a/extern/Eigen3/Eigen/src/Core/BandMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/BandMatrix.h
@@ -3,30 +3,16 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BANDMATRIX_H
 #define EIGEN_BANDMATRIX_H
 
-namespace internal {
+namespace Eigen { 
 
+namespace internal {
 
 template<typename Derived>
 class BandMatrixBase : public EigenBase<Derived>
@@ -343,4 +329,6 @@ class TridiagonalMatrix : public BandMatrix<Scalar,Size,Size,Options&SelfAdjoint
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_BANDMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/Block.h b/extern/Eigen3/Eigen/src/Core/Block.h
index d470bc13400..5f29cb3d1b3 100644
--- a/extern/Eigen3/Eigen/src/Core/Block.h
+++ b/extern/Eigen3/Eigen/src/Core/Block.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BLOCK_H
 #define EIGEN_BLOCK_H
 
+namespace Eigen { 
+
 /** \class Block
   * \ingroup Core_Module
   *
@@ -242,6 +229,21 @@ 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;
@@ -304,6 +306,11 @@ 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
     {
@@ -341,9 +348,10 @@ class Block<XprType,BlockRows,BlockCols, InnerPanel,true>
                     : m_xpr.innerStride();
     }
 
-    const typename XprType::Nested m_xpr;
+    typename XprType::Nested m_xpr;
     Index m_outerStride;
 };
 
+} // end namespace Eigen
 
 #endif // EIGEN_BLOCK_H
diff --git a/extern/Eigen3/Eigen/src/Core/BooleanRedux.h b/extern/Eigen3/Eigen/src/Core/BooleanRedux.h
index 5c3444a57c9..57efd8e6953 100644
--- a/extern/Eigen3/Eigen/src/Core/BooleanRedux.h
+++ b/extern/Eigen3/Eigen/src/Core/BooleanRedux.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ALLANDANY_H
 #define EIGEN_ALLANDANY_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename Derived, int UnrollCount>
@@ -35,7 +22,7 @@ struct all_unroller
     row = (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
-  inline static bool run(const Derived &mat)
+  static inline bool run(const Derived &mat)
   {
     return all_unroller<Derived, UnrollCount-1>::run(mat) && mat.coeff(row, col);
   }
@@ -44,13 +31,13 @@ struct all_unroller
 template<typename Derived>
 struct all_unroller<Derived, 1>
 {
-  inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
+  static inline bool run(const Derived &mat) { return mat.coeff(0, 0); }
 };
 
 template<typename Derived>
 struct all_unroller<Derived, Dynamic>
 {
-  inline static bool run(const Derived &) { return false; }
+  static inline bool run(const Derived &) { return false; }
 };
 
 template<typename Derived, int UnrollCount>
@@ -61,7 +48,7 @@ struct any_unroller
     row = (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
-  inline static bool run(const Derived &mat)
+  static inline bool run(const Derived &mat)
   {
     return any_unroller<Derived, UnrollCount-1>::run(mat) || mat.coeff(row, col);
   }
@@ -70,13 +57,13 @@ struct any_unroller
 template<typename Derived>
 struct any_unroller<Derived, 1>
 {
-  inline static bool run(const Derived &mat) { return mat.coeff(0, 0); }
+  static inline bool run(const Derived &mat) { return mat.coeff(0, 0); }
 };
 
 template<typename Derived>
 struct any_unroller<Derived, Dynamic>
 {
-  inline static bool run(const Derived &) { return false; }
+  static inline bool run(const Derived &) { return false; }
 };
 
 } // end namespace internal
@@ -146,4 +133,6 @@ 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
diff --git a/extern/Eigen3/Eigen/src/Core/CommaInitializer.h b/extern/Eigen3/Eigen/src/Core/CommaInitializer.h
index 92422bf2fa0..4adce64143c 100644
--- a/extern/Eigen3/Eigen/src/Core/CommaInitializer.h
+++ b/extern/Eigen3/Eigen/src/Core/CommaInitializer.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COMMAINITIALIZER_H
 #define EIGEN_COMMAINITIALIZER_H
 
+namespace Eigen { 
+
 /** \class CommaInitializer
   * \ingroup Core_Module
   *
@@ -147,4 +134,6 @@ DenseBase<Derived>::operator<<(const DenseBase<OtherDerived>& other)
   return CommaInitializer<Derived>(*static_cast<Derived *>(this), other);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_COMMAINITIALIZER_H
diff --git a/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h b/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h
index 7386b2e1843..1b93af31b60 100644
--- a/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h
+++ b/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_BINARY_OP_H
 #define EIGEN_CWISE_BINARY_OP_H
 
+namespace Eigen {
+
 /** \class CwiseBinaryOp
   * \ingroup Core_Module
   *
@@ -167,8 +154,8 @@ class CwiseBinaryOp : internal::no_assignment_operator,
     const BinaryOp& functor() const { return m_functor; }
 
   protected:
-    const LhsNested m_lhs;
-    const RhsNested m_rhs;
+    LhsNested m_lhs;
+    RhsNested m_rhs;
     const BinaryOp m_functor;
 };
 
@@ -237,4 +224,6 @@ MatrixBase<Derived>::operator+=(const MatrixBase<OtherDerived>& other)
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_CWISE_BINARY_OP_H
diff --git a/extern/Eigen3/Eigen/src/Core/CwiseNullaryOp.h b/extern/Eigen3/Eigen/src/Core/CwiseNullaryOp.h
index c616e7ae13d..2635a62b07b 100644
--- a/extern/Eigen3/Eigen/src/Core/CwiseNullaryOp.h
+++ b/extern/Eigen3/Eigen/src/Core/CwiseNullaryOp.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_NULLARY_OP_H
 #define EIGEN_CWISE_NULLARY_OP_H
 
+namespace Eigen {
+
 /** \class CwiseNullaryOp
   * \ingroup Core_Module
   *
@@ -101,6 +88,9 @@ 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;
@@ -238,6 +228,8 @@ 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
@@ -270,6 +262,7 @@ 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
   *
@@ -381,6 +374,7 @@ 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
   *
@@ -396,6 +390,23 @@ 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.
@@ -848,4 +859,6 @@ 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
diff --git a/extern/Eigen3/Eigen/src/Core/CwiseUnaryOp.h b/extern/Eigen3/Eigen/src/Core/CwiseUnaryOp.h
index 958571d64bf..063355ae521 100644
--- a/extern/Eigen3/Eigen/src/Core/CwiseUnaryOp.h
+++ b/extern/Eigen3/Eigen/src/Core/CwiseUnaryOp.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_UNARY_OP_H
 #define EIGEN_CWISE_UNARY_OP_H
 
+namespace Eigen { 
+
 /** \class CwiseUnaryOp
   * \ingroup Core_Module
   *
@@ -95,7 +82,7 @@ class CwiseUnaryOp : internal::no_assignment_operator,
     nestedExpression() { return m_xpr.const_cast_derived(); }
 
   protected:
-    const typename XprType::Nested m_xpr;
+    typename XprType::Nested m_xpr;
     const UnaryOp m_functor;
 };
 
@@ -134,4 +121,6 @@ class CwiseUnaryOpImpl<UnaryOp,XprType,Dense>
     }
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_CWISE_UNARY_OP_H
diff --git a/extern/Eigen3/Eigen/src/Core/CwiseUnaryView.h b/extern/Eigen3/Eigen/src/Core/CwiseUnaryView.h
index d24ef037314..66f73a9505b 100644
--- a/extern/Eigen3/Eigen/src/Core/CwiseUnaryView.h
+++ b/extern/Eigen3/Eigen/src/Core/CwiseUnaryView.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_UNARY_VIEW_H
 #define EIGEN_CWISE_UNARY_VIEW_H
 
+namespace Eigen {
+
 /** \class CwiseUnaryView
   * \ingroup Core_Module
   *
@@ -97,7 +84,7 @@ class CwiseUnaryView : internal::no_assignment_operator,
 
   protected:
     // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC
-    const typename internal::nested<MatrixType>::type m_matrix;
+    typename internal::nested<MatrixType>::type m_matrix;
     ViewOp m_functor;
 };
 
@@ -143,6 +130,6 @@ class CwiseUnaryViewImpl<ViewOp,MatrixType,Dense>
     }
 };
 
-
+} // end namespace Eigen
 
 #endif // EIGEN_CWISE_UNARY_VIEW_H
diff --git a/extern/Eigen3/Eigen/src/Core/DenseBase.h b/extern/Eigen3/Eigen/src/Core/DenseBase.h
index 920904f243a..1cc0314ef0b 100644
--- a/extern/Eigen3/Eigen/src/Core/DenseBase.h
+++ b/extern/Eigen3/Eigen/src/Core/DenseBase.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DENSEBASE_H
 #define EIGEN_DENSEBASE_H
 
+namespace Eigen {
+
 /** \class DenseBase
   * \ingroup Core_Module
   *
@@ -376,12 +363,13 @@ 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 const typename internal::eval<Derived>::type eval() const
+    EIGEN_STRONG_INLINE EvalReturnType 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
@@ -540,4 +528,6 @@ template<typename Derived> class DenseBase
     template<typename OtherDerived> explicit DenseBase(const DenseBase<OtherDerived>&);
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_DENSEBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/DenseCoeffsBase.h b/extern/Eigen3/Eigen/src/Core/DenseCoeffsBase.h
index e45238fb584..72704c2d79f 100644
--- a/extern/Eigen3/Eigen/src/Core/DenseCoeffsBase.h
+++ b/extern/Eigen3/Eigen/src/Core/DenseCoeffsBase.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DENSECOEFFSBASE_H
 #define EIGEN_DENSECOEFFSBASE_H
 
+namespace Eigen {
+
 namespace internal {
 template<typename T> struct add_const_on_value_type_if_arithmetic
 {
@@ -710,16 +697,16 @@ namespace internal {
 template<typename Derived, bool JustReturnZero>
 struct first_aligned_impl
 {
-  inline static typename Derived::Index run(const Derived&)
+  static inline typename Derived::Index run(const Derived&)
   { return 0; }
 };
 
 template<typename Derived>
 struct first_aligned_impl<Derived, false>
 {
-  inline static typename Derived::Index run(const Derived& m)
+  static inline typename Derived::Index run(const Derived& m)
   {
-    return first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
+    return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size());
   }
 };
 
@@ -729,7 +716,7 @@ struct first_aligned_impl<Derived, false>
   * documentation.
   */
 template<typename Derived>
-inline static typename Derived::Index first_aligned(const Derived& m)
+static inline typename Derived::Index first_aligned(const Derived& m)
 {
   return first_aligned_impl
           <Derived, (Derived::Flags & AlignedBit) || !(Derived::Flags & DirectAccessBit)>
@@ -762,4 +749,6 @@ struct outer_stride_at_compile_time<Derived, false>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_DENSECOEFFSBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/DenseStorage.h b/extern/Eigen3/Eigen/src/Core/DenseStorage.h
index 813053b00dd..1fc2daf2c40 100644
--- a/extern/Eigen3/Eigen/src/Core/DenseStorage.h
+++ b/extern/Eigen3/Eigen/src/Core/DenseStorage.h
@@ -5,24 +5,9 @@
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATRIXSTORAGE_H
 #define EIGEN_MATRIXSTORAGE_H
@@ -33,6 +18,8 @@
   #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN
 #endif
 
+namespace Eigen {
+
 namespace internal {
 
 struct constructor_without_unaligned_array_assert {};
@@ -104,8 +91,8 @@ 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); }
-    inline static DenseIndex rows(void) {return _Rows;}
-    inline static DenseIndex cols(void) {return _Cols;}
+    static inline DenseIndex rows(void) {return _Rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
     inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
     inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
     inline const T *data() const { return m_data.array; }
@@ -120,14 +107,24 @@ 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& ) {}
-    inline static DenseIndex rows(void) {return _Rows;}
-    inline static DenseIndex cols(void) {return _Cols;}
+    static inline DenseIndex rows(void) {return _Rows;}
+    static inline DenseIndex cols(void) {return _Cols;}
     inline void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {}
     inline void resize(DenseIndex,DenseIndex,DenseIndex) {}
     inline const T *data() const { return 0; }
     inline T *data() { return 0; }
 };
 
+// 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>
 {
@@ -241,7 +238,7 @@ 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); }
-    inline static DenseIndex rows(void) {return _Rows;}
+    static inline DenseIndex rows(void) {return _Rows;}
     inline DenseIndex cols(void) const {return m_cols;}
     inline void conservativeResize(DenseIndex size, DenseIndex, DenseIndex cols)
     {
@@ -278,7 +275,7 @@ 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;}
-    inline static DenseIndex cols(void) {return _Cols;}
+    static inline DenseIndex cols(void) {return _Cols;}
     inline void conservativeResize(DenseIndex size, DenseIndex rows, DenseIndex)
     {
       m_data = internal::conditional_aligned_realloc_new_auto<T,(_Options&DontAlign)==0>(m_data, size, m_rows*_Cols);
@@ -301,4 +298,6 @@ 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
diff --git a/extern/Eigen3/Eigen/src/Core/Diagonal.h b/extern/Eigen3/Eigen/src/Core/Diagonal.h
index 61d3b063a44..16261968a0f 100644
--- a/extern/Eigen3/Eigen/src/Core/Diagonal.h
+++ b/extern/Eigen3/Eigen/src/Core/Diagonal.h
@@ -2,29 +2,17 @@
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DIAGONAL_H
 #define EIGEN_DIAGONAL_H
 
+namespace Eigen { 
+
 /** \class Diagonal
   * \ingroup Core_Module
   *
@@ -53,16 +41,15 @@ struct traits<Diagonal<MatrixType,DiagIndex> >
   typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
   typedef typename MatrixType::StorageKind StorageKind;
   enum {
-    AbsDiagIndex = DiagIndex<0 ? -DiagIndex : DiagIndex, // only used if DiagIndex != Dynamic
-    // FIXME these computations are broken in the case where the matrix is rectangular and DiagIndex!=0
     RowsAtCompileTime = (int(DiagIndex) == Dynamic || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic
-                      : (EIGEN_SIZE_MIN_PREFER_DYNAMIC(MatrixType::RowsAtCompileTime,
-                                        MatrixType::ColsAtCompileTime) - AbsDiagIndex),
+    : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                            MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
     ColsAtCompileTime = 1,
     MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic
                          : DiagIndex == Dynamic ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime,
-                                                                    MatrixType::MaxColsAtCompileTime)
-                         : (EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime) - AbsDiagIndex),
+                                                                              MatrixType::MaxColsAtCompileTime)
+                         : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0),
+                                                 MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))),
     MaxColsAtCompileTime = 1,
     MaskLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
     Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit,
@@ -101,6 +88,15 @@ 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)
@@ -133,8 +129,19 @@ 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:
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
     const internal::variable_if_dynamic<Index, DiagIndex> m_index;
 
   private:
@@ -224,4 +231,6 @@ MatrixBase<Derived>::diagonal() const
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_DIAGONAL_H
diff --git a/extern/Eigen3/Eigen/src/Core/DiagonalMatrix.h b/extern/Eigen3/Eigen/src/Core/DiagonalMatrix.h
index f41a74bfae7..88190da684d 100644
--- a/extern/Eigen3/Eigen/src/Core/DiagonalMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/DiagonalMatrix.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DIAGONALMATRIX_H
 #define EIGEN_DIAGONALMATRIX_H
 
+namespace Eigen { 
+
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 template<typename Derived>
 class DiagonalBase : public EigenBase<Derived>
@@ -72,7 +59,7 @@ class DiagonalBase : public EigenBase<Derived>
     const DiagonalProduct<MatrixDerived, Derived, OnTheLeft>
     operator*(const MatrixBase<MatrixDerived> &matrix) const;
 
-    inline const DiagonalWrapper<CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
+    inline const DiagonalWrapper<const CwiseUnaryOp<internal::scalar_inverse_op<Scalar>, const DiagonalVectorType> >
     inverse() const
     {
       return diagonal().cwiseInverse();
@@ -251,13 +238,13 @@ class DiagonalWrapper
     #endif
 
     /** Constructor from expression of diagonal coefficients to wrap. */
-    inline DiagonalWrapper(const DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
+    inline DiagonalWrapper(DiagonalVectorType& diagonal) : m_diagonal(diagonal) {}
 
     /** \returns a const reference to the wrapped expression of diagonal coefficients. */
     const DiagonalVectorType& diagonal() const { return m_diagonal; }
 
   protected:
-    const typename DiagonalVectorType::Nested m_diagonal;
+    typename DiagonalVectorType::Nested m_diagonal;
 };
 
 /** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients
@@ -303,4 +290,6 @@ bool MatrixBase<Derived>::isDiagonal(RealScalar prec) const
   return true;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_DIAGONALMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/DiagonalProduct.h b/extern/Eigen3/Eigen/src/Core/DiagonalProduct.h
index de0c6ed11b7..598c6b3e19a 100644
--- a/extern/Eigen3/Eigen/src/Core/DiagonalProduct.h
+++ b/extern/Eigen3/Eigen/src/Core/DiagonalProduct.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DIAGONALPRODUCT_H
 #define EIGEN_DIAGONALPRODUCT_H
 
+namespace Eigen { 
+
 namespace internal {
 template<typename MatrixType, typename DiagonalType, int ProductOrder>
 struct traits<DiagonalProduct<MatrixType, DiagonalType, ProductOrder> >
@@ -107,8 +94,8 @@ class DiagonalProduct : internal::no_assignment_operator,
                      m_diagonal.diagonal().template packet<DiagonalVectorPacketLoadMode>(id));
     }
 
-    const typename MatrixType::Nested m_matrix;
-    const typename DiagonalType::Nested m_diagonal;
+    typename MatrixType::Nested m_matrix;
+    typename DiagonalType::Nested m_diagonal;
 };
 
 /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal.
@@ -131,5 +118,6 @@ DiagonalBase<DiagonalDerived>::operator*(const MatrixBase<MatrixDerived> &matrix
   return DiagonalProduct<MatrixDerived, DiagonalDerived, OnTheLeft>(matrix.derived(), derived());
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_DIAGONALPRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Core/Dot.h b/extern/Eigen3/Eigen/src/Core/Dot.h
index 42da7849896..ae9274e36dd 100644
--- a/extern/Eigen3/Eigen/src/Core/Dot.h
+++ b/extern/Eigen3/Eigen/src/Core/Dot.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2008, 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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
@@ -176,7 +163,7 @@ template<typename Derived, int p>
 struct lpNorm_selector
 {
   typedef typename NumTraits<typename traits<Derived>::Scalar>::Real RealScalar;
-  inline static RealScalar run(const MatrixBase<Derived>& m)
+  static inline RealScalar run(const MatrixBase<Derived>& m)
   {
     return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p);
   }
@@ -185,7 +172,7 @@ struct lpNorm_selector
 template<typename Derived>
 struct lpNorm_selector<Derived, 1>
 {
-  inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.cwiseAbs().sum();
   }
@@ -194,7 +181,7 @@ struct lpNorm_selector<Derived, 1>
 template<typename Derived>
 struct lpNorm_selector<Derived, 2>
 {
-  inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.norm();
   }
@@ -203,7 +190,7 @@ struct lpNorm_selector<Derived, 2>
 template<typename Derived>
 struct lpNorm_selector<Derived, Infinity>
 {
-  inline static typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
+  static inline typename NumTraits<typename traits<Derived>::Scalar>::Real run(const MatrixBase<Derived>& m)
   {
     return m.cwiseAbs().maxCoeff();
   }
@@ -269,4 +256,6 @@ bool MatrixBase<Derived>::isUnitary(RealScalar prec) const
   return true;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_DOT_H
diff --git a/extern/Eigen3/Eigen/src/Core/EigenBase.h b/extern/Eigen3/Eigen/src/Core/EigenBase.h
index 0472539af33..0bbd28bec21 100644
--- a/extern/Eigen3/Eigen/src/Core/EigenBase.h
+++ b/extern/Eigen3/Eigen/src/Core/EigenBase.h
@@ -4,28 +4,14 @@
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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).
   *
@@ -169,4 +155,6 @@ inline void MatrixBase<Derived>::applyOnTheLeft(const EigenBase<OtherDerived> &o
   other.derived().applyThisOnTheLeft(derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_EIGENBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/Flagged.h b/extern/Eigen3/Eigen/src/Core/Flagged.h
index 458213ab553..1f2955fc1de 100644
--- a/extern/Eigen3/Eigen/src/Core/Flagged.h
+++ b/extern/Eigen3/Eigen/src/Core/Flagged.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FLAGGED_H
 #define EIGEN_FLAGGED_H
 
+namespace Eigen { 
+
 /** \class Flagged
   * \ingroup Core_Module
   *
@@ -148,4 +135,6 @@ DenseBase<Derived>::flagged() const
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_FLAGGED_H
diff --git a/extern/Eigen3/Eigen/src/Core/ForceAlignedAccess.h b/extern/Eigen3/Eigen/src/Core/ForceAlignedAccess.h
index 11c1f8f709a..807c7a29346 100644
--- a/extern/Eigen3/Eigen/src/Core/ForceAlignedAccess.h
+++ b/extern/Eigen3/Eigen/src/Core/ForceAlignedAccess.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FORCEALIGNEDACCESS_H
 #define EIGEN_FORCEALIGNEDACCESS_H
 
+namespace Eigen {
+
 /** \class ForceAlignedAccess
   * \ingroup Core_Module
   *
@@ -154,4 +141,6 @@ MatrixBase<Derived>::forceAlignedAccessIf()
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_FORCEALIGNEDACCESS_H
diff --git a/extern/Eigen3/Eigen/src/Core/Functors.h b/extern/Eigen3/Eigen/src/Core/Functors.h
index 54636e0d459..278c46c6b61 100644
--- a/extern/Eigen3/Eigen/src/Core/Functors.h
+++ b/extern/Eigen3/Eigen/src/Core/Functors.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FUNCTORS_H
 #define EIGEN_FUNCTORS_H
 
+namespace Eigen {
+
 namespace internal {
 
 // associative functors:
@@ -178,6 +165,18 @@ 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
@@ -220,6 +219,38 @@ 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
@@ -249,7 +280,7 @@ struct functor_traits<scalar_opposite_op<Scalar> >
 template<typename Scalar> struct scalar_abs_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op)
   typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return abs(a); }
+  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs(a); }
   template<typename Packet>
   EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
   { return internal::pabs(a); }
@@ -271,7 +302,7 @@ struct functor_traits<scalar_abs_op<Scalar> >
 template<typename Scalar> struct scalar_abs2_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op)
   typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return abs2(a); }
+  EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return internal::abs2(a); }
   template<typename Packet>
   EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const
   { return internal::pmul(a,a); }
@@ -287,7 +318,7 @@ struct functor_traits<scalar_abs2_op<Scalar> >
   */
 template<typename Scalar> struct scalar_conjugate_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op)
-  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return conj(a); }
+  EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return internal::conj(a); }
   template<typename Packet>
   EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); }
 };
@@ -324,7 +355,7 @@ template<typename Scalar>
 struct scalar_real_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op)
   typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return real(a); }
+  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::real(a); }
 };
 template<typename Scalar>
 struct functor_traits<scalar_real_op<Scalar> >
@@ -339,7 +370,7 @@ template<typename Scalar>
 struct scalar_imag_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op)
   typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return imag(a); }
+  EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return internal::imag(a); }
 };
 template<typename Scalar>
 struct functor_traits<scalar_imag_op<Scalar> >
@@ -354,7 +385,7 @@ template<typename Scalar>
 struct scalar_real_ref_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op)
   typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return real_ref(*const_cast<Scalar*>(&a)); }
+  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::real_ref(*const_cast<Scalar*>(&a)); }
 };
 template<typename Scalar>
 struct functor_traits<scalar_real_ref_op<Scalar> >
@@ -369,7 +400,7 @@ template<typename Scalar>
 struct scalar_imag_ref_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op)
   typedef typename NumTraits<Scalar>::Real result_type;
-  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return imag_ref(*const_cast<Scalar*>(&a)); }
+  EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return internal::imag_ref(*const_cast<Scalar*>(&a)); }
 };
 template<typename Scalar>
 struct functor_traits<scalar_imag_ref_op<Scalar> >
@@ -383,7 +414,7 @@ struct functor_traits<scalar_imag_ref_op<Scalar> >
   */
 template<typename Scalar> struct scalar_exp_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op)
-  inline const Scalar operator() (const Scalar& a) const { return exp(a); }
+  inline const Scalar operator() (const Scalar& a) const { return internal::exp(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::pexp(a); }
 };
@@ -399,7 +430,7 @@ struct functor_traits<scalar_exp_op<Scalar> >
   */
 template<typename Scalar> struct scalar_log_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op)
-  inline const Scalar operator() (const Scalar& a) const { return log(a); }
+  inline const Scalar operator() (const Scalar& a) const { return internal::log(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::plog(a); }
 };
@@ -584,7 +615,7 @@ 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(low, (high-low)/(num_steps-1)) {}
+  linspaced_op(Scalar low, Scalar high, int num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/(num_steps-1))) {}
 
   template<typename Index>
   EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); }
@@ -657,7 +688,7 @@ struct functor_traits<scalar_add_op<Scalar> >
   */
 template<typename Scalar> struct scalar_sqrt_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op)
-  inline const Scalar operator() (const Scalar& a) const { return sqrt(a); }
+  inline const Scalar operator() (const Scalar& a) const { return internal::sqrt(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); }
 };
@@ -675,7 +706,7 @@ struct functor_traits<scalar_sqrt_op<Scalar> >
   */
 template<typename Scalar> struct scalar_cos_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op)
-  inline Scalar operator() (const Scalar& a) const { return cos(a); }
+  inline Scalar operator() (const Scalar& a) const { return internal::cos(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::pcos(a); }
 };
@@ -694,7 +725,7 @@ struct functor_traits<scalar_cos_op<Scalar> >
   */
 template<typename Scalar> struct scalar_sin_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op)
-  inline const Scalar operator() (const Scalar& a) const { return sin(a); }
+  inline const Scalar operator() (const Scalar& a) const { return internal::sin(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::psin(a); }
 };
@@ -714,7 +745,7 @@ struct functor_traits<scalar_sin_op<Scalar> >
   */
 template<typename Scalar> struct scalar_tan_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op)
-  inline const Scalar operator() (const Scalar& a) const { return tan(a); }
+  inline const Scalar operator() (const Scalar& a) const { return internal::tan(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::ptan(a); }
 };
@@ -733,7 +764,7 @@ struct functor_traits<scalar_tan_op<Scalar> >
   */
 template<typename Scalar> struct scalar_acos_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op)
-  inline const Scalar operator() (const Scalar& a) const { return acos(a); }
+  inline const Scalar operator() (const Scalar& a) const { return internal::acos(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::pacos(a); }
 };
@@ -752,7 +783,7 @@ struct functor_traits<scalar_acos_op<Scalar> >
   */
 template<typename Scalar> struct scalar_asin_op {
   EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op)
-  inline const Scalar operator() (const Scalar& a) const { return asin(a); }
+  inline const Scalar operator() (const Scalar& a) const { return internal::asin(a); }
   typedef typename packet_traits<Scalar>::type Packet;
   inline Packet packetOp(const Packet& a) const { return internal::pasin(a); }
 };
@@ -782,6 +813,20 @@ 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()
   */
@@ -939,4 +984,6 @@ struct functor_traits<std::binary_compose<T0,T1,T2> >
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_FUNCTORS_H
diff --git a/extern/Eigen3/Eigen/src/Core/Fuzzy.h b/extern/Eigen3/Eigen/src/Core/Fuzzy.h
index d266eed0ac6..d74edcfdb9d 100644
--- a/extern/Eigen3/Eigen/src/Core/Fuzzy.h
+++ b/extern/Eigen3/Eigen/src/Core/Fuzzy.h
@@ -4,28 +4,15 @@
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FUZZY_H
 #define EIGEN_FUZZY_H
 
+namespace Eigen { 
+
 namespace internal
 {
 
@@ -35,8 +22,8 @@ struct isApprox_selector
   static bool run(const Derived& x, const OtherDerived& y, typename Derived::RealScalar prec)
   {
     using std::min;
-    const typename internal::nested<Derived,2>::type nested(x);
-    const typename internal::nested<OtherDerived,2>::type otherNested(y);
+    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());
   }
 };
@@ -158,4 +145,6 @@ bool DenseBase<Derived>::isMuchSmallerThan(
   return internal::isMuchSmallerThan_object_selector<Derived, OtherDerived>::run(derived(), other.derived(), prec);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_FUZZY_H
diff --git a/extern/Eigen3/Eigen/src/Core/GeneralProduct.h b/extern/Eigen3/Eigen/src/Core/GeneralProduct.h
new file mode 100644
index 00000000000..bfc2a67b12f
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/GeneralProduct.h
@@ -0,0 +1,613 @@
+// 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>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_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
diff --git a/extern/Eigen3/Eigen/src/Core/GenericPacketMath.h b/extern/Eigen3/Eigen/src/Core/GenericPacketMath.h
index 8ed83532712..858fb243ec8 100644
--- a/extern/Eigen3/Eigen/src/Core/GenericPacketMath.h
+++ b/extern/Eigen3/Eigen/src/Core/GenericPacketMath.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERIC_PACKET_MATH_H
 #define EIGEN_GENERIC_PACKET_MATH_H
 
+namespace Eigen {
+
 namespace internal {
 
 /** \internal
@@ -312,7 +299,7 @@ template<int Offset,typename PacketType>
 struct palign_impl
 {
   // by default data are aligned, so there is nothing to be done :)
-  inline static void run(PacketType&, const PacketType&) {}
+  static inline void run(PacketType&, const PacketType&) {}
 };
 
 /** \internal update \a first using the concatenation of the \a Offset last elements
@@ -335,5 +322,7 @@ template<> inline std::complex<double> pmul(const std::complex<double>& a, const
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_GENERIC_PACKET_MATH_H
 
diff --git a/extern/Eigen3/Eigen/src/Core/GlobalFunctions.h b/extern/Eigen3/Eigen/src/Core/GlobalFunctions.h
index 144145a955c..e63726c4735 100644
--- a/extern/Eigen3/Eigen/src/Core/GlobalFunctions.h
+++ b/extern/Eigen3/Eigen/src/Core/GlobalFunctions.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GLOBAL_FUNCTIONS_H
 #define EIGEN_GLOBAL_FUNCTIONS_H
@@ -66,13 +51,36 @@ 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); \
+  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()
+    );
   }
 }
 
 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)
diff --git a/extern/Eigen3/Eigen/src/Core/IO.h b/extern/Eigen3/Eigen/src/Core/IO.h
index f3cfcdbf4a3..cc8e18a0076 100644
--- a/extern/Eigen3/Eigen/src/Core/IO.h
+++ b/extern/Eigen3/Eigen/src/Core/IO.h
@@ -4,28 +4,15 @@
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_IO_H
 #define EIGEN_IO_H
 
+namespace Eigen { 
+
 enum { DontAlignCols = 1 };
 enum { StreamPrecision = -1,
        FullPrecision = -2 };
@@ -171,7 +158,7 @@ std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat&
     return s;
   }
   
-  const typename Derived::Nested m = _m;
+  typename Derived::Nested m = _m;
   typedef typename Derived::Scalar Scalar;
   typedef typename Derived::Index Index;
 
@@ -257,4 +244,6 @@ std::ostream & operator <<
   return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_IO_H
diff --git a/extern/Eigen3/Eigen/src/Core/Map.h b/extern/Eigen3/Eigen/src/Core/Map.h
index 2bf80b3af3d..15a19226e29 100644
--- a/extern/Eigen3/Eigen/src/Core/Map.h
+++ b/extern/Eigen3/Eigen/src/Core/Map.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2007-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MAP_H
 #define EIGEN_MAP_H
 
+namespace Eigen { 
+
 /** \class Map
   * \ingroup Core_Module
   *
@@ -200,4 +187,6 @@ inline Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>
   this->_set_noalias(Eigen::Map<const Matrix>(data));
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_MAP_H
diff --git a/extern/Eigen3/Eigen/src/Core/MapBase.h b/extern/Eigen3/Eigen/src/Core/MapBase.h
index 9426e2d24dd..a388d61ea92 100644
--- a/extern/Eigen3/Eigen/src/Core/MapBase.h
+++ b/extern/Eigen3/Eigen/src/Core/MapBase.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2007-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MAPBASE_H
 #define EIGEN_MAPBASE_H
@@ -30,6 +15,7 @@
       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
@@ -251,5 +237,6 @@ template<typename Derived> class MapBase<Derived, WriteAccessors>
     using Base::Base::operator=;
 };
 
+} // end namespace Eigen
 
 #endif // EIGEN_MAPBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/MathFunctions.h b/extern/Eigen3/Eigen/src/Core/MathFunctions.h
index 2b454db21e9..05e913f2fec 100644
--- a/extern/Eigen3/Eigen/src/Core/MathFunctions.h
+++ b/extern/Eigen3/Eigen/src/Core/MathFunctions.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATHFUNCTIONS_H
 #define EIGEN_MATHFUNCTIONS_H
 
+namespace Eigen {
+
 namespace internal {
 
 /** \internal \struct global_math_functions_filtering_base
@@ -309,8 +296,7 @@ struct abs2_impl<std::complex<RealScalar> >
 {
   static inline RealScalar run(const std::complex<RealScalar>& x)
   {
-    using std::norm;
-    return norm(x);
+    return real(x)*real(x) + imag(x)*imag(x);
   }
 };
 
@@ -553,7 +539,7 @@ 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;
@@ -838,6 +824,19 @@ 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
diff --git a/extern/Eigen3/Eigen/src/Core/Matrix.h b/extern/Eigen3/Eigen/src/Core/Matrix.h
index 982c9256af0..99160b591b0 100644
--- a/extern/Eigen3/Eigen/src/Core/Matrix.h
+++ b/extern/Eigen3/Eigen/src/Core/Matrix.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATRIX_H
 #define EIGEN_MATRIX_H
 
+namespace Eigen {
+
 /** \class Matrix
   * \ingroup Core_Module
   *
@@ -411,25 +398,8 @@ EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex<double>, cd)
 
 #undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES
 #undef EIGEN_MAKE_TYPEDEFS
+#undef EIGEN_MAKE_FIXED_TYPEDEFS
 
-#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)
+} // end namespace Eigen
 
 #endif // EIGEN_MATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/MatrixBase.h b/extern/Eigen3/Eigen/src/Core/MatrixBase.h
index 62877bce09e..c1e0ed132cc 100644
--- a/extern/Eigen3/Eigen/src/Core/MatrixBase.h
+++ b/extern/Eigen3/Eigen/src/Core/MatrixBase.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2006-2009 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATRIXBASE_H
 #define EIGEN_MATRIXBASE_H
 
+namespace Eigen {
+
 /** \class MatrixBase
   * \ingroup Core_Module
   *
@@ -250,8 +237,7 @@ template<typename Derived> class MatrixBase
     
     // huuuge hack. make Eigen2's matrix.part<Diagonal>() work in eigen3. Problem: Diagonal is now a class template instead
     // of an integer constant. Solution: overload the part() method template wrt template parameters list.
-    // Note: replacing next line by "template<template<typename T, int n> class U>" produces a mysterious error C2082 in MSVC.
-    template<template<typename, int> class U>
+    template<template<typename T, int n> class U>
     const DiagonalWrapper<ConstDiagonalReturnType> part() const
     { return diagonal().asDiagonal(); }
     #endif // EIGEN2_SUPPORT
@@ -331,7 +317,7 @@ 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<Derived> array() const { return derived(); }
+    const ArrayWrapper<const Derived> array() const { return derived(); }
 
 /////////// LU module ///////////
 
@@ -466,6 +452,8 @@ 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>
@@ -512,10 +500,12 @@ template<typename Derived> class MatrixBase
   protected:
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator+=(const ArrayBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
     // mixing arrays and matrices is not legal
     template<typename OtherDerived> Derived& operator-=(const ArrayBase<OtherDerived>& )
-    {EIGEN_STATIC_ASSERT(sizeof(typename OtherDerived::Scalar)==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES);}
+    {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;}
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_MATRIXBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/NestByValue.h b/extern/Eigen3/Eigen/src/Core/NestByValue.h
index a6104d2a426..a893b1761b5 100644
--- a/extern/Eigen3/Eigen/src/Core/NestByValue.h
+++ b/extern/Eigen3/Eigen/src/Core/NestByValue.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_NESTBYVALUE_H
 #define EIGEN_NESTBYVALUE_H
 
+namespace Eigen {
+
 /** \class NestByValue
   * \ingroup Core_Module
   *
@@ -119,4 +106,6 @@ DenseBase<Derived>::nestByValue() const
   return NestByValue<Derived>(derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_NESTBYVALUE_H
diff --git a/extern/Eigen3/Eigen/src/Core/NoAlias.h b/extern/Eigen3/Eigen/src/Core/NoAlias.h
index da64affcf9a..ecb3fa2850e 100644
--- a/extern/Eigen3/Eigen/src/Core/NoAlias.h
+++ b/extern/Eigen3/Eigen/src/Core/NoAlias.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_NOALIAS_H
 #define EIGEN_NOALIAS_H
 
+namespace Eigen {
+
 /** \class NoAlias
   * \ingroup Core_Module
   *
@@ -133,4 +120,6 @@ NoAlias<Derived,MatrixBase> MatrixBase<Derived>::noalias()
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_NOALIAS_H
diff --git a/extern/Eigen3/Eigen/src/Core/NumTraits.h b/extern/Eigen3/Eigen/src/Core/NumTraits.h
index 73ef05dfe7a..c94ef026b42 100644
--- a/extern/Eigen3/Eigen/src/Core/NumTraits.h
+++ b/extern/Eigen3/Eigen/src/Core/NumTraits.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_NUMTRAITS_H
 #define EIGEN_NUMTRAITS_H
 
+namespace Eigen {
+
 /** \class NumTraits
   * \ingroup Core_Module
   *
@@ -81,14 +68,14 @@ template<typename T> struct GenericNumTraits
                    >::type NonInteger;
   typedef T Nested;
 
-  inline static Real epsilon() { return std::numeric_limits<T>::epsilon(); }
-  inline static Real dummy_precision()
+  static inline Real epsilon() { return std::numeric_limits<T>::epsilon(); }
+  static inline Real dummy_precision()
   {
     // make sure to override this for floating-point types
     return Real(0);
   }
-  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)()); }
+  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)()); }
   
 #ifdef EIGEN2_SUPPORT
   enum {
@@ -104,12 +91,12 @@ template<typename T> struct NumTraits : GenericNumTraits<T>
 template<> struct NumTraits<float>
   : GenericNumTraits<float>
 {
-  inline static float dummy_precision() { return 1e-5f; }
+  static inline float dummy_precision() { return 1e-5f; }
 };
 
 template<> struct NumTraits<double> : GenericNumTraits<double>
 {
-  inline static double dummy_precision() { return 1e-12; }
+  static inline double dummy_precision() { return 1e-12; }
 };
 
 template<> struct NumTraits<long double>
@@ -130,8 +117,8 @@ template<typename _Real> struct NumTraits<std::complex<_Real> >
     MulCost = 4 * NumTraits<Real>::MulCost + 2 * NumTraits<Real>::AddCost
   };
 
-  inline static Real epsilon() { return NumTraits<Real>::epsilon(); }
-  inline static Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
+  static inline Real epsilon() { return NumTraits<Real>::epsilon(); }
+  static inline Real dummy_precision() { return NumTraits<Real>::dummy_precision(); }
 };
 
 template<typename Scalar, int Rows, int Cols, int Options, int MaxRows, int MaxCols>
@@ -155,6 +142,6 @@ struct NumTraits<Array<Scalar, Rows, Cols, Options, MaxRows, MaxCols> >
   };
 };
 
-
+} // end namespace Eigen
 
 #endif // EIGEN_NUMTRAITS_H
diff --git a/extern/Eigen3/Eigen/src/Core/PermutationMatrix.h b/extern/Eigen3/Eigen/src/Core/PermutationMatrix.h
index a064e053e51..bc29f814205 100644
--- a/extern/Eigen3/Eigen/src/Core/PermutationMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/PermutationMatrix.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2009-2011 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PERMUTATIONMATRIX_H
 #define EIGEN_PERMUTATIONMATRIX_H
 
+namespace Eigen { 
+
 template<int RowCol,typename IndicesType,typename MatrixType, typename StorageKind> class PermutedImpl;
 
 /** \class PermutationBase
@@ -56,6 +43,8 @@ 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
@@ -511,7 +500,7 @@ class PermutationWrapper : public PermutationBase<PermutationWrapper<_IndicesTyp
 
   protected:
 
-    const typename IndicesType::Nested m_indices;
+    typename IndicesType::Nested m_indices;
 };
 
 /** \returns the matrix with the permutation applied to the columns.
@@ -608,7 +597,7 @@ struct permut_matrix_product_retval
 
   protected:
     const PermutationType& m_permutation;
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
 };
 
 /* Template partial specialization for transposed/inverse permutations */
@@ -693,4 +682,6 @@ const PermutationWrapper<const Derived> MatrixBase<Derived>::asPermutation() con
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_PERMUTATIONMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/PlainObjectBase.h b/extern/Eigen3/Eigen/src/Core/PlainObjectBase.h
index 612254e9da9..71c74309acc 100644
--- a/extern/Eigen3/Eigen/src/Core/PlainObjectBase.h
+++ b/extern/Eigen3/Eigen/src/Core/PlainObjectBase.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DENSESTORAGEBASE_H
 #define EIGEN_DENSESTORAGEBASE_H
@@ -32,6 +17,8 @@
 # define EIGEN_INITIALIZE_BY_ZERO_IF_THAT_OPTION_IS_ENABLED
 #endif
 
+namespace Eigen {
+
 namespace internal {
 
 template<typename Index>
@@ -47,13 +34,13 @@ EIGEN_ALWAYS_INLINE void check_rows_cols_for_overflow(Index rows, Index cols)
     throw_std_bad_alloc();
 }
 
-template <typename Derived, typename OtherDerived = Derived, bool IsVector = static_cast<bool>(Derived::IsVectorAtCompileTime)> struct conservative_resize_like_impl;
+template <typename Derived, typename OtherDerived = Derived, bool IsVector = 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
@@ -61,8 +48,29 @@ 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 };
@@ -443,68 +451,68 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
       * \see class Map
       */
     //@{
-    inline static ConstMapType Map(const Scalar* data)
+    static inline ConstMapType Map(const Scalar* data)
     { return ConstMapType(data); }
-    inline static MapType Map(Scalar* data)
+    static inline MapType Map(Scalar* data)
     { return MapType(data); }
-    inline static ConstMapType Map(const Scalar* data, Index size)
+    static inline ConstMapType Map(const Scalar* data, Index size)
     { return ConstMapType(data, size); }
-    inline static MapType Map(Scalar* data, Index size)
+    static inline MapType Map(Scalar* data, Index size)
     { return MapType(data, size); }
-    inline static ConstMapType Map(const Scalar* data, Index rows, Index cols)
+    static inline ConstMapType Map(const Scalar* data, Index rows, Index cols)
     { return ConstMapType(data, rows, cols); }
-    inline static MapType Map(Scalar* data, Index rows, Index cols)
+    static inline MapType Map(Scalar* data, Index rows, Index cols)
     { return MapType(data, rows, cols); }
 
-    inline static ConstAlignedMapType MapAligned(const Scalar* data)
+    static inline ConstAlignedMapType MapAligned(const Scalar* data)
     { return ConstAlignedMapType(data); }
-    inline static AlignedMapType MapAligned(Scalar* data)
+    static inline AlignedMapType MapAligned(Scalar* data)
     { return AlignedMapType(data); }
-    inline static ConstAlignedMapType MapAligned(const Scalar* data, Index size)
+    static inline ConstAlignedMapType MapAligned(const Scalar* data, Index size)
     { return ConstAlignedMapType(data, size); }
-    inline static AlignedMapType MapAligned(Scalar* data, Index size)
+    static inline AlignedMapType MapAligned(Scalar* data, Index size)
     { return AlignedMapType(data, size); }
-    inline static ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols)
+    static inline ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols)
     { return ConstAlignedMapType(data, rows, cols); }
-    inline static AlignedMapType MapAligned(Scalar* data, Index rows, Index cols)
+    static inline AlignedMapType MapAligned(Scalar* data, Index rows, Index cols)
     { return AlignedMapType(data, rows, cols); }
 
     template<int Outer, int Inner>
-    inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedConstMapType<Stride<Outer, Inner> >::type Map(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedMapType<Stride<Outer, Inner> >::type Map(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index size, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedConstAlignedMapType<Stride<Outer, Inner> >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    static inline 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>
-    inline static typename StridedAlignedMapType<Stride<Outer, Inner> >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride<Outer, Inner>& stride)
+    static inline 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); }
     //@}
 
@@ -594,6 +602,9 @@ 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);      
@@ -623,7 +634,7 @@ class PlainObjectBase : public internal::dense_xpr_base<Derived>::type
 
   public:
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-    EIGEN_STRONG_INLINE static void _check_template_params()
+    static EIGEN_STRONG_INLINE 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)
@@ -751,4 +762,6 @@ struct matrix_swap_impl<MatrixTypeA, MatrixTypeB, true>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_DENSESTORAGEBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/Product.h b/extern/Eigen3/Eigen/src/Core/Product.h
index e2035b242b1..30aa8943b4c 100644
--- a/extern/Eigen3/Eigen/src/Core/Product.h
+++ b/extern/Eigen3/Eigen/src/Core/Product.h
@@ -1,625 +1,98 @@
 // 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 Gael Guennebaud <gael.guennebaud@inria.fr>
+// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla Public
+// License, v. 2.0. If a copy of the MPL was not distributed with this
+// file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PRODUCT_H
 #define EIGEN_PRODUCT_H
 
-/** \class GeneralProduct
+template<typename Lhs, typename Rhs> class Product;
+template<typename Lhs, typename Rhs, typename StorageKind> class ProductImpl;
+
+/** \class Product
   * \ingroup Core_Module
   *
-  * \brief Expression of the product of two general matrices or vectors
+  * \brief Expression of the product of two arbitrary 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
+  * \param Lhs the type of the left-hand side expression
+  * \param Rhs the type of the right-hand side expression
   *
-  * 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.
+  * This class represents an expression of the product of two arbitrary matrices.
   *
-  * \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:
+template<typename Lhs, typename Rhs>
+struct traits<Product<Lhs, Rhs> >
+{
+  typedef MatrixXpr XprKind;
+  typedef typename remove_all<Lhs>::type LhsCleaned;
+  typedef typename remove_all<Rhs>::type RhsCleaned;
+  typedef typename scalar_product_traits<typename traits<LhsCleaned>::Scalar, typename traits<RhsCleaned>::Scalar>::ReturnType Scalar;
+  typedef typename promote_storage_type<typename traits<LhsCleaned>::StorageKind,
+                                        typename traits<RhsCleaned>::StorageKind>::ret StorageKind;
+  typedef typename promote_index_type<typename traits<LhsCleaned>::Index,
+                                      typename traits<RhsCleaned>::Index>::type Index;
   enum {
-    value = selector::ret
+    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
   };
-#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>
+class Product : public ProductImpl<Lhs,Rhs,typename internal::promote_storage_type<typename internal::traits<Lhs>::StorageKind,
+                                                                            typename internal::traits<Rhs>::StorageKind>::ret>
 {
   public:
-    EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct)
-
-    GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs)
+    
+    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)
     {
-      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)
+      eigen_assert(lhs.cols() == rhs.rows()
+        && "invalid matrix product"
+        && "if you wanted a coeff-wise or a dot product use the respective explicit functions");
     }
 
-    template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
-    {
-      internal::outer_product_selector<(int(Dest::Flags)&RowMajorBit) ? RowMajor : ColMajor>::run(*this, dest, alpha);
-    }
-};
+    inline Index rows() const { return m_lhs.rows(); }
+    inline Index cols() const { return m_rhs.cols(); }
 
-namespace internal {
+    const LhsNestedCleaned& lhs() const { return m_lhs; }
+    const RhsNestedCleaned& rhs() const { return m_rhs; }
 
-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();
-  }
-};
+  protected:
 
-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();
-  }
+    const LhsNested m_lhs;
+    const RhsNested m_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>
+class ProductImpl<Lhs,Rhs,Dense> : public internal::dense_xpr_base<Product<Lhs,Rhs> >::type
 {
+    typedef Product<Lhs, Rhs> Derived;
   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();
-  }
+    typedef typename internal::dense_xpr_base<Product<Lhs, Rhs> >::type Base;
+    EIGEN_DENSE_PUBLIC_INTERFACE(Derived)
 };
 
-} // 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
diff --git a/extern/Eigen3/Eigen/src/Core/ProductBase.h b/extern/Eigen3/Eigen/src/Core/ProductBase.h
index 91975880fdc..ec12e5c9f6b 100644
--- a/extern/Eigen3/Eigen/src/Core/ProductBase.h
+++ b/extern/Eigen3/Eigen/src/Core/ProductBase.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PRODUCTBASE_H
 #define EIGEN_PRODUCTBASE_H
 
+namespace Eigen { 
+
 /** \class ProductBase
   * \ingroup Core_Module
   *
@@ -115,10 +102,10 @@ 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,1); }
+    inline void addTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(1)); }
 
     template<typename Dest>
-    inline void subTo(Dest& dst) const { scaleAndAddTo(dst,-1); }
+    inline void subTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(-1)); }
 
     template<typename Dest>
     inline void scaleAndAddTo(Dest& dst,Scalar alpha) const { derived().scaleAndAddTo(dst,alpha); }
@@ -181,8 +168,8 @@ class ProductBase : public MatrixBase<Derived>
 
   protected:
 
-    const LhsNested m_lhs;
-    const RhsNested m_rhs;
+    LhsNested m_lhs;
+    RhsNested m_rhs;
 
     mutable PlainObject m_result;
 };
@@ -286,5 +273,6 @@ Derived& MatrixBase<Derived>::lazyAssign(const ProductBase<ProductDerived, Lhs,R
   return derived();
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_PRODUCTBASE_H
diff --git a/extern/Eigen3/Eigen/src/Core/Random.h b/extern/Eigen3/Eigen/src/Core/Random.h
index b7d90103a5b..a9f7f434666 100644
--- a/extern/Eigen3/Eigen/src/Core/Random.h
+++ b/extern/Eigen3/Eigen/src/Core/Random.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_RANDOM_H
 #define EIGEN_RANDOM_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename Scalar> struct scalar_random_op {
@@ -160,4 +147,6 @@ PlainObjectBase<Derived>::setRandom(Index rows, Index cols)
   return setRandom();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_RANDOM_H
diff --git a/extern/Eigen3/Eigen/src/Core/Redux.h b/extern/Eigen3/Eigen/src/Core/Redux.h
index f9f5a95d546..b7ce7c658a2 100644
--- a/extern/Eigen3/Eigen/src/Core/Redux.h
+++ b/extern/Eigen3/Eigen/src/Core/Redux.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_REDUX_H
 #define EIGEN_REDUX_H
 
+namespace Eigen { 
+
 namespace internal {
 
 // TODO
@@ -95,7 +82,7 @@ struct redux_novec_unroller
 
   typedef typename Derived::Scalar Scalar;
 
-  EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func& func)
+  static EIGEN_STRONG_INLINE 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));
@@ -112,7 +99,7 @@ struct redux_novec_unroller<Func, Derived, Start, 1>
 
   typedef typename Derived::Scalar Scalar;
 
-  EIGEN_STRONG_INLINE static Scalar run(const Derived &mat, const Func&)
+  static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func&)
   {
     return mat.coeffByOuterInner(outer, inner);
   }
@@ -125,7 +112,7 @@ template<typename Func, typename Derived, int Start>
 struct redux_novec_unroller<Func, Derived, Start, 0>
 {
   typedef typename Derived::Scalar Scalar;
-  EIGEN_STRONG_INLINE static Scalar run(const Derived&, const Func&) { return Scalar(); }
+  static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); }
 };
 
 /*** vectorization ***/
@@ -141,7 +128,7 @@ struct redux_vec_unroller
   typedef typename Derived::Scalar Scalar;
   typedef typename packet_traits<Scalar>::type PacketScalar;
 
-  EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func& func)
+  static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func& func)
   {
     return func.packetOp(
             redux_vec_unroller<Func, Derived, Start, HalfLength>::run(mat,func),
@@ -162,7 +149,7 @@ struct redux_vec_unroller<Func, Derived, Start, 1>
   typedef typename Derived::Scalar Scalar;
   typedef typename packet_traits<Scalar>::type PacketScalar;
 
-  EIGEN_STRONG_INLINE static PacketScalar run(const Derived &mat, const Func&)
+  static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func&)
   {
     return mat.template packetByOuterInner<alignment>(outer, inner);
   }
@@ -214,20 +201,33 @@ 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 = first_aligned(mat);
+    const Index alignedStart = internal::first_aligned(mat);
     enum {
       alignment = bool(Derived::Flags & DirectAccessBit) || bool(Derived::Flags & AlignedBit)
                 ? Aligned : Unaligned
     };
-    const Index alignedSize = ((size-alignedStart)/packetSize)*packetSize;
-    const Index alignedEnd = alignedStart + alignedSize;
+    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;
     Scalar res;
     if(alignedSize)
     {
-      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);
+      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);
 
       for(Index index = 0; index < alignedStart; ++index)
         res = func(res,mat.coeff(index));
@@ -296,7 +296,7 @@ struct redux_impl<Func, Derived, LinearVectorizedTraversal, CompleteUnrolling>
     Size = Derived::SizeAtCompileTime,
     VectorizedSize = (Size / PacketSize) * PacketSize
   };
-  EIGEN_STRONG_INLINE static Scalar run(const Derived& mat, const Func& func)
+  static EIGEN_STRONG_INLINE 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));
@@ -401,4 +401,6 @@ MatrixBase<Derived>::trace() const
   return derived().diagonal().sum();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_REDUX_H
diff --git a/extern/Eigen3/Eigen/src/Core/Replicate.h b/extern/Eigen3/Eigen/src/Core/Replicate.h
index 4c171f8d580..b61fdc29e2f 100644
--- a/extern/Eigen3/Eigen/src/Core/Replicate.h
+++ b/extern/Eigen3/Eigen/src/Core/Replicate.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_REPLICATE_H
 #define EIGEN_REPLICATE_H
 
+namespace Eigen { 
+
 /**
   * \class Replicate
   * \ingroup Core_Module
@@ -92,7 +79,7 @@ template<typename MatrixType,int RowFactor,int ColFactor> class Replicate
     }
 
     template<typename OriginalMatrixType>
-    inline Replicate(const OriginalMatrixType& matrix, int rowFactor, int colFactor)
+    inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor)
       : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor)
     {
       EIGEN_STATIC_ASSERT((internal::is_same<typename internal::remove_const<MatrixType>::type,OriginalMatrixType>::value),
@@ -127,9 +114,13 @@ 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:
-    const MatrixTypeNested m_matrix;
+    MatrixTypeNested m_matrix;
     const internal::variable_if_dynamic<Index, RowFactor> m_rowFactor;
     const internal::variable_if_dynamic<Index, ColFactor> m_colFactor;
 };
@@ -181,4 +172,6 @@ VectorwiseOp<ExpressionType,Direction>::replicate(Index factor) const
           (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_REPLICATE_H
diff --git a/extern/Eigen3/Eigen/src/Core/ReturnByValue.h b/extern/Eigen3/Eigen/src/Core/ReturnByValue.h
index 24c5a4e215d..613912ffa8c 100644
--- a/extern/Eigen3/Eigen/src/Core/ReturnByValue.h
+++ b/extern/Eigen3/Eigen/src/Core/ReturnByValue.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2009-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_RETURNBYVALUE_H
 #define EIGEN_RETURNBYVALUE_H
 
+namespace Eigen {
+
 /** \class ReturnByValue
   * \ingroup Core_Module
   *
@@ -96,4 +83,6 @@ Derived& DenseBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_RETURNBYVALUE_H
diff --git a/extern/Eigen3/Eigen/src/Core/Reverse.h b/extern/Eigen3/Eigen/src/Core/Reverse.h
index 600744ae758..e30ae3d281b 100644
--- a/extern/Eigen3/Eigen/src/Core/Reverse.h
+++ b/extern/Eigen3/Eigen/src/Core/Reverse.h
@@ -5,28 +5,15 @@
 // Copyright (C) 2009 Ricard Marxer <email@ricardmarxer.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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_REVERSE_H
 #define EIGEN_REVERSE_H
 
+namespace Eigen { 
+
 /** \class Reverse
   * \ingroup Core_Module
   *
@@ -183,8 +170,14 @@ 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:
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
 };
 
 /** \returns an expression of the reverse of *this.
@@ -226,5 +219,6 @@ inline void DenseBase<Derived>::reverseInPlace()
   derived() = derived().reverse().eval();
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_REVERSE_H
diff --git a/extern/Eigen3/Eigen/src/Core/Select.h b/extern/Eigen3/Eigen/src/Core/Select.h
index d0cd66a261a..2bf6e91d0aa 100644
--- a/extern/Eigen3/Eigen/src/Core/Select.h
+++ b/extern/Eigen3/Eigen/src/Core/Select.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELECT_H
 #define EIGEN_SELECT_H
 
+namespace Eigen { 
+
 /** \class Select
   * \ingroup Core_Module
   *
@@ -101,10 +88,25 @@ 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:
-    const typename ConditionMatrixType::Nested m_condition;
-    const typename ThenMatrixType::Nested m_then;
-    const typename ElseMatrixType::Nested m_else;
+    typename ConditionMatrixType::Nested m_condition;
+    typename ThenMatrixType::Nested m_then;
+    typename ElseMatrixType::Nested m_else;
 };
 
 
@@ -155,4 +157,6 @@ DenseBase<Derived>::select(typename ElseDerived::Scalar thenScalar,
     derived(), ElseDerived::Constant(rows(),cols(),thenScalar), elseMatrix.derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SELECT_H
diff --git a/extern/Eigen3/Eigen/src/Core/SelfAdjointView.h b/extern/Eigen3/Eigen/src/Core/SelfAdjointView.h
index 4bb68755eee..82cc4da736a 100644
--- a/extern/Eigen3/Eigen/src/Core/SelfAdjointView.h
+++ b/extern/Eigen3/Eigen/src/Core/SelfAdjointView.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELFADJOINTMATRIX_H
 #define EIGEN_SELFADJOINTMATRIX_H
 
+namespace Eigen { 
+
 /** \class SelfAdjointView
   * \ingroup Core_Module
   *
@@ -82,7 +69,7 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
     };
     typedef typename MatrixType::PlainObject PlainObject;
 
-    inline SelfAdjointView(const MatrixType& matrix) : m_matrix(matrix)
+    inline SelfAdjointView(MatrixType& matrix) : m_matrix(matrix)
     {}
 
     inline Index rows() const { return m_matrix.rows(); }
@@ -199,7 +186,7 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
     #endif
 
   protected:
-    const MatrixTypeNested m_matrix;
+    MatrixTypeNested m_matrix;
 };
 
 
@@ -222,7 +209,7 @@ struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), U
     row = (UnrollCount-1) % Derived1::RowsAtCompileTime
   };
 
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Upper), UnrollCount-1, ClearOpposite>::run(dst, src);
 
@@ -236,7 +223,7 @@ 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>
 {
-  inline static void run(Derived1 &, const Derived2 &) {}
+  static inline void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, int UnrollCount, bool ClearOpposite>
@@ -247,7 +234,7 @@ struct triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), U
     row = (UnrollCount-1) % Derived1::RowsAtCompileTime
   };
 
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     triangular_assignment_selector<Derived1, Derived2, (SelfAdjoint|Lower), UnrollCount-1, ClearOpposite>::run(dst, src);
 
@@ -261,14 +248,14 @@ 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>
 {
-  inline static void run(Derived1 &, const Derived2 &) {}
+  static inline 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;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -285,7 +272,7 @@ 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>
 {
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
   typedef typename Derived1::Index Index;
     for(Index i = 0; i < dst.rows(); ++i)
@@ -322,4 +309,6 @@ MatrixBase<Derived>::selfadjointView()
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SELFADJOINTMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/SelfCwiseBinaryOp.h b/extern/Eigen3/Eigen/src/Core/SelfCwiseBinaryOp.h
index 4e9ca88745d..0caf2bab1d8 100644
--- a/extern/Eigen3/Eigen/src/Core/SelfCwiseBinaryOp.h
+++ b/extern/Eigen3/Eigen/src/Core/SelfCwiseBinaryOp.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELFCWISEBINARYOP_H
 #define EIGEN_SELFCWISEBINARYOP_H
 
+namespace Eigen { 
+
 /** \class SelfCwiseBinaryOp
   * \ingroup Core_Module
   *
@@ -163,6 +150,16 @@ 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;
@@ -192,4 +189,6 @@ inline Derived& DenseBase<Derived>::operator/=(const Scalar& other)
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SELFCWISEBINARYOP_H
diff --git a/extern/Eigen3/Eigen/src/Core/SolveTriangular.h b/extern/Eigen3/Eigen/src/Core/SolveTriangular.h
index a23014a343f..ef17f288e29 100644
--- a/extern/Eigen3/Eigen/src/Core/SolveTriangular.h
+++ b/extern/Eigen3/Eigen/src/Core/SolveTriangular.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SOLVETRIANGULAR_H
 #define EIGEN_SOLVETRIANGULAR_H
 
+namespace Eigen { 
+
 namespace internal {
 
 // Forward declarations:
@@ -98,12 +85,22 @@ struct triangular_solver_selector<Lhs,Rhs,Side,Mode,NoUnrolling,Dynamic>
   typedef typename Rhs::Index Index;
   typedef blas_traits<Lhs> LhsProductTraits;
   typedef typename LhsProductTraits::DirectLinearAccessType ActualLhsType;
+
   static void run(const Lhs& lhs, Rhs& rhs)
   {
-    const ActualLhsType actualLhs = LhsProductTraits::extract(lhs);
+    typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsProductTraits::extract(lhs);
+
+    const Index size = lhs.rows();
+    const Index othersize = Side==OnTheLeft? rhs.cols() : rhs.rows();
+
+    typedef internal::gemm_blocking_space<(Rhs::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
+              Rhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxRowsAtCompileTime,4> BlockingType;
+
+    BlockingType blocking(rhs.rows(), rhs.cols(), size);
+
     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());
+      ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.outerStride(), blocking);
   }
 };
 
@@ -177,10 +174,8 @@ 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());
-  eigen_assert( (Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols()) );
-  eigen_assert(!(Mode & ZeroDiag));
-  eigen_assert((Mode & (Upper|Lower)) != 0);
+  eigen_assert( cols() == rows() && ((Side==OnTheLeft && cols() == other.rows()) || (Side==OnTheRight && cols() == other.cols())) );
+  eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
 
   enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit  && OtherDerived::IsVectorAtCompileTime };
   typedef typename internal::conditional<copy,
@@ -255,9 +250,11 @@ template<int Side, typename TriangularType, typename Rhs> struct triangular_solv
 
   protected:
     const TriangularType& m_triangularMatrix;
-    const typename Rhs::Nested m_rhs;
+    typename Rhs::Nested m_rhs;
 };
 
 } // namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_SOLVETRIANGULAR_H
diff --git a/extern/Eigen3/Eigen/src/Core/StableNorm.h b/extern/Eigen3/Eigen/src/Core/StableNorm.h
index f667272e4a4..d8bf7db70e4 100644
--- a/extern/Eigen3/Eigen/src/Core/StableNorm.h
+++ b/extern/Eigen3/Eigen/src/Core/StableNorm.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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)
@@ -58,9 +45,9 @@ 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
   };
@@ -187,4 +174,6 @@ MatrixBase<Derived>::hypotNorm() const
   return this->cwiseAbs().redux(internal::scalar_hypot_op<RealScalar>());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_STABLENORM_H
diff --git a/extern/Eigen3/Eigen/src/Core/Stride.h b/extern/Eigen3/Eigen/src/Core/Stride.h
index 0430f111627..1e3f5fe9fff 100644
--- a/extern/Eigen3/Eigen/src/Core/Stride.h
+++ b/extern/Eigen3/Eigen/src/Core/Stride.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STRIDE_H
 #define EIGEN_STRIDE_H
 
+namespace Eigen { 
+
 /** \class Stride
   * \ingroup Core_Module
   *
@@ -116,4 +103,6 @@ class OuterStride : public Stride<Value, 0>
     OuterStride(Index v) : Base(v,0) {}
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_STRIDE_H
diff --git a/extern/Eigen3/Eigen/src/Core/Swap.h b/extern/Eigen3/Eigen/src/Core/Swap.h
index 5fb03286675..fd73cf3ad7e 100644
--- a/extern/Eigen3/Eigen/src/Core/Swap.h
+++ b/extern/Eigen3/Eigen/src/Core/Swap.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SWAP_H
 #define EIGEN_SWAP_H
 
+namespace Eigen { 
+
 /** \class SwapWrapper
   * \ingroup Core_Module
   *
@@ -52,6 +39,15 @@ 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)
     {
@@ -119,8 +115,12 @@ 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
diff --git a/extern/Eigen3/Eigen/src/Core/Transpose.h b/extern/Eigen3/Eigen/src/Core/Transpose.h
index 3f7c7df6ee1..045a1cce671 100644
--- a/extern/Eigen3/Eigen/src/Core/Transpose.h
+++ b/extern/Eigen3/Eigen/src/Core/Transpose.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2006-2008 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRANSPOSE_H
 #define EIGEN_TRANSPOSE_H
 
+namespace Eigen { 
+
 /** \class Transpose
   * \ingroup Core_Module
   *
@@ -91,7 +78,7 @@ template<typename MatrixType> class Transpose
     nestedExpression() { return m_matrix.const_cast_derived(); }
 
   protected:
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
 };
 
 namespace internal {
@@ -152,12 +139,12 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Dense>
       return derived().nestedExpression().coeffRef(index);
     }
 
-    inline const CoeffReturnType coeff(Index row, Index col) const
+    inline CoeffReturnType coeff(Index row, Index col) const
     {
       return derived().nestedExpression().coeff(col, row);
     }
 
-    inline const CoeffReturnType coeff(Index index) const
+    inline CoeffReturnType coeff(Index index) const
     {
       return derived().nestedExpression().coeff(index);
     }
@@ -422,4 +409,6 @@ void DenseBase<Derived>::checkTransposeAliasing(const OtherDerived& other) const
 }
 #endif
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRANSPOSE_H
diff --git a/extern/Eigen3/Eigen/src/Core/Transpositions.h b/extern/Eigen3/Eigen/src/Core/Transpositions.h
index 88fdfb2226f..2cd268a5fa0 100644
--- a/extern/Eigen3/Eigen/src/Core/Transpositions.h
+++ b/extern/Eigen3/Eigen/src/Core/Transpositions.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2010-2011 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRANSPOSITIONS_H
 #define EIGEN_TRANSPOSITIONS_H
 
+namespace Eigen { 
+
 /** \class Transpositions
   * \ingroup Core_Module
   *
@@ -404,7 +391,7 @@ struct transposition_matrix_product_retval
 
   protected:
     const TranspositionType& m_transpositions;
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
 };
 
 } // end namespace internal
@@ -444,4 +431,6 @@ class Transpose<TranspositionsBase<TranspositionsDerived> >
     const TranspositionType& m_transpositions;
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRANSPOSITIONS_H
diff --git a/extern/Eigen3/Eigen/src/Core/TriangularMatrix.h b/extern/Eigen3/Eigen/src/Core/TriangularMatrix.h
index 033e81036f3..de9540063c2 100644
--- a/extern/Eigen3/Eigen/src/Core/TriangularMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/TriangularMatrix.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULARMATRIX_H
 #define EIGEN_TRIANGULARMATRIX_H
 
+namespace Eigen { 
+
 namespace internal {
   
 template<int Side, typename TriangularType, typename Rhs> struct triangular_solve_retval;
@@ -273,11 +260,8 @@ 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<typename MatrixType::AdjointReturnType,TransposeMode> adjoint() const
+    inline const TriangularView<const typename MatrixType::AdjointReturnType,TransposeMode> adjoint() const
     { return m_matrix.adjoint(); }
 
     /** \sa MatrixBase::transpose() */
@@ -288,11 +272,13 @@ 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
@@ -375,7 +361,8 @@ template<typename _MatrixType, unsigned int _Mode> class TriangularView
     template<typename OtherDerived>
     void swap(MatrixBase<OtherDerived> const & other)
     {
-      TriangularView<SwapWrapper<MatrixType>,Mode>(const_cast<MatrixType&>(m_matrix)).lazyAssign(other.derived());
+      SwapWrapper<MatrixType> swaper(const_cast<MatrixType&>(m_matrix));
+      TriangularView<SwapWrapper<MatrixType>,Mode>(swaper).lazyAssign(other.derived());
     }
 
     Scalar determinant() const
@@ -433,7 +420,7 @@ 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);
 
-    const MatrixTypeNested m_matrix;
+    MatrixTypeNested m_matrix;
 };
 
 /***************************************************************************
@@ -452,7 +439,7 @@ struct triangular_assignment_selector
   
   typedef typename Derived1::Scalar Scalar;
 
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     triangular_assignment_selector<Derived1, Derived2, Mode, UnrollCount-1, ClearOpposite>::run(dst, src);
 
@@ -480,7 +467,7 @@ struct triangular_assignment_selector
 template<typename Derived1, typename Derived2, unsigned int Mode, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, Mode, 0, ClearOpposite>
 {
-  inline static void run(Derived1 &, const Derived2 &) {}
+  static inline void run(Derived1 &, const Derived2 &) {}
 };
 
 template<typename Derived1, typename Derived2, bool ClearOpposite>
@@ -488,7 +475,7 @@ struct triangular_assignment_selector<Derived1, Derived2, Upper, Dynamic, ClearO
 {
   typedef typename Derived1::Index Index;
   typedef typename Derived1::Scalar Scalar;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -506,7 +493,7 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, Lower, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -524,7 +511,7 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, StrictlyUpper, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -542,7 +529,7 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, StrictlyLower, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -560,7 +547,7 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, UnitUpper, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -580,7 +567,7 @@ template<typename Derived1, typename Derived2, bool ClearOpposite>
 struct triangular_assignment_selector<Derived1, Derived2, UnitLower, Dynamic, ClearOpposite>
 {
   typedef typename Derived1::Index Index;
-  inline static void run(Derived1 &dst, const Derived2 &src)
+  static inline void run(Derived1 &dst, const Derived2 &src)
   {
     for(Index j = 0; j < dst.cols(); ++j)
     {
@@ -835,4 +822,6 @@ bool MatrixBase<Derived>::isLowerTriangular(RealScalar prec) const
   return true;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRIANGULARMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/VectorBlock.h b/extern/Eigen3/Eigen/src/Core/VectorBlock.h
index 858e4c7865a..6f4effca055 100644
--- a/extern/Eigen3/Eigen/src/Core/VectorBlock.h
+++ b/extern/Eigen3/Eigen/src/Core/VectorBlock.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_VECTORBLOCK_H
 #define EIGEN_VECTORBLOCK_H
 
+namespace Eigen { 
+
 /** \class VectorBlock
   * \ingroup Core_Module
   *
@@ -292,5 +279,6 @@ DenseBase<Derived>::tail() const
   return typename ConstFixedSegmentReturnType<Size>::Type(derived(), size() - Size);
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_VECTORBLOCK_H
diff --git a/extern/Eigen3/Eigen/src/Core/VectorwiseOp.h b/extern/Eigen3/Eigen/src/Core/VectorwiseOp.h
index 20f6881575b..862c0f33608 100644
--- a/extern/Eigen3/Eigen/src/Core/VectorwiseOp.h
+++ b/extern/Eigen3/Eigen/src/Core/VectorwiseOp.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PARTIAL_REDUX_H
 #define EIGEN_PARTIAL_REDUX_H
 
+namespace Eigen { 
+
 /** \class PartialReduxExpr
   * \ingroup Core_Module
   *
@@ -110,7 +97,7 @@ class PartialReduxExpr : internal::no_assignment_operator,
     }
 
   protected:
-    const MatrixTypeNested m_matrix;
+    MatrixTypeNested m_matrix;
     const MemberOp m_functor;
 };
 
@@ -237,7 +224,10 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     typename ExtendedType<OtherDerived>::Type
     extendedTo(const DenseBase<OtherDerived>& other) const
     {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived);
+      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)
       return typename ExtendedType<OtherDerived>::Type
                       (other.derived(),
                        Direction==Vertical   ? 1 : m_matrix.rows(),
@@ -418,10 +408,9 @@ 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)
       //eigen_assert((m_matrix.isNull()) == (other.isNull())); FIXME
-      for(Index j=0; j<subVectors(); ++j)
-        subVector(j) = other;
-      return const_cast<ExpressionType&>(m_matrix);
+      return const_cast<ExpressionType&>(m_matrix = extendedTo(other.derived()));
     }
 
     /** Adds the vector \a other to each subvector of \c *this */
@@ -429,9 +418,8 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     ExpressionType& operator+=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      for(Index j=0; j<subVectors(); ++j)
-        subVector(j) += other.derived();
-      return const_cast<ExpressionType&>(m_matrix);
+      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
+      return const_cast<ExpressionType&>(m_matrix += extendedTo(other.derived()));
     }
 
     /** Substracts the vector \a other to each subvector of \c *this */
@@ -439,8 +427,29 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
     ExpressionType& operator-=(const DenseBase<OtherDerived>& other)
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-      for(Index j=0; j<subVectors(); ++j)
-        subVector(j) -= other.derived();
+      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());
       return const_cast<ExpressionType&>(m_matrix);
     }
 
@@ -451,7 +460,8 @@ 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_VECTOR_ONLY(OtherDerived)
+      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, OtherDerived)
       return m_matrix + extendedTo(other.derived());
     }
 
@@ -462,10 +472,39 @@ 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_VECTOR_ONLY(OtherDerived)
+      EIGEN_STATIC_ASSERT_SAME_XPR_KIND(ExpressionType, 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
@@ -509,7 +548,7 @@ template<typename ExpressionType, int Direction> class VectorwiseOp
   * Example: \include MatrixBase_colwise.cpp
   * Output: \verbinclude MatrixBase_colwise.out
   *
-  * \sa rowwise(), class VectorwiseOp
+  * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
   */
 template<typename Derived>
 inline const typename DenseBase<Derived>::ConstColwiseReturnType
@@ -520,7 +559,7 @@ DenseBase<Derived>::colwise() const
 
 /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
   *
-  * \sa rowwise(), class VectorwiseOp
+  * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::ColwiseReturnType
@@ -534,7 +573,7 @@ DenseBase<Derived>::colwise()
   * Example: \include MatrixBase_rowwise.cpp
   * Output: \verbinclude MatrixBase_rowwise.out
   *
-  * \sa colwise(), class VectorwiseOp
+  * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
   */
 template<typename Derived>
 inline const typename DenseBase<Derived>::ConstRowwiseReturnType
@@ -545,7 +584,7 @@ DenseBase<Derived>::rowwise() const
 
 /** \returns a writable VectorwiseOp wrapper of *this providing additional partial reduction operations
   *
-  * \sa colwise(), class VectorwiseOp
+  * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
   */
 template<typename Derived>
 inline typename DenseBase<Derived>::RowwiseReturnType
@@ -554,4 +593,6 @@ DenseBase<Derived>::rowwise()
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_PARTIAL_REDUX_H
diff --git a/extern/Eigen3/Eigen/src/Core/Visitor.h b/extern/Eigen3/Eigen/src/Core/Visitor.h
index 378ebcba174..916bfd096a9 100644
--- a/extern/Eigen3/Eigen/src/Core/Visitor.h
+++ b/extern/Eigen3/Eigen/src/Core/Visitor.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_VISITOR_H
 #define EIGEN_VISITOR_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename Visitor, typename Derived, int UnrollCount>
@@ -35,7 +22,7 @@ struct visitor_impl
     row = (UnrollCount-1) % Derived::RowsAtCompileTime
   };
 
-  inline static void run(const Derived &mat, Visitor& visitor)
+  static inline void run(const Derived &mat, Visitor& visitor)
   {
     visitor_impl<Visitor, Derived, UnrollCount-1>::run(mat, visitor);
     visitor(mat.coeff(row, col), row, col);
@@ -45,7 +32,7 @@ struct visitor_impl
 template<typename Visitor, typename Derived>
 struct visitor_impl<Visitor, Derived, 1>
 {
-  inline static void run(const Derived &mat, Visitor& visitor)
+  static inline void run(const Derived &mat, Visitor& visitor)
   {
     return visitor.init(mat.coeff(0, 0), 0, 0);
   }
@@ -55,7 +42,7 @@ template<typename Visitor, typename Derived>
 struct visitor_impl<Visitor, Derived, Dynamic>
 {
   typedef typename Derived::Index Index;
-  inline static void run(const Derived& mat, Visitor& visitor)
+  static inline void run(const Derived& mat, Visitor& visitor)
   {
     visitor.init(mat.coeff(0,0), 0, 0);
     for(Index i = 1; i < mat.rows(); ++i)
@@ -245,4 +232,6 @@ DenseBase<Derived>::maxCoeff(IndexType* index) const
   return maxVisitor.res;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_VISITOR_H
diff --git a/extern/Eigen3/Eigen/src/Core/arch/AltiVec/Complex.h b/extern/Eigen3/Eigen/src/Core/arch/AltiVec/Complex.h
index f8adf1b6385..68d9a2bff8d 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/AltiVec/Complex.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/AltiVec/Complex.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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 };
@@ -168,7 +155,7 @@ template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet2cf>(const P
 template<int Offset>
 struct palign_impl<Offset,Packet2cf>
 {
-  EIGEN_STRONG_INLINE static void run(Packet2cf& first, const Packet2cf& second)
+  static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second)
   {
     if (Offset==1)
     {
@@ -225,4 +212,6 @@ template<> EIGEN_STRONG_INLINE Packet2cf pcplxflip<Packet2cf>(const Packet2cf& x
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_COMPLEX_ALTIVEC_H
diff --git a/extern/Eigen3/Eigen/src/Core/arch/AltiVec/PacketMath.h b/extern/Eigen3/Eigen/src/Core/arch/AltiVec/PacketMath.h
index dc34ebbd660..75de1931198 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/AltiVec/PacketMath.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/AltiVec/PacketMath.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008 Konstantinos Margaritis <markos@codex.gr>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PACKET_MATH_ALTIVEC_H
 #define EIGEN_PACKET_MATH_ALTIVEC_H
 
+namespace Eigen {
+
 namespace internal {
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
@@ -487,7 +474,7 @@ template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
 template<int Offset>
 struct palign_impl<Offset,Packet4f>
 {
-  EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second)
+  static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
   {
     if (Offset!=0)
       first = vec_sld(first, second, Offset*4);
@@ -497,7 +484,7 @@ struct palign_impl<Offset,Packet4f>
 template<int Offset>
 struct palign_impl<Offset,Packet4i>
 {
-  EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second)
+  static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
   {
     if (Offset!=0)
       first = vec_sld(first, second, Offset*4);
@@ -506,4 +493,6 @@ struct palign_impl<Offset,Packet4i>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_PACKET_MATH_ALTIVEC_H
diff --git a/extern/Eigen3/Eigen/src/Core/arch/Default/Settings.h b/extern/Eigen3/Eigen/src/Core/arch/Default/Settings.h
index 957adc8fe42..097373c84dc 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/Default/Settings.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/Default/Settings.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 
 /* All the parameters defined in this file can be specialized in the
diff --git a/extern/Eigen3/Eigen/src/Core/arch/NEON/Complex.h b/extern/Eigen3/Eigen/src/Core/arch/NEON/Complex.h
index 212887184c2..795b4be7303 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/NEON/Complex.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/NEON/Complex.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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);
@@ -267,4 +254,6 @@ template<> EIGEN_STRONG_INLINE Packet2cf pdiv<Packet2cf>(const Packet2cf& a, con
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_COMPLEX_NEON_H
diff --git a/extern/Eigen3/Eigen/src/Core/arch/NEON/PacketMath.h b/extern/Eigen3/Eigen/src/Core/arch/NEON/PacketMath.h
index 6c7cd159097..a20250f7c65 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/NEON/PacketMath.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/NEON/PacketMath.h
@@ -5,28 +5,15 @@
 // Copyright (C) 2010 Konstantinos Margaritis <markos@codex.gr>
 // Heavily based on Gael's SSE version.
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PACKET_MATH_NEON_H
 #define EIGEN_PACKET_MATH_NEON_H
 
+namespace Eigen {
+
 namespace internal {
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
@@ -158,7 +145,8 @@ 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 Packet4i pmadd(const Packet4i& a, const Packet4i& b, const Packet4i& c) { return padd(pmul(a,b), c); }
+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 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); }
@@ -431,4 +419,6 @@ PALIGN_NEON(3,Packet4i,vextq_s32)
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_PACKET_MATH_NEON_H
diff --git a/extern/Eigen3/Eigen/src/Core/arch/SSE/Complex.h b/extern/Eigen3/Eigen/src/Core/arch/SSE/Complex.h
index c352bb3e6cf..12df987754c 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/SSE/Complex.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/SSE/Complex.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COMPLEX_SSE_H
 #define EIGEN_COMPLEX_SSE_H
 
+namespace Eigen {
+
 namespace internal {
 
 //---------- float ----------
@@ -102,7 +89,7 @@ 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), (const __m64*)&from);
+  res.v = _mm_loadl_pi(_mm_set1_ps(0.0f), reinterpret_cast<const __m64*>(&from));
   #else
   res.v = _mm_loadl_pi(res.v, (const __m64*)&from);
   #endif
@@ -151,7 +138,7 @@ template<> EIGEN_STRONG_INLINE std::complex<float> predux_mul<Packet2cf>(const P
 template<int Offset>
 struct palign_impl<Offset,Packet2cf>
 {
-  EIGEN_STRONG_INLINE static void run(Packet2cf& first, const Packet2cf& second)
+  static EIGEN_STRONG_INLINE void run(Packet2cf& first, const Packet2cf& second)
   {
     if (Offset==1)
     {
@@ -350,7 +337,7 @@ template<> EIGEN_STRONG_INLINE std::complex<double> predux_mul<Packet1cd>(const
 template<int Offset>
 struct palign_impl<Offset,Packet1cd>
 {
-  EIGEN_STRONG_INLINE static void run(Packet1cd& /*first*/, const Packet1cd& /*second*/)
+  static EIGEN_STRONG_INLINE 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...
@@ -444,4 +431,6 @@ EIGEN_STRONG_INLINE Packet1cd pcplxflip/*<Packet1cd>*/(const Packet1cd& x)
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_COMPLEX_SSE_H
diff --git a/extern/Eigen3/Eigen/src/Core/arch/SSE/MathFunctions.h b/extern/Eigen3/Eigen/src/Core/arch/SSE/MathFunctions.h
index 9d56d82180b..3f41a4e2600 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/SSE/MathFunctions.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/SSE/MathFunctions.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2007 Julien Pommier
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 /* The sin, cos, exp, and log functions of this file come from
  * Julien Pommier's sse math library: http://gruntthepeon.free.fr/ssemath/
@@ -30,6 +15,8 @@
 #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
@@ -121,7 +108,7 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
   _EIGEN_DECLARE_CONST_Packet4i(0x7f, 0x7f);
 
 
-  _EIGEN_DECLARE_CONST_Packet4f(exp_hi, 88.3762626647949f);
+  _EIGEN_DECLARE_CONST_Packet4f(exp_hi,  88.3762626647950f);
   _EIGEN_DECLARE_CONST_Packet4f(exp_lo, -88.3762626647949f);
 
   _EIGEN_DECLARE_CONST_Packet4f(cephes_LOG2EF, 1.44269504088896341f);
@@ -168,7 +155,7 @@ Packet4f pexp<Packet4f>(const Packet4f& _x)
   y = pmadd(y, z, x);
   y = padd(y, p4f_1);
 
-  /* build 2^n */
+  // build 2^n
   emm0 = _mm_cvttps_epi32(fx);
   emm0 = _mm_add_epi32(emm0, p4i_0x7f);
   emm0 = _mm_slli_epi32(emm0, 23);
@@ -392,4 +379,6 @@ Packet4f psqrt<Packet4f>(const Packet4f& _x)
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_MATH_FUNCTIONS_SSE_H
diff --git a/extern/Eigen3/Eigen/src/Core/arch/SSE/PacketMath.h b/extern/Eigen3/Eigen/src/Core/arch/SSE/PacketMath.h
index 908e27368e8..10d9182190f 100644
--- a/extern/Eigen3/Eigen/src/Core/arch/SSE/PacketMath.h
+++ b/extern/Eigen3/Eigen/src/Core/arch/SSE/PacketMath.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PACKET_MATH_SSE_H
 #define EIGEN_PACKET_MATH_SSE_H
 
+namespace Eigen {
+
 namespace internal {
 
 #ifndef EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD
@@ -110,9 +97,18 @@ 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)); }
@@ -282,7 +278,7 @@ 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((const double*)from)), 0, 0, 1, 1);
+  return vec4f_swizzle1(_mm_castpd_ps(_mm_load_sd(reinterpret_cast<const double*>(from))), 0, 0, 1, 1);
 }
 template<> EIGEN_STRONG_INLINE Packet2d ploaddup<Packet2d>(const double*  from)
 { return pset1<Packet2d>(from[0]); }
@@ -302,8 +298,8 @@ 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((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)); }
+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)); }
 
 // 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)
@@ -541,7 +537,7 @@ template<> EIGEN_STRONG_INLINE int predux_max<Packet4i>(const Packet4i& a)
 template<int Offset>
 struct palign_impl<Offset,Packet4f>
 {
-  EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second)
+  static EIGEN_STRONG_INLINE 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));
@@ -551,7 +547,7 @@ struct palign_impl<Offset,Packet4f>
 template<int Offset>
 struct palign_impl<Offset,Packet4i>
 {
-  EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second)
+  static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
   {
     if (Offset!=0)
       first = _mm_alignr_epi8(second,first, Offset*4);
@@ -561,7 +557,7 @@ struct palign_impl<Offset,Packet4i>
 template<int Offset>
 struct palign_impl<Offset,Packet2d>
 {
-  EIGEN_STRONG_INLINE static void run(Packet2d& first, const Packet2d& second)
+  static EIGEN_STRONG_INLINE 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));
@@ -572,7 +568,7 @@ struct palign_impl<Offset,Packet2d>
 template<int Offset>
 struct palign_impl<Offset,Packet4f>
 {
-  EIGEN_STRONG_INLINE static void run(Packet4f& first, const Packet4f& second)
+  static EIGEN_STRONG_INLINE void run(Packet4f& first, const Packet4f& second)
   {
     if (Offset==1)
     {
@@ -595,7 +591,7 @@ struct palign_impl<Offset,Packet4f>
 template<int Offset>
 struct palign_impl<Offset,Packet4i>
 {
-  EIGEN_STRONG_INLINE static void run(Packet4i& first, const Packet4i& second)
+  static EIGEN_STRONG_INLINE void run(Packet4i& first, const Packet4i& second)
   {
     if (Offset==1)
     {
@@ -618,7 +614,7 @@ struct palign_impl<Offset,Packet4i>
 template<int Offset>
 struct palign_impl<Offset,Packet2d>
 {
-  EIGEN_STRONG_INLINE static void run(Packet2d& first, const Packet2d& second)
+  static EIGEN_STRONG_INLINE void run(Packet2d& first, const Packet2d& second)
   {
     if (Offset==1)
     {
@@ -631,4 +627,6 @@ struct palign_impl<Offset,Packet2d>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_PACKET_MATH_SSE_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/CoeffBasedProduct.h b/extern/Eigen3/Eigen/src/Core/products/CoeffBasedProduct.h
index dc20f7e1e29..403d25fa9eb 100644
--- a/extern/Eigen3/Eigen/src/Core/products/CoeffBasedProduct.h
+++ b/extern/Eigen3/Eigen/src/Core/products/CoeffBasedProduct.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COEFFBASED_PRODUCT_H
 #define EIGEN_COEFFBASED_PRODUCT_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /*********************************************************************************
@@ -224,8 +211,8 @@ class CoeffBasedProduct
     { return reinterpret_cast<const LazyCoeffBasedProductType&>(*this).diagonal(index); }
 
   protected:
-    const LhsNested m_lhs;
-    const RhsNested m_rhs;
+    typename internal::add_const_on_value_type<LhsNested>::type m_lhs;
+    typename internal::add_const_on_value_type<RhsNested>::type m_rhs;
 
     mutable PlainObject m_result;
 };
@@ -252,7 +239,7 @@ template<int UnrollingIndex, typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<DefaultTraversal, UnrollingIndex, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  static EIGEN_STRONG_INLINE 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);
@@ -263,7 +250,7 @@ template<typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<DefaultTraversal, 0, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  static EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
   {
     res = lhs.coeff(row, 0) * rhs.coeff(0, col);
   }
@@ -273,7 +260,7 @@ template<typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<DefaultTraversal, Dynamic, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar& res)
+  static EIGEN_STRONG_INLINE 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);
@@ -291,7 +278,7 @@ struct product_coeff_vectorized_unroller
 {
   typedef typename Lhs::Index Index;
   enum { PacketSize = packet_traits<typename Lhs::Scalar>::size };
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
+  static EIGEN_STRONG_INLINE 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) ));
@@ -302,7 +289,7 @@ template<typename Lhs, typename Rhs, typename Packet>
 struct product_coeff_vectorized_unroller<0, Lhs, Rhs, Packet>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::PacketScalar &pres)
+  static EIGEN_STRONG_INLINE 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));
   }
@@ -314,7 +301,7 @@ 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 };
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, RetScalar &res)
+  static EIGEN_STRONG_INLINE 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);
@@ -327,7 +314,7 @@ template<typename Lhs, typename Rhs, int LhsRows = Lhs::RowsAtCompileTime, int R
 struct product_coeff_vectorized_dyn_selector
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  static EIGEN_STRONG_INLINE 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();
   }
@@ -339,7 +326,7 @@ template<typename Lhs, typename Rhs, int RhsCols>
 struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,RhsCols>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.transpose().cwiseProduct(rhs.col(col)).sum();
   }
@@ -349,7 +336,7 @@ template<typename Lhs, typename Rhs, int LhsRows>
 struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,LhsRows,1>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  static EIGEN_STRONG_INLINE void run(Index row, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.row(row).transpose().cwiseProduct(rhs).sum();
   }
@@ -359,7 +346,7 @@ template<typename Lhs, typename Rhs>
 struct product_coeff_vectorized_dyn_selector<Lhs,Rhs,1,1>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  static EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
   {
     res = lhs.transpose().cwiseProduct(rhs).sum();
   }
@@ -369,7 +356,7 @@ template<typename Lhs, typename Rhs, typename RetScalar>
 struct product_coeff_impl<InnerVectorizedTraversal, Dynamic, Lhs, Rhs, RetScalar>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, typename Lhs::Scalar &res)
+  static EIGEN_STRONG_INLINE 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);
   }
@@ -383,7 +370,7 @@ 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;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  static EIGEN_STRONG_INLINE 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);
@@ -394,7 +381,7 @@ 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;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  static EIGEN_STRONG_INLINE 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);
@@ -405,7 +392,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<RowMajor, 0, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  static EIGEN_STRONG_INLINE 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));
   }
@@ -415,7 +402,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<ColMajor, 0, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet &res)
+  static EIGEN_STRONG_INLINE 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)));
   }
@@ -425,7 +412,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<RowMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
+  static EIGEN_STRONG_INLINE 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));
@@ -438,7 +425,7 @@ template<typename Lhs, typename Rhs, typename Packet, int LoadMode>
 struct product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
 {
   typedef typename Lhs::Index Index;
-  EIGEN_STRONG_INLINE static void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, Packet& res)
+  static EIGEN_STRONG_INLINE 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)));
@@ -449,4 +436,6 @@ struct product_packet_impl<ColMajor, Dynamic, Lhs, Rhs, Packet, LoadMode>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_COEFFBASED_PRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/extern/Eigen3/Eigen/src/Core/products/GeneralBlockPanelKernel.h
index cd1c37c780e..5eb03c98ccf 100644
--- a/extern/Eigen3/Eigen/src/Core/products/GeneralBlockPanelKernel.h
+++ b/extern/Eigen3/Eigen/src/Core/products/GeneralBlockPanelKernel.h
@@ -3,34 +3,23 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_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;
 
-inline std::ptrdiff_t manage_caching_sizes_second_if_negative(std::ptrdiff_t a, std::ptrdiff_t b)
+
+/** \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;
 }
@@ -38,9 +27,14 @@ inline std::ptrdiff_t manage_caching_sizes_second_if_negative(std::ptrdiff_t 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_second_if_negative(queryL1CacheSize(),8 * 1024);
-  static std::ptrdiff_t m_l2CacheSize = manage_caching_sizes_second_if_negative(queryTopLevelCacheSize(),1*1024*1024);
-
+  static std::ptrdiff_t m_l1CacheSize = 0;
+  static std::ptrdiff_t m_l2CacheSize = 0;
+  if(m_l2CacheSize==0)
+  {
+    m_l1CacheSize = manage_caching_sizes_helper(queryL1CacheSize(),8 * 1024);
+    m_l2CacheSize = manage_caching_sizes_helper(queryTopLevelCacheSize(),1*1024*1024);
+  }
+  
   if(action==SetAction)
   {
     // set the cpu cache size and cache all block sizes from a global cache size in byte
@@ -533,7 +527,7 @@ struct gebp_kernel
     ResPacketSize = Traits::ResPacketSize
   };
 
-  EIGEN_FLATTEN_ATTRIB
+  EIGEN_DONT_INLINE 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)
   {
@@ -595,64 +589,64 @@ struct gebp_kernel
           if(nr==2)
           {
             LhsPacket A0, A1;
-            RhsPacket B0;
+            RhsPacket B_0;
             RhsPacket T0;
             
 EIGEN_ASM_COMMENT("mybegin2");
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            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.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.loadLhs(&blA[2*LhsProgress], A0);
             traits.loadLhs(&blA[3*LhsProgress], A1);
-            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.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.loadLhs(&blA[4*LhsProgress], A0);
             traits.loadLhs(&blA[5*LhsProgress], A1);
-            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.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.loadLhs(&blA[6*LhsProgress], A0);
             traits.loadLhs(&blA[7*LhsProgress], A1);
-            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);
+            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);
 EIGEN_ASM_COMMENT("myend");
           }
           else
           {
 EIGEN_ASM_COMMENT("mybegin4");
             LhsPacket A0, A1;
-            RhsPacket B0, B1, B2, B3;
+            RhsPacket B_0, B1, B2, B3;
             RhsPacket T0;
             
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.loadRhs(&blB[0*RhsProgress], B_0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
 
-            traits.madd(A0,B0,C0,T0);
+            traits.madd(A0,B_0,C0,T0);
             traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.madd(A1,B0,C4,B0);
+            traits.madd(A1,B_0,C4,B_0);
             traits.loadRhs(&blB[3*RhsProgress], B3);
-            traits.loadRhs(&blB[4*RhsProgress], B0);
+            traits.loadRhs(&blB[4*RhsProgress], B_0);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.loadRhs(&blB[5*RhsProgress], B1);
@@ -664,9 +658,9 @@ 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,B0,C0,T0);
-            traits.madd(A1,B0,C4,B0);
-            traits.loadRhs(&blB[8*RhsProgress], B0);
+            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,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.loadRhs(&blB[9*RhsProgress], B1);
@@ -679,9 +673,9 @@ EIGEN_ASM_COMMENT("mybegin4");
             traits.loadLhs(&blA[5*LhsProgress], A1);
             traits.loadRhs(&blB[11*RhsProgress], B3);
 
-            traits.madd(A0,B0,C0,T0);
-            traits.madd(A1,B0,C4,B0);
-            traits.loadRhs(&blB[12*RhsProgress], B0);
+            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,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.loadRhs(&blB[13*RhsProgress], B1);
@@ -693,8 +687,8 @@ 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,B0,C0,T0);
-            traits.madd(A1,B0,C4,B0);
+            traits.madd(A0,B_0,C0,T0);
+            traits.madd(A1,B_0,C4,B_0);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
             traits.madd(A0,B2,C2,T0);
@@ -712,32 +706,32 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsPacket A0, A1;
-            RhsPacket B0;
+            RhsPacket B_0;
             RhsPacket T0;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            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.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);
           }
           else
           {
             LhsPacket A0, A1;
-            RhsPacket B0, B1, B2, B3;
+            RhsPacket B_0, B1, B2, B3;
             RhsPacket T0;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
             traits.loadLhs(&blA[1*LhsProgress], A1);
-            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.loadRhs(&blB[0*RhsProgress], B_0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
 
-            traits.madd(A0,B0,C0,T0);
+            traits.madd(A0,B_0,C0,T0);
             traits.loadRhs(&blB[2*RhsProgress], B2);
-            traits.madd(A1,B0,C4,B0);
+            traits.madd(A1,B_0,C4,B_0);
             traits.loadRhs(&blB[3*RhsProgress], B3);
             traits.madd(A0,B1,C1,T0);
             traits.madd(A1,B1,C5,B1);
@@ -824,42 +818,42 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsPacket A0;
-            RhsPacket B0, B1;
+            RhsPacket B_0, B1;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.loadRhs(&blB[0*RhsProgress], B_0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
-            traits.madd(A0,B0,C0,B0);
-            traits.loadRhs(&blB[2*RhsProgress], B0);
+            traits.madd(A0,B_0,C0,B_0);
+            traits.loadRhs(&blB[2*RhsProgress], B_0);
             traits.madd(A0,B1,C1,B1);
             traits.loadLhs(&blA[1*LhsProgress], A0);
             traits.loadRhs(&blB[3*RhsProgress], B1);
-            traits.madd(A0,B0,C0,B0);
-            traits.loadRhs(&blB[4*RhsProgress], B0);
+            traits.madd(A0,B_0,C0,B_0);
+            traits.loadRhs(&blB[4*RhsProgress], B_0);
             traits.madd(A0,B1,C1,B1);
             traits.loadLhs(&blA[2*LhsProgress], A0);
             traits.loadRhs(&blB[5*RhsProgress], B1);
-            traits.madd(A0,B0,C0,B0);
-            traits.loadRhs(&blB[6*RhsProgress], B0);
+            traits.madd(A0,B_0,C0,B_0);
+            traits.loadRhs(&blB[6*RhsProgress], B_0);
             traits.madd(A0,B1,C1,B1);
             traits.loadLhs(&blA[3*LhsProgress], A0);
             traits.loadRhs(&blB[7*RhsProgress], B1);
-            traits.madd(A0,B0,C0,B0);
+            traits.madd(A0,B_0,C0,B_0);
             traits.madd(A0,B1,C1,B1);
           }
           else
           {
             LhsPacket A0;
-            RhsPacket B0, B1, B2, B3;
+            RhsPacket B_0, B1, B2, B3;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.loadRhs(&blB[0*RhsProgress], B_0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
 
-            traits.madd(A0,B0,C0,B0);
+            traits.madd(A0,B_0,C0,B_0);
             traits.loadRhs(&blB[2*RhsProgress], B2);
             traits.loadRhs(&blB[3*RhsProgress], B3);
-            traits.loadRhs(&blB[4*RhsProgress], B0);
+            traits.loadRhs(&blB[4*RhsProgress], B_0);
             traits.madd(A0,B1,C1,B1);
             traits.loadRhs(&blB[5*RhsProgress], B1);
             traits.madd(A0,B2,C2,B2);
@@ -867,8 +861,8 @@ 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,B0,C0,B0);
-            traits.loadRhs(&blB[8*RhsProgress], B0);
+            traits.madd(A0,B_0,C0,B_0);
+            traits.loadRhs(&blB[8*RhsProgress], B_0);
             traits.madd(A0,B1,C1,B1);
             traits.loadRhs(&blB[9*RhsProgress], B1);
             traits.madd(A0,B2,C2,B2);
@@ -877,8 +871,8 @@ EIGEN_ASM_COMMENT("mybegin4");
             traits.loadLhs(&blA[2*LhsProgress], A0);
             traits.loadRhs(&blB[11*RhsProgress], B3);
 
-            traits.madd(A0,B0,C0,B0);
-            traits.loadRhs(&blB[12*RhsProgress], B0);
+            traits.madd(A0,B_0,C0,B_0);
+            traits.loadRhs(&blB[12*RhsProgress], B_0);
             traits.madd(A0,B1,C1,B1);
             traits.loadRhs(&blB[13*RhsProgress], B1);
             traits.madd(A0,B2,C2,B2);
@@ -887,7 +881,7 @@ EIGEN_ASM_COMMENT("mybegin4");
 
             traits.loadLhs(&blA[3*LhsProgress], A0);
             traits.loadRhs(&blB[15*RhsProgress], B3);
-            traits.madd(A0,B0,C0,B0);
+            traits.madd(A0,B_0,C0,B_0);
             traits.madd(A0,B1,C1,B1);
             traits.madd(A0,B2,C2,B2);
             traits.madd(A0,B3,C3,B3);
@@ -902,26 +896,26 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsPacket A0;
-            RhsPacket B0, B1;
+            RhsPacket B_0, B1;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.loadRhs(&blB[0*RhsProgress], B_0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
-            traits.madd(A0,B0,C0,B0);
+            traits.madd(A0,B_0,C0,B_0);
             traits.madd(A0,B1,C1,B1);
           }
           else
           {
             LhsPacket A0;
-            RhsPacket B0, B1, B2, B3;
+            RhsPacket B_0, B1, B2, B3;
 
             traits.loadLhs(&blA[0*LhsProgress], A0);
-            traits.loadRhs(&blB[0*RhsProgress], B0);
+            traits.loadRhs(&blB[0*RhsProgress], B_0);
             traits.loadRhs(&blB[1*RhsProgress], B1);
             traits.loadRhs(&blB[2*RhsProgress], B2);
             traits.loadRhs(&blB[3*RhsProgress], B3);
 
-            traits.madd(A0,B0,C0,B0);
+            traits.madd(A0,B_0,C0,B_0);
             traits.madd(A0,B1,C1,B1);
             traits.madd(A0,B2,C2,B2);
             traits.madd(A0,B3,C3,B3);
@@ -968,26 +962,26 @@ EIGEN_ASM_COMMENT("mybegin4");
           if(nr==2)
           {
             LhsScalar A0;
-            RhsScalar B0, B1;
+            RhsScalar B_0, B1;
 
             A0 = blA[k];
-            B0 = blB[0];
+            B_0 = blB[0];
             B1 = blB[1];
-            MADD(cj,A0,B0,C0,B0);
+            MADD(cj,A0,B_0,C0,B_0);
             MADD(cj,A0,B1,C1,B1);
           }
           else
           {
             LhsScalar A0;
-            RhsScalar B0, B1, B2, B3;
+            RhsScalar B_0, B1, B2, B3;
 
             A0 = blA[k];
-            B0 = blB[0];
+            B_0 = blB[0];
             B1 = blB[1];
             B2 = blB[2];
             B3 = blB[3];
 
-            MADD(cj,A0,B0,C0,B0);
+            MADD(cj,A0,B_0,C0,B_0);
             MADD(cj,A0,B1,C1,B1);
             MADD(cj,A0,B2,C2,B2);
             MADD(cj,A0,B3,C3,B3);
@@ -1024,14 +1018,14 @@ EIGEN_ASM_COMMENT("mybegin4");
         for(Index k=0; k<depth; k++)
         {
           LhsPacket A0, A1;
-          RhsPacket B0;
+          RhsPacket B_0;
           RhsPacket T0;
 
           traits.loadLhs(&blA[0*LhsProgress], A0);
           traits.loadLhs(&blA[1*LhsProgress], A1);
-          traits.loadRhs(&blB[0*RhsProgress], B0);
-          traits.madd(A0,B0,C0,T0);
-          traits.madd(A1,B0,C4,B0);
+          traits.loadRhs(&blB[0*RhsProgress], B_0);
+          traits.madd(A0,B_0,C0,T0);
+          traits.madd(A1,B_0,C4,B_0);
 
           blB += RhsProgress;
           blA += 2*LhsProgress;
@@ -1063,10 +1057,10 @@ EIGEN_ASM_COMMENT("mybegin4");
         for(Index k=0; k<depth; k++)
         {
           LhsPacket A0;
-          RhsPacket B0;
+          RhsPacket B_0;
           traits.loadLhs(blA, A0);
-          traits.loadRhs(blB, B0);
-          traits.madd(A0, B0, C0, B0);
+          traits.loadRhs(blB, B_0);
+          traits.madd(A0, B_0, C0, B_0);
           blB += RhsProgress;
           blA += LhsProgress;
         }
@@ -1088,8 +1082,8 @@ EIGEN_ASM_COMMENT("mybegin4");
         for(Index k=0; k<depth; k++)
         {
           LhsScalar A0 = blA[k];
-          RhsScalar B0 = blB[k];
-          MADD(cj, A0, B0, C0, B0);
+          RhsScalar B_0 = blB[k];
+          MADD(cj, A0, B_0, C0, B_0);
         }
         res[(j2+0)*resStride + i] += alpha*C0;
       }
@@ -1100,7 +1094,7 @@ EIGEN_ASM_COMMENT("mybegin4");
 #undef CJMADD
 
 // pack a block of the lhs
-// The travesal is as follow (mr==4):
+// The traversal is as follow (mr==4):
 //   0  4  8 12 ...
 //   1  5  9 13 ...
 //   2  6 10 14 ...
@@ -1116,11 +1110,15 @@ EIGEN_ASM_COMMENT("mybegin4");
 template<typename Scalar, typename Index, int Pack1, int Pack2, int StorageOrder, bool Conjugate, bool PanelMode>
 struct gemm_pack_lhs
 {
-  void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows,
+  EIGEN_DONT_INLINE void operator()(Scalar* blockA, const Scalar* EIGEN_RESTRICT _lhs, Index lhsStride, Index depth, Index rows,
                   Index stride=0, Index offset=0)
   {
-//     enum { PacketSize = packet_traits<Scalar>::size };
+    typedef typename packet_traits<Scalar>::type Packet;
+    enum { PacketSize = packet_traits<Scalar>::size };
+
+    EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK LHS");
     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;
@@ -1128,9 +1126,44 @@ struct gemm_pack_lhs
     for(Index i=0; i<peeled_mc; i+=Pack1)
     {
       if(PanelMode) count += Pack1 * offset;
-      for(Index k=0; k<depth; k++)
-        for(Index w=0; w<Pack1; w++)
-          blockA[count++] = cj(lhs(i+w, k));
+
+      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));
+        }
+      }
       if(PanelMode) count += Pack1 * (stride-offset-depth);
     }
     if(rows-peeled_mc>=Pack2)
@@ -1164,9 +1197,10 @@ struct gemm_pack_rhs<Scalar, Index, nr, ColMajor, Conjugate, PanelMode>
 {
   typedef typename packet_traits<Scalar>::type Packet;
   enum { PacketSize = packet_traits<Scalar>::size };
-  void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
+  EIGEN_DONT_INLINE 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;
@@ -1211,9 +1245,10 @@ 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 };
-  void operator()(Scalar* blockB, const Scalar* rhs, Index rhsStride, Index depth, Index cols,
+  EIGEN_DONT_INLINE 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;
@@ -1279,4 +1314,6 @@ 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
diff --git a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrix.h b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrix.h
index ae94a27953b..73a465ec5ee 100644
--- a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrix.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERAL_MATRIX_MATRIX_H
 #define EIGEN_GENERAL_MATRIX_MATRIX_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename _LhsScalar, typename _RhsScalar> class level3_blocking;
@@ -77,7 +64,7 @@ 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 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 nc = blocking.nc(); // cache block size along the N direction
 
@@ -247,7 +234,7 @@ struct gemm_functor
     BlockingType& m_blocking;
 };
 
-template<int StorageOrder, typename LhsScalar, typename RhsScalar, int MaxRows, int MaxCols, int MaxDepth,
+template<int StorageOrder, typename LhsScalar, typename RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor=1,
 bool FiniteAtCompileTime = MaxRows!=Dynamic && MaxCols!=Dynamic && MaxDepth != Dynamic> class gemm_blocking_space;
 
 template<typename _LhsScalar, typename _RhsScalar>
@@ -280,8 +267,8 @@ class level3_blocking
     inline RhsScalar* blockW() { return m_blockW; }
 };
 
-template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth>
-class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, true>
+template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor>
+class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, true>
   : public level3_blocking<
       typename conditional<StorageOrder==RowMajor,_RhsScalar,_LhsScalar>::type,
       typename conditional<StorageOrder==RowMajor,_LhsScalar,_RhsScalar>::type>
@@ -322,8 +309,8 @@ class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, M
     inline void allocateAll() {}
 };
 
-template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth>
-class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, false>
+template<int StorageOrder, typename _LhsScalar, typename _RhsScalar, int MaxRows, int MaxCols, int MaxDepth, int KcFactor>
+class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, MaxDepth, KcFactor, false>
   : public level3_blocking<
       typename conditional<StorageOrder==RowMajor,_RhsScalar,_LhsScalar>::type,
       typename conditional<StorageOrder==RowMajor,_LhsScalar,_RhsScalar>::type>
@@ -347,7 +334,7 @@ class gemm_blocking_space<StorageOrder,_LhsScalar,_RhsScalar,MaxRows, MaxCols, M
       this->m_nc = Transpose ? rows : cols;
       this->m_kc = depth;
 
-      computeProductBlockingSizes<LhsScalar,RhsScalar>(this->m_kc, this->m_mc, this->m_nc);
+      computeProductBlockingSizes<LhsScalar,RhsScalar,KcFactor>(this->m_kc, this->m_mc, this->m_nc);
       m_sizeA = this->m_mc * this->m_kc;
       m_sizeB = this->m_kc * this->m_nc;
       m_sizeW = this->m_kc*Traits::WorkSpaceFactor;
@@ -412,8 +399,8 @@ class GeneralProduct<Lhs, Rhs, GemmProduct>
     {
       eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
 
-      const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
-      const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
+      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);
 
       Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                                  * RhsBlasTraits::extractScalarFactor(m_rhs);
@@ -436,4 +423,6 @@ class GeneralProduct<Lhs, Rhs, GemmProduct>
     }
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_GENERAL_MATRIX_MATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
index 5043b64fe2e..432d3a9dc84 100644
--- a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
+++ b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H
 #define EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /**********************************************************************
@@ -42,14 +29,14 @@ struct tribb_kernel;
 template <typename Index,
           typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs,
           typename RhsScalar, int RhsStorageOrder, bool ConjugateRhs,
-                              int ResStorageOrder, int  UpLo>
+                              int ResStorageOrder, int  UpLo, int Version = Specialized>
 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>
-struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor,UpLo>
-{  
+                          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>
+{
   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)
@@ -63,8 +50,8 @@ 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>
-struct general_matrix_matrix_triangular_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor,UpLo>
+                          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>
 {
   typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   static EIGEN_STRONG_INLINE void run(Index size, Index depth,const LhsScalar* _lhs, Index lhsStride,
@@ -201,13 +188,13 @@ 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;
-  const ActualLhs actualLhs = LhsBlasTraits::extract(prod.lhs());
+  typename internal::add_const_on_value_type<ActualLhs>::type 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;
-  const ActualRhs actualRhs = RhsBlasTraits::extract(prod.rhs());
+  typename internal::add_const_on_value_type<ActualRhs>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
 
   typename ProductDerived::Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs().derived()) * RhsBlasTraits::extractScalarFactor(prod.rhs().derived());
 
@@ -222,4 +209,6 @@ TriangularView<MatrixType,UpLo>& TriangularView<MatrixType,UpLo>::assignProduct(
   return *this;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_GENERAL_MATRIX_MATRIX_TRIANGULAR_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h
new file mode 100644
index 00000000000..3deed068e39
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h
@@ -0,0 +1,146 @@
+/*
+ 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
diff --git a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h
new file mode 100644
index 00000000000..060af328ebe
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h
@@ -0,0 +1,118 @@
+/*
+ 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
+ *   General matrix-matrix product functionality based on ?GEMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_GENERAL_MATRIX_MATRIX_MKL_H
+#define EIGEN_GENERAL_MATRIX_MATRIX_MKL_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements general matrix-matrix multiplication using BLAS
+* gemm function via partial specialization of
+* general_matrix_matrix_product::run(..) method for float, double,
+* std::complex<float> and std::complex<double> types
+**********************************************************************/
+
+// gemm specialization
+
+#define GEMM_SPECIALIZATION(EIGTYPE, EIGPREFIX, MKLTYPE, MKLPREFIX) \
+template< \
+  typename Index, \
+  int LhsStorageOrder, bool ConjugateLhs, \
+  int RhsStorageOrder, bool ConjugateRhs> \
+struct general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor> \
+{ \
+static void run(Index rows, Index cols, Index depth, \
+  const EIGTYPE* _lhs, Index lhsStride, \
+  const EIGTYPE* _rhs, Index rhsStride, \
+  EIGTYPE* res, Index resStride, \
+  EIGTYPE alpha, \
+  level3_blocking<EIGTYPE, EIGTYPE>& /*blocking*/, \
+  GemmParallelInfo<Index>* /*info = 0*/) \
+{ \
+  using std::conj; \
+\
+  char transa, transb; \
+  MKL_INT m, n, k, lda, ldb, ldc; \
+  const EIGTYPE *a, *b; \
+  MKLTYPE alpha_, beta_; \
+  MatrixX##EIGPREFIX a_tmp, b_tmp; \
+  EIGTYPE myone(1);\
+\
+/* Set transpose options */ \
+  transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \
+  transb = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \
+\
+/* Set m, n, k */ \
+  m = (MKL_INT)rows;  \
+  n = (MKL_INT)cols;  \
+  k = (MKL_INT)depth; \
+\
+/* Set alpha_ & beta_ */ \
+  assign_scalar_eig2mkl(alpha_, alpha); \
+  assign_scalar_eig2mkl(beta_, myone); \
+\
+/* Set lda, ldb, ldc */ \
+  lda = (MKL_INT)lhsStride; \
+  ldb = (MKL_INT)rhsStride; \
+  ldc = (MKL_INT)resStride; \
+\
+/* Set a, b, c */ \
+  if ((LhsStorageOrder==ColMajor) && (ConjugateLhs)) { \
+    Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,m,k,OuterStride<>(lhsStride)); \
+    a_tmp = lhs.conjugate(); \
+    a = a_tmp.data(); \
+    lda = a_tmp.outerStride(); \
+  } else a = _lhs; \
+\
+  if ((RhsStorageOrder==ColMajor) && (ConjugateRhs)) { \
+    Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,k,n,OuterStride<>(rhsStride)); \
+    b_tmp = rhs.conjugate(); \
+    b = b_tmp.data(); \
+    ldb = b_tmp.outerStride(); \
+  } else b = _rhs; \
+\
+  MKLPREFIX##gemm(&transa, &transb, &m, &n, &k, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
+}};
+
+GEMM_SPECIALIZATION(double,   d,  double,        d)
+GEMM_SPECIALIZATION(float,    f,  float,         s)
+GEMM_SPECIALIZATION(dcomplex, cd, MKL_Complex16, z)
+GEMM_SPECIALIZATION(scomplex, cf, MKL_Complex8,  c)
+
+} // end namespase internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_GENERAL_MATRIX_MATRIX_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixVector.h b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixVector.h
index e0e2cbf8f62..ba1f73957db 100644
--- a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixVector.h
+++ b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixVector.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERAL_MATRIX_VECTOR_H
 #define EIGEN_GENERAL_MATRIX_VECTOR_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /* Optimized col-major matrix * vector product:
@@ -40,8 +27,8 @@ namespace internal {
  *  |cplx |real |cplx | invalid, the caller has to do tmp: = A * B; C += alpha*tmp
  *  |cplx |real |real | optimal case, vectorization possible via real-cplx mul
  */
-template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs>
-struct general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs>
+template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
+struct general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>
 {
 typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
 
@@ -99,7 +86,7 @@ EIGEN_DONT_INLINE static void run(
   
   // How many coeffs of the result do we have to skip to be aligned.
   // Here we assume data are at least aligned on the base scalar type.
-  Index alignedStart = first_aligned(res,size);
+  Index alignedStart = internal::first_aligned(res,size);
   Index alignedSize = ResPacketSize>1 ? alignedStart + ((size-alignedStart) & ~ResPacketAlignedMask) : 0;
   const Index peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
 
@@ -109,7 +96,7 @@ EIGEN_DONT_INLINE static void run(
                        : FirstAligned;
 
   // we cannot assume the first element is aligned because of sub-matrices
-  const Index lhsAlignmentOffset = first_aligned(lhs,size);
+  const Index lhsAlignmentOffset = internal::first_aligned(lhs,size);
 
   // find how many columns do we have to skip to be aligned with the result (if possible)
   Index skipColumns = 0;
@@ -296,8 +283,8 @@ EIGEN_DONT_INLINE static void run(
  *  - alpha is always a complex (or converted to a complex)
  *  - no vectorization
  */
-template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs>
-struct general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjugateLhs,RhsScalar,ConjugateRhs>
+template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
+struct general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>
 {
 typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
 
@@ -351,7 +338,7 @@ EIGEN_DONT_INLINE static void run(
   // How many coeffs of the result do we have to skip to be aligned.
   // Here we assume data are at least aligned on the base scalar type
   // if that's not the case then vectorization is discarded, see below.
-  Index alignedStart = first_aligned(rhs, depth);
+  Index alignedStart = internal::first_aligned(rhs, depth);
   Index alignedSize = RhsPacketSize>1 ? alignedStart + ((depth-alignedStart) & ~RhsPacketAlignedMask) : 0;
   const Index peeledSize  = peels>1 ? alignedStart + ((alignedSize-alignedStart) & ~PeelAlignedMask) : alignedStart;
 
@@ -361,7 +348,7 @@ EIGEN_DONT_INLINE static void run(
                          : FirstAligned;
 
   // we cannot assume the first element is aligned because of sub-matrices
-  const Index lhsAlignmentOffset = first_aligned(lhs,depth);
+  const Index lhsAlignmentOffset = internal::first_aligned(lhs,depth);
 
   // find how many rows do we have to skip to be aligned with rhs (if possible)
   Index skipRows = 0;
@@ -556,4 +543,6 @@ EIGEN_DONT_INLINE static void run(
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_GENERAL_MATRIX_VECTOR_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixVector_MKL.h b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixVector_MKL.h
new file mode 100644
index 00000000000..e9de6af3ed1
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/GeneralMatrixVector_MKL.h
@@ -0,0 +1,131 @@
+/*
+ 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
+ *   General matrix-vector product functionality based on ?GEMV.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
+#define EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements general matrix-vector multiplication using BLAS
+* gemv function via partial specialization of
+* general_matrix_vector_product::run(..) method for float, double,
+* std::complex<float> and std::complex<double> types
+**********************************************************************/
+
+// gemv specialization
+
+template<typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs>
+struct general_matrix_vector_product_gemv :
+  general_matrix_vector_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,ConjugateRhs,BuiltIn> {};
+
+#define EIGEN_MKL_GEMV_SPECIALIZE(Scalar) \
+template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
+struct general_matrix_vector_product<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
+static EIGEN_DONT_INLINE void run( \
+  Index rows, Index cols, \
+  const Scalar* lhs, Index lhsStride, \
+  const Scalar* rhs, Index rhsIncr, \
+  Scalar* res, Index resIncr, Scalar alpha) \
+{ \
+  if (ConjugateLhs) { \
+    general_matrix_vector_product<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs,BuiltIn>::run( \
+      rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
+  } else { \
+    general_matrix_vector_product_gemv<Index,Scalar,ColMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
+      rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
+  } \
+} \
+}; \
+template<typename Index, bool ConjugateLhs, bool ConjugateRhs> \
+struct general_matrix_vector_product<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs,Specialized> { \
+static EIGEN_DONT_INLINE void run( \
+  Index rows, Index cols, \
+  const Scalar* lhs, Index lhsStride, \
+  const Scalar* rhs, Index rhsIncr, \
+  Scalar* res, Index resIncr, Scalar alpha) \
+{ \
+    general_matrix_vector_product_gemv<Index,Scalar,RowMajor,ConjugateLhs,Scalar,ConjugateRhs>::run( \
+      rows, cols, lhs, lhsStride, rhs, rhsIncr, res, resIncr, alpha); \
+} \
+}; \
+
+EIGEN_MKL_GEMV_SPECIALIZE(double)
+EIGEN_MKL_GEMV_SPECIALIZE(float)
+EIGEN_MKL_GEMV_SPECIALIZE(dcomplex)
+EIGEN_MKL_GEMV_SPECIALIZE(scomplex)
+
+#define EIGEN_MKL_GEMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLPREFIX) \
+template<typename Index, int LhsStorageOrder, bool ConjugateLhs, bool ConjugateRhs> \
+struct general_matrix_vector_product_gemv<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,ConjugateRhs> \
+{ \
+typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> GEMVVector;\
+\
+static EIGEN_DONT_INLINE void run( \
+  Index rows, Index cols, \
+  const EIGTYPE* lhs, Index lhsStride, \
+  const EIGTYPE* rhs, Index rhsIncr, \
+  EIGTYPE* res, Index resIncr, EIGTYPE alpha) \
+{ \
+  MKL_INT m=rows, n=cols, lda=lhsStride, incx=rhsIncr, incy=resIncr; \
+  MKLTYPE alpha_, beta_; \
+  const EIGTYPE *x_ptr, myone(1); \
+  char trans=(LhsStorageOrder==ColMajor) ? 'N' : (ConjugateLhs) ? 'C' : 'T'; \
+  if (LhsStorageOrder==RowMajor) { \
+    m=cols; \
+    n=rows; \
+  }\
+  assign_scalar_eig2mkl(alpha_, alpha); \
+  assign_scalar_eig2mkl(beta_, myone); \
+  GEMVVector x_tmp; \
+  if (ConjugateRhs) { \
+    Map<const GEMVVector, 0, InnerStride<> > map_x(rhs,cols,1,InnerStride<>(incx)); \
+    x_tmp=map_x.conjugate(); \
+    x_ptr=x_tmp.data(); \
+    incx=1; \
+  } else x_ptr=rhs; \
+  MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \
+}\
+};
+
+EIGEN_MKL_GEMV_SPECIALIZATION(double,   double,        d)
+EIGEN_MKL_GEMV_SPECIALIZATION(float,    float,         s)
+EIGEN_MKL_GEMV_SPECIALIZATION(dcomplex, MKL_Complex16, z)
+EIGEN_MKL_GEMV_SPECIALIZATION(scomplex, MKL_Complex8,  c)
+
+} // end namespase internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_GENERAL_MATRIX_VECTOR_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/Parallelizer.h b/extern/Eigen3/Eigen/src/Core/products/Parallelizer.h
index ecdedc363ce..5c3e9b7ac15 100644
--- a/extern/Eigen3/Eigen/src/Core/products/Parallelizer.h
+++ b/extern/Eigen3/Eigen/src/Core/products/Parallelizer.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PARALLELIZER_H
 #define EIGEN_PARALLELIZER_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /** \internal */
@@ -55,12 +42,23 @@ inline void manage_multi_threading(Action action, int* v)
   }
 }
 
+}
+
+/** Must be call first when calling Eigen from multiple threads */
+inline void initParallel()
+{
+  int nbt;
+  internal::manage_multi_threading(GetAction, &nbt);
+  std::ptrdiff_t l1, l2;
+  internal::manage_caching_sizes(GetAction, &l1, &l2);
+}
+
 /** \returns the max number of threads reserved for Eigen
   * \sa setNbThreads */
 inline int nbThreads()
 {
   int ret;
-  manage_multi_threading(GetAction, &ret);
+  internal::manage_multi_threading(GetAction, &ret);
   return ret;
 }
 
@@ -68,9 +66,11 @@ inline int nbThreads()
   * \sa nbThreads */
 inline void setNbThreads(int v)
 {
-  manage_multi_threading(SetAction, &v);
+  internal::manage_multi_threading(SetAction, &v);
 }
 
+namespace internal {
+
 template<typename Index> struct GemmParallelInfo
 {
   GemmParallelInfo() : sync(-1), users(0), rhs_start(0), rhs_length(0) {}
@@ -85,7 +85,9 @@ template<typename Index> struct GemmParallelInfo
 template<bool Condition, typename Functor, typename Index>
 void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpose)
 {
-#ifndef EIGEN_HAS_OPENMP
+  // TODO when EIGEN_USE_BLAS is defined,
+  // we should still enable OMP for other scalar types
+#if !(defined (EIGEN_HAS_OPENMP)) || defined (EIGEN_USE_BLAS)
   // FIXME the transpose variable is only needed to properly split
   // the matrix product when multithreading is enabled. This is a temporary
   // fix to support row-major destination matrices. This whole
@@ -117,6 +119,7 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpos
   if(threads==1)
     return func(0,rows, 0,cols);
 
+  Eigen::initParallel();
   func.initParallelSession();
 
   if(transpose)
@@ -151,4 +154,6 @@ void parallelize_gemm(const Functor& func, Index rows, Index cols, bool transpos
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_PARALLELIZER_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
index ccd757cfaf8..48209636eed 100644
--- a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_H
 #define EIGEN_SELFADJOINT_MATRIX_MATRIX_H
 
+namespace Eigen { 
+
 namespace internal {
 
 // pack a selfadjoint block diagonal for use with the gebp_kernel
@@ -400,8 +387,8 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>
   {
     eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
 
-    const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
-    const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
+    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);
 
     Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                                * RhsBlasTraits::extractScalarFactor(m_rhs);
@@ -424,4 +411,6 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,RhsMode,false>
   }
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h
new file mode 100644
index 00000000000..4e5c4125c01
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h
@@ -0,0 +1,295 @@
+/*
+ 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
+ *   Self adjoint matrix * matrix product functionality based on ?SYMM/?HEMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H
+#define EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H
+
+namespace Eigen { 
+
+namespace internal {
+
+
+/* Optimized selfadjoint matrix * matrix (?SYMM/?HEMM) product */
+
+#define EIGEN_MKL_SYMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
+{\
+\
+  static EIGEN_DONT_INLINE void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha) \
+  { \
+    char side='L', uplo='L'; \
+    MKL_INT m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    MKLTYPE alpha_, beta_; \
+    MatrixX##EIGPREFIX b_tmp; \
+    EIGTYPE myone(1);\
+\
+/* Set transpose options */ \
+/* Set m, n, k */ \
+    m = (MKL_INT)rows;  \
+    n = (MKL_INT)cols;  \
+\
+/* Set alpha_ & beta_ */ \
+    assign_scalar_eig2mkl(alpha_, alpha); \
+    assign_scalar_eig2mkl(beta_, myone); \
+\
+/* Set lda, ldb, ldc */ \
+    lda = (MKL_INT)lhsStride; \
+    ldb = (MKL_INT)rhsStride; \
+    ldc = (MKL_INT)resStride; \
+\
+/* Set a, b, c */ \
+    if (LhsStorageOrder==RowMajor) uplo='U'; \
+    a = _lhs; \
+\
+    if (RhsStorageOrder==RowMajor) { \
+      Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
+      b_tmp = rhs.adjoint(); \
+      b = b_tmp.data(); \
+      ldb = b_tmp.outerStride(); \
+    } else b = _rhs; \
+\
+    MKLPREFIX##symm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
+\
+  } \
+};
+
+
+#define EIGEN_MKL_HEMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,true,ConjugateLhs,RhsStorageOrder,false,ConjugateRhs,ColMajor> \
+{\
+  static EIGEN_DONT_INLINE void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha) \
+  { \
+    char side='L', uplo='L'; \
+    MKL_INT m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    MKLTYPE alpha_, beta_; \
+    MatrixX##EIGPREFIX b_tmp; \
+    Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> a_tmp; \
+    EIGTYPE myone(1); \
+\
+/* Set transpose options */ \
+/* Set m, n, k */ \
+    m = (MKL_INT)rows; \
+    n = (MKL_INT)cols; \
+\
+/* Set alpha_ & beta_ */ \
+    assign_scalar_eig2mkl(alpha_, alpha); \
+    assign_scalar_eig2mkl(beta_, myone); \
+\
+/* Set lda, ldb, ldc */ \
+    lda = (MKL_INT)lhsStride; \
+    ldb = (MKL_INT)rhsStride; \
+    ldc = (MKL_INT)resStride; \
+\
+/* Set a, b, c */ \
+    if (((LhsStorageOrder==ColMajor) && ConjugateLhs) || ((LhsStorageOrder==RowMajor) && (!ConjugateLhs))) { \
+      Map<const Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder>, 0, OuterStride<> > lhs(_lhs,m,m,OuterStride<>(lhsStride)); \
+      a_tmp = lhs.conjugate(); \
+      a = a_tmp.data(); \
+      lda = a_tmp.outerStride(); \
+    } else a = _lhs; \
+    if (LhsStorageOrder==RowMajor) uplo='U'; \
+\
+    if (RhsStorageOrder==ColMajor && (!ConjugateRhs)) { \
+       b = _rhs; } \
+    else { \
+      if (RhsStorageOrder==ColMajor && ConjugateRhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,m,n,OuterStride<>(rhsStride)); \
+        b_tmp = rhs.conjugate(); \
+      } else \
+      if (ConjugateRhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
+        b_tmp = rhs.adjoint(); \
+      } else { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > rhs(_rhs,n,m,OuterStride<>(rhsStride)); \
+        b_tmp = rhs.transpose(); \
+      } \
+      b = b_tmp.data(); \
+      ldb = b_tmp.outerStride(); \
+    } \
+\
+    MKLPREFIX##hemm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
+\
+  } \
+};
+
+EIGEN_MKL_SYMM_L(double, double, d, d)
+EIGEN_MKL_SYMM_L(float, float, f, s)
+EIGEN_MKL_HEMM_L(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_HEMM_L(scomplex, MKL_Complex8, cf, c)
+
+
+/* Optimized matrix * selfadjoint matrix (?SYMM/?HEMM) product */
+
+#define EIGEN_MKL_SYMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
+{\
+\
+  static EIGEN_DONT_INLINE void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha) \
+  { \
+    char side='R', uplo='L'; \
+    MKL_INT m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    MKLTYPE alpha_, beta_; \
+    MatrixX##EIGPREFIX b_tmp; \
+    EIGTYPE myone(1);\
+\
+/* Set m, n, k */ \
+    m = (MKL_INT)rows;  \
+    n = (MKL_INT)cols;  \
+\
+/* Set alpha_ & beta_ */ \
+    assign_scalar_eig2mkl(alpha_, alpha); \
+    assign_scalar_eig2mkl(beta_, myone); \
+\
+/* Set lda, ldb, ldc */ \
+    lda = (MKL_INT)rhsStride; \
+    ldb = (MKL_INT)lhsStride; \
+    ldc = (MKL_INT)resStride; \
+\
+/* Set a, b, c */ \
+    if (RhsStorageOrder==RowMajor) uplo='U'; \
+    a = _rhs; \
+\
+    if (LhsStorageOrder==RowMajor) { \
+      Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(rhsStride)); \
+      b_tmp = lhs.adjoint(); \
+      b = b_tmp.data(); \
+      ldb = b_tmp.outerStride(); \
+    } else b = _lhs; \
+\
+    MKLPREFIX##symm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
+\
+  } \
+};
+
+
+#define EIGEN_MKL_HEMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template <typename Index, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_selfadjoint_matrix<EIGTYPE,Index,LhsStorageOrder,false,ConjugateLhs,RhsStorageOrder,true,ConjugateRhs,ColMajor> \
+{\
+  static EIGEN_DONT_INLINE void run( \
+    Index rows, Index cols, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha) \
+  { \
+    char side='R', uplo='L'; \
+    MKL_INT m, n, lda, ldb, ldc; \
+    const EIGTYPE *a, *b; \
+    MKLTYPE alpha_, beta_; \
+    MatrixX##EIGPREFIX b_tmp; \
+    Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> a_tmp; \
+    EIGTYPE myone(1); \
+\
+/* Set m, n, k */ \
+    m = (MKL_INT)rows; \
+    n = (MKL_INT)cols; \
+\
+/* Set alpha_ & beta_ */ \
+    assign_scalar_eig2mkl(alpha_, alpha); \
+    assign_scalar_eig2mkl(beta_, myone); \
+\
+/* Set lda, ldb, ldc */ \
+    lda = (MKL_INT)rhsStride; \
+    ldb = (MKL_INT)lhsStride; \
+    ldc = (MKL_INT)resStride; \
+\
+/* Set a, b, c */ \
+    if (((RhsStorageOrder==ColMajor) && ConjugateRhs) || ((RhsStorageOrder==RowMajor) && (!ConjugateRhs))) { \
+      Map<const Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder>, 0, OuterStride<> > rhs(_rhs,n,n,OuterStride<>(rhsStride)); \
+      a_tmp = rhs.conjugate(); \
+      a = a_tmp.data(); \
+      lda = a_tmp.outerStride(); \
+    } else a = _rhs; \
+    if (RhsStorageOrder==RowMajor) uplo='U'; \
+\
+    if (LhsStorageOrder==ColMajor && (!ConjugateLhs)) { \
+       b = _lhs; } \
+    else { \
+      if (LhsStorageOrder==ColMajor && ConjugateLhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,m,n,OuterStride<>(lhsStride)); \
+        b_tmp = lhs.conjugate(); \
+      } else \
+      if (ConjugateLhs) { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \
+        b_tmp = lhs.adjoint(); \
+      } else { \
+        Map<const MatrixX##EIGPREFIX, 0, OuterStride<> > lhs(_lhs,n,m,OuterStride<>(lhsStride)); \
+        b_tmp = lhs.transpose(); \
+      } \
+      b = b_tmp.data(); \
+      ldb = b_tmp.outerStride(); \
+    } \
+\
+    MKLPREFIX##hemm(&side, &uplo, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)b, &ldb, &beta_, (MKLTYPE*)res, &ldc); \
+  } \
+};
+
+EIGEN_MKL_SYMM_R(double, double, d, d)
+EIGEN_MKL_SYMM_R(float, float, f, s)
+EIGEN_MKL_HEMM_R(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_HEMM_R(scomplex, MKL_Complex8, cf, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SELFADJOINT_MATRIX_MATRIX_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h
index d6121fc07bd..c3145c69a5f 100644
--- a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h
+++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_H
 #define EIGEN_SELFADJOINT_MATRIX_VECTOR_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /* Optimized selfadjoint matrix * vector product:
@@ -32,8 +19,15 @@ namespace internal {
  * the number of load/stores of the result by a factor 2 and to reduce
  * the instruction dependency.
  */
-template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
-static EIGEN_DONT_INLINE void product_selfadjoint_vector(
+
+template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version=Specialized>
+struct selfadjoint_matrix_vector_product;
+
+template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs, int Version>
+struct selfadjoint_matrix_vector_product
+
+{
+static EIGEN_DONT_INLINE void run(
   Index size,
   const Scalar*  lhs, Index lhsStride,
   const Scalar* _rhs, Index rhsIncr,
@@ -85,14 +79,14 @@ static EIGEN_DONT_INLINE void product_selfadjoint_vector(
     Scalar t1 = cjAlpha * rhs[j+1];
     Packet ptmp1 = pset1<Packet>(t1);
 
-    Scalar t2 = 0;
+    Scalar t2(0);
     Packet ptmp2 = pset1<Packet>(t2);
-    Scalar t3 = 0;
+    Scalar t3(0);
     Packet ptmp3 = pset1<Packet>(t3);
 
     size_t starti = FirstTriangular ? 0 : j+2;
     size_t endi   = FirstTriangular ? j : size;
-    size_t alignedStart = (starti) + first_aligned(&res[starti], endi-starti);
+    size_t alignedStart = (starti) + internal::first_aligned(&res[starti], endi-starti);
     size_t alignedEnd = alignedStart + ((endi-alignedStart)/(PacketSize))*(PacketSize);
 
     // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed
@@ -148,7 +142,7 @@ static EIGEN_DONT_INLINE void product_selfadjoint_vector(
     register const Scalar* EIGEN_RESTRICT A0 = lhs + j*lhsStride;
 
     Scalar t1 = cjAlpha * rhs[j];
-    Scalar t2 = 0;
+    Scalar t2(0);
     // TODO make sure this product is a real * complex and that the rhs is properly conjugated if needed
     res[j] += cjd.pmul(internal::real(A0[j]), t1);
     for (Index i=FirstTriangular ? 0 : j+1; i<(FirstTriangular ? j : size); i++)
@@ -159,6 +153,7 @@ static EIGEN_DONT_INLINE void product_selfadjoint_vector(
     res[j] += alpha * t2;
   }
 }
+};
 
 } // end namespace internal 
 
@@ -193,8 +188,8 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>
     
     eigen_assert(dest.rows()==m_lhs.rows() && dest.cols()==m_rhs.cols());
 
-    const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
-    const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
+    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);
 
     Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                                * RhsBlasTraits::extractScalarFactor(m_rhs);
@@ -232,7 +227,7 @@ struct SelfadjointProductMatrix<Lhs,LhsMode,false,Rhs,0,true>
     }
       
       
-    internal::product_selfadjoint_vector<Scalar, Index, (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>
+    internal::selfadjoint_matrix_vector_product<Scalar, Index, (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, int(LhsUpLo), bool(LhsBlasTraits::NeedToConjugate), bool(RhsBlasTraits::NeedToConjugate)>::run
       (
         lhs.rows(),                             // size
         &lhs.coeffRef(0,0),  lhs.outerStride(), // lhs info
@@ -274,5 +269,6 @@ struct SelfadjointProductMatrix<Lhs,0,true,Rhs,RhsMode,false>
   }
 };
 
+} // end namespace Eigen
 
 #endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h
new file mode 100644
index 00000000000..f88d483b653
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h
@@ -0,0 +1,114 @@
+/*
+ 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
+ *   Selfadjoint matrix-vector product functionality based on ?SYMV/HEMV.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
+#define EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements selfadjoint matrix-vector multiplication using BLAS
+**********************************************************************/
+
+// symv/hemv specialization
+
+template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs>
+struct selfadjoint_matrix_vector_product_symv :
+  selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn> {};
+
+#define EIGEN_MKL_SYMV_SPECIALIZE(Scalar) \
+template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
+struct selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,Specialized> { \
+static EIGEN_DONT_INLINE void run( \
+  Index size, const Scalar*  lhs, Index lhsStride, \
+  const Scalar* _rhs, Index rhsIncr, Scalar* res, Scalar alpha) { \
+    enum {\
+      IsColMajor = StorageOrder==ColMajor \
+    }; \
+    if (IsColMajor == ConjugateLhs) {\
+      selfadjoint_matrix_vector_product<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs,BuiltIn>::run( \
+        size, lhs, lhsStride, _rhs, rhsIncr, res, alpha);  \
+    } else {\
+      selfadjoint_matrix_vector_product_symv<Scalar,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs>::run( \
+        size, lhs, lhsStride, _rhs, rhsIncr, res, alpha);  \
+    }\
+  } \
+}; \
+
+EIGEN_MKL_SYMV_SPECIALIZE(double)
+EIGEN_MKL_SYMV_SPECIALIZE(float)
+EIGEN_MKL_SYMV_SPECIALIZE(dcomplex)
+EIGEN_MKL_SYMV_SPECIALIZE(scomplex)
+
+#define EIGEN_MKL_SYMV_SPECIALIZATION(EIGTYPE,MKLTYPE,MKLFUNC) \
+template<typename Index, int StorageOrder, int UpLo, bool ConjugateLhs, bool ConjugateRhs> \
+struct selfadjoint_matrix_vector_product_symv<EIGTYPE,Index,StorageOrder,UpLo,ConjugateLhs,ConjugateRhs> \
+{ \
+typedef Matrix<EIGTYPE,Dynamic,1,ColMajor> SYMVVector;\
+\
+static EIGEN_DONT_INLINE void run( \
+Index size, const EIGTYPE*  lhs, Index lhsStride, \
+const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* res, EIGTYPE alpha) \
+{ \
+  enum {\
+    IsRowMajor = StorageOrder==RowMajor ? 1 : 0, \
+    IsLower = UpLo == Lower ? 1 : 0 \
+  }; \
+  MKL_INT n=size, lda=lhsStride, incx=rhsIncr, incy=1; \
+  MKLTYPE alpha_, beta_; \
+  const EIGTYPE *x_ptr, myone(1); \
+  char uplo=(IsRowMajor) ? (IsLower ? 'U' : 'L') : (IsLower ? 'L' : 'U'); \
+  assign_scalar_eig2mkl(alpha_, alpha); \
+  assign_scalar_eig2mkl(beta_, myone); \
+  SYMVVector x_tmp; \
+  if (ConjugateRhs) { \
+    Map<const SYMVVector, 0, InnerStride<> > map_x(_rhs,size,1,InnerStride<>(incx)); \
+    x_tmp=map_x.conjugate(); \
+    x_ptr=x_tmp.data(); \
+    incx=1; \
+  } else x_ptr=_rhs; \
+  MKLFUNC(&uplo, &n, &alpha_, (const MKLTYPE*)lhs, &lda, (const MKLTYPE*)x_ptr, &incx, &beta_, (MKLTYPE*)res, &incy); \
+}\
+};
+
+EIGEN_MKL_SYMV_SPECIALIZATION(double,   double,        dsymv)
+EIGEN_MKL_SYMV_SPECIALIZATION(float,    float,         ssymv)
+EIGEN_MKL_SYMV_SPECIALIZATION(dcomplex, MKL_Complex16, zhemv)
+EIGEN_MKL_SYMV_SPECIALIZATION(scomplex, MKL_Complex8,  chemv)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SELFADJOINT_MATRIX_VECTOR_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointProduct.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointProduct.h
index 3a4523fa4a9..6a55f3d7715 100644
--- a/extern/Eigen3/Eigen/src/Core/products/SelfadjointProduct.h
+++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointProduct.h
@@ -3,24 +3,9 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELFADJOINT_PRODUCT_H
 #define EIGEN_SELFADJOINT_PRODUCT_H
@@ -31,6 +16,8 @@
 * It corresponds to the level 3 SYRK and level 2 SYR Blas routines.
 **********************************************************************/
 
+namespace Eigen { 
+
 template<typename Scalar, typename Index, int StorageOrder, int UpLo, bool ConjLhs, bool ConjRhs>
 struct selfadjoint_rank1_update;
 
@@ -72,7 +59,7 @@ struct selfadjoint_product_selector<MatrixType,OtherType,UpLo,true>
     typedef internal::blas_traits<OtherType> OtherBlasTraits;
     typedef typename OtherBlasTraits::DirectLinearAccessType ActualOtherType;
     typedef typename internal::remove_all<ActualOtherType>::type _ActualOtherType;
-    const ActualOtherType actualOther = OtherBlasTraits::extract(other.derived());
+    typename internal::add_const_on_value_type<ActualOtherType>::type actualOther = OtherBlasTraits::extract(other.derived());
 
     Scalar actualAlpha = alpha * OtherBlasTraits::extractScalarFactor(other.derived());
 
@@ -105,12 +92,12 @@ struct selfadjoint_product_selector<MatrixType,OtherType,UpLo,false>
     typedef internal::blas_traits<OtherType> OtherBlasTraits;
     typedef typename OtherBlasTraits::DirectLinearAccessType ActualOtherType;
     typedef typename internal::remove_all<ActualOtherType>::type _ActualOtherType;
-    const ActualOtherType actualOther = OtherBlasTraits::extract(other.derived());
+    typename internal::add_const_on_value_type<ActualOtherType>::type actualOther = OtherBlasTraits::extract(other.derived());
 
     Scalar actualAlpha = alpha * OtherBlasTraits::extractScalarFactor(other.derived());
 
     enum { IsRowMajor = (internal::traits<MatrixType>::Flags&RowMajorBit) ? 1 : 0 };
-    
+
     internal::general_matrix_matrix_triangular_product<Index,
       Scalar, _ActualOtherType::Flags&RowMajorBit ? RowMajor : ColMajor,   OtherBlasTraits::NeedToConjugate  && NumTraits<Scalar>::IsComplex,
       Scalar, _ActualOtherType::Flags&RowMajorBit ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits<Scalar>::IsComplex,
@@ -133,4 +120,6 @@ SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
   return *this;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SELFADJOINT_PRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/SelfadjointRank2Update.h b/extern/Eigen3/Eigen/src/Core/products/SelfadjointRank2Update.h
index 9f8b8438a5d..57a98cc2de9 100644
--- a/extern/Eigen3/Eigen/src/Core/products/SelfadjointRank2Update.h
+++ b/extern/Eigen3/Eigen/src/Core/products/SelfadjointRank2Update.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELFADJOINTRANK2UPTADE_H
 #define EIGEN_SELFADJOINTRANK2UPTADE_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /* Optimized selfadjoint matrix += alpha * uv' + conj(alpha)*vu'
@@ -76,12 +63,12 @@ SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
   typedef internal::blas_traits<DerivedU> UBlasTraits;
   typedef typename UBlasTraits::DirectLinearAccessType ActualUType;
   typedef typename internal::remove_all<ActualUType>::type _ActualUType;
-  const ActualUType actualU = UBlasTraits::extract(u.derived());
+  typename internal::add_const_on_value_type<ActualUType>::type actualU = UBlasTraits::extract(u.derived());
 
   typedef internal::blas_traits<DerivedV> VBlasTraits;
   typedef typename VBlasTraits::DirectLinearAccessType ActualVType;
   typedef typename internal::remove_all<ActualVType>::type _ActualVType;
-  const ActualVType actualV = VBlasTraits::extract(v.derived());
+  typename internal::add_const_on_value_type<ActualVType>::type actualV = VBlasTraits::extract(v.derived());
 
   // If MatrixType is row major, then we use the routine for lower triangular in the upper triangular case and
   // vice versa, and take the complex conjugate of all coefficients and vector entries.
@@ -101,4 +88,6 @@ SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
   return *this;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SELFADJOINTRANK2UPTADE_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixMatrix.h b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixMatrix.h
index 0c48d2efb75..92cba66f615 100644
--- a/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixMatrix.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_H
 #define EIGEN_TRIANGULAR_MATRIX_MATRIX_H
 
+namespace Eigen { 
+
 namespace internal {
 
 // template<typename Scalar, int mr, int StorageOrder, bool Conjugate, int Mode>
@@ -58,23 +45,23 @@ template <typename Scalar, typename Index,
           int Mode, bool LhsIsTriangular,
           int LhsStorageOrder, bool ConjugateLhs,
           int RhsStorageOrder, bool ConjugateRhs,
-          int ResStorageOrder>
+          int ResStorageOrder, int Version = Specialized>
 struct product_triangular_matrix_matrix;
 
 template <typename Scalar, typename Index,
           int Mode, bool LhsIsTriangular,
           int LhsStorageOrder, bool ConjugateLhs,
-          int RhsStorageOrder, bool ConjugateRhs>
+          int RhsStorageOrder, bool ConjugateRhs, int Version>
 struct product_triangular_matrix_matrix<Scalar,Index,Mode,LhsIsTriangular,
                                            LhsStorageOrder,ConjugateLhs,
-                                           RhsStorageOrder,ConjugateRhs,RowMajor>
+                                           RhsStorageOrder,ConjugateRhs,RowMajor,Version>
 {
   static EIGEN_STRONG_INLINE void run(
     Index rows, Index cols, Index depth,
     const Scalar* lhs, Index lhsStride,
     const Scalar* rhs, Index rhsStride,
     Scalar* res,       Index resStride,
-    Scalar alpha)
+    Scalar alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
     product_triangular_matrix_matrix<Scalar, Index,
       (Mode&(UnitDiag|ZeroDiag)) | ((Mode&Upper) ? Lower : Upper),
@@ -84,22 +71,22 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,LhsIsTriangular,
       LhsStorageOrder==RowMajor ? ColMajor : RowMajor,
       ConjugateLhs,
       ColMajor>
-      ::run(cols, rows, depth, rhs, rhsStride, lhs, lhsStride, res, resStride, alpha);
+      ::run(cols, rows, depth, rhs, rhsStride, lhs, lhsStride, res, resStride, alpha, blocking);
   }
 };
 
 // implements col-major += alpha * op(triangular) * op(general)
 template <typename Scalar, typename Index, int Mode,
           int LhsStorageOrder, bool ConjugateLhs,
-          int RhsStorageOrder, bool ConjugateRhs>
+          int RhsStorageOrder, bool ConjugateRhs, int Version>
 struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
                                            LhsStorageOrder,ConjugateLhs,
-                                           RhsStorageOrder,ConjugateRhs,ColMajor>
+                                           RhsStorageOrder,ConjugateRhs,ColMajor,Version>
 {
   
   typedef gebp_traits<Scalar,Scalar> Traits;
   enum {
-    SmallPanelWidth   = EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr),
+    SmallPanelWidth   = 2 * EIGEN_PLAIN_ENUM_MAX(Traits::mr,Traits::nr),
     IsLower = (Mode&Lower) == Lower,
     SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1
   };
@@ -109,7 +96,7 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
     Scalar* res,        Index resStride,
-    Scalar alpha)
+    Scalar alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
     // strip zeros
     Index diagSize  = (std::min)(_rows,_depth);
@@ -120,15 +107,16 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
     const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
     const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
 
-    Index kc = depth; // cache block size along the K direction
-    Index mc = rows;  // cache block size along the M direction
-    Index nc = cols;  // cache block size along the N direction
-    computeProductBlockingSizes<Scalar,Scalar,4>(kc, mc, nc);
+    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
+
+    std::size_t sizeA = kc*mc;
+    std::size_t sizeB = kc*cols;
     std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    std::size_t sizeB = sizeW + kc*cols;
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
-    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);    
-    Scalar* blockB = allocatedBlockB + sizeW;
+
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
     Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,LhsStorageOrder> triangularBuffer;
     triangularBuffer.setZero();
@@ -186,7 +174,7 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
           pack_lhs(blockA, triangularBuffer.data(), triangularBuffer.outerStride(), actualPanelWidth, actualPanelWidth);
 
           gebp_kernel(res+startBlock, resStride, blockA, blockB, actualPanelWidth, actualPanelWidth, cols, alpha,
-                      actualPanelWidth, actual_kc, 0, blockBOffset);
+                      actualPanelWidth, actual_kc, 0, blockBOffset, blockW);
 
           // GEBP with remaining micro panel
           if (lengthTarget>0)
@@ -196,7 +184,7 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
             pack_lhs(blockA, &lhs(startTarget,startBlock), lhsStride, actualPanelWidth, lengthTarget);
 
             gebp_kernel(res+startTarget, resStride, blockA, blockB, lengthTarget, actualPanelWidth, cols, alpha,
-                        actualPanelWidth, actual_kc, 0, blockBOffset);
+                        actualPanelWidth, actual_kc, 0, blockBOffset, blockW);
           }
         }
       }
@@ -210,7 +198,7 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
           gemm_pack_lhs<Scalar, Index, Traits::mr,Traits::LhsProgress, LhsStorageOrder,false>()
             (blockA, &lhs(i2, actual_k2), lhsStride, actual_kc, actual_mc);
 
-          gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha);
+          gebp_kernel(res+i2, resStride, blockA, blockB, actual_mc, actual_kc, cols, alpha, -1, -1, 0, 0, blockW);
         }
       }
     }
@@ -220,10 +208,10 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,true,
 // implements col-major += alpha * op(general) * op(triangular)
 template <typename Scalar, typename Index, int Mode,
           int LhsStorageOrder, bool ConjugateLhs,
-          int RhsStorageOrder, bool ConjugateRhs>
+          int RhsStorageOrder, bool ConjugateRhs, int Version>
 struct product_triangular_matrix_matrix<Scalar,Index,Mode,false,
                                            LhsStorageOrder,ConjugateLhs,
-                                           RhsStorageOrder,ConjugateRhs,ColMajor>
+                                           RhsStorageOrder,ConjugateRhs,ColMajor,Version>
 {
   typedef gebp_traits<Scalar,Scalar> Traits;
   enum {
@@ -237,7 +225,7 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,false,
     const Scalar* _lhs, Index lhsStride,
     const Scalar* _rhs, Index rhsStride,
     Scalar* res,        Index resStride,
-    Scalar alpha)
+    Scalar alpha, level3_blocking<Scalar,Scalar>& blocking)
   {
     // strip zeros
     Index diagSize  = (std::min)(_cols,_depth);
@@ -248,16 +236,16 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,false,
     const_blas_data_mapper<Scalar, Index, LhsStorageOrder> lhs(_lhs,lhsStride);
     const_blas_data_mapper<Scalar, Index, RhsStorageOrder> rhs(_rhs,rhsStride);
 
-    Index kc = depth; // cache block size along the K direction
-    Index mc = rows;  // cache block size along the M direction
-    Index nc = cols;  // cache block size along the N direction
-    computeProductBlockingSizes<Scalar,Scalar,4>(kc, mc, nc);
+    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
 
+    std::size_t sizeA = kc*mc;
+    std::size_t sizeB = kc*cols;
     std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    std::size_t sizeB = sizeW + kc*cols;
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
-    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);
-    Scalar* blockB = allocatedBlockB + sizeW;
+
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
     Matrix<Scalar,SmallPanelWidth,SmallPanelWidth,RhsStorageOrder> triangularBuffer;
     triangularBuffer.setZero();
@@ -345,13 +333,13 @@ struct product_triangular_matrix_matrix<Scalar,Index,Mode,false,
                         alpha,
                         actual_kc, actual_kc,  // strides
                         blockOffset, blockOffset,// offsets
-                        allocatedBlockB); // workspace
+                        blockW); // workspace
           }
         }
         gebp_kernel(res+i2+(IsLower ? 0 : k2)*resStride, resStride,
                     blockA, geb, actual_mc, actual_kc, rs,
                     alpha,
-                    -1, -1, 0, 0, allocatedBlockB);
+                    -1, -1, 0, 0, blockW);
       }
     }
   }
@@ -378,26 +366,38 @@ struct TriangularProduct<Mode,LhsIsTriangular,Lhs,false,Rhs,false>
 
   template<typename Dest> void scaleAndAddTo(Dest& dst, Scalar alpha) const
   {
-    const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
-    const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
+    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);
 
     Scalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(m_lhs)
                                * RhsBlasTraits::extractScalarFactor(m_rhs);
 
+    typedef internal::gemm_blocking_space<(Dest::Flags&RowMajorBit) ? RowMajor : ColMajor,Scalar,Scalar,
+              Lhs::MaxRowsAtCompileTime, Rhs::MaxColsAtCompileTime, Lhs::MaxColsAtCompileTime,4> BlockingType;
+
+    enum { IsLower = (Mode&Lower) == Lower };
+    Index stripedRows  = ((!LhsIsTriangular) || (IsLower))  ? lhs.rows() : (std::min)(lhs.rows(),lhs.cols());
+    Index stripedCols  = ((LhsIsTriangular)  || (!IsLower)) ? rhs.cols() : (std::min)(rhs.cols(),rhs.rows());
+    Index stripedDepth = LhsIsTriangular ? ((!IsLower) ? lhs.cols() : (std::min)(lhs.cols(),lhs.rows()))
+                                         : ((IsLower)  ? rhs.rows() : (std::min)(rhs.rows(),rhs.cols()));
+
+    BlockingType blocking(stripedRows, stripedCols, stripedDepth);
+
     internal::product_triangular_matrix_matrix<Scalar, Index,
       Mode, LhsIsTriangular,
       (internal::traits<_ActualLhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate,
       (internal::traits<_ActualRhsType>::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate,
       (internal::traits<Dest          >::Flags&RowMajorBit) ? RowMajor : ColMajor>
       ::run(
-        lhs.rows(), rhs.cols(), lhs.cols(),// LhsIsTriangular ? rhs.cols() : lhs.rows(),           // sizes
+        stripedRows, stripedCols, stripedDepth,   // sizes
         &lhs.coeffRef(0,0),    lhs.outerStride(), // lhs info
         &rhs.coeffRef(0,0),    rhs.outerStride(), // rhs info
-        &dst.coeffRef(0,0), dst.outerStride(), // result info
-        actualAlpha                            // alpha
+        &dst.coeffRef(0,0), dst.outerStride(),    // result info
+        actualAlpha, blocking
       );
   }
 };
 
+} // end namespace Eigen
 
 #endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
new file mode 100644
index 00000000000..8173da5bb6d
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h
@@ -0,0 +1,309 @@
+/*
+ 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
+ *   Triangular matrix * matrix product functionality based on ?TRMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H
+#define EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H
+
+namespace Eigen { 
+
+namespace internal {
+
+
+template <typename Scalar, typename Index,
+          int Mode, bool LhsIsTriangular,
+          int LhsStorageOrder, bool ConjugateLhs,
+          int RhsStorageOrder, bool ConjugateRhs,
+          int ResStorageOrder>
+struct product_triangular_matrix_matrix_trmm :
+       product_triangular_matrix_matrix<Scalar,Index,Mode,
+          LhsIsTriangular,LhsStorageOrder,ConjugateLhs,
+          RhsStorageOrder, ConjugateRhs, ResStorageOrder, BuiltIn> {};
+
+
+// try to go to BLAS specialization
+#define EIGEN_MKL_TRMM_SPECIALIZE(Scalar, LhsIsTriangular) \
+template <typename Index, int Mode, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_triangular_matrix_matrix<Scalar,Index, Mode, LhsIsTriangular, \
+           LhsStorageOrder,ConjugateLhs, RhsStorageOrder,ConjugateRhs,ColMajor,Specialized> { \
+  static inline void run(Index _rows, Index _cols, Index _depth, const Scalar* _lhs, Index lhsStride,\
+    const Scalar* _rhs, Index rhsStride, Scalar* res, Index resStride, Scalar alpha) { \
+      product_triangular_matrix_matrix_trmm<Scalar,Index,Mode, \
+        LhsIsTriangular,LhsStorageOrder,ConjugateLhs, \
+        RhsStorageOrder, ConjugateRhs, ColMajor>::run( \
+        _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+  } \
+};
+
+EIGEN_MKL_TRMM_SPECIALIZE(double, true)
+EIGEN_MKL_TRMM_SPECIALIZE(double, false)
+EIGEN_MKL_TRMM_SPECIALIZE(dcomplex, true)
+EIGEN_MKL_TRMM_SPECIALIZE(dcomplex, false)
+EIGEN_MKL_TRMM_SPECIALIZE(float, true)
+EIGEN_MKL_TRMM_SPECIALIZE(float, false)
+EIGEN_MKL_TRMM_SPECIALIZE(scomplex, true)
+EIGEN_MKL_TRMM_SPECIALIZE(scomplex, false)
+
+// implements col-major += alpha * op(triangular) * op(general)
+#define EIGEN_MKL_TRMM_L(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template <typename Index, int Mode, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,true, \
+         LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper, \
+    conjA = ((LhsStorageOrder==ColMajor) && ConjugateLhs) ? 1 : 0 \
+  }; \
+\
+  static EIGEN_DONT_INLINE void run( \
+    Index _rows, Index _cols, Index _depth, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha) \
+  { \
+   Index diagSize  = (std::min)(_rows,_depth); \
+   Index rows      = IsLower ? _rows : diagSize; \
+   Index depth     = IsLower ? diagSize : _depth; \
+   Index cols      = _cols; \
+\
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> MatrixLhs; \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs; \
+\
+/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
+   if (rows != depth) { \
+\
+     int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
+\
+     if (((nthr==1) && (((std::max)(rows,depth)-diagSize)/(double)diagSize < 0.5))) { \
+     /* Most likely no benefit to call TRMM or GEMM from MKL*/ \
+       product_triangular_matrix_matrix<EIGTYPE,Index,Mode,true, \
+       LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
+           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+     /*std::cout << "TRMM_L: A is not square! Go to Eigen TRMM implementation!\n";*/ \
+     } else { \
+     /* Make sense to call GEMM */ \
+       Map<const MatrixLhs, 0, OuterStride<> > lhsMap(_lhs,rows,depth,OuterStride<>(lhsStride)); \
+       MatrixLhs aa_tmp=lhsMap.template triangularView<Mode>(); \
+       MKL_INT aStride = aa_tmp.outerStride(); \
+       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> blocking(_rows,_cols,_depth); \
+       general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
+       rows, cols, depth, aa_tmp.data(), aStride, _rhs, rhsStride, res, resStride, alpha, blocking, 0); \
+\
+     /*std::cout << "TRMM_L: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
+     } \
+     return; \
+   } \
+   char side = 'L', transa, uplo, diag = 'N'; \
+   EIGTYPE *b; \
+   const EIGTYPE *a; \
+   MKL_INT m, n, lda, ldb; \
+   MKLTYPE alpha_; \
+\
+/* Set alpha_*/ \
+   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
+\
+/* Set m, n */ \
+   m = (MKL_INT)diagSize; \
+   n = (MKL_INT)cols; \
+\
+/* Set trans */ \
+   transa = (LhsStorageOrder==RowMajor) ? ((ConjugateLhs) ? 'C' : 'T') : 'N'; \
+\
+/* Set b, ldb */ \
+   Map<const MatrixRhs, 0, OuterStride<> > rhs(_rhs,depth,cols,OuterStride<>(rhsStride)); \
+   MatrixX##EIGPREFIX b_tmp; \
+\
+   if (ConjugateRhs) b_tmp = rhs.conjugate(); else b_tmp = rhs; \
+   b = b_tmp.data(); \
+   ldb = b_tmp.outerStride(); \
+\
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (LhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   Map<const MatrixLhs, 0, OuterStride<> > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \
+   MatrixLhs a_tmp; \
+\
+   if ((conjA!=0) || (SetDiag==0)) { \
+     if (conjA) a_tmp = lhs.conjugate(); else a_tmp = lhs; \
+     if (IsZeroDiag) \
+       a_tmp.diagonal().setZero(); \
+     else if (IsUnitDiag) \
+       a_tmp.diagonal().setOnes();\
+     a = a_tmp.data(); \
+     lda = a_tmp.outerStride(); \
+   } else { \
+     a = _lhs; \
+     lda = lhsStride; \
+   } \
+   /*std::cout << "TRMM_L: A is square! Go to MKL TRMM implementation! \n";*/ \
+/* call ?trmm*/ \
+   MKLPREFIX##trmm(&side, &uplo, &transa, &diag, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (MKLTYPE*)b, &ldb); \
+\
+/* Add op(a_triangular)*b into res*/ \
+   Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
+   res_tmp=res_tmp+b_tmp; \
+  } \
+};
+
+EIGEN_MKL_TRMM_L(double, double, d, d)
+EIGEN_MKL_TRMM_L(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_TRMM_L(float, float, f, s)
+EIGEN_MKL_TRMM_L(scomplex, MKL_Complex8, cf, c)
+
+// implements col-major += alpha * op(general) * op(triangular)
+#define EIGEN_MKL_TRMM_R(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template <typename Index, int Mode, \
+          int LhsStorageOrder, bool ConjugateLhs, \
+          int RhsStorageOrder, bool ConjugateRhs> \
+struct product_triangular_matrix_matrix_trmm<EIGTYPE,Index,Mode,false, \
+         LhsStorageOrder,ConjugateLhs,RhsStorageOrder,ConjugateRhs,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper, \
+    conjA = ((RhsStorageOrder==ColMajor) && ConjugateRhs) ? 1 : 0 \
+  }; \
+\
+  static EIGEN_DONT_INLINE void run( \
+    Index _rows, Index _cols, Index _depth, \
+    const EIGTYPE* _lhs, Index lhsStride, \
+    const EIGTYPE* _rhs, Index rhsStride, \
+    EIGTYPE* res,        Index resStride, \
+    EIGTYPE alpha) \
+  { \
+   Index diagSize  = (std::min)(_cols,_depth); \
+   Index rows      = _rows; \
+   Index depth     = IsLower ? _depth : diagSize; \
+   Index cols      = IsLower ? diagSize : _cols; \
+\
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, LhsStorageOrder> MatrixLhs; \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, RhsStorageOrder> MatrixRhs; \
+\
+/* Non-square case - doesn't fit to MKL ?TRMM. Fall to default triangular product or call MKL ?GEMM*/ \
+   if (cols != depth) { \
+\
+     int nthr = mkl_domain_get_max_threads(MKL_BLAS); \
+\
+     if ((nthr==1) && (((std::max)(cols,depth)-diagSize)/(double)diagSize < 0.5)) { \
+     /* Most likely no benefit to call TRMM or GEMM from MKL*/ \
+       product_triangular_matrix_matrix<EIGTYPE,Index,Mode,false, \
+       LhsStorageOrder,ConjugateLhs, RhsStorageOrder, ConjugateRhs, ColMajor, BuiltIn>::run( \
+           _rows, _cols, _depth, _lhs, lhsStride, _rhs, rhsStride, res, resStride, alpha); \
+       /*std::cout << "TRMM_R: A is not square! Go to Eigen TRMM implementation!\n";*/ \
+     } else { \
+     /* Make sense to call GEMM */ \
+       Map<const MatrixRhs, 0, OuterStride<> > rhsMap(_rhs,depth,cols, OuterStride<>(rhsStride)); \
+       MatrixRhs aa_tmp=rhsMap.template triangularView<Mode>(); \
+       MKL_INT aStride = aa_tmp.outerStride(); \
+       gemm_blocking_space<ColMajor,EIGTYPE,EIGTYPE,Dynamic,Dynamic,Dynamic> blocking(_rows,_cols,_depth); \
+       general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor>::run( \
+       rows, cols, depth, _lhs, lhsStride, aa_tmp.data(), aStride, res, resStride, alpha, blocking, 0); \
+\
+     /*std::cout << "TRMM_R: A is not square! Go to MKL GEMM implementation! " << nthr<<" \n";*/ \
+     } \
+     return; \
+   } \
+   char side = 'R', transa, uplo, diag = 'N'; \
+   EIGTYPE *b; \
+   const EIGTYPE *a; \
+   MKL_INT m, n, lda, ldb; \
+   MKLTYPE alpha_; \
+\
+/* Set alpha_*/ \
+   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
+\
+/* Set m, n */ \
+   m = (MKL_INT)rows; \
+   n = (MKL_INT)diagSize; \
+\
+/* Set trans */ \
+   transa = (RhsStorageOrder==RowMajor) ? ((ConjugateRhs) ? 'C' : 'T') : 'N'; \
+\
+/* Set b, ldb */ \
+   Map<const MatrixLhs, 0, OuterStride<> > lhs(_lhs,rows,depth,OuterStride<>(lhsStride)); \
+   MatrixX##EIGPREFIX b_tmp; \
+\
+   if (ConjugateLhs) b_tmp = lhs.conjugate(); else b_tmp = lhs; \
+   b = b_tmp.data(); \
+   ldb = b_tmp.outerStride(); \
+\
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (RhsStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   Map<const MatrixRhs, 0, OuterStride<> > rhs(_rhs,depth,cols, OuterStride<>(rhsStride)); \
+   MatrixRhs a_tmp; \
+\
+   if ((conjA!=0) || (SetDiag==0)) { \
+     if (conjA) a_tmp = rhs.conjugate(); else a_tmp = rhs; \
+     if (IsZeroDiag) \
+       a_tmp.diagonal().setZero(); \
+     else if (IsUnitDiag) \
+       a_tmp.diagonal().setOnes();\
+     a = a_tmp.data(); \
+     lda = a_tmp.outerStride(); \
+   } else { \
+     a = _rhs; \
+     lda = rhsStride; \
+   } \
+   /*std::cout << "TRMM_R: A is square! Go to MKL TRMM implementation! \n";*/ \
+/* call ?trmm*/ \
+   MKLPREFIX##trmm(&side, &uplo, &transa, &diag, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (MKLTYPE*)b, &ldb); \
+\
+/* Add op(a_triangular)*b into res*/ \
+   Map<MatrixX##EIGPREFIX, 0, OuterStride<> > res_tmp(res,rows,cols,OuterStride<>(resStride)); \
+   res_tmp=res_tmp+b_tmp; \
+  } \
+};
+
+EIGEN_MKL_TRMM_R(double, double, d, d)
+EIGEN_MKL_TRMM_R(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_TRMM_R(float, float, f, s)
+EIGEN_MKL_TRMM_R(scomplex, MKL_Complex8, cf, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TRIANGULAR_MATRIX_MATRIX_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixVector.h b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixVector.h
index 71b4a52ab80..b1c10c201c5 100644
--- a/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixVector.h
+++ b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixVector.h
@@ -3,45 +3,36 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULARMATRIXVECTOR_H
 #define EIGEN_TRIANGULARMATRIXVECTOR_H
 
+namespace Eigen { 
+
 namespace internal {
 
-template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
-struct product_triangular_matrix_vector;
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder, int Version=Specialized>
+struct triangular_matrix_vector_product;
 
-template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
-struct product_triangular_matrix_vector<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor>
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int Version>
+struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,ColMajor,Version>
 {
   typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   enum {
     IsLower = ((Mode&Lower)==Lower),
-    HasUnitDiag = (Mode & UnitDiag)==UnitDiag
+    HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
+    HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
   };
-  static EIGEN_DONT_INLINE  void run(Index rows, Index cols, const LhsScalar* _lhs, Index lhsStride,
+  static EIGEN_DONT_INLINE  void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
                                      const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, ResScalar alpha)
   {
     static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
+    Index size = (std::min)(_rows,_cols);
+    Index rows = IsLower ? _rows : (std::min)(_rows,_cols);
+    Index cols = IsLower ? (std::min)(_rows,_cols) : _cols;
 
     typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,ColMajor>, 0, OuterStride<> > LhsMap;
     const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride));
@@ -54,45 +45,57 @@ struct product_triangular_matrix_vector<Index,Mode,LhsScalar,ConjLhs,RhsScalar,C
     typedef Map<Matrix<ResScalar,Dynamic,1> > ResMap;
     ResMap res(_res,rows);
 
-    for (Index pi=0; pi<cols; pi+=PanelWidth)
+    for (Index pi=0; pi<size; pi+=PanelWidth)
     {
-      Index actualPanelWidth = (std::min)(PanelWidth, cols-pi);
+      Index actualPanelWidth = (std::min)(PanelWidth, size-pi);
       for (Index k=0; k<actualPanelWidth; ++k)
       {
         Index i = pi + k;
-        Index s = IsLower ? (HasUnitDiag ? i+1 : i ) : pi;
+        Index s = IsLower ? ((HasUnitDiag||HasZeroDiag) ? i+1 : i ) : pi;
         Index r = IsLower ? actualPanelWidth-k : k+1;
-        if ((!HasUnitDiag) || (--r)>0)
+        if ((!(HasUnitDiag||HasZeroDiag)) || (--r)>0)
           res.segment(s,r) += (alpha * cjRhs.coeff(i)) * cjLhs.col(i).segment(s,r);
         if (HasUnitDiag)
           res.coeffRef(i) += alpha * cjRhs.coeff(i);
       }
-      Index r = IsLower ? cols - pi - actualPanelWidth : pi;
+      Index r = IsLower ? rows - pi - actualPanelWidth : pi;
       if (r>0)
       {
         Index s = IsLower ? pi+actualPanelWidth : 0;
-        general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjLhs,RhsScalar,ConjRhs>::run(
+        general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjLhs,RhsScalar,ConjRhs,BuiltIn>::run(
             r, actualPanelWidth,
             &lhs.coeffRef(s,pi), lhsStride,
             &rhs.coeffRef(pi), rhsIncr,
             &res.coeffRef(s), resIncr, alpha);
       }
     }
+    if((!IsLower) && cols>size)
+    {
+      general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjLhs,RhsScalar,ConjRhs>::run(
+          rows, cols-size,
+          &lhs.coeffRef(0,size), lhsStride,
+          &rhs.coeffRef(size), rhsIncr,
+          _res, resIncr, alpha);
+    }
   }
 };
 
-template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs>
-struct product_triangular_matrix_vector<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor>
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs,int Version>
+struct triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,RowMajor,Version>
 {
   typedef typename scalar_product_traits<LhsScalar, RhsScalar>::ReturnType ResScalar;
   enum {
     IsLower = ((Mode&Lower)==Lower),
-    HasUnitDiag = (Mode & UnitDiag)==UnitDiag
+    HasUnitDiag = (Mode & UnitDiag)==UnitDiag,
+    HasZeroDiag = (Mode & ZeroDiag)==ZeroDiag
   };
-  static void run(Index rows, Index cols, const LhsScalar* _lhs, Index lhsStride,
+  static void run(Index _rows, Index _cols, const LhsScalar* _lhs, Index lhsStride,
                   const RhsScalar* _rhs, Index rhsIncr, ResScalar* _res, Index resIncr, ResScalar alpha)
   {
     static const Index PanelWidth = EIGEN_TUNE_TRIANGULAR_PANEL_WIDTH;
+    Index diagSize = (std::min)(_rows,_cols);
+    Index rows = IsLower ? _rows : diagSize;
+    Index cols = IsLower ? diagSize : _cols;
 
     typedef Map<const Matrix<LhsScalar,Dynamic,Dynamic,RowMajor>, 0, OuterStride<> > LhsMap;
     const LhsMap lhs(_lhs,rows,cols,OuterStride<>(lhsStride));
@@ -105,15 +108,15 @@ struct product_triangular_matrix_vector<Index,Mode,LhsScalar,ConjLhs,RhsScalar,C
     typedef Map<Matrix<ResScalar,Dynamic,1>, 0, InnerStride<> > ResMap;
     ResMap res(_res,rows,InnerStride<>(resIncr));
     
-    for (Index pi=0; pi<cols; pi+=PanelWidth)
+    for (Index pi=0; pi<diagSize; pi+=PanelWidth)
     {
-      Index actualPanelWidth = (std::min)(PanelWidth, cols-pi);
+      Index actualPanelWidth = (std::min)(PanelWidth, diagSize-pi);
       for (Index k=0; k<actualPanelWidth; ++k)
       {
         Index i = pi + k;
-        Index s = IsLower ? pi  : (HasUnitDiag ? i+1 : i);
+        Index s = IsLower ? pi  : ((HasUnitDiag||HasZeroDiag) ? i+1 : i);
         Index r = IsLower ? k+1 : actualPanelWidth-k;
-        if ((!HasUnitDiag) || (--r)>0)
+        if ((!(HasUnitDiag||HasZeroDiag)) || (--r)>0)
           res.coeffRef(i) += alpha * (cjLhs.row(i).segment(s,r).cwiseProduct(cjRhs.segment(s,r).transpose())).sum();
         if (HasUnitDiag)
           res.coeffRef(i) += alpha * cjRhs.coeff(i);
@@ -122,13 +125,21 @@ struct product_triangular_matrix_vector<Index,Mode,LhsScalar,ConjLhs,RhsScalar,C
       if (r>0)
       {
         Index s = IsLower ? 0 : pi + actualPanelWidth;
-        general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjLhs,RhsScalar,ConjRhs>::run(
+        general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjLhs,RhsScalar,ConjRhs,BuiltIn>::run(
             actualPanelWidth, r,
             &lhs.coeffRef(pi,s), lhsStride,
             &rhs.coeffRef(s), rhsIncr,
             &res.coeffRef(pi), resIncr, alpha);
       }
     }
+    if(IsLower && rows>diagSize)
+    {
+      general_matrix_vector_product<Index,LhsScalar,RowMajor,ConjLhs,RhsScalar,ConjRhs>::run(
+            rows-diagSize, cols,
+            &lhs.coeffRef(diagSize,0), lhsStride,
+            &rhs.coeffRef(0), rhsIncr,
+            &res.coeffRef(diagSize), resIncr, alpha);
+    }
   }
 };
 
@@ -180,7 +191,7 @@ struct TriangularProduct<Mode,false,Lhs,true,Rhs,false>
   {
     eigen_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
 
-    typedef TriangularProduct<(Mode & UnitDiag) | ((Mode & Lower) ? Upper : Lower),true,Transpose<const Rhs>,false,Transpose<const Lhs>,true> TriangularProductTranspose;
+    typedef TriangularProduct<(Mode & (UnitDiag|ZeroDiag)) | ((Mode & Lower) ? Upper : Lower),true,Transpose<const Rhs>,false,Transpose<const Lhs>,true> TriangularProductTranspose;
     Transpose<Dest> dstT(dst);
     internal::trmv_selector<(int(internal::traits<Rhs>::Flags)&RowMajorBit) ? ColMajor : RowMajor>::run(
       TriangularProductTranspose(m_rhs.transpose(),m_lhs.transpose()), dstT, alpha);
@@ -208,8 +219,8 @@ template<> struct trmv_selector<ColMajor>
     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());
+    typename internal::add_const_on_value_type<ActualLhsType>::type actualLhs = LhsBlasTraits::extract(prod.lhs());
+    typename internal::add_const_on_value_type<ActualRhsType>::type actualRhs = RhsBlasTraits::extract(prod.rhs());
 
     ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs())
                                   * RhsBlasTraits::extractScalarFactor(prod.rhs());
@@ -247,7 +258,7 @@ template<> struct trmv_selector<ColMajor>
         MappedDest(actualDestPtr, dest.size()) = dest;
     }
     
-    internal::product_triangular_matrix_vector
+    internal::triangular_matrix_vector_product
       <Index,Mode,
        LhsScalar, LhsBlasTraits::NeedToConjugate,
        RhsScalar, RhsBlasTraits::NeedToConjugate,
@@ -307,7 +318,7 @@ template<> struct trmv_selector<RowMajor>
       Map<typename _ActualRhsType::PlainObject>(actualRhsPtr, actualRhs.size()) = actualRhs;
     }
     
-    internal::product_triangular_matrix_vector
+    internal::triangular_matrix_vector_product
       <Index,Mode,
        LhsScalar, LhsBlasTraits::NeedToConjugate,
        RhsScalar, RhsBlasTraits::NeedToConjugate,
@@ -322,4 +333,6 @@ template<> struct trmv_selector<RowMajor>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRIANGULARMATRIXVECTOR_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixVector_MKL.h b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
new file mode 100644
index 00000000000..3589b8c5ef6
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/TriangularMatrixVector_MKL.h
@@ -0,0 +1,247 @@
+/*
+ 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
+ *   Triangular matrix-vector product functionality based on ?TRMV.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
+#define EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/**********************************************************************
+* This file implements triangular matrix-vector multiplication using BLAS
+**********************************************************************/
+
+// trmv/hemv specialization
+
+template<typename Index, int Mode, typename LhsScalar, bool ConjLhs, typename RhsScalar, bool ConjRhs, int StorageOrder>
+struct triangular_matrix_vector_product_trmv :
+  triangular_matrix_vector_product<Index,Mode,LhsScalar,ConjLhs,RhsScalar,ConjRhs,StorageOrder,BuiltIn> {};
+
+#define EIGEN_MKL_TRMV_SPECIALIZE(Scalar) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor,Specialized> { \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
+                                     const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
+      triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,ColMajor>::run( \
+        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+  } \
+}; \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor,Specialized> { \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const Scalar* _lhs, Index lhsStride, \
+                                     const Scalar* _rhs, Index rhsIncr, Scalar* _res, Index resIncr, Scalar alpha) { \
+      triangular_matrix_vector_product_trmv<Index,Mode,Scalar,ConjLhs,Scalar,ConjRhs,RowMajor>::run( \
+        _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha); \
+  } \
+};
+
+EIGEN_MKL_TRMV_SPECIALIZE(double)
+EIGEN_MKL_TRMV_SPECIALIZE(float)
+EIGEN_MKL_TRMV_SPECIALIZE(dcomplex)
+EIGEN_MKL_TRMV_SPECIALIZE(scomplex)
+
+// implements col-major: res += alpha * op(triangular) * vector
+#define EIGEN_MKL_TRMV_CM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor> { \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper \
+  }; \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
+                             const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+ { \
+   if (ConjLhs || IsZeroDiag) { \
+     triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,ColMajor,BuiltIn>::run( \
+       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+     return; \
+   }\
+   Index size = (std::min)(_rows,_cols); \
+   Index rows = IsLower ? _rows : size; \
+   Index cols = IsLower ? size : _cols; \
+\
+   typedef VectorX##EIGPREFIX VectorRhs; \
+   EIGTYPE *x, *y;\
+\
+/* Set x*/ \
+   Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
+   VectorRhs x_tmp; \
+   if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+   x = x_tmp.data(); \
+\
+/* Square part handling */\
+\
+   char trans, uplo, diag; \
+   MKL_INT m, n, lda, incx, incy; \
+   EIGTYPE const *a; \
+   MKLTYPE alpha_, beta_; \
+   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
+   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
+\
+/* Set m, n */ \
+   n = (MKL_INT)size; \
+   lda = lhsStride; \
+   incx = 1; \
+   incy = resIncr; \
+\
+/* Set uplo, trans and diag*/ \
+   trans = 'N'; \
+   uplo = IsLower ? 'L' : 'U'; \
+   diag = IsUnitDiag ? 'U' : 'N'; \
+\
+/* call ?TRMV*/ \
+   MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
+\
+/* Add op(a_tr)rhs into res*/ \
+   MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
+/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
+   if (size<(std::max)(rows,cols)) { \
+     typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
+     if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+     x = x_tmp.data(); \
+     if (size<rows) { \
+       y = _res + size*resIncr; \
+       a = _lhs + size; \
+       m = rows-size; \
+       n = size; \
+     } \
+     else { \
+       x += size; \
+       y = _res; \
+       a = _lhs + size*lda; \
+       m = size; \
+       n = cols-size; \
+     } \
+     MKLPREFIX##gemv(&trans, &m, &n, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
+   } \
+  } \
+};
+
+EIGEN_MKL_TRMV_CM(double, double, d, d)
+EIGEN_MKL_TRMV_CM(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_TRMV_CM(float, float, f, s)
+EIGEN_MKL_TRMV_CM(scomplex, MKL_Complex8, cf, c)
+
+// implements row-major: res += alpha * op(triangular) * vector
+#define EIGEN_MKL_TRMV_RM(EIGTYPE, MKLTYPE, EIGPREFIX, MKLPREFIX) \
+template<typename Index, int Mode, bool ConjLhs, bool ConjRhs> \
+struct triangular_matrix_vector_product_trmv<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor> { \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    SetDiag = (Mode&(ZeroDiag|UnitDiag)) ? 0 : 1, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    LowUp = IsLower ? Lower : Upper \
+  }; \
+ static EIGEN_DONT_INLINE void run(Index _rows, Index _cols, const EIGTYPE* _lhs, Index lhsStride, \
+                             const EIGTYPE* _rhs, Index rhsIncr, EIGTYPE* _res, Index resIncr, EIGTYPE alpha, level3_blocking<EIGTYPE,EIGTYPE>& blocking) \
+ { \
+   if (IsZeroDiag) { \
+     triangular_matrix_vector_product<Index,Mode,EIGTYPE,ConjLhs,EIGTYPE,ConjRhs,RowMajor,BuiltIn>::run( \
+       _rows, _cols, _lhs, lhsStride, _rhs, rhsIncr, _res, resIncr, alpha, blocking); \
+     return; \
+   }\
+   Index size = (std::min)(_rows,_cols); \
+   Index rows = IsLower ? _rows : size; \
+   Index cols = IsLower ? size : _cols; \
+\
+   typedef VectorX##EIGPREFIX VectorRhs; \
+   EIGTYPE *x, *y;\
+\
+/* Set x*/ \
+   Map<const VectorRhs, 0, InnerStride<> > rhs(_rhs,cols,InnerStride<>(rhsIncr)); \
+   VectorRhs x_tmp; \
+   if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+   x = x_tmp.data(); \
+\
+/* Square part handling */\
+\
+   char trans, uplo, diag; \
+   MKL_INT m, n, lda, incx, incy; \
+   EIGTYPE const *a; \
+   MKLTYPE alpha_, beta_; \
+   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(alpha_, alpha); \
+   assign_scalar_eig2mkl<MKLTYPE, EIGTYPE>(beta_, EIGTYPE(1)); \
+\
+/* Set m, n */ \
+   n = (MKL_INT)size; \
+   lda = lhsStride; \
+   incx = 1; \
+   incy = resIncr; \
+\
+/* Set uplo, trans and diag*/ \
+   trans = ConjLhs ? 'C' : 'T'; \
+   uplo = IsLower ? 'U' : 'L'; \
+   diag = IsUnitDiag ? 'U' : 'N'; \
+\
+/* call ?TRMV*/ \
+   MKLPREFIX##trmv(&uplo, &trans, &diag, &n, (const MKLTYPE*)_lhs, &lda, (MKLTYPE*)x, &incx); \
+\
+/* Add op(a_tr)rhs into res*/ \
+   MKLPREFIX##axpy(&n, &alpha_,(const MKLTYPE*)x, &incx, (MKLTYPE*)_res, &incy); \
+/* Non-square case - doesn't fit to MKL ?TRMV. Fall to default triangular product*/ \
+   if (size<(std::max)(rows,cols)) { \
+     typedef Matrix<EIGTYPE, Dynamic, Dynamic> MatrixLhs; \
+     if (ConjRhs) x_tmp = rhs.conjugate(); else x_tmp = rhs; \
+     x = x_tmp.data(); \
+     if (size<rows) { \
+       y = _res + size*resIncr; \
+       a = _lhs + size*lda; \
+       m = rows-size; \
+       n = size; \
+     } \
+     else { \
+       x += size; \
+       y = _res; \
+       a = _lhs + size; \
+       m = size; \
+       n = cols-size; \
+     } \
+     MKLPREFIX##gemv(&trans, &n, &m, &alpha_, (const MKLTYPE*)a, &lda, (const MKLTYPE*)x, &incx, &beta_, (MKLTYPE*)y, &incy); \
+   } \
+  } \
+};
+
+EIGEN_MKL_TRMV_RM(double, double, d, d)
+EIGEN_MKL_TRMV_RM(dcomplex, MKL_Complex16, cd, z)
+EIGEN_MKL_TRMV_RM(float, float, f, s)
+EIGEN_MKL_TRMV_RM(scomplex, MKL_Complex8, cf, c)
+
+} // end namespase internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TRIANGULAR_MATRIX_VECTOR_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/TriangularSolverMatrix.h b/extern/Eigen3/Eigen/src/Core/products/TriangularSolverMatrix.h
index 4dced6b0eb9..a49ea318345 100644
--- a/extern/Eigen3/Eigen/src/Core/products/TriangularSolverMatrix.h
+++ b/extern/Eigen3/Eigen/src/Core/products/TriangularSolverMatrix.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULAR_SOLVER_MATRIX_H
 #define EIGEN_TRIANGULAR_SOLVER_MATRIX_H
 
+namespace Eigen { 
+
 namespace internal {
 
 // if the rhs is row major, let's transpose the product
@@ -34,14 +21,15 @@ struct triangular_solve_matrix<Scalar,Index,Side,Mode,Conjugate,TriStorageOrder,
   static EIGEN_DONT_INLINE void run(
     Index size, Index cols,
     const Scalar*  tri, Index triStride,
-    Scalar* _other, Index otherStride)
+    Scalar* _other, Index otherStride,
+    level3_blocking<Scalar,Scalar>& blocking)
   {
     triangular_solve_matrix<
       Scalar, Index, Side==OnTheLeft?OnTheRight:OnTheLeft,
       (Mode&UnitDiag) | ((Mode&Upper) ? Lower : Upper),
       NumTraits<Scalar>::IsComplex && Conjugate,
       TriStorageOrder==RowMajor ? ColMajor : RowMajor, ColMajor>
-      ::run(size, cols, tri, triStride, _other, otherStride);
+      ::run(size, cols, tri, triStride, _other, otherStride, blocking);
   }
 };
 
@@ -53,7 +41,8 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
   static EIGEN_DONT_INLINE void run(
     Index size, Index otherSize,
     const Scalar* _tri, Index triStride,
-    Scalar* _other, Index otherStride)
+    Scalar* _other, Index otherStride,
+    level3_blocking<Scalar,Scalar>& blocking)
   {
     Index cols = otherSize;
     const_blas_data_mapper<Scalar, Index, TriStorageOrder> tri(_tri,triStride);
@@ -65,22 +54,29 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
       IsLower = (Mode&Lower) == Lower
     };
 
-    Index kc = size; // cache block size along the K direction
-    Index mc = size;  // cache block size along the M direction
-    Index nc = cols;  // cache block size along the N direction
-    computeProductBlockingSizes<Scalar,Scalar,4>(kc, mc, nc);
+    Index kc = blocking.kc();                   // cache block size along the K direction
+    Index mc = (std::min)(size,blocking.mc());  // cache block size along the M direction
 
+    std::size_t sizeA = kc*mc;
+    std::size_t sizeB = kc*cols;
     std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    std::size_t sizeB = sizeW + kc*cols;
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
-    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);
-    Scalar* blockB = allocatedBlockB + sizeW;
+
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
     conj_if<Conjugate> conj;
     gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, Conjugate, false> gebp_kernel;
     gemm_pack_lhs<Scalar, Index, Traits::mr, Traits::LhsProgress, TriStorageOrder> pack_lhs;
     gemm_pack_rhs<Scalar, Index, Traits::nr, ColMajor, false, true> pack_rhs;
 
+    // the goal here is to subdivise the Rhs panels such that we keep some cache
+    // coherence when accessing the rhs elements
+    std::ptrdiff_t l1, l2;
+    manage_caching_sizes(GetAction, &l1, &l2);
+    Index subcols = cols>0 ? l2/(4 * sizeof(Scalar) * otherStride) : 0;
+    subcols = std::max<Index>((subcols/Traits::nr)*Traits::nr, Traits::nr);
+
     for(Index k2=IsLower ? 0 : size;
         IsLower ? k2<size : k2>0;
         IsLower ? k2+=kc : k2-=kc)
@@ -92,16 +88,18 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
       // A11 (the triangular part) and A21 the remaining rectangular part.
       // Then the high level algorithm is:
       //  - B = R1                    => general block copy (done during the next step)
-      //  - R1 = L1^-1 B              => tricky part
+      //  - R1 = A11^-1 B             => tricky part
       //  - update B from the new R1  => actually this has to be performed continuously during the above step
-      //  - R2 = L2 * B               => GEPP
+      //  - R2 -= A21 * B             => GEPP
 
-      // The tricky part: compute R1 = L1^-1 B while updating B from R1
-      // The idea is to split L1 into multiple small vertical panels.
-      // Each panel can be split into a small triangular part A1 which is processed without optimization,
-      // and the remaining small part A2 which is processed using gebp with appropriate block strides
+      // The tricky part: compute R1 = A11^-1 B while updating B from R1
+      // The idea is to split A11 into multiple small vertical panels.
+      // Each panel can be split into a small triangular part T1k which is processed without optimization,
+      // and the remaining small part T2k which is processed using gebp with appropriate block strides
+      for(Index j2=0; j2<cols; j2+=subcols)
       {
-        // for each small vertical panels of lhs
+        Index actual_cols = (std::min)(cols-j2,subcols);
+        // for each small vertical panels [T1k^T, T2k^T]^T of lhs
         for (Index k1=0; k1<actual_kc; k1+=SmallPanelWidth)
         {
           Index actualPanelWidth = std::min<Index>(actual_kc-k1, SmallPanelWidth);
@@ -114,11 +112,11 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
             Index rs = actualPanelWidth - k - 1; // remaining size
 
             Scalar a = (Mode & UnitDiag) ? Scalar(1) : Scalar(1)/conj(tri(i,i));
-            for (Index j=0; j<cols; ++j)
+            for (Index j=j2; j<j2+actual_cols; ++j)
             {
               if (TriStorageOrder==RowMajor)
               {
-                Scalar b = 0;
+                Scalar b(0);
                 const Scalar* l = &tri(i,s);
                 Scalar* r = &other(s,j);
                 for (Index i3=0; i3<k; ++i3)
@@ -143,7 +141,7 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
           Index blockBOffset = IsLower ? k1 : lengthTarget;
 
           // update the respective rows of B from other
-          pack_rhs(blockB, _other+startBlock, otherStride, actualPanelWidth, cols, actual_kc, blockBOffset);
+          pack_rhs(blockB+actual_kc*j2, &other(startBlock,j2), otherStride, actualPanelWidth, actual_cols, actual_kc, blockBOffset);
 
           // GEBP
           if (lengthTarget>0)
@@ -152,13 +150,13 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
 
             pack_lhs(blockA, &tri(startTarget,startBlock), triStride, actualPanelWidth, lengthTarget);
 
-            gebp_kernel(_other+startTarget, otherStride, blockA, blockB, lengthTarget, actualPanelWidth, cols, Scalar(-1),
-                        actualPanelWidth, actual_kc, 0, blockBOffset);
+            gebp_kernel(&other(startTarget,j2), otherStride, blockA, blockB+actual_kc*j2, lengthTarget, actualPanelWidth, actual_cols, Scalar(-1),
+                        actualPanelWidth, actual_kc, 0, blockBOffset, blockW);
           }
         }
       }
-
-      // R2 = A2 * B => GEPP
+      
+      // R2 -= A21 * B => GEPP
       {
         Index start = IsLower ? k2+kc : 0;
         Index end   = IsLower ? size : k2-kc;
@@ -169,7 +167,7 @@ struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageO
           {
             pack_lhs(blockA, &tri(i2, IsLower ? k2 : k2-kc), triStride, actual_kc, actual_mc);
 
-            gebp_kernel(_other+i2, otherStride, blockA, blockB, actual_mc, actual_kc, cols, Scalar(-1));
+            gebp_kernel(_other+i2, otherStride, blockA, blockB, actual_mc, actual_kc, cols, Scalar(-1), -1, -1, 0, 0, blockW);
           }
         }
       }
@@ -185,7 +183,8 @@ struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorage
   static EIGEN_DONT_INLINE void run(
     Index size, Index otherSize,
     const Scalar* _tri, Index triStride,
-    Scalar* _other, Index otherStride)
+    Scalar* _other, Index otherStride,
+    level3_blocking<Scalar,Scalar>& blocking)
   {
     Index rows = otherSize;
     const_blas_data_mapper<Scalar, Index, TriStorageOrder> rhs(_tri,triStride);
@@ -198,19 +197,16 @@ struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorage
       IsLower = (Mode&Lower) == Lower
     };
 
-//     Index kc = std::min<Index>(Traits::Max_kc/4,size); // cache block size along the K direction
-//     Index mc = std::min<Index>(Traits::Max_mc,size);   // cache block size along the M direction
-    // check that !!!!
-    Index kc = size; // cache block size along the K direction
-    Index mc = size;  // cache block size along the M direction
-    Index nc = rows;  // cache block size along the N direction
-    computeProductBlockingSizes<Scalar,Scalar,4>(kc, mc, nc);
+    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
 
+    std::size_t sizeA = kc*mc;
+    std::size_t sizeB = kc*size;
     std::size_t sizeW = kc*Traits::WorkSpaceFactor;
-    std::size_t sizeB = sizeW + kc*size;
-    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, kc*mc, 0);
-    ei_declare_aligned_stack_constructed_variable(Scalar, allocatedBlockB, sizeB, 0);
-    Scalar* blockB = allocatedBlockB + sizeW;
+
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockA, sizeA, blocking.blockA());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockB, sizeB, blocking.blockB());
+    ei_declare_aligned_stack_constructed_variable(Scalar, blockW, sizeW, blocking.blockW());
 
     conj_if<Conjugate> conj;
     gebp_kernel<Scalar,Scalar, Index, Traits::mr, Traits::nr, false, Conjugate> gebp_kernel;
@@ -277,7 +273,7 @@ struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorage
                           Scalar(-1),
                           actual_kc, actual_kc, // strides
                           panelOffset, panelOffset, // offsets
-                          allocatedBlockB);  // workspace
+                          blockW);  // workspace
             }
 
             // unblocked triangular solve
@@ -308,7 +304,7 @@ struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorage
         if (rs>0)
           gebp_kernel(_other+i2+startPanel*otherStride, otherStride, blockA, geb,
                       actual_mc, actual_kc, rs, Scalar(-1),
-                      -1, -1, 0, 0, allocatedBlockB);
+                      -1, -1, 0, 0, blockW);
       }
     }
   }
@@ -316,4 +312,6 @@ struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorage
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRIANGULAR_SOLVER_MATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h b/extern/Eigen3/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h
new file mode 100644
index 00000000000..a4f508b2e83
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h
@@ -0,0 +1,155 @@
+/*
+ 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
+ *   Triangular matrix * matrix product functionality based on ?TRMM.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_TRIANGULAR_SOLVER_MATRIX_MKL_H
+#define EIGEN_TRIANGULAR_SOLVER_MATRIX_MKL_H
+
+namespace Eigen {
+
+namespace internal {
+
+// implements LeftSide op(triangular)^-1 * general
+#define EIGEN_MKL_TRSM_L(EIGTYPE, MKLTYPE, MKLPREFIX) \
+template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
+struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
+  }; \
+  static EIGEN_DONT_INLINE void run( \
+      Index size, Index otherSize, \
+      const EIGTYPE* _tri, Index triStride, \
+      EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
+  { \
+   MKL_INT m = size, n = otherSize, lda, ldb; \
+   char side = 'L', uplo, diag='N', transa; \
+   /* Set alpha_ */ \
+   MKLTYPE alpha; \
+   EIGTYPE myone(1); \
+   assign_scalar_eig2mkl(alpha, myone); \
+   ldb = otherStride;\
+\
+   const EIGTYPE *a; \
+/* Set trans */ \
+   transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, TriStorageOrder> MatrixTri; \
+   Map<const MatrixTri, 0, OuterStride<> > tri(_tri,size,size,OuterStride<>(triStride)); \
+   MatrixTri a_tmp; \
+\
+   if (conjA) { \
+     a_tmp = tri.conjugate(); \
+     a = a_tmp.data(); \
+     lda = a_tmp.outerStride(); \
+   } else { \
+     a = _tri; \
+     lda = triStride; \
+   } \
+   if (IsUnitDiag) diag='U'; \
+/* call ?trsm*/ \
+   MKLPREFIX##trsm(&side, &uplo, &transa, &diag, &m, &n, &alpha, (const MKLTYPE*)a, &lda, (MKLTYPE*)_other, &ldb); \
+ } \
+};
+
+EIGEN_MKL_TRSM_L(double, double, d)
+EIGEN_MKL_TRSM_L(dcomplex, MKL_Complex16, z)
+EIGEN_MKL_TRSM_L(float, float, s)
+EIGEN_MKL_TRSM_L(scomplex, MKL_Complex8, c)
+
+
+// implements RightSide general * op(triangular)^-1
+#define EIGEN_MKL_TRSM_R(EIGTYPE, MKLTYPE, MKLPREFIX) \
+template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
+struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor> \
+{ \
+  enum { \
+    IsLower = (Mode&Lower) == Lower, \
+    IsUnitDiag  = (Mode&UnitDiag) ? 1 : 0, \
+    IsZeroDiag  = (Mode&ZeroDiag) ? 1 : 0, \
+    conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
+  }; \
+  static EIGEN_DONT_INLINE void run( \
+      Index size, Index otherSize, \
+      const EIGTYPE* _tri, Index triStride, \
+      EIGTYPE* _other, Index otherStride, level3_blocking<EIGTYPE,EIGTYPE>& /*blocking*/) \
+  { \
+   MKL_INT m = otherSize, n = size, lda, ldb; \
+   char side = 'R', uplo, diag='N', transa; \
+   /* Set alpha_ */ \
+   MKLTYPE alpha; \
+   EIGTYPE myone(1); \
+   assign_scalar_eig2mkl(alpha, myone); \
+   ldb = otherStride;\
+\
+   const EIGTYPE *a; \
+/* Set trans */ \
+   transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
+/* Set uplo */ \
+   uplo = IsLower ? 'L' : 'U'; \
+   if (TriStorageOrder==RowMajor) uplo = (uplo == 'L') ? 'U' : 'L'; \
+/* Set a, lda */ \
+   typedef Matrix<EIGTYPE, Dynamic, Dynamic, TriStorageOrder> MatrixTri; \
+   Map<const MatrixTri, 0, OuterStride<> > tri(_tri,size,size,OuterStride<>(triStride)); \
+   MatrixTri a_tmp; \
+\
+   if (conjA) { \
+     a_tmp = tri.conjugate(); \
+     a = a_tmp.data(); \
+     lda = a_tmp.outerStride(); \
+   } else { \
+     a = _tri; \
+     lda = triStride; \
+   } \
+   if (IsUnitDiag) diag='U'; \
+/* call ?trsm*/ \
+   MKLPREFIX##trsm(&side, &uplo, &transa, &diag, &m, &n, &alpha, (const MKLTYPE*)a, &lda, (MKLTYPE*)_other, &ldb); \
+   /*std::cout << "TRMS_L specialization!\n";*/ \
+ } \
+};
+
+EIGEN_MKL_TRSM_R(double, double, d)
+EIGEN_MKL_TRSM_R(dcomplex, MKL_Complex16, z)
+EIGEN_MKL_TRSM_R(float, float, s)
+EIGEN_MKL_TRSM_R(scomplex, MKL_Complex8, c)
+
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_TRIANGULAR_SOLVER_MATRIX_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Core/products/TriangularSolverVector.h b/extern/Eigen3/Eigen/src/Core/products/TriangularSolverVector.h
index 639d4a5b476..ce4d1008801 100644
--- a/extern/Eigen3/Eigen/src/Core/products/TriangularSolverVector.h
+++ b/extern/Eigen3/Eigen/src/Core/products/TriangularSolverVector.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULAR_SOLVER_VECTOR_H
 #define EIGEN_TRIANGULAR_SOLVER_VECTOR_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate, int StorageOrder>
@@ -147,4 +134,6 @@ struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Con
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRIANGULAR_SOLVER_VECTOR_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/BlasUtil.h b/extern/Eigen3/Eigen/src/Core/util/BlasUtil.h
index f1d93d2f8b9..91496651c82 100644
--- a/extern/Eigen3/Eigen/src/Core/util/BlasUtil.h
+++ b/extern/Eigen3/Eigen/src/Core/util/BlasUtil.h
@@ -3,24 +3,9 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BLASUTIL_H
 #define EIGEN_BLASUTIL_H
@@ -28,6 +13,8 @@
 // This file contains many lightweight helper classes used to
 // implement and control fast level 2 and level 3 BLAS-like routines.
 
+namespace Eigen {
+
 namespace internal {
 
 // forward declarations
@@ -47,7 +34,7 @@ template<
   int ResStorageOrder>
 struct general_matrix_matrix_product;
 
-template<typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs>
+template<typename Index, typename LhsScalar, int LhsStorageOrder, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version=Specialized>
 struct general_matrix_vector_product;
 
 
@@ -56,11 +43,15 @@ template<bool Conjugate> struct conj_if;
 template<> struct conj_if<true> {
   template<typename T>
   inline T operator()(const T& x) { return conj(x); }
+  template<typename T>
+  inline T pconj(const T& x) { return internal::pconj(x); }
 };
 
 template<> struct conj_if<false> {
   template<typename T>
   inline const T& operator()(const T& x) { return x; }
+  template<typename T>
+  inline const T& pconj(const T& x) { return x; }
 };
 
 template<typename Scalar> struct conj_helper<Scalar,Scalar,false,false>
@@ -118,11 +109,11 @@ template<typename RealScalar,bool Conj> struct conj_helper<RealScalar, std::comp
 };
 
 template<typename From,typename To> struct get_factor {
-  EIGEN_STRONG_INLINE static To run(const From& x) { return x; }
+  static EIGEN_STRONG_INLINE To run(const From& x) { return x; }
 };
 
 template<typename Scalar> struct get_factor<Scalar,typename NumTraits<Scalar>::Real> {
-  EIGEN_STRONG_INLINE static typename NumTraits<Scalar>::Real run(const Scalar& x) { return real(x); }
+  static EIGEN_STRONG_INLINE typename NumTraits<Scalar>::Real run(const Scalar& x) { return real(x); }
 };
 
 // Lightweight helper class to access matrix coefficients.
@@ -175,7 +166,7 @@ template<typename XprType> struct blas_traits
     ExtractType,
     typename _ExtractType::PlainObject
     >::type DirectLinearAccessType;
-  static inline const ExtractType extract(const XprType& x) { return x; }
+  static inline ExtractType extract(const XprType& x) { return x; }
   static inline const Scalar extractScalarFactor(const XprType&) { return Scalar(1); }
 };
 
@@ -192,7 +183,7 @@ struct blas_traits<CwiseUnaryOp<scalar_conjugate_op<Scalar>, NestedXpr> >
     IsComplex = NumTraits<Scalar>::IsComplex,
     NeedToConjugate = Base::NeedToConjugate ? 0 : IsComplex
   };
-  static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
+  static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
   static inline Scalar extractScalarFactor(const XprType& x) { return conj(Base::extractScalarFactor(x.nestedExpression())); }
 };
 
@@ -204,7 +195,7 @@ struct blas_traits<CwiseUnaryOp<scalar_multiple_op<Scalar>, NestedXpr> >
   typedef blas_traits<NestedXpr> Base;
   typedef CwiseUnaryOp<scalar_multiple_op<Scalar>, NestedXpr> XprType;
   typedef typename Base::ExtractType ExtractType;
-  static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
+  static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
   static inline Scalar extractScalarFactor(const XprType& x)
   { return x.functor().m_other * Base::extractScalarFactor(x.nestedExpression()); }
 };
@@ -217,7 +208,7 @@ struct blas_traits<CwiseUnaryOp<scalar_opposite_op<Scalar>, NestedXpr> >
   typedef blas_traits<NestedXpr> Base;
   typedef CwiseUnaryOp<scalar_opposite_op<Scalar>, NestedXpr> XprType;
   typedef typename Base::ExtractType ExtractType;
-  static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
+  static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
   static inline Scalar extractScalarFactor(const XprType& x)
   { return - Base::extractScalarFactor(x.nestedExpression()); }
 };
@@ -239,7 +230,7 @@ struct blas_traits<Transpose<NestedXpr> >
   enum {
     IsTransposed = Base::IsTransposed ? 0 : 1
   };
-  static inline const ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
+  static inline ExtractType extract(const XprType& x) { return Base::extract(x.nestedExpression()); }
   static inline Scalar extractScalarFactor(const XprType& x) { return Base::extractScalarFactor(x.nestedExpression()); }
 };
 
@@ -252,7 +243,7 @@ template<typename T, bool HasUsableDirectAccess=blas_traits<T>::HasUsableDirectA
 struct extract_data_selector {
   static const typename T::Scalar* run(const T& m)
   {
-    return const_cast<typename T::Scalar*>(&blas_traits<T>::extract(m).coeffRef(0,0)); // FIXME this should be .data()
+    return blas_traits<T>::extract(m).data();
   }
 };
 
@@ -268,4 +259,6 @@ template<typename T> const typename T::Scalar* extract_data(const T& m)
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_BLASUTIL_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/Constants.h b/extern/Eigen3/Eigen/src/Core/util/Constants.h
index c3dd3a09d00..3fd45e84f8e 100644
--- a/extern/Eigen3/Eigen/src/Core/util/Constants.h
+++ b/extern/Eigen3/Eigen/src/Core/util/Constants.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2007-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CONSTANTS_H
 #define EIGEN_CONSTANTS_H
 
+namespace Eigen {
+
 /** This value means that a quantity is not known at compile-time, and that instead the value is
   * stored in some runtime variable.
   *
@@ -188,7 +175,9 @@ enum {
   /** View matrix as an upper triangular matrix with zeros on the diagonal. */
   StrictlyUpper=ZeroDiag|Upper,
   /** Used in BandMatrix and SelfAdjointView to indicate that the matrix is self-adjoint. */
-  SelfAdjoint=0x10
+  SelfAdjoint=0x10,
+  /** Used to support symmetric, non-selfadjoint, complex matrices. */
+  Symmetric=0x20
 };
 
 /** \ingroup enums
@@ -200,8 +189,6 @@ enum {
   Aligned=1 
 };
 
-enum { ConditionalJumpCost = 5 };
-
 /** \ingroup enums
  * Enum used by DenseBase::corner() in Eigen2 compatibility mode. */
 // FIXME after the corner() API change, this was not needed anymore, except by AlignedBox
@@ -223,8 +210,6 @@ enum DirectionType {
   BothDirections 
 };
 
-enum ProductEvaluationMode { NormalProduct, CacheFriendlyProduct };
-
 /** \internal \ingroup enums
   * Enum to specify how to traverse the entries of a matrix. */
 enum {
@@ -257,6 +242,13 @@ enum {
   CompleteUnrolling
 };
 
+/** \internal \ingroup enums
+  * Enum to specify whether to use the default (built-in) implementation or the specialization. */
+enum {
+  Specialized,
+  BuiltIn
+};
+
 /** \ingroup enums
   * Enum containing possible values for the \p _Options template parameter of
   * Matrix, Array and BandMatrix. */
@@ -280,26 +272,21 @@ enum {
   OnTheRight = 2  
 };
 
-/* the following could as well be written:
- *   enum NoChange_t { NoChange };
- * but it feels dangerous to disambiguate overloaded functions on enum/integer types.
- * If on some platform it is really impossible to get rid of "unused variable" warnings, then
- * we can always come back to that solution.
+/* the following used to be written as:
+ *
+ *   struct NoChange_t {};
+ *   namespace {
+ *     EIGEN_UNUSED NoChange_t NoChange;
+ *   }
+ *
+ * on the ground that it feels dangerous to disambiguate overloaded functions on enum/integer types.  
+ * However, this leads to "variable declared but never referenced" warnings on Intel Composer XE,
+ * and we do not know how to get rid of them (bug 450).
  */
-struct NoChange_t {};
-namespace {
-  EIGEN_UNUSED NoChange_t NoChange;
-}
-
-struct Sequential_t {};
-namespace {
-  EIGEN_UNUSED Sequential_t Sequential;
-}
 
-struct Default_t {};
-namespace {
-  EIGEN_UNUSED Default_t Default;
-}
+enum NoChange_t   { NoChange };
+enum Sequential_t { Sequential };
+enum Default_t    { Default };
 
 /** \internal \ingroup enums
   * Used in AmbiVector. */
@@ -375,7 +362,7 @@ enum QRPreconditioners {
 #error The preprocessor symbol 'Success' is defined, possibly by the X11 header file X.h
 #endif
 
-/** \ingroups enums
+/** \ingroup enums
   * Enum for reporting the status of a computation. */
 enum ComputationInfo {
   /** Computation was successful. */
@@ -383,7 +370,10 @@ enum ComputationInfo {
   /** The provided data did not satisfy the prerequisites. */
   NumericalIssue = 1, 
   /** Iterative procedure did not converge. */
-  NoConvergence = 2
+  NoConvergence = 2,
+  /** The inputs are invalid, or the algorithm has been improperly called.
+    * When assertions are enabled, such errors trigger an assert. */
+  InvalidInput = 3
 };
 
 /** \ingroup enums
@@ -436,4 +426,6 @@ struct MatrixXpr {};
 /** The type used to identify an array expression */
 struct ArrayXpr {};
 
+} // end namespace Eigen
+
 #endif // EIGEN_CONSTANTS_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/DisableStupidWarnings.h b/extern/Eigen3/Eigen/src/Core/util/DisableStupidWarnings.h
index 00730524b26..6a0bf0629c5 100644
--- a/extern/Eigen3/Eigen/src/Core/util/DisableStupidWarnings.h
+++ b/extern/Eigen3/Eigen/src/Core/util/DisableStupidWarnings.h
@@ -21,15 +21,13 @@
 #elif defined __INTEL_COMPILER
   // 2196 - routine is both "inline" and "noinline" ("noinline" assumed)
   //        ICC 12 generates this warning even without any inline keyword, when defining class methods 'inline' i.e. inside of class body
-  // 2536 - type qualifiers are meaningless here
-  //        ICC 12 generates this warning when a function return type is const qualified, even if that type is a template-parameter-dependent
   //        typedef that may be a reference type.
   // 279  - controlling expression is constant
   //        ICC 12 generates this warning on assert(constant_expression_depending_on_template_params) and frankly this is a legitimate use case.
   #ifndef EIGEN_PERMANENTLY_DISABLE_STUPID_WARNINGS
     #pragma warning push
   #endif
-  #pragma warning disable 2196 2536 279
+  #pragma warning disable 2196 279
 #elif defined __clang__
   // -Wconstant-logical-operand - warning: use of logical && with constant operand; switch to bitwise & or remove constant
   //     this is really a stupid warning as it warns on compile-time expressions involving enums
diff --git a/extern/Eigen3/Eigen/src/Core/util/ForwardDeclarations.h b/extern/Eigen3/Eigen/src/Core/util/ForwardDeclarations.h
index 7fbccf98c2b..bcdfe3914e3 100644
--- a/extern/Eigen3/Eigen/src/Core/util/ForwardDeclarations.h
+++ b/extern/Eigen3/Eigen/src/Core/util/ForwardDeclarations.h
@@ -4,28 +4,14 @@
 // Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FORWARDDECLARATIONS_H
 #define EIGEN_FORWARDDECLARATIONS_H
 
+namespace Eigen {
 namespace internal {
 
 template<typename T> struct traits;
@@ -133,6 +119,7 @@ template<typename ExpressionType> class WithFormat;
 template<typename MatrixType> struct CommaInitializer;
 template<typename Derived> class ReturnByValue;
 template<typename ExpressionType> class ArrayWrapper;
+template<typename ExpressionType> class MatrixWrapper;
 
 namespace internal {
 template<typename DecompositionType, typename Rhs> struct solve_retval_base;
@@ -282,6 +269,8 @@ template<typename MatrixType,int Direction> class Homogeneous;
 // MatrixFunctions module
 template<typename Derived> struct MatrixExponentialReturnValue;
 template<typename Derived> class MatrixFunctionReturnValue;
+template<typename Derived> class MatrixSquareRootReturnValue;
+template<typename Derived> class MatrixLogarithmReturnValue;
 
 namespace internal {
 template <typename Scalar>
@@ -304,4 +293,6 @@ template<typename MatrixType, unsigned int Mode> struct eigen2_part_return_type;
 }
 #endif
 
+} // end namespace Eigen
+
 #endif // EIGEN_FORWARDDECLARATIONS_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/MKL_support.h b/extern/Eigen3/Eigen/src/Core/util/MKL_support.h
new file mode 100644
index 00000000000..1e6e355d626
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/util/MKL_support.h
@@ -0,0 +1,109 @@
+/*
+ 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
+ *   Include file with common MKL declarations
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_MKL_SUPPORT_H
+#define EIGEN_MKL_SUPPORT_H
+
+#ifdef EIGEN_USE_MKL_ALL
+  #ifndef EIGEN_USE_BLAS
+    #define EIGEN_USE_BLAS
+  #endif
+  #ifndef EIGEN_USE_LAPACKE
+    #define EIGEN_USE_LAPACKE
+  #endif
+  #ifndef EIGEN_USE_MKL_VML
+    #define EIGEN_USE_MKL_VML
+  #endif
+#endif
+
+#ifdef EIGEN_USE_LAPACKE_STRICT
+  #define EIGEN_USE_LAPACKE
+#endif
+
+#if defined(EIGEN_USE_BLAS) || defined(EIGEN_USE_LAPACKE) || defined(EIGEN_USE_MKL_VML)
+  #define EIGEN_USE_MKL
+#endif
+
+#if defined EIGEN_USE_MKL
+
+#include <mkl.h>
+#include <mkl_lapacke.h>
+#define EIGEN_MKL_VML_THRESHOLD 128
+
+namespace Eigen {
+
+typedef std::complex<double> dcomplex;
+typedef std::complex<float>  scomplex;
+
+namespace internal {
+
+template<typename MKLType, typename EigenType>
+static inline void assign_scalar_eig2mkl(MKLType& mklScalar, const EigenType& eigenScalar) {
+  mklScalar=eigenScalar;
+}
+
+template<typename MKLType, typename EigenType>
+static inline void assign_conj_scalar_eig2mkl(MKLType& mklScalar, const EigenType& eigenScalar) {
+  mklScalar=eigenScalar;
+}
+
+template <>
+inline void assign_scalar_eig2mkl<MKL_Complex16,dcomplex>(MKL_Complex16& mklScalar, const dcomplex& eigenScalar) {
+  mklScalar.real=eigenScalar.real();
+  mklScalar.imag=eigenScalar.imag();
+}
+
+template <>
+inline void assign_scalar_eig2mkl<MKL_Complex8,scomplex>(MKL_Complex8& mklScalar, const scomplex& eigenScalar) {
+  mklScalar.real=eigenScalar.real();
+  mklScalar.imag=eigenScalar.imag();
+}
+
+template <>
+inline void assign_conj_scalar_eig2mkl<MKL_Complex16,dcomplex>(MKL_Complex16& mklScalar, const dcomplex& eigenScalar) {
+  mklScalar.real=eigenScalar.real();
+  mklScalar.imag=-eigenScalar.imag();
+}
+
+template <>
+inline void assign_conj_scalar_eig2mkl<MKL_Complex8,scomplex>(MKL_Complex8& mklScalar, const scomplex& eigenScalar) {
+  mklScalar.real=eigenScalar.real();
+  mklScalar.imag=-eigenScalar.imag();
+}
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif
+
+#endif // EIGEN_MKL_SUPPORT_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/Macros.h b/extern/Eigen3/Eigen/src/Core/util/Macros.h
index b7c2b79af92..d973a68372f 100644
--- a/extern/Eigen3/Eigen/src/Core/util/Macros.h
+++ b/extern/Eigen3/Eigen/src/Core/util/Macros.h
@@ -1,35 +1,19 @@
-
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MACROS_H
 #define EIGEN_MACROS_H
 
 #define EIGEN_WORLD_VERSION 3
-#define EIGEN_MAJOR_VERSION 0
-#define EIGEN_MINOR_VERSION 5
+#define EIGEN_MAJOR_VERSION 1
+#define EIGEN_MINOR_VERSION 1
 
 #define EIGEN_VERSION_AT_LEAST(x,y,z) (EIGEN_WORLD_VERSION>x || (EIGEN_WORLD_VERSION>=x && \
                                       (EIGEN_MAJOR_VERSION>y || (EIGEN_MAJOR_VERSION>=y && \
@@ -235,12 +219,16 @@
 #define EIGEN_ONLY_USED_FOR_DEBUG(x)
 #endif
 
-#if (defined __GNUC__)
-#define EIGEN_DEPRECATED __attribute__((deprecated))
-#elif (defined _MSC_VER)
-#define EIGEN_DEPRECATED __declspec(deprecated)
+#ifndef EIGEN_NO_DEPRECATED_WARNING
+  #if (defined __GNUC__)
+    #define EIGEN_DEPRECATED __attribute__((deprecated))
+  #elif (defined _MSC_VER)
+    #define EIGEN_DEPRECATED __declspec(deprecated)
+  #else
+    #define EIGEN_DEPRECATED
+  #endif
 #else
-#define EIGEN_DEPRECATED
+  #define EIGEN_DEPRECATED
 #endif
 
 #if (defined __GNUC__)
@@ -252,7 +240,7 @@
 // Suppresses 'unused variable' warnings.
 #define EIGEN_UNUSED_VARIABLE(var) (void)var;
 
-#if (defined __GNUC__)
+#if !defined(EIGEN_ASM_COMMENT) && (defined __GNUC__)
 #define EIGEN_ASM_COMMENT(X)  asm("#" X)
 #else
 #define EIGEN_ASM_COMMENT(X)
@@ -265,7 +253,7 @@
  * If we made alignment depend on whether or not EIGEN_VECTORIZE is defined, it would be impossible to link
  * vectorized and non-vectorized code.
  */
-#if (defined __GNUC__) || (defined __PGI) || (defined __IBMCPP__)
+#if (defined __GNUC__) || (defined __PGI) || (defined __IBMCPP__) || (defined __ARMCC_VERSION)
   #define EIGEN_ALIGN_TO_BOUNDARY(n) __attribute__((aligned(n)))
 #elif (defined _MSC_VER)
   #define EIGEN_ALIGN_TO_BOUNDARY(n) __declspec(align(n))
diff --git a/extern/Eigen3/Eigen/src/Core/util/Memory.h b/extern/Eigen3/Eigen/src/Core/util/Memory.h
index 023716dc9e0..6e06ace44a0 100644
--- a/extern/Eigen3/Eigen/src/Core/util/Memory.h
+++ b/extern/Eigen3/Eigen/src/Core/util/Memory.h
@@ -7,24 +7,9 @@
 // Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
 // Copyright (C) 2010 Thomas Capricelli <orzel@freehackers.org>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 
 /*****************************************************************************
@@ -80,6 +65,8 @@
   #define EIGEN_HAS_MM_MALLOC 0
 #endif
 
+namespace Eigen {
+
 namespace internal {
 
 inline void throw_std_bad_alloc()
@@ -457,7 +444,7 @@ template<typename T, bool Align> inline void conditional_aligned_delete_auto(T *
   * There is also the variant first_aligned(const MatrixBase&) defined in DenseCoeffsBase.h.
   */
 template<typename Scalar, typename Index>
-inline static Index first_aligned(const Scalar* array, Index size)
+static inline Index first_aligned(const Scalar* array, Index size)
 {
   typedef typename packet_traits<Scalar>::type Packet;
   enum { PacketSize = packet_traits<Scalar>::size,
@@ -483,7 +470,26 @@ inline static Index first_aligned(const Scalar* array, Index size)
   }
 }
 
-} // end namespace internal
+
+// std::copy is much slower than memcpy, so let's introduce a smart_copy which
+// use memcpy on trivial types, i.e., on types that does not require an initialization ctor.
+template<typename T, bool UseMemcpy> struct smart_copy_helper;
+
+template<typename T> void smart_copy(const T* start, const T* end, T* target)
+{
+  smart_copy_helper<T,!NumTraits<T>::RequireInitialization>::run(start, end, target);
+}
+
+template<typename T> struct smart_copy_helper<T,true> {
+  static inline void run(const T* start, const T* end, T* target)
+  { memcpy(target, start, std::ptrdiff_t(end)-std::ptrdiff_t(start)); }
+};
+
+template<typename T> struct smart_copy_helper<T,false> {
+  static inline void run(const T* start, const T* end, T* target)
+  { std::copy(start, end, target); }
+};
+
 
 /*****************************************************************************
 *** Implementation of runtime stack allocation (falling back to malloc)    ***
@@ -499,8 +505,6 @@ inline static Index first_aligned(const Scalar* array, Index size)
   #endif
 #endif
 
-namespace internal {
-
 // This helper class construct the allocated memory, and takes care of destructing and freeing the handled data
 // at destruction time. In practice this helper class is mainly useful to avoid memory leak in case of exceptions.
 template<typename T> class aligned_stack_memory_handler
@@ -531,14 +535,14 @@ template<typename T> class aligned_stack_memory_handler
     bool m_deallocate;
 };
 
-}
+} // end namespace internal
 
 /** \internal
   * Declares, allocates and construct an aligned buffer named NAME of SIZE elements of type TYPE on the stack
   * if SIZE is smaller than EIGEN_STACK_ALLOCATION_LIMIT, and if stack allocation is supported by the platform
   * (currently, this is Linux and Visual Studio only). Otherwise the memory is allocated on the heap.
   * The allocated buffer is automatically deleted when exiting the scope of this declaration.
-  * If BUFFER is non nul, then the declared variable is simply an alias for BUFFER, and no allocation/deletion occurs.
+  * If BUFFER is non null, then the declared variable is simply an alias for BUFFER, and no allocation/deletion occurs.
   * Here is an example:
   * \code
   * {
@@ -619,7 +623,7 @@ template<typename T> class aligned_stack_memory_handler
 
 #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(true)
 #define EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(Scalar,Size) \
-  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(((Size)!=Eigen::Dynamic) && ((sizeof(Scalar)*(Size))%16==0))
+  EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(bool(((Size)!=Eigen::Dynamic) && ((sizeof(Scalar)*(Size))%16==0)))
 
 /****************************************************************************/
 
@@ -667,24 +671,24 @@ public:
         return &value;
     }
 
-    aligned_allocator() throw()
+    aligned_allocator()
     {
     }
 
-    aligned_allocator( const aligned_allocator& ) throw()
+    aligned_allocator( const aligned_allocator& )
     {
     }
 
     template<class U>
-    aligned_allocator( const aligned_allocator<U>& ) throw()
+    aligned_allocator( const aligned_allocator<U>& )
     {
     }
 
-    ~aligned_allocator() throw()
+    ~aligned_allocator()
     {
     }
 
-    size_type max_size() const throw()
+    size_type max_size() const
     {
         return (std::numeric_limits<size_type>::max)();
     }
@@ -701,6 +705,15 @@ public:
         ::new( p ) T( value );
     }
 
+    // Support for c++11
+#if (__cplusplus >= 201103L)
+    template<typename... Args>
+    void  construct(pointer p, Args&&... args)
+    {
+      ::new(p) T(std::forward<Args>(args)...);
+    }
+#endif
+
     void destroy( pointer p )
     {
         p->~T();
@@ -720,19 +733,21 @@ public:
 
 //---------- Cache sizes ----------
 
-#if defined(__GNUC__) && ( defined(__i386__) || defined(__x86_64__) )
-#  if defined(__PIC__) && defined(__i386__)
-     // Case for x86 with PIC
-#    define EIGEN_CPUID(abcd,func,id) \
-       __asm__ __volatile__ ("xchgl %%ebx, %%esi;cpuid; xchgl %%ebx,%%esi": "=a" (abcd[0]), "=S" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id));
-#  else
-     // Case for x86_64 or x86 w/o PIC
-#    define EIGEN_CPUID(abcd,func,id) \
-       __asm__ __volatile__ ("cpuid": "=a" (abcd[0]), "=b" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id) );
-#  endif
-#elif defined(_MSC_VER)
-#  if (_MSC_VER > 1500)
-#    define EIGEN_CPUID(abcd,func,id) __cpuidex((int*)abcd,func,id)
+#if !defined(EIGEN_NO_CPUID)
+#  if defined(__GNUC__) && ( defined(__i386__) || defined(__x86_64__) )
+#    if defined(__PIC__) && defined(__i386__)
+       // Case for x86 with PIC
+#      define EIGEN_CPUID(abcd,func,id) \
+         __asm__ __volatile__ ("xchgl %%ebx, %%esi;cpuid; xchgl %%ebx,%%esi": "=a" (abcd[0]), "=S" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id));
+#    else
+       // Case for x86_64 or x86 w/o PIC
+#      define EIGEN_CPUID(abcd,func,id) \
+         __asm__ __volatile__ ("cpuid": "=a" (abcd[0]), "=b" (abcd[1]), "=c" (abcd[2]), "=d" (abcd[3]) : "a" (func), "c" (id) );
+#    endif
+#  elif defined(_MSC_VER)
+#    if (_MSC_VER > 1500)
+#      define EIGEN_CPUID(abcd,func,id) __cpuidex((int*)abcd,func,id)
+#    endif
 #  endif
 #endif
 
@@ -742,7 +757,7 @@ namespace internal {
 
 inline bool cpuid_is_vendor(int abcd[4], const char* vendor)
 {
-  return abcd[1]==((int*)(vendor))[0] && abcd[3]==((int*)(vendor))[1] && abcd[2]==((int*)(vendor))[2];
+  return abcd[1]==(reinterpret_cast<const int*>(vendor))[0] && abcd[3]==(reinterpret_cast<const int*>(vendor))[1] && abcd[2]==(reinterpret_cast<const int*>(vendor))[2];
 }
 
 inline void queryCacheSizes_intel_direct(int& l1, int& l2, int& l3)
@@ -932,4 +947,6 @@ inline int queryTopLevelCacheSize()
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_MEMORY_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/Meta.h b/extern/Eigen3/Eigen/src/Core/util/Meta.h
index 4518261efef..a5f31164d15 100644
--- a/extern/Eigen3/Eigen/src/Core/util/Meta.h
+++ b/extern/Eigen3/Eigen/src/Core/util/Meta.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_META_H
 #define EIGEN_META_H
 
+namespace Eigen {
+
 namespace internal {
 
 /** \internal
@@ -80,8 +67,6 @@ template<> struct is_arithmetic<signed int>    { enum { value = true }; };
 template<> struct is_arithmetic<unsigned int>  { enum { value = true }; };
 template<> struct is_arithmetic<signed long>   { enum { value = true }; };
 template<> struct is_arithmetic<unsigned long> { enum { value = true }; };
-template<> struct is_arithmetic<signed long long>   { enum { value = true }; };
-template<> struct is_arithmetic<unsigned long long> { enum { value = true }; };
 
 template <typename T> struct add_const { typedef const T type; };
 template <typename T> struct add_const<T&> { typedef T& type; };
@@ -103,6 +88,21 @@ template<bool Condition, typename T> struct enable_if;
 template<typename T> struct enable_if<true,T>
 { typedef T type; };
 
+
+
+/** \internal
+  * A base class do disable default copy ctor and copy assignement operator.
+  */
+class noncopyable
+{
+  noncopyable(const noncopyable&);
+  const noncopyable& operator=(const noncopyable&);
+protected:
+  noncopyable() {}
+  ~noncopyable() {}
+};
+
+
 /** \internal
   * Convenient struct to get the result type of a unary or binary functor.
   *
@@ -226,4 +226,6 @@ template<typename T, int S> struct is_diagonal<DiagonalMatrix<T,S> >
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_META_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/NonMPL2.h b/extern/Eigen3/Eigen/src/Core/util/NonMPL2.h
new file mode 100644
index 00000000000..1af67cf18c7
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Core/util/NonMPL2.h
@@ -0,0 +1,3 @@
+#ifdef EIGEN_MPL2_ONLY
+#error Including non-MPL2 code in EIGEN_MPL2_ONLY mode
+#endif
diff --git a/extern/Eigen3/Eigen/src/Core/util/StaticAssert.h b/extern/Eigen3/Eigen/src/Core/util/StaticAssert.h
index 99c7c9972f0..b46a75b3783 100644
--- a/extern/Eigen3/Eigen/src/Core/util/StaticAssert.h
+++ b/extern/Eigen3/Eigen/src/Core/util/StaticAssert.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STATIC_ASSERT_H
 #define EIGEN_STATIC_ASSERT_H
@@ -48,6 +33,8 @@
 
   #else // not CXX0X
 
+    namespace Eigen {
+
     namespace internal {
 
     template<bool condition>
@@ -70,6 +57,7 @@
         YOU_CALLED_A_DYNAMIC_SIZE_METHOD_ON_A_FIXED_SIZE_MATRIX_OR_VECTOR,
         UNALIGNED_LOAD_AND_STORE_OPERATIONS_UNIMPLEMENTED_ON_ALTIVEC,
         THIS_FUNCTION_IS_NOT_FOR_INTEGER_NUMERIC_TYPES,
+        FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED,
         NUMERIC_TYPE_MUST_BE_REAL,
         COEFFICIENT_WRITE_ACCESS_TO_SELFADJOINT_NOT_SUPPORTED,
         WRITING_TO_TRIANGULAR_PART_WITH_UNIT_DIAGONAL_IS_NOT_SUPPORTED,
@@ -95,12 +83,20 @@
         YOU_PERFORMED_AN_INVALID_TRANSFORMATION_CONVERSION,
         THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY,
         YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT,
-        THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS
+        THIS_METHOD_IS_ONLY_FOR_1x1_EXPRESSIONS,
+        THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL,
+        THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES,
+        YOU_PASSED_A_ROW_VECTOR_BUT_A_COLUMN_VECTOR_WAS_EXPECTED,
+        YOU_PASSED_A_COLUMN_VECTOR_BUT_A_ROW_VECTOR_WAS_EXPECTED,
+        THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE,
+        THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH
       };
     };
 
     } // end namespace internal
 
+    } // end namespace Eigen
+
     // Specialized implementation for MSVC to avoid "conditional
     // expression is constant" warnings.  This implementation doesn't
     // appear to work under GCC, hence the multiple implementations.
@@ -195,4 +191,15 @@
       EIGEN_STATIC_ASSERT(internal::is_lvalue<Derived>::value, \
                           THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY)
 
+#define EIGEN_STATIC_ASSERT_ARRAYXPR(Derived) \
+      EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Derived>::XprKind, ArrayXpr>::value), \
+                          THIS_METHOD_IS_ONLY_FOR_ARRAYS_NOT_MATRICES)
+
+#define EIGEN_STATIC_ASSERT_SAME_XPR_KIND(Derived1, Derived2) \
+      EIGEN_STATIC_ASSERT((internal::is_same<typename internal::traits<Derived1>::XprKind, \
+                                             typename internal::traits<Derived2>::XprKind \
+                                            >::value), \
+                          YOU_CANNOT_MIX_ARRAYS_AND_MATRICES)
+
+
 #endif // EIGEN_STATIC_ASSERT_H
diff --git a/extern/Eigen3/Eigen/src/Core/util/XprHelper.h b/extern/Eigen3/Eigen/src/Core/util/XprHelper.h
index c2078f13786..2a65c7cbfa4 100644
--- a/extern/Eigen3/Eigen/src/Core/util/XprHelper.h
+++ b/extern/Eigen3/Eigen/src/Core/util/XprHelper.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_XPRHELPER_H
 #define EIGEN_XPRHELPER_H
@@ -37,6 +22,8 @@
   #define EIGEN_EMPTY_STRUCT_CTOR(X)
 #endif
 
+namespace Eigen {
+
 typedef EIGEN_DEFAULT_DENSE_INDEX_TYPE DenseIndex;
 
 namespace internal {
@@ -260,30 +247,27 @@ template<typename T> struct plain_matrix_type_row_major
 // we should be able to get rid of this one too
 template<typename T> struct must_nest_by_value { enum { ret = false }; };
 
-template<class T>
-struct is_reference
-{
-  enum { ret = false };
-};
-
-template<class T>
-struct is_reference<T&>
-{
-  enum { ret = true };
-};
-
-/**
-* \internal The reference selector for template expressions. The idea is that we don't
-* need to use references for expressions since they are light weight proxy
-* objects which should generate no copying overhead.
-**/
+/** \internal The reference selector for template expressions. The idea is that we don't
+  * need to use references for expressions since they are light weight proxy
+  * objects which should generate no copying overhead. */
 template <typename T>
 struct ref_selector
 {
   typedef typename conditional<
     bool(traits<T>::Flags & NestByRefBit),
     T const&,
-    T
+    const T
+  >::type type;
+};
+
+/** \internal Adds the const qualifier on the value-type of T2 if and only if T1 is a const type */
+template<typename T1, typename T2>
+struct transfer_constness
+{
+  typedef typename conditional<
+    bool(internal::is_const<T1>::value),
+    typename internal::add_const_on_value_type<T2>::type,
+    T2
   >::type type;
 };
 
@@ -297,6 +281,8 @@ struct ref_selector
   * \param T the type of the expression being nested
   * \param n the number of coefficient accesses in the nested expression for each coefficient access in the bigger expression.
   *
+  * Note that if no evaluation occur, then the constness of T is preserved.
+  *
   * Example. Suppose that a, b, and c are of type Matrix3d. The user forms the expression a*(b+c).
   * b+c is an expression "sum of matrices", which we will denote by S. In order to determine how to nest it,
   * the Product expression uses: nested<S, 3>::ret, which turns out to be Matrix3d because the internal logic of
@@ -456,4 +442,6 @@ struct is_lvalue
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_XPRHELPER_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Block.h b/extern/Eigen3/Eigen/src/Eigen2Support/Block.h
index bc28051e017..604456f40e7 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Block.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Block.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BLOCK2_H
 #define EIGEN_BLOCK2_H
 
+namespace Eigen { 
+
 /** \returns a dynamic-size expression of a corner of *this.
   *
   * \param type the type of corner. Can be \a Eigen::TopLeft, \a Eigen::TopRight,
@@ -134,4 +121,6 @@ DenseBase<Derived>::corner(CornerType type) const
   }
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_BLOCK2_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Cwise.h b/extern/Eigen3/Eigen/src/Eigen2Support/Cwise.h
index 2dc83b6a7dd..d95009b6e29 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Cwise.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Cwise.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_CWISE_H
 #define EIGEN_CWISE_H
 
+namespace Eigen { 
+
 /** \internal
   * convenient macro to defined the return type of a cwise binary operation */
 #define EIGEN_CWISE_BINOP_RETURN_TYPE(OP) \
@@ -200,4 +187,6 @@ inline Cwise<Derived> MatrixBase<Derived>::cwise()
   return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_CWISE_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/CwiseOperators.h b/extern/Eigen3/Eigen/src/Eigen2Support/CwiseOperators.h
index 9c28559c329..482f3064856 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/CwiseOperators.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/CwiseOperators.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ARRAY_CWISE_OPERATORS_H
 #define EIGEN_ARRAY_CWISE_OPERATORS_H
 
+namespace Eigen { 
+
 /***************************************************************************
 * The following functions were defined in Core
 ***************************************************************************/
@@ -306,4 +293,6 @@ inline ExpressionType& Cwise<ExpressionType>::operator-=(const Scalar& scalar)
   return m_matrix.const_cast_derived() = *this - scalar;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_ARRAY_CWISE_OPERATORS_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AlignedBox.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
index 78df29d408a..5c928e8fc2d 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AlignedBox.h
@@ -3,27 +3,14 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   * \nonstableyet
   *
@@ -63,7 +50,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim==
   ~AlignedBox() {}
 
   /** \returns the dimension in which the box holds */
-  inline int dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : int(AmbientDimAtCompileTime); }
+  inline int dim() const { return AmbientDimAtCompileTime==Dynamic ? m_min.size()-1 : AmbientDimAtCompileTime; }
 
   /** \returns true if the box is null, i.e, empty. */
   inline bool isNull() const { return (m_min.cwise() > m_max).any(); }
@@ -157,14 +144,16 @@ protected:
 template<typename Scalar,int AmbiantDim>
 inline Scalar AlignedBox<Scalar,AmbiantDim>::squaredExteriorDistance(const VectorType& p) const
 {
-  Scalar dist2 = 0.;
+  Scalar dist2(0);
   Scalar aux;
   for (int k=0; k<dim(); ++k)
   {
-    if ((aux = (p[k]-m_min[k]))<0.)
+    if ((aux = (p[k]-m_min[k]))<Scalar(0))
       dist2 += aux*aux;
-    else if ( (aux = (m_max[k]-p[k]))<0. )
+    else if ( (aux = (m_max[k]-p[k]))<Scalar(0))
       dist2 += aux*aux;
   }
   return dist2;
 }
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/All.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/All.h
index 9d8244b07a0..e0b00fccccf 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/All.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/All.h
@@ -112,4 +112,4 @@
 #undef Hyperplane
 #undef ParametrizedLine
 
-#endif // EIGEN2_GEOMETRY_MODULE_H
\ No newline at end of file
+#endif // EIGEN2_GEOMETRY_MODULE_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AngleAxis.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
index f7b2d51e3e2..20f1fceeb19 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/AngleAxis.h
@@ -3,27 +3,13 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
 
 /** \geometry_module \ingroup Geometry_Module
   *
@@ -224,3 +210,5 @@ AngleAxis<Scalar>::toRotationMatrix(void) const
 
   return res;
 }
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Hyperplane.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
index 81c4f55b173..19cc1bfd883 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Hyperplane.h
@@ -4,27 +4,14 @@
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class Hyperplane
@@ -263,3 +250,5 @@ protected:
 
   Coefficients m_coeffs;
 };
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
index 411c4b57079..6e4a168a8cd 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/ParametrizedLine.h
@@ -4,27 +4,13 @@
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
 
 /** \geometry_module \ingroup Geometry_Module
   *
@@ -151,3 +137,5 @@ inline _Scalar ParametrizedLine<_Scalar, _AmbientDim>::intersection(const Hyperp
   return -(hyperplane.offset()+origin().eigen2_dot(hyperplane.normal()))
           /(direction().eigen2_dot(hyperplane.normal()));
 }
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Quaternion.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Quaternion.h
index a75fa42aeac..ec87da054d6 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Quaternion.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Quaternion.h
@@ -3,27 +3,14 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
+
 template<typename Other,
          int OtherRows=Other::RowsAtCompileTime,
          int OtherCols=Other::ColsAtCompileTime>
@@ -143,7 +130,7 @@ public:
   /** \returns a quaternion representing an identity rotation
     * \sa MatrixBase::Identity()
     */
-  inline static Quaternion Identity() { return Quaternion(1, 0, 0, 0); }
+  static inline Quaternion Identity() { return Quaternion(1, 0, 0, 0); }
 
   /** \sa Quaternion::Identity(), MatrixBase::setIdentity()
     */
@@ -314,9 +301,9 @@ Quaternion<Scalar>::toRotationMatrix(void) const
   // it has to be inlined, and so the return by value is not an issue
   Matrix3 res;
 
-  const Scalar tx  = 2*this->x();
-  const Scalar ty  = 2*this->y();
-  const Scalar tz  = 2*this->z();
+  const Scalar tx  = Scalar(2)*this->x();
+  const Scalar ty  = Scalar(2)*this->y();
+  const Scalar tz  = Scalar(2)*this->z();
   const Scalar twx = tx*this->w();
   const Scalar twy = ty*this->w();
   const Scalar twz = tz*this->w();
@@ -327,15 +314,15 @@ Quaternion<Scalar>::toRotationMatrix(void) const
   const Scalar tyz = tz*this->y();
   const Scalar tzz = tz*this->z();
 
-  res.coeffRef(0,0) = 1-(tyy+tzz);
+  res.coeffRef(0,0) = Scalar(1)-(tyy+tzz);
   res.coeffRef(0,1) = txy-twz;
   res.coeffRef(0,2) = txz+twy;
   res.coeffRef(1,0) = txy+twz;
-  res.coeffRef(1,1) = 1-(txx+tzz);
+  res.coeffRef(1,1) = Scalar(1)-(txx+tzz);
   res.coeffRef(1,2) = tyz-twx;
   res.coeffRef(2,0) = txz-twy;
   res.coeffRef(2,1) = tyz+twx;
-  res.coeffRef(2,2) = 1-(txx+tyy);
+  res.coeffRef(2,2) = Scalar(1)-(txx+tyy);
 
   return res;
 }
@@ -460,7 +447,7 @@ template<typename Other>
 struct ei_quaternion_assign_impl<Other,3,3>
 {
   typedef typename Other::Scalar Scalar;
-  inline static void run(Quaternion<Scalar>& q, const Other& mat)
+  static inline void run(Quaternion<Scalar>& q, const Other& mat)
   {
     // This algorithm comes from  "Quaternion Calculus and Fast Animation",
     // Ken Shoemake, 1987 SIGGRAPH course notes
@@ -499,8 +486,10 @@ template<typename Other>
 struct ei_quaternion_assign_impl<Other,4,1>
 {
   typedef typename Other::Scalar Scalar;
-  inline static void run(Quaternion<Scalar>& q, const Other& vec)
+  static inline void run(Quaternion<Scalar>& q, const Other& vec)
   {
     q.coeffs() = vec;
   }
 };
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Rotation2D.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
index ee7c80e7eaa..3e02b7a4fd1 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Rotation2D.h
@@ -3,27 +3,13 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
 
 /** \geometry_module \ingroup Geometry_Module
   *
@@ -155,3 +141,5 @@ Rotation2D<Scalar>::toRotationMatrix(void) const
   Scalar cosA = ei_cos(m_angle);
   return (Matrix2() << cosA, -sinA, sinA, cosA).finished();
 }
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/RotationBase.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/RotationBase.h
index 2f494f198bd..78ad73b60ad 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/RotationBase.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/RotationBase.h
@@ -3,27 +3,14 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
+
 // this file aims to contains the various representations of rotation/orientation
 // in 2D and 3D space excepted Matrix and Quaternion.
 
@@ -113,22 +100,24 @@ Matrix<_Scalar, _Rows, _Cols, _Storage, _MaxRows, _MaxCols>
   * \sa class Transform, class Rotation2D, class Quaternion, class AngleAxis
   */
 template<typename Scalar, int Dim>
-inline static Matrix<Scalar,2,2> ei_toRotationMatrix(const Scalar& s)
+static inline Matrix<Scalar,2,2> ei_toRotationMatrix(const Scalar& s)
 {
   EIGEN_STATIC_ASSERT(Dim==2,YOU_MADE_A_PROGRAMMING_MISTAKE)
   return Rotation2D<Scalar>(s).toRotationMatrix();
 }
 
 template<typename Scalar, int Dim, typename OtherDerived>
-inline static Matrix<Scalar,Dim,Dim> ei_toRotationMatrix(const RotationBase<OtherDerived,Dim>& r)
+static inline Matrix<Scalar,Dim,Dim> ei_toRotationMatrix(const RotationBase<OtherDerived,Dim>& r)
 {
   return r.toRotationMatrix();
 }
 
 template<typename Scalar, int Dim, typename OtherDerived>
-inline static const MatrixBase<OtherDerived>& ei_toRotationMatrix(const MatrixBase<OtherDerived>& mat)
+static inline const MatrixBase<OtherDerived>& ei_toRotationMatrix(const MatrixBase<OtherDerived>& mat)
 {
   EIGEN_STATIC_ASSERT(OtherDerived::RowsAtCompileTime==Dim && OtherDerived::ColsAtCompileTime==Dim,
     YOU_MADE_A_PROGRAMMING_MISTAKE)
   return mat;
 }
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Scaling.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Scaling.h
index 108e6d7d58f..a07c1c7c762 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Scaling.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Scaling.h
@@ -3,27 +3,13 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
 
 /** \geometry_module \ingroup Geometry_Module
   *
@@ -177,3 +163,5 @@ Scaling<Scalar,Dim>::operator* (const TransformType& t) const
   res.prescale(m_coeffs);
   return res;
 }
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Transform.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Transform.h
index 88956c86c73..dceb8020383 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Transform.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Transform.h
@@ -4,27 +4,13 @@
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
 
 // Note that we have to pass Dim and HDim because it is not allowed to use a template
 // parameter to define a template specialization. To be more precise, in the following
@@ -796,3 +782,5 @@ struct ei_transform_product_impl<Other,Dim,HDim, Dim,1>
   { return ((tr.linear() * other) + tr.translation())
           * (Scalar(1) / ( (tr.matrix().template block<1,Dim>(Dim,0) * other).coeff(0) + tr.matrix().coeff(Dim,Dim))); }
 };
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Translation.h b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Translation.h
index e651e310212..0fb9a9f9a5a 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Translation.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Geometry/Translation.h
@@ -3,27 +3,13 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // no include guard, we'll include this twice from All.h from Eigen2Support, and it's internal anyway
 
+namespace Eigen { 
 
 /** \geometry_module \ingroup Geometry_Module
   *
@@ -194,3 +180,5 @@ Translation<Scalar,Dim>::operator* (const TransformType& t) const
   res.pretranslate(m_coeffs);
   return res;
 }
+
+} // end namespace Eigen
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/LU.h b/extern/Eigen3/Eigen/src/Eigen2Support/LU.h
index c23c11baa72..49f19ad76e3 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/LU.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/LU.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_LU_H
 #define EIGEN2_LU_H
 
+namespace Eigen { 
+
 template<typename MatrixType>
 class LU : public FullPivLU<MatrixType>
 {
@@ -57,7 +44,6 @@ class LU : public FullPivLU<MatrixType>
     > ImageResultType;
 
     typedef FullPivLU<MatrixType> Base;
-    LU() : Base() {}
 
     template<typename T>
     explicit LU(const T& t) : Base(t), m_originalMatrix(t) {}
@@ -129,5 +115,6 @@ MatrixBase<Derived>::eigen2_lu() const
 }
 #endif
 
+} // end namespace Eigen
 
 #endif // EIGEN2_LU_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Lazy.h b/extern/Eigen3/Eigen/src/Eigen2Support/Lazy.h
index c4288ede2ef..593fc78e6de 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Lazy.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Lazy.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LAZY_H
 #define EIGEN_LAZY_H
 
+namespace Eigen { 
+
 /** \deprecated it is only used by lazy() which is deprecated
   *
   * \returns an expression of *this with added flags
@@ -79,4 +66,6 @@ Derived& MatrixBase<Derived>::operator-=(const Flagged<ProductBase<ProductDerive
   other._expression().derived().subTo(derived()); return derived();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_LAZY_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/LeastSquares.h b/extern/Eigen3/Eigen/src/Eigen2Support/LeastSquares.h
index 4b62ffa92c7..7aff428dc45 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/LeastSquares.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/LeastSquares.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_LEASTSQUARES_H
 #define EIGEN2_LEASTSQUARES_H
 
+namespace Eigen { 
+
 /** \ingroup LeastSquares_Module
   *
   * \leastsquares_module
@@ -178,5 +165,6 @@ void fitHyperplane(int numPoints,
   result->offset() = - (result->normal().cwise()* mean).sum();
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN2_LEASTSQUARES_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Macros.h b/extern/Eigen3/Eigen/src/Eigen2Support/Macros.h
index 77e85a41e3d..351c32afb60 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Macros.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Macros.h
@@ -3,24 +3,9 @@
 //
 // Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_MACROS_H
 #define EIGEN2_MACROS_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/MathFunctions.h b/extern/Eigen3/Eigen/src/Eigen2Support/MathFunctions.h
index caa44e63f32..3a8a9ca8146 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/MathFunctions.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/MathFunctions.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_MATH_FUNCTIONS_H
 #define EIGEN2_MATH_FUNCTIONS_H
 
+namespace Eigen { 
+
 template<typename T> inline typename NumTraits<T>::Real ei_real(const T& x) { return internal::real(x); }
 template<typename T> inline typename NumTraits<T>::Real ei_imag(const T& x) { return internal::imag(x); }
 template<typename T> inline T ei_conj(const T& x) { return internal::conj(x); }
@@ -65,4 +52,6 @@ inline bool ei_isApproxOrLessThan(const Scalar& x, const Scalar& y,
   return internal::isApproxOrLessThan(x, y, precision);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN2_MATH_FUNCTIONS_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Memory.h b/extern/Eigen3/Eigen/src/Eigen2Support/Memory.h
index 0283475419e..f86372b6b56 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Memory.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Memory.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_MEMORY_H
 #define EIGEN2_MEMORY_H
 
+namespace Eigen { 
+
 inline void* ei_aligned_malloc(size_t size) { return internal::aligned_malloc(size); }
 inline void  ei_aligned_free(void *ptr) { internal::aligned_free(ptr); }
 inline void* ei_aligned_realloc(void *ptr, size_t new_size, size_t old_size) { return internal::aligned_realloc(ptr, new_size, old_size); }
@@ -53,6 +40,6 @@ template<typename T> inline void ei_aligned_delete(T *ptr, size_t size)
   return internal::aligned_delete(ptr, size);
 }
 
-
+} // end namespace Eigen
 
 #endif // EIGEN2_MACROS_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Meta.h b/extern/Eigen3/Eigen/src/Eigen2Support/Meta.h
index 6e500b79a2e..fa37cfc961e 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Meta.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Meta.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_META_H
 #define EIGEN2_META_H
 
+namespace Eigen { 
+
 template<typename T>
 struct ei_traits : internal::traits<T>
 {};
@@ -83,4 +70,6 @@ class ei_meta_sqrt
 template<int Y, int InfX, int SupX>
 class ei_meta_sqrt<Y, InfX, SupX, true> { public:  enum { ret = (SupX*SupX <= Y) ? SupX : InfX }; };
 
+} // end namespace Eigen
+
 #endif // EIGEN2_META_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/Minor.h b/extern/Eigen3/Eigen/src/Eigen2Support/Minor.h
index eda91cc32be..4cded5734fa 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/Minor.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/Minor.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MINOR_H
 #define EIGEN_MINOR_H
 
+namespace Eigen { 
+
 /**
   * \class Minor
   *
@@ -125,4 +112,6 @@ MatrixBase<Derived>::minor(Index row, Index col) const
   return Minor<Derived>(derived(), row, col);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_MINOR_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/QR.h b/extern/Eigen3/Eigen/src/Eigen2Support/QR.h
index 64f5d5ccb30..2042c98510a 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/QR.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/QR.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 // Copyright (C) 2011 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_QR_H
 #define EIGEN2_QR_H
 
+namespace Eigen { 
+
 template<typename MatrixType>
 class QR : public HouseholderQR<MatrixType>
 {
@@ -75,5 +62,6 @@ MatrixBase<Derived>::qr() const
   return QR<PlainObject>(eval());
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN2_QR_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/SVD.h b/extern/Eigen3/Eigen/src/Eigen2Support/SVD.h
index 16b4b488f0c..3d2eeb44586 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/SVD.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/SVD.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_SVD_H
 #define EIGEN2_SVD_H
 
+namespace Eigen {
+
 /** \ingroup SVD_Module
   * \nonstableyet
   *
@@ -390,7 +377,7 @@ void SVD<MatrixType>::compute(const MatrixType& matrix)
         Scalar ek = e[k]/scale;
         Scalar b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/Scalar(2);
         Scalar c = (sp*epm1)*(sp*epm1);
-        Scalar shift = 0.0;
+        Scalar shift(0);
         if ((b != 0.0) || (c != 0.0))
         {
           shift = ei_sqrt(b*b + c);
@@ -646,4 +633,6 @@ MatrixBase<Derived>::svd() const
   return SVD<PlainObject>(derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN2_SVD_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/TriangularSolver.h b/extern/Eigen3/Eigen/src/Eigen2Support/TriangularSolver.h
index e94e47a5093..ebbeb3b4958 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/TriangularSolver.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/TriangularSolver.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIANGULAR_SOLVER2_H
 #define EIGEN_TRIANGULAR_SOLVER2_H
 
+namespace Eigen { 
+
 const unsigned int UnitDiagBit = UnitDiag;
 const unsigned int SelfAdjointBit = SelfAdjoint;
 const unsigned int UpperTriangularBit = Upper;
@@ -49,5 +36,7 @@ void Flagged<ExpressionType,Added,Removed>::solveTriangularInPlace(const MatrixB
 {
   m_matrix.template triangularView<Added>().solveInPlace(other.derived());
 }
+
+} // end namespace Eigen
     
 #endif // EIGEN_TRIANGULAR_SOLVER2_H
diff --git a/extern/Eigen3/Eigen/src/Eigen2Support/VectorBlock.h b/extern/Eigen3/Eigen/src/Eigen2Support/VectorBlock.h
index 010031d1971..71a8080a9fc 100644
--- a/extern/Eigen3/Eigen/src/Eigen2Support/VectorBlock.h
+++ b/extern/Eigen3/Eigen/src/Eigen2Support/VectorBlock.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN2_VECTORBLOCK_H
 #define EIGEN2_VECTORBLOCK_H
 
+namespace Eigen { 
+
 /** \deprecated use DenseMase::head(Index) */
 template<typename Derived>
 inline VectorBlock<Derived>
@@ -102,4 +89,6 @@ MatrixBase<Derived>::end() const
   return VectorBlock<const Derived, Size>(derived(), size() - Size);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN2_VECTORBLOCK_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/extern/Eigen3/Eigen/src/Eigenvalues/ComplexEigenSolver.h
index 57e00227d72..c4b8a308cee 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/ComplexEigenSolver.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/ComplexEigenSolver.h
@@ -5,31 +5,17 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COMPLEX_EIGEN_SOLVER_H
 #define EIGEN_COMPLEX_EIGEN_SOLVER_H
 
-#include "./EigenvaluesCommon.h"
 #include "./ComplexSchur.h"
 
+namespace Eigen { 
+
 /** \eigenvalues_module \ingroup Eigenvalues_Module
   *
   *
@@ -328,5 +314,6 @@ void ComplexEigenSolver<MatrixType>::sortEigenvalues(bool computeEigenvectors)
   }
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_COMPLEX_EIGEN_SOLVER_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/ComplexSchur.h b/extern/Eigen3/Eigen/src/Eigenvalues/ComplexSchur.h
index ec93af2e58a..16a9a03d219 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/ComplexSchur.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/ComplexSchur.h
@@ -5,31 +5,17 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COMPLEX_SCHUR_H
 #define EIGEN_COMPLEX_SCHUR_H
 
-#include "./EigenvaluesCommon.h"
 #include "./HessenbergDecomposition.h"
 
+namespace Eigen { 
+
 namespace internal {
 template<typename MatrixType, bool IsComplex> struct complex_schur_reduce_to_hessenberg;
 }
@@ -227,46 +213,6 @@ template<typename _MatrixType> class ComplexSchur
     friend struct internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>;
 };
 
-namespace internal {
-
-/** Computes the principal value of the square root of the complex \a z. */
-template<typename RealScalar>
-std::complex<RealScalar> sqrt(const std::complex<RealScalar> &z)
-{
-  RealScalar t, tre, tim;
-
-  t = abs(z);
-
-  if (abs(real(z)) <= abs(imag(z)))
-  {
-    // No cancellation in these formulas
-    tre = sqrt(RealScalar(0.5)*(t + real(z)));
-    tim = sqrt(RealScalar(0.5)*(t - real(z)));
-  }
-  else
-  {
-    // Stable computation of the above formulas
-    if (z.real() > RealScalar(0))
-    {
-      tre = t + z.real();
-      tim = abs(imag(z))*sqrt(RealScalar(0.5)/tre);
-      tre = sqrt(RealScalar(0.5)*tre);
-    }
-    else
-    {
-      tim = t - z.real();
-      tre = abs(imag(z))*sqrt(RealScalar(0.5)/tim);
-      tim = sqrt(RealScalar(0.5)*tim);
-    }
-  }
-  if(z.imag() < RealScalar(0))
-    tim = -tim;
-
-  return (std::complex<RealScalar>(tre,tim));
-}
-} // end namespace internal
-
-
 /** If m_matT(i+1,i) is neglegible in floating point arithmetic
   * compared to m_matT(i,i) and m_matT(j,j), then set it to zero and
   * return true, else return false. */
@@ -302,7 +248,7 @@ typename ComplexSchur<MatrixType>::ComplexScalar ComplexSchur<MatrixType>::compu
 
   ComplexScalar b = t.coeff(0,1) * t.coeff(1,0);
   ComplexScalar c = t.coeff(0,0) - t.coeff(1,1);
-  ComplexScalar disc = internal::sqrt(c*c + RealScalar(4)*b);
+  ComplexScalar disc = sqrt(c*c + RealScalar(4)*b);
   ComplexScalar det = t.coeff(0,0) * t.coeff(1,1) - b;
   ComplexScalar trace = t.coeff(0,0) + t.coeff(1,1);
   ComplexScalar eival1 = (trace + disc) / RealScalar(2);
@@ -406,7 +352,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
 
     // if we spent too many iterations on the current element, we give up
     iter++;
-    if(iter > m_maxIterations) break;
+    if(iter > m_maxIterations * m_matT.cols()) break;
 
     // find il, the top row of the active submatrix
     il = iu-1;
@@ -436,7 +382,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
     }
   }
 
-  if(iter <= m_maxIterations) 
+  if(iter <= m_maxIterations * m_matT.cols()) 
     m_info = Success;
   else
     m_info = NoConvergence;
@@ -445,4 +391,6 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
   m_matUisUptodate = computeU;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_COMPLEX_SCHUR_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/ComplexSchur_MKL.h b/extern/Eigen3/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
new file mode 100644
index 00000000000..aa18e696352
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/ComplexSchur_MKL.h
@@ -0,0 +1,94 @@
+/*
+ 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
+ *    Complex Schur needed to complex unsymmetrical eigenvalues/eigenvectors.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_COMPLEX_SCHUR_MKL_H
+#define EIGEN_COMPLEX_SCHUR_MKL_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by MKL */
+
+#define EIGEN_MKL_SCHUR_COMPLEX(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
+template<> inline\
+ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
+ComplexSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
+{ \
+  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> MatrixType; \
+  typedef MatrixType::Scalar Scalar; \
+  typedef MatrixType::RealScalar RealScalar; \
+  typedef std::complex<RealScalar> ComplexScalar; \
+\
+  assert(matrix.cols() == matrix.rows()); \
+\
+  m_matUisUptodate = false; \
+  if(matrix.cols() == 1) \
+  { \
+    m_matT = matrix.cast<ComplexScalar>(); \
+    if(computeU)  m_matU = ComplexMatrixType::Identity(1,1); \
+      m_info = Success; \
+      m_isInitialized = true; \
+      m_matUisUptodate = computeU; \
+      return *this; \
+  } \
+  lapack_int n = matrix.cols(), sdim, info; \
+  lapack_int lda = matrix.outerStride(); \
+  lapack_int matrix_order = MKLCOLROW; \
+  char jobvs, sort='N'; \
+  LAPACK_##MKLPREFIX_U##_SELECT1 select = 0; \
+  jobvs = (computeU) ? 'V' : 'N'; \
+  m_matU.resize(n, n); \
+  lapack_int ldvs  = m_matU.outerStride(); \
+  m_matT = matrix; \
+  Matrix<EIGTYPE, Dynamic, Dynamic> w; \
+  w.resize(n, 1);\
+  info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)w.data(), (MKLTYPE*)m_matU.data(), ldvs ); \
+  if(info == 0) \
+    m_info = Success; \
+  else \
+    m_info = NoConvergence; \
+\
+  m_isInitialized = true; \
+  m_matUisUptodate = computeU; \
+  return *this; \
+\
+}
+
+EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8,  c, C, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_SCHUR_COMPLEX(dcomplex, MKL_Complex16, z, Z, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_SCHUR_COMPLEX(scomplex, MKL_Complex8,  c, C, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_COMPLEX_SCHUR_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h b/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h
index f57353c065f..c16ff2b74e2 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h
@@ -4,31 +4,17 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_EIGENSOLVER_H
 #define EIGEN_EIGENSOLVER_H
 
-#include "./EigenvaluesCommon.h"
 #include "./RealSchur.h"
 
+namespace Eigen { 
+
 /** \eigenvalues_module \ingroup Eigenvalues_Module
   *
   *
@@ -432,7 +418,7 @@ void EigenSolver<MatrixType>::doComputeEigenvectors()
   const Scalar eps = NumTraits<Scalar>::epsilon();
 
   // inefficient! this is already computed in RealSchur
-  Scalar norm = 0.0;
+  Scalar norm(0);
   for (Index j = 0; j < size; ++j)
   {
     norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum();
@@ -452,7 +438,7 @@ void EigenSolver<MatrixType>::doComputeEigenvectors()
     // Scalar vector
     if (q == Scalar(0))
     {
-      Scalar lastr=0, lastw=0;
+      Scalar lastr(0), lastw(0);
       Index l = n;
 
       m_matT.coeffRef(n,n) = 1.0;
@@ -498,7 +484,7 @@ void EigenSolver<MatrixType>::doComputeEigenvectors()
     }
     else if (q < Scalar(0) && n > 0) // Complex vector
     {
-      Scalar lastra=0, lastsa=0, lastw=0;
+      Scalar lastra(0), lastsa(0), lastw(0);
       Index l = n-1;
 
       // Last vector component imaginary so matrix is triangular
@@ -588,4 +574,6 @@ void EigenSolver<MatrixType>::doComputeEigenvectors()
   }
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_EIGENSOLVER_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/EigenvaluesCommon.h b/extern/Eigen3/Eigen/src/Eigenvalues/EigenvaluesCommon.h
deleted file mode 100644
index 749bea79500..00000000000
--- a/extern/Eigen3/Eigen/src/Eigenvalues/EigenvaluesCommon.h
+++ /dev/null
@@ -1,31 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
-//
-// 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_EIGENVALUES_COMMON_H
-#define EIGEN_EIGENVALUES_COMMON_H
-
-
-
-#endif // EIGEN_EIGENVALUES_COMMON_H
-
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h b/extern/Eigen3/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h
index 980af14ce71..07bf1ea0956 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h
@@ -4,31 +4,17 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H
 #define EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H
 
-#include "./EigenvaluesCommon.h"
 #include "./Tridiagonalization.h"
 
+namespace Eigen { 
+
 /** \eigenvalues_module \ingroup Eigenvalues_Module
   *
   *
@@ -236,4 +222,6 @@ compute(const MatrixType& matA, const MatrixType& matB, int options)
   return *this;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_GENERALIZEDSELFADJOINTEIGENSOLVER_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/HessenbergDecomposition.h b/extern/Eigen3/Eigen/src/Eigenvalues/HessenbergDecomposition.h
index c17f155a59b..b8378b08a09 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/HessenbergDecomposition.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/HessenbergDecomposition.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_HESSENBERGDECOMPOSITION_H
 #define EIGEN_HESSENBERGDECOMPOSITION_H
 
+namespace Eigen { 
+
 namespace internal {
   
 template<typename MatrixType> struct HessenbergDecompositionMatrixHReturnType;
@@ -379,6 +366,8 @@ template<typename MatrixType> struct HessenbergDecompositionMatrixHReturnType
     const HessenbergDecomposition<MatrixType>& m_hess;
 };
 
-}
+} // end namespace internal
+
+} // end namespace Eigen
 
 #endif // EIGEN_HESSENBERGDECOMPOSITION_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h b/extern/Eigen3/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h
index 5591519fb75..6af481c75f6 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MATRIXBASEEIGENVALUES_H
 #define EIGEN_MATRIXBASEEIGENVALUES_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename Derived, bool IsComplex>
@@ -167,4 +154,6 @@ SelfAdjointView<MatrixType, UpLo>::operatorNorm() const
   return eigenvalues().cwiseAbs().maxCoeff();
 }
 
+} // end namespace Eigen
+
 #endif
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/RealSchur.h b/extern/Eigen3/Eigen/src/Eigenvalues/RealSchur.h
index cc9af11c117..781692eccd3 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/RealSchur.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/RealSchur.h
@@ -4,31 +4,17 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_REAL_SCHUR_H
 #define EIGEN_REAL_SCHUR_H
 
-#include "./EigenvaluesCommon.h"
 #include "./HessenbergDecomposition.h"
 
+namespace Eigen { 
+
 /** \eigenvalues_module \ingroup Eigenvalues_Module
   *
   *
@@ -235,42 +221,44 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
   // Rows iu+1,...,end are already brought in triangular form.
   Index iu = m_matT.cols() - 1;
   Index iter = 0; // iteration count
-  Scalar exshift = 0.0; // sum of exceptional shifts
+  Scalar exshift(0); // sum of exceptional shifts
   Scalar norm = computeNormOfT();
 
-  while (iu >= 0)
+  if(norm!=0)
   {
-    Index il = findSmallSubdiagEntry(iu, norm);
-
-    // Check for convergence
-    if (il == iu) // One root found
-    {
-      m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift;
-      if (iu > 0) 
-        m_matT.coeffRef(iu, iu-1) = Scalar(0);
-      iu--;
-      iter = 0;
-    }
-    else if (il == iu-1) // Two roots found
-    {
-      splitOffTwoRows(iu, computeU, exshift);
-      iu -= 2;
-      iter = 0;
-    }
-    else // No convergence yet
+    while (iu >= 0)
     {
-      // The firstHouseholderVector vector has to be initialized to something to get rid of a silly GCC warning (-O1 -Wall -DNDEBUG )
-      Vector3s firstHouseholderVector(0,0,0), shiftInfo;
-      computeShift(iu, iter, exshift, shiftInfo);
-      iter = iter + 1; 
-      if (iter > m_maxIterations) break;
-      Index im;
-      initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
-      performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
+      Index il = findSmallSubdiagEntry(iu, norm);
+
+      // Check for convergence
+      if (il == iu) // One root found
+      {
+        m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift;
+        if (iu > 0)
+          m_matT.coeffRef(iu, iu-1) = Scalar(0);
+        iu--;
+        iter = 0;
+      }
+      else if (il == iu-1) // Two roots found
+      {
+        splitOffTwoRows(iu, computeU, exshift);
+        iu -= 2;
+        iter = 0;
+      }
+      else // No convergence yet
+      {
+        // The firstHouseholderVector vector has to be initialized to something to get rid of a silly GCC warning (-O1 -Wall -DNDEBUG )
+        Vector3s firstHouseholderVector(0,0,0), shiftInfo;
+        computeShift(iu, iter, exshift, shiftInfo);
+        iter = iter + 1;
+        if (iter > m_maxIterations * m_matT.cols()) break;
+        Index im;
+        initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
+        performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
+      }
     }
-  } 
-
-  if(iter <= m_maxIterations) 
+  }
+  if(iter <= m_maxIterations * m_matT.cols()) 
     m_info = Success;
   else
     m_info = NoConvergence;
@@ -288,7 +276,7 @@ inline typename MatrixType::Scalar RealSchur<MatrixType>::computeNormOfT()
   // FIXME to be efficient the following would requires a triangular reduxion code
   // Scalar norm = m_matT.upper().cwiseAbs().sum() 
   //               + m_matT.bottomLeftCorner(size-1,size-1).diagonal().cwiseAbs().sum();
-  Scalar norm = 0.0;
+  Scalar norm(0);
   for (Index j = 0; j < size; ++j)
     norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum();
   return norm;
@@ -471,4 +459,6 @@ inline void RealSchur<MatrixType>::performFrancisQRStep(Index il, Index im, Inde
   }
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_REAL_SCHUR_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/RealSchur_MKL.h b/extern/Eigen3/Eigen/src/Eigenvalues/RealSchur_MKL.h
new file mode 100644
index 00000000000..960ec3c764a
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/RealSchur_MKL.h
@@ -0,0 +1,83 @@
+/*
+ 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
+ *    Real Schur needed to real unsymmetrical eigenvalues/eigenvectors.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_REAL_SCHUR_MKL_H
+#define EIGEN_REAL_SCHUR_MKL_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by MKL */
+
+#define EIGEN_MKL_SCHUR_REAL(EIGTYPE, MKLTYPE, MKLPREFIX, MKLPREFIX_U, EIGCOLROW, MKLCOLROW) \
+template<> inline \
+RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
+RealSchur<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, bool computeU) \
+{ \
+  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> MatrixType; \
+  typedef MatrixType::Scalar Scalar; \
+  typedef MatrixType::RealScalar RealScalar; \
+\
+  assert(matrix.cols() == matrix.rows()); \
+\
+  lapack_int n = matrix.cols(), sdim, info; \
+  lapack_int lda = matrix.outerStride(); \
+  lapack_int matrix_order = MKLCOLROW; \
+  char jobvs, sort='N'; \
+  LAPACK_##MKLPREFIX_U##_SELECT2 select = 0; \
+  jobvs = (computeU) ? 'V' : 'N'; \
+  m_matU.resize(n, n); \
+  lapack_int ldvs  = m_matU.outerStride(); \
+  m_matT = matrix; \
+  Matrix<EIGTYPE, Dynamic, Dynamic> wr, wi; \
+  wr.resize(n, 1); wi.resize(n, 1); \
+  info = LAPACKE_##MKLPREFIX##gees( matrix_order, jobvs, sort, select, n, (MKLTYPE*)m_matT.data(), lda, &sdim, (MKLTYPE*)wr.data(), (MKLTYPE*)wi.data(), (MKLTYPE*)m_matU.data(), ldvs ); \
+  if(info == 0) \
+    m_info = Success; \
+  else \
+    m_info = NoConvergence; \
+\
+  m_isInitialized = true; \
+  m_matUisUptodate = computeU; \
+  return *this; \
+\
+}
+
+EIGEN_MKL_SCHUR_REAL(double,   double, d, D, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_SCHUR_REAL(float,    float,  s, S, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_SCHUR_REAL(double,   double, d, D, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_SCHUR_REAL(float,    float,  s, S, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_REAL_SCHUR_MKL_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
index ad107c63282..acc5576feb1 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -4,34 +4,24 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SELFADJOINTEIGENSOLVER_H
 #define EIGEN_SELFADJOINTEIGENSOLVER_H
 
-#include "./EigenvaluesCommon.h"
 #include "./Tridiagonalization.h"
 
+namespace Eigen { 
+
 template<typename _MatrixType>
 class GeneralizedSelfAdjointEigenSolver;
 
+namespace internal {
+template<typename SolverType,int Size,bool IsComplex> struct direct_selfadjoint_eigenvalues;
+}
+
 /** \eigenvalues_module \ingroup Eigenvalues_Module
   *
   *
@@ -86,7 +76,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       Options = MatrixType::Options,
       MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
     };
-
+    
     /** \brief Scalar type for matrices of type \p _MatrixType. */
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::Index Index;
@@ -98,6 +88,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       * complex.
       */
     typedef typename NumTraits<Scalar>::Real RealScalar;
+    
+    friend struct internal::direct_selfadjoint_eigenvalues<SelfAdjointEigenSolver,Size,NumTraits<Scalar>::IsComplex>;
 
     /** \brief Type for vector of eigenvalues as returned by eigenvalues().
       *
@@ -198,6 +190,22 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
       * \sa SelfAdjointEigenSolver(const MatrixType&, int)
       */
     SelfAdjointEigenSolver& compute(const MatrixType& matrix, int options = ComputeEigenvectors);
+    
+    /** \brief Computes eigendecomposition of given matrix using a direct algorithm
+      *
+      * This is a variant of compute(const MatrixType&, int options) which
+      * directly solves the underlying polynomial equation.
+      * 
+      * Currently only 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d).
+      * 
+      * This method is usually significantly faster than the QR algorithm
+      * but it might also be less accurate. It is also worth noting that
+      * for 3x3 matrices it involves trigonometric operations which are
+      * not necessarily available for all scalar types.
+      *
+      * \sa compute(const MatrixType&, int options)
+      */
+    SelfAdjointEigenSolver& computeDirect(const MatrixType& matrix, int options = ComputeEigenvectors);
 
     /** \brief Returns the eigenvectors of given matrix.
       *
@@ -401,7 +409,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
 
   // map the matrix coefficients to [-1:1] to avoid over- and underflow.
   RealScalar scale = matrix.cwiseAbs().maxCoeff();
-  if(scale==Scalar(0)) scale = 1;
+  if(scale==RealScalar(0)) scale = RealScalar(1);
   mat = matrix / scale;
   m_subdiag.resize(n-1);
   internal::tridiagonalization_inplace(mat, diag, m_subdiag, computeEigenvectors);
@@ -466,19 +474,277 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
   return *this;
 }
 
+
+namespace internal {
+  
+template<typename SolverType,int Size,bool IsComplex> struct direct_selfadjoint_eigenvalues
+{
+  static inline void run(SolverType& eig, const typename SolverType::MatrixType& A, int options)
+  { eig.compute(A,options); }
+};
+
+template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3,false>
+{
+  typedef typename SolverType::MatrixType MatrixType;
+  typedef typename SolverType::RealVectorType VectorType;
+  typedef typename SolverType::Scalar Scalar;
+  
+  static inline void computeRoots(const MatrixType& m, VectorType& roots)
+  {
+    using std::sqrt;
+    using std::atan2;
+    using std::cos;
+    using std::sin;
+    const Scalar s_inv3 = Scalar(1.0)/Scalar(3.0);
+    const Scalar s_sqrt3 = sqrt(Scalar(3.0));
+
+    // The characteristic equation is x^3 - c2*x^2 + c1*x - c0 = 0.  The
+    // eigenvalues are the roots to this equation, all guaranteed to be
+    // real-valued, because the matrix is symmetric.
+    Scalar c0 = m(0,0)*m(1,1)*m(2,2) + Scalar(2)*m(1,0)*m(2,0)*m(2,1) - m(0,0)*m(2,1)*m(2,1) - m(1,1)*m(2,0)*m(2,0) - m(2,2)*m(1,0)*m(1,0);
+    Scalar c1 = m(0,0)*m(1,1) - m(1,0)*m(1,0) + m(0,0)*m(2,2) - m(2,0)*m(2,0) + m(1,1)*m(2,2) - m(2,1)*m(2,1);
+    Scalar c2 = m(0,0) + m(1,1) + m(2,2);
+
+    // Construct the parameters used in classifying the roots of the equation
+    // and in solving the equation for the roots in closed form.
+    Scalar c2_over_3 = c2*s_inv3;
+    Scalar a_over_3 = (c1 - c2*c2_over_3)*s_inv3;
+    if (a_over_3 > Scalar(0))
+      a_over_3 = Scalar(0);
+
+    Scalar half_b = Scalar(0.5)*(c0 + c2_over_3*(Scalar(2)*c2_over_3*c2_over_3 - c1));
+
+    Scalar q = half_b*half_b + a_over_3*a_over_3*a_over_3;
+    if (q > Scalar(0))
+      q = Scalar(0);
+
+    // Compute the eigenvalues by solving for the roots of the polynomial.
+    Scalar rho = sqrt(-a_over_3);
+    Scalar theta = atan2(sqrt(-q),half_b)*s_inv3;
+    Scalar cos_theta = cos(theta);
+    Scalar sin_theta = sin(theta);
+    roots(0) = c2_over_3 + Scalar(2)*rho*cos_theta;
+    roots(1) = c2_over_3 - rho*(cos_theta + s_sqrt3*sin_theta);
+    roots(2) = c2_over_3 - rho*(cos_theta - s_sqrt3*sin_theta);
+
+    // Sort in increasing order.
+    if (roots(0) >= roots(1))
+      std::swap(roots(0),roots(1));
+    if (roots(1) >= roots(2))
+    {
+      std::swap(roots(1),roots(2));
+      if (roots(0) >= roots(1))
+        std::swap(roots(0),roots(1));
+    }
+  }
+  
+  static inline void run(SolverType& solver, const MatrixType& mat, int options)
+  {
+    using std::sqrt;
+    eigen_assert(mat.cols() == 3 && mat.cols() == mat.rows());
+    eigen_assert((options&~(EigVecMask|GenEigMask))==0
+            && (options&EigVecMask)!=EigVecMask
+            && "invalid option parameter");
+    bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
+    
+    MatrixType& eivecs = solver.m_eivec;
+    VectorType& eivals = solver.m_eivalues;
+  
+    // map the matrix coefficients to [-1:1] to avoid over- and underflow.
+    Scalar scale = mat.cwiseAbs().maxCoeff();
+    MatrixType scaledMat = mat / scale;
+
+    // compute the eigenvalues
+    computeRoots(scaledMat,eivals);
+
+    // compute the eigen vectors
+    if(computeEigenvectors)
+    {
+      Scalar safeNorm2 = Eigen::NumTraits<Scalar>::epsilon();
+      safeNorm2 *= safeNorm2;
+      if((eivals(2)-eivals(0))<=Eigen::NumTraits<Scalar>::epsilon())
+      {
+        eivecs.setIdentity();
+      }
+      else
+      {
+        scaledMat = scaledMat.template selfadjointView<Lower>();
+        MatrixType tmp;
+        tmp = scaledMat;
+
+        Scalar d0 = eivals(2) - eivals(1);
+        Scalar d1 = eivals(1) - eivals(0);
+        int k =  d0 > d1 ? 2 : 0;
+        d0 = d0 > d1 ? d1 : d0;
+
+        tmp.diagonal().array () -= eivals(k);
+        VectorType cross;
+        Scalar n;
+        n = (cross = tmp.row(0).cross(tmp.row(1))).squaredNorm();
+
+        if(n>safeNorm2)
+          eivecs.col(k) = cross / sqrt(n);
+        else
+        {
+          n = (cross = tmp.row(0).cross(tmp.row(2))).squaredNorm();
+
+          if(n>safeNorm2)
+            eivecs.col(k) = cross / sqrt(n);
+          else
+          {
+            n = (cross = tmp.row(1).cross(tmp.row(2))).squaredNorm();
+
+            if(n>safeNorm2)
+              eivecs.col(k) = cross / sqrt(n);
+            else
+            {
+              // the input matrix and/or the eigenvaues probably contains some inf/NaN,
+              // => exit
+              // scale back to the original size.
+              eivals *= scale;
+
+              solver.m_info = NumericalIssue;
+              solver.m_isInitialized = true;
+              solver.m_eigenvectorsOk = computeEigenvectors;
+              return;
+            }
+          }
+        }
+
+        tmp = scaledMat;
+        tmp.diagonal().array() -= eivals(1);
+
+        if(d0<=Eigen::NumTraits<Scalar>::epsilon())
+          eivecs.col(1) = eivecs.col(k).unitOrthogonal();
+        else
+        {
+          n = (cross = eivecs.col(k).cross(tmp.row(0).normalized())).squaredNorm();
+          if(n>safeNorm2)
+            eivecs.col(1) = cross / sqrt(n);
+          else
+          {
+            n = (cross = eivecs.col(k).cross(tmp.row(1))).squaredNorm();
+            if(n>safeNorm2)
+              eivecs.col(1) = cross / sqrt(n);
+            else
+            {
+              n = (cross = eivecs.col(k).cross(tmp.row(2))).squaredNorm();
+              if(n>safeNorm2)
+                eivecs.col(1) = cross / sqrt(n);
+              else
+              {
+                // we should never reach this point,
+                // if so the last two eigenvalues are likely to ve very closed to each other
+                eivecs.col(1) = eivecs.col(k).unitOrthogonal();
+              }
+            }
+          }
+
+          // make sure that eivecs[1] is orthogonal to eivecs[2]
+          Scalar d = eivecs.col(1).dot(eivecs.col(k));
+          eivecs.col(1) = (eivecs.col(1) - d * eivecs.col(k)).normalized();
+        }
+
+        eivecs.col(k==2 ? 0 : 2) = eivecs.col(k).cross(eivecs.col(1)).normalized();
+      }
+    }
+    // Rescale back to the original size.
+    eivals *= scale;
+    
+    solver.m_info = Success;
+    solver.m_isInitialized = true;
+    solver.m_eigenvectorsOk = computeEigenvectors;
+  }
+};
+
+// 2x2 direct eigenvalues decomposition, code from Hauke Heibel
+template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,2,false>
+{
+  typedef typename SolverType::MatrixType MatrixType;
+  typedef typename SolverType::RealVectorType VectorType;
+  typedef typename SolverType::Scalar Scalar;
+  
+  static inline void computeRoots(const MatrixType& m, VectorType& roots)
+  {
+    using std::sqrt;
+    const Scalar t0 = Scalar(0.5) * sqrt( abs2(m(0,0)-m(1,1)) + Scalar(4)*m(1,0)*m(1,0));
+    const Scalar t1 = Scalar(0.5) * (m(0,0) + m(1,1));
+    roots(0) = t1 - t0;
+    roots(1) = t1 + t0;
+  }
+  
+  static inline void run(SolverType& solver, const MatrixType& mat, int options)
+  {
+    eigen_assert(mat.cols() == 2 && mat.cols() == mat.rows());
+    eigen_assert((options&~(EigVecMask|GenEigMask))==0
+            && (options&EigVecMask)!=EigVecMask
+            && "invalid option parameter");
+    bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors;
+    
+    MatrixType& eivecs = solver.m_eivec;
+    VectorType& eivals = solver.m_eivalues;
+  
+    // map the matrix coefficients to [-1:1] to avoid over- and underflow.
+    Scalar scale = mat.cwiseAbs().maxCoeff();
+    scale = (std::max)(scale,Scalar(1));
+    MatrixType scaledMat = mat / scale;
+    
+    // Compute the eigenvalues
+    computeRoots(scaledMat,eivals);
+    
+    // compute the eigen vectors
+    if(computeEigenvectors)
+    {
+      scaledMat.diagonal().array () -= eivals(1);
+      Scalar a2 = abs2(scaledMat(0,0));
+      Scalar c2 = abs2(scaledMat(1,1));
+      Scalar b2 = abs2(scaledMat(1,0));
+      if(a2>c2)
+      {
+        eivecs.col(1) << -scaledMat(1,0), scaledMat(0,0);
+        eivecs.col(1) /= sqrt(a2+b2);
+      }
+      else
+      {
+        eivecs.col(1) << -scaledMat(1,1), scaledMat(1,0);
+        eivecs.col(1) /= sqrt(c2+b2);
+      }
+
+      eivecs.col(0) << eivecs.col(1).unitOrthogonal();
+    }
+    
+    // Rescale back to the original size.
+    eivals *= scale;
+    
+    solver.m_info = Success;
+    solver.m_isInitialized = true;
+    solver.m_eigenvectorsOk = computeEigenvectors;
+  }
+};
+
+}
+
+template<typename MatrixType>
+SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
+::computeDirect(const MatrixType& matrix, int options)
+{
+  internal::direct_selfadjoint_eigenvalues<SelfAdjointEigenSolver,Size,NumTraits<Scalar>::IsComplex>::run(*this,matrix,options);
+  return *this;
+}
+
 namespace internal {
 template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
 static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
 {
-  // NOTE this version avoids over & underflow, however since the matrix is prescaled, overflow cannot occur,
-  // and underflows should be meaningless anyway. So I don't any reason to enable this version, but I keep
-  // it here for reference:
-//   RealScalar td = (diag[end-1] - diag[end])*RealScalar(0.5);
-//   RealScalar e = subdiag[end-1];
-//   RealScalar mu = diag[end] - (e / (td + (td>0 ? 1 : -1))) * (e / hypot(td,e));
   RealScalar td = (diag[end-1] - diag[end])*RealScalar(0.5);
-  RealScalar e2 = abs2(subdiag[end-1]);
-  RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
+  RealScalar e = subdiag[end-1];
+  // Note that thanks to scaling, e^2 or td^2 cannot overflow, however they can still
+  // underflow thus leading to inf/NaN values when using the following commented code:
+//   RealScalar e2 = abs2(subdiag[end-1]);
+//   RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
+  // This explain the following, somewhat more complicated, version:
+  RealScalar mu = diag[end] - (e / (td + (td>0 ? 1 : -1))) * (e / hypot(td,e));
+  
   RealScalar x = diag[start] - mu;
   RealScalar z = subdiag[start];
   for (Index k = start; k < end; ++k)
@@ -515,6 +781,9 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
     }
   }
 }
+
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_SELFADJOINTEIGENSOLVER_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h b/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
new file mode 100644
index 00000000000..9380956b5f9
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h
@@ -0,0 +1,92 @@
+/*
+ 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
+ *    Self-adjoint eigenvalues/eigenvectors.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_SAEIGENSOLVER_MKL_H
+#define EIGEN_SAEIGENSOLVER_MKL_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by MKL */
+
+#define EIGEN_MKL_EIG_SELFADJ(EIGTYPE, MKLTYPE, MKLRTYPE, MKLNAME, EIGCOLROW, MKLCOLROW ) \
+template<> inline\
+SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \
+SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW>& matrix, int options) \
+{ \
+  eigen_assert(matrix.cols() == matrix.rows()); \
+  eigen_assert((options&~(EigVecMask|GenEigMask))==0 \
+          && (options&EigVecMask)!=EigVecMask \
+          && "invalid option parameter"); \
+  bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \
+  lapack_int n = matrix.cols(), lda, matrix_order, info; \
+  m_eivalues.resize(n,1); \
+  m_subdiag.resize(n-1); \
+  m_eivec = matrix; \
+\
+  if(n==1) \
+  { \
+    m_eivalues.coeffRef(0,0) = internal::real(matrix.coeff(0,0)); \
+    if(computeEigenvectors) m_eivec.setOnes(n,n); \
+    m_info = Success; \
+    m_isInitialized = true; \
+    m_eigenvectorsOk = computeEigenvectors; \
+    return *this; \
+  } \
+\
+  lda = matrix.outerStride(); \
+  matrix_order=MKLCOLROW; \
+  char jobz, uplo='L'/*, range='A'*/; \
+  jobz = computeEigenvectors ? 'V' : 'N'; \
+\
+  info = LAPACKE_##MKLNAME( matrix_order, jobz, uplo, n, (MKLTYPE*)m_eivec.data(), lda, (MKLRTYPE*)m_eivalues.data() ); \
+  m_info = (info==0) ? Success : NoConvergence; \
+  m_isInitialized = true; \
+  m_eigenvectorsOk = computeEigenvectors; \
+  return *this; \
+}
+
+
+EIGEN_MKL_EIG_SELFADJ(double,   double,        double, dsyev, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_EIG_SELFADJ(float,    float,         float,  ssyev, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8,  float,  cheev, ColMajor, LAPACK_COL_MAJOR)
+
+EIGEN_MKL_EIG_SELFADJ(double,   double,        double, dsyev, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_EIG_SELFADJ(float,    float,         float,  ssyev, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_EIG_SELFADJ(dcomplex, MKL_Complex16, double, zheev, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_EIG_SELFADJ(scomplex, MKL_Complex8,  float,  cheev, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_SAEIGENSOLVER_H
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/Tridiagonalization.h b/extern/Eigen3/Eigen/src/Eigenvalues/Tridiagonalization.h
index ae4cdce7aeb..c34b7b3b801 100644
--- a/extern/Eigen3/Eigen/src/Eigenvalues/Tridiagonalization.h
+++ b/extern/Eigen3/Eigen/src/Eigenvalues/Tridiagonalization.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Jitse Niesen <jitse@maths.leeds.ac.uk>
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRIDIAGONALIZATION_H
 #define EIGEN_TRIDIAGONALIZATION_H
 
+namespace Eigen { 
+
 namespace internal {
   
 template<typename MatrixType> struct TridiagonalizationMatrixTReturnType;
@@ -97,13 +84,13 @@ template<typename _MatrixType> class Tridiagonalization
     typedef internal::TridiagonalizationMatrixTReturnType<MatrixTypeRealView> MatrixTReturnType;
 
     typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
-              const typename Diagonal<const MatrixType>::RealReturnType,
+              typename internal::add_const_on_value_type<typename Diagonal<const MatrixType>::RealReturnType>::type,
               const Diagonal<const MatrixType>
             >::type DiagonalReturnType;
 
     typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
-              const typename Diagonal<
-                Block<const MatrixType,SizeMinusOne,SizeMinusOne> >::RealReturnType,
+              typename internal::add_const_on_value_type<typename Diagonal<
+                Block<const MatrixType,SizeMinusOne,SizeMinusOne> >::RealReturnType>::type,
               const Diagonal<
                 Block<const MatrixType,SizeMinusOne,SizeMinusOne> >
             >::type SubDiagonalReturnType;
@@ -560,9 +547,11 @@ template<typename MatrixType> struct TridiagonalizationMatrixTReturnType
     Index cols() const { return m_matrix.cols(); }
 
   protected:
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
 };
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRIDIAGONALIZATION_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/AlignedBox.h b/extern/Eigen3/Eigen/src/Geometry/AlignedBox.h
index b51deb3f3c3..5830fcd35fc 100644
--- a/extern/Eigen3/Eigen/src/Geometry/AlignedBox.h
+++ b/extern/Eigen3/Eigen/src/Geometry/AlignedBox.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ALIGNEDBOX_H
 #define EIGEN_ALIGNEDBOX_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   *
@@ -190,7 +177,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
   template<typename Derived>
   inline bool contains(const MatrixBase<Derived>& a_p) const
   {
-    const typename internal::nested<Derived,2>::type p(a_p.derived());
+    typename internal::nested<Derived,2>::type p(a_p.derived());
     return (m_min.array()<=p.array()).all() && (p.array()<=m_max.array()).all();
   }
 
@@ -202,7 +189,7 @@ EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF_VECTORIZABLE_FIXED_SIZE(_Scalar,_AmbientDim)
   template<typename Derived>
   inline AlignedBox& extend(const MatrixBase<Derived>& a_p)
   {
-    const typename internal::nested<Derived,2>::type p(a_p.derived());
+    typename internal::nested<Derived,2>::type p(a_p.derived());
     m_min = m_min.cwiseMin(p);
     m_max = m_max.cwiseMax(p);
     return *this;
@@ -310,7 +297,7 @@ template<typename Derived>
 inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const MatrixBase<Derived>& a_p) const
 {
   const typename internal::nested<Derived,2*AmbientDim>::type p(a_p.derived());
-  Scalar dist2 = 0.;
+  Scalar dist2(0);
   Scalar aux;
   for (Index k=0; k<dim(); ++k)
   {
@@ -331,7 +318,7 @@ inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const Matri
 template<typename Scalar,int AmbientDim>
 inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const AlignedBox& b) const
 {
-  Scalar dist2 = 0.;
+  Scalar dist2(0);
   Scalar aux;
   for (Index k=0; k<dim(); ++k)
   {
@@ -349,4 +336,40 @@ inline Scalar AlignedBox<Scalar,AmbientDim>::squaredExteriorDistance(const Align
   return dist2;
 }
 
+/** \defgroup alignedboxtypedefs Global aligned box typedefs
+  *
+  * \ingroup Geometry_Module
+  *
+  * Eigen defines several typedef shortcuts for most common aligned box types.
+  *
+  * The general patterns are the following:
+  *
+  * \c AlignedBoxSizeType where \c Size can be \c 1, \c 2,\c 3,\c 4 for fixed size boxes or \c X for dynamic size,
+  * and where \c Type can be \c i for integer, \c f for float, \c d for double.
+  *
+  * For example, \c AlignedBox3d is a fixed-size 3x3 aligned box type of doubles, and \c AlignedBoxXf is a dynamic-size aligned box of floats.
+  *
+  * \sa class AlignedBox
+  */
+
+#define EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix)    \
+/** \ingroup alignedboxtypedefs */                                 \
+typedef AlignedBox<Type, Size>   AlignedBox##SizeSuffix##TypeSuffix;
+
+#define EIGEN_MAKE_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \
+EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 1, 1) \
+EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 2, 2) \
+EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 3, 3) \
+EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 4, 4) \
+EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Dynamic, X)
+
+EIGEN_MAKE_TYPEDEFS_ALL_SIZES(int,                  i)
+EIGEN_MAKE_TYPEDEFS_ALL_SIZES(float,                f)
+EIGEN_MAKE_TYPEDEFS_ALL_SIZES(double,               d)
+
+#undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES
+#undef EIGEN_MAKE_TYPEDEFS
+
+} // end namespace Eigen
+
 #endif // EIGEN_ALIGNEDBOX_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/AngleAxis.h b/extern/Eigen3/Eigen/src/Geometry/AngleAxis.h
index 0ec4624cf98..67197ac78c3 100644
--- a/extern/Eigen3/Eigen/src/Geometry/AngleAxis.h
+++ b/extern/Eigen3/Eigen/src/Geometry/AngleAxis.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ANGLEAXIS_H
 #define EIGEN_ANGLEAXIS_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class AngleAxis
@@ -144,7 +131,7 @@ public:
     m_angle = Scalar(other.angle());
   }
 
-  inline static const AngleAxis Identity() { return AngleAxis(0, Vector3::UnitX()); }
+  static inline const AngleAxis Identity() { return AngleAxis(0, Vector3::UnitX()); }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
@@ -238,4 +225,6 @@ AngleAxis<Scalar>::toRotationMatrix(void) const
   return res;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_ANGLEAXIS_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/EulerAngles.h b/extern/Eigen3/Eigen/src/Geometry/EulerAngles.h
index d246a6ebf4a..e424d240604 100644
--- a/extern/Eigen3/Eigen/src/Geometry/EulerAngles.h
+++ b/extern/Eigen3/Eigen/src/Geometry/EulerAngles.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_EULERANGLES_H
 #define EIGEN_EULERANGLES_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   *
@@ -92,5 +79,6 @@ MatrixBase<Derived>::eulerAngles(Index a0, Index a1, Index a2) const
   return res;
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_EULERANGLES_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Homogeneous.h b/extern/Eigen3/Eigen/src/Geometry/Homogeneous.h
index 2bc4f7e87e3..df03feb55c6 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Homogeneous.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Homogeneous.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_HOMOGENEOUS_H
 #define EIGEN_HOMOGENEOUS_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class Homogeneous
@@ -121,7 +108,7 @@ template<typename MatrixType,int _Direction> class Homogeneous
     }
 
   protected:
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
 };
 
 /** \geometry_module
@@ -216,8 +203,8 @@ template<typename Scalar, int Dim, int Mode,int Options>
 struct take_matrix_for_product<Transform<Scalar, Dim, Mode, Options> >
 {
   typedef Transform<Scalar, Dim, Mode, Options> TransformType;
-  typedef typename TransformType::ConstAffinePart type;
-  static const type run (const TransformType& x) { return x.affine(); }
+  typedef typename internal::add_const<typename TransformType::ConstAffinePart>::type type;
+  static type run (const TransformType& x) { return x.affine(); }
 };
 
 template<typename Scalar, int Dim, int Options>
@@ -270,8 +257,8 @@ struct homogeneous_left_product_impl<Homogeneous<MatrixType,Vertical>,Lhs>
             .template replicate<MatrixType::ColsAtCompileTime>(m_rhs.cols());
   }
 
-  const typename LhsMatrixTypeCleaned::Nested m_lhs;
-  const typename MatrixType::Nested m_rhs;
+  typename LhsMatrixTypeCleaned::Nested m_lhs;
+  typename MatrixType::Nested m_rhs;
 };
 
 template<typename MatrixType,typename Rhs>
@@ -309,10 +296,12 @@ struct homogeneous_right_product_impl<Homogeneous<MatrixType,Horizontal>,Rhs>
             .template replicate<MatrixType::RowsAtCompileTime>(m_lhs.rows());
   }
 
-  const typename MatrixType::Nested m_lhs;
-  const typename Rhs::Nested m_rhs;
+  typename MatrixType::Nested m_lhs;
+  typename Rhs::Nested m_rhs;
 };
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_HOMOGENEOUS_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Hyperplane.h b/extern/Eigen3/Eigen/src/Geometry/Hyperplane.h
index d85d3e553f8..1b7c7c78c80 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Hyperplane.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Hyperplane.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_HYPERPLANE_H
 #define EIGEN_HYPERPLANE_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class Hyperplane
@@ -277,4 +264,6 @@ protected:
   Coefficients m_coeffs;
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_HYPERPLANE_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/OrthoMethods.h b/extern/Eigen3/Eigen/src/Geometry/OrthoMethods.h
index 52b46988196..11ad5829cda 100644
--- a/extern/Eigen3/Eigen/src/Geometry/OrthoMethods.h
+++ b/extern/Eigen3/Eigen/src/Geometry/OrthoMethods.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ORTHOMETHODS_H
 #define EIGEN_ORTHOMETHODS_H
 
+namespace Eigen { 
+
 /** \geometry_module
   *
   * \returns the cross product of \c *this and \a other
@@ -43,8 +30,8 @@ MatrixBase<Derived>::cross(const MatrixBase<OtherDerived>& other) const
 
   // Note that there is no need for an expression here since the compiler
   // optimize such a small temporary very well (even within a complex expression)
-  const typename internal::nested<Derived,2>::type lhs(derived());
-  const typename internal::nested<OtherDerived,2>::type rhs(other.derived());
+  typename internal::nested<Derived,2>::type lhs(derived());
+  typename internal::nested<OtherDerived,2>::type rhs(other.derived());
   return typename cross_product_return_type<OtherDerived>::type(
     internal::conj(lhs.coeff(1) * rhs.coeff(2) - lhs.coeff(2) * rhs.coeff(1)),
     internal::conj(lhs.coeff(2) * rhs.coeff(0) - lhs.coeff(0) * rhs.coeff(2)),
@@ -56,9 +43,9 @@ namespace internal {
 
 template< int Arch,typename VectorLhs,typename VectorRhs,
           typename Scalar = typename VectorLhs::Scalar,
-          bool Vectorizable = (VectorLhs::Flags&VectorRhs::Flags)&PacketAccessBit>
+          bool Vectorizable = bool((VectorLhs::Flags&VectorRhs::Flags)&PacketAccessBit)>
 struct cross3_impl {
-  inline static typename internal::plain_matrix_type<VectorLhs>::type
+  static inline typename internal::plain_matrix_type<VectorLhs>::type
   run(const VectorLhs& lhs, const VectorRhs& rhs)
   {
     return typename internal::plain_matrix_type<VectorLhs>::type(
@@ -145,7 +132,7 @@ struct unitOrthogonal_selector
   typedef typename NumTraits<Scalar>::Real RealScalar;
   typedef typename Derived::Index Index;
   typedef Matrix<Scalar,2,1> Vector2;
-  inline static VectorType run(const Derived& src)
+  static inline VectorType run(const Derived& src)
   {
     VectorType perp = VectorType::Zero(src.size());
     Index maxi = 0;
@@ -167,7 +154,7 @@ struct unitOrthogonal_selector<Derived,3>
   typedef typename plain_matrix_type<Derived>::type VectorType;
   typedef typename traits<Derived>::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  inline static VectorType run(const Derived& src)
+  static inline VectorType run(const Derived& src)
   {
     VectorType perp;
     /* Let us compute the crossed product of *this with a vector
@@ -205,7 +192,7 @@ template<typename Derived>
 struct unitOrthogonal_selector<Derived,2>
 {
   typedef typename plain_matrix_type<Derived>::type VectorType;
-  inline static VectorType run(const Derived& src)
+  static inline VectorType run(const Derived& src)
   { return VectorType(-conj(src.y()), conj(src.x())).normalized(); }
 };
 
@@ -226,4 +213,6 @@ MatrixBase<Derived>::unitOrthogonal() const
   return internal::unitOrthogonal_selector<Derived>::run(derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_ORTHOMETHODS_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/ParametrizedLine.h b/extern/Eigen3/Eigen/src/Geometry/ParametrizedLine.h
index b90f9c088a2..719a904413d 100644
--- a/extern/Eigen3/Eigen/src/Geometry/ParametrizedLine.h
+++ b/extern/Eigen3/Eigen/src/Geometry/ParametrizedLine.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PARAMETRIZEDLINE_H
 #define EIGEN_PARAMETRIZEDLINE_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class ParametrizedLine
@@ -106,8 +93,16 @@ public:
   VectorType projection(const VectorType& p) const
   { return origin() + direction().dot(p-origin()) * direction(); }
 
+  VectorType pointAt( Scalar t ) const;
+  
+  template <int OtherOptions>
+  Scalar intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
+ 
   template <int OtherOptions>
   Scalar intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
+  
+  template <int OtherOptions>
+  VectorType intersectionPoint(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const;
 
   /** \returns \c *this with scalar type casted to \a NewScalarType
     *
@@ -155,14 +150,46 @@ inline ParametrizedLine<_Scalar, _AmbientDim,_Options>::ParametrizedLine(const H
   origin() = -hyperplane.normal()*hyperplane.offset();
 }
 
-/** \returns the parameter value of the intersection between \c *this and the given hyperplane
+/** \returns the point at \a t along this line
+  */
+template <typename _Scalar, int _AmbientDim, int _Options>
+inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
+ParametrizedLine<_Scalar, _AmbientDim,_Options>::pointAt( _Scalar t ) const
+{
+  return origin() + (direction()*t); 
+}
+
+/** \returns the parameter value of the intersection between \c *this and the given \a hyperplane
   */
 template <typename _Scalar, int _AmbientDim, int _Options>
 template <int OtherOptions>
-inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
+inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersectionParameter(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
 {
   return -(hyperplane.offset()+hyperplane.normal().dot(origin()))
           / hyperplane.normal().dot(direction());
 }
 
+
+/** \deprecated use intersectionParameter()
+  * \returns the parameter value of the intersection between \c *this and the given \a hyperplane
+  */
+template <typename _Scalar, int _AmbientDim, int _Options>
+template <int OtherOptions>
+inline _Scalar ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersection(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
+{
+  return intersectionParameter(hyperplane);
+}
+
+/** \returns the point of the intersection between \c *this and the given hyperplane
+  */
+template <typename _Scalar, int _AmbientDim, int _Options>
+template <int OtherOptions>
+inline typename ParametrizedLine<_Scalar, _AmbientDim,_Options>::VectorType
+ParametrizedLine<_Scalar, _AmbientDim,_Options>::intersectionPoint(const Hyperplane<_Scalar, _AmbientDim, OtherOptions>& hyperplane) const
+{
+  return pointAt(intersectionParameter(hyperplane));
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_PARAMETRIZEDLINE_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Quaternion.h b/extern/Eigen3/Eigen/src/Geometry/Quaternion.h
index 9180db67d84..8792e2da2ae 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Quaternion.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Quaternion.h
@@ -4,27 +4,14 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Mathieu Gautier <mathieu.gautier@cea.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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_QUATERNION_H
 #define EIGEN_QUATERNION_H
+namespace Eigen { 
+
 
 /***************************************************************************
 * Definition of QuaternionBase<Derived>
@@ -38,6 +25,12 @@ template<typename Other,
 struct quaternionbase_assign_impl;
 }
 
+/** \geometry_module \ingroup Geometry_Module
+  * \class QuaternionBase
+  * \brief Base class for quaternion expressions
+  * \tparam Derived derived type (CRTP)
+  * \sa class Quaternion
+  */
 template<class Derived>
 class QuaternionBase : public RotationBase<Derived, 3>
 {
@@ -109,7 +102,7 @@ public:
   /** \returns a quaternion representing an identity rotation
     * \sa MatrixBase::Identity()
     */
-  inline static Quaternion<Scalar> Identity() { return Quaternion<Scalar>(1, 0, 0, 0); }
+  static inline Quaternion<Scalar> Identity() { return Quaternion<Scalar>(1, 0, 0, 0); }
 
   /** \sa QuaternionBase::Identity(), MatrixBase::setIdentity()
     */
@@ -278,6 +271,9 @@ public:
   explicit inline Quaternion(const Quaternion<OtherScalar, OtherOptions>& other)
   { m_coeffs = other.coeffs().template cast<Scalar>(); }
 
+  template<typename Derived1, typename Derived2>
+  static Quaternion FromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b);
+
   inline Coefficients& coeffs() { return m_coeffs;}
   inline const Coefficients& coeffs() const { return m_coeffs;}
 
@@ -287,7 +283,7 @@ protected:
   Coefficients m_coeffs;
   
 #ifndef EIGEN_PARSED_BY_DOXYGEN
-    EIGEN_STRONG_INLINE static void _check_template_params()
+    static EIGEN_STRONG_INLINE void _check_template_params()
     {
       EIGEN_STATIC_ASSERT( (_Options & DontAlign) == _Options,
         INVALID_MATRIX_TEMPLATE_PARAMETERS)
@@ -434,7 +430,7 @@ typedef Map<Quaternion<double>, Aligned>  QuaternionMapAlignedd;
 namespace internal {
 template<int Arch, class Derived1, class Derived2, typename Scalar, int _Options> struct quat_product
 {
-  EIGEN_STRONG_INLINE static Quaternion<Scalar> run(const QuaternionBase<Derived1>& a, const QuaternionBase<Derived2>& b){
+  static EIGEN_STRONG_INLINE Quaternion<Scalar> run(const QuaternionBase<Derived1>& a, const QuaternionBase<Derived2>& b){
     return Quaternion<Scalar>
     (
       a.w() * b.w() - a.x() * b.x() - a.y() * b.y() - a.z() * b.z(),
@@ -544,9 +540,9 @@ QuaternionBase<Derived>::toRotationMatrix(void) const
   // it has to be inlined, and so the return by value is not an issue
   Matrix3 res;
 
-  const Scalar tx  = 2*this->x();
-  const Scalar ty  = 2*this->y();
-  const Scalar tz  = 2*this->z();
+  const Scalar tx  = Scalar(2)*this->x();
+  const Scalar ty  = Scalar(2)*this->y();
+  const Scalar tz  = Scalar(2)*this->z();
   const Scalar twx = tx*this->w();
   const Scalar twy = ty*this->w();
   const Scalar twz = tz*this->w();
@@ -557,15 +553,15 @@ QuaternionBase<Derived>::toRotationMatrix(void) const
   const Scalar tyz = tz*this->y();
   const Scalar tzz = tz*this->z();
 
-  res.coeffRef(0,0) = 1-(tyy+tzz);
+  res.coeffRef(0,0) = Scalar(1)-(tyy+tzz);
   res.coeffRef(0,1) = txy-twz;
   res.coeffRef(0,2) = txz+twy;
   res.coeffRef(1,0) = txy+twz;
-  res.coeffRef(1,1) = 1-(txx+tzz);
+  res.coeffRef(1,1) = Scalar(1)-(txx+tzz);
   res.coeffRef(1,2) = tyz-twx;
   res.coeffRef(2,0) = txz-twy;
   res.coeffRef(2,1) = tyz+twx;
-  res.coeffRef(2,2) = 1-(txx+tyy);
+  res.coeffRef(2,2) = Scalar(1)-(txx+tyy);
 
   return res;
 }
@@ -618,6 +614,27 @@ inline Derived& QuaternionBase<Derived>::setFromTwoVectors(const MatrixBase<Deri
   return derived();
 }
 
+
+/** Returns a quaternion representing a rotation between
+  * the two arbitrary vectors \a a and \a b. In other words, the built
+  * rotation represent a rotation sending the line of direction \a a
+  * to the line of direction \a b, both lines passing through the origin.
+  *
+  * \returns resulting quaternion
+  *
+  * Note that the two input vectors do \b not have to be normalized, and
+  * do not need to have the same norm.
+  */
+template<typename Scalar, int Options>
+template<typename Derived1, typename Derived2>
+Quaternion<Scalar,Options> Quaternion<Scalar,Options>::FromTwoVectors(const MatrixBase<Derived1>& a, const MatrixBase<Derived2>& b)
+{
+    Quaternion quat;
+    quat.setFromTwoVectors(a, b);
+    return quat;
+}
+
+
 /** \returns the multiplicative inverse of \c *this
   * Note that in most cases, i.e., if you simply want the opposite rotation,
   * and/or the quaternion is normalized, then it is enough to use the conjugate.
@@ -709,7 +726,7 @@ struct quaternionbase_assign_impl<Other,3,3>
 {
   typedef typename Other::Scalar Scalar;
   typedef DenseIndex Index;
-  template<class Derived> inline static void run(QuaternionBase<Derived>& q, const Other& mat)
+  template<class Derived> static inline void run(QuaternionBase<Derived>& q, const Other& mat)
   {
     // This algorithm comes from  "Quaternion Calculus and Fast Animation",
     // Ken Shoemake, 1987 SIGGRAPH course notes
@@ -748,7 +765,7 @@ template<typename Other>
 struct quaternionbase_assign_impl<Other,4,1>
 {
   typedef typename Other::Scalar Scalar;
-  template<class Derived> inline static void run(QuaternionBase<Derived>& q, const Other& vec)
+  template<class Derived> static inline void run(QuaternionBase<Derived>& q, const Other& vec)
   {
     q.coeffs() = vec;
   }
@@ -756,4 +773,6 @@ struct quaternionbase_assign_impl<Other,4,1>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_QUATERNION_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Rotation2D.h b/extern/Eigen3/Eigen/src/Geometry/Rotation2D.h
index cf36da1c50c..868e2ef312f 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Rotation2D.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Rotation2D.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ROTATION2D_H
 #define EIGEN_ROTATION2D_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class Rotation2D
@@ -121,7 +108,7 @@ public:
     m_angle = Scalar(other.angle());
   }
 
-  inline static Rotation2D Identity() { return Rotation2D(0); }
+  static inline Rotation2D Identity() { return Rotation2D(0); }
 
   /** \returns \c true if \c *this is approximately equal to \a other, within the precision
     * determined by \a prec.
@@ -162,4 +149,6 @@ Rotation2D<Scalar>::toRotationMatrix(void) const
   return (Matrix2() << cosA, -sinA, sinA, cosA).finished();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_ROTATION2D_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/RotationBase.h b/extern/Eigen3/Eigen/src/Geometry/RotationBase.h
index 1abf06bb640..b88661de6b1 100644
--- a/extern/Eigen3/Eigen/src/Geometry/RotationBase.h
+++ b/extern/Eigen3/Eigen/src/Geometry/RotationBase.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_ROTATIONBASE_H
 #define EIGEN_ROTATIONBASE_H
 
+namespace Eigen { 
+
 // forward declaration
 namespace internal {
 template<typename RotationDerived, typename MatrixType, bool IsVector=MatrixType::IsVectorAtCompileTime>
@@ -115,7 +102,7 @@ struct rotation_base_generic_product_selector<RotationDerived,MatrixType,false>
 {
   enum { Dim = RotationDerived::Dim };
   typedef Matrix<typename RotationDerived::Scalar,Dim,Dim> ReturnType;
-  inline static ReturnType run(const RotationDerived& r, const MatrixType& m)
+  static inline ReturnType run(const RotationDerived& r, const MatrixType& m)
   { return r.toRotationMatrix() * m; }
 };
 
@@ -123,7 +110,7 @@ template<typename RotationDerived, typename Scalar, int Dim, int MaxDim>
 struct rotation_base_generic_product_selector< RotationDerived, DiagonalMatrix<Scalar,Dim,MaxDim>, false >
 {
   typedef Transform<Scalar,Dim,Affine> ReturnType;
-  inline static ReturnType run(const RotationDerived& r, const DiagonalMatrix<Scalar,Dim,MaxDim>& m)
+  static inline ReturnType run(const RotationDerived& r, const DiagonalMatrix<Scalar,Dim,MaxDim>& m)
   {
     ReturnType res(r);
     res.linear() *= m;
@@ -136,7 +123,7 @@ struct rotation_base_generic_product_selector<RotationDerived,OtherVectorType,tr
 {
   enum { Dim = RotationDerived::Dim };
   typedef Matrix<typename RotationDerived::Scalar,Dim,1> ReturnType;
-  EIGEN_STRONG_INLINE static ReturnType run(const RotationDerived& r, const OtherVectorType& v)
+  static EIGEN_STRONG_INLINE ReturnType run(const RotationDerived& r, const OtherVectorType& v)
   {
     return r._transformVector(v);
   }
@@ -192,20 +179,20 @@ namespace internal {
   * \sa class Transform, class Rotation2D, class Quaternion, class AngleAxis
   */
 template<typename Scalar, int Dim>
-inline static Matrix<Scalar,2,2> toRotationMatrix(const Scalar& s)
+static inline Matrix<Scalar,2,2> toRotationMatrix(const Scalar& s)
 {
   EIGEN_STATIC_ASSERT(Dim==2,YOU_MADE_A_PROGRAMMING_MISTAKE)
   return Rotation2D<Scalar>(s).toRotationMatrix();
 }
 
 template<typename Scalar, int Dim, typename OtherDerived>
-inline static Matrix<Scalar,Dim,Dim> toRotationMatrix(const RotationBase<OtherDerived,Dim>& r)
+static inline Matrix<Scalar,Dim,Dim> toRotationMatrix(const RotationBase<OtherDerived,Dim>& r)
 {
   return r.toRotationMatrix();
 }
 
 template<typename Scalar, int Dim, typename OtherDerived>
-inline static const MatrixBase<OtherDerived>& toRotationMatrix(const MatrixBase<OtherDerived>& mat)
+static inline const MatrixBase<OtherDerived>& toRotationMatrix(const MatrixBase<OtherDerived>& mat)
 {
   EIGEN_STATIC_ASSERT(OtherDerived::RowsAtCompileTime==Dim && OtherDerived::ColsAtCompileTime==Dim,
     YOU_MADE_A_PROGRAMMING_MISTAKE)
@@ -214,4 +201,6 @@ inline static const MatrixBase<OtherDerived>& toRotationMatrix(const MatrixBase<
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_ROTATIONBASE_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Scaling.h b/extern/Eigen3/Eigen/src/Geometry/Scaling.h
index c911d13e1d3..8edcac31c74 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Scaling.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Scaling.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SCALING_H
 #define EIGEN_SCALING_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class Scaling
@@ -73,7 +60,12 @@ public:
 
   /** Concatenates a uniform scaling and an affine transformation */
   template<int Dim, int Mode, int Options>
-  inline Transform<Scalar,Dim,Mode> operator* (const Transform<Scalar,Dim, Mode, Options>& t) const;
+  inline Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Mode)> operator* (const Transform<Scalar,Dim, Mode, Options>& t) const
+  {
+   Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Mode)> res = t;
+   res.prescale(factor());
+   return res;
+}
 
   /** Concatenates a uniform scaling and a linear transformation matrix */
   // TODO returns an expression
@@ -169,14 +161,6 @@ UniformScaling<Scalar>::operator* (const Translation<Scalar,Dim>& t) const
   return res;
 }
 
-template<typename Scalar>
-template<int Dim,int Mode,int Options>
-inline Transform<Scalar,Dim,Mode>
-UniformScaling<Scalar>::operator* (const Transform<Scalar,Dim, Mode, Options>& t) const
-{
-  Transform<Scalar,Dim,Mode> res = t;
-  res.prescale(factor());
-  return res;
-}
+} // end namespace Eigen
 
 #endif // EIGEN_SCALING_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Transform.h b/extern/Eigen3/Eigen/src/Geometry/Transform.h
index a694673ebed..4c1ef8eaade 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Transform.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Transform.h
@@ -5,28 +5,15 @@
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2010 Hauke Heibel <hauke.heibel@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRANSFORM_H
 #define EIGEN_TRANSFORM_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename Transform>
@@ -37,7 +24,7 @@ struct transform_traits
     Dim = Transform::Dim,
     HDim = Transform::HDim,
     Mode = Transform::Mode,
-    IsProjective = (Mode==Projective)
+    IsProjective = (int(Mode)==int(Projective))
   };
 };
 
@@ -207,9 +194,9 @@ public:
   /** type of the matrix used to represent the linear part of the transformation */
   typedef Matrix<Scalar,Dim,Dim,Options> LinearMatrixType;
   /** type of read/write reference to the linear part of the transformation */
-  typedef Block<MatrixType,Dim,Dim> LinearPart;
+  typedef Block<MatrixType,Dim,Dim,int(Mode)==(AffineCompact)> LinearPart;
   /** type of read reference to the linear part of the transformation */
-  typedef const Block<ConstMatrixType,Dim,Dim> ConstLinearPart;
+  typedef const Block<ConstMatrixType,Dim,Dim,int(Mode)==(AffineCompact)> ConstLinearPart;
   /** type of read/write reference to the affine part of the transformation */
   typedef typename internal::conditional<int(Mode)==int(AffineCompact),
                               MatrixType&,
@@ -221,9 +208,9 @@ public:
   /** type of a vector */
   typedef Matrix<Scalar,Dim,1> VectorType;
   /** type of a read/write reference to the translation part of the rotation */
-  typedef Block<MatrixType,Dim,1> TranslationPart;
+  typedef Block<MatrixType,Dim,1,int(Mode)==(AffineCompact)> TranslationPart;
   /** type of a read reference to the translation part of the rotation */
-  typedef const Block<ConstMatrixType,Dim,1> ConstTranslationPart;
+  typedef const Block<ConstMatrixType,Dim,1,int(Mode)==(AffineCompact)> ConstTranslationPart;
   /** corresponding translation type */
   typedef Translation<Scalar,Dim> TranslationType;
   
@@ -279,6 +266,9 @@ public:
   template<typename OtherDerived>
   inline explicit Transform(const EigenBase<OtherDerived>& other)
   {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar,typename OtherDerived::Scalar>::value),
+      YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY);
+
     check_template_params();
     internal::transform_construct_from_matrix<OtherDerived,Mode,Options,Dim,HDim>::run(this, other.derived());
   }
@@ -287,6 +277,9 @@ public:
   template<typename OtherDerived>
   inline Transform& operator=(const EigenBase<OtherDerived>& other)
   {
+    EIGEN_STATIC_ASSERT((internal::is_same<Scalar,typename OtherDerived::Scalar>::value),
+      YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY);
+
     internal::transform_construct_from_matrix<OtherDerived,Mode,Options,Dim,HDim>::run(this, other.derived());
     return *this;
   }
@@ -376,9 +369,9 @@ public:
   inline MatrixType& matrix() { return m_matrix; }
 
   /** \returns a read-only expression of the linear part of the transformation */
-  inline ConstLinearPart linear() const { return m_matrix.template block<Dim,Dim>(0,0); }
+  inline ConstLinearPart linear() const { return ConstLinearPart(m_matrix,0,0); }
   /** \returns a writable expression of the linear part of the transformation */
-  inline LinearPart linear() { return m_matrix.template block<Dim,Dim>(0,0); }
+  inline LinearPart linear() { return LinearPart(m_matrix,0,0); }
 
   /** \returns a read-only expression of the Dim x HDim affine part of the transformation */
   inline ConstAffinePart affine() const { return take_affine_part::run(m_matrix); }
@@ -386,9 +379,9 @@ public:
   inline AffinePart affine() { return take_affine_part::run(m_matrix); }
 
   /** \returns a read-only expression of the translation vector of the transformation */
-  inline ConstTranslationPart translation() const { return m_matrix.template block<Dim,1>(0,Dim); }
+  inline ConstTranslationPart translation() const { return ConstTranslationPart(m_matrix,0,Dim); }
   /** \returns a writable expression of the translation vector of the transformation */
-  inline TranslationPart translation() { return m_matrix.template block<Dim,1>(0,Dim); }
+  inline TranslationPart translation() { return TranslationPart(m_matrix,0,Dim); }
 
   /** \returns an expression of the product between the transform \c *this and a matrix expression \a other
     *
@@ -460,15 +453,40 @@ public:
   {
     return internal::transform_transform_product_impl<Transform,Transform>::run(*this,other);
   }
-
+  
+  #ifdef __INTEL_COMPILER
+private:
+  // this intermediate structure permits to workaround a bug in ICC 11:
+  //   error: template instantiation resulted in unexpected function type of "Eigen::Transform<double, 3, 32, 0>
+  //             (const Eigen::Transform<double, 3, 2, 0> &) const"
+  //  (the meaning of a name may have changed since the template declaration -- the type of the template is:
+  // "Eigen::internal::transform_transform_product_impl<Eigen::Transform<double, 3, 32, 0>,
+  //     Eigen::Transform<double, 3, Mode, Options>, <expression>>::ResultType (const Eigen::Transform<double, 3, Mode, Options> &) const")
+  // 
+  template<int OtherMode,int OtherOptions> struct icc_11_workaround
+  {
+    typedef internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> > ProductType;
+    typedef typename ProductType::ResultType ResultType;
+  };
+  
+public:
+  /** Concatenates two different transformations */
+  template<int OtherMode,int OtherOptions>
+  inline typename icc_11_workaround<OtherMode,OtherOptions>::ResultType
+    operator * (const Transform<Scalar,Dim,OtherMode,OtherOptions>& other) const
+  {
+    typedef typename icc_11_workaround<OtherMode,OtherOptions>::ProductType ProductType;
+    return ProductType::run(*this,other);
+  }
+  #else
   /** Concatenates two different transformations */
   template<int OtherMode,int OtherOptions>
-  inline const typename internal::transform_transform_product_impl<
-    Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::ResultType
+  inline typename internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::ResultType
     operator * (const Transform<Scalar,Dim,OtherMode,OtherOptions>& other) const
   {
     return internal::transform_transform_product_impl<Transform,Transform<Scalar,Dim,OtherMode,OtherOptions> >::run(*this,other);
   }
+  #endif
 
   /** \sa MatrixBase::setIdentity() */
   void setIdentity() { m_matrix.setIdentity(); }
@@ -512,7 +530,12 @@ public:
 
   inline Transform& operator=(const UniformScaling<Scalar>& t);
   inline Transform& operator*=(const UniformScaling<Scalar>& s) { return scale(s.factor()); }
-  inline Transform operator*(const UniformScaling<Scalar>& s) const;
+  inline Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Isometry)> operator*(const UniformScaling<Scalar>& s) const
+  {
+    Transform<Scalar,Dim,(int(Mode)==int(Isometry)?Affine:Isometry),Options> res = *this;
+    res.scale(s.factor());
+    return res;
+  }
 
   inline Transform& operator*=(const DiagonalMatrix<Scalar,Dim>& s) { linear() *= s; return *this; }
 
@@ -571,7 +594,7 @@ public:
     if(int(Mode)!=int(AffineCompact))
     {
       matrix().template block<1,Dim>(Dim,0).setZero();
-      matrix().coeffRef(Dim,Dim) = 1;
+      matrix().coeffRef(Dim,Dim) = Scalar(1);
     }
   }
 
@@ -608,7 +631,7 @@ public:
   
 protected:
   #ifndef EIGEN_PARSED_BY_DOXYGEN
-    EIGEN_STRONG_INLINE static void check_template_params()
+    static EIGEN_STRONG_INLINE void check_template_params()
     {
       EIGEN_STATIC_ASSERT((Options & (DontAlign|RowMajor)) == Options, INVALID_MATRIX_TEMPLATE_PARAMETERS)
     }
@@ -941,14 +964,6 @@ inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::o
 }
 
 template<typename Scalar, int Dim, int Mode, int Options>
-inline Transform<Scalar,Dim,Mode,Options> Transform<Scalar,Dim,Mode,Options>::operator*(const UniformScaling<Scalar>& s) const
-{
-  Transform res = *this;
-  res.scale(s.factor());
-  return res;
-}
-
-template<typename Scalar, int Dim, int Mode, int Options>
 template<typename Derived>
 inline Transform<Scalar,Dim,Mode,Options>& Transform<Scalar,Dim,Mode,Options>::operator=(const RotationBase<Derived,Dim>& r)
 {
@@ -1219,7 +1234,7 @@ struct transform_right_product_impl< TransformType, MatrixType, 0 >
 {
   typedef typename MatrixType::PlainObject ResultType;
 
-  EIGEN_STRONG_INLINE static ResultType run(const TransformType& T, const MatrixType& other)
+  static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
   {
     return T.matrix() * other;
   }
@@ -1237,11 +1252,11 @@ struct transform_right_product_impl< TransformType, MatrixType, 1 >
 
   typedef typename MatrixType::PlainObject ResultType;
 
-  EIGEN_STRONG_INLINE static ResultType run(const TransformType& T, const MatrixType& other)
+  static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
   {
     EIGEN_STATIC_ASSERT(OtherRows==HDim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES);
 
-    typedef Block<ResultType, Dim, OtherCols> TopLeftLhs;
+    typedef Block<ResultType, Dim, OtherCols, int(MatrixType::RowsAtCompileTime)==Dim> TopLeftLhs;
 
     ResultType res(other.rows(),other.cols());
     TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() = T.affine() * other;
@@ -1263,15 +1278,13 @@ struct transform_right_product_impl< TransformType, MatrixType, 2 >
 
   typedef typename MatrixType::PlainObject ResultType;
 
-  EIGEN_STRONG_INLINE static ResultType run(const TransformType& T, const MatrixType& other)
+  static EIGEN_STRONG_INLINE ResultType run(const TransformType& T, const MatrixType& other)
   {
     EIGEN_STATIC_ASSERT(OtherRows==Dim, YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES);
 
-    typedef Block<ResultType, Dim, OtherCols> TopLeftLhs;
-
-    ResultType res(other.rows(),other.cols());
-    TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() = T.linear() * other;
-    TopLeftLhs(res, 0, 0, Dim, other.cols()).colwise() += T.translation();
+    typedef Block<ResultType, Dim, OtherCols, true> TopLeftLhs;
+    ResultType res(Replicate<typename TransformType::ConstTranslationPart, 1, OtherCols>(T.translation(),1,other.cols()));
+    TopLeftLhs(res, 0, 0, Dim, other.cols()).noalias() += T.linear() * other;
 
     return res;
   }
@@ -1422,4 +1435,6 @@ struct transform_transform_product_impl<Transform<Scalar,Dim,Projective,LhsOptio
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRANSFORM_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Translation.h b/extern/Eigen3/Eigen/src/Geometry/Translation.h
index d8fe50f987e..7fda179cc35 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Translation.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Translation.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_TRANSLATION_H
 #define EIGEN_TRANSLATION_H
 
+namespace Eigen { 
+
 /** \geometry_module \ingroup Geometry_Module
   *
   * \class Translation
@@ -54,6 +41,8 @@ public:
   typedef Matrix<Scalar,Dim,Dim> LinearMatrixType;
   /** corresponding affine transformation type */
   typedef Transform<Scalar,Dim,Affine> AffineTransformType;
+  /** corresponding isometric transformation type */
+  typedef Transform<Scalar,Dim,Isometry> IsometryTransformType;
 
 protected:
 
@@ -114,8 +103,8 @@ public:
 
   /** Concatenates a translation and a rotation */
   template<typename Derived>
-  inline AffineTransformType operator*(const RotationBase<Derived,Dim>& r) const
-  { return *this * r.toRotationMatrix(); }
+  inline IsometryTransformType operator*(const RotationBase<Derived,Dim>& r) const
+  { return *this * IsometryTransformType(r); }
 
   /** \returns the concatenation of a linear transformation \a l with the translation \a t */
   // its a nightmare to define a templated friend function outside its declaration
@@ -212,4 +201,6 @@ Translation<Scalar,Dim>::operator* (const EigenBase<OtherDerived>& linear) const
   return res;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_TRANSLATION_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/Umeyama.h b/extern/Eigen3/Eigen/src/Geometry/Umeyama.h
index b50f461730e..ac0939cde52 100644
--- a/extern/Eigen3/Eigen/src/Geometry/Umeyama.h
+++ b/extern/Eigen3/Eigen/src/Geometry/Umeyama.h
@@ -3,24 +3,9 @@
 //
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_UMEYAMA_H
 #define EIGEN_UMEYAMA_H
@@ -31,6 +16,8 @@
 // * Eigen/SVD
 // * Eigen/Array
 
+namespace Eigen { 
+
 #ifndef EIGEN_PARSED_BY_DOXYGEN
 
 // These helpers are required since it allows to use mixed types as parameters
@@ -180,4 +167,6 @@ umeyama(const MatrixBase<Derived>& src, const MatrixBase<OtherDerived>& dst, boo
   return Rt;
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_UMEYAMA_H
diff --git a/extern/Eigen3/Eigen/src/Geometry/arch/Geometry_SSE.h b/extern/Eigen3/Eigen/src/Geometry/arch/Geometry_SSE.h
index 2af32678d1c..3d8284f2d0c 100644
--- a/extern/Eigen3/Eigen/src/Geometry/arch/Geometry_SSE.h
+++ b/extern/Eigen3/Eigen/src/Geometry/arch/Geometry_SSE.h
@@ -4,34 +4,21 @@
 // Copyright (C) 2009 Rohit Garg <rpg.314@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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_GEOMETRY_SSE_H
 #define EIGEN_GEOMETRY_SSE_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<class Derived, class OtherDerived>
 struct quat_product<Architecture::SSE, Derived, OtherDerived, float, Aligned>
 {
-  inline static Quaternion<float> run(const QuaternionBase<Derived>& _a, const QuaternionBase<OtherDerived>& _b)
+  static inline Quaternion<float> run(const QuaternionBase<Derived>& _a, const QuaternionBase<OtherDerived>& _b)
   {
     const __m128 mask = _mm_castsi128_ps(_mm_setr_epi32(0,0,0,0x80000000));
     Quaternion<float> res;
@@ -53,7 +40,7 @@ struct quat_product<Architecture::SSE, Derived, OtherDerived, float, Aligned>
 template<typename VectorLhs,typename VectorRhs>
 struct cross3_impl<Architecture::SSE,VectorLhs,VectorRhs,float,true>
 {
-  inline static typename plain_matrix_type<VectorLhs>::type
+  static inline typename plain_matrix_type<VectorLhs>::type
   run(const VectorLhs& lhs, const VectorRhs& rhs)
   {
     __m128 a = lhs.template packet<VectorLhs::Flags&AlignedBit ? Aligned : Unaligned>(0);
@@ -72,7 +59,7 @@ struct cross3_impl<Architecture::SSE,VectorLhs,VectorRhs,float,true>
 template<class Derived, class OtherDerived>
 struct quat_product<Architecture::SSE, Derived, OtherDerived, double, Aligned>
 {
-  inline static Quaternion<double> run(const QuaternionBase<Derived>& _a, const QuaternionBase<OtherDerived>& _b)
+  static inline Quaternion<double> run(const QuaternionBase<Derived>& _a, const QuaternionBase<OtherDerived>& _b)
   {
   const Packet2d mask = _mm_castsi128_pd(_mm_set_epi32(0x0,0x0,0x80000000,0x0));
 
@@ -123,4 +110,6 @@ struct quat_product<Architecture::SSE, Derived, OtherDerived, double, Aligned>
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_GEOMETRY_SSE_H
diff --git a/extern/Eigen3/Eigen/src/Householder/BlockHouseholder.h b/extern/Eigen3/Eigen/src/Householder/BlockHouseholder.h
index 23ce1bfbd46..1991c652738 100644
--- a/extern/Eigen3/Eigen/src/Householder/BlockHouseholder.h
+++ b/extern/Eigen3/Eigen/src/Householder/BlockHouseholder.h
@@ -4,30 +4,17 @@
 // Copyright (C) 2010 Vincent Lejeune
 // Copyright (C) 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BLOCK_HOUSEHOLDER_H
 #define EIGEN_BLOCK_HOUSEHOLDER_H
 
 // This file contains some helper function to deal with block householder reflectors
 
+namespace Eigen { 
+
 namespace internal {
 
 /** \internal */
@@ -64,7 +51,7 @@ void apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vec
   Matrix<typename MatrixType::Scalar, TFactorSize, TFactorSize> T(nbVecs,nbVecs);
   make_block_householder_triangular_factor(T, vectors, hCoeffs);
 
-  const TriangularView<VectorsType, UnitLower>& V(vectors);
+  const TriangularView<const VectorsType, UnitLower>& V(vectors);
 
   // A -= V T V^* A
   Matrix<typename MatrixType::Scalar,VectorsType::ColsAtCompileTime,MatrixType::ColsAtCompileTime,0,
@@ -76,4 +63,6 @@ void apply_block_householder_on_the_left(MatrixType& mat, const VectorsType& vec
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_BLOCK_HOUSEHOLDER_H
diff --git a/extern/Eigen3/Eigen/src/Householder/Householder.h b/extern/Eigen3/Eigen/src/Householder/Householder.h
index 74139c0dcce..3f64b7dde2f 100644
--- a/extern/Eigen3/Eigen/src/Householder/Householder.h
+++ b/extern/Eigen3/Eigen/src/Householder/Householder.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_HOUSEHOLDER_H
 #define EIGEN_HOUSEHOLDER_H
 
+namespace Eigen { 
+
 namespace internal {
 template<int n> struct decrement_size
 {
@@ -35,6 +22,22 @@ template<int n> struct decrement_size
 };
 }
 
+/** Computes the elementary reflector H such that:
+  * \f$ H *this = [ beta 0 ... 0]^T \f$
+  * where the transformation H is:
+  * \f$ H = I - tau v v^*\f$
+  * and the vector v is:
+  * \f$ v^T = [1 essential^T] \f$
+  *
+  * The essential part of the vector \c v is stored in *this.
+  * 
+  * On output:
+  * \param tau the scaling factor of the Householder transformation
+  * \param beta the result of H * \c *this
+  *
+  * \sa MatrixBase::makeHouseholder(), MatrixBase::applyHouseholderOnTheLeft(),
+  *     MatrixBase::applyHouseholderOnTheRight()
+  */
 template<typename Derived>
 void MatrixBase<Derived>::makeHouseholderInPlace(Scalar& tau, RealScalar& beta)
 {
@@ -51,7 +54,7 @@ void MatrixBase<Derived>::makeHouseholderInPlace(Scalar& tau, RealScalar& beta)
   *
   * On output:
   * \param essential the essential part of the vector \c v
-  * \param tau the scaling factor of the householder transformation
+  * \param tau the scaling factor of the Householder transformation
   * \param beta the result of H * \c *this
   *
   * \sa MatrixBase::makeHouseholderInPlace(), MatrixBase::applyHouseholderOnTheLeft(),
@@ -86,6 +89,21 @@ void MatrixBase<Derived>::makeHouseholder(
   }
 }
 
+/** Apply the elementary reflector H given by
+  * \f$ H = I - tau v v^*\f$
+  * with
+  * \f$ v^T = [1 essential^T] \f$
+  * from the left to a vector or matrix.
+  *
+  * On input:
+  * \param essential the essential part of the vector \c v
+  * \param tau the scaling factor of the Householder transformation
+  * \param workspace a pointer to working space with at least
+  *                  this->cols() * essential.size() entries
+  *
+  * \sa MatrixBase::makeHouseholder(), MatrixBase::makeHouseholderInPlace(), 
+  *     MatrixBase::applyHouseholderOnTheRight()
+  */
 template<typename Derived>
 template<typename EssentialPart>
 void MatrixBase<Derived>::applyHouseholderOnTheLeft(
@@ -108,6 +126,21 @@ void MatrixBase<Derived>::applyHouseholderOnTheLeft(
   }
 }
 
+/** Apply the elementary reflector H given by
+  * \f$ H = I - tau v v^*\f$
+  * with
+  * \f$ v^T = [1 essential^T] \f$
+  * from the right to a vector or matrix.
+  *
+  * On input:
+  * \param essential the essential part of the vector \c v
+  * \param tau the scaling factor of the Householder transformation
+  * \param workspace a pointer to working space with at least
+  *                  this->cols() * essential.size() entries
+  *
+  * \sa MatrixBase::makeHouseholder(), MatrixBase::makeHouseholderInPlace(), 
+  *     MatrixBase::applyHouseholderOnTheLeft()
+  */
 template<typename Derived>
 template<typename EssentialPart>
 void MatrixBase<Derived>::applyHouseholderOnTheRight(
@@ -130,4 +163,6 @@ void MatrixBase<Derived>::applyHouseholderOnTheRight(
   }
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_HOUSEHOLDER_H
diff --git a/extern/Eigen3/Eigen/src/Householder/HouseholderSequence.h b/extern/Eigen3/Eigen/src/Householder/HouseholderSequence.h
index 717f29c99e9..1e71e16a785 100644
--- a/extern/Eigen3/Eigen/src/Householder/HouseholderSequence.h
+++ b/extern/Eigen3/Eigen/src/Householder/HouseholderSequence.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_HOUSEHOLDER_SEQUENCE_H
 #define EIGEN_HOUSEHOLDER_SEQUENCE_H
 
+namespace Eigen { 
+
 /** \ingroup Householder_Module
   * \householder_module
   * \class HouseholderSequence
@@ -237,13 +224,20 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
     ConjugateReturnType inverse() const { return adjoint(); }
 
     /** \internal */
-    template<typename DestType> void evalTo(DestType& dst) const
+    template<typename DestType> inline void evalTo(DestType& dst) const
     {
-      Index vecs = m_length;
-      // FIXME find a way to pass this temporary if the user wants to
       Matrix<Scalar, DestType::RowsAtCompileTime, 1,
-             AutoAlign|ColMajor, DestType::MaxRowsAtCompileTime, 1> temp(rows());
-      if(    internal::is_same<typename internal::remove_all<VectorsType>::type,DestType>::value
+             AutoAlign|ColMajor, DestType::MaxRowsAtCompileTime, 1> workspace(rows());
+      evalTo(dst, workspace);
+    }
+
+    /** \internal */
+    template<typename Dest, typename Workspace>
+    void evalTo(Dest& dst, Workspace& workspace) const
+    {
+      workspace.resize(rows());
+      Index vecs = m_length;
+      if(    internal::is_same<typename internal::remove_all<VectorsType>::type,Dest>::value
           && internal::extract_data(dst) == internal::extract_data(m_vectors))
       {
         // in-place
@@ -254,10 +248,10 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
           Index cornerSize = rows() - k - m_shift;
           if(m_trans)
             dst.bottomRightCorner(cornerSize, cornerSize)
-            .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0));
+               .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), workspace.data());
           else
             dst.bottomRightCorner(cornerSize, cornerSize)
-              .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0));
+               .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), workspace.data());
 
           // clear the off diagonal vector
           dst.col(k).tail(rows()-k-1).setZero();
@@ -274,10 +268,10 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
           Index cornerSize = rows() - k - m_shift;
           if(m_trans)
             dst.bottomRightCorner(cornerSize, cornerSize)
-            .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0));
+               .applyHouseholderOnTheRight(essentialVector(k), m_coeffs.coeff(k), &workspace.coeffRef(0));
           else
             dst.bottomRightCorner(cornerSize, cornerSize)
-              .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), &temp.coeffRef(0));
+               .applyHouseholderOnTheLeft(essentialVector(k), m_coeffs.coeff(k), &workspace.coeffRef(0));
         }
       }
     }
@@ -285,24 +279,40 @@ template<typename VectorsType, typename CoeffsType, int Side> class HouseholderS
     /** \internal */
     template<typename Dest> inline void applyThisOnTheRight(Dest& dst) const
     {
-      Matrix<Scalar,1,Dest::RowsAtCompileTime> temp(dst.rows());
+      Matrix<Scalar,1,Dest::RowsAtCompileTime,RowMajor,1,Dest::MaxRowsAtCompileTime> workspace(dst.rows());
+      applyThisOnTheRight(dst, workspace);
+    }
+
+    /** \internal */
+    template<typename Dest, typename Workspace>
+    inline void applyThisOnTheRight(Dest& dst, Workspace& workspace) const
+    {
+      workspace.resize(dst.rows());
       for(Index k = 0; k < m_length; ++k)
       {
         Index actual_k = m_trans ? m_length-k-1 : k;
         dst.rightCols(rows()-m_shift-actual_k)
-           .applyHouseholderOnTheRight(essentialVector(actual_k), m_coeffs.coeff(actual_k), &temp.coeffRef(0));
+           .applyHouseholderOnTheRight(essentialVector(actual_k), m_coeffs.coeff(actual_k), workspace.data());
       }
     }
 
     /** \internal */
     template<typename Dest> inline void applyThisOnTheLeft(Dest& dst) const
     {
-      Matrix<Scalar,1,Dest::ColsAtCompileTime> temp(dst.cols());
+      Matrix<Scalar,1,Dest::ColsAtCompileTime,RowMajor,1,Dest::MaxColsAtCompileTime> workspace(dst.cols());
+      applyThisOnTheLeft(dst, workspace);
+    }
+
+    /** \internal */
+    template<typename Dest, typename Workspace>
+    inline void applyThisOnTheLeft(Dest& dst, Workspace& workspace) const
+    {
+      workspace.resize(dst.cols());
       for(Index k = 0; k < m_length; ++k)
       {
         Index actual_k = m_trans ? k : m_length-k-1;
         dst.bottomRows(rows()-m_shift-actual_k)
-           .applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), &temp.coeffRef(0));
+           .applyHouseholderOnTheLeft(essentialVector(actual_k), m_coeffs.coeff(actual_k), workspace.data());
       }
     }
 
@@ -426,4 +436,6 @@ HouseholderSequence<VectorsType,CoeffsType,OnTheRight> rightHouseholderSequence(
   return HouseholderSequence<VectorsType,CoeffsType,OnTheRight>(v, h);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_HOUSEHOLDER_SEQUENCE_H
diff --git a/extern/Eigen3/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h
new file mode 100644
index 00000000000..73ca9bfde6a
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/BasicPreconditioners.h
@@ -0,0 +1,149 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_BASIC_PRECONDITIONERS_H
+#define EIGEN_BASIC_PRECONDITIONERS_H
+
+namespace Eigen { 
+
+/** \ingroup IterativeLinearSolvers_Module
+  * \brief A preconditioner based on the digonal entries
+  *
+  * This class allows to approximately solve for A.x = b problems assuming A is a diagonal matrix.
+  * In other words, this preconditioner neglects all off diagonal entries and, in Eigen's language, solves for:
+  * \code
+  * A.diagonal().asDiagonal() . x = b
+  * \endcode
+  *
+  * \tparam _Scalar the type of the scalar.
+  *
+  * This preconditioner is suitable for both selfadjoint and general problems.
+  * The diagonal entries are pre-inverted and stored into a dense vector.
+  *
+  * \note A variant that has yet to be implemented would attempt to preserve the norm of each column.
+  *
+  */
+template <typename _Scalar>
+class DiagonalPreconditioner
+{
+    typedef _Scalar Scalar;
+    typedef Matrix<Scalar,Dynamic,1> Vector;
+    typedef typename Vector::Index Index;
+
+  public:
+    // this typedef is only to export the scalar type and compile-time dimensions to solve_retval
+    typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
+
+    DiagonalPreconditioner() : m_isInitialized(false) {}
+
+    template<typename MatType>
+    DiagonalPreconditioner(const MatType& mat) : m_invdiag(mat.cols())
+    {
+      compute(mat);
+    }
+
+    Index rows() const { return m_invdiag.size(); }
+    Index cols() const { return m_invdiag.size(); }
+    
+    template<typename MatType>
+    DiagonalPreconditioner& analyzePattern(const MatType& )
+    {
+      return *this;
+    }
+    
+    template<typename MatType>
+    DiagonalPreconditioner& factorize(const MatType& mat)
+    {
+      m_invdiag.resize(mat.cols());
+      for(int j=0; j<mat.outerSize(); ++j)
+      {
+        typename MatType::InnerIterator it(mat,j);
+        while(it && it.index()!=j) ++it;
+        if(it && it.index()==j)
+          m_invdiag(j) = Scalar(1)/it.value();
+        else
+          m_invdiag(j) = 0;
+      }
+      m_isInitialized = true;
+      return *this;
+    }
+    
+    template<typename MatType>
+    DiagonalPreconditioner& compute(const MatType& mat)
+    {
+      return factorize(mat);
+    }
+
+    template<typename Rhs, typename Dest>
+    void _solve(const Rhs& b, Dest& x) const
+    {
+      x = m_invdiag.array() * b.array() ;
+    }
+
+    template<typename Rhs> inline const internal::solve_retval<DiagonalPreconditioner, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "DiagonalPreconditioner is not initialized.");
+      eigen_assert(m_invdiag.size()==b.rows()
+                && "DiagonalPreconditioner::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<DiagonalPreconditioner, Rhs>(*this, b.derived());
+    }
+
+  protected:
+    Vector m_invdiag;
+    bool m_isInitialized;
+};
+
+namespace internal {
+
+template<typename _MatrixType, typename Rhs>
+struct solve_retval<DiagonalPreconditioner<_MatrixType>, Rhs>
+  : solve_retval_base<DiagonalPreconditioner<_MatrixType>, Rhs>
+{
+  typedef DiagonalPreconditioner<_MatrixType> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+}
+
+/** \ingroup IterativeLinearSolvers_Module
+  * \brief A naive preconditioner which approximates any matrix as the identity matrix
+  *
+  * \sa class DiagonalPreconditioner
+  */
+class IdentityPreconditioner
+{
+  public:
+
+    IdentityPreconditioner() {}
+
+    template<typename MatrixType>
+    IdentityPreconditioner(const MatrixType& ) {}
+    
+    template<typename MatrixType>
+    IdentityPreconditioner& analyzePattern(const MatrixType& ) { return *this; }
+    
+    template<typename MatrixType>
+    IdentityPreconditioner& factorize(const MatrixType& ) { return *this; }
+
+    template<typename MatrixType>
+    IdentityPreconditioner& compute(const MatrixType& ) { return *this; }
+    
+    template<typename Rhs>
+    inline const Rhs& solve(const Rhs& b) const { return b; }
+};
+
+} // end namespace Eigen
+
+#endif // EIGEN_BASIC_PRECONDITIONERS_H
diff --git a/extern/Eigen3/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
new file mode 100644
index 00000000000..126341be8d8
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h
@@ -0,0 +1,254 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_BICGSTAB_H
+#define EIGEN_BICGSTAB_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal Low-level bi conjugate gradient stabilized algorithm
+  * \param mat The matrix A
+  * \param rhs The right hand side vector b
+  * \param x On input and initial solution, on output the computed solution.
+  * \param precond A preconditioner being able to efficiently solve for an
+  *                approximation of Ax=b (regardless of b)
+  * \param iters On input the max number of iteration, on output the number of performed iterations.
+  * \param tol_error On input the tolerance error, on output an estimation of the relative error.
+  * \return false in the case of numerical issue, for example a break down of BiCGSTAB. 
+  */
+template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
+bool bicgstab(const MatrixType& mat, const Rhs& rhs, Dest& x,
+              const Preconditioner& precond, int& iters,
+              typename Dest::RealScalar& tol_error)
+{
+  using std::sqrt;
+  using std::abs;
+  typedef typename Dest::RealScalar RealScalar;
+  typedef typename Dest::Scalar Scalar;
+  typedef Matrix<Scalar,Dynamic,1> VectorType;
+  RealScalar tol = tol_error;
+  int maxIters = iters;
+
+  int n = mat.cols();
+  VectorType r  = rhs - mat * x;
+  VectorType r0 = r;
+  
+  RealScalar r0_sqnorm = r0.squaredNorm();
+  Scalar rho    = 1;
+  Scalar alpha  = 1;
+  Scalar w      = 1;
+  
+  VectorType v = VectorType::Zero(n), p = VectorType::Zero(n);
+  VectorType y(n),  z(n);
+  VectorType kt(n), ks(n);
+
+  VectorType s(n), t(n);
+
+  RealScalar tol2 = tol*tol;
+  int i = 0;
+
+  while ( r.squaredNorm()/r0_sqnorm > tol2 && i<maxIters )
+  {
+    Scalar rho_old = rho;
+
+    rho = r0.dot(r);
+    if (rho == Scalar(0)) return false; /* New search directions cannot be found */
+    Scalar beta = (rho/rho_old) * (alpha / w);
+    p = r + beta * (p - w * v);
+    
+    y = precond.solve(p);
+    
+    v.noalias() = mat * y;
+
+    alpha = rho / r0.dot(v);
+    s = r - alpha * v;
+
+    z = precond.solve(s);
+    t.noalias() = mat * z;
+
+    w = t.dot(s) / t.squaredNorm();
+    x += alpha * y + w * z;
+    r = s - w * t;
+    ++i;
+  }
+  tol_error = sqrt(r.squaredNorm()/r0_sqnorm);
+  iters = i;
+  return true; 
+}
+
+}
+
+template< typename _MatrixType,
+          typename _Preconditioner = DiagonalPreconditioner<typename _MatrixType::Scalar> >
+class BiCGSTAB;
+
+namespace internal {
+
+template< typename _MatrixType, typename _Preconditioner>
+struct traits<BiCGSTAB<_MatrixType,_Preconditioner> >
+{
+  typedef _MatrixType MatrixType;
+  typedef _Preconditioner Preconditioner;
+};
+
+}
+
+/** \ingroup IterativeLinearSolvers_Module
+  * \brief A bi conjugate gradient stabilized solver for sparse square problems
+  *
+  * This class allows to solve for A.x = b sparse linear problems using a bi conjugate gradient
+  * stabilized algorithm. The vectors x and b can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
+  * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
+  *
+  * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
+  * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
+  * and NumTraits<Scalar>::epsilon() for the tolerance.
+  * 
+  * This class can be used as the direct solver classes. Here is a typical usage example:
+  * \code
+  * int n = 10000;
+  * VectorXd x(n), b(n);
+  * SparseMatrix<double> A(n,n);
+  * // fill A and b
+  * BiCGSTAB<SparseMatrix<double> > solver;
+  * solver(A);
+  * x = solver.solve(b);
+  * std::cout << "#iterations:     " << solver.iterations() << std::endl;
+  * std::cout << "estimated error: " << solver.error()      << std::endl;
+  * // update b, and solve again
+  * x = solver.solve(b);
+  * \endcode
+  * 
+  * By default the iterations start with x=0 as an initial guess of the solution.
+  * One can control the start using the solveWithGuess() method. Here is a step by
+  * step execution example starting with a random guess and printing the evolution
+  * of the estimated error:
+  * * \code
+  * x = VectorXd::Random(n);
+  * solver.setMaxIterations(1);
+  * int i = 0;
+  * do {
+  *   x = solver.solveWithGuess(b,x);
+  *   std::cout << i << " : " << solver.error() << std::endl;
+  *   ++i;
+  * } while (solver.info()!=Success && i<100);
+  * \endcode
+  * Note that such a step by step excution is slightly slower.
+  * 
+  * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
+  */
+template< typename _MatrixType, typename _Preconditioner>
+class BiCGSTAB : public IterativeSolverBase<BiCGSTAB<_MatrixType,_Preconditioner> >
+{
+  typedef IterativeSolverBase<BiCGSTAB> Base;
+  using Base::mp_matrix;
+  using Base::m_error;
+  using Base::m_iterations;
+  using Base::m_info;
+  using Base::m_isInitialized;
+public:
+  typedef _MatrixType MatrixType;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef _Preconditioner Preconditioner;
+
+public:
+
+  /** Default constructor. */
+  BiCGSTAB() : Base() {}
+
+  /** Initialize the solver with matrix \a A for further \c Ax=b solving.
+    * 
+    * This constructor is a shortcut for the default constructor followed
+    * by a call to compute().
+    * 
+    * \warning this class stores a reference to the matrix A as well as some
+    * precomputed values that depend on it. Therefore, if \a A is changed
+    * this class becomes invalid. Call compute() to update it with the new
+    * matrix A, or modify a copy of A.
+    */
+  BiCGSTAB(const MatrixType& A) : Base(A) {}
+
+  ~BiCGSTAB() {}
+  
+  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
+    * \a x0 as an initial solution.
+    *
+    * \sa compute()
+    */
+  template<typename Rhs,typename Guess>
+  inline const internal::solve_retval_with_guess<BiCGSTAB, Rhs, Guess>
+  solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
+  {
+    eigen_assert(m_isInitialized && "BiCGSTAB is not initialized.");
+    eigen_assert(Base::rows()==b.rows()
+              && "BiCGSTAB::solve(): invalid number of rows of the right hand side matrix b");
+    return internal::solve_retval_with_guess
+            <BiCGSTAB, Rhs, Guess>(*this, b.derived(), x0);
+  }
+  
+  /** \internal */
+  template<typename Rhs,typename Dest>
+  void _solveWithGuess(const Rhs& b, Dest& x) const
+  {    
+    bool failed = false;
+    for(int j=0; j<b.cols(); ++j)
+    {
+      m_iterations = Base::maxIterations();
+      m_error = Base::m_tolerance;
+      
+      typename Dest::ColXpr xj(x,j);
+      if(!internal::bicgstab(*mp_matrix, b.col(j), xj, Base::m_preconditioner, m_iterations, m_error))
+        failed = true;
+    }
+    m_info = failed ? NumericalIssue
+           : m_error <= Base::m_tolerance ? Success
+           : NoConvergence;
+    m_isInitialized = true;
+  }
+
+  /** \internal */
+  template<typename Rhs,typename Dest>
+  void _solve(const Rhs& b, Dest& x) const
+  {
+    x.setZero();
+    _solveWithGuess(b,x);
+  }
+
+protected:
+
+};
+
+
+namespace internal {
+
+  template<typename _MatrixType, typename _Preconditioner, typename Rhs>
+struct solve_retval<BiCGSTAB<_MatrixType, _Preconditioner>, Rhs>
+  : solve_retval_base<BiCGSTAB<_MatrixType, _Preconditioner>, Rhs>
+{
+  typedef BiCGSTAB<_MatrixType, _Preconditioner> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_BICGSTAB_H
diff --git a/extern/Eigen3/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
new file mode 100644
index 00000000000..f64f2534d28
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/ConjugateGradient.h
@@ -0,0 +1,251 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CONJUGATE_GRADIENT_H
+#define EIGEN_CONJUGATE_GRADIENT_H
+
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal Low-level conjugate gradient algorithm
+  * \param mat The matrix A
+  * \param rhs The right hand side vector b
+  * \param x On input and initial solution, on output the computed solution.
+  * \param precond A preconditioner being able to efficiently solve for an
+  *                approximation of Ax=b (regardless of b)
+  * \param iters On input the max number of iteration, on output the number of performed iterations.
+  * \param tol_error On input the tolerance error, on output an estimation of the relative error.
+  */
+template<typename MatrixType, typename Rhs, typename Dest, typename Preconditioner>
+EIGEN_DONT_INLINE
+void conjugate_gradient(const MatrixType& mat, const Rhs& rhs, Dest& x,
+                        const Preconditioner& precond, int& iters,
+                        typename Dest::RealScalar& tol_error)
+{
+  using std::sqrt;
+  using std::abs;
+  typedef typename Dest::RealScalar RealScalar;
+  typedef typename Dest::Scalar Scalar;
+  typedef Matrix<Scalar,Dynamic,1> VectorType;
+  
+  RealScalar tol = tol_error;
+  int maxIters = iters;
+  
+  int n = mat.cols();
+
+  VectorType residual = rhs - mat * x; //initial residual
+  VectorType p(n);
+
+  p = precond.solve(residual);      //initial search direction
+
+  VectorType z(n), tmp(n);
+  RealScalar absNew = internal::real(residual.dot(p));  // the square of the absolute value of r scaled by invM
+  RealScalar rhsNorm2 = rhs.squaredNorm();
+  RealScalar residualNorm2 = 0;
+  RealScalar threshold = tol*tol*rhsNorm2;
+  int i = 0;
+  while(i < maxIters)
+  {
+    tmp.noalias() = mat * p;              // the bottleneck of the algorithm
+
+    Scalar alpha = absNew / p.dot(tmp);   // the amount we travel on dir
+    x += alpha * p;                       // update solution
+    residual -= alpha * tmp;              // update residue
+    
+    residualNorm2 = residual.squaredNorm();
+    if(residualNorm2 < threshold)
+      break;
+    
+    z = precond.solve(residual);          // approximately solve for "A z = residual"
+
+    RealScalar absOld = absNew;
+    absNew = internal::real(residual.dot(z));     // update the absolute value of r
+    RealScalar beta = absNew / absOld;            // calculate the Gram-Schmidt value used to create the new search direction
+    p = z + beta * p;                             // update search direction
+    i++;
+  }
+  tol_error = sqrt(residualNorm2 / rhsNorm2);
+  iters = i;
+}
+
+}
+
+template< typename _MatrixType, int _UpLo=Lower,
+          typename _Preconditioner = DiagonalPreconditioner<typename _MatrixType::Scalar> >
+class ConjugateGradient;
+
+namespace internal {
+
+template< typename _MatrixType, int _UpLo, typename _Preconditioner>
+struct traits<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
+{
+  typedef _MatrixType MatrixType;
+  typedef _Preconditioner Preconditioner;
+};
+
+}
+
+/** \ingroup IterativeLinearSolvers_Module
+  * \brief A conjugate gradient solver for sparse self-adjoint problems
+  *
+  * This class allows to solve for A.x = b sparse linear problems using a conjugate gradient algorithm.
+  * The sparse matrix A must be selfadjoint. The vectors x and b can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, can be a dense or a sparse matrix.
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  * \tparam _Preconditioner the type of the preconditioner. Default is DiagonalPreconditioner
+  *
+  * The maximal number of iterations and tolerance value can be controlled via the setMaxIterations()
+  * and setTolerance() methods. The defaults are the size of the problem for the maximal number of iterations
+  * and NumTraits<Scalar>::epsilon() for the tolerance.
+  * 
+  * This class can be used as the direct solver classes. Here is a typical usage example:
+  * \code
+  * int n = 10000;
+  * VectorXd x(n), b(n);
+  * SparseMatrix<double> A(n,n);
+  * // fill A and b
+  * ConjugateGradient<SparseMatrix<double> > cg;
+  * cg.compute(A);
+  * x = cg.solve(b);
+  * std::cout << "#iterations:     " << cg.iterations() << std::endl;
+  * std::cout << "estimated error: " << cg.error()      << std::endl;
+  * // update b, and solve again
+  * x = cg.solve(b);
+  * \endcode
+  * 
+  * By default the iterations start with x=0 as an initial guess of the solution.
+  * One can control the start using the solveWithGuess() method. Here is a step by
+  * step execution example starting with a random guess and printing the evolution
+  * of the estimated error:
+  * * \code
+  * x = VectorXd::Random(n);
+  * cg.setMaxIterations(1);
+  * int i = 0;
+  * do {
+  *   x = cg.solveWithGuess(b,x);
+  *   std::cout << i << " : " << cg.error() << std::endl;
+  *   ++i;
+  * } while (cg.info()!=Success && i<100);
+  * \endcode
+  * Note that such a step by step excution is slightly slower.
+  * 
+  * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
+  */
+template< typename _MatrixType, int _UpLo, typename _Preconditioner>
+class ConjugateGradient : public IterativeSolverBase<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> >
+{
+  typedef IterativeSolverBase<ConjugateGradient> Base;
+  using Base::mp_matrix;
+  using Base::m_error;
+  using Base::m_iterations;
+  using Base::m_info;
+  using Base::m_isInitialized;
+public:
+  typedef _MatrixType MatrixType;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::RealScalar RealScalar;
+  typedef _Preconditioner Preconditioner;
+
+  enum {
+    UpLo = _UpLo
+  };
+
+public:
+
+  /** Default constructor. */
+  ConjugateGradient() : Base() {}
+
+  /** Initialize the solver with matrix \a A for further \c Ax=b solving.
+    * 
+    * This constructor is a shortcut for the default constructor followed
+    * by a call to compute().
+    * 
+    * \warning this class stores a reference to the matrix A as well as some
+    * precomputed values that depend on it. Therefore, if \a A is changed
+    * this class becomes invalid. Call compute() to update it with the new
+    * matrix A, or modify a copy of A.
+    */
+  ConjugateGradient(const MatrixType& A) : Base(A) {}
+
+  ~ConjugateGradient() {}
+  
+  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A
+    * \a x0 as an initial solution.
+    *
+    * \sa compute()
+    */
+  template<typename Rhs,typename Guess>
+  inline const internal::solve_retval_with_guess<ConjugateGradient, Rhs, Guess>
+  solveWithGuess(const MatrixBase<Rhs>& b, const Guess& x0) const
+  {
+    eigen_assert(m_isInitialized && "ConjugateGradient is not initialized.");
+    eigen_assert(Base::rows()==b.rows()
+              && "ConjugateGradient::solve(): invalid number of rows of the right hand side matrix b");
+    return internal::solve_retval_with_guess
+            <ConjugateGradient, Rhs, Guess>(*this, b.derived(), x0);
+  }
+
+  /** \internal */
+  template<typename Rhs,typename Dest>
+  void _solveWithGuess(const Rhs& b, Dest& x) const
+  {
+    m_iterations = Base::maxIterations();
+    m_error = Base::m_tolerance;
+
+    for(int j=0; j<b.cols(); ++j)
+    {
+      m_iterations = Base::maxIterations();
+      m_error = Base::m_tolerance;
+
+      typename Dest::ColXpr xj(x,j);
+      internal::conjugate_gradient(mp_matrix->template selfadjointView<UpLo>(), b.col(j), xj,
+                                   Base::m_preconditioner, m_iterations, m_error);
+    }
+
+    m_isInitialized = true;
+    m_info = m_error <= Base::m_tolerance ? Success : NoConvergence;
+  }
+  
+  /** \internal */
+  template<typename Rhs,typename Dest>
+  void _solve(const Rhs& b, Dest& x) const
+  {
+    x.setOnes();
+    _solveWithGuess(b,x);
+  }
+
+protected:
+
+};
+
+
+namespace internal {
+
+template<typename _MatrixType, int _UpLo, typename _Preconditioner, typename Rhs>
+struct solve_retval<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner>, Rhs>
+  : solve_retval_base<ConjugateGradient<_MatrixType,_UpLo,_Preconditioner>, Rhs>
+{
+  typedef ConjugateGradient<_MatrixType,_UpLo,_Preconditioner> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CONJUGATE_GRADIENT_H
diff --git a/extern/Eigen3/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
new file mode 100644
index 00000000000..224304f0eb8
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h
@@ -0,0 +1,466 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_INCOMPLETE_LUT_H
+#define EIGEN_INCOMPLETE_LUT_H
+
+namespace Eigen { 
+
+/**
+ * \brief Incomplete LU factorization with dual-threshold strategy
+ * During the numerical factorization, two dropping rules are used :
+ *  1) any element whose magnitude is less than some tolerance is dropped.
+ *    This tolerance is obtained by multiplying the input tolerance @p droptol 
+ *    by the average magnitude of all the original elements in the current row.
+ *  2) After the elimination of the row, only the @p fill largest elements in 
+ *    the L part and the @p fill largest elements in the U part are kept 
+ *    (in addition to the diagonal element ). Note that @p fill is computed from 
+ *    the input parameter @p fillfactor which is used the ratio to control the fill_in 
+ *    relatively to the initial number of nonzero elements.
+ * 
+ * The two extreme cases are when @p droptol=0 (to keep all the @p fill*2 largest elements)
+ * and when @p fill=n/2 with @p droptol being different to zero. 
+ * 
+ * References : Yousef Saad, ILUT: A dual threshold incomplete LU factorization, 
+ *              Numerical Linear Algebra with Applications, 1(4), pp 387-402, 1994.
+ * 
+ * NOTE : The following implementation is derived from the ILUT implementation
+ * in the SPARSKIT package, Copyright (C) 2005, the Regents of the University of Minnesota 
+ *  released under the terms of the GNU LGPL: 
+ *    http://www-users.cs.umn.edu/~saad/software/SPARSKIT/README
+ * However, Yousef Saad gave us permission to relicense his ILUT code to MPL2.
+ * See the Eigen mailing list archive, thread: ILUT, date: July 8, 2012:
+ *   http://listengine.tuxfamily.org/lists.tuxfamily.org/eigen/2012/07/msg00064.html
+ * alternatively, on GMANE:
+ *   http://comments.gmane.org/gmane.comp.lib.eigen/3302
+ */
+template <typename _Scalar>
+class IncompleteLUT : internal::noncopyable
+{
+    typedef _Scalar Scalar;
+    typedef typename NumTraits<Scalar>::Real RealScalar;
+    typedef Matrix<Scalar,Dynamic,1> Vector;
+    typedef SparseMatrix<Scalar,RowMajor> FactorType;
+    typedef SparseMatrix<Scalar,ColMajor> PermutType;
+    typedef typename FactorType::Index Index;
+
+  public:
+    typedef Matrix<Scalar,Dynamic,Dynamic> MatrixType;
+    
+    IncompleteLUT()
+      : m_droptol(NumTraits<Scalar>::dummy_precision()), m_fillfactor(10),
+        m_analysisIsOk(false), m_factorizationIsOk(false), m_isInitialized(false)
+    {}
+    
+    template<typename MatrixType>
+    IncompleteLUT(const MatrixType& mat, RealScalar droptol=NumTraits<Scalar>::dummy_precision(), int fillfactor = 10)
+      : m_droptol(droptol),m_fillfactor(fillfactor),
+        m_analysisIsOk(false),m_factorizationIsOk(false),m_isInitialized(false)
+    {
+      eigen_assert(fillfactor != 0);
+      compute(mat); 
+    }
+    
+    Index rows() const { return m_lu.rows(); }
+    
+    Index cols() const { return m_lu.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 && "IncompleteLUT is not initialized.");
+      return m_info;
+    }
+    
+    template<typename MatrixType>
+    void analyzePattern(const MatrixType& amat);
+    
+    template<typename MatrixType>
+    void factorize(const MatrixType& amat);
+    
+    /**
+      * Compute an incomplete LU factorization with dual threshold on the matrix mat
+      * No pivoting is done in this version
+      * 
+      **/
+    template<typename MatrixType>
+    IncompleteLUT<Scalar>& compute(const MatrixType& amat)
+    {
+      analyzePattern(amat); 
+      factorize(amat);
+      eigen_assert(m_factorizationIsOk == true); 
+      m_isInitialized = true;
+      return *this;
+    }
+
+    void setDroptol(RealScalar droptol); 
+    void setFillfactor(int fillfactor); 
+    
+    template<typename Rhs, typename Dest>
+    void _solve(const Rhs& b, Dest& x) const
+    {
+      x = m_Pinv * b;  
+      x = m_lu.template triangularView<UnitLower>().solve(x);
+      x = m_lu.template triangularView<Upper>().solve(x);
+      x = m_P * x; 
+    }
+
+    template<typename Rhs> inline const internal::solve_retval<IncompleteLUT, Rhs>
+     solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "IncompleteLUT is not initialized.");
+      eigen_assert(cols()==b.rows()
+                && "IncompleteLUT::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<IncompleteLUT, Rhs>(*this, b.derived());
+    }
+
+protected:
+
+    template <typename VectorV, typename VectorI>
+    int QuickSplit(VectorV &row, VectorI &ind, int ncut);
+
+
+    /** keeps off-diagonal entries; drops diagonal entries */
+    struct keep_diag {
+      inline bool operator() (const Index& row, const Index& col, const Scalar&) const
+      {
+        return row!=col;
+      }
+    };
+
+protected:
+
+    FactorType m_lu;
+    RealScalar m_droptol;
+    int m_fillfactor;
+    bool m_analysisIsOk;
+    bool m_factorizationIsOk;
+    bool m_isInitialized;
+    ComputationInfo m_info;
+    PermutationMatrix<Dynamic,Dynamic,Index> m_P;     // Fill-reducing permutation
+    PermutationMatrix<Dynamic,Dynamic,Index> m_Pinv;  // Inverse permutation
+};
+
+/**
+ * Set control parameter droptol
+ *  \param droptol   Drop any element whose magnitude is less than this tolerance 
+ **/ 
+template<typename Scalar>
+void IncompleteLUT<Scalar>::setDroptol(RealScalar droptol)
+{
+  this->m_droptol = droptol;   
+}
+
+/**
+ * Set control parameter fillfactor
+ * \param fillfactor  This is used to compute the  number @p fill_in of largest elements to keep on each row. 
+ **/ 
+template<typename Scalar>
+void IncompleteLUT<Scalar>::setFillfactor(int fillfactor)
+{
+  this->m_fillfactor = fillfactor;   
+}
+
+
+/**
+ * Compute a quick-sort split of a vector 
+ * On output, the vector row is permuted such that its elements satisfy
+ * abs(row(i)) >= abs(row(ncut)) if i<ncut
+ * abs(row(i)) <= abs(row(ncut)) if i>ncut 
+ * \param row The vector of values
+ * \param ind The array of index for the elements in @p row
+ * \param ncut  The number of largest elements to keep
+ **/ 
+template <typename Scalar>
+template <typename VectorV, typename VectorI>
+int IncompleteLUT<Scalar>::QuickSplit(VectorV &row, VectorI &ind, int ncut)
+{
+  using std::swap;
+  int mid;
+  int n = row.size(); /* length of the vector */
+  int first, last ; 
+  
+  ncut--; /* to fit the zero-based indices */
+  first = 0; 
+  last = n-1; 
+  if (ncut < first || ncut > last ) return 0;
+  
+  do {
+    mid = first; 
+    RealScalar abskey = std::abs(row(mid)); 
+    for (int j = first + 1; j <= last; j++) {
+      if ( std::abs(row(j)) > abskey) {
+        ++mid;
+        swap(row(mid), row(j));
+        swap(ind(mid), ind(j));
+      }
+    }
+    /* Interchange for the pivot element */
+    swap(row(mid), row(first));
+    swap(ind(mid), ind(first));
+    
+    if (mid > ncut) last = mid - 1;
+    else if (mid < ncut ) first = mid + 1; 
+  } while (mid != ncut );
+  
+  return 0; /* mid is equal to ncut */ 
+}
+
+template <typename Scalar>
+template<typename _MatrixType>
+void IncompleteLUT<Scalar>::analyzePattern(const _MatrixType& amat)
+{
+  // Compute the Fill-reducing permutation
+  SparseMatrix<Scalar,ColMajor, Index> mat1 = amat;
+  SparseMatrix<Scalar,ColMajor, Index> mat2 = amat.transpose();
+  // Symmetrize the pattern
+  // FIXME for a matrix with nearly symmetric pattern, mat2+mat1 is the appropriate choice.
+  //       on the other hand for a really non-symmetric pattern, mat2*mat1 should be prefered...
+  SparseMatrix<Scalar,ColMajor, Index> AtA = mat2 + mat1;
+  AtA.prune(keep_diag());
+  internal::minimum_degree_ordering<Scalar, Index>(AtA, m_P);  // Then compute the AMD ordering...
+
+  m_Pinv  = m_P.inverse(); // ... and the inverse permutation
+
+  m_analysisIsOk = true;
+}
+
+template <typename Scalar>
+template<typename _MatrixType>
+void IncompleteLUT<Scalar>::factorize(const _MatrixType& amat)
+{
+  using std::sqrt;
+  using std::swap;
+  using std::abs;
+
+  eigen_assert((amat.rows() == amat.cols()) && "The factorization should be done on a square matrix");
+  int n = amat.cols();  // Size of the matrix
+  m_lu.resize(n,n);
+  // Declare Working vectors and variables
+  Vector u(n) ;     // real values of the row -- maximum size is n --
+  VectorXi ju(n);   // column position of the values in u -- maximum size  is n
+  VectorXi jr(n);   // Indicate the position of the nonzero elements in the vector u -- A zero location is indicated by -1
+
+  // Apply the fill-reducing permutation
+  eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
+  SparseMatrix<Scalar,RowMajor, Index> mat;
+  mat = amat.twistedBy(m_Pinv);
+
+  // Initialization
+  jr.fill(-1);
+  ju.fill(0);
+  u.fill(0);
+
+  // number of largest elements to keep in each row:
+  int fill_in =   static_cast<int> (amat.nonZeros()*m_fillfactor)/n+1;
+  if (fill_in > n) fill_in = n;
+
+  // number of largest nonzero elements to keep in the L and the U part of the current row:
+  int nnzL = fill_in/2;
+  int nnzU = nnzL;
+  m_lu.reserve(n * (nnzL + nnzU + 1));
+
+  // global loop over the rows of the sparse matrix
+  for (int ii = 0; ii < n; ii++)
+  {
+    // 1 - copy the lower and the upper part of the row i of mat in the working vector u
+
+    int sizeu = 1; // number of nonzero elements in the upper part of the current row
+    int sizel = 0; // number of nonzero elements in the lower part of the current row
+    ju(ii)    = ii;
+    u(ii)     = 0;
+    jr(ii)    = ii;
+    RealScalar rownorm = 0;
+
+    typename FactorType::InnerIterator j_it(mat, ii); // Iterate through the current row ii
+    for (; j_it; ++j_it)
+    {
+      int k = j_it.index();
+      if (k < ii)
+      {
+        // copy the lower part
+        ju(sizel) = k;
+        u(sizel) = j_it.value();
+        jr(k) = sizel;
+        ++sizel;
+      }
+      else if (k == ii)
+      {
+        u(ii) = j_it.value();
+      }
+      else
+      {
+        // copy the upper part
+        int jpos = ii + sizeu;
+        ju(jpos) = k;
+        u(jpos) = j_it.value();
+        jr(k) = jpos;
+        ++sizeu;
+      }
+      rownorm += internal::abs2(j_it.value());
+    }
+
+    // 2 - detect possible zero row
+    if(rownorm==0)
+    {
+      m_info = NumericalIssue;
+      return;
+    }
+    // Take the 2-norm of the current row as a relative tolerance
+    rownorm = sqrt(rownorm);
+
+    // 3 - eliminate the previous nonzero rows
+    int jj = 0;
+    int len = 0;
+    while (jj < sizel)
+    {
+      // In order to eliminate in the correct order,
+      // we must select first the smallest column index among  ju(jj:sizel)
+      int k;
+      int minrow = ju.segment(jj,sizel-jj).minCoeff(&k); // k is relative to the segment
+      k += jj;
+      if (minrow != ju(jj))
+      {
+        // swap the two locations
+        int j = ju(jj);
+        swap(ju(jj), ju(k));
+        jr(minrow) = jj;   jr(j) = k;
+        swap(u(jj), u(k));
+      }
+      // Reset this location
+      jr(minrow) = -1;
+
+      // Start elimination
+      typename FactorType::InnerIterator ki_it(m_lu, minrow);
+      while (ki_it && ki_it.index() < minrow) ++ki_it;
+      eigen_internal_assert(ki_it && ki_it.col()==minrow);
+      Scalar fact = u(jj) / ki_it.value();
+
+      // drop too small elements
+      if(abs(fact) <= m_droptol)
+      {
+        jj++;
+        continue;
+      }
+
+      // linear combination of the current row ii and the row minrow
+      ++ki_it;
+      for (; ki_it; ++ki_it)
+      {
+        Scalar prod = fact * ki_it.value();
+        int j       = ki_it.index();
+        int jpos    = jr(j);
+        if (jpos == -1) // fill-in element
+        {
+          int newpos;
+          if (j >= ii) // dealing with the upper part
+          {
+            newpos = ii + sizeu;
+            sizeu++;
+            eigen_internal_assert(sizeu<=n);
+          }
+          else // dealing with the lower part
+          {
+            newpos = sizel;
+            sizel++;
+            eigen_internal_assert(sizel<=ii);
+          }
+          ju(newpos) = j;
+          u(newpos) = -prod;
+          jr(j) = newpos;
+        }
+        else
+          u(jpos) -= prod;
+      }
+      // store the pivot element
+      u(len) = fact;
+      ju(len) = minrow;
+      ++len;
+
+      jj++;
+    } // end of the elimination on the row ii
+
+    // reset the upper part of the pointer jr to zero
+    for(int k = 0; k <sizeu; k++) jr(ju(ii+k)) = -1;
+
+    // 4 - partially sort and insert the elements in the m_lu matrix
+
+    // sort the L-part of the row
+    sizel = len;
+    len = (std::min)(sizel, nnzL);
+    typename Vector::SegmentReturnType ul(u.segment(0, sizel));
+    typename VectorXi::SegmentReturnType jul(ju.segment(0, sizel));
+    QuickSplit(ul, jul, len);
+
+    // store the largest m_fill elements of the L part
+    m_lu.startVec(ii);
+    for(int k = 0; k < len; k++)
+      m_lu.insertBackByOuterInnerUnordered(ii,ju(k)) = u(k);
+
+    // store the diagonal element
+    // apply a shifting rule to avoid zero pivots (we are doing an incomplete factorization)
+    if (u(ii) == Scalar(0))
+      u(ii) = sqrt(m_droptol) * rownorm;
+    m_lu.insertBackByOuterInnerUnordered(ii, ii) = u(ii);
+
+    // sort the U-part of the row
+    // apply the dropping rule first
+    len = 0;
+    for(int k = 1; k < sizeu; k++)
+    {
+      if(abs(u(ii+k)) > m_droptol * rownorm )
+      {
+        ++len;
+        u(ii + len)  = u(ii + k);
+        ju(ii + len) = ju(ii + k);
+      }
+    }
+    sizeu = len + 1; // +1 to take into account the diagonal element
+    len = (std::min)(sizeu, nnzU);
+    typename Vector::SegmentReturnType uu(u.segment(ii+1, sizeu-1));
+    typename VectorXi::SegmentReturnType juu(ju.segment(ii+1, sizeu-1));
+    QuickSplit(uu, juu, len);
+
+    // store the largest elements of the U part
+    for(int k = ii + 1; k < ii + len; k++)
+      m_lu.insertBackByOuterInnerUnordered(ii,ju(k)) = u(k);
+  }
+
+  m_lu.finalize();
+  m_lu.makeCompressed();
+
+  m_factorizationIsOk = true;
+  m_info = Success;
+}
+
+namespace internal {
+
+template<typename _MatrixType, typename Rhs>
+struct solve_retval<IncompleteLUT<_MatrixType>, Rhs>
+  : solve_retval_base<IncompleteLUT<_MatrixType>, Rhs>
+{
+  typedef IncompleteLUT<_MatrixType> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_INCOMPLETE_LUT_H
+
diff --git a/extern/Eigen3/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
new file mode 100644
index 00000000000..11706cebabd
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/IterativeLinearSolvers/IterativeSolverBase.h
@@ -0,0 +1,254 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_ITERATIVE_SOLVER_BASE_H
+#define EIGEN_ITERATIVE_SOLVER_BASE_H
+
+namespace Eigen { 
+
+/** \ingroup IterativeLinearSolvers_Module
+  * \brief Base class for linear iterative solvers
+  *
+  * \sa class SimplicialCholesky, DiagonalPreconditioner, IdentityPreconditioner
+  */
+template< typename Derived>
+class IterativeSolverBase : internal::noncopyable
+{
+public:
+  typedef typename internal::traits<Derived>::MatrixType MatrixType;
+  typedef typename internal::traits<Derived>::Preconditioner Preconditioner;
+  typedef typename MatrixType::Scalar Scalar;
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::RealScalar RealScalar;
+
+public:
+
+  Derived& derived() { return *static_cast<Derived*>(this); }
+  const Derived& derived() const { return *static_cast<const Derived*>(this); }
+
+  /** Default constructor. */
+  IterativeSolverBase()
+    : mp_matrix(0)
+  {
+    init();
+  }
+
+  /** Initialize the solver with matrix \a A for further \c Ax=b solving.
+    * 
+    * This constructor is a shortcut for the default constructor followed
+    * by a call to compute().
+    * 
+    * \warning this class stores a reference to the matrix A as well as some
+    * precomputed values that depend on it. Therefore, if \a A is changed
+    * this class becomes invalid. Call compute() to update it with the new
+    * matrix A, or modify a copy of A.
+    */
+  IterativeSolverBase(const MatrixType& A)
+  {
+    init();
+    compute(A);
+  }
+
+  ~IterativeSolverBase() {}
+  
+  /** Initializes the iterative solver for the sparcity pattern of the matrix \a A for further solving \c Ax=b problems.
+    *
+    * Currently, this function mostly call analyzePattern on the preconditioner. In the future
+    * we might, for instance, implement column reodering for faster matrix vector products.
+    */
+  Derived& analyzePattern(const MatrixType& A)
+  {
+    m_preconditioner.analyzePattern(A);
+    m_isInitialized = true;
+    m_analysisIsOk = true;
+    m_info = Success;
+    return derived();
+  }
+  
+  /** Initializes the iterative solver with the numerical values of the matrix \a A for further solving \c Ax=b problems.
+    *
+    * Currently, this function mostly call factorize on the preconditioner.
+    *
+    * \warning this class stores a reference to the matrix A as well as some
+    * precomputed values that depend on it. Therefore, if \a A is changed
+    * this class becomes invalid. Call compute() to update it with the new
+    * matrix A, or modify a copy of A.
+    */
+  Derived& factorize(const MatrixType& A)
+  {
+    eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); 
+    mp_matrix = &A;
+    m_preconditioner.factorize(A);
+    m_factorizationIsOk = true;
+    m_info = Success;
+    return derived();
+  }
+
+  /** Initializes the iterative solver with the matrix \a A for further solving \c Ax=b problems.
+    *
+    * Currently, this function mostly initialized/compute the preconditioner. In the future
+    * we might, for instance, implement column reodering for faster matrix vector products.
+    *
+    * \warning this class stores a reference to the matrix A as well as some
+    * precomputed values that depend on it. Therefore, if \a A is changed
+    * this class becomes invalid. Call compute() to update it with the new
+    * matrix A, or modify a copy of A.
+    */
+  Derived& compute(const MatrixType& A)
+  {
+    mp_matrix = &A;
+    m_preconditioner.compute(A);
+    m_isInitialized = true;
+    m_analysisIsOk = true;
+    m_factorizationIsOk = true;
+    m_info = Success;
+    return derived();
+  }
+
+  /** \internal */
+  Index rows() const { return mp_matrix ? mp_matrix->rows() : 0; }
+  /** \internal */
+  Index cols() const { return mp_matrix ? mp_matrix->cols() : 0; }
+
+  /** \returns the tolerance threshold used by the stopping criteria */
+  RealScalar tolerance() const { return m_tolerance; }
+  
+  /** Sets the tolerance threshold used by the stopping criteria */
+  Derived& setTolerance(RealScalar tolerance)
+  {
+    m_tolerance = tolerance;
+    return derived();
+  }
+
+  /** \returns a read-write reference to the preconditioner for custom configuration. */
+  Preconditioner& preconditioner() { return m_preconditioner; }
+  
+  /** \returns a read-only reference to the preconditioner. */
+  const Preconditioner& preconditioner() const { return m_preconditioner; }
+
+  /** \returns the max number of iterations */
+  int maxIterations() const
+  {
+    return (mp_matrix && m_maxIterations<0) ? mp_matrix->cols() : m_maxIterations;
+  }
+  
+  /** Sets the max number of iterations */
+  Derived& setMaxIterations(int maxIters)
+  {
+    m_maxIterations = maxIters;
+    return derived();
+  }
+
+  /** \returns the number of iterations performed during the last solve */
+  int iterations() const
+  {
+    eigen_assert(m_isInitialized && "ConjugateGradient is not initialized.");
+    return m_iterations;
+  }
+
+  /** \returns the tolerance error reached during the last solve */
+  RealScalar error() const
+  {
+    eigen_assert(m_isInitialized && "ConjugateGradient is not initialized.");
+    return m_error;
+  }
+
+  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+    *
+    * \sa compute()
+    */
+  template<typename Rhs> inline const internal::solve_retval<Derived, Rhs>
+  solve(const MatrixBase<Rhs>& b) const
+  {
+    eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized.");
+    eigen_assert(rows()==b.rows()
+              && "IterativeSolverBase::solve(): invalid number of rows of the right hand side matrix b");
+    return internal::solve_retval<Derived, Rhs>(derived(), b.derived());
+  }
+  
+  /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+    *
+    * \sa compute()
+    */
+  template<typename Rhs>
+  inline const internal::sparse_solve_retval<IterativeSolverBase, Rhs>
+  solve(const SparseMatrixBase<Rhs>& b) const
+  {
+    eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized.");
+    eigen_assert(rows()==b.rows()
+              && "IterativeSolverBase::solve(): invalid number of rows of the right hand side matrix b");
+    return internal::sparse_solve_retval<IterativeSolverBase, Rhs>(*this, b.derived());
+  }
+
+  /** \returns Success if the iterations converged, and NoConvergence otherwise. */
+  ComputationInfo info() const
+  {
+    eigen_assert(m_isInitialized && "IterativeSolverBase is not initialized.");
+    return m_info;
+  }
+  
+  /** \internal */
+  template<typename Rhs, typename DestScalar, int DestOptions, typename DestIndex>
+  void _solve_sparse(const Rhs& b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+  {
+    eigen_assert(rows()==b.rows());
+    
+    int rhsCols = b.cols();
+    int size = b.rows();
+    Eigen::Matrix<DestScalar,Dynamic,1> tb(size);
+    Eigen::Matrix<DestScalar,Dynamic,1> tx(size);
+    for(int k=0; k<rhsCols; ++k)
+    {
+      tb = b.col(k);
+      tx = derived().solve(tb);
+      dest.col(k) = tx.sparseView(0);
+    }
+  }
+
+protected:
+  void init()
+  {
+    m_isInitialized = false;
+    m_analysisIsOk = false;
+    m_factorizationIsOk = false;
+    m_maxIterations = -1;
+    m_tolerance = NumTraits<Scalar>::epsilon();
+  }
+  const MatrixType* mp_matrix;
+  Preconditioner m_preconditioner;
+
+  int m_maxIterations;
+  RealScalar m_tolerance;
+  
+  mutable RealScalar m_error;
+  mutable int m_iterations;
+  mutable ComputationInfo m_info;
+  mutable bool m_isInitialized, m_analysisIsOk, m_factorizationIsOk;
+};
+
+namespace internal {
+ 
+template<typename Derived, typename Rhs>
+struct sparse_solve_retval<IterativeSolverBase<Derived>, Rhs>
+  : sparse_solve_retval_base<IterativeSolverBase<Derived>, Rhs>
+{
+  typedef IterativeSolverBase<Derived> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec().derived()._solve_sparse(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_ITERATIVE_SOLVER_BASE_H
diff --git a/extern/Eigen3/Eigen/src/Jacobi/Jacobi.h b/extern/Eigen3/Eigen/src/Jacobi/Jacobi.h
index 98dea6800bc..a9c17dcdf19 100644
--- a/extern/Eigen3/Eigen/src/Jacobi/Jacobi.h
+++ b/extern/Eigen3/Eigen/src/Jacobi/Jacobi.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_JACOBI_H
 #define EIGEN_JACOBI_H
 
+namespace Eigen { 
+
 /** \ingroup Jacobi_Module
   * \jacobi_module
   * \class JacobiRotation
@@ -326,7 +313,7 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
     // both vectors are sequentially stored in memory => vectorization
     enum { Peeling = 2 };
 
-    Index alignedStart = first_aligned(y, size);
+    Index alignedStart = internal::first_aligned(y, size);
     Index alignedEnd = alignedStart + ((size-alignedStart)/PacketSize)*PacketSize;
 
     const Packet pc = pset1<Packet>(j.c());
@@ -344,7 +331,7 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
     Scalar* EIGEN_RESTRICT px = x + alignedStart;
     Scalar* EIGEN_RESTRICT py = y + alignedStart;
 
-    if(first_aligned(x, size)==alignedStart)
+    if(internal::first_aligned(x, size)==alignedStart)
     {
       for(Index i=alignedStart; i<alignedEnd; i+=PacketSize)
       {
@@ -425,6 +412,9 @@ void /*EIGEN_DONT_INLINE*/ apply_rotation_in_the_plane(VectorX& _x, VectorY& _y,
     }
   }
 }
-}
+
+} // end namespace internal
+
+} // end namespace Eigen
 
 #endif // EIGEN_JACOBI_H
diff --git a/extern/Eigen3/Eigen/src/LU/Determinant.h b/extern/Eigen3/Eigen/src/LU/Determinant.h
index b4fe36eb061..d862c5d7784 100644
--- a/extern/Eigen3/Eigen/src/LU/Determinant.h
+++ b/extern/Eigen3/Eigen/src/LU/Determinant.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_DETERMINANT_H
 #define EIGEN_DETERMINANT_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename Derived>
@@ -109,4 +96,6 @@ inline typename internal::traits<Derived>::Scalar MatrixBase<Derived>::determina
   return internal::determinant_impl<typename internal::remove_all<Nested>::type>::run(derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_DETERMINANT_H
diff --git a/extern/Eigen3/Eigen/src/LU/FullPivLU.h b/extern/Eigen3/Eigen/src/LU/FullPivLU.h
index 46ae7d651c8..e23f96cdcf1 100644
--- a/extern/Eigen3/Eigen/src/LU/FullPivLU.h
+++ b/extern/Eigen3/Eigen/src/LU/FullPivLU.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_LU_H
 #define EIGEN_LU_H
 
+namespace Eigen { 
+
 /** \ingroup LU_Module
   *
   * \class FullPivLU
@@ -282,6 +269,7 @@ template<typename _MatrixType> class FullPivLU
     FullPivLU& setThreshold(Default_t)
     {
       m_usePrescribedThreshold = false;
+      return *this;
     }
 
     /** Returns the threshold that will be used by certain methods such as rank().
@@ -743,4 +731,6 @@ MatrixBase<Derived>::fullPivLu() const
   return FullPivLU<PlainObject>(eval());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_LU_H
diff --git a/extern/Eigen3/Eigen/src/LU/Inverse.h b/extern/Eigen3/Eigen/src/LU/Inverse.h
index 2d3e6d10529..39b8cdbc8dc 100644
--- a/extern/Eigen3/Eigen/src/LU/Inverse.h
+++ b/extern/Eigen3/Eigen/src/LU/Inverse.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_INVERSE_H
 #define EIGEN_INVERSE_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /**********************************
@@ -286,7 +273,7 @@ struct inverse_impl : public ReturnByValue<inverse_impl<MatrixType> >
   typedef typename MatrixType::Index Index;
   typedef typename internal::eval<MatrixType>::type MatrixTypeNested;
   typedef typename remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
-  const MatrixTypeNested m_matrix;
+  MatrixTypeNested m_matrix;
 
   inverse_impl(const MatrixType& matrix)
     : m_matrix(matrix)
@@ -404,4 +391,6 @@ inline void MatrixBase<Derived>::computeInverseWithCheck(
   computeInverseAndDetWithCheck(inverse,determinant,invertible,absDeterminantThreshold);
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_INVERSE_H
diff --git a/extern/Eigen3/Eigen/src/LU/PartialPivLU.h b/extern/Eigen3/Eigen/src/LU/PartialPivLU.h
index 09394b01f5b..c9ff9dd5a36 100644
--- a/extern/Eigen3/Eigen/src/LU/PartialPivLU.h
+++ b/extern/Eigen3/Eigen/src/LU/PartialPivLU.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2006-2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_PARTIALLU_H
 #define EIGEN_PARTIALLU_H
 
+namespace Eigen { 
+
 /** \ingroup LU_Module
   *
   * \class PartialPivLU
@@ -506,4 +493,6 @@ MatrixBase<Derived>::lu() const
 }
 #endif
 
+} // end namespace Eigen
+
 #endif // EIGEN_PARTIALLU_H
diff --git a/extern/Eigen3/Eigen/src/LU/PartialPivLU_MKL.h b/extern/Eigen3/Eigen/src/LU/PartialPivLU_MKL.h
new file mode 100644
index 00000000000..9035953c82f
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/LU/PartialPivLU_MKL.h
@@ -0,0 +1,85 @@
+/*
+ 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
+ *     LU decomposition with partial pivoting based on LAPACKE_?getrf function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_PARTIALLU_LAPACK_H
+#define EIGEN_PARTIALLU_LAPACK_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal Specialization for the data types supported by MKL */
+
+#define EIGEN_MKL_LU_PARTPIV(EIGTYPE, MKLTYPE, MKLPREFIX) \
+template<int StorageOrder> \
+struct partial_lu_impl<EIGTYPE, StorageOrder, lapack_int> \
+{ \
+  /* \internal performs the LU decomposition in-place of the matrix represented */ \
+  static lapack_int blocked_lu(lapack_int rows, lapack_int cols, EIGTYPE* lu_data, lapack_int luStride, lapack_int* row_transpositions, lapack_int& nb_transpositions, lapack_int maxBlockSize=256) \
+  { \
+    EIGEN_UNUSED_VARIABLE(maxBlockSize);\
+    lapack_int matrix_order, first_zero_pivot; \
+    lapack_int m, n, lda, *ipiv, info; \
+    EIGTYPE* a; \
+/* Set up parameters for ?getrf */ \
+    matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
+    lda = luStride; \
+    a = lu_data; \
+    ipiv = row_transpositions; \
+    m = rows; \
+    n = cols; \
+    nb_transpositions = 0; \
+\
+    info = LAPACKE_##MKLPREFIX##getrf( matrix_order, m, n, (MKLTYPE*)a, lda, ipiv ); \
+\
+    for(int i=0;i<m;i++) { ipiv[i]--; if (ipiv[i]!=i) nb_transpositions++; } \
+\
+    eigen_assert(info >= 0); \
+/* something should be done with nb_transpositions */ \
+\
+    first_zero_pivot = info; \
+    return first_zero_pivot; \
+  } \
+};
+
+EIGEN_MKL_LU_PARTPIV(double, double, d)
+EIGEN_MKL_LU_PARTPIV(float, float, s)
+EIGEN_MKL_LU_PARTPIV(dcomplex, MKL_Complex16, z)
+EIGEN_MKL_LU_PARTPIV(scomplex, MKL_Complex8, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PARTIALLU_LAPACK_H
diff --git a/extern/Eigen3/Eigen/src/LU/arch/Inverse_SSE.h b/extern/Eigen3/Eigen/src/LU/arch/Inverse_SSE.h
index 4c6153f0aff..60b7a23763e 100644
--- a/extern/Eigen3/Eigen/src/LU/arch/Inverse_SSE.h
+++ b/extern/Eigen3/Eigen/src/LU/arch/Inverse_SSE.h
@@ -5,24 +5,9 @@
 // Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // The SSE code for the 4x4 float and double matrix inverse in this file
 // comes from the following Intel's library:
@@ -42,6 +27,8 @@
 #ifndef EIGEN_INVERSE_SSE_H
 #define EIGEN_INVERSE_SSE_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename MatrixType, typename ResultType>
@@ -335,6 +322,8 @@ struct compute_inverse_size4<Architecture::SSE, double, MatrixType, ResultType>
   }
 };
 
-}
+} // end namespace internal
+
+} // end namespace Eigen
 
 #endif // EIGEN_INVERSE_SSE_H
diff --git a/extern/Eigen3/Eigen/src/OrderingMethods/Amd.h b/extern/Eigen3/Eigen/src/OrderingMethods/Amd.h
new file mode 100644
index 00000000000..ce04852b872
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/OrderingMethods/Amd.h
@@ -0,0 +1,439 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*
+
+NOTE: this routine has been adapted from the CSparse library:
+
+Copyright (c) 2006, Timothy A. Davis.
+http://www.cise.ufl.edu/research/sparse/CSparse
+
+CSparse is free software; you can redistribute it and/or
+modify it under the terms of the GNU Lesser General Public
+License as published by the Free Software Foundation; either
+version 2.1 of the License, or (at your option) any later version.
+
+CSparse is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+Lesser General Public License for more details.
+
+You should have received a copy of the GNU Lesser General Public
+License along with this Module; if not, write to the Free Software
+Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
+
+*/
+
+#include "../Core/util/NonMPL2.h"
+
+#ifndef EIGEN_SPARSE_AMD_H
+#define EIGEN_SPARSE_AMD_H
+
+namespace Eigen { 
+
+namespace internal {
+  
+template<typename T> inline T amd_flip(const T& i) { return -i-2; }
+template<typename T> inline T amd_unflip(const T& i) { return i<0 ? amd_flip(i) : i; }
+template<typename T0, typename T1> inline bool amd_marked(const T0* w, const T1& j) { return w[j]<0; }
+template<typename T0, typename T1> inline void amd_mark(const T0* w, const T1& j) { return w[j] = amd_flip(w[j]); }
+
+/* clear w */
+template<typename Index>
+static int cs_wclear (Index mark, Index lemax, Index *w, Index n)
+{
+  Index k;
+  if(mark < 2 || (mark + lemax < 0))
+  {
+    for(k = 0; k < n; k++)
+      if(w[k] != 0)
+        w[k] = 1;
+    mark = 2;
+  }
+  return (mark);     /* at this point, w[0..n-1] < mark holds */
+}
+
+/* depth-first search and postorder of a tree rooted at node j */
+template<typename Index>
+Index cs_tdfs(Index j, Index k, Index *head, const Index *next, Index *post, Index *stack)
+{
+  int i, p, top = 0;
+  if(!head || !next || !post || !stack) return (-1);    /* check inputs */
+  stack[0] = j;                 /* place j on the stack */
+  while (top >= 0)                /* while (stack is not empty) */
+  {
+    p = stack[top];           /* p = top of stack */
+    i = head[p];              /* i = youngest child of p */
+    if(i == -1)
+    {
+      top--;                 /* p has no unordered children left */
+      post[k++] = p;        /* node p is the kth postordered node */
+    }
+    else
+    {
+      head[p] = next[i];   /* remove i from children of p */
+      stack[++top] = i;     /* start dfs on child node i */
+    }
+  }
+  return k;
+}
+
+
+/** \internal
+  * Approximate minimum degree ordering algorithm.
+  * \returns the permutation P reducing the fill-in of the input matrix \a C
+  * The input matrix \a C must be a selfadjoint compressed column major SparseMatrix object. Both the upper and lower parts have to be stored, but the diagonal entries are optional.
+  * On exit the values of C are destroyed */
+template<typename Scalar, typename Index>
+void minimum_degree_ordering(SparseMatrix<Scalar,ColMajor,Index>& C, PermutationMatrix<Dynamic,Dynamic,Index>& perm)
+{
+  using std::sqrt;
+  typedef SparseMatrix<Scalar,ColMajor,Index> CCS;
+  
+  int d, dk, dext, lemax = 0, e, elenk, eln, i, j, k, k1,
+      k2, k3, jlast, ln, dense, nzmax, mindeg = 0, nvi, nvj, nvk, mark, wnvi,
+      ok, nel = 0, p, p1, p2, p3, p4, pj, pk, pk1, pk2, pn, q, t;
+  unsigned int h;
+  
+  Index n = C.cols();
+  dense = std::max<Index> (16, Index(10 * sqrt(double(n))));   /* find dense threshold */
+  dense = std::min<Index> (n-2, dense);
+  
+  Index cnz = C.nonZeros();
+  perm.resize(n+1);
+  t = cnz + cnz/5 + 2*n;                 /* add elbow room to C */
+  C.resizeNonZeros(t);
+  
+  Index* W       = new Index[8*(n+1)]; /* get workspace */
+  Index* len     = W;
+  Index* nv      = W +   (n+1);
+  Index* next    = W + 2*(n+1);
+  Index* head    = W + 3*(n+1);
+  Index* elen    = W + 4*(n+1);
+  Index* degree  = W + 5*(n+1);
+  Index* w       = W + 6*(n+1);
+  Index* hhead   = W + 7*(n+1);
+  Index* last    = perm.indices().data();                              /* use P as workspace for last */
+  
+  /* --- Initialize quotient graph ---------------------------------------- */
+  Index* Cp = C.outerIndexPtr();
+  Index* Ci = C.innerIndexPtr();
+  for(k = 0; k < n; k++)
+    len[k] = Cp[k+1] - Cp[k];
+  len[n] = 0;
+  nzmax = t;
+  
+  for(i = 0; i <= n; i++)
+  {
+    head[i]   = -1;                     // degree list i is empty
+    last[i]   = -1;
+    next[i]   = -1;
+    hhead[i]  = -1;                     // hash list i is empty 
+    nv[i]     = 1;                      // node i is just one node
+    w[i]      = 1;                      // node i is alive
+    elen[i]   = 0;                      // Ek of node i is empty
+    degree[i] = len[i];                 // degree of node i
+  }
+  mark = internal::cs_wclear<Index>(0, 0, w, n);         /* clear w */
+  elen[n] = -2;                         /* n is a dead element */
+  Cp[n] = -1;                           /* n is a root of assembly tree */
+  w[n] = 0;                             /* n is a dead element */
+  
+  /* --- Initialize degree lists ------------------------------------------ */
+  for(i = 0; i < n; i++)
+  {
+    d = degree[i];
+    if(d == 0)                         /* node i is empty */
+    {
+      elen[i] = -2;                 /* element i is dead */
+      nel++;
+      Cp[i] = -1;                   /* i is a root of assembly tree */
+      w[i] = 0;
+    }
+    else if(d > dense)                 /* node i is dense */
+    {
+      nv[i] = 0;                    /* absorb i into element n */
+      elen[i] = -1;                 /* node i is dead */
+      nel++;
+      Cp[i] = amd_flip (n);
+      nv[n]++;
+    }
+    else
+    {
+      if(head[d] != -1) last[head[d]] = i;
+      next[i] = head[d];           /* put node i in degree list d */
+      head[d] = i;
+    }
+  }
+  
+  while (nel < n)                         /* while (selecting pivots) do */
+  {
+    /* --- Select node of minimum approximate degree -------------------- */
+    for(k = -1; mindeg < n && (k = head[mindeg]) == -1; mindeg++) {}
+    if(next[k] != -1) last[next[k]] = -1;
+    head[mindeg] = next[k];          /* remove k from degree list */
+    elenk = elen[k];                  /* elenk = |Ek| */
+    nvk = nv[k];                      /* # of nodes k represents */
+    nel += nvk;                        /* nv[k] nodes of A eliminated */
+    
+    /* --- Garbage collection ------------------------------------------- */
+    if(elenk > 0 && cnz + mindeg >= nzmax)
+    {
+      for(j = 0; j < n; j++)
+      {
+        if((p = Cp[j]) >= 0)      /* j is a live node or element */
+        {
+          Cp[j] = Ci[p];          /* save first entry of object */
+          Ci[p] = amd_flip (j);    /* first entry is now amd_flip(j) */
+        }
+      }
+      for(q = 0, p = 0; p < cnz; ) /* scan all of memory */
+      {
+        if((j = amd_flip (Ci[p++])) >= 0)  /* found object j */
+        {
+          Ci[q] = Cp[j];       /* restore first entry of object */
+          Cp[j] = q++;          /* new pointer to object j */
+          for(k3 = 0; k3 < len[j]-1; k3++) Ci[q++] = Ci[p++];
+        }
+      }
+      cnz = q;                       /* Ci[cnz...nzmax-1] now free */
+    }
+    
+    /* --- Construct new element ---------------------------------------- */
+    dk = 0;
+    nv[k] = -nvk;                     /* flag k as in Lk */
+    p = Cp[k];
+    pk1 = (elenk == 0) ? p : cnz;      /* do in place if elen[k] == 0 */
+    pk2 = pk1;
+    for(k1 = 1; k1 <= elenk + 1; k1++)
+    {
+      if(k1 > elenk)
+      {
+        e = k;                     /* search the nodes in k */
+        pj = p;                    /* list of nodes starts at Ci[pj]*/
+        ln = len[k] - elenk;      /* length of list of nodes in k */
+      }
+      else
+      {
+        e = Ci[p++];              /* search the nodes in e */
+        pj = Cp[e];
+        ln = len[e];              /* length of list of nodes in e */
+      }
+      for(k2 = 1; k2 <= ln; k2++)
+      {
+        i = Ci[pj++];
+        if((nvi = nv[i]) <= 0) continue; /* node i dead, or seen */
+        dk += nvi;                 /* degree[Lk] += size of node i */
+        nv[i] = -nvi;             /* negate nv[i] to denote i in Lk*/
+        Ci[pk2++] = i;            /* place i in Lk */
+        if(next[i] != -1) last[next[i]] = last[i];
+        if(last[i] != -1)         /* remove i from degree list */
+        {
+          next[last[i]] = next[i];
+        }
+        else
+        {
+          head[degree[i]] = next[i];
+        }
+      }
+      if(e != k)
+      {
+        Cp[e] = amd_flip (k);      /* absorb e into k */
+        w[e] = 0;                 /* e is now a dead element */
+      }
+    }
+    if(elenk != 0) cnz = pk2;         /* Ci[cnz...nzmax] is free */
+    degree[k] = dk;                   /* external degree of k - |Lk\i| */
+    Cp[k] = pk1;                      /* element k is in Ci[pk1..pk2-1] */
+    len[k] = pk2 - pk1;
+    elen[k] = -2;                     /* k is now an element */
+    
+    /* --- Find set differences ----------------------------------------- */
+    mark = internal::cs_wclear<Index>(mark, lemax, w, n);  /* clear w if necessary */
+    for(pk = pk1; pk < pk2; pk++)    /* scan 1: find |Le\Lk| */
+    {
+      i = Ci[pk];
+      if((eln = elen[i]) <= 0) continue;/* skip if elen[i] empty */
+      nvi = -nv[i];                      /* nv[i] was negated */
+      wnvi = mark - nvi;
+      for(p = Cp[i]; p <= Cp[i] + eln - 1; p++)  /* scan Ei */
+      {
+        e = Ci[p];
+        if(w[e] >= mark)
+        {
+          w[e] -= nvi;          /* decrement |Le\Lk| */
+        }
+        else if(w[e] != 0)        /* ensure e is a live element */
+        {
+          w[e] = degree[e] + wnvi; /* 1st time e seen in scan 1 */
+        }
+      }
+    }
+    
+    /* --- Degree update ------------------------------------------------ */
+    for(pk = pk1; pk < pk2; pk++)    /* scan2: degree update */
+    {
+      i = Ci[pk];                   /* consider node i in Lk */
+      p1 = Cp[i];
+      p2 = p1 + elen[i] - 1;
+      pn = p1;
+      for(h = 0, d = 0, p = p1; p <= p2; p++)    /* scan Ei */
+      {
+        e = Ci[p];
+        if(w[e] != 0)             /* e is an unabsorbed element */
+        {
+          dext = w[e] - mark;   /* dext = |Le\Lk| */
+          if(dext > 0)
+          {
+            d += dext;         /* sum up the set differences */
+            Ci[pn++] = e;     /* keep e in Ei */
+            h += e;            /* compute the hash of node i */
+          }
+          else
+          {
+            Cp[e] = amd_flip (k);  /* aggressive absorb. e->k */
+            w[e] = 0;             /* e is a dead element */
+          }
+        }
+      }
+      elen[i] = pn - p1 + 1;        /* elen[i] = |Ei| */
+      p3 = pn;
+      p4 = p1 + len[i];
+      for(p = p2 + 1; p < p4; p++) /* prune edges in Ai */
+      {
+        j = Ci[p];
+        if((nvj = nv[j]) <= 0) continue; /* node j dead or in Lk */
+        d += nvj;                  /* degree(i) += |j| */
+        Ci[pn++] = j;             /* place j in node list of i */
+        h += j;                    /* compute hash for node i */
+      }
+      if(d == 0)                     /* check for mass elimination */
+      {
+        Cp[i] = amd_flip (k);      /* absorb i into k */
+        nvi = -nv[i];
+        dk -= nvi;                 /* |Lk| -= |i| */
+        nvk += nvi;                /* |k| += nv[i] */
+        nel += nvi;
+        nv[i] = 0;
+        elen[i] = -1;             /* node i is dead */
+      }
+      else
+      {
+        degree[i] = std::min<Index> (degree[i], d);   /* update degree(i) */
+        Ci[pn] = Ci[p3];         /* move first node to end */
+        Ci[p3] = Ci[p1];         /* move 1st el. to end of Ei */
+        Ci[p1] = k;               /* add k as 1st element in of Ei */
+        len[i] = pn - p1 + 1;     /* new len of adj. list of node i */
+        h %= n;                    /* finalize hash of i */
+        next[i] = hhead[h];      /* place i in hash bucket */
+        hhead[h] = i;
+        last[i] = h;              /* save hash of i in last[i] */
+      }
+    }                                   /* scan2 is done */
+    degree[k] = dk;                   /* finalize |Lk| */
+    lemax = std::max<Index>(lemax, dk);
+    mark = internal::cs_wclear<Index>(mark+lemax, lemax, w, n);    /* clear w */
+    
+    /* --- Supernode detection ------------------------------------------ */
+    for(pk = pk1; pk < pk2; pk++)
+    {
+      i = Ci[pk];
+      if(nv[i] >= 0) continue;         /* skip if i is dead */
+      h = last[i];                      /* scan hash bucket of node i */
+      i = hhead[h];
+      hhead[h] = -1;                    /* hash bucket will be empty */
+      for(; i != -1 && next[i] != -1; i = next[i], mark++)
+      {
+        ln = len[i];
+        eln = elen[i];
+        for(p = Cp[i]+1; p <= Cp[i] + ln-1; p++) w[Ci[p]] = mark;
+        jlast = i;
+        for(j = next[i]; j != -1; ) /* compare i with all j */
+        {
+          ok = (len[j] == ln) && (elen[j] == eln);
+          for(p = Cp[j] + 1; ok && p <= Cp[j] + ln - 1; p++)
+          {
+            if(w[Ci[p]] != mark) ok = 0;    /* compare i and j*/
+          }
+          if(ok)                     /* i and j are identical */
+          {
+            Cp[j] = amd_flip (i);  /* absorb j into i */
+            nv[i] += nv[j];
+            nv[j] = 0;
+            elen[j] = -1;         /* node j is dead */
+            j = next[j];          /* delete j from hash bucket */
+            next[jlast] = j;
+          }
+          else
+          {
+            jlast = j;             /* j and i are different */
+            j = next[j];
+          }
+        }
+      }
+    }
+    
+    /* --- Finalize new element------------------------------------------ */
+    for(p = pk1, pk = pk1; pk < pk2; pk++)   /* finalize Lk */
+    {
+      i = Ci[pk];
+      if((nvi = -nv[i]) <= 0) continue;/* skip if i is dead */
+      nv[i] = nvi;                      /* restore nv[i] */
+      d = degree[i] + dk - nvi;         /* compute external degree(i) */
+      d = std::min<Index> (d, n - nel - nvi);
+      if(head[d] != -1) last[head[d]] = i;
+      next[i] = head[d];               /* put i back in degree list */
+      last[i] = -1;
+      head[d] = i;
+      mindeg = std::min<Index> (mindeg, d);       /* find new minimum degree */
+      degree[i] = d;
+      Ci[p++] = i;                      /* place i in Lk */
+    }
+    nv[k] = nvk;                      /* # nodes absorbed into k */
+    if((len[k] = p-pk1) == 0)         /* length of adj list of element k*/
+    {
+      Cp[k] = -1;                   /* k is a root of the tree */
+      w[k] = 0;                     /* k is now a dead element */
+    }
+    if(elenk != 0) cnz = p;           /* free unused space in Lk */
+  }
+  
+  /* --- Postordering ----------------------------------------------------- */
+  for(i = 0; i < n; i++) Cp[i] = amd_flip (Cp[i]);/* fix assembly tree */
+  for(j = 0; j <= n; j++) head[j] = -1;
+  for(j = n; j >= 0; j--)              /* place unordered nodes in lists */
+  {
+    if(nv[j] > 0) continue;          /* skip if j is an element */
+    next[j] = head[Cp[j]];          /* place j in list of its parent */
+    head[Cp[j]] = j;
+  }
+  for(e = n; e >= 0; e--)              /* place elements in lists */
+  {
+    if(nv[e] <= 0) continue;         /* skip unless e is an element */
+    if(Cp[e] != -1)
+    {
+      next[e] = head[Cp[e]];      /* place e in list of its parent */
+      head[Cp[e]] = e;
+    }
+  }
+  for(k = 0, i = 0; i <= n; i++)       /* postorder the assembly tree */
+  {
+    if(Cp[i] == -1) k = internal::cs_tdfs<Index>(i, k, head, next, perm.indices().data(), w);
+  }
+  
+  perm.indices().conservativeResize(n);
+
+  delete[] W;
+}
+
+} // namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_AMD_H
diff --git a/extern/Eigen3/Eigen/src/PaStiXSupport/PaStiXSupport.h b/extern/Eigen3/Eigen/src/PaStiXSupport/PaStiXSupport.h
new file mode 100644
index 00000000000..82e137c645a
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/PaStiXSupport/PaStiXSupport.h
@@ -0,0 +1,742 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Désiré Nuentsa-Wakam <desire.nuentsa_wakam@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_PASTIXSUPPORT_H
+#define EIGEN_PASTIXSUPPORT_H
+
+namespace Eigen { 
+
+/** \ingroup PaStiXSupport_Module
+  * \brief Interface to the PaStix solver
+  * 
+  * This class is used to solve the linear systems A.X = B via the PaStix library. 
+  * The matrix can be either real or complex, symmetric or not.
+  *
+  * \sa TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType, bool IsStrSym = false> class PastixLU;
+template<typename _MatrixType, int Options> class PastixLLT;
+template<typename _MatrixType, int Options> class PastixLDLT;
+
+namespace internal
+{
+    
+  template<class Pastix> struct pastix_traits;
+
+  template<typename _MatrixType>
+  struct pastix_traits< PastixLU<_MatrixType> >
+  {
+    typedef _MatrixType MatrixType;
+    typedef typename _MatrixType::Scalar Scalar;
+    typedef typename _MatrixType::RealScalar RealScalar;
+    typedef typename _MatrixType::Index Index;
+  };
+
+  template<typename _MatrixType, int Options>
+  struct pastix_traits< PastixLLT<_MatrixType,Options> >
+  {
+    typedef _MatrixType MatrixType;
+    typedef typename _MatrixType::Scalar Scalar;
+    typedef typename _MatrixType::RealScalar RealScalar;
+    typedef typename _MatrixType::Index Index;
+  };
+
+  template<typename _MatrixType, int Options>
+  struct pastix_traits< PastixLDLT<_MatrixType,Options> >
+  {
+    typedef _MatrixType MatrixType;
+    typedef typename _MatrixType::Scalar Scalar;
+    typedef typename _MatrixType::RealScalar RealScalar;
+    typedef typename _MatrixType::Index Index;
+  };
+  
+  void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, float *vals, int *perm, int * invp, float *x, int nbrhs, int *iparm, double *dparm)
+  {
+    if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; }
+    if (nbrhs == 0) {x = NULL; nbrhs=1;}
+    s_pastix(pastix_data, pastix_comm, n, ptr, idx, vals, perm, invp, x, nbrhs, iparm, dparm); 
+  }
+  
+  void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, double *vals, int *perm, int * invp, double *x, int nbrhs, int *iparm, double *dparm)
+  {
+    if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; }
+    if (nbrhs == 0) {x = NULL; nbrhs=1;}
+    d_pastix(pastix_data, pastix_comm, n, ptr, idx, vals, perm, invp, x, nbrhs, iparm, dparm); 
+  }
+  
+  void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<float> *vals, int *perm, int * invp, std::complex<float> *x, int nbrhs, int *iparm, double *dparm)
+  {
+    if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; }
+    if (nbrhs == 0) {x = NULL; nbrhs=1;}
+    c_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast<COMPLEX*>(vals), perm, invp, reinterpret_cast<COMPLEX*>(x), nbrhs, iparm, dparm); 
+  }
+  
+  void eigen_pastix(pastix_data_t **pastix_data, int pastix_comm, int n, int *ptr, int *idx, std::complex<double> *vals, int *perm, int * invp, std::complex<double> *x, int nbrhs, int *iparm, double *dparm)
+  {
+    if (n == 0) { ptr = NULL; idx = NULL; vals = NULL; }
+    if (nbrhs == 0) {x = NULL; nbrhs=1;}
+    z_pastix(pastix_data, pastix_comm, n, ptr, idx, reinterpret_cast<DCOMPLEX*>(vals), perm, invp, reinterpret_cast<DCOMPLEX*>(x), nbrhs, iparm, dparm); 
+  }
+
+  // Convert the matrix  to Fortran-style Numbering
+  template <typename MatrixType>
+  void c_to_fortran_numbering (MatrixType& mat)
+  {
+    if ( !(mat.outerIndexPtr()[0]) ) 
+    { 
+      int i;
+      for(i = 0; i <= mat.rows(); ++i)
+        ++mat.outerIndexPtr()[i];
+      for(i = 0; i < mat.nonZeros(); ++i)
+        ++mat.innerIndexPtr()[i];
+    }
+  }
+  
+  // Convert to C-style Numbering
+  template <typename MatrixType>
+  void fortran_to_c_numbering (MatrixType& mat)
+  {
+    // Check the Numbering
+    if ( mat.outerIndexPtr()[0] == 1 ) 
+    { // Convert to C-style numbering
+      int i;
+      for(i = 0; i <= mat.rows(); ++i)
+        --mat.outerIndexPtr()[i];
+      for(i = 0; i < mat.nonZeros(); ++i)
+        --mat.innerIndexPtr()[i];
+    }
+  }
+}
+
+// This is the base class to interface with PaStiX functions. 
+// Users should not used this class directly. 
+template <class Derived>
+class PastixBase : internal::noncopyable
+{
+  public:
+    typedef typename internal::pastix_traits<Derived>::MatrixType _MatrixType;
+    typedef _MatrixType MatrixType;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    typedef Matrix<Scalar,Dynamic,1> Vector;
+    typedef SparseMatrix<Scalar, ColMajor> ColSpMatrix;
+    
+  public:
+    
+    PastixBase() : m_initisOk(false), m_analysisIsOk(false), m_factorizationIsOk(false), m_isInitialized(false), m_pastixdata(0), m_size(0)
+    {
+      init();
+    }
+    
+    ~PastixBase() 
+    {
+      clean();
+    }
+
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<PastixBase, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "Pastix solver is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "PastixBase::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<PastixBase, Rhs>(*this, b.derived());
+    }
+    
+    template<typename Rhs,typename Dest>
+    bool _solve (const MatrixBase<Rhs> &b, MatrixBase<Dest> &x) const;
+    
+    /** \internal */
+    template<typename Rhs, typename DestScalar, int DestOptions, typename DestIndex>
+    void _solve_sparse(const Rhs& b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+    {
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      eigen_assert(rows()==b.rows());
+      
+      // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix.
+      static const int NbColsAtOnce = 1;
+      int rhsCols = b.cols();
+      int size = b.rows();
+      Eigen::Matrix<DestScalar,Dynamic,Dynamic> tmp(size,rhsCols);
+      for(int k=0; k<rhsCols; k+=NbColsAtOnce)
+      {
+        int actualCols = std::min<int>(rhsCols-k, NbColsAtOnce);
+        tmp.leftCols(actualCols) = b.middleCols(k,actualCols);
+        tmp.leftCols(actualCols) = derived().solve(tmp.leftCols(actualCols));
+        dest.middleCols(k,actualCols) = tmp.leftCols(actualCols).sparseView();
+      }
+    }
+    
+    Derived& derived()
+    {
+      return *static_cast<Derived*>(this);
+    }
+    const Derived& derived() const
+    {
+      return *static_cast<const Derived*>(this);
+    }
+
+    /** Returns a reference to the integer vector IPARM of PaStiX parameters
+      * to modify the default parameters. 
+      * The statistics related to the different phases of factorization and solve are saved here as well
+      * \sa analyzePattern() factorize()
+      */
+    Array<Index,IPARM_SIZE,1>& iparm()
+    {
+      return m_iparm; 
+    }
+    
+    /** Return a reference to a particular index parameter of the IPARM vector 
+     * \sa iparm()
+     */
+    
+    int& iparm(int idxparam)
+    {
+      return m_iparm(idxparam);
+    }
+    
+     /** Returns a reference to the double vector DPARM of PaStiX parameters 
+      * The statistics related to the different phases of factorization and solve are saved here as well
+      * \sa analyzePattern() factorize()
+      */
+    Array<RealScalar,IPARM_SIZE,1>& dparm()
+    {
+      return m_dparm; 
+    }
+    
+    
+    /** Return a reference to a particular index parameter of the DPARM vector 
+     * \sa dparm()
+     */
+    double& dparm(int idxparam)
+    {
+      return m_dparm(idxparam);
+    }
+    
+    inline Index cols() const { return m_size; }
+    inline Index rows() const { return m_size; }
+    
+     /** \brief Reports whether previous computation was successful.
+      *
+      * \returns \c Success if computation was succesful,
+      *          \c NumericalIssue if the PaStiX reports a problem
+      *          \c InvalidInput if the input matrix is invalid
+      *
+      * \sa iparm()          
+      */
+    ComputationInfo info() const
+    {
+      eigen_assert(m_isInitialized && "Decomposition is not initialized.");
+      return m_info;
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::sparse_solve_retval<PastixBase, Rhs>
+    solve(const SparseMatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "Pastix LU, LLT or LDLT is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "PastixBase::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::sparse_solve_retval<PastixBase, Rhs>(*this, b.derived());
+    }
+    
+  protected:
+
+    // Initialize the Pastix data structure, check the matrix
+    void init(); 
+    
+    // Compute the ordering and the symbolic factorization
+    void analyzePattern(ColSpMatrix& mat);
+    
+    // Compute the numerical factorization
+    void factorize(ColSpMatrix& mat);
+    
+    // Free all the data allocated by Pastix
+    void clean()
+    {
+      eigen_assert(m_initisOk && "The Pastix structure should be allocated first"); 
+      m_iparm(IPARM_START_TASK) = API_TASK_CLEAN;
+      m_iparm(IPARM_END_TASK) = API_TASK_CLEAN;
+      internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, 0, 0, 0, (Scalar*)0,
+                             m_perm.data(), m_invp.data(), 0, 0, m_iparm.data(), m_dparm.data());
+    }
+    
+    void compute(ColSpMatrix& mat);
+    
+    int m_initisOk; 
+    int m_analysisIsOk;
+    int m_factorizationIsOk;
+    bool m_isInitialized;
+    mutable ComputationInfo m_info; 
+    mutable pastix_data_t *m_pastixdata; // Data structure for pastix
+    mutable int m_comm; // The MPI communicator identifier
+    mutable Matrix<int,IPARM_SIZE,1> m_iparm; // integer vector for the input parameters
+    mutable Matrix<double,DPARM_SIZE,1> m_dparm; // Scalar vector for the input parameters
+    mutable Matrix<Index,Dynamic,1> m_perm;  // Permutation vector
+    mutable Matrix<Index,Dynamic,1> m_invp;  // Inverse permutation vector
+    mutable int m_size; // Size of the matrix 
+}; 
+
+ /** Initialize the PaStiX data structure. 
+   *A first call to this function fills iparm and dparm with the default PaStiX parameters
+   * \sa iparm() dparm()
+   */
+template <class Derived>
+void PastixBase<Derived>::init()
+{
+  m_size = 0; 
+  m_iparm.setZero(IPARM_SIZE);
+  m_dparm.setZero(DPARM_SIZE);
+  
+  m_iparm(IPARM_MODIFY_PARAMETER) = API_NO;
+  pastix(&m_pastixdata, MPI_COMM_WORLD,
+         0, 0, 0, 0,
+         0, 0, 0, 1, m_iparm.data(), m_dparm.data());
+  
+  m_iparm[IPARM_MATRIX_VERIFICATION] = API_NO;
+  m_iparm[IPARM_VERBOSE]             = 2;
+  m_iparm[IPARM_ORDERING]            = API_ORDER_SCOTCH;
+  m_iparm[IPARM_INCOMPLETE]          = API_NO;
+  m_iparm[IPARM_OOC_LIMIT]           = 2000;
+  m_iparm[IPARM_RHS_MAKING]          = API_RHS_B;
+  m_iparm(IPARM_MATRIX_VERIFICATION) = API_NO;
+  
+  m_iparm(IPARM_START_TASK) = API_TASK_INIT;
+  m_iparm(IPARM_END_TASK) = API_TASK_INIT;
+  internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, 0, 0, 0, (Scalar*)0,
+                         0, 0, 0, 0, m_iparm.data(), m_dparm.data());
+  
+  // Check the returned error
+  if(m_iparm(IPARM_ERROR_NUMBER)) {
+    m_info = InvalidInput;
+    m_initisOk = false;
+  }
+  else { 
+    m_info = Success;
+    m_initisOk = true;
+  }
+}
+
+template <class Derived>
+void PastixBase<Derived>::compute(ColSpMatrix& mat)
+{
+  eigen_assert(mat.rows() == mat.cols() && "The input matrix should be squared");
+  
+  analyzePattern(mat);  
+  factorize(mat);
+  
+  m_iparm(IPARM_MATRIX_VERIFICATION) = API_NO;
+  m_isInitialized = m_factorizationIsOk;
+}
+
+
+template <class Derived>
+void PastixBase<Derived>::analyzePattern(ColSpMatrix& mat)
+{                         
+  eigen_assert(m_initisOk && "The initialization of PaSTiX failed");
+  
+  // clean previous calls
+  if(m_size>0)
+    clean();
+  
+  m_size = mat.rows();
+  m_perm.resize(m_size);
+  m_invp.resize(m_size);
+  
+  m_iparm(IPARM_START_TASK) = API_TASK_ORDERING;
+  m_iparm(IPARM_END_TASK) = API_TASK_ANALYSE;
+  internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, m_size, mat.outerIndexPtr(), mat.innerIndexPtr(),
+               mat.valuePtr(), m_perm.data(), m_invp.data(), 0, 0, m_iparm.data(), m_dparm.data());
+  
+  // Check the returned error
+  if(m_iparm(IPARM_ERROR_NUMBER))
+  {
+    m_info = NumericalIssue;
+    m_analysisIsOk = false;
+  }
+  else
+  { 
+    m_info = Success;
+    m_analysisIsOk = true;
+  }
+}
+
+template <class Derived>
+void PastixBase<Derived>::factorize(ColSpMatrix& mat)
+{
+//   if(&m_cpyMat != &mat) m_cpyMat = mat;
+  eigen_assert(m_analysisIsOk && "The analysis phase should be called before the factorization phase");
+  m_iparm(IPARM_START_TASK) = API_TASK_NUMFACT;
+  m_iparm(IPARM_END_TASK) = API_TASK_NUMFACT;
+  m_size = mat.rows();
+  
+  internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, m_size, mat.outerIndexPtr(), mat.innerIndexPtr(),
+               mat.valuePtr(), m_perm.data(), m_invp.data(), 0, 0, m_iparm.data(), m_dparm.data());
+  
+  // Check the returned error
+  if(m_iparm(IPARM_ERROR_NUMBER))
+  {
+    m_info = NumericalIssue;
+    m_factorizationIsOk = false;
+    m_isInitialized = false;
+  }
+  else
+  {
+    m_info = Success;
+    m_factorizationIsOk = true;
+    m_isInitialized = true;
+  }
+}
+
+/* Solve the system */
+template<typename Base>
+template<typename Rhs,typename Dest>
+bool PastixBase<Base>::_solve (const MatrixBase<Rhs> &b, MatrixBase<Dest> &x) const
+{
+  eigen_assert(m_isInitialized && "The matrix should be factorized first");
+  EIGEN_STATIC_ASSERT((Dest::Flags&RowMajorBit)==0,
+                     THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
+  int rhs = 1;
+  
+  x = b; /* on return, x is overwritten by the computed solution */
+  
+  for (int i = 0; i < b.cols(); i++){
+    m_iparm[IPARM_START_TASK]          = API_TASK_SOLVE;
+    m_iparm[IPARM_END_TASK]            = API_TASK_REFINE;
+  
+    internal::eigen_pastix(&m_pastixdata, MPI_COMM_WORLD, x.rows(), 0, 0, 0,
+                           m_perm.data(), m_invp.data(), &x(0, i), rhs, m_iparm.data(), m_dparm.data());
+  }
+  
+  // Check the returned error
+  m_info = m_iparm(IPARM_ERROR_NUMBER)==0 ? Success : NumericalIssue;
+  
+  return m_iparm(IPARM_ERROR_NUMBER)==0;
+}
+
+/** \ingroup PaStiXSupport_Module
+  * \class PastixLU
+  * \brief Sparse direct LU solver based on PaStiX library
+  * 
+  * This class is used to solve the linear systems A.X = B with a supernodal LU 
+  * factorization in the PaStiX library. The matrix A should be squared and nonsingular
+  * PaStiX requires that the matrix A has a symmetric structural pattern. 
+  * This interface can symmetrize the input matrix otherwise. 
+  * The vectors or matrices X and B can be either dense or sparse.
+  * 
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam IsStrSym Indicates if the input matrix has a symmetric pattern, default is false
+  * NOTE : Note that if the analysis and factorization phase are called separately, 
+  * the input matrix will be symmetrized at each call, hence it is advised to 
+  * symmetrize the matrix in a end-user program and set \p IsStrSym to true
+  * 
+  * \sa \ref TutorialSparseDirectSolvers
+  * 
+  */
+template<typename _MatrixType, bool IsStrSym>
+class PastixLU : public PastixBase< PastixLU<_MatrixType> >
+{
+  public:
+    typedef _MatrixType MatrixType;
+    typedef PastixBase<PastixLU<MatrixType> > Base;
+    typedef typename Base::ColSpMatrix ColSpMatrix;
+    typedef typename MatrixType::Index Index;
+    
+  public:
+    PastixLU() : Base()
+    {
+      init();
+    }
+    
+    PastixLU(const MatrixType& matrix):Base()
+    {
+      init();
+      compute(matrix);
+    }
+    /** Compute the LU supernodal factorization of \p matrix. 
+      * iparm and dparm can be used to tune the PaStiX parameters. 
+      * see the PaStiX user's manual
+      * \sa analyzePattern() factorize()
+      */
+    void compute (const MatrixType& matrix)
+    {
+      m_structureIsUptodate = false;
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::compute(temp);
+    }
+    /** Compute the LU symbolic factorization of \p matrix using its sparsity pattern. 
+      * Several ordering methods can be used at this step. See the PaStiX user's manual. 
+      * The result of this operation can be used with successive matrices having the same pattern as \p matrix
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    {
+      m_structureIsUptodate = false;
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::analyzePattern(temp);
+    }
+
+    /** Compute the LU supernodal factorization of \p matrix
+      * WARNING The matrix \p matrix should have the same structural pattern 
+      * as the same used in the analysis phase.
+      * \sa analyzePattern()
+      */ 
+    void factorize(const MatrixType& matrix)
+    {
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::factorize(temp);
+    }
+  protected:
+    
+    void init()
+    {
+      m_structureIsUptodate = false;
+      m_iparm(IPARM_SYM) = API_SYM_NO;
+      m_iparm(IPARM_FACTORIZATION) = API_FACT_LU;
+    }
+    
+    void grabMatrix(const MatrixType& matrix, ColSpMatrix& out)
+    {
+      if(IsStrSym)
+        out = matrix;
+      else
+      {
+        if(!m_structureIsUptodate)
+        {
+          // update the transposed structure
+          m_transposedStructure = matrix.transpose();
+          
+          // Set the elements of the matrix to zero 
+          for (Index j=0; j<m_transposedStructure.outerSize(); ++j) 
+            for(typename ColSpMatrix::InnerIterator it(m_transposedStructure, j); it; ++it)
+              it.valueRef() = 0.0;
+
+          m_structureIsUptodate = true;
+        }
+        
+        out = m_transposedStructure + matrix;
+      }
+      internal::c_to_fortran_numbering(out);
+    }
+    
+    using Base::m_iparm;
+    using Base::m_dparm;
+    
+    ColSpMatrix m_transposedStructure;
+    bool m_structureIsUptodate;
+};
+
+/** \ingroup PaStiXSupport_Module
+  * \class PastixLLT
+  * \brief A sparse direct supernodal Cholesky (LLT) factorization and solver based on the PaStiX library
+  * 
+  * This class is used to solve the linear systems A.X = B via a LL^T supernodal Cholesky factorization
+  * available in the PaStiX library. The matrix A should be symmetric and positive definite
+  * WARNING Selfadjoint complex matrices are not supported in the current version of PaStiX
+  * The vectors or matrices X and B can be either dense or sparse
+  * 
+  * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam UpLo The part of the matrix to use : Lower or Upper. The default is Lower as required by PaStiX
+  * 
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType, int _UpLo>
+class PastixLLT : public PastixBase< PastixLLT<_MatrixType, _UpLo> >
+{
+  public:
+    typedef _MatrixType MatrixType;
+    typedef PastixBase<PastixLLT<MatrixType, _UpLo> > Base;
+    typedef typename Base::ColSpMatrix ColSpMatrix;
+    
+  public:
+    enum { UpLo = _UpLo };
+    PastixLLT() : Base()
+    {
+      init();
+    }
+    
+    PastixLLT(const MatrixType& matrix):Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    /** Compute the L factor of the LL^T supernodal factorization of \p matrix 
+      * \sa analyzePattern() factorize()
+      */
+    void compute (const MatrixType& matrix)
+    {
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::compute(temp);
+    }
+
+     /** Compute the LL^T symbolic factorization of \p matrix using its sparsity pattern
+      * The result of this operation can be used with successive matrices having the same pattern as \p matrix
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    {
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::analyzePattern(temp);
+    }
+      /** Compute the LL^T supernodal numerical factorization of \p matrix 
+        * \sa analyzePattern()
+        */
+    void factorize(const MatrixType& matrix)
+    {
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::factorize(temp);
+    }
+  protected:
+    using Base::m_iparm;
+    
+    void init()
+    {
+      m_iparm(IPARM_SYM) = API_SYM_YES;
+      m_iparm(IPARM_FACTORIZATION) = API_FACT_LLT;
+    }
+    
+    void grabMatrix(const MatrixType& matrix, ColSpMatrix& out)
+    {
+      // Pastix supports only lower, column-major matrices 
+      out.template selfadjointView<Lower>() = matrix.template selfadjointView<UpLo>();
+      internal::c_to_fortran_numbering(out);
+    }
+};
+
+/** \ingroup PaStiXSupport_Module
+  * \class PastixLDLT
+  * \brief A sparse direct supernodal Cholesky (LLT) factorization and solver based on the PaStiX library
+  * 
+  * This class is used to solve the linear systems A.X = B via a LDL^T supernodal Cholesky factorization
+  * available in the PaStiX library. The matrix A should be symmetric and positive definite
+  * WARNING Selfadjoint complex matrices are not supported in the current version of PaStiX
+  * The vectors or matrices X and B can be either dense or sparse
+  * 
+  * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam UpLo The part of the matrix to use : Lower or Upper. The default is Lower as required by PaStiX
+  * 
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType, int _UpLo>
+class PastixLDLT : public PastixBase< PastixLDLT<_MatrixType, _UpLo> >
+{
+  public:
+    typedef _MatrixType MatrixType;
+    typedef PastixBase<PastixLDLT<MatrixType, _UpLo> > Base; 
+    typedef typename Base::ColSpMatrix ColSpMatrix;
+    
+  public:
+    enum { UpLo = _UpLo };
+    PastixLDLT():Base()
+    {
+      init();
+    }
+    
+    PastixLDLT(const MatrixType& matrix):Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    /** Compute the L and D factors of the LDL^T factorization of \p matrix 
+      * \sa analyzePattern() factorize()
+      */
+    void compute (const MatrixType& matrix)
+    {
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::compute(temp);
+    }
+
+    /** Compute the LDL^T symbolic factorization of \p matrix using its sparsity pattern
+      * The result of this operation can be used with successive matrices having the same pattern as \p matrix
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    { 
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::analyzePattern(temp);
+    }
+    /** Compute the LDL^T supernodal numerical factorization of \p matrix 
+      * 
+      */
+    void factorize(const MatrixType& matrix)
+    {
+      ColSpMatrix temp;
+      grabMatrix(matrix, temp);
+      Base::factorize(temp);
+    }
+
+  protected:
+    using Base::m_iparm;
+    
+    void init()
+    {
+      m_iparm(IPARM_SYM) = API_SYM_YES;
+      m_iparm(IPARM_FACTORIZATION) = API_FACT_LDLT;
+    }
+    
+    void grabMatrix(const MatrixType& matrix, ColSpMatrix& out)
+    {
+      // Pastix supports only lower, column-major matrices 
+      out.template selfadjointView<Lower>() = matrix.template selfadjointView<UpLo>();
+      internal::c_to_fortran_numbering(out);
+    }
+};
+
+namespace internal {
+
+template<typename _MatrixType, typename Rhs>
+struct solve_retval<PastixBase<_MatrixType>, Rhs>
+  : solve_retval_base<PastixBase<_MatrixType>, Rhs>
+{
+  typedef PastixBase<_MatrixType> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+template<typename _MatrixType, typename Rhs>
+struct sparse_solve_retval<PastixBase<_MatrixType>, Rhs>
+  : sparse_solve_retval_base<PastixBase<_MatrixType>, Rhs>
+{
+  typedef PastixBase<_MatrixType> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve_sparse(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif
diff --git a/extern/Eigen3/Eigen/src/PardisoSupport/PardisoSupport.h b/extern/Eigen3/Eigen/src/PardisoSupport/PardisoSupport.h
new file mode 100644
index 00000000000..e6defc8c39e
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/PardisoSupport/PardisoSupport.h
@@ -0,0 +1,614 @@
+/*
+ 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 PARDISO
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_PARDISOSUPPORT_H
+#define EIGEN_PARDISOSUPPORT_H
+
+namespace Eigen { 
+
+template<typename _MatrixType> class PardisoLU;
+template<typename _MatrixType, int Options=Upper> class PardisoLLT;
+template<typename _MatrixType, int Options=Upper> class PardisoLDLT;
+
+namespace internal
+{
+  template<typename Index>
+  struct pardiso_run_selector
+  {
+    static Index run( _MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a,
+                      Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x)
+    {
+      Index error = 0;
+      ::pardiso(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error);
+      return error;
+    }
+  };
+  template<>
+  struct pardiso_run_selector<long long int>
+  {
+    typedef long long int Index;
+    static Index run( _MKL_DSS_HANDLE_t pt, Index maxfct, Index mnum, Index type, Index phase, Index n, void *a,
+                      Index *ia, Index *ja, Index *perm, Index nrhs, Index *iparm, Index msglvl, void *b, void *x)
+    {
+      Index error = 0;
+      ::pardiso_64(pt, &maxfct, &mnum, &type, &phase, &n, a, ia, ja, perm, &nrhs, iparm, &msglvl, b, x, &error);
+      return error;
+    }
+  };
+
+  template<class Pardiso> struct pardiso_traits;
+
+  template<typename _MatrixType>
+  struct pardiso_traits< PardisoLU<_MatrixType> >
+  {
+    typedef _MatrixType MatrixType;
+    typedef typename _MatrixType::Scalar Scalar;
+    typedef typename _MatrixType::RealScalar RealScalar;
+    typedef typename _MatrixType::Index Index;
+  };
+
+  template<typename _MatrixType, int Options>
+  struct pardiso_traits< PardisoLLT<_MatrixType, Options> >
+  {
+    typedef _MatrixType MatrixType;
+    typedef typename _MatrixType::Scalar Scalar;
+    typedef typename _MatrixType::RealScalar RealScalar;
+    typedef typename _MatrixType::Index Index;
+  };
+
+  template<typename _MatrixType, int Options>
+  struct pardiso_traits< PardisoLDLT<_MatrixType, Options> >
+  {
+    typedef _MatrixType MatrixType;
+    typedef typename _MatrixType::Scalar Scalar;
+    typedef typename _MatrixType::RealScalar RealScalar;
+    typedef typename _MatrixType::Index Index;    
+  };
+
+}
+
+template<class Derived>
+class PardisoImpl
+{
+    typedef internal::pardiso_traits<Derived> Traits;
+  public:
+    typedef typename Traits::MatrixType MatrixType;
+    typedef typename Traits::Scalar Scalar;
+    typedef typename Traits::RealScalar RealScalar;
+    typedef typename Traits::Index Index;
+    typedef SparseMatrix<Scalar,RowMajor,Index> SparseMatrixType;
+    typedef Matrix<Scalar,Dynamic,1> VectorType;
+    typedef Matrix<Index, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
+    typedef Matrix<Index, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
+    enum {
+      ScalarIsComplex = NumTraits<Scalar>::IsComplex
+    };
+
+    PardisoImpl()
+    {
+      eigen_assert((sizeof(Index) >= sizeof(_INTEGER_t) && sizeof(Index) <= 8) && "Non-supported index type");
+      m_iparm.setZero();
+      m_msglvl = 0; // No output
+      m_initialized = false;
+    }
+
+    ~PardisoImpl()
+    {
+      pardisoRelease();
+    }
+
+    inline Index cols() const { return m_size; }
+    inline Index rows() const { return m_size; }
+  
+    /** \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_initialized && "Decomposition is not initialized.");
+      return m_info;
+    }
+
+    /** \warning for advanced usage only.
+      * \returns a reference to the parameter array controlling PARDISO.
+      * See the PARDISO manual to know how to use it. */
+    Array<Index,64,1>& pardisoParameterArray()
+    {
+      return m_iparm;
+    }
+    
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      * 
+      * \sa factorize()
+      */
+    Derived& analyzePattern(const MatrixType& matrix);
+    
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    Derived& factorize(const MatrixType& matrix);
+
+    Derived& compute(const MatrixType& matrix);
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<PardisoImpl, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_initialized && "Pardiso solver is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<PardisoImpl, Rhs>(*this, b.derived());
+    }
+
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::sparse_solve_retval<PardisoImpl, Rhs>
+    solve(const SparseMatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_initialized && "Pardiso solver is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "PardisoImpl::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::sparse_solve_retval<PardisoImpl, Rhs>(*this, b.derived());
+    }
+
+    Derived& derived()
+    {
+      return *static_cast<Derived*>(this);
+    }
+    const Derived& derived() const
+    {
+      return *static_cast<const Derived*>(this);
+    }
+
+    template<typename BDerived, typename XDerived>
+    bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>& x) const;
+
+    /** \internal */
+    template<typename Rhs, typename DestScalar, int DestOptions, typename DestIndex>
+    void _solve_sparse(const Rhs& b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+    {
+      eigen_assert(m_size==b.rows());
+
+      // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix.
+      static const int NbColsAtOnce = 4;
+      int rhsCols = b.cols();
+      int size = b.rows();
+      // Pardiso cannot solve in-place,
+      // so we need two temporaries
+      Eigen::Matrix<DestScalar,Dynamic,Dynamic,ColMajor> tmp_rhs(size,rhsCols);
+      Eigen::Matrix<DestScalar,Dynamic,Dynamic,ColMajor> tmp_res(size,rhsCols);
+      for(int k=0; k<rhsCols; k+=NbColsAtOnce)
+      {
+        int actualCols = std::min<int>(rhsCols-k, NbColsAtOnce);
+        tmp_rhs.leftCols(actualCols) = b.middleCols(k,actualCols);
+        tmp_res.leftCols(actualCols) = derived().solve(tmp_rhs.leftCols(actualCols));
+        dest.middleCols(k,actualCols) = tmp_res.leftCols(actualCols).sparseView();
+      }
+    }
+
+  protected:
+    void pardisoRelease()
+    {
+      if(m_initialized) // Factorization ran at least once
+      {
+        internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, -1, m_size, 0, 0, 0, m_perm.data(), 0,
+                                                   m_iparm.data(), m_msglvl, 0, 0);
+      }
+    }
+
+    void pardisoInit(int type)
+    {
+      m_type = type;
+      bool symmetric = abs(m_type) < 10;
+      m_iparm[0] = 1;   // No solver default
+      m_iparm[1] = 3;   // use Metis for the ordering
+      m_iparm[2] = 1;   // Numbers of processors, value of OMP_NUM_THREADS
+      m_iparm[3] = 0;   // No iterative-direct algorithm
+      m_iparm[4] = 0;   // No user fill-in reducing permutation
+      m_iparm[5] = 0;   // Write solution into x
+      m_iparm[6] = 0;   // Not in use
+      m_iparm[7] = 2;   // Max numbers of iterative refinement steps
+      m_iparm[8] = 0;   // Not in use
+      m_iparm[9] = 13;  // Perturb the pivot elements with 1E-13
+      m_iparm[10] = symmetric ? 0 : 1; // Use nonsymmetric permutation and scaling MPS
+      m_iparm[11] = 0;  // Not in use
+      m_iparm[12] = symmetric ? 0 : 1;  // Maximum weighted matching algorithm is switched-off (default for symmetric).
+                                        // Try m_iparm[12] = 1 in case of inappropriate accuracy
+      m_iparm[13] = 0;  // Output: Number of perturbed pivots
+      m_iparm[14] = 0;  // Not in use
+      m_iparm[15] = 0;  // Not in use
+      m_iparm[16] = 0;  // Not in use
+      m_iparm[17] = -1; // Output: Number of nonzeros in the factor LU
+      m_iparm[18] = -1; // Output: Mflops for LU factorization
+      m_iparm[19] = 0;  // Output: Numbers of CG Iterations
+      
+      m_iparm[20] = 0;  // 1x1 pivoting
+      m_iparm[26] = 0;  // No matrix checker
+      m_iparm[27] = (sizeof(RealScalar) == 4) ? 1 : 0;
+      m_iparm[34] = 1;  // C indexing
+      m_iparm[59] = 1;  // Automatic switch between In-Core and Out-of-Core modes
+    }
+
+  protected:
+    // cached data to reduce reallocation, etc.
+    
+    void manageErrorCode(Index error)
+    {
+      switch(error)
+      {
+        case 0:
+          m_info = Success;
+          break;
+        case -4:
+        case -7:
+          m_info = NumericalIssue;
+          break;
+        default:
+          m_info = InvalidInput;
+      }
+    }
+
+    mutable SparseMatrixType m_matrix;
+    ComputationInfo m_info;
+    bool m_initialized, m_analysisIsOk, m_factorizationIsOk;
+    Index m_type, m_msglvl;
+    mutable void *m_pt[64];
+    mutable Array<Index,64,1> m_iparm;
+    mutable IntColVectorType m_perm;
+    Index m_size;
+    
+  private:
+    PardisoImpl(PardisoImpl &) {}
+};
+
+template<class Derived>
+Derived& PardisoImpl<Derived>::compute(const MatrixType& a)
+{
+  m_size = a.rows();
+  eigen_assert(a.rows() == a.cols());
+
+  pardisoRelease();
+  memset(m_pt, 0, sizeof(m_pt));
+  m_perm.setZero(m_size);
+  derived().getMatrix(a);
+  
+  Index error;
+  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 12, m_size,
+                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                     m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
+
+  manageErrorCode(error);
+  m_analysisIsOk = true;
+  m_factorizationIsOk = true;
+  m_initialized = true;
+  return derived();
+}
+
+template<class Derived>
+Derived& PardisoImpl<Derived>::analyzePattern(const MatrixType& a)
+{
+  m_size = a.rows();
+  eigen_assert(m_size == a.cols());
+
+  pardisoRelease();
+  memset(m_pt, 0, sizeof(m_pt));
+  m_perm.setZero(m_size);
+  derived().getMatrix(a);
+  
+  Index error;
+  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 11, m_size,
+                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                     m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
+  
+  manageErrorCode(error);
+  m_analysisIsOk = true;
+  m_factorizationIsOk = false;
+  m_initialized = true;
+  return derived();
+}
+
+template<class Derived>
+Derived& PardisoImpl<Derived>::factorize(const MatrixType& a)
+{
+  eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
+  eigen_assert(m_size == a.rows() && m_size == a.cols());
+  
+  derived().getMatrix(a);
+
+  Index error;  
+  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 22, m_size,
+                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                     m_perm.data(), 0, m_iparm.data(), m_msglvl, NULL, NULL);
+  
+  manageErrorCode(error);
+  m_factorizationIsOk = true;
+  return derived();
+}
+
+template<class Base>
+template<typename BDerived,typename XDerived>
+bool PardisoImpl<Base>::_solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived>& x) const
+{
+  if(m_iparm[0] == 0) // Factorization was not computed
+    return false;
+
+  //Index n = m_matrix.rows();
+  Index nrhs = Index(b.cols());
+  eigen_assert(m_size==b.rows());
+  eigen_assert(((MatrixBase<BDerived>::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major right hand sides are not supported");
+  eigen_assert(((MatrixBase<XDerived>::Flags & RowMajorBit) == 0 || nrhs == 1) && "Row-major matrices of unknowns are not supported");
+  eigen_assert(((nrhs == 1) || b.outerStride() == b.rows()));
+
+
+//  switch (transposed) {
+//    case SvNoTrans    : m_iparm[11] = 0 ; break;
+//    case SvTranspose  : m_iparm[11] = 2 ; break;
+//    case SvAdjoint    : m_iparm[11] = 1 ; break;
+//    default:
+//      //std::cerr << "Eigen: transposition  option \"" << transposed << "\" not supported by the PARDISO backend\n";
+//      m_iparm[11] = 0;
+//  }
+
+  Scalar* rhs_ptr = const_cast<Scalar*>(b.derived().data());
+  Matrix<Scalar,Dynamic,Dynamic,ColMajor> tmp;
+  
+  // Pardiso cannot solve in-place
+  if(rhs_ptr == x.derived().data())
+  {
+    tmp = b;
+    rhs_ptr = tmp.data();
+  }
+  
+  Index error;
+  error = internal::pardiso_run_selector<Index>::run(m_pt, 1, 1, m_type, 33, m_size,
+                                                     m_matrix.valuePtr(), m_matrix.outerIndexPtr(), m_matrix.innerIndexPtr(),
+                                                     m_perm.data(), nrhs, m_iparm.data(), m_msglvl,
+                                                     rhs_ptr, x.derived().data());
+
+  return error==0;
+}
+
+
+/** \ingroup PardisoSupport_Module
+  * \class PardisoLU
+  * \brief A sparse direct LU factorization and solver based on the PARDISO library
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a direct LU factorization
+  * using the Intel MKL PARDISO library. The sparse matrix A must be squared and invertible.
+  * The vectors or matrices X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename MatrixType>
+class PardisoLU : public PardisoImpl< PardisoLU<MatrixType> >
+{
+  protected:
+    typedef PardisoImpl< PardisoLU<MatrixType> > Base;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::RealScalar RealScalar;
+    using Base::pardisoInit;
+    using Base::m_matrix;
+    friend class PardisoImpl< PardisoLU<MatrixType> >;
+
+  public:
+
+    using Base::compute;
+    using Base::solve;
+
+    PardisoLU()
+      : Base()
+    {
+      pardisoInit(Base::ScalarIsComplex ? 13 : 11);
+    }
+
+    PardisoLU(const MatrixType& matrix)
+      : Base()
+    {
+      pardisoInit(Base::ScalarIsComplex ? 13 : 11);
+      compute(matrix);
+    }
+  protected:
+    void getMatrix(const MatrixType& matrix)
+    {
+      m_matrix = matrix;
+    }
+    
+  private:
+    PardisoLU(PardisoLU& ) {}
+};
+
+/** \ingroup PardisoSupport_Module
+  * \class PardisoLLT
+  * \brief A sparse direct Cholesky (LLT) factorization and solver based on the PARDISO library
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a LL^T Cholesky factorization
+  * using the Intel MKL PARDISO library. The sparse matrix A must be selfajoint and positive definite.
+  * The vectors or matrices X and B can be either dense or sparse.
+  *
+  * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam UpLo can be any bitwise combination of Upper, Lower. The default is Upper, meaning only the upper triangular part has to be used.
+  *         Upper|Lower can be used to tell both triangular parts can be used as input.
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename MatrixType, int _UpLo>
+class PardisoLLT : public PardisoImpl< PardisoLLT<MatrixType,_UpLo> >
+{
+  protected:
+    typedef PardisoImpl< PardisoLLT<MatrixType,_UpLo> > Base;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::Index Index;
+    typedef typename Base::RealScalar RealScalar;
+    using Base::pardisoInit;
+    using Base::m_matrix;
+    friend class PardisoImpl< PardisoLLT<MatrixType,_UpLo> >;
+
+  public:
+
+    enum { UpLo = _UpLo };
+    using Base::compute;
+    using Base::solve;
+
+    PardisoLLT()
+      : Base()
+    {
+      pardisoInit(Base::ScalarIsComplex ? 4 : 2);
+    }
+
+    PardisoLLT(const MatrixType& matrix)
+      : Base()
+    {
+      pardisoInit(Base::ScalarIsComplex ? 4 : 2);
+      compute(matrix);
+    }
+    
+  protected:
+    
+    void getMatrix(const MatrixType& matrix)
+    {
+      // PARDISO supports only upper, row-major matrices
+      PermutationMatrix<Dynamic,Dynamic,Index> p_null;
+      m_matrix.resize(matrix.rows(), matrix.cols());
+      m_matrix.template selfadjointView<Upper>() = matrix.template selfadjointView<UpLo>().twistedBy(p_null);
+    }
+    
+  private:
+    PardisoLLT(PardisoLLT& ) {}
+};
+
+/** \ingroup PardisoSupport_Module
+  * \class PardisoLDLT
+  * \brief A sparse direct Cholesky (LDLT) factorization and solver based on the PARDISO library
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a LDL^T Cholesky factorization
+  * using the Intel MKL PARDISO library. The sparse matrix A is assumed to be selfajoint and positive definite.
+  * For complex matrices, A can also be symmetric only, see the \a Options template parameter.
+  * The vectors or matrices X and B can be either dense or sparse.
+  *
+  * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam Options can be any bitwise combination of Upper, Lower, and Symmetric. The default is Upper, meaning only the upper triangular part has to be used.
+  *         Symmetric can be used for symmetric, non-selfadjoint complex matrices, the default being to assume a selfadjoint matrix.
+  *         Upper|Lower can be used to tell both triangular parts can be used as input.
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename MatrixType, int Options>
+class PardisoLDLT : public PardisoImpl< PardisoLDLT<MatrixType,Options> >
+{
+  protected:
+    typedef PardisoImpl< PardisoLDLT<MatrixType,Options> > Base;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::Index Index;
+    typedef typename Base::RealScalar RealScalar;
+    using Base::pardisoInit;
+    using Base::m_matrix;
+    friend class PardisoImpl< PardisoLDLT<MatrixType,Options> >;
+
+  public:
+
+    using Base::compute;
+    using Base::solve;
+    enum { UpLo = Options&(Upper|Lower) };
+
+    PardisoLDLT()
+      : Base()
+    {
+      pardisoInit(Base::ScalarIsComplex ? ( bool(Options&Symmetric) ? 6 : -4 ) : -2);
+    }
+
+    PardisoLDLT(const MatrixType& matrix)
+      : Base()
+    {
+      pardisoInit(Base::ScalarIsComplex ? ( bool(Options&Symmetric) ? 6 : -4 ) : -2);
+      compute(matrix);
+    }
+    
+    void getMatrix(const MatrixType& matrix)
+    {
+      // PARDISO supports only upper, row-major matrices
+      PermutationMatrix<Dynamic,Dynamic,Index> p_null;
+      m_matrix.resize(matrix.rows(), matrix.cols());
+      m_matrix.template selfadjointView<Upper>() = matrix.template selfadjointView<UpLo>().twistedBy(p_null);
+    }
+    
+  private:
+    PardisoLDLT(PardisoLDLT& ) {}
+};
+
+namespace internal {
+  
+template<typename _Derived, typename Rhs>
+struct solve_retval<PardisoImpl<_Derived>, Rhs>
+  : solve_retval_base<PardisoImpl<_Derived>, Rhs>
+{
+  typedef PardisoImpl<_Derived> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+template<typename Derived, typename Rhs>
+struct sparse_solve_retval<PardisoImpl<Derived>, Rhs>
+  : sparse_solve_retval_base<PardisoImpl<Derived>, Rhs>
+{
+  typedef PardisoImpl<Derived> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec().derived()._solve_sparse(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_PARDISOSUPPORT_H
diff --git a/extern/Eigen3/Eigen/src/QR/ColPivHouseholderQR.h b/extern/Eigen3/Eigen/src/QR/ColPivHouseholderQR.h
index f04c6038d6a..2daa23cc354 100644
--- a/extern/Eigen3/Eigen/src/QR/ColPivHouseholderQR.h
+++ b/extern/Eigen3/Eigen/src/QR/ColPivHouseholderQR.h
@@ -4,28 +4,15 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_H
 #define EIGEN_COLPIVOTINGHOUSEHOLDERQR_H
 
+namespace Eigen { 
+
 /** \ingroup QR_Module
   *
   * \class ColPivHouseholderQR
@@ -528,5 +515,6 @@ MatrixBase<Derived>::colPivHouseholderQr() const
   return ColPivHouseholderQR<PlainObject>(eval());
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_COLPIVOTINGHOUSEHOLDERQR_H
diff --git a/extern/Eigen3/Eigen/src/QR/ColPivHouseholderQR_MKL.h b/extern/Eigen3/Eigen/src/QR/ColPivHouseholderQR_MKL.h
new file mode 100644
index 00000000000..745ecf8be98
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/QR/ColPivHouseholderQR_MKL.h
@@ -0,0 +1,98 @@
+/*
+ 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
+ *    Householder QR decomposition of a matrix with column pivoting based on
+ *    LAPACKE_?geqp3 function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H
+#define EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by MKL */
+
+#define EIGEN_MKL_QR_COLPIV(EIGTYPE, MKLTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
+template<> inline\
+ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >& \
+ColPivHouseholderQR<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> >::compute( \
+              const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix) \
+\
+{ \
+  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
+  typedef MatrixType::Scalar Scalar; \
+  typedef MatrixType::RealScalar RealScalar; \
+  Index rows = matrix.rows();\
+  Index cols = matrix.cols();\
+  Index size = matrix.diagonalSize();\
+\
+  m_qr = matrix;\
+  m_hCoeffs.resize(size);\
+\
+  m_colsTranspositions.resize(cols);\
+  /*Index number_of_transpositions = 0;*/ \
+\
+  m_nonzero_pivots = 0; \
+  m_maxpivot = RealScalar(0);\
+  m_colsPermutation.resize(cols); \
+  m_colsPermutation.indices().setZero(); \
+\
+  lapack_int lda = m_qr.outerStride(), i; \
+  lapack_int matrix_order = MKLCOLROW; \
+  LAPACKE_##MKLPREFIX##geqp3( matrix_order, rows, cols, (MKLTYPE*)m_qr.data(), lda, (lapack_int*)m_colsPermutation.indices().data(), (MKLTYPE*)m_hCoeffs.data()); \
+  m_isInitialized = true; \
+  m_maxpivot=m_qr.diagonal().cwiseAbs().maxCoeff(); \
+  m_hCoeffs.adjointInPlace(); \
+  RealScalar premultiplied_threshold = internal::abs(m_maxpivot) * threshold(); \
+  lapack_int *perm = m_colsPermutation.indices().data(); \
+  for(i=0;i<size;i++) { \
+    m_nonzero_pivots += (internal::abs(m_qr.coeff(i,i)) > premultiplied_threshold);\
+  } \
+  for(i=0;i<cols;i++) perm[i]--;\
+\
+  /*m_det_pq = (number_of_transpositions%2) ? -1 : 1;  // TODO: It's not needed now; fix upon availability in Eigen */ \
+\
+  return *this; \
+}
+
+EIGEN_MKL_QR_COLPIV(double,   double,        d, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_QR_COLPIV(float,    float,         s, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_QR_COLPIV(dcomplex, MKL_Complex16, z, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_QR_COLPIV(scomplex, MKL_Complex8,  c, ColMajor, LAPACK_COL_MAJOR)
+
+EIGEN_MKL_QR_COLPIV(double,   double,        d, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_QR_COLPIV(float,    float,         s, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_QR_COLPIV(dcomplex, MKL_Complex16, z, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_QR_COLPIV(scomplex, MKL_Complex8,  c, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_COLPIVOTINGHOUSEHOLDERQR_MKL_H
diff --git a/extern/Eigen3/Eigen/src/QR/FullPivHouseholderQR.h b/extern/Eigen3/Eigen/src/QR/FullPivHouseholderQR.h
index dde3013be9d..37898e77cc2 100644
--- a/extern/Eigen3/Eigen/src/QR/FullPivHouseholderQR.h
+++ b/extern/Eigen3/Eigen/src/QR/FullPivHouseholderQR.h
@@ -4,28 +4,27 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_FULLPIVOTINGHOUSEHOLDERQR_H
 #define EIGEN_FULLPIVOTINGHOUSEHOLDERQR_H
 
+namespace Eigen { 
+
+namespace internal {
+
+template<typename MatrixType> struct FullPivHouseholderQRMatrixQReturnType;
+
+template<typename MatrixType>
+struct traits<FullPivHouseholderQRMatrixQReturnType<MatrixType> >
+{
+  typedef typename MatrixType::PlainObject ReturnType;
+};
+
+}
+
 /** \ingroup QR_Module
   *
   * \class FullPivHouseholderQR
@@ -62,7 +61,7 @@ template<typename _MatrixType> class FullPivHouseholderQR
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::RealScalar RealScalar;
     typedef typename MatrixType::Index Index;
-    typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, Options, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixQType;
+    typedef internal::FullPivHouseholderQRMatrixQReturnType<MatrixType> MatrixQReturnType;
     typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
     typedef Matrix<Index, 1, ColsAtCompileTime, RowMajor, 1, MaxColsAtCompileTime> IntRowVectorType;
     typedef PermutationMatrix<ColsAtCompileTime, MaxColsAtCompileTime> PermutationType;
@@ -139,7 +138,9 @@ template<typename _MatrixType> class FullPivHouseholderQR
       return internal::solve_retval<FullPivHouseholderQR, Rhs>(*this, b.derived());
     }
 
-    MatrixQType matrixQ(void) const;
+    /** \returns Expression object representing the matrix Q
+      */
+    MatrixQReturnType matrixQ(void) const;
 
     /** \returns a reference to the matrix where the Householder QR decomposition is stored
       */
@@ -508,28 +509,73 @@ struct solve_retval<FullPivHouseholderQR<_MatrixType>, Rhs>
   }
 };
 
+/** \ingroup QR_Module
+  *
+  * \brief Expression type for return value of FullPivHouseholderQR::matrixQ()
+  *
+  * \tparam MatrixType type of underlying dense matrix
+  */
+template<typename MatrixType> struct FullPivHouseholderQRMatrixQReturnType
+  : public ReturnByValue<FullPivHouseholderQRMatrixQReturnType<MatrixType> >
+{
+public:
+  typedef typename MatrixType::Index Index;
+  typedef typename internal::plain_col_type<MatrixType, Index>::type IntColVectorType;
+  typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
+  typedef Matrix<typename MatrixType::Scalar, 1, MatrixType::RowsAtCompileTime, RowMajor, 1,
+                 MatrixType::MaxRowsAtCompileTime> WorkVectorType;
+
+  FullPivHouseholderQRMatrixQReturnType(const MatrixType&       qr,
+                                        const HCoeffsType&      hCoeffs,
+                                        const IntColVectorType& rowsTranspositions)
+    : m_qr(qr),
+      m_hCoeffs(hCoeffs),
+      m_rowsTranspositions(rowsTranspositions)
+      {}
+
+  template <typename ResultType>
+  void evalTo(ResultType& result) const
+  {
+    const Index rows = m_qr.rows();
+    WorkVectorType workspace(rows);
+    evalTo(result, workspace);
+  }
+
+  template <typename ResultType>
+  void evalTo(ResultType& result, WorkVectorType& workspace) const
+  {
+    // compute the product H'_0 H'_1 ... H'_n-1,
+    // where H_k is the k-th Householder transformation I - h_k v_k v_k'
+    // and v_k is the k-th Householder vector [1,m_qr(k+1,k), m_qr(k+2,k), ...]
+    const Index rows = m_qr.rows();
+    const Index cols = m_qr.cols();
+    const Index size = (std::min)(rows, cols);
+    workspace.resize(rows);
+    result.setIdentity(rows, rows);
+    for (Index k = size-1; k >= 0; k--)
+    {
+      result.block(k, k, rows-k, rows-k)
+            .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), internal::conj(m_hCoeffs.coeff(k)), &workspace.coeffRef(k));
+      result.row(k).swap(result.row(m_rowsTranspositions.coeff(k)));
+    }
+  }
+
+    Index rows() const { return m_qr.rows(); }
+    Index cols() const { return m_qr.rows(); }
+
+protected:
+  typename MatrixType::Nested m_qr;
+  typename HCoeffsType::Nested m_hCoeffs;
+  typename IntColVectorType::Nested m_rowsTranspositions;
+};
+
 } // end namespace internal
 
-/** \returns the matrix Q */
 template<typename MatrixType>
-typename FullPivHouseholderQR<MatrixType>::MatrixQType FullPivHouseholderQR<MatrixType>::matrixQ() const
+inline typename FullPivHouseholderQR<MatrixType>::MatrixQReturnType FullPivHouseholderQR<MatrixType>::matrixQ() const
 {
   eigen_assert(m_isInitialized && "FullPivHouseholderQR is not initialized.");
-  // compute the product H'_0 H'_1 ... H'_n-1,
-  // where H_k is the k-th Householder transformation I - h_k v_k v_k'
-  // and v_k is the k-th Householder vector [1,m_qr(k+1,k), m_qr(k+2,k), ...]
-  Index rows = m_qr.rows();
-  Index cols = m_qr.cols();
-  Index size = (std::min)(rows,cols);
-  MatrixQType res = MatrixQType::Identity(rows, rows);
-  Matrix<Scalar,1,MatrixType::RowsAtCompileTime> temp(rows);
-  for (Index k = size-1; k >= 0; k--)
-  {
-    res.block(k, k, rows-k, rows-k)
-       .applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), internal::conj(m_hCoeffs.coeff(k)), &temp.coeffRef(k));
-    res.row(k).swap(res.row(m_rows_transpositions.coeff(k)));
-  }
-  return res;
+  return MatrixQReturnType(m_qr, m_hCoeffs, m_rows_transpositions);
 }
 
 /** \return the full-pivoting Householder QR decomposition of \c *this.
@@ -543,4 +589,6 @@ MatrixBase<Derived>::fullPivHouseholderQr() const
   return FullPivHouseholderQR<PlainObject>(eval());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_FULLPIVOTINGHOUSEHOLDERQR_H
diff --git a/extern/Eigen3/Eigen/src/QR/HouseholderQR.h b/extern/Eigen3/Eigen/src/QR/HouseholderQR.h
index 9ee96de2680..5bcb32c1e18 100644
--- a/extern/Eigen3/Eigen/src/QR/HouseholderQR.h
+++ b/extern/Eigen3/Eigen/src/QR/HouseholderQR.h
@@ -5,28 +5,15 @@
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 // Copyright (C) 2010 Vincent Lejeune
 //
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_QR_H
 #define EIGEN_QR_H
 
+namespace Eigen { 
+
 /** \ingroup QR_Module
   *
   *
@@ -351,5 +338,6 @@ MatrixBase<Derived>::householderQr() const
   return HouseholderQR<PlainObject>(eval());
 }
 
+} // end namespace Eigen
 
 #endif // EIGEN_QR_H
diff --git a/extern/Eigen3/Eigen/src/QR/HouseholderQR_MKL.h b/extern/Eigen3/Eigen/src/QR/HouseholderQR_MKL.h
new file mode 100644
index 00000000000..5313de604d2
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/QR/HouseholderQR_MKL.h
@@ -0,0 +1,69 @@
+/*
+ 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
+ *    Householder QR decomposition of a matrix w/o pivoting based on
+ *    LAPACKE_?geqrf function.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_QR_MKL_H
+#define EIGEN_QR_MKL_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal Specialization for the data types supported by MKL */
+
+#define EIGEN_MKL_QR_NOPIV(EIGTYPE, MKLTYPE, MKLPREFIX) \
+template<typename MatrixQR, typename HCoeffs> \
+void householder_qr_inplace_blocked(MatrixQR& mat, HCoeffs& hCoeffs, \
+                                       typename MatrixQR::Index maxBlockSize=32, \
+                                       EIGTYPE* tempData = 0) \
+{ \
+  lapack_int m = mat.rows(); \
+  lapack_int n = mat.cols(); \
+  lapack_int lda = mat.outerStride(); \
+  lapack_int matrix_order = (MatrixQR::IsRowMajor) ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \
+  LAPACKE_##MKLPREFIX##geqrf( matrix_order, m, n, (MKLTYPE*)mat.data(), lda, (MKLTYPE*)hCoeffs.data()); \
+  hCoeffs.adjointInPlace(); \
+\
+}
+
+EIGEN_MKL_QR_NOPIV(double, double, d)
+EIGEN_MKL_QR_NOPIV(float, float, s)
+EIGEN_MKL_QR_NOPIV(dcomplex, MKL_Complex16, z)
+EIGEN_MKL_QR_NOPIV(scomplex, MKL_Complex8, c)
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_QR_MKL_H
diff --git a/extern/Eigen3/Eigen/src/SVD/JacobiSVD.h b/extern/Eigen3/Eigen/src/SVD/JacobiSVD.h
index 3c423095c31..a7dbf073766 100644
--- a/extern/Eigen3/Eigen/src/SVD/JacobiSVD.h
+++ b/extern/Eigen3/Eigen/src/SVD/JacobiSVD.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_JACOBISVD_H
 #define EIGEN_JACOBISVD_H
 
+namespace Eigen { 
+
 namespace internal {
 // forward declaration (needed by ICC)
 // the empty body is required by MSVC
@@ -61,9 +48,12 @@ template<typename MatrixType, int QRPreconditioner, int Case,
 > struct qr_preconditioner_impl {};
 
 template<typename MatrixType, int QRPreconditioner, int Case>
-struct qr_preconditioner_impl<MatrixType, QRPreconditioner, Case, false>
+class qr_preconditioner_impl<MatrixType, QRPreconditioner, Case, false>
 {
-  static bool run(JacobiSVD<MatrixType, QRPreconditioner>&, const MatrixType&)
+public:
+  typedef typename MatrixType::Index Index;
+  void allocate(const JacobiSVD<MatrixType, QRPreconditioner>&) {}
+  bool run(JacobiSVD<MatrixType, QRPreconditioner>&, const MatrixType&)
   {
     return false;
   }
@@ -72,134 +62,279 @@ struct qr_preconditioner_impl<MatrixType, QRPreconditioner, Case, false>
 /*** preconditioner using FullPivHouseholderQR ***/
 
 template<typename MatrixType>
-struct qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
+class qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
 {
-  static bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
+public:
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::Scalar Scalar;
+  enum
+  {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime
+  };
+  typedef Matrix<Scalar, 1, RowsAtCompileTime, RowMajor, 1, MaxRowsAtCompileTime> WorkspaceType;
+
+  void allocate(const JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd)
+  {
+    if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
+    {
+      m_qr = FullPivHouseholderQR<MatrixType>(svd.rows(), svd.cols());
+    }
+    if (svd.m_computeFullU) m_workspace.resize(svd.rows());
+  }
+
+  bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
   {
     if(matrix.rows() > matrix.cols())
     {
-      FullPivHouseholderQR<MatrixType> qr(matrix);
-      svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
-      if(svd.m_computeFullU) svd.m_matrixU = qr.matrixQ();
-      if(svd.computeV()) svd.m_matrixV = qr.colsPermutation();
+      m_qr.compute(matrix);
+      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
+      if(svd.m_computeFullU) m_qr.matrixQ().evalTo(svd.m_matrixU, m_workspace);
+      if(svd.computeV()) svd.m_matrixV = m_qr.colsPermutation();
       return true;
     }
     return false;
   }
+private:
+  FullPivHouseholderQR<MatrixType> m_qr;
+  WorkspaceType m_workspace;
 };
 
 template<typename MatrixType>
-struct qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
+class qr_preconditioner_impl<MatrixType, FullPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
 {
-  static bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
+public:
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::Scalar Scalar;
+  enum
+  {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
+    Options = MatrixType::Options
+  };
+  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
+          TransposeTypeWithSameStorageOrder;
+
+  void allocate(const JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd)
+  {
+    if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
+    {
+      m_qr = FullPivHouseholderQR<TransposeTypeWithSameStorageOrder>(svd.cols(), svd.rows());
+    }
+    m_adjoint.resize(svd.cols(), svd.rows());
+    if (svd.m_computeFullV) m_workspace.resize(svd.cols());
+  }
+
+  bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
   {
     if(matrix.cols() > matrix.rows())
     {
-      typedef Matrix<typename MatrixType::Scalar, MatrixType::ColsAtCompileTime, MatrixType::RowsAtCompileTime,
-                     MatrixType::Options, MatrixType::MaxColsAtCompileTime, MatrixType::MaxRowsAtCompileTime>
-              TransposeTypeWithSameStorageOrder;
-      FullPivHouseholderQR<TransposeTypeWithSameStorageOrder> qr(matrix.adjoint());
-      svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
-      if(svd.m_computeFullV) svd.m_matrixV = qr.matrixQ();
-      if(svd.computeU()) svd.m_matrixU = qr.colsPermutation();
+      m_adjoint = matrix.adjoint();
+      m_qr.compute(m_adjoint);
+      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
+      if(svd.m_computeFullV) m_qr.matrixQ().evalTo(svd.m_matrixV, m_workspace);
+      if(svd.computeU()) svd.m_matrixU = m_qr.colsPermutation();
       return true;
     }
     else return false;
   }
+private:
+  FullPivHouseholderQR<TransposeTypeWithSameStorageOrder> m_qr;
+  TransposeTypeWithSameStorageOrder m_adjoint;
+  typename internal::plain_row_type<MatrixType>::type m_workspace;
 };
 
 /*** preconditioner using ColPivHouseholderQR ***/
 
 template<typename MatrixType>
-struct qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
+class qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
 {
-  static bool run(JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
+public:
+  typedef typename MatrixType::Index Index;
+
+  void allocate(const JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd)
+  {
+    if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
+    {
+      m_qr = ColPivHouseholderQR<MatrixType>(svd.rows(), svd.cols());
+    }
+    if (svd.m_computeFullU) m_workspace.resize(svd.rows());
+    else if (svd.m_computeThinU) m_workspace.resize(svd.cols());
+  }
+
+  bool run(JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
   {
     if(matrix.rows() > matrix.cols())
     {
-      ColPivHouseholderQR<MatrixType> qr(matrix);
-      svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
-      if(svd.m_computeFullU) svd.m_matrixU = qr.householderQ();
-      else if(svd.m_computeThinU) {
+      m_qr.compute(matrix);
+      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
+      if(svd.m_computeFullU) m_qr.householderQ().evalTo(svd.m_matrixU, m_workspace);
+      else if(svd.m_computeThinU)
+      {
         svd.m_matrixU.setIdentity(matrix.rows(), matrix.cols());
-        qr.householderQ().applyThisOnTheLeft(svd.m_matrixU);
+        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixU, m_workspace);
       }
-      if(svd.computeV()) svd.m_matrixV = qr.colsPermutation();
+      if(svd.computeV()) svd.m_matrixV = m_qr.colsPermutation();
       return true;
     }
     return false;
   }
+
+private:
+  ColPivHouseholderQR<MatrixType> m_qr;
+  typename internal::plain_col_type<MatrixType>::type m_workspace;
 };
 
 template<typename MatrixType>
-struct qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
+class qr_preconditioner_impl<MatrixType, ColPivHouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
 {
-  static bool run(JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
+public:
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::Scalar Scalar;
+  enum
+  {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
+    Options = MatrixType::Options
+  };
+
+  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
+          TransposeTypeWithSameStorageOrder;
+
+  void allocate(const JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd)
+  {
+    if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
+    {
+      m_qr = ColPivHouseholderQR<TransposeTypeWithSameStorageOrder>(svd.cols(), svd.rows());
+    }
+    if (svd.m_computeFullV) m_workspace.resize(svd.cols());
+    else if (svd.m_computeThinV) m_workspace.resize(svd.rows());
+    m_adjoint.resize(svd.cols(), svd.rows());
+  }
+
+  bool run(JacobiSVD<MatrixType, ColPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix)
   {
     if(matrix.cols() > matrix.rows())
     {
-      typedef Matrix<typename MatrixType::Scalar, MatrixType::ColsAtCompileTime, MatrixType::RowsAtCompileTime,
-                     MatrixType::Options, MatrixType::MaxColsAtCompileTime, MatrixType::MaxRowsAtCompileTime>
-              TransposeTypeWithSameStorageOrder;
-      ColPivHouseholderQR<TransposeTypeWithSameStorageOrder> qr(matrix.adjoint());
-      svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
-      if(svd.m_computeFullV) svd.m_matrixV = qr.householderQ();
-      else if(svd.m_computeThinV) {
+      m_adjoint = matrix.adjoint();
+      m_qr.compute(m_adjoint);
+
+      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
+      if(svd.m_computeFullV) m_qr.householderQ().evalTo(svd.m_matrixV, m_workspace);
+      else if(svd.m_computeThinV)
+      {
         svd.m_matrixV.setIdentity(matrix.cols(), matrix.rows());
-        qr.householderQ().applyThisOnTheLeft(svd.m_matrixV);
+        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixV, m_workspace);
       }
-      if(svd.computeU()) svd.m_matrixU = qr.colsPermutation();
+      if(svd.computeU()) svd.m_matrixU = m_qr.colsPermutation();
       return true;
     }
     else return false;
   }
+
+private:
+  ColPivHouseholderQR<TransposeTypeWithSameStorageOrder> m_qr;
+  TransposeTypeWithSameStorageOrder m_adjoint;
+  typename internal::plain_row_type<MatrixType>::type m_workspace;
 };
 
 /*** preconditioner using HouseholderQR ***/
 
 template<typename MatrixType>
-struct qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
+class qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreRowsThanCols, true>
 {
-  static bool run(JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd, const MatrixType& matrix)
+public:
+  typedef typename MatrixType::Index Index;
+
+  void allocate(const JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd)
+  {
+    if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols())
+    {
+      m_qr = HouseholderQR<MatrixType>(svd.rows(), svd.cols());
+    }
+    if (svd.m_computeFullU) m_workspace.resize(svd.rows());
+    else if (svd.m_computeThinU) m_workspace.resize(svd.cols());
+  }
+
+  bool run(JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd, const MatrixType& matrix)
   {
     if(matrix.rows() > matrix.cols())
     {
-      HouseholderQR<MatrixType> qr(matrix);
-      svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
-      if(svd.m_computeFullU) svd.m_matrixU = qr.householderQ();
-      else if(svd.m_computeThinU) {
+      m_qr.compute(matrix);
+      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<Upper>();
+      if(svd.m_computeFullU) m_qr.householderQ().evalTo(svd.m_matrixU, m_workspace);
+      else if(svd.m_computeThinU)
+      {
         svd.m_matrixU.setIdentity(matrix.rows(), matrix.cols());
-        qr.householderQ().applyThisOnTheLeft(svd.m_matrixU);
+        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixU, m_workspace);
       }
       if(svd.computeV()) svd.m_matrixV.setIdentity(matrix.cols(), matrix.cols());
       return true;
     }
     return false;
   }
+private:
+  HouseholderQR<MatrixType> m_qr;
+  typename internal::plain_col_type<MatrixType>::type m_workspace;
 };
 
 template<typename MatrixType>
-struct qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
+class qr_preconditioner_impl<MatrixType, HouseholderQRPreconditioner, PreconditionIfMoreColsThanRows, true>
 {
-  static bool run(JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd, const MatrixType& matrix)
+public:
+  typedef typename MatrixType::Index Index;
+  typedef typename MatrixType::Scalar Scalar;
+  enum
+  {
+    RowsAtCompileTime = MatrixType::RowsAtCompileTime,
+    ColsAtCompileTime = MatrixType::ColsAtCompileTime,
+    MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
+    MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime,
+    Options = MatrixType::Options
+  };
+
+  typedef Matrix<Scalar, ColsAtCompileTime, RowsAtCompileTime, Options, MaxColsAtCompileTime, MaxRowsAtCompileTime>
+          TransposeTypeWithSameStorageOrder;
+
+  void allocate(const JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd)
+  {
+    if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols())
+    {
+      m_qr = HouseholderQR<TransposeTypeWithSameStorageOrder>(svd.cols(), svd.rows());
+    }
+    if (svd.m_computeFullV) m_workspace.resize(svd.cols());
+    else if (svd.m_computeThinV) m_workspace.resize(svd.rows());
+    m_adjoint.resize(svd.cols(), svd.rows());
+  }
+
+  bool run(JacobiSVD<MatrixType, HouseholderQRPreconditioner>& svd, const MatrixType& matrix)
   {
     if(matrix.cols() > matrix.rows())
     {
-      typedef Matrix<typename MatrixType::Scalar, MatrixType::ColsAtCompileTime, MatrixType::RowsAtCompileTime,
-                     MatrixType::Options, MatrixType::MaxColsAtCompileTime, MatrixType::MaxRowsAtCompileTime>
-              TransposeTypeWithSameStorageOrder;
-      HouseholderQR<TransposeTypeWithSameStorageOrder> qr(matrix.adjoint());
-      svd.m_workMatrix = qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
-      if(svd.m_computeFullV) svd.m_matrixV = qr.householderQ();
-      else if(svd.m_computeThinV) {
+      m_adjoint = matrix.adjoint();
+      m_qr.compute(m_adjoint);
+
+      svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.rows(),matrix.rows()).template triangularView<Upper>().adjoint();
+      if(svd.m_computeFullV) m_qr.householderQ().evalTo(svd.m_matrixV, m_workspace);
+      else if(svd.m_computeThinV)
+      {
         svd.m_matrixV.setIdentity(matrix.cols(), matrix.rows());
-        qr.householderQ().applyThisOnTheLeft(svd.m_matrixV);
+        m_qr.householderQ().applyThisOnTheLeft(svd.m_matrixV, m_workspace);
       }
       if(svd.computeU()) svd.m_matrixU.setIdentity(matrix.rows(), matrix.rows());
       return true;
     }
     else return false;
   }
+
+private:
+  HouseholderQR<TransposeTypeWithSameStorageOrder> m_qr;
+  TransposeTypeWithSameStorageOrder m_adjoint;
+  typename internal::plain_row_type<MatrixType>::type m_workspace;
 };
 
 /*** 2x2 SVD implementation
@@ -316,7 +451,7 @@ void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q,
   * Here's an example demonstrating basic usage:
   * \include JacobiSVD_basic.cpp
   * Output: \verbinclude JacobiSVD_basic.out
-  * 
+  *
   * This JacobiSVD class is a two-sided Jacobi R-SVD decomposition, ensuring optimal reliability and accuracy. The downside is that it's slower than
   * bidiagonalizing SVD algorithms for large square matrices; however its complexity is still \f$ O(n^2p) \f$ where \a n is the smaller dimension and
   * \a p is the greater dimension, meaning that it is still of the same order of complexity as the faster bidiagonalizing R-SVD algorithms.
@@ -324,7 +459,7 @@ void real_2x2_jacobi_svd(const MatrixType& matrix, Index p, Index q,
   *
   * If the input matrix has inf or nan coefficients, the result of the computation is undefined, but the computation is guaranteed to
   * terminate in finite (and reasonable) time.
-  * 
+  *
   * The possible values for QRPreconditioner are:
   * \li ColPivHouseholderQRPreconditioner is the default. In practice it's very safe. It uses column-pivoting QR.
   * \li FullPivHouseholderQRPreconditioner, is the safest and slowest. It uses full-pivoting QR.
@@ -494,7 +629,7 @@ template<typename _MatrixType, int QRPreconditioner> class JacobiSVD
       * \param b the right-hand-side of the equation to solve.
       *
       * \note Solving requires both U and V to be computed. Thin U and V are enough, there is no need for full U or V.
-      * 
+      *
       * \note SVD solving is implicitly least-squares. Thus, this method serves both purposes of exact solving and least-squares solving.
       * In other words, the returned solution is guaranteed to minimize the Euclidean norm \f$ \Vert A x - b \Vert \f$.
       */
@@ -535,6 +670,9 @@ template<typename _MatrixType, int QRPreconditioner> class JacobiSVD
     friend struct internal::svd_precondition_2x2_block_to_be_real;
     template<typename __MatrixType, int _QRPreconditioner, int _Case, bool _DoAnything>
     friend struct internal::qr_preconditioner_impl;
+
+    internal::qr_preconditioner_impl<MatrixType, QRPreconditioner, internal::PreconditionIfMoreColsThanRows> m_qr_precond_morecols;
+    internal::qr_preconditioner_impl<MatrixType, QRPreconditioner, internal::PreconditionIfMoreRowsThanCols> m_qr_precond_morerows;
 };
 
 template<typename MatrixType, int QRPreconditioner>
@@ -578,6 +716,9 @@ void JacobiSVD<MatrixType, QRPreconditioner>::allocate(Index rows, Index cols, u
                           : m_computeThinV ? m_diagSize
                           : 0);
   m_workMatrix.resize(m_diagSize, m_diagSize);
+  
+  if(m_cols>m_rows) m_qr_precond_morecols.allocate(*this);
+  if(m_rows>m_cols) m_qr_precond_morerows.allocate(*this);
 }
 
 template<typename MatrixType, int QRPreconditioner>
@@ -595,8 +736,7 @@ JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsig
 
   /*** step 1. The R-SVD step: we use a QR decomposition to reduce to the case of a square matrix */
 
-  if(!internal::qr_preconditioner_impl<MatrixType, QRPreconditioner, internal::PreconditionIfMoreColsThanRows>::run(*this, matrix)
-  && !internal::qr_preconditioner_impl<MatrixType, QRPreconditioner, internal::PreconditionIfMoreRowsThanCols>::run(*this, matrix))
+  if(!m_qr_precond_morecols.run(*this, matrix) && !m_qr_precond_morerows.run(*this, matrix))
   {
     m_workMatrix = matrix.block(0,0,m_diagSize,m_diagSize);
     if(m_computeFullU) m_matrixU.setIdentity(m_rows,m_rows);
@@ -722,6 +862,6 @@ MatrixBase<Derived>::jacobiSvd(unsigned int computationOptions) const
   return JacobiSVD<PlainObject>(*this, computationOptions);
 }
 
-
+} // end namespace Eigen
 
 #endif // EIGEN_JACOBISVD_H
diff --git a/extern/Eigen3/Eigen/src/SVD/JacobiSVD_MKL.h b/extern/Eigen3/Eigen/src/SVD/JacobiSVD_MKL.h
new file mode 100644
index 00000000000..4d479f6b26e
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SVD/JacobiSVD_MKL.h
@@ -0,0 +1,92 @@
+/*
+ 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
+ *    Singular Value Decomposition - SVD.
+ ********************************************************************************
+*/
+
+#ifndef EIGEN_JACOBISVD_MKL_H
+#define EIGEN_JACOBISVD_MKL_H
+
+#include "Eigen/src/Core/util/MKL_support.h"
+
+namespace Eigen { 
+
+/** \internal Specialization for the data types supported by MKL */
+
+#define EIGEN_MKL_SVD(EIGTYPE, MKLTYPE, MKLRTYPE, MKLPREFIX, EIGCOLROW, MKLCOLROW) \
+template<> inline\
+JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>& \
+JacobiSVD<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>, ColPivHouseholderQRPreconditioner>::compute(const Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic>& matrix, unsigned int computationOptions) \
+{ \
+  typedef Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW, Dynamic, Dynamic> MatrixType; \
+  typedef MatrixType::Scalar Scalar; \
+  typedef MatrixType::RealScalar RealScalar; \
+  allocate(matrix.rows(), matrix.cols(), computationOptions); \
+\
+  /*const RealScalar precision = RealScalar(2) * NumTraits<Scalar>::epsilon();*/ \
+  m_nonzeroSingularValues = m_diagSize; \
+\
+  lapack_int lda = matrix.outerStride(), ldu, ldvt; \
+  lapack_int matrix_order = MKLCOLROW; \
+  char jobu, jobvt; \
+  MKLTYPE *u, *vt, dummy; \
+  jobu  = (m_computeFullU) ? 'A' : (m_computeThinU) ? 'S' : 'N'; \
+  jobvt = (m_computeFullV) ? 'A' : (m_computeThinV) ? 'S' : 'N'; \
+  if (computeU()) { \
+    ldu  = m_matrixU.outerStride(); \
+    u    = (MKLTYPE*)m_matrixU.data(); \
+  } else { ldu=1; u=&dummy; }\
+  MatrixType localV; \
+  ldvt = (m_computeFullV) ? m_cols : (m_computeThinV) ? m_diagSize : 1; \
+  if (computeV()) { \
+    localV.resize(ldvt, m_cols); \
+    vt   = (MKLTYPE*)localV.data(); \
+  } else { ldvt=1; vt=&dummy; }\
+  Matrix<MKLRTYPE, Dynamic, Dynamic> superb; superb.resize(m_diagSize, 1); \
+  MatrixType m_temp; m_temp = matrix; \
+  LAPACKE_##MKLPREFIX##gesvd( matrix_order, jobu, jobvt, m_rows, m_cols, (MKLTYPE*)m_temp.data(), lda, (MKLRTYPE*)m_singularValues.data(), u, ldu, vt, ldvt, superb.data()); \
+  if (computeV()) m_matrixV = localV.adjoint(); \
+ /* for(int i=0;i<m_diagSize;i++) if (m_singularValues.coeffRef(i) < precision) { m_nonzeroSingularValues--; m_singularValues.coeffRef(i)=RealScalar(0);}*/ \
+  m_isInitialized = true; \
+  return *this; \
+}
+
+EIGEN_MKL_SVD(double,   double,        double, d, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_SVD(float,    float,         float , s, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_SVD(dcomplex, MKL_Complex16, double, z, ColMajor, LAPACK_COL_MAJOR)
+EIGEN_MKL_SVD(scomplex, MKL_Complex8,  float , c, ColMajor, LAPACK_COL_MAJOR)
+
+EIGEN_MKL_SVD(double,   double,        double, d, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_SVD(float,    float,         float , s, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_SVD(dcomplex, MKL_Complex16, double, z, RowMajor, LAPACK_ROW_MAJOR)
+EIGEN_MKL_SVD(scomplex, MKL_Complex8,  float , c, RowMajor, LAPACK_ROW_MAJOR)
+
+} // end namespace Eigen
+
+#endif // EIGEN_JACOBISVD_MKL_H
diff --git a/extern/Eigen3/Eigen/src/SVD/UpperBidiagonalization.h b/extern/Eigen3/Eigen/src/SVD/UpperBidiagonalization.h
index 2de197da953..213b3100df5 100644
--- a/extern/Eigen3/Eigen/src/SVD/UpperBidiagonalization.h
+++ b/extern/Eigen3/Eigen/src/SVD/UpperBidiagonalization.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BIDIAGONALIZATION_H
 #define EIGEN_BIDIAGONALIZATION_H
 
+namespace Eigen { 
+
 namespace internal {
 // UpperBidiagonalization will probably be replaced by a Bidiagonalization class, don't want to make it stable API.
 // At the same time, it's useful to keep for now as it's about the only thing that is testing the BandMatrix class.
@@ -156,4 +143,6 @@ MatrixBase<Derived>::bidiagonalization() const
 
 } // end namespace internal
 
+} // end namespace Eigen
+
 #endif // EIGEN_BIDIAGONALIZATION_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/DynamicSparseMatrix.h b/extern/Eigen3/Eigen/src/Sparse/DynamicSparseMatrix.h
deleted file mode 100644
index 93e75f4c601..00000000000
--- a/extern/Eigen3/Eigen/src/Sparse/DynamicSparseMatrix.h
+++ /dev/null
@@ -1,346 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2009 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_DYNAMIC_SPARSEMATRIX_H
-#define EIGEN_DYNAMIC_SPARSEMATRIX_H
-
-/** \class DynamicSparseMatrix
-  *
-  * \brief A sparse matrix class designed for matrix assembly purpose
-  *
-  * \param _Scalar the scalar type, i.e. the type of the coefficients
-  *
-  * Unlike SparseMatrix, this class provides a much higher degree of flexibility. In particular, it allows
-  * random read/write accesses in log(rho*outer_size) where \c rho is the probability that a coefficient is
-  * nonzero and outer_size is the number of columns if the matrix is column-major and the number of rows
-  * otherwise.
-  *
-  * Internally, the data are stored as a std::vector of compressed vector. The performances of random writes might
-  * decrease as the number of nonzeros per inner-vector increase. In practice, we observed very good performance
-  * till about 100 nonzeros/vector, and the performance remains relatively good till 500 nonzeros/vectors.
-  *
-  * \see SparseMatrix
-  */
-
-namespace internal {
-template<typename _Scalar, int _Options, typename _Index>
-struct traits<DynamicSparseMatrix<_Scalar, _Options, _Index> >
-{
-  typedef _Scalar Scalar;
-  typedef _Index Index;
-  typedef Sparse StorageKind;
-  typedef MatrixXpr XprKind;
-  enum {
-    RowsAtCompileTime = Dynamic,
-    ColsAtCompileTime = Dynamic,
-    MaxRowsAtCompileTime = Dynamic,
-    MaxColsAtCompileTime = Dynamic,
-    Flags = _Options | NestByRefBit | LvalueBit,
-    CoeffReadCost = NumTraits<Scalar>::ReadCost,
-    SupportedAccessPatterns = OuterRandomAccessPattern
-  };
-};
-}
-
-template<typename _Scalar, int _Options, typename _Index>
-class DynamicSparseMatrix
-  : public SparseMatrixBase<DynamicSparseMatrix<_Scalar, _Options, _Index> >
-{
-  public:
-    EIGEN_SPARSE_PUBLIC_INTERFACE(DynamicSparseMatrix)
-    // FIXME: why are these operator already alvailable ???
-    // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, +=)
-    // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, -=)
-    typedef MappedSparseMatrix<Scalar,Flags> Map;
-    using Base::IsRowMajor;
-    using Base::operator=;
-    enum {
-      Options = _Options
-    };
-
-  protected:
-
-    typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
-
-    Index m_innerSize;
-    std::vector<CompressedStorage<Scalar,Index> > m_data;
-
-  public:
-
-    inline Index rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
-    inline Index cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
-    inline Index innerSize() const { return m_innerSize; }
-    inline Index outerSize() const { return static_cast<Index>(m_data.size()); }
-    inline Index innerNonZeros(Index j) const { return m_data[j].size(); }
-
-    std::vector<CompressedStorage<Scalar,Index> >& _data() { return m_data; }
-    const std::vector<CompressedStorage<Scalar,Index> >& _data() const { return m_data; }
-
-    /** \returns the coefficient value at given position \a row, \a col
-      * This operation involes a log(rho*outer_size) binary search.
-      */
-    inline Scalar coeff(Index row, Index col) const
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-      return m_data[outer].at(inner);
-    }
-
-    /** \returns a reference to the coefficient value at given position \a row, \a col
-      * This operation involes a log(rho*outer_size) binary search. If the coefficient does not
-      * exist yet, then a sorted insertion into a sequential buffer is performed.
-      */
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-      return m_data[outer].atWithInsertion(inner);
-    }
-
-    class InnerIterator;
-
-    void setZero()
-    {
-      for (Index j=0; j<outerSize(); ++j)
-        m_data[j].clear();
-    }
-
-    /** \returns the number of non zero coefficients */
-    Index nonZeros() const
-    {
-      Index res = 0;
-      for (Index j=0; j<outerSize(); ++j)
-        res += static_cast<Index>(m_data[j].size());
-      return res;
-    }
-
-
-
-    void reserve(Index reserveSize = 1000)
-    {
-      if (outerSize()>0)
-      {
-        Index reserveSizePerVector = (std::max)(reserveSize/outerSize(),Index(4));
-        for (Index j=0; j<outerSize(); ++j)
-        {
-          m_data[j].reserve(reserveSizePerVector);
-        }
-      }
-    }
-
-    /** Does nothing: provided for compatibility with SparseMatrix */
-    inline void startVec(Index /*outer*/) {}
-
-    /** \returns a reference to the non zero coefficient at position \a row, \a col assuming that:
-      * - the nonzero does not already exist
-      * - the new coefficient is the last one of the given inner vector.
-      *
-      * \sa insert, insertBackByOuterInner */
-    inline Scalar& insertBack(Index row, Index col)
-    {
-      return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row);
-    }
-
-    /** \sa insertBack */
-    inline Scalar& insertBackByOuterInner(Index outer, Index inner)
-    {
-      eigen_assert(outer<Index(m_data.size()) && inner<m_innerSize && "out of range");
-      eigen_assert(((m_data[outer].size()==0) || (m_data[outer].index(m_data[outer].size()-1)<inner))
-                && "wrong sorted insertion");
-      m_data[outer].append(0, inner);
-      return m_data[outer].value(m_data[outer].size()-1);
-    }
-
-    inline Scalar& insert(Index row, Index col)
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-
-      Index startId = 0;
-      Index id = static_cast<Index>(m_data[outer].size()) - 1;
-      m_data[outer].resize(id+2,1);
-
-      while ( (id >= startId) && (m_data[outer].index(id) > inner) )
-      {
-        m_data[outer].index(id+1) = m_data[outer].index(id);
-        m_data[outer].value(id+1) = m_data[outer].value(id);
-        --id;
-      }
-      m_data[outer].index(id+1) = inner;
-      m_data[outer].value(id+1) = 0;
-      return m_data[outer].value(id+1);
-    }
-
-    /** Does nothing: provided for compatibility with SparseMatrix */
-    inline void finalize() {}
-
-    /** Suppress all nonzeros which are smaller than \a reference under the tolerence \a epsilon */
-    void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
-    {
-      for (Index j=0; j<outerSize(); ++j)
-        m_data[j].prune(reference,epsilon);
-    }
-
-    /** Resize the matrix without preserving the data (the matrix is set to zero)
-      */
-    void resize(Index rows, Index cols)
-    {
-      const Index outerSize = IsRowMajor ? rows : cols;
-      m_innerSize = IsRowMajor ? cols : rows;
-      setZero();
-      if (Index(m_data.size()) != outerSize)
-      {
-        m_data.resize(outerSize);
-      }
-    }
-
-    void resizeAndKeepData(Index rows, Index cols)
-    {
-      const Index outerSize = IsRowMajor ? rows : cols;
-      const Index innerSize = IsRowMajor ? cols : rows;
-      if (m_innerSize>innerSize)
-      {
-        // remove all coefficients with innerCoord>=innerSize
-        // TODO
-        //std::cerr << "not implemented yet\n";
-        exit(2);
-      }
-      if (m_data.size() != outerSize)
-      {
-        m_data.resize(outerSize);
-      }
-    }
-
-    inline DynamicSparseMatrix()
-      : m_innerSize(0), m_data(0)
-    {
-      eigen_assert(innerSize()==0 && outerSize()==0);
-    }
-
-    inline DynamicSparseMatrix(Index rows, Index cols)
-      : m_innerSize(0)
-    {
-      resize(rows, cols);
-    }
-
-    template<typename OtherDerived>
-    explicit inline DynamicSparseMatrix(const SparseMatrixBase<OtherDerived>& other)
-      : m_innerSize(0)
-    {
-    Base::operator=(other.derived());
-    }
-
-    inline DynamicSparseMatrix(const DynamicSparseMatrix& other)
-      : Base(), m_innerSize(0)
-    {
-      *this = other.derived();
-    }
-
-    inline void swap(DynamicSparseMatrix& other)
-    {
-      //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
-      std::swap(m_innerSize, other.m_innerSize);
-      //std::swap(m_outerSize, other.m_outerSize);
-      m_data.swap(other.m_data);
-    }
-
-    inline DynamicSparseMatrix& operator=(const DynamicSparseMatrix& other)
-    {
-      if (other.isRValue())
-      {
-        swap(other.const_cast_derived());
-      }
-      else
-      {
-        resize(other.rows(), other.cols());
-        m_data = other.m_data;
-      }
-      return *this;
-    }
-
-    /** Destructor */
-    inline ~DynamicSparseMatrix() {}
-
-  public:
-
-    /** \deprecated
-      * Set the matrix to zero and reserve the memory for \a reserveSize nonzero coefficients. */
-    EIGEN_DEPRECATED void startFill(Index reserveSize = 1000)
-    {
-      setZero();
-      reserve(reserveSize);
-    }
-
-    /** \deprecated use insert()
-      * inserts a nonzero coefficient at given coordinates \a row, \a col and returns its reference assuming that:
-      *  1 - the coefficient does not exist yet
-      *  2 - this the coefficient with greater inner coordinate for the given outer coordinate.
-      * In other words, assuming \c *this is column-major, then there must not exists any nonzero coefficient of coordinates
-      * \c i \c x \a col such that \c i >= \a row. Otherwise the matrix is invalid.
-      *
-      * \see fillrand(), coeffRef()
-      */
-    EIGEN_DEPRECATED Scalar& fill(Index row, Index col)
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-      return insertBack(outer,inner);
-    }
-
-    /** \deprecated use insert()
-      * Like fill() but with random inner coordinates.
-      * Compared to the generic coeffRef(), the unique limitation is that we assume
-      * the coefficient does not exist yet.
-      */
-    EIGEN_DEPRECATED Scalar& fillrand(Index row, Index col)
-    {
-      return insert(row,col);
-    }
-
-    /** \deprecated use finalize()
-      * Does nothing. Provided for compatibility with SparseMatrix. */
-    EIGEN_DEPRECATED void endFill() {}
-    
-#   ifdef EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
-#     include EIGEN_DYNAMICSPARSEMATRIX_PLUGIN
-#   endif
-};
-
-template<typename Scalar, int _Options, typename _Index>
-class DynamicSparseMatrix<Scalar,_Options,_Index>::InnerIterator : public SparseVector<Scalar,_Options>::InnerIterator
-{
-    typedef typename SparseVector<Scalar,_Options>::InnerIterator Base;
-  public:
-    InnerIterator(const DynamicSparseMatrix& mat, Index outer)
-      : Base(mat.m_data[outer]), m_outer(outer)
-    {}
-
-    inline Index row() const { return IsRowMajor ? m_outer : Base::index(); }
-    inline Index col() const { return IsRowMajor ? Base::index() : m_outer; }
-
-  protected:
-    const Index m_outer;
-};
-
-#endif // EIGEN_DYNAMIC_SPARSEMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseCwiseUnaryOp.h b/extern/Eigen3/Eigen/src/Sparse/SparseCwiseUnaryOp.h
deleted file mode 100644
index aa068835fbb..00000000000
--- a/extern/Eigen3/Eigen/src/Sparse/SparseCwiseUnaryOp.h
+++ /dev/null
@@ -1,146 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 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
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_SPARSE_CWISE_UNARY_OP_H
-#define EIGEN_SPARSE_CWISE_UNARY_OP_H
-
-// template<typename UnaryOp, typename MatrixType>
-// struct internal::traits<SparseCwiseUnaryOp<UnaryOp, MatrixType> > : internal::traits<MatrixType>
-// {
-//   typedef typename internal::result_of<
-//                      UnaryOp(typename MatrixType::Scalar)
-//                    >::type Scalar;
-//   typedef typename MatrixType::Nested MatrixTypeNested;
-//   typedef typename internal::remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
-//   enum {
-//     CoeffReadCost = _MatrixTypeNested::CoeffReadCost + internal::functor_traits<UnaryOp>::Cost
-//   };
-// };
-
-template<typename UnaryOp, typename MatrixType>
-class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>
-  : public SparseMatrixBase<CwiseUnaryOp<UnaryOp, MatrixType> >
-{
-  public:
-
-    class InnerIterator;
-//     typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
-
-    typedef CwiseUnaryOp<UnaryOp, MatrixType> Derived;
-    EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
-};
-
-template<typename UnaryOp, typename MatrixType>
-class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::InnerIterator
-{
-    typedef typename CwiseUnaryOpImpl::Scalar Scalar;
-    typedef typename internal::traits<Derived>::_XprTypeNested _MatrixTypeNested;
-    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
-    typedef typename MatrixType::Index Index;
-  public:
-
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, Index outer)
-      : m_iter(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
-    {}
-
-    EIGEN_STRONG_INLINE InnerIterator& operator++()
-    { ++m_iter; return *this; }
-
-    EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_iter.value()); }
-
-    EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
-    EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
-    EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
-
-    EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
-
-  protected:
-    MatrixTypeIterator m_iter;
-    const UnaryOp m_functor;
-};
-
-template<typename ViewOp, typename MatrixType>
-class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>
-  : public SparseMatrixBase<CwiseUnaryView<ViewOp, MatrixType> >
-{
-  public:
-
-    class InnerIterator;
-//     typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
-
-    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
-    EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
-};
-
-template<typename ViewOp, typename MatrixType>
-class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::InnerIterator
-{
-    typedef typename CwiseUnaryViewImpl::Scalar Scalar;
-    typedef typename internal::traits<Derived>::_MatrixTypeNested _MatrixTypeNested;
-    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
-    typedef typename MatrixType::Index Index;
-  public:
-
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryView, Index outer)
-      : m_iter(unaryView.derived().nestedExpression(),outer), m_functor(unaryView.derived().functor())
-    {}
-
-    EIGEN_STRONG_INLINE InnerIterator& operator++()
-    { ++m_iter; return *this; }
-
-    EIGEN_STRONG_INLINE Scalar value() const { return m_functor(m_iter.value()); }
-    EIGEN_STRONG_INLINE Scalar& valueRef() { return m_functor(m_iter.valueRef()); }
-
-    EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); }
-    EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); }
-    EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); }
-
-    EIGEN_STRONG_INLINE operator bool() const { return m_iter; }
-
-  protected:
-    MatrixTypeIterator m_iter;
-    const ViewOp m_functor;
-};
-
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-SparseMatrixBase<Derived>::operator*=(const Scalar& other)
-{
-  for (Index j=0; j<outerSize(); ++j)
-    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
-      i.valueRef() *= other;
-  return derived();
-}
-
-template<typename Derived>
-EIGEN_STRONG_INLINE Derived&
-SparseMatrixBase<Derived>::operator/=(const Scalar& other)
-{
-  for (Index j=0; j<outerSize(); ++j)
-    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
-      i.valueRef() /= other;
-  return derived();
-}
-
-#endif // EIGEN_SPARSE_CWISE_UNARY_OP_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseFuzzy.h b/extern/Eigen3/Eigen/src/Sparse/SparseFuzzy.h
deleted file mode 100644
index f00b3d6469b..00000000000
--- a/extern/Eigen3/Eigen/src/Sparse/SparseFuzzy.h
+++ /dev/null
@@ -1,41 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// 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
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
-
-#ifndef EIGEN_SPARSE_FUZZY_H
-#define EIGEN_SPARSE_FUZZY_H
-
-// template<typename Derived>
-// template<typename OtherDerived>
-// bool SparseMatrixBase<Derived>::isApprox(
-//   const OtherDerived& other,
-//   typename NumTraits<Scalar>::Real prec
-// ) const
-// {
-//   const typename internal::nested<Derived,2>::type nested(derived());
-//   const typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
-//   return    (nested - otherNested).cwise().abs2().sum()
-//          <= prec * prec * (std::min)(nested.cwise().abs2().sum(), otherNested.cwise().abs2().sum());
-// }
-
-#endif // EIGEN_SPARSE_FUZZY_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseMatrix.h b/extern/Eigen3/Eigen/src/Sparse/SparseMatrix.h
deleted file mode 100644
index 0e175ec6e71..00000000000
--- a/extern/Eigen3/Eigen/src/Sparse/SparseMatrix.h
+++ /dev/null
@@ -1,651 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 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
-// 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_SPARSEMATRIX_H
-#define EIGEN_SPARSEMATRIX_H
-
-/** \ingroup Sparse_Module
-  *
-  * \class SparseMatrix
-  *
-  * \brief The main sparse matrix class
-  *
-  * This class implements a sparse matrix using the very common compressed row/column storage
-  * scheme.
-  *
-  * \tparam _Scalar the scalar type, i.e. the type of the coefficients
-  * \tparam _Options Union of bit flags controlling the storage scheme. Currently the only possibility
-  *                 is RowMajor. The default is 0 which means column-major.
-  * \tparam _Index the type of the indices. Default is \c int.
-  *
-  * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
-  *
-  * This class can be extended with the help of the plugin mechanism described on the page
-  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIX_PLUGIN.
-  */
-
-namespace internal {
-template<typename _Scalar, int _Options, typename _Index>
-struct traits<SparseMatrix<_Scalar, _Options, _Index> >
-{
-  typedef _Scalar Scalar;
-  typedef _Index Index;
-  typedef Sparse StorageKind;
-  typedef MatrixXpr XprKind;
-  enum {
-    RowsAtCompileTime = Dynamic,
-    ColsAtCompileTime = Dynamic,
-    MaxRowsAtCompileTime = Dynamic,
-    MaxColsAtCompileTime = Dynamic,
-    Flags = _Options | NestByRefBit | LvalueBit,
-    CoeffReadCost = NumTraits<Scalar>::ReadCost,
-    SupportedAccessPatterns = InnerRandomAccessPattern
-  };
-};
-
-} // end namespace internal
-
-template<typename _Scalar, int _Options, typename _Index>
-class SparseMatrix
-  : public SparseMatrixBase<SparseMatrix<_Scalar, _Options, _Index> >
-{
-  public:
-    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix)
-//     using Base::operator=;
-    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=)
-    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=)
-    // FIXME: why are these operator already alvailable ???
-    // EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(SparseMatrix, *=)
-    // EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(SparseMatrix, /=)
-
-    typedef MappedSparseMatrix<Scalar,Flags> Map;
-    using Base::IsRowMajor;
-    typedef CompressedStorage<Scalar,Index> Storage;
-    enum {
-      Options = _Options
-    };
-
-  protected:
-
-    typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
-
-    Index m_outerSize;
-    Index m_innerSize;
-    Index* m_outerIndex;
-    CompressedStorage<Scalar,Index> m_data;
-
-  public:
-
-    inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
-    inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
-
-    inline Index innerSize() const { return m_innerSize; }
-    inline Index outerSize() const { return m_outerSize; }
-    inline Index innerNonZeros(Index j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
-
-    inline const Scalar* _valuePtr() const { return &m_data.value(0); }
-    inline Scalar* _valuePtr() { return &m_data.value(0); }
-
-    inline const Index* _innerIndexPtr() const { return &m_data.index(0); }
-    inline Index* _innerIndexPtr() { return &m_data.index(0); }
-
-    inline const Index* _outerIndexPtr() const { return m_outerIndex; }
-    inline Index* _outerIndexPtr() { return m_outerIndex; }
-
-    inline Storage& data() { return m_data; }
-    inline const Storage& data() const { return m_data; }
-
-    inline Scalar coeff(Index row, Index col) const
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-      return m_data.atInRange(m_outerIndex[outer], m_outerIndex[outer+1], inner);
-    }
-
-    inline Scalar& coeffRef(Index row, Index col)
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-
-      Index start = m_outerIndex[outer];
-      Index end = m_outerIndex[outer+1];
-      eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
-      eigen_assert(end>start && "coeffRef cannot be called on a zero coefficient");
-      const Index p = m_data.searchLowerIndex(start,end-1,inner);
-      eigen_assert((p<end) && (m_data.index(p)==inner) && "coeffRef cannot be called on a zero coefficient");
-      return m_data.value(p);
-    }
-
-  public:
-
-    class InnerIterator;
-
-    /** Removes all non zeros */
-    inline void setZero()
-    {
-      m_data.clear();
-      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
-    }
-
-    /** \returns the number of non zero coefficients */
-    inline Index nonZeros() const  { return static_cast<Index>(m_data.size()); }
-
-    /** Preallocates \a reserveSize non zeros */
-    inline void reserve(Index reserveSize)
-    {
-      m_data.reserve(reserveSize);
-    }
-
-    //--- low level purely coherent filling ---
-
-    /** \returns a reference to the non zero coefficient at position \a row, \a col assuming that:
-      * - the nonzero does not already exist
-      * - the new coefficient is the last one according to the storage order
-      *
-      * Before filling a given inner vector you must call the statVec(Index) function.
-      *
-      * After an insertion session, you should call the finalize() function.
-      *
-      * \sa insert, insertBackByOuterInner, startVec */
-    inline Scalar& insertBack(Index row, Index col)
-    {
-      return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row);
-    }
-
-    /** \sa insertBack, startVec */
-    inline Scalar& insertBackByOuterInner(Index outer, Index inner)
-    {
-      eigen_assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)");
-      eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)<inner) && "Invalid ordered insertion (invalid inner index)");
-      Index p = m_outerIndex[outer+1];
-      ++m_outerIndex[outer+1];
-      m_data.append(0, inner);
-      return m_data.value(p);
-    }
-
-    /** \warning use it only if you know what you are doing */
-    inline Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner)
-    {
-      Index p = m_outerIndex[outer+1];
-      ++m_outerIndex[outer+1];
-      m_data.append(0, inner);
-      return m_data.value(p);
-    }
-
-    /** \sa insertBack, insertBackByOuterInner */
-    inline void startVec(Index outer)
-    {
-      eigen_assert(m_outerIndex[outer]==int(m_data.size()) && "You must call startVec for each inner vector sequentially");
-      eigen_assert(m_outerIndex[outer+1]==0 && "You must call startVec for each inner vector sequentially");
-      m_outerIndex[outer+1] = m_outerIndex[outer];
-    }
-
-    //---
-
-    /** \returns a reference to a novel non zero coefficient with coordinates \a row x \a col.
-      * The non zero coefficient must \b not already exist.
-      *
-      * \warning This function can be extremely slow if the non zero coefficients
-      * are not inserted in a coherent order.
-      *
-      * After an insertion session, you should call the finalize() function.
-      */
-    EIGEN_DONT_INLINE Scalar& insert(Index row, Index col)
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-
-      Index previousOuter = outer;
-      if (m_outerIndex[outer+1]==0)
-      {
-        // we start a new inner vector
-        while (previousOuter>=0 && m_outerIndex[previousOuter]==0)
-        {
-          m_outerIndex[previousOuter] = static_cast<Index>(m_data.size());
-          --previousOuter;
-        }
-        m_outerIndex[outer+1] = m_outerIndex[outer];
-      }
-
-      // here we have to handle the tricky case where the outerIndex array
-      // starts with: [ 0 0 0 0 0 1 ...] and we are inserting in, e.g.,
-      // the 2nd inner vector...
-      bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0))
-                    && (size_t(m_outerIndex[outer+1]) == m_data.size());
-
-      size_t startId = m_outerIndex[outer];
-      // FIXME let's make sure sizeof(long int) == sizeof(size_t)
-      size_t p = m_outerIndex[outer+1];
-      ++m_outerIndex[outer+1];
-
-      float reallocRatio = 1;
-      if (m_data.allocatedSize()<=m_data.size())
-      {
-        // if there is no preallocated memory, let's reserve a minimum of 32 elements
-        if (m_data.size()==0)
-        {
-          m_data.reserve(32);
-        }
-        else
-        {
-          // we need to reallocate the data, to reduce multiple reallocations
-          // we use a smart resize algorithm based on the current filling ratio
-          // in addition, we use float to avoid integers overflows
-          float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1);
-          reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size());
-          // furthermore we bound the realloc ratio to:
-          //   1) reduce multiple minor realloc when the matrix is almost filled
-          //   2) avoid to allocate too much memory when the matrix is almost empty
-          reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f);
-        }
-      }
-      m_data.resize(m_data.size()+1,reallocRatio);
-
-      if (!isLastVec)
-      {
-        if (previousOuter==-1)
-        {
-          // oops wrong guess.
-          // let's correct the outer offsets
-          for (Index k=0; k<=(outer+1); ++k)
-            m_outerIndex[k] = 0;
-          Index k=outer+1;
-          while(m_outerIndex[k]==0)
-            m_outerIndex[k++] = 1;
-          while (k<=m_outerSize && m_outerIndex[k]!=0)
-            m_outerIndex[k++]++;
-          p = 0;
-          --k;
-          k = m_outerIndex[k]-1;
-          while (k>0)
-          {
-            m_data.index(k) = m_data.index(k-1);
-            m_data.value(k) = m_data.value(k-1);
-            k--;
-          }
-        }
-        else
-        {
-          // we are not inserting into the last inner vec
-          // update outer indices:
-          Index j = outer+2;
-          while (j<=m_outerSize && m_outerIndex[j]!=0)
-            m_outerIndex[j++]++;
-          --j;
-          // shift data of last vecs:
-          Index k = m_outerIndex[j]-1;
-          while (k>=Index(p))
-          {
-            m_data.index(k) = m_data.index(k-1);
-            m_data.value(k) = m_data.value(k-1);
-            k--;
-          }
-        }
-      }
-
-      while ( (p > startId) && (m_data.index(p-1) > inner) )
-      {
-        m_data.index(p) = m_data.index(p-1);
-        m_data.value(p) = m_data.value(p-1);
-        --p;
-      }
-
-      m_data.index(p) = inner;
-      return (m_data.value(p) = 0);
-    }
-
-
-
-
-    /** Must be called after inserting a set of non zero entries.
-      */
-    inline void finalize()
-    {
-      Index size = static_cast<Index>(m_data.size());
-      Index i = m_outerSize;
-      // find the last filled column
-      while (i>=0 && m_outerIndex[i]==0)
-        --i;
-      ++i;
-      while (i<=m_outerSize)
-      {
-        m_outerIndex[i] = size;
-        ++i;
-      }
-    }
-
-    /** Suppress all nonzeros which are smaller than \a reference under the tolerence \a epsilon */
-    void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
-    {
-      prune(default_prunning_func(reference,epsilon));
-    }
-    
-    /** Suppress all nonzeros which do not satisfy the predicate \a keep.
-      * The functor type \a KeepFunc must implement the following function:
-      * \code
-      * bool operator() (const Index& row, const Index& col, const Scalar& value) const;
-      * \endcode
-      * \sa prune(Scalar,RealScalar)
-      */
-    template<typename KeepFunc>
-    void prune(const KeepFunc& keep = KeepFunc())
-    {
-      Index k = 0;
-      for(Index j=0; j<m_outerSize; ++j)
-      {
-        Index previousStart = m_outerIndex[j];
-        m_outerIndex[j] = k;
-        Index end = m_outerIndex[j+1];
-        for(Index i=previousStart; i<end; ++i)
-        {
-          if(keep(IsRowMajor?j:m_data.index(i), IsRowMajor?m_data.index(i):j, m_data.value(i)))
-          {
-            m_data.value(k) = m_data.value(i);
-            m_data.index(k) = m_data.index(i);
-            ++k;
-          }
-        }
-      }
-      m_outerIndex[m_outerSize] = k;
-      m_data.resize(k,0);
-    }
-
-    /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero
-      * \sa resizeNonZeros(Index), reserve(), setZero()
-      */
-    void resize(Index rows, Index cols)
-    {
-      const Index outerSize = IsRowMajor ? rows : cols;
-      m_innerSize = IsRowMajor ? cols : rows;
-      m_data.clear();
-      if (m_outerSize != outerSize || m_outerSize==0)
-      {
-        delete[] m_outerIndex;
-        m_outerIndex = new Index [outerSize+1];
-        m_outerSize = outerSize;
-      }
-      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
-    }
-
-    /** Low level API
-      * Resize the nonzero vector to \a size */
-    void resizeNonZeros(Index size)
-    {
-      m_data.resize(size);
-    }
-
-    /** Default constructor yielding an empty \c 0 \c x \c 0 matrix */
-    inline SparseMatrix()
-      : m_outerSize(-1), m_innerSize(0), m_outerIndex(0)
-    {
-      resize(0, 0);
-    }
-
-    /** Constructs a \a rows \c x \a cols empty matrix */
-    inline SparseMatrix(Index rows, Index cols)
-      : m_outerSize(0), m_innerSize(0), m_outerIndex(0)
-    {
-      resize(rows, cols);
-    }
-
-    /** Constructs a sparse matrix from the sparse expression \a other */
-    template<typename OtherDerived>
-    inline SparseMatrix(const SparseMatrixBase<OtherDerived>& other)
-      : m_outerSize(0), m_innerSize(0), m_outerIndex(0)
-    {
-      *this = other.derived();
-    }
-
-    /** Copy constructor */
-    inline SparseMatrix(const SparseMatrix& other)
-      : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0)
-    {
-      *this = other.derived();
-    }
-
-    /** Swap the content of two sparse matrices of same type (optimization) */
-    inline void swap(SparseMatrix& other)
-    {
-      //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
-      std::swap(m_outerIndex, other.m_outerIndex);
-      std::swap(m_innerSize, other.m_innerSize);
-      std::swap(m_outerSize, other.m_outerSize);
-      m_data.swap(other.m_data);
-    }
-
-    inline SparseMatrix& operator=(const SparseMatrix& other)
-    {
-//       std::cout << "SparseMatrix& operator=(const SparseMatrix& other)\n";
-      if (other.isRValue())
-      {
-        swap(other.const_cast_derived());
-      }
-      else
-      {
-        resize(other.rows(), other.cols());
-        memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(Index));
-        m_data = other.m_data;
-      }
-      return *this;
-    }
-
-    #ifndef EIGEN_PARSED_BY_DOXYGEN
-    template<typename Lhs, typename Rhs>
-    inline SparseMatrix& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
-    { return Base::operator=(product); }
-    
-    template<typename OtherDerived>
-    inline SparseMatrix& operator=(const ReturnByValue<OtherDerived>& other)
-    { return Base::operator=(other); }
-    
-    template<typename OtherDerived>
-    inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other)
-    { return Base::operator=(other); }
-    #endif
-
-    template<typename OtherDerived>
-    EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other)
-    {
-      const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
-      if (needToTranspose)
-      {
-        // two passes algorithm:
-        //  1 - compute the number of coeffs per dest inner vector
-        //  2 - do the actual copy/eval
-        // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
-        typedef typename internal::nested<OtherDerived,2>::type OtherCopy;
-        typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
-        OtherCopy otherCopy(other.derived());
-
-        resize(other.rows(), other.cols());
-        Eigen::Map<Matrix<Index, Dynamic, 1> > (m_outerIndex,outerSize()).setZero();
-        // pass 1
-        // FIXME the above copy could be merged with that pass
-        for (Index j=0; j<otherCopy.outerSize(); ++j)
-          for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
-            ++m_outerIndex[it.index()];
-
-        // prefix sum
-        Index count = 0;
-        VectorXi positions(outerSize());
-        for (Index j=0; j<outerSize(); ++j)
-        {
-          Index tmp = m_outerIndex[j];
-          m_outerIndex[j] = count;
-          positions[j] = count;
-          count += tmp;
-        }
-        m_outerIndex[outerSize()] = count;
-        // alloc
-        m_data.resize(count);
-        // pass 2
-        for (Index j=0; j<otherCopy.outerSize(); ++j)
-        {
-          for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
-          {
-            Index pos = positions[it.index()]++;
-            m_data.index(pos) = j;
-            m_data.value(pos) = it.value();
-          }
-        }
-        return *this;
-      }
-      else
-      {
-        // there is no special optimization
-        return SparseMatrixBase<SparseMatrix>::operator=(other.derived());
-      }
-    }
-
-    friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m)
-    {
-      EIGEN_DBG_SPARSE(
-        s << "Nonzero entries:\n";
-        for (Index i=0; i<m.nonZeros(); ++i)
-        {
-          s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
-        }
-        s << std::endl;
-        s << std::endl;
-        s << "Column pointers:\n";
-        for (Index i=0; i<m.outerSize(); ++i)
-        {
-          s << m.m_outerIndex[i] << " ";
-        }
-        s << " $" << std::endl;
-        s << std::endl;
-      );
-      s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m);
-      return s;
-    }
-
-    /** Destructor */
-    inline ~SparseMatrix()
-    {
-      delete[] m_outerIndex;
-    }
-
-    /** Overloaded for performance */
-    Scalar sum() const;
-
-  public:
-
-    /** \deprecated use setZero() and reserve()
-      * Initializes the filling process of \c *this.
-      * \param reserveSize approximate number of nonzeros
-      * Note that the matrix \c *this is zero-ed.
-      */
-    EIGEN_DEPRECATED void startFill(Index reserveSize = 1000)
-    {
-      setZero();
-      m_data.reserve(reserveSize);
-    }
-
-    /** \deprecated use insert()
-      * Like fill() but with random inner coordinates.
-      */
-    EIGEN_DEPRECATED Scalar& fillrand(Index row, Index col)
-    {
-      return insert(row,col);
-    }
-
-    /** \deprecated use insert()
-      */
-    EIGEN_DEPRECATED Scalar& fill(Index row, Index col)
-    {
-      const Index outer = IsRowMajor ? row : col;
-      const Index inner = IsRowMajor ? col : row;
-
-      if (m_outerIndex[outer+1]==0)
-      {
-        // we start a new inner vector
-        Index i = outer;
-        while (i>=0 && m_outerIndex[i]==0)
-        {
-          m_outerIndex[i] = m_data.size();
-          --i;
-        }
-        m_outerIndex[outer+1] = m_outerIndex[outer];
-      }
-      else
-      {
-        eigen_assert(m_data.index(m_data.size()-1)<inner && "wrong sorted insertion");
-      }
-//       std::cerr << size_t(m_outerIndex[outer+1]) << " == " << m_data.size() << "\n";
-      assert(size_t(m_outerIndex[outer+1]) == m_data.size());
-      Index p = m_outerIndex[outer+1];
-      ++m_outerIndex[outer+1];
-
-      m_data.append(0, inner);
-      return m_data.value(p);
-    }
-
-    /** \deprecated use finalize */
-    EIGEN_DEPRECATED void endFill() { finalize(); }
-    
-#   ifdef EIGEN_SPARSEMATRIX_PLUGIN
-#     include EIGEN_SPARSEMATRIX_PLUGIN
-#   endif
-
-private:
-  struct default_prunning_func {
-    default_prunning_func(Scalar ref, RealScalar eps) : reference(ref), epsilon(eps) {}
-    inline bool operator() (const Index&, const Index&, const Scalar& value) const
-    {
-      return !internal::isMuchSmallerThan(value, reference, epsilon);
-    }
-    Scalar reference;
-    RealScalar epsilon;
-  };
-};
-
-template<typename Scalar, int _Options, typename _Index>
-class SparseMatrix<Scalar,_Options,_Index>::InnerIterator
-{
-  public:
-    InnerIterator(const SparseMatrix& mat, Index outer)
-      : m_values(mat._valuePtr()), m_indices(mat._innerIndexPtr()), m_outer(outer), m_id(mat.m_outerIndex[outer]), m_end(mat.m_outerIndex[outer+1])
-    {}
-
-    inline InnerIterator& operator++() { m_id++; return *this; }
-
-    inline const Scalar& value() const { return m_values[m_id]; }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id]); }
-
-    inline Index index() const { return m_indices[m_id]; }
-    inline Index outer() const { return m_outer; }
-    inline Index row() const { return IsRowMajor ? m_outer : index(); }
-    inline Index col() const { return IsRowMajor ? index() : m_outer; }
-
-    inline operator bool() const { return (m_id < m_end); }
-
-  protected:
-    const Scalar* m_values;
-    const Index* m_indices;
-    const Index m_outer;
-    Index m_id;
-    const Index m_end;
-};
-
-#endif // EIGEN_SPARSEMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseSparseProduct.h b/extern/Eigen3/Eigen/src/Sparse/SparseSparseProduct.h
deleted file mode 100644
index 19abcd1f8e4..00000000000
--- a/extern/Eigen3/Eigen/src/Sparse/SparseSparseProduct.h
+++ /dev/null
@@ -1,401 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2008-2010 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
-// 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_SPARSESPARSEPRODUCT_H
-#define EIGEN_SPARSESPARSEPRODUCT_H
-
-namespace internal {
-
-template<typename Lhs, typename Rhs, typename ResultType>
-static void sparse_product_impl2(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-{
-  typedef typename remove_all<Lhs>::type::Scalar Scalar;
-  typedef typename remove_all<Lhs>::type::Index Index;
-
-  // make sure to call innerSize/outerSize since we fake the storage order.
-  Index rows = lhs.innerSize();
-  Index cols = rhs.outerSize();
-  eigen_assert(lhs.outerSize() == rhs.innerSize());
-
-  std::vector<bool> mask(rows,false);
-  Matrix<Scalar,Dynamic,1> values(rows);
-  Matrix<Index,Dynamic,1>    indices(rows);
-
-  // estimate the number of non zero entries
-  float ratioLhs = float(lhs.nonZeros())/(float(lhs.rows())*float(lhs.cols()));
-  float avgNnzPerRhsColumn = float(rhs.nonZeros())/float(cols);
-  float ratioRes = (std::min)(ratioLhs * avgNnzPerRhsColumn, 1.f);
-
-//  int t200 = rows/(log2(200)*1.39);
-//  int t = (rows*100)/139;
-
-  res.resize(rows, cols);
-  res.reserve(Index(ratioRes*rows*cols));
-  // we compute each column of the result, one after the other
-  for (Index j=0; j<cols; ++j)
-  {
-
-    res.startVec(j);
-    Index nnz = 0;
-    for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
-    {
-      Scalar y = rhsIt.value();
-      Index k = rhsIt.index();
-      for (typename Lhs::InnerIterator lhsIt(lhs, k); lhsIt; ++lhsIt)
-      {
-        Index i = lhsIt.index();
-        Scalar x = lhsIt.value();
-        if(!mask[i])
-        {
-          mask[i] = true;
-//           values[i] = x * y;
-//           indices[nnz] = i;
-          ++nnz;
-        }
-        else
-          values[i] += x * y;
-      }
-    }
-    // FIXME reserve nnz non zeros
-    // FIXME implement fast sort algorithms for very small nnz
-    // if the result is sparse enough => use a quick sort
-    // otherwise => loop through the entire vector
-    // In order to avoid to perform an expensive log2 when the
-    // result is clearly very sparse we use a linear bound up to 200.
-//     if((nnz<200 && nnz<t200) || nnz * log2(nnz) < t)
-//     {
-//       if(nnz>1) std::sort(indices.data(),indices.data()+nnz);
-//       for(int k=0; k<nnz; ++k)
-//       {
-//         int i = indices[k];
-//         res.insertBackNoCheck(j,i) = values[i];
-//         mask[i] = false;
-//       }
-//     }
-//     else
-//     {
-//       // dense path
-//       for(int i=0; i<rows; ++i)
-//       {
-//         if(mask[i])
-//         {
-//           mask[i] = false;
-//           res.insertBackNoCheck(j,i) = values[i];
-//         }
-//       }
-//     }
-
-  }
-  res.finalize();
-}
-
-// perform a pseudo in-place sparse * sparse product assuming all matrices are col major
-template<typename Lhs, typename Rhs, typename ResultType>
-static void sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-{
-//   return sparse_product_impl2(lhs,rhs,res);
-
-  typedef typename remove_all<Lhs>::type::Scalar Scalar;
-  typedef typename remove_all<Lhs>::type::Index Index;
-
-  // make sure to call innerSize/outerSize since we fake the storage order.
-  Index rows = lhs.innerSize();
-  Index cols = rhs.outerSize();
-  //int size = lhs.outerSize();
-  eigen_assert(lhs.outerSize() == rhs.innerSize());
-
-  // allocate a temporary buffer
-  AmbiVector<Scalar,Index> tempVector(rows);
-
-  // estimate the number of non zero entries
-  float ratioLhs = float(lhs.nonZeros())/(float(lhs.rows())*float(lhs.cols()));
-  float avgNnzPerRhsColumn = float(rhs.nonZeros())/float(cols);
-  float ratioRes = (std::min)(ratioLhs * avgNnzPerRhsColumn, 1.f);
-
-  // mimics a resizeByInnerOuter:
-  if(ResultType::IsRowMajor)
-    res.resize(cols, rows);
-  else
-    res.resize(rows, cols);
-
-  res.reserve(Index(ratioRes*rows*cols));
-  for (Index j=0; j<cols; ++j)
-  {
-    // let's do a more accurate determination of the nnz ratio for the current column j of res
-    //float ratioColRes = (std::min)(ratioLhs * rhs.innerNonZeros(j), 1.f);
-    // FIXME find a nice way to get the number of nonzeros of a sub matrix (here an inner vector)
-    float ratioColRes = ratioRes;
-    tempVector.init(ratioColRes);
-    tempVector.setZero();
-    for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
-    {
-      // FIXME should be written like this: tmp += rhsIt.value() * lhs.col(rhsIt.index())
-      tempVector.restart();
-      Scalar x = rhsIt.value();
-      for (typename Lhs::InnerIterator lhsIt(lhs, rhsIt.index()); lhsIt; ++lhsIt)
-      {
-        tempVector.coeffRef(lhsIt.index()) += lhsIt.value() * x;
-      }
-    }
-    res.startVec(j);
-    for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector); it; ++it)
-      res.insertBackByOuterInner(j,it.index()) = it.value();
-  }
-  res.finalize();
-}
-
-template<typename Lhs, typename Rhs, typename ResultType,
-  int LhsStorageOrder = traits<Lhs>::Flags&RowMajorBit,
-  int RhsStorageOrder = traits<Rhs>::Flags&RowMajorBit,
-  int ResStorageOrder = traits<ResultType>::Flags&RowMajorBit>
-struct sparse_product_selector;
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,ColMajor>
-{
-  typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
-
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-//     std::cerr << __LINE__ << "\n";
-    typename remove_all<ResultType>::type _res(res.rows(), res.cols());
-    sparse_product_impl<Lhs,Rhs,ResultType>(lhs, rhs, _res);
-    res.swap(_res);
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,RowMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-//     std::cerr << __LINE__ << "\n";
-    // we need a col-major matrix to hold the result
-    typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType;
-    SparseTemporaryType _res(res.rows(), res.cols());
-    sparse_product_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, _res);
-    res = _res;
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-//     std::cerr << __LINE__ << "\n";
-    // let's transpose the product to get a column x column product
-    typename remove_all<ResultType>::type _res(res.rows(), res.cols());
-    sparse_product_impl<Rhs,Lhs,ResultType>(rhs, lhs, _res);
-    res.swap(_res);
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-//     std::cerr << "here...\n";
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
-    ColMajorMatrix colLhs(lhs);
-    ColMajorMatrix colRhs(rhs);
-//     std::cerr << "more...\n";
-    sparse_product_impl<ColMajorMatrix,ColMajorMatrix,ResultType>(colLhs, colRhs, res);
-//     std::cerr << "OK.\n";
-
-    // let's transpose the product to get a column x column product
-
-//     typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType;
-//     SparseTemporaryType _res(res.cols(), res.rows());
-//     sparse_product_impl<Rhs,Lhs,SparseTemporaryType>(rhs, lhs, _res);
-//     res = _res.transpose();
-  }
-};
-
-// NOTE the 2 others cases (col row *) must never occur since they are caught
-// by ProductReturnType which transforms it to (col col *) by evaluating rhs.
-
-} // end namespace internal
-
-// sparse = sparse * sparse
-template<typename Derived>
-template<typename Lhs, typename Rhs>
-inline Derived& SparseMatrixBase<Derived>::operator=(const SparseSparseProduct<Lhs,Rhs>& product)
-{
-//   std::cerr << "there..." << typeid(Lhs).name() << "  " << typeid(Lhs).name() << " " << (Derived::Flags&&RowMajorBit) << "\n";
-  internal::sparse_product_selector<
-    typename internal::remove_all<Lhs>::type,
-    typename internal::remove_all<Rhs>::type,
-    Derived>::run(product.lhs(),product.rhs(),derived());
-  return derived();
-}
-
-namespace internal {
-
-template<typename Lhs, typename Rhs, typename ResultType,
-  int LhsStorageOrder = traits<Lhs>::Flags&RowMajorBit,
-  int RhsStorageOrder = traits<Rhs>::Flags&RowMajorBit,
-  int ResStorageOrder = traits<ResultType>::Flags&RowMajorBit>
-struct sparse_product_selector2;
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,ColMajor,ColMajor,ColMajor>
-{
-  typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
-
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-    sparse_product_impl2<Lhs,Rhs,ResultType>(lhs, rhs, res);
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,RowMajor,ColMajor,ColMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-      // prevent warnings until the code is fixed
-      EIGEN_UNUSED_VARIABLE(lhs);
-      EIGEN_UNUSED_VARIABLE(rhs);
-      EIGEN_UNUSED_VARIABLE(res);
-
-//     typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
-//     RowMajorMatrix rhsRow = rhs;
-//     RowMajorMatrix resRow(res.rows(), res.cols());
-//     sparse_product_impl2<RowMajorMatrix,Lhs,RowMajorMatrix>(rhsRow, lhs, resRow);
-//     res = resRow;
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,ColMajor,RowMajor,ColMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-    typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
-    RowMajorMatrix lhsRow = lhs;
-    RowMajorMatrix resRow(res.rows(), res.cols());
-    sparse_product_impl2<Rhs,RowMajorMatrix,RowMajorMatrix>(rhs, lhsRow, resRow);
-    res = resRow;
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-    typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
-    RowMajorMatrix resRow(res.rows(), res.cols());
-    sparse_product_impl2<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow);
-    res = resRow;
-  }
-};
-
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,ColMajor,ColMajor,RowMajor>
-{
-  typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
-
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
-    ColMajorMatrix resCol(res.rows(), res.cols());
-    sparse_product_impl2<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol);
-    res = resCol;
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,RowMajor,ColMajor,RowMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
-    ColMajorMatrix lhsCol = lhs;
-    ColMajorMatrix resCol(res.rows(), res.cols());
-    sparse_product_impl2<ColMajorMatrix,Rhs,ColMajorMatrix>(lhsCol, rhs, resCol);
-    res = resCol;
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,ColMajor,RowMajor,RowMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
-    ColMajorMatrix rhsCol = rhs;
-    ColMajorMatrix resCol(res.rows(), res.cols());
-    sparse_product_impl2<Lhs,ColMajorMatrix,ColMajorMatrix>(lhs, rhsCol, resCol);
-    res = resCol;
-  }
-};
-
-template<typename Lhs, typename Rhs, typename ResultType>
-struct sparse_product_selector2<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor>
-{
-  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
-  {
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
-//     ColMajorMatrix lhsTr(lhs);
-//     ColMajorMatrix rhsTr(rhs);
-//     ColMajorMatrix aux(res.rows(), res.cols());
-//     sparse_product_impl2<Rhs,Lhs,ColMajorMatrix>(rhs, lhs, aux);
-// //     ColMajorMatrix aux2 = aux.transpose();
-//     res = aux;
-    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
-    ColMajorMatrix lhsCol(lhs);
-    ColMajorMatrix rhsCol(rhs);
-    ColMajorMatrix resCol(res.rows(), res.cols());
-    sparse_product_impl2<ColMajorMatrix,ColMajorMatrix,ColMajorMatrix>(lhsCol, rhsCol, resCol);
-    res = resCol;
-  }
-};
-
-} // end namespace internal
-
-template<typename Derived>
-template<typename Lhs, typename Rhs>
-inline void SparseMatrixBase<Derived>::_experimentalNewProduct(const Lhs& lhs, const Rhs& rhs)
-{
-  //derived().resize(lhs.rows(), rhs.cols());
-  internal::sparse_product_selector2<
-    typename internal::remove_all<Lhs>::type,
-    typename internal::remove_all<Rhs>::type,
-    Derived>::run(lhs,rhs,derived());
-}
-
-// sparse * sparse
-template<typename Derived>
-template<typename OtherDerived>
-inline const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type
-SparseMatrixBase<Derived>::operator*(const SparseMatrixBase<OtherDerived> &other) const
-{
-  return typename SparseSparseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
-}
-
-#endif // EIGEN_SPARSESPARSEPRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseTriangularView.h b/extern/Eigen3/Eigen/src/Sparse/SparseTriangularView.h
deleted file mode 100644
index 319eaf06638..00000000000
--- a/extern/Eigen3/Eigen/src/Sparse/SparseTriangularView.h
+++ /dev/null
@@ -1,100 +0,0 @@
-// This file is part of Eigen, a lightweight C++ template library
-// for linear algebra.
-//
-// Copyright (C) 2009 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_SPARSE_TRIANGULARVIEW_H
-#define EIGEN_SPARSE_TRIANGULARVIEW_H
-
-namespace internal {
-  
-template<typename MatrixType, int Mode>
-struct traits<SparseTriangularView<MatrixType,Mode> >
-: public traits<MatrixType>
-{};
-
-} // namespace internal
-
-template<typename MatrixType, int Mode> class SparseTriangularView
-  : public SparseMatrixBase<SparseTriangularView<MatrixType,Mode> >
-{
-    enum { SkipFirst = (Mode==Lower && !(MatrixType::Flags&RowMajorBit))
-                    || (Mode==Upper &&  (MatrixType::Flags&RowMajorBit)) };
-  public:
-    
-    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseTriangularView)
-
-    class InnerIterator;
-
-    inline Index rows() const { return m_matrix.rows(); }
-    inline Index cols() const { return m_matrix.cols(); }
-
-    typedef typename internal::conditional<internal::must_nest_by_value<MatrixType>::ret,
-        MatrixType, const MatrixType&>::type MatrixTypeNested;
-
-    inline SparseTriangularView(const MatrixType& matrix) : m_matrix(matrix) {}
-
-    /** \internal */
-    inline const MatrixType& nestedExpression() const { return m_matrix; }
-
-    template<typename OtherDerived>
-    typename internal::plain_matrix_type_column_major<OtherDerived>::type
-    solve(const MatrixBase<OtherDerived>& other) const;
-
-    template<typename OtherDerived> void solveInPlace(MatrixBase<OtherDerived>& other) const;
-    template<typename OtherDerived> void solveInPlace(SparseMatrixBase<OtherDerived>& other) const;
-
-  protected:
-    MatrixTypeNested m_matrix;
-};
-
-template<typename MatrixType, int Mode>
-class SparseTriangularView<MatrixType,Mode>::InnerIterator : public MatrixType::InnerIterator
-{
-    typedef typename MatrixType::InnerIterator Base;
-  public:
-
-    EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, Index outer)
-      : Base(view.nestedExpression(), outer)
-    {
-      if(SkipFirst)
-        while((*this) && this->index()<outer)
-          ++(*this);
-    }
-    inline Index row() const { return Base::row(); }
-    inline Index col() const { return Base::col(); }
-
-    EIGEN_STRONG_INLINE operator bool() const
-    {
-      return SkipFirst ? Base::operator bool() : (Base::operator bool() && this->index() <= this->outer());
-    }
-};
-
-template<typename Derived>
-template<int Mode>
-inline const SparseTriangularView<Derived, Mode>
-SparseMatrixBase<Derived>::triangularView() const
-{
-  return derived();
-}
-
-#endif // EIGEN_SPARSE_TRIANGULARVIEW_H
diff --git a/extern/Eigen3/Eigen/src/SparseCholesky/SimplicialCholesky.h b/extern/Eigen3/Eigen/src/SparseCholesky/SimplicialCholesky.h
new file mode 100644
index 00000000000..9bf38ab2d91
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCholesky/SimplicialCholesky.h
@@ -0,0 +1,873 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+/*
+
+NOTE: the _symbolic, and _numeric functions has been adapted from
+      the LDL library:
+
+LDL Copyright (c) 2005 by Timothy A. Davis.  All Rights Reserved.
+
+LDL License:
+
+    Your use or distribution of LDL or any modified version of
+    LDL implies that you agree to this License.
+
+    This library is free software; you can redistribute it and/or
+    modify it under the terms of the GNU Lesser General Public
+    License as published by the Free Software Foundation; either
+    version 2.1 of the License, or (at your option) any later version.
+
+    This library is distributed in the hope that it will be useful,
+    but WITHOUT ANY WARRANTY; without even the implied warranty of
+    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+    Lesser General Public License for more details.
+
+    You should have received a copy of the GNU Lesser General Public
+    License along with this library; if not, write to the Free Software
+    Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301
+    USA
+
+    Permission is hereby granted to use or copy this program under the
+    terms of the GNU LGPL, provided that the Copyright, this License,
+    and the Availability of the original version is retained on all copies.
+    User documentation of any code that uses this code or any modified
+    version of this code must cite the Copyright, this License, the
+    Availability note, and "Used by permission." Permission to modify
+    the code and to distribute modified code is granted, provided the
+    Copyright, this License, and the Availability note are retained,
+    and a notice that the code was modified is included.
+ */
+
+#include "../Core/util/NonMPL2.h"
+
+#ifndef EIGEN_SIMPLICIAL_CHOLESKY_H
+#define EIGEN_SIMPLICIAL_CHOLESKY_H
+
+namespace Eigen { 
+
+enum SimplicialCholeskyMode {
+  SimplicialCholeskyLLT,
+  SimplicialCholeskyLDLT
+};
+
+/** \ingroup SparseCholesky_Module
+  * \brief A direct sparse Cholesky factorizations
+  *
+  * These classes provide LL^T and LDL^T Cholesky factorizations of sparse matrices that are
+  * selfadjoint and positive definite. The factorization allows for solving A.X = B where
+  * X and B can be either dense or sparse.
+  * 
+  * In order to reduce the fill-in, a symmetric permutation P is applied prior to the factorization
+  * such that the factorized matrix is P A P^-1.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  */
+template<typename Derived>
+class SimplicialCholeskyBase : internal::noncopyable
+{
+  public:
+    typedef typename internal::traits<Derived>::MatrixType MatrixType;
+    enum { UpLo = internal::traits<Derived>::UpLo };
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
+    typedef Matrix<Scalar,Dynamic,1> VectorType;
+
+  public:
+
+    /** Default constructor */
+    SimplicialCholeskyBase()
+      : m_info(Success), m_isInitialized(false), m_shiftOffset(0), m_shiftScale(1)
+    {}
+
+    SimplicialCholeskyBase(const MatrixType& matrix)
+      : m_info(Success), m_isInitialized(false), m_shiftOffset(0), m_shiftScale(1)
+    {
+      derived().compute(matrix);
+    }
+
+    ~SimplicialCholeskyBase()
+    {
+    }
+
+    Derived& derived() { return *static_cast<Derived*>(this); }
+    const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    
+    inline Index cols() const { return m_matrix.cols(); }
+    inline Index rows() const { return m_matrix.rows(); }
+    
+    /** \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 && "Decomposition is not initialized.");
+      return m_info;
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<SimplicialCholeskyBase, Rhs>
+    solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "Simplicial LLT or LDLT is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "SimplicialCholeskyBase::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<SimplicialCholeskyBase, Rhs>(*this, b.derived());
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::sparse_solve_retval<SimplicialCholeskyBase, Rhs>
+    solve(const SparseMatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "Simplicial LLT or LDLT is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "SimplicialCholesky::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::sparse_solve_retval<SimplicialCholeskyBase, Rhs>(*this, b.derived());
+    }
+    
+    /** \returns the permutation P
+      * \sa permutationPinv() */
+    const PermutationMatrix<Dynamic,Dynamic,Index>& permutationP() const
+    { return m_P; }
+    
+    /** \returns the inverse P^-1 of the permutation P
+      * \sa permutationP() */
+    const PermutationMatrix<Dynamic,Dynamic,Index>& permutationPinv() const
+    { return m_Pinv; }
+
+    /** Sets the shift parameters that will be used to adjust the diagonal coefficients during the numerical factorization.
+      *
+      * During the numerical factorization, the diagonal coefficients are transformed by the following linear model:\n
+      * \c d_ii = \a offset + \a scale * \c d_ii
+      *
+      * The default is the identity transformation with \a offset=0, and \a scale=1.
+      *
+      * \returns a reference to \c *this.
+      */
+    Derived& setShift(const RealScalar& offset, const RealScalar& scale = 1)
+    {
+      m_shiftOffset = offset;
+      m_shiftScale = scale;
+      return derived();
+    }
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal */
+    template<typename Stream>
+    void dumpMemory(Stream& s)
+    {
+      int total = 0;
+      s << "  L:        " << ((total+=(m_matrix.cols()+1) * sizeof(int) + m_matrix.nonZeros()*(sizeof(int)+sizeof(Scalar))) >> 20) << "Mb" << "\n";
+      s << "  diag:     " << ((total+=m_diag.size() * sizeof(Scalar)) >> 20) << "Mb" << "\n";
+      s << "  tree:     " << ((total+=m_parent.size() * sizeof(int)) >> 20) << "Mb" << "\n";
+      s << "  nonzeros: " << ((total+=m_nonZerosPerCol.size() * sizeof(int)) >> 20) << "Mb" << "\n";
+      s << "  perm:     " << ((total+=m_P.size() * sizeof(int)) >> 20) << "Mb" << "\n";
+      s << "  perm^-1:  " << ((total+=m_Pinv.size() * sizeof(int)) >> 20) << "Mb" << "\n";
+      s << "  TOTAL:    " << (total>> 20) << "Mb" << "\n";
+    }
+
+    /** \internal */
+    template<typename Rhs,typename Dest>
+    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    {
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      eigen_assert(m_matrix.rows()==b.rows());
+
+      if(m_info!=Success)
+        return;
+
+      if(m_P.size()>0)
+        dest = m_P * b;
+      else
+        dest = b;
+
+      if(m_matrix.nonZeros()>0) // otherwise L==I
+        derived().matrixL().solveInPlace(dest);
+
+      if(m_diag.size()>0)
+        dest = m_diag.asDiagonal().inverse() * dest;
+
+      if (m_matrix.nonZeros()>0) // otherwise U==I
+        derived().matrixU().solveInPlace(dest);
+
+      if(m_P.size()>0)
+        dest = m_Pinv * dest;
+    }
+
+    /** \internal */
+    template<typename Rhs, typename DestScalar, int DestOptions, typename DestIndex>
+    void _solve_sparse(const Rhs& b, SparseMatrix<DestScalar,DestOptions,DestIndex> &dest) const
+    {
+      eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      eigen_assert(m_matrix.rows()==b.rows());
+      
+      // we process the sparse rhs per block of NbColsAtOnce columns temporarily stored into a dense matrix.
+      static const int NbColsAtOnce = 4;
+      int rhsCols = b.cols();
+      int size = b.rows();
+      Eigen::Matrix<DestScalar,Dynamic,Dynamic> tmp(size,rhsCols);
+      for(int k=0; k<rhsCols; k+=NbColsAtOnce)
+      {
+        int actualCols = std::min<int>(rhsCols-k, NbColsAtOnce);
+        tmp.leftCols(actualCols) = b.middleCols(k,actualCols);
+        tmp.leftCols(actualCols) = derived().solve(tmp.leftCols(actualCols));
+        dest.middleCols(k,actualCols) = tmp.leftCols(actualCols).sparseView();
+      }
+    }
+
+#endif // EIGEN_PARSED_BY_DOXYGEN
+
+  protected:
+    
+    /** Computes the sparse Cholesky decomposition of \a matrix */
+    template<bool DoLDLT>
+    void compute(const MatrixType& matrix)
+    {
+      eigen_assert(matrix.rows()==matrix.cols());
+      Index size = matrix.cols();
+      CholMatrixType ap(size,size);
+      ordering(matrix, ap);
+      analyzePattern_preordered(ap, DoLDLT);
+      factorize_preordered<DoLDLT>(ap);
+    }
+    
+    template<bool DoLDLT>
+    void factorize(const MatrixType& a)
+    {
+      eigen_assert(a.rows()==a.cols());
+      int size = a.cols();
+      CholMatrixType ap(size,size);
+      ap.template selfadjointView<Upper>() = a.template selfadjointView<UpLo>().twistedBy(m_P);
+      factorize_preordered<DoLDLT>(ap);
+    }
+
+    template<bool DoLDLT>
+    void factorize_preordered(const CholMatrixType& a);
+
+    void analyzePattern(const MatrixType& a, bool doLDLT)
+    {
+      eigen_assert(a.rows()==a.cols());
+      int size = a.cols();
+      CholMatrixType ap(size,size);
+      ordering(a, ap);
+      analyzePattern_preordered(ap,doLDLT);
+    }
+    void analyzePattern_preordered(const CholMatrixType& a, bool doLDLT);
+    
+    void ordering(const MatrixType& a, CholMatrixType& ap);
+
+    /** keeps off-diagonal entries; drops diagonal entries */
+    struct keep_diag {
+      inline bool operator() (const Index& row, const Index& col, const Scalar&) const
+      {
+        return row!=col;
+      }
+    };
+
+    mutable ComputationInfo m_info;
+    bool m_isInitialized;
+    bool m_factorizationIsOk;
+    bool m_analysisIsOk;
+    
+    CholMatrixType m_matrix;
+    VectorType m_diag;                                // the diagonal coefficients (LDLT mode)
+    VectorXi m_parent;                                // elimination tree
+    VectorXi m_nonZerosPerCol;
+    PermutationMatrix<Dynamic,Dynamic,Index> m_P;     // the permutation
+    PermutationMatrix<Dynamic,Dynamic,Index> m_Pinv;  // the inverse permutation
+
+    RealScalar m_shiftOffset;
+    RealScalar m_shiftScale;
+};
+
+template<typename _MatrixType, int _UpLo = Lower> class SimplicialLLT;
+template<typename _MatrixType, int _UpLo = Lower> class SimplicialLDLT;
+template<typename _MatrixType, int _UpLo = Lower> class SimplicialCholesky;
+
+namespace internal {
+
+template<typename _MatrixType, int _UpLo> struct traits<SimplicialLLT<_MatrixType,_UpLo> >
+{
+  typedef _MatrixType MatrixType;
+  enum { UpLo = _UpLo };
+  typedef typename MatrixType::Scalar                         Scalar;
+  typedef typename MatrixType::Index                          Index;
+  typedef SparseMatrix<Scalar, ColMajor, Index>               CholMatrixType;
+  typedef SparseTriangularView<CholMatrixType, Eigen::Lower>  MatrixL;
+  typedef SparseTriangularView<typename CholMatrixType::AdjointReturnType, Eigen::Upper>   MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return m; }
+  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+};
+
+template<typename _MatrixType,int _UpLo> struct traits<SimplicialLDLT<_MatrixType,_UpLo> >
+{
+  typedef _MatrixType MatrixType;
+  enum { UpLo = _UpLo };
+  typedef typename MatrixType::Scalar                             Scalar;
+  typedef typename MatrixType::Index                              Index;
+  typedef SparseMatrix<Scalar, ColMajor, Index>                   CholMatrixType;
+  typedef SparseTriangularView<CholMatrixType, Eigen::UnitLower>  MatrixL;
+  typedef SparseTriangularView<typename CholMatrixType::AdjointReturnType, Eigen::UnitUpper> MatrixU;
+  static inline MatrixL getL(const MatrixType& m) { return m; }
+  static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); }
+};
+
+template<typename _MatrixType, int _UpLo> struct traits<SimplicialCholesky<_MatrixType,_UpLo> >
+{
+  typedef _MatrixType MatrixType;
+  enum { UpLo = _UpLo };
+};
+
+}
+
+/** \ingroup SparseCholesky_Module
+  * \class SimplicialLLT
+  * \brief A direct sparse LLT Cholesky factorizations
+  *
+  * This class provides a LL^T Cholesky factorizations of sparse matrices that are
+  * selfadjoint and positive definite. The factorization allows for solving A.X = B where
+  * X and B can be either dense or sparse.
+  * 
+  * In order to reduce the fill-in, a symmetric permutation P is applied prior to the factorization
+  * such that the factorized matrix is P A P^-1.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * \sa class SimplicialLDLT
+  */
+template<typename _MatrixType, int _UpLo>
+    class SimplicialLLT : public SimplicialCholeskyBase<SimplicialLLT<_MatrixType,_UpLo> >
+{
+public:
+    typedef _MatrixType MatrixType;
+    enum { UpLo = _UpLo };
+    typedef SimplicialCholeskyBase<SimplicialLLT> Base;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
+    typedef Matrix<Scalar,Dynamic,1> VectorType;
+    typedef internal::traits<SimplicialLLT> Traits;
+    typedef typename Traits::MatrixL  MatrixL;
+    typedef typename Traits::MatrixU  MatrixU;
+public:
+    /** Default constructor */
+    SimplicialLLT() : Base() {}
+    /** Constructs and performs the LLT factorization of \a matrix */
+    SimplicialLLT(const MatrixType& matrix)
+        : Base(matrix) {}
+
+    /** \returns an expression of the factor L */
+    inline const MatrixL matrixL() const {
+        eigen_assert(Base::m_factorizationIsOk && "Simplicial LLT not factorized");
+        return Traits::getL(Base::m_matrix);
+    }
+
+    /** \returns an expression of the factor U (= L^*) */
+    inline const MatrixU matrixU() const {
+        eigen_assert(Base::m_factorizationIsOk && "Simplicial LLT not factorized");
+        return Traits::getU(Base::m_matrix);
+    }
+    
+    /** Computes the sparse Cholesky decomposition of \a matrix */
+    SimplicialLLT& compute(const MatrixType& matrix)
+    {
+      Base::template compute<false>(matrix);
+      return *this;
+    }
+
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      *
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& a)
+    {
+      Base::analyzePattern(a, false);
+    }
+
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    void factorize(const MatrixType& a)
+    {
+      Base::template factorize<false>(a);
+    }
+
+    /** \returns the determinant of the underlying matrix from the current factorization */
+    Scalar determinant() const
+    {
+      Scalar detL = Base::m_matrix.diagonal().prod();
+      return internal::abs2(detL);
+    }
+};
+
+/** \ingroup SparseCholesky_Module
+  * \class SimplicialLDLT
+  * \brief A direct sparse LDLT Cholesky factorizations without square root.
+  *
+  * This class provides a LDL^T Cholesky factorizations without square root of sparse matrices that are
+  * selfadjoint and positive definite. The factorization allows for solving A.X = B where
+  * X and B can be either dense or sparse.
+  * 
+  * In order to reduce the fill-in, a symmetric permutation P is applied prior to the factorization
+  * such that the factorized matrix is P A P^-1.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower
+  *               or Upper. Default is Lower.
+  *
+  * \sa class SimplicialLLT
+  */
+template<typename _MatrixType, int _UpLo>
+    class SimplicialLDLT : public SimplicialCholeskyBase<SimplicialLDLT<_MatrixType,_UpLo> >
+{
+public:
+    typedef _MatrixType MatrixType;
+    enum { UpLo = _UpLo };
+    typedef SimplicialCholeskyBase<SimplicialLDLT> Base;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
+    typedef Matrix<Scalar,Dynamic,1> VectorType;
+    typedef internal::traits<SimplicialLDLT> Traits;
+    typedef typename Traits::MatrixL  MatrixL;
+    typedef typename Traits::MatrixU  MatrixU;
+public:
+    /** Default constructor */
+    SimplicialLDLT() : Base() {}
+
+    /** Constructs and performs the LLT factorization of \a matrix */
+    SimplicialLDLT(const MatrixType& matrix)
+        : Base(matrix) {}
+
+    /** \returns a vector expression of the diagonal D */
+    inline const VectorType vectorD() const {
+        eigen_assert(Base::m_factorizationIsOk && "Simplicial LDLT not factorized");
+        return Base::m_diag;
+    }
+    /** \returns an expression of the factor L */
+    inline const MatrixL matrixL() const {
+        eigen_assert(Base::m_factorizationIsOk && "Simplicial LDLT not factorized");
+        return Traits::getL(Base::m_matrix);
+    }
+
+    /** \returns an expression of the factor U (= L^*) */
+    inline const MatrixU matrixU() const {
+        eigen_assert(Base::m_factorizationIsOk && "Simplicial LDLT not factorized");
+        return Traits::getU(Base::m_matrix);
+    }
+
+    /** Computes the sparse Cholesky decomposition of \a matrix */
+    SimplicialLDLT& compute(const MatrixType& matrix)
+    {
+      Base::template compute<true>(matrix);
+      return *this;
+    }
+    
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      *
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& a)
+    {
+      Base::analyzePattern(a, true);
+    }
+
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    void factorize(const MatrixType& a)
+    {
+      Base::template factorize<true>(a);
+    }
+
+    /** \returns the determinant of the underlying matrix from the current factorization */
+    Scalar determinant() const
+    {
+      return Base::m_diag.prod();
+    }
+};
+
+/** \deprecated use SimplicialLDLT or class SimplicialLLT
+  * \ingroup SparseCholesky_Module
+  * \class SimplicialCholesky
+  *
+  * \sa class SimplicialLDLT, class SimplicialLLT
+  */
+template<typename _MatrixType, int _UpLo>
+    class SimplicialCholesky : public SimplicialCholeskyBase<SimplicialCholesky<_MatrixType,_UpLo> >
+{
+public:
+    typedef _MatrixType MatrixType;
+    enum { UpLo = _UpLo };
+    typedef SimplicialCholeskyBase<SimplicialCholesky> Base;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    typedef SparseMatrix<Scalar,ColMajor,Index> CholMatrixType;
+    typedef Matrix<Scalar,Dynamic,1> VectorType;
+    typedef internal::traits<SimplicialCholesky> Traits;
+    typedef internal::traits<SimplicialLDLT<MatrixType,UpLo> > LDLTTraits;
+    typedef internal::traits<SimplicialLLT<MatrixType,UpLo>  > LLTTraits;
+  public:
+    SimplicialCholesky() : Base(), m_LDLT(true) {}
+
+    SimplicialCholesky(const MatrixType& matrix)
+      : Base(), m_LDLT(true)
+    {
+      compute(matrix);
+    }
+
+    SimplicialCholesky& setMode(SimplicialCholeskyMode mode)
+    {
+      switch(mode)
+      {
+      case SimplicialCholeskyLLT:
+        m_LDLT = false;
+        break;
+      case SimplicialCholeskyLDLT:
+        m_LDLT = true;
+        break;
+      default:
+        break;
+      }
+
+      return *this;
+    }
+
+    inline const VectorType vectorD() const {
+        eigen_assert(Base::m_factorizationIsOk && "Simplicial Cholesky not factorized");
+        return Base::m_diag;
+    }
+    inline const CholMatrixType rawMatrix() const {
+        eigen_assert(Base::m_factorizationIsOk && "Simplicial Cholesky not factorized");
+        return Base::m_matrix;
+    }
+    
+    /** Computes the sparse Cholesky decomposition of \a matrix */
+    SimplicialCholesky& compute(const MatrixType& matrix)
+    {
+      if(m_LDLT)
+        Base::template compute<true>(matrix);
+      else
+        Base::template compute<false>(matrix);
+      return *this;
+    }
+
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      *
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& a)
+    {
+      Base::analyzePattern(a, m_LDLT);
+    }
+
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    void factorize(const MatrixType& a)
+    {
+      if(m_LDLT)
+        Base::template factorize<true>(a);
+      else
+        Base::template factorize<false>(a);
+    }
+
+    /** \internal */
+    template<typename Rhs,typename Dest>
+    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const
+    {
+      eigen_assert(Base::m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()");
+      eigen_assert(Base::m_matrix.rows()==b.rows());
+
+      if(Base::m_info!=Success)
+        return;
+
+      if(Base::m_P.size()>0)
+        dest = Base::m_P * b;
+      else
+        dest = b;
+
+      if(Base::m_matrix.nonZeros()>0) // otherwise L==I
+      {
+        if(m_LDLT)
+          LDLTTraits::getL(Base::m_matrix).solveInPlace(dest);
+        else
+          LLTTraits::getL(Base::m_matrix).solveInPlace(dest);
+      }
+
+      if(Base::m_diag.size()>0)
+        dest = Base::m_diag.asDiagonal().inverse() * dest;
+
+      if (Base::m_matrix.nonZeros()>0) // otherwise I==I
+      {
+        if(m_LDLT)
+          LDLTTraits::getU(Base::m_matrix).solveInPlace(dest);
+        else
+          LLTTraits::getU(Base::m_matrix).solveInPlace(dest);
+      }
+
+      if(Base::m_P.size()>0)
+        dest = Base::m_Pinv * dest;
+    }
+    
+    Scalar determinant() const
+    {
+      if(m_LDLT)
+      {
+        return Base::m_diag.prod();
+      }
+      else
+      {
+        Scalar detL = Diagonal<const CholMatrixType>(Base::m_matrix).prod();
+        return internal::abs2(detL);
+      }
+    }
+    
+  protected:
+    bool m_LDLT;
+};
+
+template<typename Derived>
+void SimplicialCholeskyBase<Derived>::ordering(const MatrixType& a, CholMatrixType& ap)
+{
+  eigen_assert(a.rows()==a.cols());
+  const Index size = a.rows();
+  // TODO allows to configure the permutation
+  // Note that amd compute the inverse permutation
+  {
+    CholMatrixType C;
+    C = a.template selfadjointView<UpLo>();
+    // remove diagonal entries:
+    // seems not to be needed
+    // C.prune(keep_diag());
+    internal::minimum_degree_ordering(C, m_Pinv);
+  }
+
+  if(m_Pinv.size()>0)
+    m_P = m_Pinv.inverse();
+  else
+    m_P.resize(0);
+
+  ap.resize(size,size);
+  ap.template selfadjointView<Upper>() = a.template selfadjointView<UpLo>().twistedBy(m_P);
+}
+
+template<typename Derived>
+void SimplicialCholeskyBase<Derived>::analyzePattern_preordered(const CholMatrixType& ap, bool doLDLT)
+{
+  const Index size = ap.rows();
+  m_matrix.resize(size, size);
+  m_parent.resize(size);
+  m_nonZerosPerCol.resize(size);
+  
+  ei_declare_aligned_stack_constructed_variable(Index, tags, size, 0);
+
+  for(Index k = 0; k < size; ++k)
+  {
+    /* L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) */
+    m_parent[k] = -1;             /* parent of k is not yet known */
+    tags[k] = k;                  /* mark node k as visited */
+    m_nonZerosPerCol[k] = 0;      /* count of nonzeros in column k of L */
+    for(typename CholMatrixType::InnerIterator it(ap,k); it; ++it)
+    {
+      Index i = it.index();
+      if(i < k)
+      {
+        /* follow path from i to root of etree, stop at flagged node */
+        for(; tags[i] != k; i = m_parent[i])
+        {
+          /* find parent of i if not yet determined */
+          if (m_parent[i] == -1)
+            m_parent[i] = k;
+          m_nonZerosPerCol[i]++;        /* L (k,i) is nonzero */
+          tags[i] = k;                  /* mark i as visited */
+        }
+      }
+    }
+  }
+  
+  /* construct Lp index array from m_nonZerosPerCol column counts */
+  Index* Lp = m_matrix.outerIndexPtr();
+  Lp[0] = 0;
+  for(Index k = 0; k < size; ++k)
+    Lp[k+1] = Lp[k] + m_nonZerosPerCol[k] + (doLDLT ? 0 : 1);
+
+  m_matrix.resizeNonZeros(Lp[size]);
+  
+  m_isInitialized     = true;
+  m_info              = Success;
+  m_analysisIsOk      = true;
+  m_factorizationIsOk = false;
+}
+
+
+template<typename Derived>
+template<bool DoLDLT>
+void SimplicialCholeskyBase<Derived>::factorize_preordered(const CholMatrixType& ap)
+{
+  eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
+  eigen_assert(ap.rows()==ap.cols());
+  const Index size = ap.rows();
+  eigen_assert(m_parent.size()==size);
+  eigen_assert(m_nonZerosPerCol.size()==size);
+
+  const Index* Lp = m_matrix.outerIndexPtr();
+  Index* Li = m_matrix.innerIndexPtr();
+  Scalar* Lx = m_matrix.valuePtr();
+
+  ei_declare_aligned_stack_constructed_variable(Scalar, y, size, 0);
+  ei_declare_aligned_stack_constructed_variable(Index,  pattern, size, 0);
+  ei_declare_aligned_stack_constructed_variable(Index,  tags, size, 0);
+  
+  bool ok = true;
+  m_diag.resize(DoLDLT ? size : 0);
+  
+  for(Index k = 0; k < size; ++k)
+  {
+    // compute nonzero pattern of kth row of L, in topological order
+    y[k] = 0.0;                     // Y(0:k) is now all zero
+    Index top = size;               // stack for pattern is empty
+    tags[k] = k;                    // mark node k as visited
+    m_nonZerosPerCol[k] = 0;        // count of nonzeros in column k of L
+    for(typename MatrixType::InnerIterator it(ap,k); it; ++it)
+    {
+      Index i = it.index();
+      if(i <= k)
+      {
+        y[i] += internal::conj(it.value());            /* scatter A(i,k) into Y (sum duplicates) */
+        Index len;
+        for(len = 0; tags[i] != k; i = m_parent[i])
+        {
+          pattern[len++] = i;     /* L(k,i) is nonzero */
+          tags[i] = k;            /* mark i as visited */
+        }
+        while(len > 0)
+          pattern[--top] = pattern[--len];
+      }
+    }
+
+    /* compute numerical values kth row of L (a sparse triangular solve) */
+
+    RealScalar d = internal::real(y[k]) * m_shiftScale + m_shiftOffset;    // get D(k,k), apply the shift function, and clear Y(k)
+    y[k] = 0.0;
+    for(; top < size; ++top)
+    {
+      Index i = pattern[top];       /* pattern[top:n-1] is pattern of L(:,k) */
+      Scalar yi = y[i];             /* get and clear Y(i) */
+      y[i] = 0.0;
+      
+      /* the nonzero entry L(k,i) */
+      Scalar l_ki;
+      if(DoLDLT)
+        l_ki = yi / m_diag[i];       
+      else
+        yi = l_ki = yi / Lx[Lp[i]];
+      
+      Index p2 = Lp[i] + m_nonZerosPerCol[i];
+      Index p;
+      for(p = Lp[i] + (DoLDLT ? 0 : 1); p < p2; ++p)
+        y[Li[p]] -= internal::conj(Lx[p]) * yi;
+      d -= internal::real(l_ki * internal::conj(yi));
+      Li[p] = k;                          /* store L(k,i) in column form of L */
+      Lx[p] = l_ki;
+      ++m_nonZerosPerCol[i];              /* increment count of nonzeros in col i */
+    }
+    if(DoLDLT)
+    {
+      m_diag[k] = d;
+      if(d == RealScalar(0))
+      {
+        ok = false;                         /* failure, D(k,k) is zero */
+        break;
+      }
+    }
+    else
+    {
+      Index p = Lp[k] + m_nonZerosPerCol[k]++;
+      Li[p] = k ;                /* store L(k,k) = sqrt (d) in column k */
+      if(d <= RealScalar(0)) {
+        ok = false;              /* failure, matrix is not positive definite */
+        break;
+      }
+      Lx[p] = internal::sqrt(d) ;
+    }
+  }
+
+  m_info = ok ? Success : NumericalIssue;
+  m_factorizationIsOk = true;
+}
+
+namespace internal {
+  
+template<typename Derived, typename Rhs>
+struct solve_retval<SimplicialCholeskyBase<Derived>, Rhs>
+  : solve_retval_base<SimplicialCholeskyBase<Derived>, Rhs>
+{
+  typedef SimplicialCholeskyBase<Derived> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec().derived()._solve(rhs(),dst);
+  }
+};
+
+template<typename Derived, typename Rhs>
+struct sparse_solve_retval<SimplicialCholeskyBase<Derived>, Rhs>
+  : sparse_solve_retval_base<SimplicialCholeskyBase<Derived>, Rhs>
+{
+  typedef SimplicialCholeskyBase<Derived> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec().derived()._solve_sparse(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SIMPLICIAL_CHOLESKY_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/AmbiVector.h b/extern/Eigen3/Eigen/src/SparseCore/AmbiVector.h
index 2ea8ba3096b..6cfaadbaa9a 100644
--- a/extern/Eigen3/Eigen/src/Sparse/AmbiVector.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/AmbiVector.h
@@ -3,28 +3,17 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_AMBIVECTOR_H
 #define EIGEN_AMBIVECTOR_H
 
+namespace Eigen { 
+
+namespace internal {
+
 /** \internal
   * Hybrid sparse/dense vector class designed for intensive read-write operations.
   *
@@ -299,7 +288,7 @@ class AmbiVector<_Scalar,_Index>::Iterator
       * In practice, all coefficients having a magnitude smaller than \a epsilon
       * are skipped.
       */
-    Iterator(const AmbiVector& vec, RealScalar epsilon = RealScalar(0.1)*NumTraits<RealScalar>::dummy_precision())
+    Iterator(const AmbiVector& vec, RealScalar epsilon = 0)
       : m_vector(vec)
     {
       m_epsilon = epsilon;
@@ -315,7 +304,7 @@ class AmbiVector<_Scalar,_Index>::Iterator
       {
         ListEl* EIGEN_RESTRICT llElements = reinterpret_cast<ListEl*>(m_vector.m_buffer);
         m_currentEl = m_vector.m_llStart;
-        while (m_currentEl>=0 && internal::abs(llElements[m_currentEl].value)<m_epsilon)
+        while (m_currentEl>=0 && internal::abs(llElements[m_currentEl].value)<=m_epsilon)
           m_currentEl = llElements[m_currentEl].next;
         if (m_currentEl<0)
         {
@@ -375,5 +364,8 @@ class AmbiVector<_Scalar,_Index>::Iterator
     bool m_isDense;             // mode of the vector
 };
 
+} // end namespace internal
+
+} // end namespace Eigen
 
 #endif // EIGEN_AMBIVECTOR_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/CompressedStorage.h b/extern/Eigen3/Eigen/src/SparseCore/CompressedStorage.h
index b3bde272ec2..85a998aff10 100644
--- a/extern/Eigen3/Eigen/src/Sparse/CompressedStorage.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/CompressedStorage.h
@@ -3,29 +3,19 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COMPRESSED_STORAGE_H
 #define EIGEN_COMPRESSED_STORAGE_H
 
-/** Stores a sparse set of values as a list of values and a list of indices.
+namespace Eigen { 
+
+namespace internal {
+
+/** \internal
+  * Stores a sparse set of values as a list of values and a list of indices.
   *
   */
 template<typename _Scalar,typename _Index>
@@ -218,8 +208,8 @@ class CompressedStorage
       Index* newIndices = new Index[size];
       size_t copySize = (std::min)(size, m_size);
       // copy
-      memcpy(newValues,  m_values,  copySize * sizeof(Scalar));
-      memcpy(newIndices, m_indices, copySize * sizeof(Index));
+      internal::smart_copy(m_values, m_values+copySize, newValues);
+      internal::smart_copy(m_indices, m_indices+copySize, newIndices);
       // delete old stuff
       delete[] m_values;
       delete[] m_indices;
@@ -236,4 +226,8 @@ class CompressedStorage
 
 };
 
+} // end namespace internal
+
+} // end namespace Eigen
+
 #endif // EIGEN_COMPRESSED_STORAGE_H
diff --git a/extern/Eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/extern/Eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h
new file mode 100644
index 00000000000..16b5e1dba6c
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h
@@ -0,0 +1,245 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H
+#define EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename Lhs, typename Rhs, typename ResultType>
+static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+{
+  typedef typename remove_all<Lhs>::type::Scalar Scalar;
+  typedef typename remove_all<Lhs>::type::Index Index;
+
+  // make sure to call innerSize/outerSize since we fake the storage order.
+  Index rows = lhs.innerSize();
+  Index cols = rhs.outerSize();
+  eigen_assert(lhs.outerSize() == rhs.innerSize());
+
+  std::vector<bool> mask(rows,false);
+  Matrix<Scalar,Dynamic,1> values(rows);
+  Matrix<Index,Dynamic,1>  indices(rows);
+
+  // estimate the number of non zero entries
+  // given a rhs column containing Y non zeros, we assume that the respective Y columns
+  // of the lhs differs in average of one non zeros, thus the number of non zeros for
+  // the product of a rhs column with the lhs is X+Y where X is the average number of non zero
+  // per column of the lhs.
+  // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs)
+  Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros();
+
+  res.setZero();
+  res.reserve(Index(estimated_nnz_prod));
+  // we compute each column of the result, one after the other
+  for (Index j=0; j<cols; ++j)
+  {
+
+    res.startVec(j);
+    Index nnz = 0;
+    for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
+    {
+      Scalar y = rhsIt.value();
+      Index k = rhsIt.index();
+      for (typename Lhs::InnerIterator lhsIt(lhs, k); lhsIt; ++lhsIt)
+      {
+        Index i = lhsIt.index();
+        Scalar x = lhsIt.value();
+        if(!mask[i])
+        {
+          mask[i] = true;
+          values[i] = x * y;
+          indices[nnz] = i;
+          ++nnz;
+        }
+        else
+          values[i] += x * y;
+      }
+    }
+
+    // unordered insertion
+    for(int k=0; k<nnz; ++k)
+    {
+      int i = indices[k];
+      res.insertBackByOuterInnerUnordered(j,i) = values[i];
+      mask[i] = false;
+    }
+
+#if 0
+    // alternative ordered insertion code:
+
+    int t200 = rows/(log2(200)*1.39);
+    int t = (rows*100)/139;
+
+    // FIXME reserve nnz non zeros
+    // FIXME implement fast sort algorithms for very small nnz
+    // if the result is sparse enough => use a quick sort
+    // otherwise => loop through the entire vector
+    // In order to avoid to perform an expensive log2 when the
+    // result is clearly very sparse we use a linear bound up to 200.
+    //if((nnz<200 && nnz<t200) || nnz * log2(nnz) < t)
+    //res.startVec(j);
+    if(true)
+    {
+      if(nnz>1) std::sort(indices.data(),indices.data()+nnz);
+      for(int k=0; k<nnz; ++k)
+      {
+        int i = indices[k];
+        res.insertBackByOuterInner(j,i) = values[i];
+        mask[i] = false;
+      }
+    }
+    else
+    {
+      // dense path
+      for(int i=0; i<rows; ++i)
+      {
+        if(mask[i])
+        {
+          mask[i] = false;
+          res.insertBackByOuterInner(j,i) = values[i];
+        }
+      }
+    }
+#endif
+
+  }
+  res.finalize();
+}
+
+
+} // end namespace internal
+
+namespace internal {
+
+template<typename Lhs, typename Rhs, typename ResultType,
+  int LhsStorageOrder = traits<Lhs>::Flags&RowMajorBit,
+  int RhsStorageOrder = traits<Rhs>::Flags&RowMajorBit,
+  int ResStorageOrder = traits<ResultType>::Flags&RowMajorBit>
+struct conservative_sparse_sparse_product_selector;
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,ColMajor>
+{
+  typedef typename remove_all<Lhs>::type LhsCleaned;
+  typedef typename LhsCleaned::Scalar Scalar;
+
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
+    ColMajorMatrix resCol(lhs.rows(),rhs.cols());
+    internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol);
+    // sort the non zeros:
+    RowMajorMatrix resRow(resCol);
+    res = resRow;
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,ColMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+     typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
+     RowMajorMatrix rhsRow = rhs;
+     RowMajorMatrix resRow(lhs.rows(), rhs.cols());
+     internal::conservative_sparse_sparse_product_impl<RowMajorMatrix,Lhs,RowMajorMatrix>(rhsRow, lhs, resRow);
+     res = resRow;
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,ColMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
+    RowMajorMatrix lhsRow = lhs;
+    RowMajorMatrix resRow(lhs.rows(), rhs.cols());
+    internal::conservative_sparse_sparse_product_impl<Rhs,RowMajorMatrix,RowMajorMatrix>(rhs, lhsRow, resRow);
+    res = resRow;
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
+    RowMajorMatrix resRow(lhs.rows(), rhs.cols());
+    internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow);
+    res = resRow;
+  }
+};
+
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,RowMajor>
+{
+  typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
+
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
+    ColMajorMatrix resCol(lhs.rows(), rhs.cols());
+    internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol);
+    res = resCol;
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,ColMajor,RowMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
+    ColMajorMatrix lhsCol = lhs;
+    ColMajorMatrix resCol(lhs.rows(), rhs.cols());
+    internal::conservative_sparse_sparse_product_impl<ColMajorMatrix,Rhs,ColMajorMatrix>(lhsCol, rhs, resCol);
+    res = resCol;
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,RowMajor,RowMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
+    ColMajorMatrix rhsCol = rhs;
+    ColMajorMatrix resCol(lhs.rows(), rhs.cols());
+    internal::conservative_sparse_sparse_product_impl<Lhs,ColMajorMatrix,ColMajorMatrix>(lhs, rhsCol, resCol);
+    res = resCol;
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor>
+{
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,RowMajor> RowMajorMatrix;
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
+    RowMajorMatrix resRow(lhs.rows(),rhs.cols());
+    internal::conservative_sparse_sparse_product_impl<Rhs,Lhs,RowMajorMatrix>(rhs, lhs, resRow);
+    // sort the non zeros:
+    ColMajorMatrix resCol(resRow);
+    res = resCol;
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_CONSERVATIVESPARSESPARSEPRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/CoreIterators.h b/extern/Eigen3/Eigen/src/SparseCore/CoreIterators.h
index b4beaeee69e..6da4683d2c2 100644
--- a/extern/Eigen3/Eigen/src/Sparse/CoreIterators.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/CoreIterators.h
@@ -3,32 +3,20 @@
 //
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_COREITERATORS_H
 #define EIGEN_COREITERATORS_H
 
+namespace Eigen { 
+
 /* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core
  */
 
-/** \class InnerIterator
+/** \ingroup SparseCore_Module
+  * \class InnerIterator
   * \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression
   *
   * todo
@@ -68,4 +56,6 @@ template<typename Derived> class DenseBase<Derived>::InnerIterator
     const Index m_end;
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_COREITERATORS_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/MappedSparseMatrix.h b/extern/Eigen3/Eigen/src/SparseCore/MappedSparseMatrix.h
index 31a431fb224..93cd4832dea 100644
--- a/extern/Eigen3/Eigen/src/Sparse/MappedSparseMatrix.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/MappedSparseMatrix.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MAPPED_SPARSEMATRIX_H
 #define EIGEN_MAPPED_SPARSEMATRIX_H
 
+namespace Eigen { 
+
 /** \class MappedSparseMatrix
   *
   * \brief Sparse matrix
@@ -46,9 +33,9 @@ class MappedSparseMatrix
 {
   public:
     EIGEN_SPARSE_PUBLIC_INTERFACE(MappedSparseMatrix)
+    enum { IsRowMajor = Base::IsRowMajor };
 
   protected:
-    enum { IsRowMajor = Base::IsRowMajor };
 
     Index   m_outerSize;
     Index   m_innerSize;
@@ -63,18 +50,17 @@ class MappedSparseMatrix
     inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
     inline Index innerSize() const { return m_innerSize; }
     inline Index outerSize() const { return m_outerSize; }
-    inline Index innerNonZeros(Index j) const { return m_outerIndex[j+1]-m_outerIndex[j]; }
 
     //----------------------------------------
     // direct access interface
-    inline const Scalar* _valuePtr() const { return m_values; }
-    inline Scalar* _valuePtr() { return m_values; }
+    inline const Scalar* valuePtr() const { return m_values; }
+    inline Scalar* valuePtr() { return m_values; }
 
-    inline const Index* _innerIndexPtr() const { return m_innerIndices; }
-    inline Index* _innerIndexPtr() { return m_innerIndices; }
+    inline const Index* innerIndexPtr() const { return m_innerIndices; }
+    inline Index* innerIndexPtr() { return m_innerIndices; }
 
-    inline const Index* _outerIndexPtr() const { return m_outerIndex; }
-    inline Index* _outerIndexPtr() { return m_outerIndex; }
+    inline const Index* outerIndexPtr() const { return m_outerIndex; }
+    inline Index* outerIndexPtr() { return m_outerIndex; }
     //----------------------------------------
 
     inline Scalar coeff(Index row, Index col) const
@@ -112,6 +98,7 @@ class MappedSparseMatrix
     }
 
     class InnerIterator;
+    class ReverseInnerIterator;
 
     /** \returns the number of non zero coefficients */
     inline Index nonZeros() const  { return m_nnz; }
@@ -132,23 +119,17 @@ class MappedSparseMatrix<Scalar,_Flags,_Index>::InnerIterator
     InnerIterator(const MappedSparseMatrix& mat, Index outer)
       : m_matrix(mat),
         m_outer(outer),
-        m_id(mat._outerIndexPtr()[outer]),
+        m_id(mat.outerIndexPtr()[outer]),
         m_start(m_id),
-        m_end(mat._outerIndexPtr()[outer+1])
-    {}
-
-    template<unsigned int Added, unsigned int Removed>
-    InnerIterator(const Flagged<MappedSparseMatrix,Added,Removed>& mat, Index outer)
-      : m_matrix(mat._expression()), m_id(m_matrix._outerIndexPtr()[outer]),
-        m_start(m_id), m_end(m_matrix._outerIndexPtr()[outer+1])
+        m_end(mat.outerIndexPtr()[outer+1])
     {}
 
     inline InnerIterator& operator++() { m_id++; return *this; }
 
-    inline Scalar value() const { return m_matrix._valuePtr()[m_id]; }
-    inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix._valuePtr()[m_id]); }
+    inline Scalar value() const { return m_matrix.valuePtr()[m_id]; }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.valuePtr()[m_id]); }
 
-    inline Index index() const { return m_matrix._innerIndexPtr()[m_id]; }
+    inline Index index() const { return m_matrix.innerIndexPtr()[m_id]; }
     inline Index row() const { return IsRowMajor ? m_outer : index(); }
     inline Index col() const { return IsRowMajor ? index() : m_outer; }
 
@@ -162,4 +143,37 @@ class MappedSparseMatrix<Scalar,_Flags,_Index>::InnerIterator
     const Index m_end;
 };
 
+template<typename Scalar, int _Flags, typename _Index>
+class MappedSparseMatrix<Scalar,_Flags,_Index>::ReverseInnerIterator
+{
+  public:
+    ReverseInnerIterator(const MappedSparseMatrix& mat, Index outer)
+      : m_matrix(mat),
+        m_outer(outer),
+        m_id(mat.outerIndexPtr()[outer+1]),
+        m_start(mat.outerIndexPtr()[outer]),
+        m_end(m_id)
+    {}
+
+    inline ReverseInnerIterator& operator--() { m_id--; return *this; }
+
+    inline Scalar value() const { return m_matrix.valuePtr()[m_id-1]; }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_matrix.valuePtr()[m_id-1]); }
+
+    inline Index index() const { return m_matrix.innerIndexPtr()[m_id-1]; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
+
+    inline operator bool() const { return (m_id <= m_end) && (m_id>m_start); }
+
+  protected:
+    const MappedSparseMatrix& m_matrix;
+    const Index m_outer;
+    Index m_id;
+    const Index m_start;
+    const Index m_end;
+};
+
+} // end namespace Eigen
+
 #endif // EIGEN_MAPPED_SPARSEMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseAssign.h b/extern/Eigen3/Eigen/src/SparseCore/SparseAssign.h
index e69de29bb2d..e69de29bb2d 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseAssign.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseAssign.h
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseBlock.h b/extern/Eigen3/Eigen/src/SparseCore/SparseBlock.h
index 8079c999994..eefd8070251 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseBlock.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseBlock.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_BLOCK_H
 #define EIGEN_SPARSE_BLOCK_H
 
+namespace Eigen { 
+
 namespace internal {
 template<typename MatrixType, int Size>
 struct traits<SparseInnerVectorSet<MatrixType, Size> >
@@ -65,6 +52,17 @@ class SparseInnerVectorSet : internal::no_assignment_operator,
       protected:
         Index m_outer;
     };
+    class ReverseInnerIterator: public MatrixType::ReverseInnerIterator
+    {
+      public:
+        inline ReverseInnerIterator(const SparseInnerVectorSet& xpr, Index outer)
+          : MatrixType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
+        {}
+        inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
+        inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
+      protected:
+        Index m_outer;
+    };
 
     inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize)
       : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
@@ -101,15 +99,16 @@ class SparseInnerVectorSet : internal::no_assignment_operator,
     const internal::variable_if_dynamic<Index, Size> m_outerSize;
 };
 
+
 /***************************************************************************
-* specialisation for DynamicSparseMatrix
+* specialisation for SparseMatrix
 ***************************************************************************/
 
-template<typename _Scalar, int _Options, int Size>
-class SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options>, Size>
-  : public SparseMatrixBase<SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options>, Size> >
+template<typename _Scalar, int _Options, typename _Index, int Size>
+class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
+  : public SparseMatrixBase<SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size> >
 {
-    typedef DynamicSparseMatrix<_Scalar, _Options> MatrixType;
+    typedef SparseMatrix<_Scalar, _Options, _Index> MatrixType;
   public:
 
     enum { IsRowMajor = internal::traits<SparseInnerVectorSet>::IsRowMajor };
@@ -126,98 +125,11 @@ class SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options>, Size>
       protected:
         Index m_outer;
     };
-
-    inline SparseInnerVectorSet(const MatrixType& matrix, Index outerStart, Index outerSize)
-      : m_matrix(matrix), m_outerStart(outerStart), m_outerSize(outerSize)
-    {
-      eigen_assert( (outerStart>=0) && ((outerStart+outerSize)<=matrix.outerSize()) );
-    }
-
-    inline SparseInnerVectorSet(const MatrixType& matrix, Index outer)
-      : m_matrix(matrix), m_outerStart(outer), m_outerSize(Size)
-    {
-      eigen_assert(Size!=Dynamic);
-      eigen_assert( (outer>=0) && (outer<matrix.outerSize()) );
-    }
-
-    template<typename OtherDerived>
-    inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
-    {
-      if (IsRowMajor != ((OtherDerived::Flags&RowMajorBit)==RowMajorBit))
-      {
-        // need to transpose => perform a block evaluation followed by a big swap
-        DynamicSparseMatrix<Scalar,IsRowMajor?RowMajorBit:0> aux(other);
-        *this = aux.markAsRValue();
-      }
-      else
-      {
-        // evaluate/copy vector per vector
-        for (Index j=0; j<m_outerSize.value(); ++j)
-        {
-          SparseVector<Scalar,IsRowMajor ? RowMajorBit : 0> aux(other.innerVector(j));
-          m_matrix.const_cast_derived()._data()[m_outerStart+j].swap(aux._data());
-        }
-      }
-      return *this;
-    }
-
-    inline SparseInnerVectorSet& operator=(const SparseInnerVectorSet& other)
-    {
-      return operator=<SparseInnerVectorSet>(other);
-    }
-
-    Index nonZeros() const
-    {
-      Index count = 0;
-      for (Index j=0; j<m_outerSize.value(); ++j)
-        count += m_matrix._data()[m_outerStart+j].size();
-      return count;
-    }
-
-    const Scalar& lastCoeff() const
-    {
-      EIGEN_STATIC_ASSERT_VECTOR_ONLY(SparseInnerVectorSet);
-      eigen_assert(m_matrix.data()[m_outerStart].size()>0);
-      return m_matrix.data()[m_outerStart].vale(m_matrix.data()[m_outerStart].size()-1);
-    }
-
-//     template<typename Sparse>
-//     inline SparseInnerVectorSet& operator=(const SparseMatrixBase<OtherDerived>& other)
-//     {
-//       return *this;
-//     }
-
-    EIGEN_STRONG_INLINE Index rows() const { return IsRowMajor ? m_outerSize.value() : m_matrix.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return IsRowMajor ? m_matrix.cols() : m_outerSize.value(); }
-
-  protected:
-
-    const typename MatrixType::Nested m_matrix;
-    Index m_outerStart;
-    const internal::variable_if_dynamic<Index, Size> m_outerSize;
-
-};
-
-
-/***************************************************************************
-* specialisation for SparseMatrix
-***************************************************************************/
-
-template<typename _Scalar, int _Options, typename _Index, int Size>
-class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
-  : public SparseMatrixBase<SparseInnerVectorSet<SparseMatrix<_Scalar, _Options>, Size> >
-{
-    typedef SparseMatrix<_Scalar, _Options> MatrixType;
-  public:
-
-    enum { IsRowMajor = internal::traits<SparseInnerVectorSet>::IsRowMajor };
-
-    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseInnerVectorSet)
-    class InnerIterator: public MatrixType::InnerIterator
+    class ReverseInnerIterator: public MatrixType::ReverseInnerIterator
     {
       public:
-        inline InnerIterator(const SparseInnerVectorSet& xpr, Index outer)
-          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
+        inline ReverseInnerIterator(const SparseInnerVectorSet& xpr, Index outer)
+          : MatrixType::ReverseInnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
         {}
         inline Index row() const { return IsRowMajor ? m_outer : this->index(); }
         inline Index col() const { return IsRowMajor ? this->index() : m_outer; }
@@ -243,19 +155,19 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
     {
       typedef typename internal::remove_all<typename MatrixType::Nested>::type _NestedMatrixType;
       _NestedMatrixType& matrix = const_cast<_NestedMatrixType&>(m_matrix);;
-      // This assignement is slow if this vector set not empty
+      // This assignement is slow if this vector set is not empty
       // and/or it is not at the end of the nonzeros of the underlying matrix.
 
       // 1 - eval to a temporary to avoid transposition and/or aliasing issues
       SparseMatrix<Scalar, IsRowMajor ? RowMajor : ColMajor, Index> tmp(other);
 
       // 2 - let's check whether there is enough allocated memory
-      Index nnz = tmp.nonZeros();
-      Index nnz_previous = nonZeros();
-      Index free_size = matrix.data().allocatedSize() - nnz_previous;
-      std::size_t nnz_head = m_outerStart==0 ? 0 : matrix._outerIndexPtr()[m_outerStart];
-      std::size_t tail = m_matrix._outerIndexPtr()[m_outerStart+m_outerSize.value()];
-      std::size_t nnz_tail = matrix.nonZeros() - tail;
+      Index nnz           = tmp.nonZeros();
+      Index nnz_previous  = nonZeros();
+      Index free_size     = Index(matrix.data().allocatedSize()) + nnz_previous;
+      Index nnz_head      = m_outerStart==0 ? 0 : matrix.outerIndexPtr()[m_outerStart];
+      Index tail          = m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()];
+      Index nnz_tail      = matrix.nonZeros() - tail;
 
       if(nnz>free_size)
       {
@@ -298,15 +210,15 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
 
       // update outer index pointers
       Index p = nnz_head;
-      for(Index k=1; k<m_outerSize.value(); ++k)
+      for(Index k=0; k<m_outerSize.value(); ++k)
       {
-        matrix._outerIndexPtr()[m_outerStart+k] = p;
+        matrix.outerIndexPtr()[m_outerStart+k] = p;
         p += tmp.innerVector(k).nonZeros();
       }
       std::ptrdiff_t offset = nnz - nnz_previous;
       for(Index k = m_outerStart + m_outerSize.value(); k<=matrix.outerSize(); ++k)
       {
-        matrix._outerIndexPtr()[k] += offset;
+        matrix.outerIndexPtr()[k] += offset;
       }
 
       return *this;
@@ -317,32 +229,40 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
       return operator=<SparseInnerVectorSet>(other);
     }
 
-    inline const Scalar* _valuePtr() const
-    { return m_matrix._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
-    inline Scalar* _valuePtr()
-    { return m_matrix.const_cast_derived()._valuePtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
+    inline const Scalar* valuePtr() const
+    { return m_matrix.valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
+    inline Scalar* valuePtr()
+    { return m_matrix.const_cast_derived().valuePtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
 
-    inline const Index* _innerIndexPtr() const
-    { return m_matrix._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
-    inline Index* _innerIndexPtr()
-    { return m_matrix.const_cast_derived()._innerIndexPtr() + m_matrix._outerIndexPtr()[m_outerStart]; }
+    inline const Index* innerIndexPtr() const
+    { return m_matrix.innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
+    inline Index* innerIndexPtr()
+    { return m_matrix.const_cast_derived().innerIndexPtr() + m_matrix.outerIndexPtr()[m_outerStart]; }
 
-    inline const Index* _outerIndexPtr() const
-    { return m_matrix._outerIndexPtr() + m_outerStart; }
-    inline Index* _outerIndexPtr()
-    { return m_matrix.const_cast_derived()._outerIndexPtr() + m_outerStart; }
+    inline const Index* outerIndexPtr() const
+    { return m_matrix.outerIndexPtr() + m_outerStart; }
+    inline Index* outerIndexPtr()
+    { return m_matrix.const_cast_derived().outerIndexPtr() + m_outerStart; }
 
     Index nonZeros() const
     {
-      return  std::size_t(m_matrix._outerIndexPtr()[m_outerStart+m_outerSize.value()])
-            - std::size_t(m_matrix._outerIndexPtr()[m_outerStart]);
+      if(m_matrix.isCompressed())
+        return  std::size_t(m_matrix.outerIndexPtr()[m_outerStart+m_outerSize.value()])
+              - std::size_t(m_matrix.outerIndexPtr()[m_outerStart]);
+      else if(m_outerSize.value()==0)
+        return 0;
+      else
+        return Map<const Matrix<Index,Size,1> >(m_matrix.innerNonZeroPtr()+m_outerStart, m_outerSize.value()).sum();
     }
 
     const Scalar& lastCoeff() const
     {
       EIGEN_STATIC_ASSERT_VECTOR_ONLY(SparseInnerVectorSet);
       eigen_assert(nonZeros()>0);
-      return m_matrix._valuePtr()[m_matrix._outerIndexPtr()[m_outerStart+1]-1];
+      if(m_matrix.isCompressed())
+        return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart+1]-1];
+      else
+        return m_matrix.valuePtr()[m_matrix.outerIndexPtr()[m_outerStart]+m_matrix.innerNonZeroPtr()[m_outerStart]-1];
     }
 
 //     template<typename Sparse>
@@ -356,7 +276,7 @@ class SparseInnerVectorSet<SparseMatrix<_Scalar, _Options, _Index>, Size>
 
   protected:
 
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
     Index m_outerStart;
     const internal::variable_if_dynamic<Index, Size> m_outerSize;
 
@@ -412,11 +332,9 @@ template<typename Derived>
 const SparseInnerVectorSet<Derived,1> SparseMatrixBase<Derived>::innerVector(Index outer) const
 { return SparseInnerVectorSet<Derived,1>(derived(), outer); }
 
-//----------
-
 /** \returns the i-th row of the matrix \c *this. For row-major matrix only. */
 template<typename Derived>
-SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(Index start, Index size)
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::middleRows(Index start, Index size)
 {
   EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
   return innerVectors(start, size);
@@ -425,7 +343,7 @@ SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(Index s
 /** \returns the i-th row of the matrix \c *this. For row-major matrix only.
   * (read-only version) */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(Index start, Index size) const
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::middleRows(Index start, Index size) const
 {
   EIGEN_STATIC_ASSERT(IsRowMajor,THIS_METHOD_IS_ONLY_FOR_ROW_MAJOR_MATRICES);
   return innerVectors(start, size);
@@ -433,7 +351,7 @@ const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subrows(I
 
 /** \returns the i-th column of the matrix \c *this. For column-major matrix only. */
 template<typename Derived>
-SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(Index start, Index size)
+SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::middleCols(Index start, Index size)
 {
   EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
   return innerVectors(start, size);
@@ -442,12 +360,14 @@ SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(Index s
 /** \returns the i-th column of the matrix \c *this. For column-major matrix only.
   * (read-only version) */
 template<typename Derived>
-const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::subcols(Index start, Index size) const
+const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::middleCols(Index start, Index size) const
 {
   EIGEN_STATIC_ASSERT(!IsRowMajor,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES);
   return innerVectors(start, size);
 }
 
+
+
 /** \returns the \a outer -th column (resp. row) of the matrix \c *this if \c *this
   * is col-major (resp. row-major).
   */
@@ -462,4 +382,6 @@ template<typename Derived>
 const SparseInnerVectorSet<Derived,Dynamic> SparseMatrixBase<Derived>::innerVectors(Index outerStart, Index outerSize) const
 { return SparseInnerVectorSet<Derived,Dynamic>(derived(), outerStart, outerSize); }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSE_BLOCK_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseCwiseBinaryOp.h b/extern/Eigen3/Eigen/src/SparseCore/SparseCwiseBinaryOp.h
index cde5bbc0300..d5f97f78fc9 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseCwiseBinaryOp.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseCwiseBinaryOp.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_CWISE_BINARY_OP_H
 #define EIGEN_SPARSE_CWISE_BINARY_OP_H
 
+namespace Eigen { 
+
 // Here we have to handle 3 cases:
 //  1 - sparse op dense
 //  2 - dense op sparse
@@ -63,8 +50,18 @@ class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Sparse>
 {
   public:
     class InnerIterator;
+    class ReverseInnerIterator;
     typedef CwiseBinaryOp<BinaryOp, Lhs, Rhs> Derived;
     EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
+    CwiseBinaryOpImpl()
+    {
+      typedef typename internal::traits<Lhs>::StorageKind LhsStorageKind;
+      typedef typename internal::traits<Rhs>::StorageKind RhsStorageKind;
+      EIGEN_STATIC_ASSERT((
+                (!internal::is_same<LhsStorageKind,RhsStorageKind>::value)
+            ||  ((Lhs::Flags&RowMajorBit) == (Rhs::Flags&RowMajorBit))),
+            THE_STORAGE_ORDER_OF_BOTH_SIDES_MUST_MATCH);
+    }
 };
 
 template<typename BinaryOp, typename Lhs, typename Rhs>
@@ -76,7 +73,7 @@ class CwiseBinaryOpImpl<BinaryOp,Lhs,Rhs,Sparse>::InnerIterator
     typedef internal::sparse_cwise_binary_op_inner_iterator_selector<
       BinaryOp,Lhs,Rhs, InnerIterator> Base;
 
-    EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, Index outer)
+    EIGEN_STRONG_INLINE InnerIterator(const CwiseBinaryOpImpl& binOp, typename CwiseBinaryOpImpl::Index outer)
       : Base(binOp.derived(),outer)
     {}
 };
@@ -246,7 +243,7 @@ class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs,
     EIGEN_STRONG_INLINE operator bool() const { return m_lhsIter; }
 
   protected:
-    const RhsNested m_rhs;
+    RhsNested m_rhs;
     LhsIterator m_lhsIter;
     const BinaryFunc m_functor;
     const Index m_outer;
@@ -298,16 +295,6 @@ class sparse_cwise_binary_op_inner_iterator_selector<scalar_product_op<T>, Lhs,
 * Implementation of SparseMatrixBase and SparseCwise functions/operators
 ***************************************************************************/
 
-// template<typename Derived>
-// template<typename OtherDerived>
-// EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_difference_op<typename internal::traits<Derived>::Scalar>,
-//                                  Derived, OtherDerived>
-// SparseMatrixBase<Derived>::operator-(const SparseMatrixBase<OtherDerived> &other) const
-// {
-//   return CwiseBinaryOp<internal::scalar_difference_op<Scalar>,
-//                        Derived, OtherDerived>(derived(), other.derived());
-// }
-
 template<typename Derived>
 template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived &
@@ -316,14 +303,6 @@ SparseMatrixBase<Derived>::operator-=(const SparseMatrixBase<OtherDerived> &othe
   return *this = derived() - other.derived();
 }
 
-// template<typename Derived>
-// template<typename OtherDerived>
-// EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_sum_op<typename internal::traits<Derived>::Scalar>, Derived, OtherDerived>
-// SparseMatrixBase<Derived>::operator+(const SparseMatrixBase<OtherDerived> &other) const
-// {
-//   return CwiseBinaryOp<internal::scalar_sum_op<Scalar>, Derived, OtherDerived>(derived(), other.derived());
-// }
-
 template<typename Derived>
 template<typename OtherDerived>
 EIGEN_STRONG_INLINE Derived &
@@ -332,14 +311,6 @@ SparseMatrixBase<Derived>::operator+=(const SparseMatrixBase<OtherDerived>& othe
   return *this = derived() + other.derived();
 }
 
-// template<typename ExpressionType>
-// template<typename OtherDerived>
-// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
-// SparseCwise<ExpressionType>::operator*(const SparseMatrixBase<OtherDerived> &other) const
-// {
-//   return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(_expression(), other.derived());
-// }
-
 template<typename Derived>
 template<typename OtherDerived>
 EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
@@ -348,28 +319,6 @@ SparseMatrixBase<Derived>::cwiseProduct(const MatrixBase<OtherDerived> &other) c
   return EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE(derived(), other.derived());
 }
 
-// template<typename ExpressionType>
-// template<typename OtherDerived>
-// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)
-// SparseCwise<ExpressionType>::operator/(const SparseMatrixBase<OtherDerived> &other) const
-// {
-//   return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)(_expression(), other.derived());
-// }
-//
-// template<typename ExpressionType>
-// template<typename OtherDerived>
-// EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)
-// SparseCwise<ExpressionType>::operator/(const MatrixBase<OtherDerived> &other) const
-// {
-//   return EIGEN_SPARSE_CWISE_BINOP_RETURN_TYPE(internal::scalar_quotient_op)(_expression(), other.derived());
-// }
-
-// template<typename ExpressionType>
-// template<typename OtherDerived>
-// inline ExpressionType& SparseCwise<ExpressionType>::operator*=(const SparseMatrixBase<OtherDerived> &other)
-// {
-//   return m_matrix.const_cast_derived() = _expression() * other.derived();
-// }
-
+} // end namespace Eigen
 
 #endif // EIGEN_SPARSE_CWISE_BINARY_OP_H
diff --git a/extern/Eigen3/Eigen/src/SparseCore/SparseCwiseUnaryOp.h b/extern/Eigen3/Eigen/src/SparseCore/SparseCwiseUnaryOp.h
new file mode 100644
index 00000000000..5a50c780303
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseCwiseUnaryOp.h
@@ -0,0 +1,163 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_CWISE_UNARY_OP_H
+#define EIGEN_SPARSE_CWISE_UNARY_OP_H
+
+namespace Eigen { 
+
+template<typename UnaryOp, typename MatrixType>
+class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>
+  : public SparseMatrixBase<CwiseUnaryOp<UnaryOp, MatrixType> >
+{
+  public:
+
+    class InnerIterator;
+    class ReverseInnerIterator;
+
+    typedef CwiseUnaryOp<UnaryOp, MatrixType> Derived;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
+
+  protected:
+    typedef typename internal::traits<Derived>::_XprTypeNested _MatrixTypeNested;
+    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
+    typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator;
+};
+
+template<typename UnaryOp, typename MatrixType>
+class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::InnerIterator
+    : public CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeIterator
+{
+    typedef typename CwiseUnaryOpImpl::Scalar Scalar;
+    typedef typename CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer)
+      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
+    {}
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    { Base::operator++(); return *this; }
+
+    EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); }
+
+  protected:
+    const UnaryOp m_functor;
+  private:
+    typename CwiseUnaryOpImpl::Scalar& valueRef();
+};
+
+template<typename UnaryOp, typename MatrixType>
+class CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::ReverseInnerIterator
+    : public CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeReverseIterator
+{
+    typedef typename CwiseUnaryOpImpl::Scalar Scalar;
+    typedef typename CwiseUnaryOpImpl<UnaryOp,MatrixType,Sparse>::MatrixTypeReverseIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryOpImpl& unaryOp, typename CwiseUnaryOpImpl::Index outer)
+      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
+    {}
+
+    EIGEN_STRONG_INLINE ReverseInnerIterator& operator--()
+    { Base::operator--(); return *this; }
+
+    EIGEN_STRONG_INLINE typename CwiseUnaryOpImpl::Scalar value() const { return m_functor(Base::value()); }
+
+  protected:
+    const UnaryOp m_functor;
+  private:
+    typename CwiseUnaryOpImpl::Scalar& valueRef();
+};
+
+template<typename ViewOp, typename MatrixType>
+class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>
+  : public SparseMatrixBase<CwiseUnaryView<ViewOp, MatrixType> >
+{
+  public:
+
+    class InnerIterator;
+    class ReverseInnerIterator;
+
+    typedef CwiseUnaryView<ViewOp, MatrixType> Derived;
+    EIGEN_SPARSE_PUBLIC_INTERFACE(Derived)
+
+  protected:
+    typedef typename internal::traits<Derived>::_MatrixTypeNested _MatrixTypeNested;
+    typedef typename _MatrixTypeNested::InnerIterator MatrixTypeIterator;
+    typedef typename _MatrixTypeNested::ReverseInnerIterator MatrixTypeReverseIterator;
+};
+
+template<typename ViewOp, typename MatrixType>
+class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::InnerIterator
+    : public CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeIterator
+{
+    typedef typename CwiseUnaryViewImpl::Scalar Scalar;
+    typedef typename CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer)
+      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
+    {}
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    { Base::operator++(); return *this; }
+
+    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); }
+    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); }
+
+  protected:
+    const ViewOp m_functor;
+};
+
+template<typename ViewOp, typename MatrixType>
+class CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::ReverseInnerIterator
+    : public CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeReverseIterator
+{
+    typedef typename CwiseUnaryViewImpl::Scalar Scalar;
+    typedef typename CwiseUnaryViewImpl<ViewOp,MatrixType,Sparse>::MatrixTypeReverseIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE ReverseInnerIterator(const CwiseUnaryViewImpl& unaryOp, typename CwiseUnaryViewImpl::Index outer)
+      : Base(unaryOp.derived().nestedExpression(),outer), m_functor(unaryOp.derived().functor())
+    {}
+
+    EIGEN_STRONG_INLINE ReverseInnerIterator& operator--()
+    { Base::operator--(); return *this; }
+
+    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar value() const { return m_functor(Base::value()); }
+    EIGEN_STRONG_INLINE typename CwiseUnaryViewImpl::Scalar& valueRef() { return m_functor(Base::valueRef()); }
+
+  protected:
+    const ViewOp m_functor;
+};
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+SparseMatrixBase<Derived>::operator*=(const Scalar& other)
+{
+  for (Index j=0; j<outerSize(); ++j)
+    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
+      i.valueRef() *= other;
+  return derived();
+}
+
+template<typename Derived>
+EIGEN_STRONG_INLINE Derived&
+SparseMatrixBase<Derived>::operator/=(const Scalar& other)
+{
+  for (Index j=0; j<outerSize(); ++j)
+    for (typename Derived::InnerIterator i(derived(),j); i; ++i)
+      i.valueRef() /= other;
+  return derived();
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_CWISE_UNARY_OP_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseDenseProduct.h b/extern/Eigen3/Eigen/src/SparseCore/SparseDenseProduct.h
index 0f77aa5be99..6f32940d6c1 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseDenseProduct.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseDenseProduct.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSEDENSEPRODUCT_H
 #define EIGEN_SPARSEDENSEPRODUCT_H
 
+namespace Eigen { 
+
 template<typename Lhs, typename Rhs, int InnerSize> struct SparseDenseProductReturnType
 {
   typedef SparseTimeDenseProduct<Lhs,Rhs> Type;
@@ -149,6 +136,102 @@ struct traits<SparseTimeDenseProduct<Lhs,Rhs> >
   typedef Dense StorageKind;
   typedef MatrixXpr XprKind;
 };
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType,
+         int LhsStorageOrder = ((SparseLhsType::Flags&RowMajorBit)==RowMajorBit) ? RowMajor : ColMajor,
+         bool ColPerCol = ((DenseRhsType::Flags&RowMajorBit)==0) || DenseRhsType::ColsAtCompileTime==1>
+struct sparse_time_dense_product_impl;
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, RowMajor, true>
+{
+  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
+  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
+  typedef typename internal::remove_all<DenseResType>::type Res;
+  typedef typename Lhs::Index Index;
+  typedef typename Lhs::InnerIterator LhsInnerIterator;
+  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+  {
+    for(Index c=0; c<rhs.cols(); ++c)
+    {
+      int n = lhs.outerSize();
+      for(Index j=0; j<n; ++j)
+      {
+        typename Res::Scalar tmp(0);
+        for(LhsInnerIterator it(lhs,j); it ;++it)
+          tmp += it.value() * rhs.coeff(it.index(),c);
+        res.coeffRef(j,c) = alpha * tmp;
+      }
+    }
+  }
+};
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, ColMajor, true>
+{
+  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
+  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
+  typedef typename internal::remove_all<DenseResType>::type Res;
+  typedef typename Lhs::InnerIterator LhsInnerIterator;
+  typedef typename Lhs::Index Index;
+  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+  {
+    for(Index c=0; c<rhs.cols(); ++c)
+    {
+      for(Index j=0; j<lhs.outerSize(); ++j)
+      {
+        typename Res::Scalar rhs_j = alpha * rhs.coeff(j,c);
+        for(LhsInnerIterator it(lhs,j); it ;++it)
+          res.coeffRef(it.index(),c) += it.value() * rhs_j;
+      }
+    }
+  }
+};
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, RowMajor, false>
+{
+  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
+  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
+  typedef typename internal::remove_all<DenseResType>::type Res;
+  typedef typename Lhs::InnerIterator LhsInnerIterator;
+  typedef typename Lhs::Index Index;
+  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+  {
+    for(Index j=0; j<lhs.outerSize(); ++j)
+    {
+      typename Res::RowXpr res_j(res.row(j));
+      for(LhsInnerIterator it(lhs,j); it ;++it)
+        res_j += (alpha*it.value()) * rhs.row(it.index());
+    }
+  }
+};
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType>
+struct sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType, ColMajor, false>
+{
+  typedef typename internal::remove_all<SparseLhsType>::type Lhs;
+  typedef typename internal::remove_all<DenseRhsType>::type Rhs;
+  typedef typename internal::remove_all<DenseResType>::type Res;
+  typedef typename Lhs::InnerIterator LhsInnerIterator;
+  typedef typename Lhs::Index Index;
+  static void run(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, typename Res::Scalar alpha)
+  {
+    for(Index j=0; j<lhs.outerSize(); ++j)
+    {
+      typename Rhs::ConstRowXpr rhs_j(rhs.row(j));
+      for(LhsInnerIterator it(lhs,j); it ;++it)
+        res.row(it.index()) += (alpha*it.value()) * rhs_j;
+    }
+  }
+};
+
+template<typename SparseLhsType, typename DenseRhsType, typename DenseResType,typename AlphaType>
+inline void sparse_time_dense_product(const SparseLhsType& lhs, const DenseRhsType& rhs, DenseResType& res, const AlphaType& alpha)
+{
+  sparse_time_dense_product_impl<SparseLhsType,DenseRhsType,DenseResType>::run(lhs, rhs, res, alpha);
+}
+
 } // end namespace internal
 
 template<typename Lhs, typename Rhs>
@@ -163,21 +246,7 @@ class SparseTimeDenseProduct
 
     template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
     {
-      typedef typename internal::remove_all<Lhs>::type _Lhs;
-      typedef typename internal::remove_all<Rhs>::type _Rhs;
-      typedef typename _Lhs::InnerIterator LhsInnerIterator;
-      enum { LhsIsRowMajor = (_Lhs::Flags&RowMajorBit)==RowMajorBit };
-      for(Index j=0; j<m_lhs.outerSize(); ++j)
-      {
-        typename Rhs::Scalar rhs_j = alpha * m_rhs.coeff(LhsIsRowMajor ? 0 : j,0);
-        typename Dest::RowXpr dest_j(dest.row(LhsIsRowMajor ? j : 0));
-        for(LhsInnerIterator it(m_lhs,j); it ;++it)
-        {
-          if(LhsIsRowMajor)                   dest_j += (alpha*it.value()) * m_rhs.row(it.index());
-          else if(Rhs::ColsAtCompileTime==1)  dest.coeffRef(it.index()) += it.value() * rhs_j;
-          else                                dest.row(it.index()) += (alpha*it.value()) * m_rhs.row(j);
-        }
-      }
+      internal::sparse_time_dense_product(m_lhs, m_rhs, dest, alpha);
     }
 
   private:
@@ -207,12 +276,10 @@ class DenseTimeSparseProduct
 
     template<typename Dest> void scaleAndAddTo(Dest& dest, Scalar alpha) const
     {
-      typedef typename internal::remove_all<Rhs>::type _Rhs;
-      typedef typename _Rhs::InnerIterator RhsInnerIterator;
-      enum { RhsIsRowMajor = (_Rhs::Flags&RowMajorBit)==RowMajorBit };
-      for(Index j=0; j<m_rhs.outerSize(); ++j)
-        for(RhsInnerIterator i(m_rhs,j); i; ++i)
-          dest.col(RhsIsRowMajor ? i.index() : j) += (alpha*i.value()) * m_lhs.col(RhsIsRowMajor ? j : i.index());
+      Transpose<const _LhsNested> lhs_t(m_lhs);
+      Transpose<const _RhsNested> rhs_t(m_rhs);
+      Transpose<Dest> dest_t(dest);
+      internal::sparse_time_dense_product(rhs_t, lhs_t, dest_t, alpha);
     }
 
   private:
@@ -228,4 +295,6 @@ SparseMatrixBase<Derived>::operator*(const MatrixBase<OtherDerived> &other) cons
   return typename SparseDenseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSEDENSEPRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseDiagonalProduct.h b/extern/Eigen3/Eigen/src/SparseCore/SparseDiagonalProduct.h
index fb9a29c051b..095bf6863fc 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseDiagonalProduct.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseDiagonalProduct.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_DIAGONAL_PRODUCT_H
 #define EIGEN_SPARSE_DIAGONAL_PRODUCT_H
 
+namespace Eigen { 
+
 // The product of a diagonal matrix with a sparse matrix can be easily
 // implemented using expression template.
 // We have two consider very different cases:
@@ -192,4 +179,6 @@ SparseMatrixBase<Derived>::operator*(const DiagonalBase<OtherDerived> &other) co
   return SparseDiagonalProduct<Derived,OtherDerived>(this->derived(), other.derived());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSE_DIAGONAL_PRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseDot.h b/extern/Eigen3/Eigen/src/SparseCore/SparseDot.h
index 1f10f71a402..5c4a593dc01 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseDot.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseDot.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_DOT_H
 #define EIGEN_SPARSE_DOT_H
 
+namespace Eigen { 
+
 template<typename Derived>
 template<typename OtherDerived>
 typename internal::traits<Derived>::Scalar
@@ -40,7 +27,7 @@ SparseMatrixBase<Derived>::dot(const MatrixBase<OtherDerived>& other) const
   eigen_assert(other.size()>0 && "you are using a non initialized vector");
 
   typename Derived::InnerIterator i(derived(),0);
-  Scalar res = 0;
+  Scalar res(0);
   while (i)
   {
     res += internal::conj(i.value()) * other.coeff(i.index());
@@ -62,9 +49,17 @@ SparseMatrixBase<Derived>::dot(const SparseMatrixBase<OtherDerived>& other) cons
 
   eigen_assert(size() == other.size());
 
-  typename Derived::InnerIterator i(derived(),0);
-  typename OtherDerived::InnerIterator j(other.derived(),0);
-  Scalar res = 0;
+  typedef typename Derived::Nested  Nested;
+  typedef typename OtherDerived::Nested  OtherNested;
+  typedef typename internal::remove_all<Nested>::type  NestedCleaned;
+  typedef typename internal::remove_all<OtherNested>::type  OtherNestedCleaned;
+
+  const Nested nthis(derived());
+  const OtherNested nother(other.derived());
+
+  typename NestedCleaned::InnerIterator i(nthis,0);
+  typename OtherNestedCleaned::InnerIterator j(nother,0);
+  Scalar res(0);
   while (i && j)
   {
     if (i.index()==j.index())
@@ -94,4 +89,6 @@ SparseMatrixBase<Derived>::norm() const
   return internal::sqrt(squaredNorm());
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSE_DOT_H
diff --git a/extern/Eigen3/Eigen/src/SparseCore/SparseFuzzy.h b/extern/Eigen3/Eigen/src/SparseCore/SparseFuzzy.h
new file mode 100644
index 00000000000..45f36e9eb90
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseFuzzy.h
@@ -0,0 +1,26 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_FUZZY_H
+#define EIGEN_SPARSE_FUZZY_H
+
+// template<typename Derived>
+// template<typename OtherDerived>
+// bool SparseMatrixBase<Derived>::isApprox(
+//   const OtherDerived& other,
+//   typename NumTraits<Scalar>::Real prec
+// ) const
+// {
+//   const typename internal::nested<Derived,2>::type nested(derived());
+//   const typename internal::nested<OtherDerived,2>::type otherNested(other.derived());
+//   return    (nested - otherNested).cwise().abs2().sum()
+//          <= prec * prec * (std::min)(nested.cwise().abs2().sum(), otherNested.cwise().abs2().sum());
+// }
+
+#endif // EIGEN_SPARSE_FUZZY_H
diff --git a/extern/Eigen3/Eigen/src/SparseCore/SparseMatrix.h b/extern/Eigen3/Eigen/src/SparseCore/SparseMatrix.h
new file mode 100644
index 00000000000..efb774f031b
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseMatrix.h
@@ -0,0 +1,1116 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSEMATRIX_H
+#define EIGEN_SPARSEMATRIX_H
+
+namespace Eigen { 
+
+/** \ingroup SparseCore_Module
+  *
+  * \class SparseMatrix
+  *
+  * \brief A versatible sparse matrix representation
+  *
+  * This class implements a more versatile variants of the common \em compressed row/column storage format.
+  * Each colmun's (resp. row) non zeros are stored as a pair of value with associated row (resp. colmiun) index.
+  * All the non zeros are stored in a single large buffer. Unlike the \em compressed format, there might be extra
+  * space inbetween the nonzeros of two successive colmuns (resp. rows) such that insertion of new non-zero
+  * can be done with limited memory reallocation and copies.
+  *
+  * A call to the function makeCompressed() turns the matrix into the standard \em compressed format
+  * compatible with many library.
+  *
+  * More details on this storage sceheme are given in the \ref TutorialSparse "manual pages".
+  *
+  * \tparam _Scalar the scalar type, i.e. the type of the coefficients
+  * \tparam _Options Union of bit flags controlling the storage scheme. Currently the only possibility
+  *                 is RowMajor. The default is 0 which means column-major.
+  * \tparam _Index the type of the indices. It has to be a \b signed type (e.g., short, int, std::ptrdiff_t). Default is \c int.
+  *
+  * This class can be extended with the help of the plugin mechanism described on the page
+  * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_SPARSEMATRIX_PLUGIN.
+  */
+
+namespace internal {
+template<typename _Scalar, int _Options, typename _Index>
+struct traits<SparseMatrix<_Scalar, _Options, _Index> >
+{
+  typedef _Scalar Scalar;
+  typedef _Index Index;
+  typedef Sparse StorageKind;
+  typedef MatrixXpr XprKind;
+  enum {
+    RowsAtCompileTime = Dynamic,
+    ColsAtCompileTime = Dynamic,
+    MaxRowsAtCompileTime = Dynamic,
+    MaxColsAtCompileTime = Dynamic,
+    Flags = _Options | NestByRefBit | LvalueBit,
+    CoeffReadCost = NumTraits<Scalar>::ReadCost,
+    SupportedAccessPatterns = InnerRandomAccessPattern
+  };
+};
+
+template<typename _Scalar, int _Options, typename _Index, int DiagIndex>
+struct traits<Diagonal<const SparseMatrix<_Scalar, _Options, _Index>, DiagIndex> >
+{
+  typedef SparseMatrix<_Scalar, _Options, _Index> MatrixType;
+  typedef typename nested<MatrixType>::type MatrixTypeNested;
+  typedef typename remove_reference<MatrixTypeNested>::type _MatrixTypeNested;
+
+  typedef _Scalar Scalar;
+  typedef Dense StorageKind;
+  typedef _Index Index;
+  typedef MatrixXpr XprKind;
+
+  enum {
+    RowsAtCompileTime = Dynamic,
+    ColsAtCompileTime = 1,
+    MaxRowsAtCompileTime = Dynamic,
+    MaxColsAtCompileTime = 1,
+    Flags = 0,
+    CoeffReadCost = _MatrixTypeNested::CoeffReadCost*10
+  };
+};
+
+} // end namespace internal
+
+template<typename _Scalar, int _Options, typename _Index>
+class SparseMatrix
+  : public SparseMatrixBase<SparseMatrix<_Scalar, _Options, _Index> >
+{
+  public:
+    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseMatrix)
+    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, +=)
+    EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseMatrix, -=)
+
+    typedef MappedSparseMatrix<Scalar,Flags> Map;
+    using Base::IsRowMajor;
+    typedef internal::CompressedStorage<Scalar,Index> Storage;
+    enum {
+      Options = _Options
+    };
+
+  protected:
+
+    typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
+
+    Index m_outerSize;
+    Index m_innerSize;
+    Index* m_outerIndex;
+    Index* m_innerNonZeros;     // optional, if null then the data is compressed
+    Storage m_data;
+    
+    Eigen::Map<Matrix<Index,Dynamic,1> > innerNonZeros() { return Eigen::Map<Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); }
+    const  Eigen::Map<const Matrix<Index,Dynamic,1> > innerNonZeros() const { return Eigen::Map<const Matrix<Index,Dynamic,1> >(m_innerNonZeros, m_innerNonZeros?m_outerSize:0); }
+
+  public:
+    
+    /** \returns whether \c *this is in compressed form. */
+    inline bool isCompressed() const { return m_innerNonZeros==0; }
+
+    /** \returns the number of rows of the matrix */
+    inline Index rows() const { return IsRowMajor ? m_outerSize : m_innerSize; }
+    /** \returns the number of columns of the matrix */
+    inline Index cols() const { return IsRowMajor ? m_innerSize : m_outerSize; }
+
+    /** \returns the number of rows (resp. columns) of the matrix if the storage order column major (resp. row major) */
+    inline Index innerSize() const { return m_innerSize; }
+    /** \returns the number of columns (resp. rows) of the matrix if the storage order column major (resp. row major) */
+    inline Index outerSize() const { return m_outerSize; }
+    
+    /** \returns a const pointer to the array of values.
+      * This function is aimed at interoperability with other libraries.
+      * \sa innerIndexPtr(), outerIndexPtr() */
+    inline const Scalar* valuePtr() const { return &m_data.value(0); }
+    /** \returns a non-const pointer to the array of values.
+      * This function is aimed at interoperability with other libraries.
+      * \sa innerIndexPtr(), outerIndexPtr() */
+    inline Scalar* valuePtr() { return &m_data.value(0); }
+
+    /** \returns a const pointer to the array of inner indices.
+      * This function is aimed at interoperability with other libraries.
+      * \sa valuePtr(), outerIndexPtr() */
+    inline const Index* innerIndexPtr() const { return &m_data.index(0); }
+    /** \returns a non-const pointer to the array of inner indices.
+      * This function is aimed at interoperability with other libraries.
+      * \sa valuePtr(), outerIndexPtr() */
+    inline Index* innerIndexPtr() { return &m_data.index(0); }
+
+    /** \returns a const pointer to the array of the starting positions of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \sa valuePtr(), innerIndexPtr() */
+    inline const Index* outerIndexPtr() const { return m_outerIndex; }
+    /** \returns a non-const pointer to the array of the starting positions of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \sa valuePtr(), innerIndexPtr() */
+    inline Index* outerIndexPtr() { return m_outerIndex; }
+
+    /** \returns a const pointer to the array of the number of non zeros of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \warning it returns the null pointer 0 in compressed mode */
+    inline const Index* innerNonZeroPtr() const { return m_innerNonZeros; }
+    /** \returns a non-const pointer to the array of the number of non zeros of the inner vectors.
+      * This function is aimed at interoperability with other libraries.
+      * \warning it returns the null pointer 0 in compressed mode */
+    inline Index* innerNonZeroPtr() { return m_innerNonZeros; }
+
+    /** \internal */
+    inline Storage& data() { return m_data; }
+    /** \internal */
+    inline const Storage& data() const { return m_data; }
+
+    /** \returns the value of the matrix at position \a i, \a j
+      * This function returns Scalar(0) if the element is an explicit \em zero */
+    inline Scalar coeff(Index row, Index col) const
+    {
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
+      Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1];
+      return m_data.atInRange(m_outerIndex[outer], end, inner);
+    }
+
+    /** \returns a non-const reference to the value of the matrix at position \a i, \a j
+      *
+      * If the element does not exist then it is inserted via the insert(Index,Index) function
+      * which itself turns the matrix into a non compressed form if that was not the case.
+      *
+      * This is a O(log(nnz_j)) operation (binary search) plus the cost of insert(Index,Index)
+      * function if the element does not already exist.
+      */
+    inline Scalar& coeffRef(Index row, Index col)
+    {
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
+
+      Index start = m_outerIndex[outer];
+      Index end = m_innerNonZeros ? m_outerIndex[outer] + m_innerNonZeros[outer] : m_outerIndex[outer+1];
+      eigen_assert(end>=start && "you probably called coeffRef on a non finalized matrix");
+      if(end<=start)
+        return insert(row,col);
+      const Index p = m_data.searchLowerIndex(start,end-1,inner);
+      if((p<end) && (m_data.index(p)==inner))
+        return m_data.value(p);
+      else
+        return insert(row,col);
+    }
+
+    /** \returns a reference to a novel non zero coefficient with coordinates \a row x \a col.
+      * The non zero coefficient must \b not already exist.
+      *
+      * If the matrix \c *this is in compressed mode, then \c *this is turned into uncompressed
+      * mode while reserving room for 2 non zeros per inner vector. It is strongly recommended to first
+      * call reserve(const SizesType &) to reserve a more appropriate number of elements per
+      * inner vector that better match your scenario.
+      *
+      * This function performs a sorted insertion in O(1) if the elements of each inner vector are
+      * inserted in increasing inner index order, and in O(nnz_j) for a random insertion.
+      *
+      */
+    EIGEN_DONT_INLINE Scalar& insert(Index row, Index col)
+    {
+      if(isCompressed())
+      {
+        reserve(VectorXi::Constant(outerSize(), 2));
+      }
+      return insertUncompressed(row,col);
+    }
+
+  public:
+
+    class InnerIterator;
+    class ReverseInnerIterator;
+
+    /** Removes all non zeros but keep allocated memory */
+    inline void setZero()
+    {
+      m_data.clear();
+      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
+      if(m_innerNonZeros)
+        memset(m_innerNonZeros, 0, (m_outerSize)*sizeof(Index));
+    }
+
+    /** \returns the number of non zero coefficients */
+    inline Index nonZeros() const
+    {
+      if(m_innerNonZeros)
+        return innerNonZeros().sum();
+      return static_cast<Index>(m_data.size());
+    }
+
+    /** Preallocates \a reserveSize non zeros.
+      *
+      * Precondition: the matrix must be in compressed mode. */
+    inline void reserve(Index reserveSize)
+    {
+      eigen_assert(isCompressed() && "This function does not make sense in non compressed mode.");
+      m_data.reserve(reserveSize);
+    }
+    
+    #ifdef EIGEN_PARSED_BY_DOXYGEN
+    /** Preallocates \a reserveSize[\c j] non zeros for each column (resp. row) \c j.
+      *
+      * This function turns the matrix in non-compressed mode */
+    template<class SizesType>
+    inline void reserve(const SizesType& reserveSizes);
+    #else
+    template<class SizesType>
+    inline void reserve(const SizesType& reserveSizes, const typename SizesType::value_type& enableif = typename SizesType::value_type())
+    {
+      EIGEN_UNUSED_VARIABLE(enableif);
+      reserveInnerVectors(reserveSizes);
+    }
+    template<class SizesType>
+    inline void reserve(const SizesType& reserveSizes, const typename SizesType::Scalar& enableif =
+    #if (!defined(_MSC_VER)) || (_MSC_VER>=1500) // MSVC 2005 fails to compile with this typename
+        typename
+    #endif
+        SizesType::Scalar())
+    {
+      EIGEN_UNUSED_VARIABLE(enableif);
+      reserveInnerVectors(reserveSizes);
+    }
+    #endif // EIGEN_PARSED_BY_DOXYGEN
+  protected:
+    template<class SizesType>
+    inline void reserveInnerVectors(const SizesType& reserveSizes)
+    {
+      
+      if(isCompressed())
+      {
+        std::size_t totalReserveSize = 0;
+        // turn the matrix into non-compressed mode
+        m_innerNonZeros = new Index[m_outerSize];
+        
+        // temporarily use m_innerSizes to hold the new starting points.
+        Index* newOuterIndex = m_innerNonZeros;
+        
+        Index count = 0;
+        for(Index j=0; j<m_outerSize; ++j)
+        {
+          newOuterIndex[j] = count;
+          count += reserveSizes[j] + (m_outerIndex[j+1]-m_outerIndex[j]);
+          totalReserveSize += reserveSizes[j];
+        }
+        m_data.reserve(totalReserveSize);
+        std::ptrdiff_t previousOuterIndex = m_outerIndex[m_outerSize];
+        for(std::ptrdiff_t j=m_outerSize-1; j>=0; --j)
+        {
+          ptrdiff_t innerNNZ = previousOuterIndex - m_outerIndex[j];
+          for(std::ptrdiff_t i=innerNNZ-1; i>=0; --i)
+          {
+            m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i);
+            m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i);
+          }
+          previousOuterIndex = m_outerIndex[j];
+          m_outerIndex[j] = newOuterIndex[j];
+          m_innerNonZeros[j] = innerNNZ;
+        }
+        m_outerIndex[m_outerSize] = m_outerIndex[m_outerSize-1] + m_innerNonZeros[m_outerSize-1] + reserveSizes[m_outerSize-1];
+        
+        m_data.resize(m_outerIndex[m_outerSize]);
+      }
+      else
+      {
+        Index* newOuterIndex = new Index[m_outerSize+1];
+        Index count = 0;
+        for(Index j=0; j<m_outerSize; ++j)
+        {
+          newOuterIndex[j] = count;
+          Index alreadyReserved = (m_outerIndex[j+1]-m_outerIndex[j]) - m_innerNonZeros[j];
+          Index toReserve = std::max<std::ptrdiff_t>(reserveSizes[j], alreadyReserved);
+          count += toReserve + m_innerNonZeros[j];
+        }
+        newOuterIndex[m_outerSize] = count;
+        
+        m_data.resize(count);
+        for(ptrdiff_t j=m_outerSize-1; j>=0; --j)
+        {
+          std::ptrdiff_t offset = newOuterIndex[j] - m_outerIndex[j];
+          if(offset>0)
+          {
+            std::ptrdiff_t innerNNZ = m_innerNonZeros[j];
+            for(std::ptrdiff_t i=innerNNZ-1; i>=0; --i)
+            {
+              m_data.index(newOuterIndex[j]+i) = m_data.index(m_outerIndex[j]+i);
+              m_data.value(newOuterIndex[j]+i) = m_data.value(m_outerIndex[j]+i);
+            }
+          }
+        }
+        
+        std::swap(m_outerIndex, newOuterIndex);
+        delete[] newOuterIndex;
+      }
+      
+    }
+  public:
+
+    //--- low level purely coherent filling ---
+
+    /** \internal
+      * \returns a reference to the non zero coefficient at position \a row, \a col assuming that:
+      * - the nonzero does not already exist
+      * - the new coefficient is the last one according to the storage order
+      *
+      * Before filling a given inner vector you must call the statVec(Index) function.
+      *
+      * After an insertion session, you should call the finalize() function.
+      *
+      * \sa insert, insertBackByOuterInner, startVec */
+    inline Scalar& insertBack(Index row, Index col)
+    {
+      return insertBackByOuterInner(IsRowMajor?row:col, IsRowMajor?col:row);
+    }
+
+    /** \internal
+      * \sa insertBack, startVec */
+    inline Scalar& insertBackByOuterInner(Index outer, Index inner)
+    {
+      eigen_assert(size_t(m_outerIndex[outer+1]) == m_data.size() && "Invalid ordered insertion (invalid outer index)");
+      eigen_assert( (m_outerIndex[outer+1]-m_outerIndex[outer]==0 || m_data.index(m_data.size()-1)<inner) && "Invalid ordered insertion (invalid inner index)");
+      Index p = m_outerIndex[outer+1];
+      ++m_outerIndex[outer+1];
+      m_data.append(0, inner);
+      return m_data.value(p);
+    }
+
+    /** \internal
+      * \warning use it only if you know what you are doing */
+    inline Scalar& insertBackByOuterInnerUnordered(Index outer, Index inner)
+    {
+      Index p = m_outerIndex[outer+1];
+      ++m_outerIndex[outer+1];
+      m_data.append(0, inner);
+      return m_data.value(p);
+    }
+
+    /** \internal
+      * \sa insertBack, insertBackByOuterInner */
+    inline void startVec(Index outer)
+    {
+      eigen_assert(m_outerIndex[outer]==int(m_data.size()) && "You must call startVec for each inner vector sequentially");
+      eigen_assert(m_outerIndex[outer+1]==0 && "You must call startVec for each inner vector sequentially");
+      m_outerIndex[outer+1] = m_outerIndex[outer];
+    }
+
+    /** \internal
+      * Must be called after inserting a set of non zero entries using the low level compressed API.
+      */
+    inline void finalize()
+    {
+      if(isCompressed())
+      {
+        Index size = static_cast<Index>(m_data.size());
+        Index i = m_outerSize;
+        // find the last filled column
+        while (i>=0 && m_outerIndex[i]==0)
+          --i;
+        ++i;
+        while (i<=m_outerSize)
+        {
+          m_outerIndex[i] = size;
+          ++i;
+        }
+      }
+    }
+
+    //---
+
+    template<typename InputIterators>
+    void setFromTriplets(const InputIterators& begin, const InputIterators& end);
+
+    void sumupDuplicates();
+
+    //---
+    
+    /** \internal
+      * same as insert(Index,Index) except that the indices are given relative to the storage order */
+    EIGEN_DONT_INLINE Scalar& insertByOuterInner(Index j, Index i)
+    {
+      return insert(IsRowMajor ? j : i, IsRowMajor ? i : j);
+    }
+
+    /** Turns the matrix into the \em compressed format.
+      */
+    void makeCompressed()
+    {
+      if(isCompressed())
+        return;
+      
+      Index oldStart = m_outerIndex[1];
+      m_outerIndex[1] = m_innerNonZeros[0];
+      for(Index j=1; j<m_outerSize; ++j)
+      {
+        Index nextOldStart = m_outerIndex[j+1];
+        std::ptrdiff_t offset = oldStart - m_outerIndex[j];
+        if(offset>0)
+        {
+          for(Index k=0; k<m_innerNonZeros[j]; ++k)
+          {
+            m_data.index(m_outerIndex[j]+k) = m_data.index(oldStart+k);
+            m_data.value(m_outerIndex[j]+k) = m_data.value(oldStart+k);
+          }
+        }
+        m_outerIndex[j+1] = m_outerIndex[j] + m_innerNonZeros[j];
+        oldStart = nextOldStart;
+      }
+      delete[] m_innerNonZeros;
+      m_innerNonZeros = 0;
+      m_data.resize(m_outerIndex[m_outerSize]);
+      m_data.squeeze();
+    }
+
+    /** Suppresses all nonzeros which are \b much \b smaller \b than \a reference under the tolerence \a epsilon */
+    void prune(Scalar reference, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision())
+    {
+      prune(default_prunning_func(reference,epsilon));
+    }
+    
+    /** Turns the matrix into compressed format, and suppresses all nonzeros which do not satisfy the predicate \a keep.
+      * The functor type \a KeepFunc must implement the following function:
+      * \code
+      * bool operator() (const Index& row, const Index& col, const Scalar& value) const;
+      * \endcode
+      * \sa prune(Scalar,RealScalar)
+      */
+    template<typename KeepFunc>
+    void prune(const KeepFunc& keep = KeepFunc())
+    {
+      // TODO optimize the uncompressed mode to avoid moving and allocating the data twice
+      // TODO also implement a unit test
+      makeCompressed();
+
+      Index k = 0;
+      for(Index j=0; j<m_outerSize; ++j)
+      {
+        Index previousStart = m_outerIndex[j];
+        m_outerIndex[j] = k;
+        Index end = m_outerIndex[j+1];
+        for(Index i=previousStart; i<end; ++i)
+        {
+          if(keep(IsRowMajor?j:m_data.index(i), IsRowMajor?m_data.index(i):j, m_data.value(i)))
+          {
+            m_data.value(k) = m_data.value(i);
+            m_data.index(k) = m_data.index(i);
+            ++k;
+          }
+        }
+      }
+      m_outerIndex[m_outerSize] = k;
+      m_data.resize(k,0);
+    }
+
+    /** Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero.
+      * \sa resizeNonZeros(Index), reserve(), setZero()
+      */
+    void resize(Index rows, Index cols)
+    {
+      const Index outerSize = IsRowMajor ? rows : cols;
+      m_innerSize = IsRowMajor ? cols : rows;
+      m_data.clear();
+      if (m_outerSize != outerSize || m_outerSize==0)
+      {
+        delete[] m_outerIndex;
+        m_outerIndex = new Index [outerSize+1];
+        m_outerSize = outerSize;
+      }
+      if(m_innerNonZeros)
+      {
+        delete[] m_innerNonZeros;
+        m_innerNonZeros = 0;
+      }
+      memset(m_outerIndex, 0, (m_outerSize+1)*sizeof(Index));
+    }
+
+    /** \internal
+      * Resize the nonzero vector to \a size */
+    void resizeNonZeros(Index size)
+    {
+      // TODO remove this function
+      m_data.resize(size);
+    }
+
+    /** \returns a const expression of the diagonal coefficients */
+    const Diagonal<const SparseMatrix> diagonal() const { return *this; }
+
+    /** Default constructor yielding an empty \c 0 \c x \c 0 matrix */
+    inline SparseMatrix()
+      : m_outerSize(-1), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
+    {
+      check_template_parameters();
+      resize(0, 0);
+    }
+
+    /** Constructs a \a rows \c x \a cols empty matrix */
+    inline SparseMatrix(Index rows, Index cols)
+      : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
+    {
+      check_template_parameters();
+      resize(rows, cols);
+    }
+
+    /** Constructs a sparse matrix from the sparse expression \a other */
+    template<typename OtherDerived>
+    inline SparseMatrix(const SparseMatrixBase<OtherDerived>& other)
+      : m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
+    {
+      check_template_parameters();
+      *this = other.derived();
+    }
+
+    /** Copy constructor (it performs a deep copy) */
+    inline SparseMatrix(const SparseMatrix& other)
+      : Base(), m_outerSize(0), m_innerSize(0), m_outerIndex(0), m_innerNonZeros(0)
+    {
+      check_template_parameters();
+      *this = other.derived();
+    }
+
+    /** Swaps the content of two sparse matrices of the same type.
+      * This is a fast operation that simply swaps the underlying pointers and parameters. */
+    inline void swap(SparseMatrix& other)
+    {
+      //EIGEN_DBG_SPARSE(std::cout << "SparseMatrix:: swap\n");
+      std::swap(m_outerIndex, other.m_outerIndex);
+      std::swap(m_innerSize, other.m_innerSize);
+      std::swap(m_outerSize, other.m_outerSize);
+      std::swap(m_innerNonZeros, other.m_innerNonZeros);
+      m_data.swap(other.m_data);
+    }
+
+    inline SparseMatrix& operator=(const SparseMatrix& other)
+    {
+      if (other.isRValue())
+      {
+        swap(other.const_cast_derived());
+      }
+      else
+      {
+        initAssignment(other);
+        if(other.isCompressed())
+        {
+          memcpy(m_outerIndex, other.m_outerIndex, (m_outerSize+1)*sizeof(Index));
+          m_data = other.m_data;
+        }
+        else
+        {
+          Base::operator=(other);
+        }
+      }
+      return *this;
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    template<typename Lhs, typename Rhs>
+    inline SparseMatrix& operator=(const SparseSparseProduct<Lhs,Rhs>& product)
+    { return Base::operator=(product); }
+    
+    template<typename OtherDerived>
+    inline SparseMatrix& operator=(const ReturnByValue<OtherDerived>& other)
+    { return Base::operator=(other.derived()); }
+    
+    template<typename OtherDerived>
+    inline SparseMatrix& operator=(const EigenBase<OtherDerived>& other)
+    { return Base::operator=(other.derived()); }
+    #endif
+
+    template<typename OtherDerived>
+    EIGEN_DONT_INLINE SparseMatrix& operator=(const SparseMatrixBase<OtherDerived>& other)
+    {
+      initAssignment(other.derived());
+      const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
+      if (needToTranspose)
+      {
+        // two passes algorithm:
+        //  1 - compute the number of coeffs per dest inner vector
+        //  2 - do the actual copy/eval
+        // Since each coeff of the rhs has to be evaluated twice, let's evaluate it if needed
+        typedef typename internal::nested<OtherDerived,2>::type OtherCopy;
+        typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
+        OtherCopy otherCopy(other.derived());
+
+        Eigen::Map<Matrix<Index, Dynamic, 1> > (m_outerIndex,outerSize()).setZero();
+        // pass 1
+        // FIXME the above copy could be merged with that pass
+        for (Index j=0; j<otherCopy.outerSize(); ++j)
+          for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
+            ++m_outerIndex[it.index()];
+
+        // prefix sum
+        Index count = 0;
+        VectorXi positions(outerSize());
+        for (Index j=0; j<outerSize(); ++j)
+        {
+          Index tmp = m_outerIndex[j];
+          m_outerIndex[j] = count;
+          positions[j] = count;
+          count += tmp;
+        }
+        m_outerIndex[outerSize()] = count;
+        // alloc
+        m_data.resize(count);
+        // pass 2
+        for (Index j=0; j<otherCopy.outerSize(); ++j)
+        {
+          for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
+          {
+            Index pos = positions[it.index()]++;
+            m_data.index(pos) = j;
+            m_data.value(pos) = it.value();
+          }
+        }
+        return *this;
+      }
+      else
+      {
+        // there is no special optimization
+        return Base::operator=(other.derived());
+      }
+    }
+
+    friend std::ostream & operator << (std::ostream & s, const SparseMatrix& m)
+    {
+      EIGEN_DBG_SPARSE(
+        s << "Nonzero entries:\n";
+        if(m.isCompressed())
+          for (Index i=0; i<m.nonZeros(); ++i)
+            s << "(" << m.m_data.value(i) << "," << m.m_data.index(i) << ") ";
+        else
+          for (Index i=0; i<m.outerSize(); ++i)
+          {
+            int p = m.m_outerIndex[i];
+            int pe = m.m_outerIndex[i]+m.m_innerNonZeros[i];
+            Index k=p;
+            for (; k<pe; ++k)
+              s << "(" << m.m_data.value(k) << "," << m.m_data.index(k) << ") ";
+            for (; k<m.m_outerIndex[i+1]; ++k)
+              s << "(_,_) ";
+          }
+        s << std::endl;
+        s << std::endl;
+        s << "Outer pointers:\n";
+        for (Index i=0; i<m.outerSize(); ++i)
+          s << m.m_outerIndex[i] << " ";
+        s << " $" << std::endl;
+        if(!m.isCompressed())
+        {
+          s << "Inner non zeros:\n";
+          for (Index i=0; i<m.outerSize(); ++i)
+            s << m.m_innerNonZeros[i] << " ";
+          s << " $" << std::endl;
+        }
+        s << std::endl;
+      );
+      s << static_cast<const SparseMatrixBase<SparseMatrix>&>(m);
+      return s;
+    }
+
+    /** Destructor */
+    inline ~SparseMatrix()
+    {
+      delete[] m_outerIndex;
+      delete[] m_innerNonZeros;
+    }
+
+#ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** Overloaded for performance */
+    Scalar sum() const;
+#endif
+    
+#   ifdef EIGEN_SPARSEMATRIX_PLUGIN
+#     include EIGEN_SPARSEMATRIX_PLUGIN
+#   endif
+
+protected:
+
+    template<typename Other>
+    void initAssignment(const Other& other)
+    {
+      resize(other.rows(), other.cols());
+      if(m_innerNonZeros)
+      {
+        delete[] m_innerNonZeros;
+        m_innerNonZeros = 0;
+      }
+    }
+
+    /** \internal
+      * \sa insert(Index,Index) */
+    EIGEN_DONT_INLINE Scalar& insertCompressed(Index row, Index col)
+    {
+      eigen_assert(isCompressed());
+
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
+
+      Index previousOuter = outer;
+      if (m_outerIndex[outer+1]==0)
+      {
+        // we start a new inner vector
+        while (previousOuter>=0 && m_outerIndex[previousOuter]==0)
+        {
+          m_outerIndex[previousOuter] = static_cast<Index>(m_data.size());
+          --previousOuter;
+        }
+        m_outerIndex[outer+1] = m_outerIndex[outer];
+      }
+
+      // here we have to handle the tricky case where the outerIndex array
+      // starts with: [ 0 0 0 0 0 1 ...] and we are inserted in, e.g.,
+      // the 2nd inner vector...
+      bool isLastVec = (!(previousOuter==-1 && m_data.size()!=0))
+                    && (size_t(m_outerIndex[outer+1]) == m_data.size());
+
+      size_t startId = m_outerIndex[outer];
+      // FIXME let's make sure sizeof(long int) == sizeof(size_t)
+      size_t p = m_outerIndex[outer+1];
+      ++m_outerIndex[outer+1];
+
+      float reallocRatio = 1;
+      if (m_data.allocatedSize()<=m_data.size())
+      {
+        // if there is no preallocated memory, let's reserve a minimum of 32 elements
+        if (m_data.size()==0)
+        {
+          m_data.reserve(32);
+        }
+        else
+        {
+          // we need to reallocate the data, to reduce multiple reallocations
+          // we use a smart resize algorithm based on the current filling ratio
+          // in addition, we use float to avoid integers overflows
+          float nnzEstimate = float(m_outerIndex[outer])*float(m_outerSize)/float(outer+1);
+          reallocRatio = (nnzEstimate-float(m_data.size()))/float(m_data.size());
+          // furthermore we bound the realloc ratio to:
+          //   1) reduce multiple minor realloc when the matrix is almost filled
+          //   2) avoid to allocate too much memory when the matrix is almost empty
+          reallocRatio = (std::min)((std::max)(reallocRatio,1.5f),8.f);
+        }
+      }
+      m_data.resize(m_data.size()+1,reallocRatio);
+
+      if (!isLastVec)
+      {
+        if (previousOuter==-1)
+        {
+          // oops wrong guess.
+          // let's correct the outer offsets
+          for (Index k=0; k<=(outer+1); ++k)
+            m_outerIndex[k] = 0;
+          Index k=outer+1;
+          while(m_outerIndex[k]==0)
+            m_outerIndex[k++] = 1;
+          while (k<=m_outerSize && m_outerIndex[k]!=0)
+            m_outerIndex[k++]++;
+          p = 0;
+          --k;
+          k = m_outerIndex[k]-1;
+          while (k>0)
+          {
+            m_data.index(k) = m_data.index(k-1);
+            m_data.value(k) = m_data.value(k-1);
+            k--;
+          }
+        }
+        else
+        {
+          // we are not inserting into the last inner vec
+          // update outer indices:
+          Index j = outer+2;
+          while (j<=m_outerSize && m_outerIndex[j]!=0)
+            m_outerIndex[j++]++;
+          --j;
+          // shift data of last vecs:
+          Index k = m_outerIndex[j]-1;
+          while (k>=Index(p))
+          {
+            m_data.index(k) = m_data.index(k-1);
+            m_data.value(k) = m_data.value(k-1);
+            k--;
+          }
+        }
+      }
+
+      while ( (p > startId) && (m_data.index(p-1) > inner) )
+      {
+        m_data.index(p) = m_data.index(p-1);
+        m_data.value(p) = m_data.value(p-1);
+        --p;
+      }
+
+      m_data.index(p) = inner;
+      return (m_data.value(p) = 0);
+    }
+
+    /** \internal
+      * A vector object that is equal to 0 everywhere but v at the position i */
+    class SingletonVector
+    {
+        Index m_index;
+        Index m_value;
+      public:
+        typedef Index value_type;
+        SingletonVector(Index i, Index v)
+          : m_index(i), m_value(v)
+        {}
+
+        Index operator[](Index i) const { return i==m_index ? m_value : 0; }
+    };
+
+    /** \internal
+      * \sa insert(Index,Index) */
+    EIGEN_DONT_INLINE Scalar& insertUncompressed(Index row, Index col)
+    {
+      eigen_assert(!isCompressed());
+
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
+
+      std::ptrdiff_t room = m_outerIndex[outer+1] - m_outerIndex[outer];
+      std::ptrdiff_t innerNNZ = m_innerNonZeros[outer];
+      if(innerNNZ>=room)
+      {
+        // this inner vector is full, we need to reallocate the whole buffer :(
+        reserve(SingletonVector(outer,std::max<std::ptrdiff_t>(2,innerNNZ)));
+      }
+
+      Index startId = m_outerIndex[outer];
+      Index p = startId + m_innerNonZeros[outer];
+      while ( (p > startId) && (m_data.index(p-1) > inner) )
+      {
+        m_data.index(p) = m_data.index(p-1);
+        m_data.value(p) = m_data.value(p-1);
+        --p;
+      }
+
+      m_innerNonZeros[outer]++;
+
+      m_data.index(p) = inner;
+      return (m_data.value(p) = 0);
+    }
+
+public:
+    /** \internal
+      * \sa insert(Index,Index) */
+    inline Scalar& insertBackUncompressed(Index row, Index col)
+    {
+      const Index outer = IsRowMajor ? row : col;
+      const Index inner = IsRowMajor ? col : row;
+
+      eigen_assert(!isCompressed());
+      eigen_assert(m_innerNonZeros[outer]<=(m_outerIndex[outer+1] - m_outerIndex[outer]));
+
+      Index p = m_outerIndex[outer] + m_innerNonZeros[outer];
+      m_innerNonZeros[outer]++;
+      m_data.index(p) = inner;
+      return (m_data.value(p) = 0);
+    }
+
+private:
+  static void check_template_parameters()
+  {
+    EIGEN_STATIC_ASSERT(NumTraits<Index>::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE);
+  }
+
+  struct default_prunning_func {
+    default_prunning_func(Scalar ref, RealScalar eps) : reference(ref), epsilon(eps) {}
+    inline bool operator() (const Index&, const Index&, const Scalar& value) const
+    {
+      return !internal::isMuchSmallerThan(value, reference, epsilon);
+    }
+    Scalar reference;
+    RealScalar epsilon;
+  };
+};
+
+template<typename Scalar, int _Options, typename _Index>
+class SparseMatrix<Scalar,_Options,_Index>::InnerIterator
+{
+  public:
+    InnerIterator(const SparseMatrix& mat, Index outer)
+      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_id(mat.m_outerIndex[outer])
+    {
+      if(mat.isCompressed())
+        m_end = mat.m_outerIndex[outer+1];
+      else
+        m_end = m_id + mat.m_innerNonZeros[outer];
+    }
+
+    inline InnerIterator& operator++() { m_id++; return *this; }
+
+    inline const Scalar& value() const { return m_values[m_id]; }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id]); }
+
+    inline Index index() const { return m_indices[m_id]; }
+    inline Index outer() const { return m_outer; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
+
+    inline operator bool() const { return (m_id < m_end); }
+
+  protected:
+    const Scalar* m_values;
+    const Index* m_indices;
+    const Index m_outer;
+    Index m_id;
+    Index m_end;
+};
+
+template<typename Scalar, int _Options, typename _Index>
+class SparseMatrix<Scalar,_Options,_Index>::ReverseInnerIterator
+{
+  public:
+    ReverseInnerIterator(const SparseMatrix& mat, Index outer)
+      : m_values(mat.valuePtr()), m_indices(mat.innerIndexPtr()), m_outer(outer), m_start(mat.m_outerIndex[outer])
+    {
+      if(mat.isCompressed())
+        m_id = mat.m_outerIndex[outer+1];
+      else
+        m_id = m_start + mat.m_innerNonZeros[outer];
+    }
+
+    inline ReverseInnerIterator& operator--() { --m_id; return *this; }
+
+    inline const Scalar& value() const { return m_values[m_id-1]; }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_values[m_id-1]); }
+
+    inline Index index() const { return m_indices[m_id-1]; }
+    inline Index outer() const { return m_outer; }
+    inline Index row() const { return IsRowMajor ? m_outer : index(); }
+    inline Index col() const { return IsRowMajor ? index() : m_outer; }
+
+    inline operator bool() const { return (m_id > m_start); }
+
+  protected:
+    const Scalar* m_values;
+    const Index* m_indices;
+    const Index m_outer;
+    Index m_id;
+    const Index m_start;
+};
+
+namespace internal {
+
+template<typename InputIterator, typename SparseMatrixType>
+void set_from_triplets(const InputIterator& begin, const InputIterator& end, SparseMatrixType& mat, int Options = 0)
+{
+  EIGEN_UNUSED_VARIABLE(Options);
+  enum { IsRowMajor = SparseMatrixType::IsRowMajor };
+  typedef typename SparseMatrixType::Scalar Scalar;
+  typedef typename SparseMatrixType::Index Index;
+  SparseMatrix<Scalar,IsRowMajor?ColMajor:RowMajor> trMat(mat.rows(),mat.cols());
+
+  // pass 1: count the nnz per inner-vector
+  VectorXi wi(trMat.outerSize());
+  wi.setZero();
+  for(InputIterator it(begin); it!=end; ++it)
+    wi(IsRowMajor ? it->col() : it->row())++;
+
+  // pass 2: insert all the elements into trMat
+  trMat.reserve(wi);
+  for(InputIterator it(begin); it!=end; ++it)
+    trMat.insertBackUncompressed(it->row(),it->col()) = it->value();
+
+  // pass 3:
+  trMat.sumupDuplicates();
+
+  // pass 4: transposed copy -> implicit sorting
+  mat = trMat;
+}
+
+}
+
+
+/** Fill the matrix \c *this with the list of \em triplets defined by the iterator range \a begin - \b.
+  *
+  * A \em triplet is a tuple (i,j,value) defining a non-zero element.
+  * The input list of triplets does not have to be sorted, and can contains duplicated elements.
+  * In any case, the result is a \b sorted and \b compressed sparse matrix where the duplicates have been summed up.
+  * This is a \em O(n) operation, with \em n the number of triplet elements.
+  * The initial contents of \c *this is destroyed.
+  * The matrix \c *this must be properly resized beforehand using the SparseMatrix(Index,Index) constructor,
+  * or the resize(Index,Index) method. The sizes are not extracted from the triplet list.
+  *
+  * The \a InputIterators value_type must provide the following interface:
+  * \code
+  * Scalar value() const; // the value
+  * Scalar row() const;   // the row index i
+  * Scalar col() const;   // the column index j
+  * \endcode
+  * See for instance the Eigen::Triplet template class.
+  *
+  * Here is a typical usage example:
+  * \code
+    typedef Triplet<double> T;
+    std::vector<T> tripletList;
+    triplets.reserve(estimation_of_entries);
+    for(...)
+    {
+      // ...
+      tripletList.push_back(T(i,j,v_ij));
+    }
+    SparseMatrixType m(rows,cols);
+    m.setFromTriplets(tripletList.begin(), tripletList.end());
+    // m is ready to go!
+  * \endcode
+  *
+  * \warning The list of triplets is read multiple times (at least twice). Therefore, it is not recommended to define
+  * an abstract iterator over a complex data-structure that would be expensive to evaluate. The triplets should rather
+  * be explicitely stored into a std::vector for instance.
+  */
+template<typename Scalar, int _Options, typename _Index>
+template<typename InputIterators>
+void SparseMatrix<Scalar,_Options,_Index>::setFromTriplets(const InputIterators& begin, const InputIterators& end)
+{
+  internal::set_from_triplets(begin, end, *this);
+}
+
+/** \internal */
+template<typename Scalar, int _Options, typename _Index>
+void SparseMatrix<Scalar,_Options,_Index>::sumupDuplicates()
+{
+  eigen_assert(!isCompressed());
+  // TODO, in practice we should be able to use m_innerNonZeros for that task
+  VectorXi wi(innerSize());
+  wi.fill(-1);
+  Index count = 0;
+  // for each inner-vector, wi[inner_index] will hold the position of first element into the index/value buffers
+  for(int j=0; j<outerSize(); ++j)
+  {
+    Index start   = count;
+    Index oldEnd  = m_outerIndex[j]+m_innerNonZeros[j];
+    for(Index k=m_outerIndex[j]; k<oldEnd; ++k)
+    {
+      Index i = m_data.index(k);
+      if(wi(i)>=start)
+      {
+        // we already meet this entry => accumulate it
+        m_data.value(wi(i)) += m_data.value(k);
+      }
+      else
+      {
+        m_data.value(count) = m_data.value(k);
+        m_data.index(count) = m_data.index(k);
+        wi(i) = count;
+        ++count;
+      }
+    }
+    m_outerIndex[j] = start;
+  }
+  m_outerIndex[m_outerSize] = count;
+
+  // turn the matrix into compressed form
+  delete[] m_innerNonZeros;
+  m_innerNonZeros = 0;
+  m_data.resize(m_outerIndex[m_outerSize]);
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSEMATRIX_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseMatrixBase.h b/extern/Eigen3/Eigen/src/SparseCore/SparseMatrixBase.h
index c01981bc935..9a1258097fe 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseMatrixBase.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseMatrixBase.h
@@ -1,31 +1,18 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSEMATRIXBASE_H
 #define EIGEN_SPARSEMATRIXBASE_H
 
-/** \ingroup Sparse_Module
+namespace Eigen { 
+
+/** \ingroup SparseCore_Module
   *
   * \class SparseMatrixBase
   *
@@ -44,6 +31,9 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     typedef typename internal::packet_traits<Scalar>::type PacketScalar;
     typedef typename internal::traits<Derived>::StorageKind StorageKind;
     typedef typename internal::traits<Derived>::Index Index;
+    typedef typename internal::add_const_on_value_type_if_arithmetic<
+                         typename internal::packet_traits<Scalar>::type
+                     >::type PacketReturnType;
 
     typedef SparseMatrixBase StorageBaseType;
     typedef EigenBase<Derived> Base;
@@ -54,8 +44,6 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
       other.derived().evalTo(derived());
       return derived();
     }
-    
-//     using Base::operator=;
 
     enum {
 
@@ -107,15 +95,6 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
       #endif
     };
 
-    /* \internal the return type of MatrixBase::conjugate() */
-//     typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
-//                         const SparseCwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, Derived>,
-//                         const Derived&
-//                      >::type ConjugateReturnType;
-    /* \internal the return type of MatrixBase::real() */
-//     typedef SparseCwiseUnaryOp<internal::scalar_real_op<Scalar>, Derived> RealReturnType;
-    /* \internal the return type of MatrixBase::imag() */
-//     typedef SparseCwiseUnaryOp<internal::scalar_imag_op<Scalar>, Derived> ImagReturnType;
     /** \internal the return type of MatrixBase::adjoint() */
     typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
                         CwiseUnaryOp<internal::scalar_conjugate_op<Scalar>, Eigen::Transpose<const Derived> >,
@@ -125,16 +104,6 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
 
     typedef SparseMatrix<Scalar, Flags&RowMajorBit ? RowMajor : ColMajor> PlainObject;
 
-#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase
-#   include "../plugins/CommonCwiseUnaryOps.h"
-#   include "../plugins/CommonCwiseBinaryOps.h"
-#   include "../plugins/MatrixCwiseUnaryOps.h"
-#   include "../plugins/MatrixCwiseBinaryOps.h"
-#   ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN
-#     include EIGEN_SPARSEMATRIXBASE_PLUGIN
-#   endif
-#   undef EIGEN_CURRENT_STORAGE_BASE_CLASS
-#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
 
 #ifndef EIGEN_PARSED_BY_DOXYGEN
     /** This is the "real scalar" type; if the \a Scalar type is already real numbers
@@ -162,12 +131,24 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     { return *static_cast<Derived*>(const_cast<SparseMatrixBase*>(this)); }
 #endif // not EIGEN_PARSED_BY_DOXYGEN
 
-    /** \returns the number of rows. \sa cols(), RowsAtCompileTime */
+#define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::SparseMatrixBase
+#   include "../plugins/CommonCwiseUnaryOps.h"
+#   include "../plugins/CommonCwiseBinaryOps.h"
+#   include "../plugins/MatrixCwiseUnaryOps.h"
+#   include "../plugins/MatrixCwiseBinaryOps.h"
+#   ifdef EIGEN_SPARSEMATRIXBASE_PLUGIN
+#     include EIGEN_SPARSEMATRIXBASE_PLUGIN
+#   endif
+#   undef EIGEN_CURRENT_STORAGE_BASE_CLASS
+#undef EIGEN_CURRENT_STORAGE_BASE_CLASS
+
+
+    /** \returns the number of rows. \sa cols() */
     inline Index rows() const { return derived().rows(); }
-    /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/
+    /** \returns the number of columns. \sa rows() */
     inline Index cols() const { return derived().cols(); }
     /** \returns the number of coefficients, which is \a rows()*cols().
-      * \sa rows(), cols(), SizeAtCompileTime. */
+      * \sa rows(), cols(). */
     inline Index size() const { return rows() * cols(); }
     /** \returns the number of nonzero coefficients which is in practice the number
       * of stored coefficients. */
@@ -188,29 +169,64 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     Derived& markAsRValue() { m_isRValue = true; return derived(); }
 
     SparseMatrixBase() : m_isRValue(false) { /* TODO check flags */ }
+
     
+    template<typename OtherDerived>
+    Derived& operator=(const ReturnByValue<OtherDerived>& other)
+    {
+      other.evalTo(derived());
+      return derived();
+    }
+
+
+    template<typename OtherDerived>
+    inline Derived& operator=(const SparseMatrixBase<OtherDerived>& other)
+    {
+      return assign(other.derived());
+    }
+
     inline Derived& operator=(const Derived& other)
     {
-//       std::cout << "Derived& operator=(const Derived& other)\n";
 //       if (other.isRValue())
 //         derived().swap(other.const_cast_derived());
 //       else
-        this->operator=<Derived>(other);
-      return derived();
+      return assign(other.derived());
     }
-    
+
+  protected:
+
     template<typename OtherDerived>
-    Derived& operator=(const ReturnByValue<OtherDerived>& other)
+    inline Derived& assign(const OtherDerived& other)
     {
-      other.evalTo(derived());
+      const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
+      const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols();
+      if ((!transpose) && other.isRValue())
+      {
+        // eval without temporary
+        derived().resize(other.rows(), other.cols());
+        derived().setZero();
+        derived().reserve((std::max)(this->rows(),this->cols())*2);
+        for (Index j=0; j<outerSize; ++j)
+        {
+          derived().startVec(j);
+          for (typename OtherDerived::InnerIterator it(other, j); it; ++it)
+          {
+            Scalar v = it.value();
+            derived().insertBackByOuterInner(j,it.index()) = v;
+          }
+        }
+        derived().finalize();
+      }
+      else
+      {
+        assignGeneric(other);
+      }
       return derived();
     }
 
-
     template<typename OtherDerived>
     inline void assignGeneric(const OtherDerived& other)
     {
-//       std::cout << "Derived& operator=(const MatrixBase<OtherDerived>& other)\n";
       //const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
       eigen_assert(( ((internal::traits<Derived>::SupportedAccessPatterns&OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
                   (!((Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit)))) &&
@@ -230,8 +246,7 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
         for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it)
         {
           Scalar v = it.value();
-          if (v!=Scalar(0))
-            temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
+          temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
         }
       }
       temp.finalize();
@@ -239,54 +254,23 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
       derived() = temp.markAsRValue();
     }
 
-
-    template<typename OtherDerived>
-    inline Derived& operator=(const SparseMatrixBase<OtherDerived>& other)
-    {
-//       std::cout << typeid(OtherDerived).name() << "\n";
-//       std::cout << Flags << " " << OtherDerived::Flags << "\n";
-      const bool transpose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
-//       std::cout << "eval transpose = " << transpose << "\n";
-      const Index outerSize = (int(OtherDerived::Flags) & RowMajorBit) ? other.rows() : other.cols();
-      if ((!transpose) && other.isRValue())
-      {
-        // eval without temporary
-        derived().resize(other.rows(), other.cols());
-        derived().setZero();
-        derived().reserve((std::max)(this->rows(),this->cols())*2);
-        for (Index j=0; j<outerSize; ++j)
-        {
-          derived().startVec(j);
-          for (typename OtherDerived::InnerIterator it(other.derived(), j); it; ++it)
-          {
-            Scalar v = it.value();
-            if (v!=Scalar(0))
-              derived().insertBackByOuterInner(j,it.index()) = v;
-          }
-        }
-        derived().finalize();
-      }
-      else
-      {
-        assignGeneric(other.derived());
-      }
-      return derived();
-    }
+  public:
 
     template<typename Lhs, typename Rhs>
     inline Derived& operator=(const SparseSparseProduct<Lhs,Rhs>& product);
 
-    template<typename Lhs, typename Rhs>
-    inline void _experimentalNewProduct(const Lhs& lhs, const Rhs& rhs);
-
     friend std::ostream & operator << (std::ostream & s, const SparseMatrixBase& m)
     {
+      typedef typename Derived::Nested Nested;
+      typedef typename internal::remove_all<Nested>::type NestedCleaned;
+
       if (Flags&RowMajorBit)
       {
-        for (Index row=0; row<m.outerSize(); ++row)
+        const Nested nm(m.derived());
+        for (Index row=0; row<nm.outerSize(); ++row)
         {
           Index col = 0;
-          for (typename Derived::InnerIterator it(m.derived(), row); it; ++it)
+          for (typename NestedCleaned::InnerIterator it(nm.derived(), row); it; ++it)
           {
             for ( ; col<it.index(); ++col)
               s << "0 ";
@@ -300,9 +284,10 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
       }
       else
       {
+        const Nested nm(m.derived());
         if (m.cols() == 1) {
           Index row = 0;
-          for (typename Derived::InnerIterator it(m.derived(), 0); it; ++it)
+          for (typename NestedCleaned::InnerIterator it(nm.derived(), 0); it; ++it)
           {
             for ( ; row<it.index(); ++row)
               s << "0" << std::endl;
@@ -314,31 +299,18 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
         }
         else
         {
-          SparseMatrix<Scalar, RowMajorBit> trans = m.derived();
-          s << trans;
+          SparseMatrix<Scalar, RowMajorBit> trans = m;
+          s << static_cast<const SparseMatrixBase<SparseMatrix<Scalar, RowMajorBit> >&>(trans);
         }
       }
       return s;
     }
 
-//     const SparseCwiseUnaryOp<internal::scalar_opposite_op<typename internal::traits<Derived>::Scalar>,Derived> operator-() const;
-
-//     template<typename OtherDerived>
-//     const CwiseBinaryOp<internal::scalar_sum_op<typename internal::traits<Derived>::Scalar>, Derived, OtherDerived>
-//     operator+(const SparseMatrixBase<OtherDerived> &other) const;
-
-//     template<typename OtherDerived>
-//     const CwiseBinaryOp<internal::scalar_difference_op<typename internal::traits<Derived>::Scalar>, Derived, OtherDerived>
-//     operator-(const SparseMatrixBase<OtherDerived> &other) const;
-
     template<typename OtherDerived>
     Derived& operator+=(const SparseMatrixBase<OtherDerived>& other);
     template<typename OtherDerived>
     Derived& operator-=(const SparseMatrixBase<OtherDerived>& other);
 
-//     template<typename Lhs,typename Rhs>
-//     Derived& operator+=(const Flagged<Product<Lhs,Rhs,CacheFriendlyProduct>, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit>& other);
-
     Derived& operator*=(const Scalar& other);
     Derived& operator/=(const Scalar& other);
 
@@ -358,16 +330,6 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     EIGEN_STRONG_INLINE const EIGEN_SPARSE_CWISE_PRODUCT_RETURN_TYPE
     cwiseProduct(const MatrixBase<OtherDerived> &other) const;
 
-//     const SparseCwiseUnaryOp<internal::scalar_multiple_op<typename internal::traits<Derived>::Scalar>, Derived>
-//     operator*(const Scalar& scalar) const;
-//     const SparseCwiseUnaryOp<internal::scalar_quotient1_op<typename internal::traits<Derived>::Scalar>, Derived>
-//     operator/(const Scalar& scalar) const;
-
-//     inline friend const SparseCwiseUnaryOp<internal::scalar_multiple_op<typename internal::traits<Derived>::Scalar>, Derived>
-//     operator*(const Scalar& scalar, const SparseMatrixBase& matrix)
-//     { return matrix*scalar; }
-
-
     // sparse * sparse
     template<typename OtherDerived>
     const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type
@@ -394,6 +356,12 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     template<typename OtherDerived>
     const typename SparseDenseProductReturnType<Derived,OtherDerived>::Type
     operator*(const MatrixBase<OtherDerived> &other) const;
+    
+     /** \returns an expression of P H P^-1 where H is the matrix represented by \c *this */
+    SparseSymmetricPermutationProduct<Derived,Upper|Lower> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const
+    {
+      return SparseSymmetricPermutationProduct<Derived,Upper|Lower>(derived(), perm);
+    }
 
     template<typename OtherDerived>
     Derived& operator*=(const SparseMatrixBase<OtherDerived>& other);
@@ -407,8 +375,6 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     // deprecated
     template<typename OtherDerived>
     void solveTriangularInPlace(MatrixBase<OtherDerived>& other) const;
-//     template<typename OtherDerived>
-//     void solveTriangularInPlace(SparseMatrixBase<OtherDerived>& other) const;
     #endif // EIGEN2_SUPPORT
 
     template<int Mode>
@@ -421,12 +387,9 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     template<typename OtherDerived> Scalar dot(const SparseMatrixBase<OtherDerived>& other) const;
     RealScalar squaredNorm() const;
     RealScalar norm()  const;
-//     const PlainObject normalized() const;
-//     void normalize();
 
     Transpose<Derived> transpose() { return derived(); }
     const Transpose<const Derived> transpose() const { return derived(); }
-    // void transposeInPlace();
     const AdjointReturnType adjoint() const { return transpose(); }
 
     // sub-vector
@@ -442,77 +405,14 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     const SparseInnerVectorSet<Derived,Dynamic> subrows(Index start, Index size) const;
     SparseInnerVectorSet<Derived,Dynamic> subcols(Index start, Index size);
     const SparseInnerVectorSet<Derived,Dynamic> subcols(Index start, Index size) const;
+    
+    SparseInnerVectorSet<Derived,Dynamic> middleRows(Index start, Index size);
+    const SparseInnerVectorSet<Derived,Dynamic> middleRows(Index start, Index size) const;
+    SparseInnerVectorSet<Derived,Dynamic> middleCols(Index start, Index size);
+    const SparseInnerVectorSet<Derived,Dynamic> middleCols(Index start, Index size) const;
     SparseInnerVectorSet<Derived,Dynamic> innerVectors(Index outerStart, Index outerSize);
     const SparseInnerVectorSet<Derived,Dynamic> innerVectors(Index outerStart, Index outerSize) const;
 
-//     typename BlockReturnType<Derived>::Type block(int startRow, int startCol, int blockRows, int blockCols);
-//     const typename BlockReturnType<Derived>::Type
-//     block(int startRow, int startCol, int blockRows, int blockCols) const;
-//
-//     typename BlockReturnType<Derived>::SubVectorType segment(int start, int size);
-//     const typename BlockReturnType<Derived>::SubVectorType segment(int start, int size) const;
-//
-//     typename BlockReturnType<Derived,Dynamic>::SubVectorType start(int size);
-//     const typename BlockReturnType<Derived,Dynamic>::SubVectorType start(int size) const;
-//
-//     typename BlockReturnType<Derived,Dynamic>::SubVectorType end(int size);
-//     const typename BlockReturnType<Derived,Dynamic>::SubVectorType end(int size) const;
-//
-//     template<int BlockRows, int BlockCols>
-//     typename BlockReturnType<Derived, BlockRows, BlockCols>::Type block(int startRow, int startCol);
-//     template<int BlockRows, int BlockCols>
-//     const typename BlockReturnType<Derived, BlockRows, BlockCols>::Type block(int startRow, int startCol) const;
-
-//     template<int Size> typename BlockReturnType<Derived,Size>::SubVectorType start(void);
-//     template<int Size> const typename BlockReturnType<Derived,Size>::SubVectorType start() const;
-
-//     template<int Size> typename BlockReturnType<Derived,Size>::SubVectorType end();
-//     template<int Size> const typename BlockReturnType<Derived,Size>::SubVectorType end() const;
-
-//     template<int Size> typename BlockReturnType<Derived,Size>::SubVectorType segment(int start);
-//     template<int Size> const typename BlockReturnType<Derived,Size>::SubVectorType segment(int start) const;
-
-//     Diagonal<Derived> diagonal();
-//     const Diagonal<Derived> diagonal() const;
-
-//     template<unsigned int Mode> Part<Derived, Mode> part();
-//     template<unsigned int Mode> const Part<Derived, Mode> part() const;
-
-
-//     static const ConstantReturnType Constant(int rows, int cols, const Scalar& value);
-//     static const ConstantReturnType Constant(int size, const Scalar& value);
-//     static const ConstantReturnType Constant(const Scalar& value);
-
-//     template<typename CustomNullaryOp>
-//     static const CwiseNullaryOp<CustomNullaryOp, Derived> NullaryExpr(int rows, int cols, const CustomNullaryOp& func);
-//     template<typename CustomNullaryOp>
-//     static const CwiseNullaryOp<CustomNullaryOp, Derived> NullaryExpr(int size, const CustomNullaryOp& func);
-//     template<typename CustomNullaryOp>
-//     static const CwiseNullaryOp<CustomNullaryOp, Derived> NullaryExpr(const CustomNullaryOp& func);
-
-//     static const ConstantReturnType Zero(int rows, int cols);
-//     static const ConstantReturnType Zero(int size);
-//     static const ConstantReturnType Zero();
-//     static const ConstantReturnType Ones(int rows, int cols);
-//     static const ConstantReturnType Ones(int size);
-//     static const ConstantReturnType Ones();
-//     static const IdentityReturnType Identity();
-//     static const IdentityReturnType Identity(int rows, int cols);
-//     static const BasisReturnType Unit(int size, int i);
-//     static const BasisReturnType Unit(int i);
-//     static const BasisReturnType UnitX();
-//     static const BasisReturnType UnitY();
-//     static const BasisReturnType UnitZ();
-//     static const BasisReturnType UnitW();
-
-//     const DiagonalMatrix<Derived> asDiagonal() const;
-
-//     Derived& setConstant(const Scalar& value);
-//     Derived& setZero();
-//     Derived& setOnes();
-//     Derived& setRandom();
-//     Derived& setIdentity();
-
       /** \internal use operator= */
       template<typename DenseDerived>
       void evalTo(MatrixBase<DenseDerived>& dst) const
@@ -537,37 +437,6 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     bool isApprox(const MatrixBase<OtherDerived>& other,
                   RealScalar prec = NumTraits<Scalar>::dummy_precision()) const
     { return toDense().isApprox(other,prec); }
-//     bool isMuchSmallerThan(const RealScalar& other,
-//                            RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-//     template<typename OtherDerived>
-//     bool isMuchSmallerThan(const MatrixBase<OtherDerived>& other,
-//                            RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-
-//     bool isApproxToConstant(const Scalar& value, RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-//     bool isZero(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-//     bool isOnes(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-//     bool isIdentity(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-//     bool isDiagonal(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-
-//     bool isUpper(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-//     bool isLower(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-
-//     template<typename OtherDerived>
-//     bool isOrthogonal(const MatrixBase<OtherDerived>& other,
-//                       RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-//     bool isUnitary(RealScalar prec = NumTraits<Scalar>::dummy_precision()) const;
-
-//     template<typename OtherDerived>
-//     inline bool operator==(const MatrixBase<OtherDerived>& other) const
-//     { return (cwise() == other).all(); }
-
-//     template<typename OtherDerived>
-//     inline bool operator!=(const MatrixBase<OtherDerived>& other) const
-//     { return (cwise() != other).any(); }
-
-
-//     template<typename NewType>
-//     const SparseCwiseUnaryOp<internal::scalar_cast_op<typename internal::traits<Derived>::Scalar, NewType>, Derived> cast() const;
 
     /** \returns the matrix or vector obtained by evaluating this expression.
       *
@@ -577,130 +446,13 @@ template<typename Derived> class SparseMatrixBase : public EigenBase<Derived>
     inline const typename internal::eval<Derived>::type eval() const
     { return typename internal::eval<Derived>::type(derived()); }
 
-//     template<typename OtherDerived>
-//     void swap(MatrixBase<OtherDerived> const & other);
-
-//     template<unsigned int Added>
-//     const SparseFlagged<Derived, Added, 0> marked() const;
-//     const Flagged<Derived, 0, EvalBeforeNestingBit | EvalBeforeAssigningBit> lazy() const;
-
-    /** \returns number of elements to skip to pass from one row (resp. column) to another
-      * for a row-major (resp. column-major) matrix.
-      * Combined with coeffRef() and the \ref flags flags, it allows a direct access to the data
-      * of the underlying matrix.
-      */
-//     inline int stride(void) const { return derived().stride(); }
-
-// FIXME
-//     ConjugateReturnType conjugate() const;
-//     const RealReturnType real() const;
-//     const ImagReturnType imag() const;
-
-//     template<typename CustomUnaryOp>
-//     const SparseCwiseUnaryOp<CustomUnaryOp, Derived> unaryExpr(const CustomUnaryOp& func = CustomUnaryOp()) const;
-
-//     template<typename CustomBinaryOp, typename OtherDerived>
-//     const CwiseBinaryOp<CustomBinaryOp, Derived, OtherDerived>
-//     binaryExpr(const MatrixBase<OtherDerived> &other, const CustomBinaryOp& func = CustomBinaryOp()) const;
-
-
     Scalar sum() const;
-//     Scalar trace() const;
-
-//     typename internal::traits<Derived>::Scalar minCoeff() const;
-//     typename internal::traits<Derived>::Scalar maxCoeff() const;
-
-//     typename internal::traits<Derived>::Scalar minCoeff(int* row, int* col = 0) const;
-//     typename internal::traits<Derived>::Scalar maxCoeff(int* row, int* col = 0) const;
-
-//     template<typename BinaryOp>
-//     typename internal::result_of<BinaryOp(typename internal::traits<Derived>::Scalar)>::type
-//     redux(const BinaryOp& func) const;
-
-//     template<typename Visitor>
-//     void visit(Visitor& func) const;
-
-
-//     const SparseCwise<Derived> cwise() const;
-//     SparseCwise<Derived> cwise();
-
-//     inline const WithFormat<Derived> format(const IOFormat& fmt) const;
-
-/////////// Array module ///////////
-    /*
-    bool all(void) const;
-    bool any(void) const;
-
-    const VectorwiseOp<Derived,Horizontal> rowwise() const;
-    const VectorwiseOp<Derived,Vertical> colwise() const;
-
-    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(int rows, int cols);
-    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random(int size);
-    static const CwiseNullaryOp<internal::scalar_random_op<Scalar>,Derived> Random();
-
-    template<typename ThenDerived,typename ElseDerived>
-    const Select<Derived,ThenDerived,ElseDerived>
-    select(const MatrixBase<ThenDerived>& thenMatrix,
-           const MatrixBase<ElseDerived>& elseMatrix) const;
-
-    template<typename ThenDerived>
-    inline const Select<Derived,ThenDerived, typename ThenDerived::ConstantReturnType>
-    select(const MatrixBase<ThenDerived>& thenMatrix, typename ThenDerived::Scalar elseScalar) const;
-
-    template<typename ElseDerived>
-    inline const Select<Derived, typename ElseDerived::ConstantReturnType, ElseDerived >
-    select(typename ElseDerived::Scalar thenScalar, const MatrixBase<ElseDerived>& elseMatrix) const;
-
-    template<int p> RealScalar lpNorm() const;
-    */
-
-
-//     template<typename OtherDerived>
-//     Scalar dot(const MatrixBase<OtherDerived>& other) const
-//     {
-//       EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived)
-//       EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived)
-//       EIGEN_STATIC_ASSERT((internal::is_same<Scalar, typename OtherDerived::Scalar>::value),
-//         YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
-//
-//       eigen_assert(derived().size() == other.size());
-//       // short version, but the assembly looks more complicated because
-//       // of the CwiseBinaryOp iterator complexity
-//       // return res = (derived().cwise() * other.derived().conjugate()).sum();
-//
-//       // optimized, generic version
-//       typename Derived::InnerIterator i(derived(),0);
-//       typename OtherDerived::InnerIterator j(other.derived(),0);
-//       Scalar res = 0;
-//       while (i && j)
-//       {
-//         if (i.index()==j.index())
-//         {
-// //           std::cerr << i.value() << " * " << j.value() << "\n";
-//           res += i.value() * internal::conj(j.value());
-//           ++i; ++j;
-//         }
-//         else if (i.index()<j.index())
-//           ++i;
-//         else
-//           ++j;
-//       }
-//       return res;
-//     }
-//
-//     Scalar sum() const
-//     {
-//       Scalar res = 0;
-//       for (typename Derived::InnerIterator iter(*this,0); iter; ++iter)
-//       {
-//         res += iter.value();
-//       }
-//       return res;
-//     }
 
   protected:
 
     bool m_isRValue;
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSEMATRIXBASE_H
diff --git a/extern/Eigen3/Eigen/src/SparseCore/SparsePermutation.h b/extern/Eigen3/Eigen/src/SparseCore/SparsePermutation.h
new file mode 100644
index 00000000000..b897b7595b5
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparsePermutation.h
@@ -0,0 +1,148 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2012 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_PERMUTATION_H
+#define EIGEN_SPARSE_PERMUTATION_H
+
+// This file implements sparse * permutation products
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
+struct traits<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
+{
+  typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
+  typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
+  typedef typename MatrixTypeNestedCleaned::Index Index;
+  enum {
+    SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
+    MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
+  };
+
+  typedef typename internal::conditional<MoveOuter,
+        SparseMatrix<Scalar,SrcStorageOrder,Index>,
+        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> >::type ReturnType;
+};
+
+template<typename PermutationType, typename MatrixType, int Side, bool Transposed>
+struct permut_sparsematrix_product_retval
+ : public ReturnByValue<permut_sparsematrix_product_retval<PermutationType, MatrixType, Side, Transposed> >
+{
+    typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
+    typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
+    typedef typename MatrixTypeNestedCleaned::Index Index;
+
+    enum {
+      SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
+      MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
+    };
+
+    permut_sparsematrix_product_retval(const PermutationType& perm, const MatrixType& matrix)
+      : m_permutation(perm), m_matrix(matrix)
+    {}
+
+    inline int rows() const { return m_matrix.rows(); }
+    inline int cols() const { return m_matrix.cols(); }
+
+    template<typename Dest> inline void evalTo(Dest& dst) const
+    {
+      if(MoveOuter)
+      {
+        SparseMatrix<Scalar,SrcStorageOrder,Index> tmp(m_matrix.rows(), m_matrix.cols());
+        VectorXi sizes(m_matrix.outerSize());
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+        {
+          Index jp = m_permutation.indices().coeff(j);
+          sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = m_matrix.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).size();
+        }
+        tmp.reserve(sizes);
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+        {
+          Index jp = m_permutation.indices().coeff(j);
+          Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j;
+          Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j;
+          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,jsrc); it; ++it)
+            tmp.insertByOuterInner(jdst,it.index()) = it.value();
+        }
+        dst = tmp;
+      }
+      else
+      {
+        SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,Index> tmp(m_matrix.rows(), m_matrix.cols());
+        VectorXi sizes(tmp.outerSize());
+        sizes.setZero();
+        PermutationMatrix<Dynamic,Dynamic,Index> perm;
+        if((Side==OnTheLeft) ^ Transposed)
+          perm = m_permutation;
+        else
+          perm = m_permutation.transpose();
+
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
+            sizes[perm.indices().coeff(it.index())]++;
+        tmp.reserve(sizes);
+        for(Index j=0; j<m_matrix.outerSize(); ++j)
+          for(typename MatrixTypeNestedCleaned::InnerIterator it(m_matrix,j); it; ++it)
+            tmp.insertByOuterInner(perm.indices().coeff(it.index()),j) = it.value();
+        dst = tmp;
+      }
+    }
+
+  protected:
+    const PermutationType& m_permutation;
+    typename MatrixType::Nested m_matrix;
+};
+
+}
+
+
+
+/** \returns the matrix with the permutation applied to the columns
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>
+operator*(const SparseMatrixBase<SparseDerived>& matrix, const PermutationBase<PermDerived>& perm)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, false>(perm, matrix.derived());
+}
+
+/** \returns the matrix with the permutation applied to the rows
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>
+operator*( const PermutationBase<PermDerived>& perm, const SparseMatrixBase<SparseDerived>& matrix)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, false>(perm, matrix.derived());
+}
+
+
+
+/** \returns the matrix with the inverse permutation applied to the columns.
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>
+operator*(const SparseMatrixBase<SparseDerived>& matrix, const Transpose<PermutationBase<PermDerived> >& tperm)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheRight, true>(tperm.nestedPermutation(), matrix.derived());
+}
+
+/** \returns the matrix with the inverse permutation applied to the rows.
+  */
+template<typename SparseDerived, typename PermDerived>
+inline const internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>
+operator*(const Transpose<PermutationBase<PermDerived> >& tperm, const SparseMatrixBase<SparseDerived>& matrix)
+{
+  return internal::permut_sparsematrix_product_retval<PermutationBase<PermDerived>, SparseDerived, OnTheLeft, true>(tperm.nestedPermutation(), matrix.derived());
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseProduct.h b/extern/Eigen3/Eigen/src/SparseCore/SparseProduct.h
index 1c1f54706ac..6a555b83434 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseProduct.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseProduct.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2010 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSEPRODUCT_H
 #define EIGEN_SPARSEPRODUCT_H
 
+namespace Eigen { 
+
 template<typename Lhs, typename Rhs>
 struct SparseSparseProductReturnType
 {
@@ -38,11 +25,11 @@ struct SparseSparseProductReturnType
 
   typedef typename internal::conditional<TransposeLhs,
     SparseMatrix<Scalar,0>,
-    const typename internal::nested<Lhs,Rhs::RowsAtCompileTime>::type>::type LhsNested;
+    typename internal::nested<Lhs,Rhs::RowsAtCompileTime>::type>::type LhsNested;
 
   typedef typename internal::conditional<TransposeRhs,
     SparseMatrix<Scalar,0>,
-    const typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type>::type RhsNested;
+    typename internal::nested<Rhs,Lhs::RowsAtCompileTime>::type>::type RhsNested;
 
   typedef SparseSparseProduct<LhsNested, RhsNested> Type;
 };
@@ -106,9 +93,42 @@ class SparseSparseProduct : internal::no_assignment_operator,
 
     template<typename Lhs, typename Rhs>
     EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs)
-      : m_lhs(lhs), m_rhs(rhs)
+      : m_lhs(lhs), m_rhs(rhs), m_tolerance(0), m_conservative(true)
+    {
+      init();
+    }
+
+    template<typename Lhs, typename Rhs>
+    EIGEN_STRONG_INLINE SparseSparseProduct(const Lhs& lhs, const Rhs& rhs, RealScalar tolerance)
+      : m_lhs(lhs), m_rhs(rhs), m_tolerance(tolerance), m_conservative(false)
+    {
+      init();
+    }
+
+    SparseSparseProduct pruned(Scalar reference = 0, RealScalar epsilon = NumTraits<RealScalar>::dummy_precision()) const
+    {
+      return SparseSparseProduct(m_lhs,m_rhs,internal::abs(reference)*epsilon);
+    }
+
+    template<typename Dest>
+    void evalTo(Dest& result) const
+    {
+      if(m_conservative)
+        internal::conservative_sparse_sparse_product_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result);
+      else
+        internal::sparse_sparse_product_with_pruning_selector<_LhsNested, _RhsNested, Dest>::run(lhs(),rhs(),result,m_tolerance);
+    }
+
+    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
+    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
+
+    EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
+    EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
+
+  protected:
+    void init()
     {
-      eigen_assert(lhs.cols() == rhs.rows());
+      eigen_assert(m_lhs.cols() == m_rhs.rows());
 
       enum {
         ProductIsValid = _LhsNested::ColsAtCompileTime==Dynamic
@@ -127,15 +147,40 @@ class SparseSparseProduct : internal::no_assignment_operator,
       EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT)
     }
 
-    EIGEN_STRONG_INLINE Index rows() const { return m_lhs.rows(); }
-    EIGEN_STRONG_INLINE Index cols() const { return m_rhs.cols(); }
-
-    EIGEN_STRONG_INLINE const _LhsNested& lhs() const { return m_lhs; }
-    EIGEN_STRONG_INLINE const _RhsNested& rhs() const { return m_rhs; }
-
-  protected:
     LhsNested m_lhs;
     RhsNested m_rhs;
+    RealScalar m_tolerance;
+    bool m_conservative;
 };
 
+// sparse = sparse * sparse
+template<typename Derived>
+template<typename Lhs, typename Rhs>
+inline Derived& SparseMatrixBase<Derived>::operator=(const SparseSparseProduct<Lhs,Rhs>& product)
+{
+  product.evalTo(derived());
+  return derived();
+}
+
+/** \returns an expression of the product of two sparse matrices.
+  * By default a conservative product preserving the symbolic non zeros is performed.
+  * The automatic pruning of the small values can be achieved by calling the pruned() function
+  * in which case a totally different product algorithm is employed:
+  * \code
+  * C = (A*B).pruned();             // supress numerical zeros (exact)
+  * C = (A*B).pruned(ref);
+  * C = (A*B).pruned(ref,epsilon);
+  * \endcode
+  * where \c ref is a meaningful non zero reference value.
+  * */
+template<typename Derived>
+template<typename OtherDerived>
+inline const typename SparseSparseProductReturnType<Derived,OtherDerived>::Type
+SparseMatrixBase<Derived>::operator*(const SparseMatrixBase<OtherDerived> &other) const
+{
+  return typename SparseSparseProductReturnType<Derived,OtherDerived>::Type(derived(), other.derived());
+}
+
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSEPRODUCT_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseRedux.h b/extern/Eigen3/Eigen/src/SparseCore/SparseRedux.h
index afc49de7aad..f3da93a71d4 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseRedux.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseRedux.h
@@ -3,34 +3,21 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSEREDUX_H
 #define EIGEN_SPARSEREDUX_H
 
+namespace Eigen { 
+
 template<typename Derived>
 typename internal::traits<Derived>::Scalar
 SparseMatrixBase<Derived>::sum() const
 {
   eigen_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
-  Scalar res = 0;
+  Scalar res(0);
   for (Index j=0; j<outerSize(); ++j)
     for (typename Derived::InnerIterator iter(derived(),j); iter; ++iter)
       res += iter.value();
@@ -53,4 +40,6 @@ SparseVector<_Scalar,_Options,_Index>::sum() const
   return Matrix<Scalar,1,Dynamic>::Map(&m_data.value(0), m_data.size()).sum();
 }
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSEREDUX_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseSelfAdjointView.h b/extern/Eigen3/Eigen/src/SparseCore/SparseSelfAdjointView.h
index d82044c789c..86ec0a6c5e2 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseSelfAdjointView.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseSelfAdjointView.h
@@ -3,30 +3,17 @@
 //
 // Copyright (C) 2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSE_SELFADJOINTVIEW_H
 #define EIGEN_SPARSE_SELFADJOINTVIEW_H
 
-/** \class SparseSelfAdjointView
-  *
+namespace Eigen { 
+
+/** \ingroup SparseCore_Module
+  * \class SparseSelfAdjointView
   *
   * \brief Pseudo expression to manipulate a triangular sparse matrix as a selfadjoint matrix.
   *
@@ -45,9 +32,6 @@ class SparseSelfAdjointTimeDenseProduct;
 template<typename Lhs, typename Rhs, int UpLo>
 class DenseTimeSparseSelfAdjointProduct;
 
-template<typename MatrixType,int UpLo>
-class SparseSymmetricPermutationProduct;
-
 namespace internal {
   
 template<typename MatrixType, unsigned int UpLo>
@@ -106,9 +90,6 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
       *
       * \returns a reference to \c *this
       *
-      * Note that it is faster to set alpha=0 than initializing the matrix to zero
-      * and then keep the default value alpha=1.
-      *
       * To perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
       * call this function with u.adjoint().
       */
@@ -116,21 +97,21 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
     SparseSelfAdjointView& rankUpdate(const SparseMatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
     
     /** \internal triggered by sparse_matrix = SparseSelfadjointView; */
-    template<typename DestScalar> void evalTo(SparseMatrix<DestScalar>& _dest) const
+    template<typename DestScalar,int StorageOrder> void evalTo(SparseMatrix<DestScalar,StorageOrder,Index>& _dest) const
     {
       internal::permute_symm_to_fullsymm<UpLo>(m_matrix, _dest);
     }
     
-    template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar>& _dest) const
+    template<typename DestScalar> void evalTo(DynamicSparseMatrix<DestScalar,ColMajor,Index>& _dest) const
     {
       // TODO directly evaluate into _dest;
-      SparseMatrix<DestScalar> tmp(_dest.rows(),_dest.cols());
+      SparseMatrix<DestScalar,ColMajor,Index> tmp(_dest.rows(),_dest.cols());
       internal::permute_symm_to_fullsymm<UpLo>(m_matrix, tmp);
       _dest = tmp;
     }
     
-    /** \returns an expression of P^-1 H P */
-    SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic>& perm) const
+    /** \returns an expression of P H P^-1 */
+    SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo> twistedBy(const PermutationMatrix<Dynamic,Dynamic,Index>& perm) const
     {
       return SparseSymmetricPermutationProduct<_MatrixTypeNested,UpLo>(m_matrix, perm);
     }
@@ -141,6 +122,20 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
       permutedMatrix.evalTo(*this);
       return *this;
     }
+
+
+    SparseSelfAdjointView& operator=(const SparseSelfAdjointView& src)
+    {
+      PermutationMatrix<Dynamic> pnull;
+      return *this = src.twistedBy(pnull);
+    }
+
+    template<typename SrcMatrixType,unsigned int SrcUpLo>
+    SparseSelfAdjointView& operator=(const SparseSelfAdjointView<SrcMatrixType,SrcUpLo>& src)
+    {
+      PermutationMatrix<Dynamic> pnull;
+      return *this = src.twistedBy(pnull);
+    }
     
 
     // const SparseLLT<PlainObject, UpLo> llt() const;
@@ -148,7 +143,7 @@ template<typename MatrixType, unsigned int UpLo> class SparseSelfAdjointView
 
   protected:
 
-    const typename MatrixType::Nested m_matrix;
+    typename MatrixType::Nested m_matrix;
     mutable VectorI m_countPerRow;
     mutable VectorI m_countPerCol;
 };
@@ -230,12 +225,15 @@ class SparseSelfAdjointTimeDenseProduct
       for (Index j=0; j<m_lhs.outerSize(); ++j)
       {
         LhsInnerIterator i(m_lhs,j);
-        if (ProcessSecondHalf && i && (i.index()==j))
+        if (ProcessSecondHalf)
         {
-          dest.row(j) += i.value() * m_rhs.row(j);
-          ++i;
+          while (i && i.index()<j) ++i;
+          if(i && i.index()==j)
+          {
+            dest.row(j) += i.value() * m_rhs.row(j);
+            ++i;
+          }
         }
-        Block<Dest,1,Dest::ColsAtCompileTime> dest_j(dest.row(LhsIsRowMajor ? j : 0));
         for(; (ProcessFirstHalf ? i && i.index() < j : i) ; ++i)
         {
           Index a = LhsIsRowMajor ? j : i.index();
@@ -300,7 +298,7 @@ void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename Matri
   enum {
     StorageOrderMatch = int(Dest::IsRowMajor) == int(MatrixType::IsRowMajor)
   };
-  eigen_assert(perm==0);
+  
   Index size = mat.rows();
   VectorI count;
   count.resize(size);
@@ -312,10 +310,14 @@ void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename Matri
     for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
     {
       Index i = it.index();
+      Index r = it.row();
+      Index c = it.col();
       Index ip = perm ? perm[i] : i;
-      if(i==j)
+      if(UpLo==(Upper|Lower))
+        count[StorageOrderMatch ? jp : ip]++;
+      else if(r==c)
         count[ip]++;
-      else if((UpLo==Lower && i>j) || (UpLo==Upper && i<j))
+      else if(( UpLo==Lower && r>c) || ( UpLo==Upper && r<c))
       {
         count[ip]++;
         count[jp]++;
@@ -325,49 +327,65 @@ void permute_symm_to_fullsymm(const MatrixType& mat, SparseMatrix<typename Matri
   Index nnz = count.sum();
   
   // reserve space
-  dest.reserve(nnz);
-  dest._outerIndexPtr()[0] = 0;
+  dest.resizeNonZeros(nnz);
+  dest.outerIndexPtr()[0] = 0;
   for(Index j=0; j<size; ++j)
-    dest._outerIndexPtr()[j+1] = dest._outerIndexPtr()[j] + count[j];
+    dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
   for(Index j=0; j<size; ++j)
-    count[j] = dest._outerIndexPtr()[j];
+    count[j] = dest.outerIndexPtr()[j];
   
   // copy data
   for(Index j = 0; j<size; ++j)
   {
-    Index jp = perm ? perm[j] : j;
     for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
     {
       Index i = it.index();
+      Index r = it.row();
+      Index c = it.col();
+      
+      Index jp = perm ? perm[j] : j;
       Index ip = perm ? perm[i] : i;
-      if(i==j)
+      
+      if(UpLo==(Upper|Lower))
+      {
+        Index k = count[StorageOrderMatch ? jp : ip]++;
+        dest.innerIndexPtr()[k] = StorageOrderMatch ? ip : jp;
+        dest.valuePtr()[k] = it.value();
+      }
+      else if(r==c)
       {
-        int k = count[ip]++;
-        dest._innerIndexPtr()[k] = ip;
-        dest._valuePtr()[k] = it.value();
+        Index k = count[ip]++;
+        dest.innerIndexPtr()[k] = ip;
+        dest.valuePtr()[k] = it.value();
       }
-      else if((UpLo==Lower && i>j) || (UpLo==Upper && i<j))
+      else if(( (UpLo&Lower)==Lower && r>c) || ( (UpLo&Upper)==Upper && r<c))
       {
-        int k = count[jp]++;
-        dest._innerIndexPtr()[k] = ip;
-        dest._valuePtr()[k] = it.value();
+        if(!StorageOrderMatch)
+          std::swap(ip,jp);
+        Index k = count[jp]++;
+        dest.innerIndexPtr()[k] = ip;
+        dest.valuePtr()[k] = it.value();
         k = count[ip]++;
-        dest._innerIndexPtr()[k] = jp;
-        dest._valuePtr()[k] = internal::conj(it.value());
+        dest.innerIndexPtr()[k] = jp;
+        dest.valuePtr()[k] = internal::conj(it.value());
       }
     }
   }
 }
 
-template<int SrcUpLo,int DstUpLo,typename MatrixType,int DestOrder>
-void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DestOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
+template<int _SrcUpLo,int _DstUpLo,typename MatrixType,int DstOrder>
+void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixType::Scalar,DstOrder,typename MatrixType::Index>& _dest, const typename MatrixType::Index* perm)
 {
   typedef typename MatrixType::Index Index;
   typedef typename MatrixType::Scalar Scalar;
-  typedef SparseMatrix<Scalar,DestOrder,Index> Dest;
-  Dest& dest(_dest.derived());
+  SparseMatrix<Scalar,DstOrder,Index>& dest(_dest.derived());
   typedef Matrix<Index,Dynamic,1> VectorI;
-  //internal::conj_if<SrcUpLo!=DstUpLo> cj;
+  enum {
+    SrcOrder = MatrixType::IsRowMajor ? RowMajor : ColMajor,
+    StorageOrderMatch = int(SrcOrder) == int(DstOrder),
+    DstUpLo = DstOrder==RowMajor ? (_DstUpLo==Upper ? Lower : Upper) : _DstUpLo,
+    SrcUpLo = SrcOrder==RowMajor ? (_SrcUpLo==Upper ? Lower : Upper) : _SrcUpLo
+  };
   
   Index size = mat.rows();
   VectorI count(size);
@@ -379,37 +397,40 @@ void permute_symm_to_symm(const MatrixType& mat, SparseMatrix<typename MatrixTyp
     for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
     {
       Index i = it.index();
-      if((SrcUpLo==Lower && i<j) || (SrcUpLo==Upper && i>j))
+      if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
         continue;
                   
       Index ip = perm ? perm[i] : i;
-      count[DstUpLo==Lower ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
+      count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
     }
   }
-  dest._outerIndexPtr()[0] = 0;
+  dest.outerIndexPtr()[0] = 0;
   for(Index j=0; j<size; ++j)
-    dest._outerIndexPtr()[j+1] = dest._outerIndexPtr()[j] + count[j];
-  dest.resizeNonZeros(dest._outerIndexPtr()[size]);
+    dest.outerIndexPtr()[j+1] = dest.outerIndexPtr()[j] + count[j];
+  dest.resizeNonZeros(dest.outerIndexPtr()[size]);
   for(Index j=0; j<size; ++j)
-    count[j] = dest._outerIndexPtr()[j];
+    count[j] = dest.outerIndexPtr()[j];
   
   for(Index j = 0; j<size; ++j)
   {
-    Index jp = perm ? perm[j] : j;
+    
     for(typename MatrixType::InnerIterator it(mat,j); it; ++it)
     {
       Index i = it.index();
-      if((SrcUpLo==Lower && i<j) || (SrcUpLo==Upper && i>j))
+      if((int(SrcUpLo)==int(Lower) && i<j) || (int(SrcUpLo)==int(Upper) && i>j))
         continue;
                   
+      Index jp = perm ? perm[j] : j;
       Index ip = perm? perm[i] : i;
-      Index k = count[DstUpLo==Lower ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
-      dest._innerIndexPtr()[k] = DstUpLo==Lower ? (std::max)(ip,jp) : (std::min)(ip,jp);
       
-      if((DstUpLo==Lower && ip<jp) || (DstUpLo==Upper && ip>jp))
-        dest._valuePtr()[k] = conj(it.value());
+      Index k = count[int(DstUpLo)==int(Lower) ? (std::min)(ip,jp) : (std::max)(ip,jp)]++;
+      dest.innerIndexPtr()[k] = int(DstUpLo)==int(Lower) ? (std::max)(ip,jp) : (std::min)(ip,jp);
+      
+      if(!StorageOrderMatch) std::swap(ip,jp);
+      if( ((int(DstUpLo)==int(Lower) && ip<jp) || (int(DstUpLo)==int(Upper) && ip>jp)))
+        dest.valuePtr()[k] = conj(it.value());
       else
-        dest._valuePtr()[k] = it.value();
+        dest.valuePtr()[k] = it.value();
     }
   }
 }
@@ -420,10 +441,12 @@ template<typename MatrixType,int UpLo>
 class SparseSymmetricPermutationProduct
   : public EigenBase<SparseSymmetricPermutationProduct<MatrixType,UpLo> >
 {
-    typedef PermutationMatrix<Dynamic> Perm;
   public:
     typedef typename MatrixType::Scalar Scalar;
     typedef typename MatrixType::Index Index;
+  protected:
+    typedef PermutationMatrix<Dynamic,Dynamic,Index> Perm;
+  public:
     typedef Matrix<Index,Dynamic,1> VectorI;
     typedef typename MatrixType::Nested MatrixTypeNested;
     typedef typename internal::remove_all<MatrixTypeNested>::type _MatrixTypeNested;
@@ -435,7 +458,8 @@ class SparseSymmetricPermutationProduct
     inline Index rows() const { return m_matrix.rows(); }
     inline Index cols() const { return m_matrix.cols(); }
     
-    template<typename DestScalar> void evalTo(SparseMatrix<DestScalar>& _dest) const
+    template<typename DestScalar, int Options, typename DstIndex>
+    void evalTo(SparseMatrix<DestScalar,Options,DstIndex>& _dest) const
     {
       internal::permute_symm_to_fullsymm<UpLo>(m_matrix,_dest,m_perm.indices().data());
     }
@@ -446,9 +470,11 @@ class SparseSymmetricPermutationProduct
     }
     
   protected:
-    const MatrixTypeNested m_matrix;
+    MatrixTypeNested m_matrix;
     const Perm& m_perm;
 
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
diff --git a/extern/Eigen3/Eigen/src/SparseCore/SparseSparseProductWithPruning.h b/extern/Eigen3/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
new file mode 100644
index 00000000000..2438ac573d0
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseSparseProductWithPruning.h
@@ -0,0 +1,149 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H
+#define EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H
+
+namespace Eigen { 
+
+namespace internal {
+
+
+// perform a pseudo in-place sparse * sparse product assuming all matrices are col major
+template<typename Lhs, typename Rhs, typename ResultType>
+static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, typename ResultType::RealScalar tolerance)
+{
+  // return sparse_sparse_product_with_pruning_impl2(lhs,rhs,res);
+
+  typedef typename remove_all<Lhs>::type::Scalar Scalar;
+  typedef typename remove_all<Lhs>::type::Index Index;
+
+  // make sure to call innerSize/outerSize since we fake the storage order.
+  Index rows = lhs.innerSize();
+  Index cols = rhs.outerSize();
+  //int size = lhs.outerSize();
+  eigen_assert(lhs.outerSize() == rhs.innerSize());
+
+  // allocate a temporary buffer
+  AmbiVector<Scalar,Index> tempVector(rows);
+
+  // estimate the number of non zero entries
+  // given a rhs column containing Y non zeros, we assume that the respective Y columns
+  // of the lhs differs in average of one non zeros, thus the number of non zeros for
+  // the product of a rhs column with the lhs is X+Y where X is the average number of non zero
+  // per column of the lhs.
+  // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs)
+  Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros();
+
+  // mimics a resizeByInnerOuter:
+  if(ResultType::IsRowMajor)
+    res.resize(cols, rows);
+  else
+    res.resize(rows, cols);
+
+  res.reserve(estimated_nnz_prod);
+  double ratioColRes = double(estimated_nnz_prod)/double(lhs.rows()*rhs.cols());
+  for (Index j=0; j<cols; ++j)
+  {
+    // FIXME:
+    //double ratioColRes = (double(rhs.innerVector(j).nonZeros()) + double(lhs.nonZeros())/double(lhs.cols()))/double(lhs.rows());
+    // let's do a more accurate determination of the nnz ratio for the current column j of res
+    tempVector.init(ratioColRes);
+    tempVector.setZero();
+    for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
+    {
+      // FIXME should be written like this: tmp += rhsIt.value() * lhs.col(rhsIt.index())
+      tempVector.restart();
+      Scalar x = rhsIt.value();
+      for (typename Lhs::InnerIterator lhsIt(lhs, rhsIt.index()); lhsIt; ++lhsIt)
+      {
+        tempVector.coeffRef(lhsIt.index()) += lhsIt.value() * x;
+      }
+    }
+    res.startVec(j);
+    for (typename AmbiVector<Scalar,Index>::Iterator it(tempVector,tolerance); it; ++it)
+      res.insertBackByOuterInner(j,it.index()) = it.value();
+  }
+  res.finalize();
+}
+
+template<typename Lhs, typename Rhs, typename ResultType,
+  int LhsStorageOrder = traits<Lhs>::Flags&RowMajorBit,
+  int RhsStorageOrder = traits<Rhs>::Flags&RowMajorBit,
+  int ResStorageOrder = traits<ResultType>::Flags&RowMajorBit>
+struct sparse_sparse_product_with_pruning_selector;
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,ColMajor>
+{
+  typedef typename traits<typename remove_all<Lhs>::type>::Scalar Scalar;
+  typedef typename ResultType::RealScalar RealScalar;
+
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+  {
+    typename remove_all<ResultType>::type _res(res.rows(), res.cols());
+    internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,ResultType>(lhs, rhs, _res, tolerance);
+    res.swap(_res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,ColMajor,ColMajor,RowMajor>
+{
+  typedef typename ResultType::RealScalar RealScalar;
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+  {
+    // we need a col-major matrix to hold the result
+    typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType;
+    SparseTemporaryType _res(res.rows(), res.cols());
+    internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, _res, tolerance);
+    res = _res;
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,RowMajor>
+{
+  typedef typename ResultType::RealScalar RealScalar;
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+  {
+    // let's transpose the product to get a column x column product
+    typename remove_all<ResultType>::type _res(res.rows(), res.cols());
+    internal::sparse_sparse_product_with_pruning_impl<Rhs,Lhs,ResultType>(rhs, lhs, _res, tolerance);
+    res.swap(_res);
+  }
+};
+
+template<typename Lhs, typename Rhs, typename ResultType>
+struct sparse_sparse_product_with_pruning_selector<Lhs,Rhs,ResultType,RowMajor,RowMajor,ColMajor>
+{
+  typedef typename ResultType::RealScalar RealScalar;
+  static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, RealScalar tolerance)
+  {
+    typedef SparseMatrix<typename ResultType::Scalar,ColMajor> ColMajorMatrix;
+    ColMajorMatrix colLhs(lhs);
+    ColMajorMatrix colRhs(rhs);
+    internal::sparse_sparse_product_with_pruning_impl<ColMajorMatrix,ColMajorMatrix,ResultType>(colLhs, colRhs, res, tolerance);
+
+    // let's transpose the product to get a column x column product
+//     typedef SparseMatrix<typename ResultType::Scalar> SparseTemporaryType;
+//     SparseTemporaryType _res(res.cols(), res.rows());
+//     sparse_sparse_product_with_pruning_impl<Rhs,Lhs,SparseTemporaryType>(rhs, lhs, _res);
+//     res = _res.transpose();
+  }
+};
+
+// NOTE the 2 others cases (col row *) must never occur since they are caught
+// by ProductReturnType which transforms it to (col col *) by evaluating rhs.
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSESPARSEPRODUCTWITHPRUNING_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseTranspose.h b/extern/Eigen3/Eigen/src/SparseCore/SparseTranspose.h
index 2aea2fa32c7..273f9de688f 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseTranspose.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseTranspose.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSETRANSPOSE_H
 #define EIGEN_SPARSETRANSPOSE_H
 
+namespace Eigen { 
+
 template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>
   : public SparseMatrixBase<Transpose<MatrixType> >
 {
@@ -39,17 +26,21 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>
     inline Index nonZeros() const { return derived().nestedExpression().nonZeros(); }
 };
 
+// NOTE: VC10 trigger an ICE if don't put typename TransposeImpl<MatrixType,Sparse>:: in front of Index,
+// a typedef typename TransposeImpl<MatrixType,Sparse>::Index Index;
+// does not fix the issue.
+// An alternative is to define the nested class in the parent class itself.
 template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::InnerIterator
   : public _MatrixTypeNested::InnerIterator
 {
     typedef typename _MatrixTypeNested::InnerIterator Base;
   public:
 
-    EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, Index outer)
+    EIGEN_STRONG_INLINE InnerIterator(const TransposeImpl& trans, typename TransposeImpl<MatrixType,Sparse>::Index outer)
       : Base(trans.derived().nestedExpression(), outer)
     {}
-    inline Index row() const { return Base::col(); }
-    inline Index col() const { return Base::row(); }
+    inline typename TransposeImpl<MatrixType,Sparse>::Index row() const { return Base::col(); }
+    inline typename TransposeImpl<MatrixType,Sparse>::Index col() const { return Base::row(); }
 };
 
 template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::ReverseInnerIterator
@@ -58,11 +49,13 @@ template<typename MatrixType> class TransposeImpl<MatrixType,Sparse>::ReverseInn
     typedef typename _MatrixTypeNested::ReverseInnerIterator Base;
   public:
 
-    EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, Index outer)
+    EIGEN_STRONG_INLINE ReverseInnerIterator(const TransposeImpl& xpr, typename TransposeImpl<MatrixType,Sparse>::Index outer)
       : Base(xpr.derived().nestedExpression(), outer)
     {}
-    inline Index row() const { return Base::col(); }
-    inline Index col() const { return Base::row(); }
+    inline typename TransposeImpl<MatrixType,Sparse>::Index row() const { return Base::col(); }
+    inline typename TransposeImpl<MatrixType,Sparse>::Index col() const { return Base::row(); }
 };
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSETRANSPOSE_H
diff --git a/extern/Eigen3/Eigen/src/SparseCore/SparseTriangularView.h b/extern/Eigen3/Eigen/src/SparseCore/SparseTriangularView.h
new file mode 100644
index 00000000000..477e4bd94b0
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseTriangularView.h
@@ -0,0 +1,164 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_TRIANGULARVIEW_H
+#define EIGEN_SPARSE_TRIANGULARVIEW_H
+
+namespace Eigen { 
+
+namespace internal {
+  
+template<typename MatrixType, int Mode>
+struct traits<SparseTriangularView<MatrixType,Mode> >
+: public traits<MatrixType>
+{};
+
+} // namespace internal
+
+template<typename MatrixType, int Mode> class SparseTriangularView
+  : public SparseMatrixBase<SparseTriangularView<MatrixType,Mode> >
+{
+    enum { SkipFirst = ((Mode&Lower) && !(MatrixType::Flags&RowMajorBit))
+                    || ((Mode&Upper) &&  (MatrixType::Flags&RowMajorBit)),
+           SkipLast = !SkipFirst,
+           HasUnitDiag = (Mode&UnitDiag) ? 1 : 0
+    };
+
+  public:
+    
+    EIGEN_SPARSE_PUBLIC_INTERFACE(SparseTriangularView)
+
+    class InnerIterator;
+    class ReverseInnerIterator;
+
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+
+    typedef typename MatrixType::Nested MatrixTypeNested;
+    typedef typename internal::remove_reference<MatrixTypeNested>::type MatrixTypeNestedNonRef;
+    typedef typename internal::remove_all<MatrixTypeNested>::type MatrixTypeNestedCleaned;
+
+    inline SparseTriangularView(const MatrixType& matrix) : m_matrix(matrix) {}
+
+    /** \internal */
+    inline const MatrixTypeNestedCleaned& nestedExpression() const { return m_matrix; }
+
+    template<typename OtherDerived>
+    typename internal::plain_matrix_type_column_major<OtherDerived>::type
+    solve(const MatrixBase<OtherDerived>& other) const;
+
+    template<typename OtherDerived> void solveInPlace(MatrixBase<OtherDerived>& other) const;
+    template<typename OtherDerived> void solveInPlace(SparseMatrixBase<OtherDerived>& other) const;
+
+  protected:
+    MatrixTypeNested m_matrix;
+};
+
+template<typename MatrixType, int Mode>
+class SparseTriangularView<MatrixType,Mode>::InnerIterator : public MatrixTypeNestedCleaned::InnerIterator
+{
+    typedef typename MatrixTypeNestedCleaned::InnerIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE InnerIterator(const SparseTriangularView& view, Index outer)
+      : Base(view.nestedExpression(), outer), m_returnOne(false)
+    {
+      if(SkipFirst)
+      {
+        while((*this) && (HasUnitDiag ? this->index()<=outer : this->index()<outer))
+          Base::operator++();
+        if(HasUnitDiag)
+          m_returnOne = true;
+      }
+      else if(HasUnitDiag && ((!Base::operator bool()) || Base::index()>=Base::outer()))
+      {
+        if((!SkipFirst) && Base::operator bool())
+          Base::operator++();
+        m_returnOne = true;
+      }
+    }
+
+    EIGEN_STRONG_INLINE InnerIterator& operator++()
+    {
+      if(HasUnitDiag && m_returnOne)
+        m_returnOne = false;
+      else
+      {
+        Base::operator++();
+        if(HasUnitDiag && (!SkipFirst) && ((!Base::operator bool()) || Base::index()>=Base::outer()))
+        {
+          if((!SkipFirst) && Base::operator bool())
+            Base::operator++();
+          m_returnOne = true;
+        }
+      }
+      return *this;
+    }
+
+    inline Index row() const { return Base::row(); }
+    inline Index col() const { return Base::col(); }
+    inline Index index() const
+    {
+      if(HasUnitDiag && m_returnOne)  return Base::outer();
+      else                            return Base::index();
+    }
+    inline Scalar value() const
+    {
+      if(HasUnitDiag && m_returnOne)  return Scalar(1);
+      else                            return Base::value();
+    }
+
+    EIGEN_STRONG_INLINE operator bool() const
+    {
+      if(HasUnitDiag && m_returnOne)
+        return true;
+      return (SkipFirst ? Base::operator bool() : (Base::operator bool() && this->index() <= this->outer()));
+    }
+  protected:
+    bool m_returnOne;
+};
+
+template<typename MatrixType, int Mode>
+class SparseTriangularView<MatrixType,Mode>::ReverseInnerIterator : public MatrixTypeNestedCleaned::ReverseInnerIterator
+{
+    typedef typename MatrixTypeNestedCleaned::ReverseInnerIterator Base;
+  public:
+
+    EIGEN_STRONG_INLINE ReverseInnerIterator(const SparseTriangularView& view, Index outer)
+      : Base(view.nestedExpression(), outer)
+    {
+      eigen_assert((!HasUnitDiag) && "ReverseInnerIterator does not support yet triangular views with a unit diagonal");
+      if(SkipLast)
+        while((*this) && this->index()>outer)
+          --(*this);
+    }
+
+    EIGEN_STRONG_INLINE InnerIterator& operator--()
+    { Base::operator--(); return *this; }
+
+    inline Index row() const { return Base::row(); }
+    inline Index col() const { return Base::col(); }
+
+    EIGEN_STRONG_INLINE operator bool() const
+    {
+      return SkipLast ? Base::operator bool() : (Base::operator bool() && this->index() >= this->outer());
+    }
+};
+
+template<typename Derived>
+template<int Mode>
+inline const SparseTriangularView<Derived, Mode>
+SparseMatrixBase<Derived>::triangularView() const
+{
+  return derived();
+}
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_TRIANGULARVIEW_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseUtil.h b/extern/Eigen3/Eigen/src/SparseCore/SparseUtil.h
index db9ae98e7a0..6062a086ff7 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseUtil.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseUtil.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSEUTIL_H
 #define EIGEN_SPARSEUTIL_H
 
+namespace Eigen { 
+
 #ifdef NDEBUG
 #define EIGEN_DBG_SPARSE(X)
 #else
@@ -58,22 +45,22 @@ EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(Derived, /=)
 
 #define _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, BaseClass) \
   typedef BaseClass Base; \
-  typedef typename Eigen::internal::traits<Derived>::Scalar Scalar; \
+  typedef typename Eigen::internal::traits<Derived >::Scalar Scalar; \
   typedef typename Eigen::NumTraits<Scalar>::Real RealScalar; \
-  typedef typename Eigen::internal::nested<Derived>::type Nested; \
-  typedef typename Eigen::internal::traits<Derived>::StorageKind StorageKind; \
-  typedef typename Eigen::internal::traits<Derived>::Index Index; \
-  enum { RowsAtCompileTime = Eigen::internal::traits<Derived>::RowsAtCompileTime, \
-        ColsAtCompileTime = Eigen::internal::traits<Derived>::ColsAtCompileTime, \
-        Flags = Eigen::internal::traits<Derived>::Flags, \
-        CoeffReadCost = Eigen::internal::traits<Derived>::CoeffReadCost, \
+  typedef typename Eigen::internal::nested<Derived >::type Nested; \
+  typedef typename Eigen::internal::traits<Derived >::StorageKind StorageKind; \
+  typedef typename Eigen::internal::traits<Derived >::Index Index; \
+  enum { RowsAtCompileTime = Eigen::internal::traits<Derived >::RowsAtCompileTime, \
+        ColsAtCompileTime = Eigen::internal::traits<Derived >::ColsAtCompileTime, \
+        Flags = Eigen::internal::traits<Derived >::Flags, \
+        CoeffReadCost = Eigen::internal::traits<Derived >::CoeffReadCost, \
         SizeAtCompileTime = Base::SizeAtCompileTime, \
         IsVectorAtCompileTime = Base::IsVectorAtCompileTime }; \
   using Base::derived; \
   using Base::const_cast_derived;
 
 #define EIGEN_SPARSE_PUBLIC_INTERFACE(Derived) \
-  _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase<Derived>)
+  _EIGEN_SPARSE_PUBLIC_INTERFACE(Derived, Eigen::SparseMatrixBase<Derived >)
 
 const int CoherentAccessPattern     = 0x1;
 const int InnerRandomAccessPattern  = 0x2 | CoherentAccessPattern;
@@ -100,20 +87,43 @@ template<typename Lhs, typename Rhs, bool Transpose> class SparseDenseOuterProdu
 template<typename Lhs, typename Rhs> struct SparseSparseProductReturnType;
 template<typename Lhs, typename Rhs, int InnerSize = internal::traits<Lhs>::ColsAtCompileTime> struct DenseSparseProductReturnType;
 template<typename Lhs, typename Rhs, int InnerSize = internal::traits<Lhs>::ColsAtCompileTime> struct SparseDenseProductReturnType;
+template<typename MatrixType,int UpLo> class SparseSymmetricPermutationProduct;
 
 namespace internal {
 
+template<typename T,int Rows,int Cols> struct sparse_eval;
+
 template<typename T> struct eval<T,Sparse>
-{
+  : public sparse_eval<T, traits<T>::RowsAtCompileTime,traits<T>::ColsAtCompileTime>
+{};
+
+template<typename T,int Cols> struct sparse_eval<T,1,Cols> {
     typedef typename traits<T>::Scalar _Scalar;
-    enum {
-          _Flags = traits<T>::Flags
-    };
+    enum { _Flags = traits<T>::Flags| RowMajorBit };
+  public:
+    typedef SparseVector<_Scalar, _Flags> type;
+};
 
+template<typename T,int Rows> struct sparse_eval<T,Rows,1> {
+    typedef typename traits<T>::Scalar _Scalar;
+    enum { _Flags = traits<T>::Flags & (~RowMajorBit) };
+  public:
+    typedef SparseVector<_Scalar, _Flags> type;
+};
+
+template<typename T,int Rows,int Cols> struct sparse_eval {
+    typedef typename traits<T>::Scalar _Scalar;
+    enum { _Flags = traits<T>::Flags };
   public:
     typedef SparseMatrix<_Scalar, _Flags> type;
 };
 
+template<typename T> struct sparse_eval<T,1,1> {
+    typedef typename traits<T>::Scalar _Scalar;
+  public:
+    typedef Matrix<_Scalar, 1, 1> type;
+};
+
 template<typename T> struct plain_matrix_type<T,Sparse>
 {
   typedef typename traits<T>::Scalar _Scalar;
@@ -127,4 +137,37 @@ template<typename T> struct plain_matrix_type<T,Sparse>
 
 } // end namespace internal
 
+/** \ingroup SparseCore_Module
+  *
+  * \class Triplet
+  *
+  * \brief A small structure to hold a non zero as a triplet (i,j,value).
+  *
+  * \sa SparseMatrix::setFromTriplets()
+  */
+template<typename Scalar, typename Index=unsigned int>
+class Triplet
+{
+public:
+  Triplet() : m_row(0), m_col(0), m_value(0) {}
+
+  Triplet(const Index& i, const Index& j, const Scalar& v = Scalar(0))
+    : m_row(i), m_col(j), m_value(v)
+  {}
+
+  /** \returns the row index of the element */
+  const Index& row() const { return m_row; }
+
+  /** \returns the column index of the element */
+  const Index& col() const { return m_col; }
+
+  /** \returns the value of the element */
+  const Scalar& value() const { return m_value; }
+protected:
+  Index m_row, m_col;
+  Scalar m_value;
+};
+
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSEUTIL_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseVector.h b/extern/Eigen3/Eigen/src/SparseCore/SparseVector.h
index ce4bb51a27e..c952f654038 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseVector.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseVector.h
@@ -3,29 +3,17 @@
 //
 // Copyright (C) 2008-2009 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSEVECTOR_H
 #define EIGEN_SPARSEVECTOR_H
 
-/** \class SparseVector
+namespace Eigen { 
+
+/** \ingroup SparseCore_Module
+  * \class SparseVector
   *
   * \brief a sparse vector class
   *
@@ -46,13 +34,13 @@ struct traits<SparseVector<_Scalar, _Options, _Index> >
   typedef Sparse StorageKind;
   typedef MatrixXpr XprKind;
   enum {
-    IsColVector = _Options & RowMajorBit ? 0 : 1,
+    IsColVector = (_Options & RowMajorBit) ? 0 : 1,
 
     RowsAtCompileTime = IsColVector ? Dynamic : 1,
     ColsAtCompileTime = IsColVector ? 1 : Dynamic,
     MaxRowsAtCompileTime = RowsAtCompileTime,
     MaxColsAtCompileTime = ColsAtCompileTime,
-    Flags = _Options | NestByRefBit | LvalueBit,
+    Flags = _Options | NestByRefBit | LvalueBit | (IsColVector ? 0 : RowMajorBit),
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
     SupportedAccessPatterns = InnerRandomAccessPattern
   };
@@ -67,7 +55,6 @@ class SparseVector
     EIGEN_SPARSE_PUBLIC_INTERFACE(SparseVector)
     EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, +=)
     EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, -=)
-//     EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(SparseVector, =)
 
   protected:
   public:
@@ -79,11 +66,11 @@ class SparseVector
       Options = _Options
     };
 
-    CompressedStorage<Scalar,Index> m_data;
+    internal::CompressedStorage<Scalar,Index> m_data;
     Index m_size;
 
-    CompressedStorage<Scalar,Index>& _data() { return m_data; }
-    CompressedStorage<Scalar,Index>& _data() const { return m_data; }
+    internal::CompressedStorage<Scalar,Index>& _data() { return m_data; }
+    internal::CompressedStorage<Scalar,Index>& _data() const { return m_data; }
 
   public:
 
@@ -91,13 +78,12 @@ class SparseVector
     EIGEN_STRONG_INLINE Index cols() const { return IsColVector ? 1 : m_size; }
     EIGEN_STRONG_INLINE Index innerSize() const { return m_size; }
     EIGEN_STRONG_INLINE Index outerSize() const { return 1; }
-    EIGEN_STRONG_INLINE Index innerNonZeros(Index j) const { eigen_assert(j==0); return m_size; }
 
-    EIGEN_STRONG_INLINE const Scalar* _valuePtr() const { return &m_data.value(0); }
-    EIGEN_STRONG_INLINE Scalar* _valuePtr() { return &m_data.value(0); }
+    EIGEN_STRONG_INLINE const Scalar* valuePtr() const { return &m_data.value(0); }
+    EIGEN_STRONG_INLINE Scalar* valuePtr() { return &m_data.value(0); }
 
-    EIGEN_STRONG_INLINE const Index* _innerIndexPtr() const { return &m_data.index(0); }
-    EIGEN_STRONG_INLINE Index* _innerIndexPtr() { return &m_data.index(0); }
+    EIGEN_STRONG_INLINE const Index* innerIndexPtr() const { return &m_data.index(0); }
+    EIGEN_STRONG_INLINE Index* innerIndexPtr() { return &m_data.index(0); }
 
     inline Scalar coeff(Index row, Index col) const
     {
@@ -126,6 +112,7 @@ class SparseVector
   public:
 
     class InnerIterator;
+    class ReverseInnerIterator;
 
     inline void setZero() { m_data.clear(); }
 
@@ -134,11 +121,13 @@ class SparseVector
 
     inline void startVec(Index outer)
     {
+      EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
     }
 
     inline Scalar& insertBackByOuterInner(Index outer, Index inner)
     {
+      EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
       return insertBack(inner);
     }
@@ -158,7 +147,7 @@ class SparseVector
     Scalar& insert(Index i)
     {
       Index startId = 0;
-      Index p = m_data.size() - 1;
+      Index p = Index(m_data.size()) - 1;
       // TODO smart realloc
       m_data.resize(p+2,1);
 
@@ -206,13 +195,6 @@ class SparseVector
     inline SparseVector(Index rows, Index cols) : m_size(0) { resize(rows,cols); }
 
     template<typename OtherDerived>
-    inline SparseVector(const MatrixBase<OtherDerived>& other)
-      : m_size(0)
-    {
-      *this = other.derived();
-    }
-
-    template<typename OtherDerived>
     inline SparseVector(const SparseMatrixBase<OtherDerived>& other)
       : m_size(0)
     {
@@ -249,9 +231,9 @@ class SparseVector
     inline SparseVector& operator=(const SparseMatrixBase<OtherDerived>& other)
     {
       if (int(RowsAtCompileTime)!=int(OtherDerived::RowsAtCompileTime))
-        return Base::operator=(other.transpose());
+        return assign(other.transpose());
       else
-        return Base::operator=(other);
+        return assign(other);
     }
 
     #ifndef EIGEN_PARSED_BY_DOXYGEN
@@ -262,56 +244,6 @@ class SparseVector
     }
     #endif
 
-//       const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
-//       if (needToTranspose)
-//       {
-//         // two passes algorithm:
-//         //  1 - compute the number of coeffs per dest inner vector
-//         //  2 - do the actual copy/eval
-//         // Since each coeff of the rhs has to be evaluated twice, let's evauluate it if needed
-//         typedef typename internal::nested<OtherDerived,2>::type OtherCopy;
-//         OtherCopy otherCopy(other.derived());
-//         typedef typename internal::remove_all<OtherCopy>::type _OtherCopy;
-//
-//         resize(other.rows(), other.cols());
-//         Eigen::Map<VectorXi>(m_outerIndex,outerSize()).setZero();
-//         // pass 1
-//         // FIXME the above copy could be merged with that pass
-//         for (int j=0; j<otherCopy.outerSize(); ++j)
-//           for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
-//             ++m_outerIndex[it.index()];
-//
-//         // prefix sum
-//         int count = 0;
-//         VectorXi positions(outerSize());
-//         for (int j=0; j<outerSize(); ++j)
-//         {
-//           int tmp = m_outerIndex[j];
-//           m_outerIndex[j] = count;
-//           positions[j] = count;
-//           count += tmp;
-//         }
-//         m_outerIndex[outerSize()] = count;
-//         // alloc
-//         m_data.resize(count);
-//         // pass 2
-//         for (int j=0; j<otherCopy.outerSize(); ++j)
-//           for (typename _OtherCopy::InnerIterator it(otherCopy, j); it; ++it)
-//           {
-//             int pos = positions[it.index()]++;
-//             m_data.index(pos) = j;
-//             m_data.value(pos) = it.value();
-//           }
-//
-//         return *this;
-//       }
-//       else
-//       {
-//         // there is no special optimization
-//         return SparseMatrixBase<SparseMatrix>::operator=(other.derived());
-//       }
-//     }
-
     friend std::ostream & operator << (std::ostream & s, const SparseVector& m)
     {
       for (Index i=0; i<m.nonZeros(); ++i)
@@ -320,28 +252,6 @@ class SparseVector
       return s;
     }
 
-    // this specialized version does not seems to be faster
-//     Scalar dot(const SparseVector& other) const
-//     {
-//       int i=0, j=0;
-//       Scalar res = 0;
-//       asm("#begindot");
-//       while (i<nonZeros() && j<other.nonZeros())
-//       {
-//         if (m_data.index(i)==other.m_data.index(j))
-//         {
-//           res += m_data.value(i) * internal::conj(other.m_data.value(j));
-//           ++i; ++j;
-//         }
-//         else if (m_data.index(i)<other.m_data.index(j))
-//           ++i;
-//         else
-//           ++j;
-//       }
-//       asm("#enddot");
-//       return res;
-//     }
-
     /** Destructor */
     inline ~SparseVector() {}
 
@@ -390,6 +300,33 @@ class SparseVector
 #   ifdef EIGEN_SPARSEVECTOR_PLUGIN
 #     include EIGEN_SPARSEVECTOR_PLUGIN
 #   endif
+
+protected:
+    template<typename OtherDerived>
+    EIGEN_DONT_INLINE SparseVector& assign(const SparseMatrixBase<OtherDerived>& _other)
+    {
+      const OtherDerived& other(_other.derived());
+      const bool needToTranspose = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit);
+      if(needToTranspose)
+      {
+        Index size = other.size();
+        Index nnz = other.nonZeros();
+        resize(size);
+        reserve(nnz);
+        for(Index i=0; i<size; ++i)
+        {
+          typename OtherDerived::InnerIterator it(other, i);
+          if(it)
+              insert(i) = it.value();
+        }
+        return *this;
+      }
+      else
+      {
+        // there is no special optimization
+        return Base::operator=(other);
+      }
+    }
 };
 
 template<typename Scalar, int _Options, typename _Index>
@@ -399,18 +336,14 @@ class SparseVector<Scalar,_Options,_Index>::InnerIterator
     InnerIterator(const SparseVector& vec, Index outer=0)
       : m_data(vec.m_data), m_id(0), m_end(static_cast<Index>(m_data.size()))
     {
+      EIGEN_UNUSED_VARIABLE(outer);
       eigen_assert(outer==0);
     }
 
-    InnerIterator(const CompressedStorage<Scalar,Index>& data)
+    InnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
       : m_data(data), m_id(0), m_end(static_cast<Index>(m_data.size()))
     {}
 
-    template<unsigned int Added, unsigned int Removed>
-    InnerIterator(const Flagged<SparseVector,Added,Removed>& vec, Index )
-      : m_data(vec._expression().m_data), m_id(0), m_end(m_data.size())
-    {}
-
     inline InnerIterator& operator++() { m_id++; return *this; }
 
     inline Scalar value() const { return m_data.value(m_id); }
@@ -423,9 +356,43 @@ class SparseVector<Scalar,_Options,_Index>::InnerIterator
     inline operator bool() const { return (m_id < m_end); }
 
   protected:
-    const CompressedStorage<Scalar,Index>& m_data;
+    const internal::CompressedStorage<Scalar,Index>& m_data;
     Index m_id;
     const Index m_end;
 };
 
+template<typename Scalar, int _Options, typename _Index>
+class SparseVector<Scalar,_Options,_Index>::ReverseInnerIterator
+{
+  public:
+    ReverseInnerIterator(const SparseVector& vec, Index outer=0)
+      : m_data(vec.m_data), m_id(static_cast<Index>(m_data.size())), m_start(0)
+    {
+      EIGEN_UNUSED_VARIABLE(outer);
+      eigen_assert(outer==0);
+    }
+
+    ReverseInnerIterator(const internal::CompressedStorage<Scalar,Index>& data)
+      : m_data(data), m_id(static_cast<Index>(m_data.size())), m_start(0)
+    {}
+
+    inline ReverseInnerIterator& operator--() { m_id--; return *this; }
+
+    inline Scalar value() const { return m_data.value(m_id-1); }
+    inline Scalar& valueRef() { return const_cast<Scalar&>(m_data.value(m_id-1)); }
+
+    inline Index index() const { return m_data.index(m_id-1); }
+    inline Index row() const { return IsColVector ? index() : 0; }
+    inline Index col() const { return IsColVector ? 0 : index(); }
+
+    inline operator bool() const { return (m_id > m_start); }
+
+  protected:
+    const internal::CompressedStorage<Scalar,Index>& m_data;
+    Index m_id;
+    const Index m_start;
+};
+
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSEVECTOR_H
diff --git a/extern/Eigen3/Eigen/src/Sparse/SparseView.h b/extern/Eigen3/Eigen/src/SparseCore/SparseView.h
index 24306561098..8b0b9ea0304 100644
--- a/extern/Eigen3/Eigen/src/Sparse/SparseView.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/SparseView.h
@@ -1,31 +1,18 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
-// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2010 Daniel Lowengrub <lowdanie@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSEVIEW_H
 #define EIGEN_SPARSEVIEW_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename MatrixType>
@@ -61,7 +48,7 @@ public:
   inline Index outerSize() const { return m_matrix.outerSize(); }
 
 protected:
-  const MatrixTypeNested m_matrix;
+  MatrixTypeNested m_matrix;
   Scalar m_reference;
   typename NumTraits<Scalar>::Real m_epsilon;
 };
@@ -92,10 +79,10 @@ protected:
 private:
   void incrementToNonZero()
   {
-    while(internal::isMuchSmallerThan(value(), m_view.m_reference, m_view.m_epsilon) && (bool(*this)))
-      {
-        IterBase::operator++();
-      }
+    while((bool(*this)) && internal::isMuchSmallerThan(value(), m_view.m_reference, m_view.m_epsilon))
+    {
+      IterBase::operator++();
+    }
   }
 };
 
@@ -106,4 +93,6 @@ const SparseView<Derived> MatrixBase<Derived>::sparseView(const Scalar& m_refere
   return SparseView<Derived>(derived(), m_reference, m_epsilon);
 }
 
+} // end namespace Eigen
+
 #endif
diff --git a/extern/Eigen3/Eigen/src/Sparse/TriangularSolver.h b/extern/Eigen3/Eigen/src/SparseCore/TriangularSolver.h
index 62bb8bb44c9..cb8ad82b4f6 100644
--- a/extern/Eigen3/Eigen/src/Sparse/TriangularSolver.h
+++ b/extern/Eigen3/Eigen/src/SparseCore/TriangularSolver.h
@@ -3,28 +3,15 @@
 //
 // 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
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_SPARSETRIANGULARSOLVER_H
 #define EIGEN_SPARSETRIANGULARSOLVER_H
 
+namespace Eigen { 
+
 namespace internal {
 
 template<typename Lhs, typename Rhs, int Mode,
@@ -48,7 +35,7 @@ struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,RowMajor>
       for(int i=0; i<lhs.rows(); ++i)
       {
         Scalar tmp = other.coeff(i,col);
-        Scalar lastVal = 0;
+        Scalar lastVal(0);
         int lastIndex = 0;
         for(typename Lhs::InnerIterator it(lhs, i); it; ++it)
         {
@@ -82,8 +69,17 @@ struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor>
       for(int i=lhs.rows()-1 ; i>=0 ; --i)
       {
         Scalar tmp = other.coeff(i,col);
+        Scalar l_ii = 0;
         typename Lhs::InnerIterator it(lhs, i);
-        if (it && it.index() == i)
+        while(it && it.index()<i)
+          ++it;
+        if(!(Mode & UnitDiag))
+        {
+          eigen_assert(it && it.index()==i);
+          l_ii = it.value();
+          ++it;
+        }
+        else if (it && it.index() == i)
           ++it;
         for(; it; ++it)
         {
@@ -93,11 +89,7 @@ struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,RowMajor>
         if (Mode & UnitDiag)
           other.coeffRef(i,col) = tmp;
         else
-        {
-          typename Lhs::InnerIterator it(lhs, i);
-          eigen_assert(it && it.index() == i);
-          other.coeffRef(i,col) = tmp/it.value();
-        }
+          other.coeffRef(i,col) = tmp/l_ii;
       }
     }
   }
@@ -118,9 +110,11 @@ struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Lower,ColMajor>
         if (tmp!=Scalar(0)) // optimization when other is actually sparse
         {
           typename Lhs::InnerIterator it(lhs, i);
+          while(it && it.index()<i)
+            ++it;
           if(!(Mode & UnitDiag))
           {
-            eigen_assert(it.index()==i);
+            eigen_assert(it && it.index()==i);
             tmp /= it.value();
           }
           if (it && it.index()==i)
@@ -149,9 +143,12 @@ struct sparse_solve_triangular_selector<Lhs,Rhs,Mode,Upper,ColMajor>
         {
           if(!(Mode & UnitDiag))
           {
-            // FIXME lhs.coeff(i,i) might not be always efficient while it must simply be the
-            // last element of the column !
-            other.coeffRef(i,col) /= lhs.innerVector(i).lastCoeff();
+            // TODO replace this by a binary search. make sure the binary search is safe for partially sorted elements
+            typename Lhs::ReverseInnerIterator it(lhs, i);
+            while(it && it.index()!=i)
+              --it;
+            eigen_assert(it && it.index()==i);
+            other.coeffRef(i,col) /= it.value();
           }
           typename Lhs::InnerIterator it(lhs, i);
           for(; it && it.index()<i; ++it)
@@ -168,10 +165,8 @@ template<typename ExpressionType,int Mode>
 template<typename OtherDerived>
 void SparseTriangularView<ExpressionType,Mode>::solveInPlace(MatrixBase<OtherDerived>& other) const
 {
-  eigen_assert(m_matrix.cols() == m_matrix.rows());
-  eigen_assert(m_matrix.cols() == other.rows());
-  eigen_assert(!(Mode & ZeroDiag));
-  eigen_assert((Mode & (Upper|Lower)) != 0);
+  eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows());
+  eigen_assert((!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
 
   enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit };
 
@@ -295,10 +290,8 @@ template<typename ExpressionType,int Mode>
 template<typename OtherDerived>
 void SparseTriangularView<ExpressionType,Mode>::solveInPlace(SparseMatrixBase<OtherDerived>& other) const
 {
-  eigen_assert(m_matrix.cols() == m_matrix.rows());
-  eigen_assert(m_matrix.cols() == other.rows());
-  eigen_assert(!(Mode & ZeroDiag));
-  eigen_assert((Mode & (Upper|Lower)) != 0);
+  eigen_assert(m_matrix.cols() == m_matrix.rows() && m_matrix.cols() == other.rows());
+  eigen_assert( (!(Mode & ZeroDiag)) && bool(Mode & (Upper|Lower)));
 
 //   enum { copy = internal::traits<OtherDerived>::Flags & RowMajorBit };
 
@@ -336,4 +329,6 @@ SparseMatrixBase<Derived>::solveTriangular(const MatrixBase<OtherDerived>& other
 }
 #endif // EIGEN2_SUPPORT
 
+} // end namespace Eigen
+
 #endif // EIGEN_SPARSETRIANGULARSOLVER_H
diff --git a/extern/Eigen3/Eigen/src/StlSupport/StdDeque.h b/extern/Eigen3/Eigen/src/StlSupport/StdDeque.h
index 6f12c106dbc..4ee8e5c10a5 100644
--- a/extern/Eigen3/Eigen/src/StlSupport/StdDeque.h
+++ b/extern/Eigen3/Eigen/src/StlSupport/StdDeque.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STDDEQUE_H
 #define EIGEN_STDDEQUE_H
diff --git a/extern/Eigen3/Eigen/src/StlSupport/StdList.h b/extern/Eigen3/Eigen/src/StlSupport/StdList.h
index d329a0b2dc5..627381ecec0 100644
--- a/extern/Eigen3/Eigen/src/StlSupport/StdList.h
+++ b/extern/Eigen3/Eigen/src/StlSupport/StdList.h
@@ -3,24 +3,9 @@
 //
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STDLIST_H
 #define EIGEN_STDLIST_H
diff --git a/extern/Eigen3/Eigen/src/StlSupport/StdVector.h b/extern/Eigen3/Eigen/src/StlSupport/StdVector.h
index 27d6ab539f9..40a9abefa82 100644
--- a/extern/Eigen3/Eigen/src/StlSupport/StdVector.h
+++ b/extern/Eigen3/Eigen/src/StlSupport/StdVector.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STDVECTOR_H
 #define EIGEN_STDVECTOR_H
diff --git a/extern/Eigen3/Eigen/src/StlSupport/details.h b/extern/Eigen3/Eigen/src/StlSupport/details.h
index 397c8ef8581..d8debc7c4f8 100644
--- a/extern/Eigen3/Eigen/src/StlSupport/details.h
+++ b/extern/Eigen3/Eigen/src/StlSupport/details.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2009 Hauke Heibel <hauke.heibel@googlemail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_STL_DETAILS_H
 #define EIGEN_STL_DETAILS_H
diff --git a/extern/Eigen3/Eigen/src/SuperLUSupport/SuperLUSupport.h b/extern/Eigen3/Eigen/src/SuperLUSupport/SuperLUSupport.h
new file mode 100644
index 00000000000..11fb014dd93
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/SuperLUSupport/SuperLUSupport.h
@@ -0,0 +1,1025 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SUPERLUSUPPORT_H
+#define EIGEN_SUPERLUSUPPORT_H
+
+namespace Eigen { 
+
+#define DECL_GSSVX(PREFIX,FLOATTYPE,KEYTYPE)		\
+    extern "C" {                                                                                          \
+      typedef struct { FLOATTYPE for_lu; FLOATTYPE total_needed; int expansions; } PREFIX##mem_usage_t;   \
+      extern void PREFIX##gssvx(superlu_options_t *, SuperMatrix *, int *, int *, int *,                  \
+                                char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *,           \
+                                void *, int, SuperMatrix *, SuperMatrix *,                                \
+                                FLOATTYPE *, FLOATTYPE *, FLOATTYPE *, FLOATTYPE *,                       \
+                                PREFIX##mem_usage_t *, SuperLUStat_t *, int *);                           \
+    }                                                                                                     \
+    inline float SuperLU_gssvx(superlu_options_t *options, SuperMatrix *A,                                \
+         int *perm_c, int *perm_r, int *etree, char *equed,                                               \
+         FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L,                                                      \
+         SuperMatrix *U, void *work, int lwork,                                                           \
+         SuperMatrix *B, SuperMatrix *X,                                                                  \
+         FLOATTYPE *recip_pivot_growth,                                                                   \
+         FLOATTYPE *rcond, FLOATTYPE *ferr, FLOATTYPE *berr,                                              \
+         SuperLUStat_t *stats, int *info, KEYTYPE) {                                                      \
+    PREFIX##mem_usage_t mem_usage;                                                                        \
+    PREFIX##gssvx(options, A, perm_c, perm_r, etree, equed, R, C, L,                                      \
+         U, work, lwork, B, X, recip_pivot_growth, rcond,                                                 \
+         ferr, berr, &mem_usage, stats, info);                                                            \
+    return mem_usage.for_lu; /* bytes used by the factor storage */                                       \
+  }
+
+DECL_GSSVX(s,float,float)
+DECL_GSSVX(c,float,std::complex<float>)
+DECL_GSSVX(d,double,double)
+DECL_GSSVX(z,double,std::complex<double>)
+
+#ifdef MILU_ALPHA
+#define EIGEN_SUPERLU_HAS_ILU
+#endif
+
+#ifdef EIGEN_SUPERLU_HAS_ILU
+
+// similarly for the incomplete factorization using gsisx
+#define DECL_GSISX(PREFIX,FLOATTYPE,KEYTYPE)                                                    \
+    extern "C" {                                                                                \
+      extern void PREFIX##gsisx(superlu_options_t *, SuperMatrix *, int *, int *, int *,        \
+                         char *, FLOATTYPE *, FLOATTYPE *, SuperMatrix *, SuperMatrix *,        \
+                         void *, int, SuperMatrix *, SuperMatrix *, FLOATTYPE *, FLOATTYPE *,   \
+                         PREFIX##mem_usage_t *, SuperLUStat_t *, int *);                        \
+    }                                                                                           \
+    inline float SuperLU_gsisx(superlu_options_t *options, SuperMatrix *A,                      \
+         int *perm_c, int *perm_r, int *etree, char *equed,                                     \
+         FLOATTYPE *R, FLOATTYPE *C, SuperMatrix *L,                                            \
+         SuperMatrix *U, void *work, int lwork,                                                 \
+         SuperMatrix *B, SuperMatrix *X,                                                        \
+         FLOATTYPE *recip_pivot_growth,                                                         \
+         FLOATTYPE *rcond,                                                                      \
+         SuperLUStat_t *stats, int *info, KEYTYPE) {                                            \
+    PREFIX##mem_usage_t mem_usage;                                                              \
+    PREFIX##gsisx(options, A, perm_c, perm_r, etree, equed, R, C, L,                            \
+         U, work, lwork, B, X, recip_pivot_growth, rcond,                                       \
+         &mem_usage, stats, info);                                                              \
+    return mem_usage.for_lu; /* bytes used by the factor storage */                             \
+  }
+
+DECL_GSISX(s,float,float)
+DECL_GSISX(c,float,std::complex<float>)
+DECL_GSISX(d,double,double)
+DECL_GSISX(z,double,std::complex<double>)
+
+#endif
+
+template<typename MatrixType>
+struct SluMatrixMapHelper;
+
+/** \internal
+  *
+  * A wrapper class for SuperLU matrices. It supports only compressed sparse matrices
+  * and dense matrices. Supernodal and other fancy format are not supported by this wrapper.
+  *
+  * This wrapper class mainly aims to avoids the need of dynamic allocation of the storage structure.
+  */
+struct SluMatrix : SuperMatrix
+{
+  SluMatrix()
+  {
+    Store = &storage;
+  }
+
+  SluMatrix(const SluMatrix& other)
+    : SuperMatrix(other)
+  {
+    Store = &storage;
+    storage = other.storage;
+  }
+
+  SluMatrix& operator=(const SluMatrix& other)
+  {
+    SuperMatrix::operator=(static_cast<const SuperMatrix&>(other));
+    Store = &storage;
+    storage = other.storage;
+    return *this;
+  }
+
+  struct
+  {
+    union {int nnz;int lda;};
+    void *values;
+    int *innerInd;
+    int *outerInd;
+  } storage;
+
+  void setStorageType(Stype_t t)
+  {
+    Stype = t;
+    if (t==SLU_NC || t==SLU_NR || t==SLU_DN)
+      Store = &storage;
+    else
+    {
+      eigen_assert(false && "storage type not supported");
+      Store = 0;
+    }
+  }
+
+  template<typename Scalar>
+  void setScalarType()
+  {
+    if (internal::is_same<Scalar,float>::value)
+      Dtype = SLU_S;
+    else if (internal::is_same<Scalar,double>::value)
+      Dtype = SLU_D;
+    else if (internal::is_same<Scalar,std::complex<float> >::value)
+      Dtype = SLU_C;
+    else if (internal::is_same<Scalar,std::complex<double> >::value)
+      Dtype = SLU_Z;
+    else
+    {
+      eigen_assert(false && "Scalar type not supported by SuperLU");
+    }
+  }
+
+  template<typename MatrixType>
+  static SluMatrix Map(MatrixBase<MatrixType>& _mat)
+  {
+    MatrixType& mat(_mat.derived());
+    eigen_assert( ((MatrixType::Flags&RowMajorBit)!=RowMajorBit) && "row-major dense matrices are not supported by SuperLU");
+    SluMatrix res;
+    res.setStorageType(SLU_DN);
+    res.setScalarType<typename MatrixType::Scalar>();
+    res.Mtype     = SLU_GE;
+
+    res.nrow      = mat.rows();
+    res.ncol      = mat.cols();
+
+    res.storage.lda       = MatrixType::IsVectorAtCompileTime ? mat.size() : mat.outerStride();
+    res.storage.values    = mat.data();
+    return res;
+  }
+
+  template<typename MatrixType>
+  static SluMatrix Map(SparseMatrixBase<MatrixType>& mat)
+  {
+    SluMatrix res;
+    if ((MatrixType::Flags&RowMajorBit)==RowMajorBit)
+    {
+      res.setStorageType(SLU_NR);
+      res.nrow      = mat.cols();
+      res.ncol      = mat.rows();
+    }
+    else
+    {
+      res.setStorageType(SLU_NC);
+      res.nrow      = mat.rows();
+      res.ncol      = mat.cols();
+    }
+
+    res.Mtype       = SLU_GE;
+
+    res.storage.nnz       = mat.nonZeros();
+    res.storage.values    = mat.derived().valuePtr();
+    res.storage.innerInd  = mat.derived().innerIndexPtr();
+    res.storage.outerInd  = mat.derived().outerIndexPtr();
+
+    res.setScalarType<typename MatrixType::Scalar>();
+
+    // FIXME the following is not very accurate
+    if (MatrixType::Flags & Upper)
+      res.Mtype = SLU_TRU;
+    if (MatrixType::Flags & Lower)
+      res.Mtype = SLU_TRL;
+
+    eigen_assert(((MatrixType::Flags & SelfAdjoint)==0) && "SelfAdjoint matrix shape not supported by SuperLU");
+
+    return res;
+  }
+};
+
+template<typename Scalar, int Rows, int Cols, int Options, int MRows, int MCols>
+struct SluMatrixMapHelper<Matrix<Scalar,Rows,Cols,Options,MRows,MCols> >
+{
+  typedef Matrix<Scalar,Rows,Cols,Options,MRows,MCols> MatrixType;
+  static void run(MatrixType& mat, SluMatrix& res)
+  {
+    eigen_assert( ((Options&RowMajor)!=RowMajor) && "row-major dense matrices is not supported by SuperLU");
+    res.setStorageType(SLU_DN);
+    res.setScalarType<Scalar>();
+    res.Mtype     = SLU_GE;
+
+    res.nrow      = mat.rows();
+    res.ncol      = mat.cols();
+
+    res.storage.lda       = mat.outerStride();
+    res.storage.values    = mat.data();
+  }
+};
+
+template<typename Derived>
+struct SluMatrixMapHelper<SparseMatrixBase<Derived> >
+{
+  typedef Derived MatrixType;
+  static void run(MatrixType& mat, SluMatrix& res)
+  {
+    if ((MatrixType::Flags&RowMajorBit)==RowMajorBit)
+    {
+      res.setStorageType(SLU_NR);
+      res.nrow      = mat.cols();
+      res.ncol      = mat.rows();
+    }
+    else
+    {
+      res.setStorageType(SLU_NC);
+      res.nrow      = mat.rows();
+      res.ncol      = mat.cols();
+    }
+
+    res.Mtype       = SLU_GE;
+
+    res.storage.nnz       = mat.nonZeros();
+    res.storage.values    = mat.valuePtr();
+    res.storage.innerInd  = mat.innerIndexPtr();
+    res.storage.outerInd  = mat.outerIndexPtr();
+
+    res.setScalarType<typename MatrixType::Scalar>();
+
+    // FIXME the following is not very accurate
+    if (MatrixType::Flags & Upper)
+      res.Mtype = SLU_TRU;
+    if (MatrixType::Flags & Lower)
+      res.Mtype = SLU_TRL;
+
+    eigen_assert(((MatrixType::Flags & SelfAdjoint)==0) && "SelfAdjoint matrix shape not supported by SuperLU");
+  }
+};
+
+namespace internal {
+
+template<typename MatrixType>
+SluMatrix asSluMatrix(MatrixType& mat)
+{
+  return SluMatrix::Map(mat);
+}
+
+/** View a Super LU matrix as an Eigen expression */
+template<typename Scalar, int Flags, typename Index>
+MappedSparseMatrix<Scalar,Flags,Index> map_superlu(SluMatrix& sluMat)
+{
+  eigen_assert((Flags&RowMajor)==RowMajor && sluMat.Stype == SLU_NR
+         || (Flags&ColMajor)==ColMajor && sluMat.Stype == SLU_NC);
+
+  Index outerSize = (Flags&RowMajor)==RowMajor ? sluMat.ncol : sluMat.nrow;
+
+  return MappedSparseMatrix<Scalar,Flags,Index>(
+    sluMat.nrow, sluMat.ncol, sluMat.storage.outerInd[outerSize],
+    sluMat.storage.outerInd, sluMat.storage.innerInd, reinterpret_cast<Scalar*>(sluMat.storage.values) );
+}
+
+} // end namespace internal
+
+/** \ingroup SuperLUSupport_Module
+  * \class SuperLUBase
+  * \brief The base class for the direct and incomplete LU factorization of SuperLU
+  */
+template<typename _MatrixType, typename Derived>
+class SuperLUBase : internal::noncopyable
+{
+  public:
+    typedef _MatrixType MatrixType;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    typedef Matrix<Scalar,Dynamic,1> Vector;
+    typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
+    typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;    
+    typedef SparseMatrix<Scalar> LUMatrixType;
+
+  public:
+
+    SuperLUBase() {}
+
+    ~SuperLUBase()
+    {
+      clearFactors();
+    }
+    
+    Derived& derived() { return *static_cast<Derived*>(this); }
+    const Derived& derived() const { return *static_cast<const Derived*>(this); }
+    
+    inline Index rows() const { return m_matrix.rows(); }
+    inline Index cols() const { return m_matrix.cols(); }
+    
+    /** \returns a reference to the Super LU option object to configure the  Super LU algorithms. */
+    inline superlu_options_t& options() { return m_sluOptions; }
+    
+    /** \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 && "Decomposition is not initialized.");
+      return m_info;
+    }
+
+    /** Computes the sparse Cholesky decomposition of \a matrix */
+    void compute(const MatrixType& matrix)
+    {
+      derived().analyzePattern(matrix);
+      derived().factorize(matrix);
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<SuperLUBase, Rhs> solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "SuperLU is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "SuperLU::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<SuperLUBase, Rhs>(*this, b.derived());
+    }
+    
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+//     template<typename Rhs>
+//     inline const internal::sparse_solve_retval<SuperLU, Rhs> solve(const SparseMatrixBase<Rhs>& b) const
+//     {
+//       eigen_assert(m_isInitialized && "SuperLU is not initialized.");
+//       eigen_assert(rows()==b.rows()
+//                 && "SuperLU::solve(): invalid number of rows of the right hand side matrix b");
+//       return internal::sparse_solve_retval<SuperLU, Rhs>(*this, b.derived());
+//     }
+    
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      * 
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& /*matrix*/)
+    {
+      m_isInitialized = true;
+      m_info = Success;
+      m_analysisIsOk = true;
+      m_factorizationIsOk = false;
+    }
+    
+    template<typename Stream>
+    void dumpMemory(Stream& s)
+    {}
+    
+  protected:
+    
+    void initFactorization(const MatrixType& a)
+    {
+      set_default_options(&this->m_sluOptions);
+      
+      const int size = a.rows();
+      m_matrix = a;
+
+      m_sluA = internal::asSluMatrix(m_matrix);
+      clearFactors();
+
+      m_p.resize(size);
+      m_q.resize(size);
+      m_sluRscale.resize(size);
+      m_sluCscale.resize(size);
+      m_sluEtree.resize(size);
+
+      // set empty B and X
+      m_sluB.setStorageType(SLU_DN);
+      m_sluB.setScalarType<Scalar>();
+      m_sluB.Mtype          = SLU_GE;
+      m_sluB.storage.values = 0;
+      m_sluB.nrow           = 0;
+      m_sluB.ncol           = 0;
+      m_sluB.storage.lda    = size;
+      m_sluX                = m_sluB;
+      
+      m_extractedDataAreDirty = true;
+    }
+    
+    void init()
+    {
+      m_info = InvalidInput;
+      m_isInitialized = false;
+      m_sluL.Store = 0;
+      m_sluU.Store = 0;
+    }
+    
+    void extractData() const;
+
+    void clearFactors()
+    {
+      if(m_sluL.Store)
+        Destroy_SuperNode_Matrix(&m_sluL);
+      if(m_sluU.Store)
+        Destroy_CompCol_Matrix(&m_sluU);
+
+      m_sluL.Store = 0;
+      m_sluU.Store = 0;
+
+      memset(&m_sluL,0,sizeof m_sluL);
+      memset(&m_sluU,0,sizeof m_sluU);
+    }
+
+    // cached data to reduce reallocation, etc.
+    mutable LUMatrixType m_l;
+    mutable LUMatrixType m_u;
+    mutable IntColVectorType m_p;
+    mutable IntRowVectorType m_q;
+
+    mutable LUMatrixType m_matrix;  // copy of the factorized matrix
+    mutable SluMatrix m_sluA;
+    mutable SuperMatrix m_sluL, m_sluU;
+    mutable SluMatrix m_sluB, m_sluX;
+    mutable SuperLUStat_t m_sluStat;
+    mutable superlu_options_t m_sluOptions;
+    mutable std::vector<int> m_sluEtree;
+    mutable Matrix<RealScalar,Dynamic,1> m_sluRscale, m_sluCscale;
+    mutable Matrix<RealScalar,Dynamic,1> m_sluFerr, m_sluBerr;
+    mutable char m_sluEqued;
+
+    mutable ComputationInfo m_info;
+    bool m_isInitialized;
+    int m_factorizationIsOk;
+    int m_analysisIsOk;
+    mutable bool m_extractedDataAreDirty;
+    
+  private:
+    SuperLUBase(SuperLUBase& ) { }
+};
+
+
+/** \ingroup SuperLUSupport_Module
+  * \class SuperLU
+  * \brief A sparse direct LU factorization and solver based on the SuperLU library
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a direct LU factorization
+  * using the SuperLU library. The sparse matrix A must be squared and invertible. The vectors or matrices
+  * X and B can be either dense or sparse.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType>
+class SuperLU : public SuperLUBase<_MatrixType,SuperLU<_MatrixType> >
+{
+  public:
+    typedef SuperLUBase<_MatrixType,SuperLU> Base;
+    typedef _MatrixType MatrixType;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::RealScalar RealScalar;
+    typedef typename Base::Index Index;
+    typedef typename Base::IntRowVectorType IntRowVectorType;
+    typedef typename Base::IntColVectorType IntColVectorType;    
+    typedef typename Base::LUMatrixType LUMatrixType;
+    typedef TriangularView<LUMatrixType, Lower|UnitDiag>  LMatrixType;
+    typedef TriangularView<LUMatrixType,  Upper>           UMatrixType;
+
+  public:
+
+    SuperLU() : Base() { init(); }
+
+    SuperLU(const MatrixType& matrix) : Base()
+    {
+      Base::init();
+      compute(matrix);
+    }
+
+    ~SuperLU()
+    {
+    }
+    
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      * 
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    {
+      m_info = InvalidInput;
+      m_isInitialized = false;
+      Base::analyzePattern(matrix);
+    }
+    
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    void factorize(const MatrixType& matrix);
+    
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal */
+    template<typename Rhs,typename Dest>
+    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const;
+    #endif // EIGEN_PARSED_BY_DOXYGEN
+    
+    inline const LMatrixType& matrixL() const
+    {
+      if (m_extractedDataAreDirty) this->extractData();
+      return m_l;
+    }
+
+    inline const UMatrixType& matrixU() const
+    {
+      if (m_extractedDataAreDirty) this->extractData();
+      return m_u;
+    }
+
+    inline const IntColVectorType& permutationP() const
+    {
+      if (m_extractedDataAreDirty) this->extractData();
+      return m_p;
+    }
+
+    inline const IntRowVectorType& permutationQ() const
+    {
+      if (m_extractedDataAreDirty) this->extractData();
+      return m_q;
+    }
+    
+    Scalar determinant() const;
+    
+  protected:
+    
+    using Base::m_matrix;
+    using Base::m_sluOptions;
+    using Base::m_sluA;
+    using Base::m_sluB;
+    using Base::m_sluX;
+    using Base::m_p;
+    using Base::m_q;
+    using Base::m_sluEtree;
+    using Base::m_sluEqued;
+    using Base::m_sluRscale;
+    using Base::m_sluCscale;
+    using Base::m_sluL;
+    using Base::m_sluU;
+    using Base::m_sluStat;
+    using Base::m_sluFerr;
+    using Base::m_sluBerr;
+    using Base::m_l;
+    using Base::m_u;
+    
+    using Base::m_analysisIsOk;
+    using Base::m_factorizationIsOk;
+    using Base::m_extractedDataAreDirty;
+    using Base::m_isInitialized;
+    using Base::m_info;
+    
+    void init()
+    {
+      Base::init();
+      
+      set_default_options(&this->m_sluOptions);
+      m_sluOptions.PrintStat        = NO;
+      m_sluOptions.ConditionNumber  = NO;
+      m_sluOptions.Trans            = NOTRANS;
+      m_sluOptions.ColPerm          = COLAMD;
+    }
+    
+    
+  private:
+    SuperLU(SuperLU& ) { }
+};
+
+template<typename MatrixType>
+void SuperLU<MatrixType>::factorize(const MatrixType& a)
+{
+  eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
+  if(!m_analysisIsOk)
+  {
+    m_info = InvalidInput;
+    return;
+  }
+  
+  this->initFactorization(a);
+  
+  int info = 0;
+  RealScalar recip_pivot_growth, rcond;
+  RealScalar ferr, berr;
+
+  StatInit(&m_sluStat);
+  SuperLU_gssvx(&m_sluOptions, &m_sluA, m_q.data(), m_p.data(), &m_sluEtree[0],
+                &m_sluEqued, &m_sluRscale[0], &m_sluCscale[0],
+                &m_sluL, &m_sluU,
+                NULL, 0,
+                &m_sluB, &m_sluX,
+                &recip_pivot_growth, &rcond,
+                &ferr, &berr,
+                &m_sluStat, &info, Scalar());
+  StatFree(&m_sluStat);
+
+  m_extractedDataAreDirty = true;
+
+  // FIXME how to better check for errors ???
+  m_info = info == 0 ? Success : NumericalIssue;
+  m_factorizationIsOk = true;
+}
+
+template<typename MatrixType>
+template<typename Rhs,typename Dest>
+void SuperLU<MatrixType>::_solve(const MatrixBase<Rhs> &b, MatrixBase<Dest>& x) const
+{
+  eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or analyzePattern()/factorize()");
+
+  const int size = m_matrix.rows();
+  const int rhsCols = b.cols();
+  eigen_assert(size==b.rows());
+
+  m_sluOptions.Trans = NOTRANS;
+  m_sluOptions.Fact = FACTORED;
+  m_sluOptions.IterRefine = NOREFINE;
+  
+
+  m_sluFerr.resize(rhsCols);
+  m_sluBerr.resize(rhsCols);
+  m_sluB = SluMatrix::Map(b.const_cast_derived());
+  m_sluX = SluMatrix::Map(x.derived());
+  
+  typename Rhs::PlainObject b_cpy;
+  if(m_sluEqued!='N')
+  {
+    b_cpy = b;
+    m_sluB = SluMatrix::Map(b_cpy.const_cast_derived());  
+  }
+
+  StatInit(&m_sluStat);
+  int info = 0;
+  RealScalar recip_pivot_growth, rcond;
+  SuperLU_gssvx(&m_sluOptions, &m_sluA,
+                m_q.data(), m_p.data(),
+                &m_sluEtree[0], &m_sluEqued,
+                &m_sluRscale[0], &m_sluCscale[0],
+                &m_sluL, &m_sluU,
+                NULL, 0,
+                &m_sluB, &m_sluX,
+                &recip_pivot_growth, &rcond,
+                &m_sluFerr[0], &m_sluBerr[0],
+                &m_sluStat, &info, Scalar());
+  StatFree(&m_sluStat);
+  m_info = info==0 ? Success : NumericalIssue;
+}
+
+// the code of this extractData() function has been adapted from the SuperLU's Matlab support code,
+//
+//  Copyright (c) 1994 by Xerox Corporation.  All rights reserved.
+//
+//  THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY
+//  EXPRESSED OR IMPLIED.  ANY USE IS AT YOUR OWN RISK.
+//
+template<typename MatrixType, typename Derived>
+void SuperLUBase<MatrixType,Derived>::extractData() const
+{
+  eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for extracting factors, you must first call either compute() or analyzePattern()/factorize()");
+  if (m_extractedDataAreDirty)
+  {
+    int         upper;
+    int         fsupc, istart, nsupr;
+    int         lastl = 0, lastu = 0;
+    SCformat    *Lstore = static_cast<SCformat*>(m_sluL.Store);
+    NCformat    *Ustore = static_cast<NCformat*>(m_sluU.Store);
+    Scalar      *SNptr;
+
+    const int size = m_matrix.rows();
+    m_l.resize(size,size);
+    m_l.resizeNonZeros(Lstore->nnz);
+    m_u.resize(size,size);
+    m_u.resizeNonZeros(Ustore->nnz);
+
+    int* Lcol = m_l.outerIndexPtr();
+    int* Lrow = m_l.innerIndexPtr();
+    Scalar* Lval = m_l.valuePtr();
+
+    int* Ucol = m_u.outerIndexPtr();
+    int* Urow = m_u.innerIndexPtr();
+    Scalar* Uval = m_u.valuePtr();
+
+    Ucol[0] = 0;
+    Ucol[0] = 0;
+
+    /* for each supernode */
+    for (int k = 0; k <= Lstore->nsuper; ++k)
+    {
+      fsupc   = L_FST_SUPC(k);
+      istart  = L_SUB_START(fsupc);
+      nsupr   = L_SUB_START(fsupc+1) - istart;
+      upper   = 1;
+
+      /* for each column in the supernode */
+      for (int j = fsupc; j < L_FST_SUPC(k+1); ++j)
+      {
+        SNptr = &((Scalar*)Lstore->nzval)[L_NZ_START(j)];
+
+        /* Extract U */
+        for (int i = U_NZ_START(j); i < U_NZ_START(j+1); ++i)
+        {
+          Uval[lastu] = ((Scalar*)Ustore->nzval)[i];
+          /* Matlab doesn't like explicit zero. */
+          if (Uval[lastu] != 0.0)
+            Urow[lastu++] = U_SUB(i);
+        }
+        for (int i = 0; i < upper; ++i)
+        {
+          /* upper triangle in the supernode */
+          Uval[lastu] = SNptr[i];
+          /* Matlab doesn't like explicit zero. */
+          if (Uval[lastu] != 0.0)
+            Urow[lastu++] = L_SUB(istart+i);
+        }
+        Ucol[j+1] = lastu;
+
+        /* Extract L */
+        Lval[lastl] = 1.0; /* unit diagonal */
+        Lrow[lastl++] = L_SUB(istart + upper - 1);
+        for (int i = upper; i < nsupr; ++i)
+        {
+          Lval[lastl] = SNptr[i];
+          /* Matlab doesn't like explicit zero. */
+          if (Lval[lastl] != 0.0)
+            Lrow[lastl++] = L_SUB(istart+i);
+        }
+        Lcol[j+1] = lastl;
+
+        ++upper;
+      } /* for j ... */
+
+    } /* for k ... */
+
+    // squeeze the matrices :
+    m_l.resizeNonZeros(lastl);
+    m_u.resizeNonZeros(lastu);
+
+    m_extractedDataAreDirty = false;
+  }
+}
+
+template<typename MatrixType>
+typename SuperLU<MatrixType>::Scalar SuperLU<MatrixType>::determinant() const
+{
+  eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for computing the determinant, you must first call either compute() or analyzePattern()/factorize()");
+  
+  if (m_extractedDataAreDirty)
+    this->extractData();
+
+  Scalar det = Scalar(1);
+  for (int j=0; j<m_u.cols(); ++j)
+  {
+    if (m_u.outerIndexPtr()[j+1]-m_u.outerIndexPtr()[j] > 0)
+    {
+      int lastId = m_u.outerIndexPtr()[j+1]-1;
+      eigen_assert(m_u.innerIndexPtr()[lastId]<=j);
+      if (m_u.innerIndexPtr()[lastId]==j)
+        det *= m_u.valuePtr()[lastId];
+    }
+  }
+  if(m_sluEqued!='N')
+    return det/m_sluRscale.prod()/m_sluCscale.prod();
+  else
+    return det;
+}
+
+#ifdef EIGEN_PARSED_BY_DOXYGEN
+#define EIGEN_SUPERLU_HAS_ILU
+#endif
+
+#ifdef EIGEN_SUPERLU_HAS_ILU
+
+/** \ingroup SuperLUSupport_Module
+  * \class SuperILU
+  * \brief A sparse direct \b incomplete LU factorization and solver based on the SuperLU library
+  *
+  * This class allows to solve for an approximate solution of A.X = B sparse linear problems via an incomplete LU factorization
+  * using the SuperLU library. This class is aimed to be used as a preconditioner of the iterative linear solvers.
+  *
+  * \warning This class requires SuperLU 4 or later.
+  *
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  *
+  * \sa \ref TutorialSparseDirectSolvers, class ConjugateGradient, class BiCGSTAB
+  */
+
+template<typename _MatrixType>
+class SuperILU : public SuperLUBase<_MatrixType,SuperILU<_MatrixType> >
+{
+  public:
+    typedef SuperLUBase<_MatrixType,SuperILU> Base;
+    typedef _MatrixType MatrixType;
+    typedef typename Base::Scalar Scalar;
+    typedef typename Base::RealScalar RealScalar;
+    typedef typename Base::Index Index;
+
+  public:
+
+    SuperILU() : Base() { init(); }
+
+    SuperILU(const MatrixType& matrix) : Base()
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~SuperILU()
+    {
+    }
+    
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      * 
+      * \sa factorize()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    {
+      Base::analyzePattern(matrix);
+    }
+    
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
+      *
+      * \sa analyzePattern()
+      */
+    void factorize(const MatrixType& matrix);
+    
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal */
+    template<typename Rhs,typename Dest>
+    void _solve(const MatrixBase<Rhs> &b, MatrixBase<Dest> &dest) const;
+    #endif // EIGEN_PARSED_BY_DOXYGEN
+    
+  protected:
+    
+    using Base::m_matrix;
+    using Base::m_sluOptions;
+    using Base::m_sluA;
+    using Base::m_sluB;
+    using Base::m_sluX;
+    using Base::m_p;
+    using Base::m_q;
+    using Base::m_sluEtree;
+    using Base::m_sluEqued;
+    using Base::m_sluRscale;
+    using Base::m_sluCscale;
+    using Base::m_sluL;
+    using Base::m_sluU;
+    using Base::m_sluStat;
+    using Base::m_sluFerr;
+    using Base::m_sluBerr;
+    using Base::m_l;
+    using Base::m_u;
+    
+    using Base::m_analysisIsOk;
+    using Base::m_factorizationIsOk;
+    using Base::m_extractedDataAreDirty;
+    using Base::m_isInitialized;
+    using Base::m_info;
+
+    void init()
+    {
+      Base::init();
+      
+      ilu_set_default_options(&m_sluOptions);
+      m_sluOptions.PrintStat        = NO;
+      m_sluOptions.ConditionNumber  = NO;
+      m_sluOptions.Trans            = NOTRANS;
+      m_sluOptions.ColPerm          = MMD_AT_PLUS_A;
+      
+      // no attempt to preserve column sum
+      m_sluOptions.ILU_MILU = SILU;
+      // only basic ILU(k) support -- no direct control over memory consumption
+      // better to use ILU_DropRule = DROP_BASIC | DROP_AREA
+      // and set ILU_FillFactor to max memory growth
+      m_sluOptions.ILU_DropRule = DROP_BASIC;
+      m_sluOptions.ILU_DropTol = NumTraits<Scalar>::dummy_precision()*10;
+    }
+    
+  private:
+    SuperILU(SuperILU& ) { }
+};
+
+template<typename MatrixType>
+void SuperILU<MatrixType>::factorize(const MatrixType& a)
+{
+  eigen_assert(m_analysisIsOk && "You must first call analyzePattern()");
+  if(!m_analysisIsOk)
+  {
+    m_info = InvalidInput;
+    return;
+  }
+  
+  this->initFactorization(a);
+
+  int info = 0;
+  RealScalar recip_pivot_growth, rcond;
+
+  StatInit(&m_sluStat);
+  SuperLU_gsisx(&m_sluOptions, &m_sluA, m_q.data(), m_p.data(), &m_sluEtree[0],
+                &m_sluEqued, &m_sluRscale[0], &m_sluCscale[0],
+                &m_sluL, &m_sluU,
+                NULL, 0,
+                &m_sluB, &m_sluX,
+                &recip_pivot_growth, &rcond,
+                &m_sluStat, &info, Scalar());
+  StatFree(&m_sluStat);
+
+  // FIXME how to better check for errors ???
+  m_info = info == 0 ? Success : NumericalIssue;
+  m_factorizationIsOk = true;
+}
+
+template<typename MatrixType>
+template<typename Rhs,typename Dest>
+void SuperILU<MatrixType>::_solve(const MatrixBase<Rhs> &b, MatrixBase<Dest>& x) const
+{
+  eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or analyzePattern()/factorize()");
+
+  const int size = m_matrix.rows();
+  const int rhsCols = b.cols();
+  eigen_assert(size==b.rows());
+
+  m_sluOptions.Trans = NOTRANS;
+  m_sluOptions.Fact = FACTORED;
+  m_sluOptions.IterRefine = NOREFINE;
+
+  m_sluFerr.resize(rhsCols);
+  m_sluBerr.resize(rhsCols);
+  m_sluB = SluMatrix::Map(b.const_cast_derived());
+  m_sluX = SluMatrix::Map(x.derived());
+
+  typename Rhs::PlainObject b_cpy;
+  if(m_sluEqued!='N')
+  {
+    b_cpy = b;
+    m_sluB = SluMatrix::Map(b_cpy.const_cast_derived());  
+  }
+  
+  int info = 0;
+  RealScalar recip_pivot_growth, rcond;
+
+  StatInit(&m_sluStat);
+  SuperLU_gsisx(&m_sluOptions, &m_sluA,
+                m_q.data(), m_p.data(),
+                &m_sluEtree[0], &m_sluEqued,
+                &m_sluRscale[0], &m_sluCscale[0],
+                &m_sluL, &m_sluU,
+                NULL, 0,
+                &m_sluB, &m_sluX,
+                &recip_pivot_growth, &rcond,
+                &m_sluStat, &info, Scalar());
+  StatFree(&m_sluStat);
+
+  m_info = info==0 ? Success : NumericalIssue;
+}
+#endif
+
+namespace internal {
+  
+template<typename _MatrixType, typename Derived, typename Rhs>
+struct solve_retval<SuperLUBase<_MatrixType,Derived>, Rhs>
+  : solve_retval_base<SuperLUBase<_MatrixType,Derived>, Rhs>
+{
+  typedef SuperLUBase<_MatrixType,Derived> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec().derived()._solve(rhs(),dst);
+  }
+};
+
+template<typename _MatrixType, typename Derived, typename Rhs>
+struct sparse_solve_retval<SuperLUBase<_MatrixType,Derived>, Rhs>
+  : sparse_solve_retval_base<SuperLUBase<_MatrixType,Derived>, Rhs>
+{
+  typedef SuperLUBase<_MatrixType,Derived> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec().derived()._solve(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SUPERLUSUPPORT_H
diff --git a/extern/Eigen3/Eigen/src/UmfPackSupport/UmfPackSupport.h b/extern/Eigen3/Eigen/src/UmfPackSupport/UmfPackSupport.h
new file mode 100644
index 00000000000..f01720362de
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/UmfPackSupport/UmfPackSupport.h
@@ -0,0 +1,431 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_UMFPACKSUPPORT_H
+#define EIGEN_UMFPACKSUPPORT_H
+
+namespace Eigen { 
+
+/* TODO extract L, extract U, compute det, etc... */
+
+// generic double/complex<double> wrapper functions:
+
+inline void umfpack_free_numeric(void **Numeric, double)
+{ umfpack_di_free_numeric(Numeric); *Numeric = 0; }
+
+inline void umfpack_free_numeric(void **Numeric, std::complex<double>)
+{ umfpack_zi_free_numeric(Numeric); *Numeric = 0; }
+
+inline void umfpack_free_symbolic(void **Symbolic, double)
+{ umfpack_di_free_symbolic(Symbolic); *Symbolic = 0; }
+
+inline void umfpack_free_symbolic(void **Symbolic, std::complex<double>)
+{ umfpack_zi_free_symbolic(Symbolic); *Symbolic = 0; }
+
+inline int umfpack_symbolic(int n_row,int n_col,
+                            const int Ap[], const int Ai[], const double Ax[], void **Symbolic,
+                            const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
+{
+  return umfpack_di_symbolic(n_row,n_col,Ap,Ai,Ax,Symbolic,Control,Info);
+}
+
+inline int umfpack_symbolic(int n_row,int n_col,
+                            const int Ap[], const int Ai[], const std::complex<double> Ax[], void **Symbolic,
+                            const double Control [UMFPACK_CONTROL], double Info [UMFPACK_INFO])
+{
+  return umfpack_zi_symbolic(n_row,n_col,Ap,Ai,&internal::real_ref(Ax[0]),0,Symbolic,Control,Info);
+}
+
+inline int umfpack_numeric( const int Ap[], const int Ai[], const double Ax[],
+                            void *Symbolic, void **Numeric,
+                            const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
+{
+  return umfpack_di_numeric(Ap,Ai,Ax,Symbolic,Numeric,Control,Info);
+}
+
+inline int umfpack_numeric( const int Ap[], const int Ai[], const std::complex<double> Ax[],
+                            void *Symbolic, void **Numeric,
+                            const double Control[UMFPACK_CONTROL],double Info [UMFPACK_INFO])
+{
+  return umfpack_zi_numeric(Ap,Ai,&internal::real_ref(Ax[0]),0,Symbolic,Numeric,Control,Info);
+}
+
+inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const double Ax[],
+                          double X[], const double B[], void *Numeric,
+                          const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
+{
+  return umfpack_di_solve(sys,Ap,Ai,Ax,X,B,Numeric,Control,Info);
+}
+
+inline int umfpack_solve( int sys, const int Ap[], const int Ai[], const std::complex<double> Ax[],
+                          std::complex<double> X[], const std::complex<double> B[], void *Numeric,
+                          const double Control[UMFPACK_CONTROL], double Info[UMFPACK_INFO])
+{
+  return umfpack_zi_solve(sys,Ap,Ai,&internal::real_ref(Ax[0]),0,&internal::real_ref(X[0]),0,&internal::real_ref(B[0]),0,Numeric,Control,Info);
+}
+
+inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, double)
+{
+  return umfpack_di_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
+}
+
+inline int umfpack_get_lunz(int *lnz, int *unz, int *n_row, int *n_col, int *nz_udiag, void *Numeric, std::complex<double>)
+{
+  return umfpack_zi_get_lunz(lnz,unz,n_row,n_col,nz_udiag,Numeric);
+}
+
+inline int umfpack_get_numeric(int Lp[], int Lj[], double Lx[], int Up[], int Ui[], double Ux[],
+                               int P[], int Q[], double Dx[], int *do_recip, double Rs[], void *Numeric)
+{
+  return umfpack_di_get_numeric(Lp,Lj,Lx,Up,Ui,Ux,P,Q,Dx,do_recip,Rs,Numeric);
+}
+
+inline int umfpack_get_numeric(int Lp[], int Lj[], std::complex<double> Lx[], int Up[], int Ui[], std::complex<double> Ux[],
+                               int P[], int Q[], std::complex<double> Dx[], int *do_recip, double Rs[], void *Numeric)
+{
+  double& lx0_real = internal::real_ref(Lx[0]);
+  double& ux0_real = internal::real_ref(Ux[0]);
+  double& dx0_real = internal::real_ref(Dx[0]);
+  return umfpack_zi_get_numeric(Lp,Lj,Lx?&lx0_real:0,0,Up,Ui,Ux?&ux0_real:0,0,P,Q,
+                                Dx?&dx0_real:0,0,do_recip,Rs,Numeric);
+}
+
+inline int umfpack_get_determinant(double *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
+{
+  return umfpack_di_get_determinant(Mx,Ex,NumericHandle,User_Info);
+}
+
+inline int umfpack_get_determinant(std::complex<double> *Mx, double *Ex, void *NumericHandle, double User_Info [UMFPACK_INFO])
+{
+  double& mx_real = internal::real_ref(*Mx);
+  return umfpack_zi_get_determinant(&mx_real,0,Ex,NumericHandle,User_Info);
+}
+
+/** \ingroup UmfPackSupport_Module
+  * \brief A sparse LU factorization and solver based on UmfPack
+  *
+  * This class allows to solve for A.X = B sparse linear problems via a LU factorization
+  * using the UmfPack library. The sparse matrix A must be squared and full rank.
+  * The vectors or matrices X and B can be either dense or sparse.
+  *
+  * \WARNING The input matrix A should be in a \b compressed and \b column-major form.
+  * Otherwise an expensive copy will be made. You can call the inexpensive makeCompressed() to get a compressed matrix.
+  * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
+  *
+  * \sa \ref TutorialSparseDirectSolvers
+  */
+template<typename _MatrixType>
+class UmfPackLU : internal::noncopyable
+{
+  public:
+    typedef _MatrixType MatrixType;
+    typedef typename MatrixType::Scalar Scalar;
+    typedef typename MatrixType::RealScalar RealScalar;
+    typedef typename MatrixType::Index Index;
+    typedef Matrix<Scalar,Dynamic,1> Vector;
+    typedef Matrix<int, 1, MatrixType::ColsAtCompileTime> IntRowVectorType;
+    typedef Matrix<int, MatrixType::RowsAtCompileTime, 1> IntColVectorType;
+    typedef SparseMatrix<Scalar> LUMatrixType;
+    typedef SparseMatrix<Scalar,ColMajor,int> UmfpackMatrixType;
+
+  public:
+
+    UmfPackLU() { init(); }
+
+    UmfPackLU(const MatrixType& matrix)
+    {
+      init();
+      compute(matrix);
+    }
+
+    ~UmfPackLU()
+    {
+      if(m_symbolic) umfpack_free_symbolic(&m_symbolic,Scalar());
+      if(m_numeric)  umfpack_free_numeric(&m_numeric,Scalar());
+    }
+
+    inline Index rows() const { return m_copyMatrix.rows(); }
+    inline Index cols() const { return m_copyMatrix.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 && "Decomposition is not initialized.");
+      return m_info;
+    }
+
+    inline const LUMatrixType& matrixL() const
+    {
+      if (m_extractedDataAreDirty) extractData();
+      return m_l;
+    }
+
+    inline const LUMatrixType& matrixU() const
+    {
+      if (m_extractedDataAreDirty) extractData();
+      return m_u;
+    }
+
+    inline const IntColVectorType& permutationP() const
+    {
+      if (m_extractedDataAreDirty) extractData();
+      return m_p;
+    }
+
+    inline const IntRowVectorType& permutationQ() const
+    {
+      if (m_extractedDataAreDirty) extractData();
+      return m_q;
+    }
+
+    /** Computes the sparse Cholesky decomposition of \a matrix 
+     *  Note that the matrix should be column-major, and in compressed format for best performance.
+     *  \sa SparseMatrix::makeCompressed().
+     */
+    void compute(const MatrixType& matrix)
+    {
+      analyzePattern(matrix);
+      factorize(matrix);
+    }
+
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+    template<typename Rhs>
+    inline const internal::solve_retval<UmfPackLU, Rhs> solve(const MatrixBase<Rhs>& b) const
+    {
+      eigen_assert(m_isInitialized && "UmfPackLU is not initialized.");
+      eigen_assert(rows()==b.rows()
+                && "UmfPackLU::solve(): invalid number of rows of the right hand side matrix b");
+      return internal::solve_retval<UmfPackLU, Rhs>(*this, b.derived());
+    }
+
+    /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A.
+      *
+      * \sa compute()
+      */
+//     template<typename Rhs>
+//     inline const internal::sparse_solve_retval<UmfPAckLU, Rhs> solve(const SparseMatrixBase<Rhs>& b) const
+//     {
+//       eigen_assert(m_isInitialized && "UmfPAckLU is not initialized.");
+//       eigen_assert(rows()==b.rows()
+//                 && "UmfPAckLU::solve(): invalid number of rows of the right hand side matrix b");
+//       return internal::sparse_solve_retval<UmfPAckLU, Rhs>(*this, b.derived());
+//     }
+
+    /** Performs a symbolic decomposition on the sparcity of \a matrix.
+      *
+      * This function is particularly useful when solving for several problems having the same structure.
+      *
+      * \sa factorize(), compute()
+      */
+    void analyzePattern(const MatrixType& matrix)
+    {
+      if(m_symbolic)
+        umfpack_free_symbolic(&m_symbolic,Scalar());
+      if(m_numeric)
+        umfpack_free_numeric(&m_numeric,Scalar());
+      
+      grapInput(matrix);
+
+      int errorCode = 0;
+      errorCode = umfpack_symbolic(matrix.rows(), matrix.cols(), m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
+                                   &m_symbolic, 0, 0);
+
+      m_isInitialized = true;
+      m_info = errorCode ? InvalidInput : Success;
+      m_analysisIsOk = true;
+      m_factorizationIsOk = false;
+    }
+
+    /** Performs a numeric decomposition of \a matrix
+      *
+      * The given matrix must has the same sparcity than the matrix on which the pattern anylysis has been performed.
+      *
+      * \sa analyzePattern(), compute()
+      */
+    void factorize(const MatrixType& matrix)
+    {
+      eigen_assert(m_analysisIsOk && "UmfPackLU: you must first call analyzePattern()");
+      if(m_numeric)
+        umfpack_free_numeric(&m_numeric,Scalar());
+
+      grapInput(matrix);
+
+      int errorCode;
+      errorCode = umfpack_numeric(m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
+                                  m_symbolic, &m_numeric, 0, 0);
+
+      m_info = errorCode ? NumericalIssue : Success;
+      m_factorizationIsOk = true;
+    }
+
+    #ifndef EIGEN_PARSED_BY_DOXYGEN
+    /** \internal */
+    template<typename BDerived,typename XDerived>
+    bool _solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const;
+    #endif
+
+    Scalar determinant() const;
+
+    void extractData() const;
+
+  protected:
+
+
+    void init()
+    {
+      m_info = InvalidInput;
+      m_isInitialized = false;
+      m_numeric = 0;
+      m_symbolic = 0;
+      m_outerIndexPtr = 0;
+      m_innerIndexPtr = 0;
+      m_valuePtr      = 0;
+    }
+    
+    void grapInput(const MatrixType& mat)
+    {
+      m_copyMatrix.resize(mat.rows(), mat.cols());
+      if( ((MatrixType::Flags&RowMajorBit)==RowMajorBit) || sizeof(typename MatrixType::Index)!=sizeof(int) || !mat.isCompressed() )
+      {
+        // non supported input -> copy
+        m_copyMatrix = mat;
+        m_outerIndexPtr = m_copyMatrix.outerIndexPtr();
+        m_innerIndexPtr = m_copyMatrix.innerIndexPtr();
+        m_valuePtr      = m_copyMatrix.valuePtr();
+      }
+      else
+      {
+        m_outerIndexPtr = mat.outerIndexPtr();
+        m_innerIndexPtr = mat.innerIndexPtr();
+        m_valuePtr      = mat.valuePtr();
+      }
+    }
+
+    // cached data to reduce reallocation, etc.
+    mutable LUMatrixType m_l;
+    mutable LUMatrixType m_u;
+    mutable IntColVectorType m_p;
+    mutable IntRowVectorType m_q;
+
+    UmfpackMatrixType m_copyMatrix;
+    const Scalar* m_valuePtr;
+    const int* m_outerIndexPtr;
+    const int* m_innerIndexPtr;
+    void* m_numeric;
+    void* m_symbolic;
+
+    mutable ComputationInfo m_info;
+    bool m_isInitialized;
+    int m_factorizationIsOk;
+    int m_analysisIsOk;
+    mutable bool m_extractedDataAreDirty;
+    
+  private:
+    UmfPackLU(UmfPackLU& ) { }
+};
+
+
+template<typename MatrixType>
+void UmfPackLU<MatrixType>::extractData() const
+{
+  if (m_extractedDataAreDirty)
+  {
+    // get size of the data
+    int lnz, unz, rows, cols, nz_udiag;
+    umfpack_get_lunz(&lnz, &unz, &rows, &cols, &nz_udiag, m_numeric, Scalar());
+
+    // allocate data
+    m_l.resize(rows,(std::min)(rows,cols));
+    m_l.resizeNonZeros(lnz);
+
+    m_u.resize((std::min)(rows,cols),cols);
+    m_u.resizeNonZeros(unz);
+
+    m_p.resize(rows);
+    m_q.resize(cols);
+
+    // extract
+    umfpack_get_numeric(m_l.outerIndexPtr(), m_l.innerIndexPtr(), m_l.valuePtr(),
+                        m_u.outerIndexPtr(), m_u.innerIndexPtr(), m_u.valuePtr(),
+                        m_p.data(), m_q.data(), 0, 0, 0, m_numeric);
+
+    m_extractedDataAreDirty = false;
+  }
+}
+
+template<typename MatrixType>
+typename UmfPackLU<MatrixType>::Scalar UmfPackLU<MatrixType>::determinant() const
+{
+  Scalar det;
+  umfpack_get_determinant(&det, 0, m_numeric, 0);
+  return det;
+}
+
+template<typename MatrixType>
+template<typename BDerived,typename XDerived>
+bool UmfPackLU<MatrixType>::_solve(const MatrixBase<BDerived> &b, MatrixBase<XDerived> &x) const
+{
+  const int rhsCols = b.cols();
+  eigen_assert((BDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major rhs yet");
+  eigen_assert((XDerived::Flags&RowMajorBit)==0 && "UmfPackLU backend does not support non col-major result yet");
+
+  int errorCode;
+  for (int j=0; j<rhsCols; ++j)
+  {
+    errorCode = umfpack_solve(UMFPACK_A,
+        m_outerIndexPtr, m_innerIndexPtr, m_valuePtr,
+        &x.col(j).coeffRef(0), &b.const_cast_derived().col(j).coeffRef(0), m_numeric, 0, 0);
+    if (errorCode!=0)
+      return false;
+  }
+
+  return true;
+}
+
+
+namespace internal {
+
+template<typename _MatrixType, typename Rhs>
+struct solve_retval<UmfPackLU<_MatrixType>, Rhs>
+  : solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
+{
+  typedef UmfPackLU<_MatrixType> Dec;
+  EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+template<typename _MatrixType, typename Rhs>
+struct sparse_solve_retval<UmfPackLU<_MatrixType>, Rhs>
+  : sparse_solve_retval_base<UmfPackLU<_MatrixType>, Rhs>
+{
+  typedef UmfPackLU<_MatrixType> Dec;
+  EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs)
+
+  template<typename Dest> void evalTo(Dest& dst) const
+  {
+    dec()._solve(rhs(),dst);
+  }
+};
+
+} // end namespace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_UMFPACKSUPPORT_H
diff --git a/extern/Eigen3/Eigen/src/misc/Image.h b/extern/Eigen3/Eigen/src/misc/Image.h
index 19b3e08cbfd..75c5f433a8a 100644
--- a/extern/Eigen3/Eigen/src/misc/Image.h
+++ b/extern/Eigen3/Eigen/src/misc/Image.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MISC_IMAGE_H
 #define EIGEN_MISC_IMAGE_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /** \class image_retval_base
@@ -92,4 +79,6 @@ template<typename _DecompositionType> struct image_retval_base
   image_retval(const DecompositionType& dec, const MatrixType& originalMatrix) \
     : Base(dec, originalMatrix) {}
 
+} // end namespace Eigen
+
 #endif // EIGEN_MISC_IMAGE_H
diff --git a/extern/Eigen3/Eigen/src/misc/Kernel.h b/extern/Eigen3/Eigen/src/misc/Kernel.h
index 0115970e8eb..b9e1518fd49 100644
--- a/extern/Eigen3/Eigen/src/misc/Kernel.h
+++ b/extern/Eigen3/Eigen/src/misc/Kernel.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MISC_KERNEL_H
 #define EIGEN_MISC_KERNEL_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /** \class kernel_retval_base
@@ -89,4 +76,6 @@ template<typename _DecompositionType> struct kernel_retval_base
   using Base::cols; \
   kernel_retval(const DecompositionType& dec) : Base(dec) {}
 
+} // end namespace Eigen
+
 #endif // EIGEN_MISC_KERNEL_H
diff --git a/extern/Eigen3/Eigen/src/misc/Solve.h b/extern/Eigen3/Eigen/src/misc/Solve.h
index b7cbcadb392..7f70d60afbd 100644
--- a/extern/Eigen3/Eigen/src/misc/Solve.h
+++ b/extern/Eigen3/Eigen/src/misc/Solve.h
@@ -3,28 +3,15 @@
 //
 // Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// 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/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_MISC_SOLVE_H
 #define EIGEN_MISC_SOLVE_H
 
+namespace Eigen { 
+
 namespace internal {
 
 /** \class solve_retval_base
@@ -66,7 +53,7 @@ template<typename _DecompositionType, typename Rhs> struct solve_retval_base
 
   protected:
     const DecompositionType& m_dec;
-    const typename Rhs::Nested m_rhs;
+    typename Rhs::Nested m_rhs;
 };
 
 } // end namespace internal
@@ -84,4 +71,6 @@ template<typename _DecompositionType, typename Rhs> struct solve_retval_base
   solve_retval(const DecompositionType& dec, const Rhs& rhs) \
     : Base(dec, rhs) {}
 
+} // end namespace Eigen
+
 #endif // EIGEN_MISC_SOLVE_H
diff --git a/extern/Eigen3/Eigen/src/misc/SparseSolve.h b/extern/Eigen3/Eigen/src/misc/SparseSolve.h
new file mode 100644
index 00000000000..272c4a479d7
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/misc/SparseSolve.h
@@ -0,0 +1,111 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2010 Gael Guennebaud <gael.guennebaud@inria.fr>
+//
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
+
+#ifndef EIGEN_SPARSE_SOLVE_H
+#define EIGEN_SPARSE_SOLVE_H
+
+namespace Eigen { 
+
+namespace internal {
+
+template<typename _DecompositionType, typename Rhs> struct sparse_solve_retval_base;
+template<typename _DecompositionType, typename Rhs> struct sparse_solve_retval;
+  
+template<typename DecompositionType, typename Rhs>
+struct traits<sparse_solve_retval_base<DecompositionType, Rhs> >
+{
+  typedef typename DecompositionType::MatrixType MatrixType;
+  typedef SparseMatrix<typename Rhs::Scalar, Rhs::Options, typename Rhs::Index> ReturnType;
+};
+
+template<typename _DecompositionType, typename Rhs> struct sparse_solve_retval_base
+ : public ReturnByValue<sparse_solve_retval_base<_DecompositionType, Rhs> >
+{
+  typedef typename remove_all<typename Rhs::Nested>::type RhsNestedCleaned;
+  typedef _DecompositionType DecompositionType;
+  typedef ReturnByValue<sparse_solve_retval_base> Base;
+  typedef typename Base::Index Index;
+
+  sparse_solve_retval_base(const DecompositionType& dec, const Rhs& rhs)
+    : m_dec(dec), m_rhs(rhs)
+  {}
+
+  inline Index rows() const { return m_dec.cols(); }
+  inline Index cols() const { return m_rhs.cols(); }
+  inline const DecompositionType& dec() const { return m_dec; }
+  inline const RhsNestedCleaned& rhs() const { return m_rhs; }
+
+  template<typename Dest> inline void evalTo(Dest& dst) const
+  {
+    static_cast<const sparse_solve_retval<DecompositionType,Rhs>*>(this)->evalTo(dst);
+  }
+
+  protected:
+    const DecompositionType& m_dec;
+    typename Rhs::Nested m_rhs;
+};
+
+#define EIGEN_MAKE_SPARSE_SOLVE_HELPERS(DecompositionType,Rhs) \
+  typedef typename DecompositionType::MatrixType MatrixType; \
+  typedef typename MatrixType::Scalar Scalar; \
+  typedef typename MatrixType::RealScalar RealScalar; \
+  typedef typename MatrixType::Index Index; \
+  typedef Eigen::internal::sparse_solve_retval_base<DecompositionType,Rhs> Base; \
+  using Base::dec; \
+  using Base::rhs; \
+  using Base::rows; \
+  using Base::cols; \
+  sparse_solve_retval(const DecompositionType& dec, const Rhs& rhs) \
+    : Base(dec, rhs) {}
+
+
+
+template<typename DecompositionType, typename Rhs, typename Guess> struct solve_retval_with_guess;
+
+template<typename DecompositionType, typename Rhs, typename Guess>
+struct traits<solve_retval_with_guess<DecompositionType, Rhs, Guess> >
+{
+  typedef typename DecompositionType::MatrixType MatrixType;
+  typedef Matrix<typename Rhs::Scalar,
+                 MatrixType::ColsAtCompileTime,
+                 Rhs::ColsAtCompileTime,
+                 Rhs::PlainObject::Options,
+                 MatrixType::MaxColsAtCompileTime,
+                 Rhs::MaxColsAtCompileTime> ReturnType;
+};
+
+template<typename DecompositionType, typename Rhs, typename Guess> struct solve_retval_with_guess
+ : public ReturnByValue<solve_retval_with_guess<DecompositionType, Rhs, Guess> >
+{
+  typedef typename DecompositionType::Index Index;
+
+  solve_retval_with_guess(const DecompositionType& dec, const Rhs& rhs, const Guess& guess)
+    : m_dec(dec), m_rhs(rhs), m_guess(guess)
+  {}
+
+  inline Index rows() const { return m_dec.cols(); }
+  inline Index cols() const { return m_rhs.cols(); }
+
+  template<typename Dest> inline void evalTo(Dest& dst) const
+  {
+    dst = m_guess;
+    m_dec._solveWithGuess(m_rhs,dst);
+  }
+
+  protected:
+    const DecompositionType& m_dec;
+    const typename Rhs::Nested m_rhs;
+    const typename Guess::Nested m_guess;
+};
+
+} // namepsace internal
+
+} // end namespace Eigen
+
+#endif // EIGEN_SPARSE_SOLVE_H
diff --git a/extern/Eigen3/Eigen/src/misc/blas.h b/extern/Eigen3/Eigen/src/misc/blas.h
new file mode 100644
index 00000000000..6fce99ed5c4
--- /dev/null
+++ b/extern/Eigen3/Eigen/src/misc/blas.h
@@ -0,0 +1,658 @@
+#ifndef BLAS_H
+#define BLAS_H
+
+#ifdef __cplusplus
+extern "C"
+{
+#endif
+
+#define BLASFUNC(FUNC) FUNC##_
+
+#ifdef __WIN64__
+typedef long long BLASLONG;
+typedef unsigned long long BLASULONG;
+#else
+typedef long BLASLONG;
+typedef unsigned long BLASULONG;
+#endif
+
+int    BLASFUNC(xerbla)(const char *, int *info, int);
+
+float  BLASFUNC(sdot)  (int *, float  *, int *, float  *, int *);
+float  BLASFUNC(sdsdot)(int *, float  *,        float  *, int *, float  *, int *);
+
+double BLASFUNC(dsdot) (int *, float  *, int *, float  *, int *);
+double BLASFUNC(ddot)  (int *, double *, int *, double *, int *);
+double BLASFUNC(qdot)  (int *, double *, int *, double *, int *);
+
+int  BLASFUNC(cdotuw)  (int *, float  *, int *, float  *, int *, float*);
+int  BLASFUNC(cdotcw)  (int *, float  *, int *, float  *, int *, float*);
+int  BLASFUNC(zdotuw)  (int *, double  *, int *, double  *, int *, double*);
+int  BLASFUNC(zdotcw)  (int *, double  *, int *, double  *, int *, double*);
+
+int    BLASFUNC(saxpy) (int *, float  *, float  *, int *, float  *, int *);
+int    BLASFUNC(daxpy) (int *, double *, double *, int *, double *, int *);
+int    BLASFUNC(qaxpy) (int *, double *, double *, int *, double *, int *);
+int    BLASFUNC(caxpy) (int *, float  *, float  *, int *, float  *, int *);
+int    BLASFUNC(zaxpy) (int *, double *, double *, int *, double *, int *);
+int    BLASFUNC(xaxpy) (int *, double *, double *, int *, double *, int *);
+int    BLASFUNC(caxpyc)(int *, float  *, float  *, int *, float  *, int *);
+int    BLASFUNC(zaxpyc)(int *, double *, double *, int *, double *, int *);
+int    BLASFUNC(xaxpyc)(int *, double *, double *, int *, double *, int *);
+
+int    BLASFUNC(scopy) (int *, float  *, int *, float  *, int *);
+int    BLASFUNC(dcopy) (int *, double *, int *, double *, int *);
+int    BLASFUNC(qcopy) (int *, double *, int *, double *, int *);
+int    BLASFUNC(ccopy) (int *, float  *, int *, float  *, int *);
+int    BLASFUNC(zcopy) (int *, double *, int *, double *, int *);
+int    BLASFUNC(xcopy) (int *, double *, int *, double *, int *);
+
+int    BLASFUNC(sswap) (int *, float  *, int *, float  *, int *);
+int    BLASFUNC(dswap) (int *, double *, int *, double *, int *);
+int    BLASFUNC(qswap) (int *, double *, int *, double *, int *);
+int    BLASFUNC(cswap) (int *, float  *, int *, float  *, int *);
+int    BLASFUNC(zswap) (int *, double *, int *, double *, int *);
+int    BLASFUNC(xswap) (int *, double *, int *, double *, int *);
+
+float  BLASFUNC(sasum) (int *, float  *, int *);
+float  BLASFUNC(scasum)(int *, float  *, int *);
+double BLASFUNC(dasum) (int *, double *, int *);
+double BLASFUNC(qasum) (int *, double *, int *);
+double BLASFUNC(dzasum)(int *, double *, int *);
+double BLASFUNC(qxasum)(int *, double *, int *);
+
+int    BLASFUNC(isamax)(int *, float  *, int *);
+int    BLASFUNC(idamax)(int *, double *, int *);
+int    BLASFUNC(iqamax)(int *, double *, int *);
+int    BLASFUNC(icamax)(int *, float  *, int *);
+int    BLASFUNC(izamax)(int *, double *, int *);
+int    BLASFUNC(ixamax)(int *, double *, int *);
+
+int    BLASFUNC(ismax) (int *, float  *, int *);
+int    BLASFUNC(idmax) (int *, double *, int *);
+int    BLASFUNC(iqmax) (int *, double *, int *);
+int    BLASFUNC(icmax) (int *, float  *, int *);
+int    BLASFUNC(izmax) (int *, double *, int *);
+int    BLASFUNC(ixmax) (int *, double *, int *);
+
+int    BLASFUNC(isamin)(int *, float  *, int *);
+int    BLASFUNC(idamin)(int *, double *, int *);
+int    BLASFUNC(iqamin)(int *, double *, int *);
+int    BLASFUNC(icamin)(int *, float  *, int *);
+int    BLASFUNC(izamin)(int *, double *, int *);
+int    BLASFUNC(ixamin)(int *, double *, int *);
+
+int    BLASFUNC(ismin)(int *, float  *, int *);
+int    BLASFUNC(idmin)(int *, double *, int *);
+int    BLASFUNC(iqmin)(int *, double *, int *);
+int    BLASFUNC(icmin)(int *, float  *, int *);
+int    BLASFUNC(izmin)(int *, double *, int *);
+int    BLASFUNC(ixmin)(int *, double *, int *);
+
+float  BLASFUNC(samax) (int *, float  *, int *);
+double BLASFUNC(damax) (int *, double *, int *);
+double BLASFUNC(qamax) (int *, double *, int *);
+float  BLASFUNC(scamax)(int *, float  *, int *);
+double BLASFUNC(dzamax)(int *, double *, int *);
+double BLASFUNC(qxamax)(int *, double *, int *);
+
+float  BLASFUNC(samin) (int *, float  *, int *);
+double BLASFUNC(damin) (int *, double *, int *);
+double BLASFUNC(qamin) (int *, double *, int *);
+float  BLASFUNC(scamin)(int *, float  *, int *);
+double BLASFUNC(dzamin)(int *, double *, int *);
+double BLASFUNC(qxamin)(int *, double *, int *);
+
+float  BLASFUNC(smax)  (int *, float  *, int *);
+double BLASFUNC(dmax)  (int *, double *, int *);
+double BLASFUNC(qmax)  (int *, double *, int *);
+float  BLASFUNC(scmax) (int *, float  *, int *);
+double BLASFUNC(dzmax) (int *, double *, int *);
+double BLASFUNC(qxmax) (int *, double *, int *);
+
+float  BLASFUNC(smin)  (int *, float  *, int *);
+double BLASFUNC(dmin)  (int *, double *, int *);
+double BLASFUNC(qmin)  (int *, double *, int *);
+float  BLASFUNC(scmin) (int *, float  *, int *);
+double BLASFUNC(dzmin) (int *, double *, int *);
+double BLASFUNC(qxmin) (int *, double *, int *);
+
+int    BLASFUNC(sscal) (int *,  float  *, float  *, int *);
+int    BLASFUNC(dscal) (int *,  double *, double *, int *);
+int    BLASFUNC(qscal) (int *,  double *, double *, int *);
+int    BLASFUNC(cscal) (int *,  float  *, float  *, int *);
+int    BLASFUNC(zscal) (int *,  double *, double *, int *);
+int    BLASFUNC(xscal) (int *,  double *, double *, int *);
+int    BLASFUNC(csscal)(int *,  float  *, float  *, int *);
+int    BLASFUNC(zdscal)(int *,  double *, double *, int *);
+int    BLASFUNC(xqscal)(int *,  double *, double *, int *);
+
+float  BLASFUNC(snrm2) (int *, float  *, int *);
+float  BLASFUNC(scnrm2)(int *, float  *, int *);
+
+double BLASFUNC(dnrm2) (int *, double *, int *);
+double BLASFUNC(qnrm2) (int *, double *, int *);
+double BLASFUNC(dznrm2)(int *, double *, int *);
+double BLASFUNC(qxnrm2)(int *, double *, int *);
+
+int    BLASFUNC(srot)  (int *, float  *, int *, float  *, int *, float  *, float  *);
+int    BLASFUNC(drot)  (int *, double *, int *, double *, int *, double *, double *);
+int    BLASFUNC(qrot)  (int *, double *, int *, double *, int *, double *, double *);
+int    BLASFUNC(csrot) (int *, float  *, int *, float  *, int *, float  *, float  *);
+int    BLASFUNC(zdrot) (int *, double *, int *, double *, int *, double *, double *);
+int    BLASFUNC(xqrot) (int *, double *, int *, double *, int *, double *, double *);
+
+int    BLASFUNC(srotg) (float  *, float  *, float  *, float  *);
+int    BLASFUNC(drotg) (double *, double *, double *, double *);
+int    BLASFUNC(qrotg) (double *, double *, double *, double *);
+int    BLASFUNC(crotg) (float  *, float  *, float  *, float  *);
+int    BLASFUNC(zrotg) (double *, double *, double *, double *);
+int    BLASFUNC(xrotg) (double *, double *, double *, double *);
+
+int    BLASFUNC(srotmg)(float  *, float  *, float  *, float  *, float  *);
+int    BLASFUNC(drotmg)(double *, double *, double *, double *, double *);
+
+int    BLASFUNC(srotm) (int *, float  *, int *, float  *, int *, float  *);
+int    BLASFUNC(drotm) (int *, double *, int *, double *, int *, double *);
+int    BLASFUNC(qrotm) (int *, double *, int *, double *, int *, double *);
+
+/* Level 2 routines */
+
+int BLASFUNC(sger)(int *,    int *, float *,  float *, int *,
+		   float *,  int *, float *,  int *);
+int BLASFUNC(dger)(int *,    int *, double *, double *, int *,
+		   double *, int *, double *, int *);
+int BLASFUNC(qger)(int *,    int *, double *, double *, int *,
+		   double *, int *, double *, int *);
+int BLASFUNC(cgeru)(int *,    int *, float *,  float *, int *,
+		    float *,  int *, float *,  int *);
+int BLASFUNC(cgerc)(int *,    int *, float *,  float *, int *,
+		    float *,  int *, float *,  int *);
+int BLASFUNC(zgeru)(int *,    int *, double *, double *, int *,
+		    double *, int *, double *, int *);
+int BLASFUNC(zgerc)(int *,    int *, double *, double *, int *,
+		    double *, int *, double *, int *);
+int BLASFUNC(xgeru)(int *,    int *, double *, double *, int *,
+		    double *, int *, double *, int *);
+int BLASFUNC(xgerc)(int *,    int *, double *, double *, int *,
+		    double *, int *, double *, int *);
+
+int BLASFUNC(sgemv)(char *, int *, int *, float  *, float  *, int *,
+		    float  *, int *, float  *, float  *, int *);
+int BLASFUNC(dgemv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(qgemv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(cgemv)(char *, int *, int *, float  *, float  *, int *,
+		    float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zgemv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(xgemv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+
+int BLASFUNC(strsv) (char *, char *, char *, int *, float  *, int *,
+		     float  *, int *);
+int BLASFUNC(dtrsv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+int BLASFUNC(qtrsv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+int BLASFUNC(ctrsv) (char *, char *, char *, int *, float  *, int *,
+		     float  *, int *);
+int BLASFUNC(ztrsv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+int BLASFUNC(xtrsv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+
+int BLASFUNC(stpsv) (char *, char *, char *, int *, float  *, float  *, int *);
+int BLASFUNC(dtpsv) (char *, char *, char *, int *, double *, double *, int *);
+int BLASFUNC(qtpsv) (char *, char *, char *, int *, double *, double *, int *);
+int BLASFUNC(ctpsv) (char *, char *, char *, int *, float  *, float  *, int *);
+int BLASFUNC(ztpsv) (char *, char *, char *, int *, double *, double *, int *);
+int BLASFUNC(xtpsv) (char *, char *, char *, int *, double *, double *, int *);
+
+int BLASFUNC(strmv) (char *, char *, char *, int *, float  *, int *,
+		     float  *, int *);
+int BLASFUNC(dtrmv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+int BLASFUNC(qtrmv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+int BLASFUNC(ctrmv) (char *, char *, char *, int *, float  *, int *,
+		     float  *, int *);
+int BLASFUNC(ztrmv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+int BLASFUNC(xtrmv) (char *, char *, char *, int *, double *, int *,
+		     double *, int *);
+
+int BLASFUNC(stpmv) (char *, char *, char *, int *, float  *, float  *, int *);
+int BLASFUNC(dtpmv) (char *, char *, char *, int *, double *, double *, int *);
+int BLASFUNC(qtpmv) (char *, char *, char *, int *, double *, double *, int *);
+int BLASFUNC(ctpmv) (char *, char *, char *, int *, float  *, float  *, int *);
+int BLASFUNC(ztpmv) (char *, char *, char *, int *, double *, double *, int *);
+int BLASFUNC(xtpmv) (char *, char *, char *, int *, double *, double *, int *);
+
+int BLASFUNC(stbmv) (char *, char *, char *, int *, int *, float  *, int *, float  *, int *);
+int BLASFUNC(dtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+int BLASFUNC(qtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+int BLASFUNC(ctbmv) (char *, char *, char *, int *, int *, float  *, int *, float  *, int *);
+int BLASFUNC(ztbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+int BLASFUNC(xtbmv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+
+int BLASFUNC(stbsv) (char *, char *, char *, int *, int *, float  *, int *, float  *, int *);
+int BLASFUNC(dtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+int BLASFUNC(qtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+int BLASFUNC(ctbsv) (char *, char *, char *, int *, int *, float  *, int *, float  *, int *);
+int BLASFUNC(ztbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+int BLASFUNC(xtbsv) (char *, char *, char *, int *, int *, double *, int *, double *, int *);
+
+int BLASFUNC(ssymv) (char *, int *, float  *, float *, int *,
+		     float  *, int *, float *, float *, int *);
+int BLASFUNC(dsymv) (char *, int *, double  *, double *, int *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(qsymv) (char *, int *, double  *, double *, int *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(csymv) (char *, int *, float  *, float *, int *,
+		     float  *, int *, float *, float *, int *);
+int BLASFUNC(zsymv) (char *, int *, double  *, double *, int *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(xsymv) (char *, int *, double  *, double *, int *,
+		     double  *, int *, double *, double *, int *);
+
+int BLASFUNC(sspmv) (char *, int *, float  *, float *,
+		     float  *, int *, float *, float *, int *);
+int BLASFUNC(dspmv) (char *, int *, double  *, double *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(qspmv) (char *, int *, double  *, double *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(cspmv) (char *, int *, float  *, float *,
+		     float  *, int *, float *, float *, int *);
+int BLASFUNC(zspmv) (char *, int *, double  *, double *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(xspmv) (char *, int *, double  *, double *,
+		     double  *, int *, double *, double *, int *);
+
+int BLASFUNC(ssyr) (char *, int *, float   *, float  *, int *,
+		    float  *, int *);
+int BLASFUNC(dsyr) (char *, int *, double  *, double *, int *,
+		    double *, int *);
+int BLASFUNC(qsyr) (char *, int *, double  *, double *, int *,
+		    double *, int *);
+int BLASFUNC(csyr) (char *, int *, float   *, float  *, int *,
+		    float  *, int *);
+int BLASFUNC(zsyr) (char *, int *, double  *, double *, int *,
+		    double *, int *);
+int BLASFUNC(xsyr) (char *, int *, double  *, double *, int *,
+		    double *, int *);
+
+int BLASFUNC(ssyr2) (char *, int *, float   *,
+		     float  *, int *, float  *, int *, float  *, int *);
+int BLASFUNC(dsyr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *, int *);
+int BLASFUNC(qsyr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *, int *);
+int BLASFUNC(csyr2) (char *, int *, float   *,
+		     float  *, int *, float  *, int *, float  *, int *);
+int BLASFUNC(zsyr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *, int *);
+int BLASFUNC(xsyr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *, int *);
+
+int BLASFUNC(sspr) (char *, int *, float   *, float  *, int *,
+		    float  *);
+int BLASFUNC(dspr) (char *, int *, double  *, double *, int *,
+		    double *);
+int BLASFUNC(qspr) (char *, int *, double  *, double *, int *,
+		    double *);
+int BLASFUNC(cspr) (char *, int *, float   *, float  *, int *,
+		    float  *);
+int BLASFUNC(zspr) (char *, int *, double  *, double *, int *,
+		    double *);
+int BLASFUNC(xspr) (char *, int *, double  *, double *, int *,
+		    double *);
+
+int BLASFUNC(sspr2) (char *, int *, float   *,
+		     float  *, int *, float  *, int *, float  *);
+int BLASFUNC(dspr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *);
+int BLASFUNC(qspr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *);
+int BLASFUNC(cspr2) (char *, int *, float   *,
+		     float  *, int *, float  *, int *, float  *);
+int BLASFUNC(zspr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *);
+int BLASFUNC(xspr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *);
+
+int BLASFUNC(cher) (char *, int *, float   *, float  *, int *,
+		    float  *, int *);
+int BLASFUNC(zher) (char *, int *, double  *, double *, int *,
+		    double *, int *);
+int BLASFUNC(xher) (char *, int *, double  *, double *, int *,
+		    double *, int *);
+
+int BLASFUNC(chpr) (char *, int *, float   *, float  *, int *, float  *);
+int BLASFUNC(zhpr) (char *, int *, double  *, double *, int *, double *);
+int BLASFUNC(xhpr) (char *, int *, double  *, double *, int *, double *);
+
+int BLASFUNC(cher2) (char *, int *, float   *,
+		     float  *, int *, float  *, int *, float  *, int *);
+int BLASFUNC(zher2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *, int *);
+int BLASFUNC(xher2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *, int *);
+
+int BLASFUNC(chpr2) (char *, int *, float   *,
+		     float  *, int *, float  *, int *, float  *);
+int BLASFUNC(zhpr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *);
+int BLASFUNC(xhpr2) (char *, int *, double  *,
+		     double *, int *, double *, int *, double *);
+
+int BLASFUNC(chemv) (char *, int *, float  *, float *, int *,
+		     float  *, int *, float *, float *, int *);
+int BLASFUNC(zhemv) (char *, int *, double  *, double *, int *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(xhemv) (char *, int *, double  *, double *, int *,
+		     double  *, int *, double *, double *, int *);
+
+int BLASFUNC(chpmv) (char *, int *, float  *, float *,
+		     float  *, int *, float *, float *, int *);
+int BLASFUNC(zhpmv) (char *, int *, double  *, double *,
+		     double  *, int *, double *, double *, int *);
+int BLASFUNC(xhpmv) (char *, int *, double  *, double *,
+		     double  *, int *, double *, double *, int *);
+
+int BLASFUNC(snorm)(char *, int *, int *, float  *, int *);
+int BLASFUNC(dnorm)(char *, int *, int *, double *, int *);
+int BLASFUNC(cnorm)(char *, int *, int *, float  *, int *);
+int BLASFUNC(znorm)(char *, int *, int *, double *, int *);
+
+int BLASFUNC(sgbmv)(char *, int *, int *, int *, int *, float  *, float  *, int *,
+		    float  *, int *, float  *, float  *, int *);
+int BLASFUNC(dgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(qgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(cgbmv)(char *, int *, int *, int *, int *, float  *, float  *, int *,
+		    float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(xgbmv)(char *, int *, int *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+
+int BLASFUNC(ssbmv)(char *, int *, int *, float  *, float  *, int *,
+		    float  *, int *, float  *, float  *, int *);
+int BLASFUNC(dsbmv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(qsbmv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(csbmv)(char *, int *, int *, float  *, float  *, int *,
+		    float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zsbmv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(xsbmv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+
+int BLASFUNC(chbmv)(char *, int *, int *, float  *, float  *, int *,
+		    float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zhbmv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+int BLASFUNC(xhbmv)(char *, int *, int *, double *, double *, int *,
+		    double *, int *, double *, double *, int *);
+
+/* Level 3 routines */
+
+int BLASFUNC(sgemm)(char *, char *, int *, int *, int *, float *,
+	   float  *, int *, float  *, int *, float  *, float  *, int *);
+int BLASFUNC(dgemm)(char *, char *, int *, int *, int *, double *,
+	   double *, int *, double *, int *, double *, double *, int *);
+int BLASFUNC(qgemm)(char *, char *, int *, int *, int *, double *,
+	   double *, int *, double *, int *, double *, double *, int *);
+int BLASFUNC(cgemm)(char *, char *, int *, int *, int *, float *,
+	   float  *, int *, float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zgemm)(char *, char *, int *, int *, int *, double *,
+	   double *, int *, double *, int *, double *, double *, int *);
+int BLASFUNC(xgemm)(char *, char *, int *, int *, int *, double *,
+	   double *, int *, double *, int *, double *, double *, int *);
+
+int BLASFUNC(cgemm3m)(char *, char *, int *, int *, int *, float *,
+	   float  *, int *, float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zgemm3m)(char *, char *, int *, int *, int *, double *,
+	   double *, int *, double *, int *, double *, double *, int *);
+int BLASFUNC(xgemm3m)(char *, char *, int *, int *, int *, double *,
+	   double *, int *, double *, int *, double *, double *, int *);
+
+int BLASFUNC(sge2mm)(char *, char *, char *, int *, int *,
+		     float *, float  *, int *, float  *, int *,
+		     float *, float  *, int *);
+int BLASFUNC(dge2mm)(char *, char *, char *, int *, int *,
+		     double *, double  *, int *, double  *, int *,
+		     double *, double  *, int *);
+int BLASFUNC(cge2mm)(char *, char *, char *, int *, int *,
+		     float *, float  *, int *, float  *, int *,
+		     float *, float  *, int *);
+int BLASFUNC(zge2mm)(char *, char *, char *, int *, int *,
+		     double *, double  *, int *, double  *, int *,
+		     double *, double  *, int *);
+
+int BLASFUNC(strsm)(char *, char *, char *, char *, int *, int *,
+	   float *,  float *, int *, float *, int *);
+int BLASFUNC(dtrsm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+int BLASFUNC(qtrsm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+int BLASFUNC(ctrsm)(char *, char *, char *, char *, int *, int *,
+	   float *,  float *, int *, float *, int *);
+int BLASFUNC(ztrsm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+int BLASFUNC(xtrsm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+
+int BLASFUNC(strmm)(char *, char *, char *, char *, int *, int *,
+	   float *,  float *, int *, float *, int *);
+int BLASFUNC(dtrmm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+int BLASFUNC(qtrmm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+int BLASFUNC(ctrmm)(char *, char *, char *, char *, int *, int *,
+	   float *,  float *, int *, float *, int *);
+int BLASFUNC(ztrmm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+int BLASFUNC(xtrmm)(char *, char *, char *, char *, int *, int *,
+	   double *,  double *, int *, double *, int *);
+
+int BLASFUNC(ssymm)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, int *, float  *, float  *, int *);
+int BLASFUNC(dsymm)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+int BLASFUNC(qsymm)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+int BLASFUNC(csymm)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zsymm)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+int BLASFUNC(xsymm)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+
+int BLASFUNC(csymm3m)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zsymm3m)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+int BLASFUNC(xsymm3m)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+
+int BLASFUNC(ssyrk)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, float  *, int *);
+int BLASFUNC(dsyrk)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, double *, int *);
+int BLASFUNC(qsyrk)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, double *, int *);
+int BLASFUNC(csyrk)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, float  *, int *);
+int BLASFUNC(zsyrk)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, double *, int *);
+int BLASFUNC(xsyrk)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, double *, int *);
+
+int BLASFUNC(ssyr2k)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float *, int *, float  *, float  *, int *);
+int BLASFUNC(dsyr2k)(char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+int BLASFUNC(qsyr2k)(char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+int BLASFUNC(csyr2k)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float *, int *, float  *, float  *, int *);
+int BLASFUNC(zsyr2k)(char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+int BLASFUNC(xsyr2k)(char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+
+int BLASFUNC(chemm)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zhemm)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+int BLASFUNC(xhemm)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+
+int BLASFUNC(chemm3m)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, int *, float  *, float  *, int *);
+int BLASFUNC(zhemm3m)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+int BLASFUNC(xhemm3m)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, int *, double *, double *, int *);
+
+int BLASFUNC(cherk)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float  *, float  *, int *);
+int BLASFUNC(zherk)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, double *, int *);
+int BLASFUNC(xherk)(char *, char *, int *, int *, double *, double *, int *,
+	   double *, double *, int *);
+
+int BLASFUNC(cher2k)(char *, char *, int *, int *, float  *, float  *, int *,
+	   float *, int *, float  *, float  *, int *);
+int BLASFUNC(zher2k)(char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+int BLASFUNC(xher2k)(char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+int BLASFUNC(cher2m)(char *, char *, char *, int *, int *, float  *, float  *, int *,
+	   float *, int *, float  *, float  *, int *);
+int BLASFUNC(zher2m)(char *, char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+int BLASFUNC(xher2m)(char *, char *, char *, int *, int *, double *, double *, int *,
+	   double*, int *, double *, double *, int *);
+
+int BLASFUNC(sgemt)(char *, int *, int *, float  *, float  *, int *,
+		    float  *, int *);
+int BLASFUNC(dgemt)(char *, int *, int *, double *, double *, int *,
+		    double *, int *);
+int BLASFUNC(cgemt)(char *, int *, int *, float  *, float  *, int *,
+		    float  *, int *);
+int BLASFUNC(zgemt)(char *, int *, int *, double *, double *, int *,
+		    double *, int *);
+
+int BLASFUNC(sgema)(char *, char *, int *, int *, float  *,
+		    float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(dgema)(char *, char *, int *, int *, double *,
+		    double *, int *, double*, double *, int *, double*, int *);
+int BLASFUNC(cgema)(char *, char *, int *, int *, float  *,
+		    float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(zgema)(char *, char *, int *, int *, double *,
+		    double *, int *, double*, double *, int *, double*, int *);
+
+int BLASFUNC(sgems)(char *, char *, int *, int *, float  *,
+		    float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(dgems)(char *, char *, int *, int *, double *,
+		    double *, int *, double*, double *, int *, double*, int *);
+int BLASFUNC(cgems)(char *, char *, int *, int *, float  *,
+		    float  *, int *, float *, float  *, int *, float *, int *);
+int BLASFUNC(zgems)(char *, char *, int *, int *, double *,
+		    double *, int *, double*, double *, int *, double*, int *);
+
+int BLASFUNC(sgetf2)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(dgetf2)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(qgetf2)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(cgetf2)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(zgetf2)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(xgetf2)(int *, int *, double *, int *, int *, int *);
+
+int BLASFUNC(sgetrf)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(dgetrf)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(qgetrf)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(cgetrf)(int *, int *, float  *, int *, int *, int *);
+int BLASFUNC(zgetrf)(int *, int *, double *, int *, int *, int *);
+int BLASFUNC(xgetrf)(int *, int *, double *, int *, int *, int *);
+
+int BLASFUNC(slaswp)(int *, float  *, int *, int *, int *, int *, int *);
+int BLASFUNC(dlaswp)(int *, double *, int *, int *, int *, int *, int *);
+int BLASFUNC(qlaswp)(int *, double *, int *, int *, int *, int *, int *);
+int BLASFUNC(claswp)(int *, float  *, int *, int *, int *, int *, int *);
+int BLASFUNC(zlaswp)(int *, double *, int *, int *, int *, int *, int *);
+int BLASFUNC(xlaswp)(int *, double *, int *, int *, int *, int *, int *);
+
+int BLASFUNC(sgetrs)(char *, int *, int *, float  *, int *, int *, float  *, int *, int *);
+int BLASFUNC(dgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+int BLASFUNC(qgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+int BLASFUNC(cgetrs)(char *, int *, int *, float  *, int *, int *, float  *, int *, int *);
+int BLASFUNC(zgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+int BLASFUNC(xgetrs)(char *, int *, int *, double *, int *, int *, double *, int *, int *);
+
+int BLASFUNC(sgesv)(int *, int *, float  *, int *, int *, float *, int *, int *);
+int BLASFUNC(dgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+int BLASFUNC(qgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+int BLASFUNC(cgesv)(int *, int *, float  *, int *, int *, float *, int *, int *);
+int BLASFUNC(zgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+int BLASFUNC(xgesv)(int *, int *, double *, int *, int *, double*, int *, int *);
+
+int BLASFUNC(spotf2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dpotf2)(char *, int *, double *, int *, int *);
+int BLASFUNC(qpotf2)(char *, int *, double *, int *, int *);
+int BLASFUNC(cpotf2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zpotf2)(char *, int *, double *, int *, int *);
+int BLASFUNC(xpotf2)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(spotrf)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dpotrf)(char *, int *, double *, int *, int *);
+int BLASFUNC(qpotrf)(char *, int *, double *, int *, int *);
+int BLASFUNC(cpotrf)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zpotrf)(char *, int *, double *, int *, int *);
+int BLASFUNC(xpotrf)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(slauu2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dlauu2)(char *, int *, double *, int *, int *);
+int BLASFUNC(qlauu2)(char *, int *, double *, int *, int *);
+int BLASFUNC(clauu2)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zlauu2)(char *, int *, double *, int *, int *);
+int BLASFUNC(xlauu2)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(slauum)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dlauum)(char *, int *, double *, int *, int *);
+int BLASFUNC(qlauum)(char *, int *, double *, int *, int *);
+int BLASFUNC(clauum)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zlauum)(char *, int *, double *, int *, int *);
+int BLASFUNC(xlauum)(char *, int *, double *, int *, int *);
+
+int BLASFUNC(strti2)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(dtrti2)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(qtrti2)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(ctrti2)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(ztrti2)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(xtrti2)(char *, char *, int *, double *, int *, int *);
+
+int BLASFUNC(strtri)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(dtrtri)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(qtrtri)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(ctrtri)(char *, char *, int *, float  *, int *, int *);
+int BLASFUNC(ztrtri)(char *, char *, int *, double *, int *, int *);
+int BLASFUNC(xtrtri)(char *, char *, int *, double *, int *, int *);
+
+int BLASFUNC(spotri)(char *, int *, float  *, int *, int *);
+int BLASFUNC(dpotri)(char *, int *, double *, int *, int *);
+int BLASFUNC(qpotri)(char *, int *, double *, int *, int *);
+int BLASFUNC(cpotri)(char *, int *, float  *, int *, int *);
+int BLASFUNC(zpotri)(char *, int *, double *, int *, int *);
+int BLASFUNC(xpotri)(char *, int *, double *, int *, int *);
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif
diff --git a/extern/Eigen3/Eigen/src/plugins/ArrayCwiseBinaryOps.h b/extern/Eigen3/Eigen/src/plugins/ArrayCwiseBinaryOps.h
index 7d509e78f3a..5b979ebf89d 100644
--- a/extern/Eigen3/Eigen/src/plugins/ArrayCwiseBinaryOps.h
+++ b/extern/Eigen3/Eigen/src/plugins/ArrayCwiseBinaryOps.h
@@ -29,6 +29,16 @@ operator/(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
   */
 EIGEN_MAKE_CWISE_BINARY_OP(min,internal::scalar_min_op)
 
+/** \returns an expression of the coefficient-wise min of \c *this and scalar \a other
+  *
+  * \sa max()
+  */
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const ConstantReturnType>
+(min)(const Scalar &other) const
+{
+  return (min)(Derived::PlainObject::Constant(rows(), cols(), other));
+}
+
 /** \returns an expression of the coefficient-wise max of \c *this and \a other
   *
   * Example: \include Cwise_max.cpp
@@ -38,6 +48,16 @@ EIGEN_MAKE_CWISE_BINARY_OP(min,internal::scalar_min_op)
   */
 EIGEN_MAKE_CWISE_BINARY_OP(max,internal::scalar_max_op)
 
+/** \returns an expression of the coefficient-wise max of \c *this and scalar \a other
+  *
+  * \sa min()
+  */
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const ConstantReturnType>
+(max)(const Scalar &other) const
+{
+  return (max)(Derived::PlainObject::Constant(rows(), cols(), other));
+}
+
 /** \returns an expression of the coefficient-wise \< operator of *this and \a other
   *
   * Example: \include Cwise_less.cpp
@@ -141,3 +161,39 @@ operator-(const Scalar& scalar,const EIGEN_CURRENT_STORAGE_BASE_CLASS<Derived>&
 {
   return (-other) + scalar;
 }
+
+/** \returns an expression of the coefficient-wise && operator of *this and \a other
+  *
+  * \warning this operator is for expression of bool only.
+  *
+  * Example: \include Cwise_boolean_and.cpp
+  * Output: \verbinclude Cwise_boolean_and.out
+  *
+  * \sa operator||(), select()
+  */
+template<typename OtherDerived>
+inline const CwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>
+operator&&(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
+{
+  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value && internal::is_same<bool,typename OtherDerived::Scalar>::value),
+                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
+  return CwiseBinaryOp<internal::scalar_boolean_and_op, const Derived, const OtherDerived>(derived(),other.derived());
+}
+
+/** \returns an expression of the coefficient-wise || operator of *this and \a other
+  *
+  * \warning this operator is for expression of bool only.
+  *
+  * Example: \include Cwise_boolean_or.cpp
+  * Output: \verbinclude Cwise_boolean_or.out
+  *
+  * \sa operator&&(), select()
+  */
+template<typename OtherDerived>
+inline const CwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>
+operator||(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
+{
+  EIGEN_STATIC_ASSERT((internal::is_same<bool,Scalar>::value && internal::is_same<bool,typename OtherDerived::Scalar>::value),
+                      THIS_METHOD_IS_ONLY_FOR_EXPRESSIONS_OF_BOOL);
+  return CwiseBinaryOp<internal::scalar_boolean_or_op, const Derived, const OtherDerived>(derived(),other.derived());
+}
diff --git a/extern/Eigen3/Eigen/src/plugins/BlockMethods.h b/extern/Eigen3/Eigen/src/plugins/BlockMethods.h
index 4eba933388a..ef224001a54 100644
--- a/extern/Eigen3/Eigen/src/plugins/BlockMethods.h
+++ b/extern/Eigen3/Eigen/src/plugins/BlockMethods.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 #ifndef EIGEN_BLOCKMETHODS_H
 #define EIGEN_BLOCKMETHODS_H
diff --git a/extern/Eigen3/Eigen/src/plugins/CommonCwiseBinaryOps.h b/extern/Eigen3/Eigen/src/plugins/CommonCwiseBinaryOps.h
index 8f7765e72bd..688d2244088 100644
--- a/extern/Eigen3/Eigen/src/plugins/CommonCwiseBinaryOps.h
+++ b/extern/Eigen3/Eigen/src/plugins/CommonCwiseBinaryOps.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // This file is a base class plugin containing common coefficient wise functions.
 
diff --git a/extern/Eigen3/Eigen/src/plugins/CommonCwiseUnaryOps.h b/extern/Eigen3/Eigen/src/plugins/CommonCwiseUnaryOps.h
index 941d5153c59..08e931aaddd 100644
--- a/extern/Eigen3/Eigen/src/plugins/CommonCwiseUnaryOps.h
+++ b/extern/Eigen3/Eigen/src/plugins/CommonCwiseUnaryOps.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // This file is a base class plugin containing common coefficient wise functions.
 
diff --git a/extern/Eigen3/Eigen/src/plugins/MatrixCwiseBinaryOps.h b/extern/Eigen3/Eigen/src/plugins/MatrixCwiseBinaryOps.h
index 35183f91f80..3a737df7b86 100644
--- a/extern/Eigen3/Eigen/src/plugins/MatrixCwiseBinaryOps.h
+++ b/extern/Eigen3/Eigen/src/plugins/MatrixCwiseBinaryOps.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // This file is a base class plugin containing matrix specifics coefficient wise functions.
 
@@ -91,6 +76,16 @@ cwiseMin(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
   return CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
 
+/** \returns an expression of the coefficient-wise min of *this and scalar \a other
+  *
+  * \sa class CwiseBinaryOp, min()
+  */
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_min_op<Scalar>, const Derived, const ConstantReturnType>
+cwiseMin(const Scalar &other) const
+{
+  return cwiseMin(Derived::PlainObject::Constant(rows(), cols(), other));
+}
+
 /** \returns an expression of the coefficient-wise max of *this and \a other
   *
   * Example: \include MatrixBase_cwiseMax.cpp
@@ -105,6 +100,17 @@ cwiseMax(const EIGEN_CURRENT_STORAGE_BASE_CLASS<OtherDerived> &other) const
   return CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const OtherDerived>(derived(), other.derived());
 }
 
+/** \returns an expression of the coefficient-wise max of *this and scalar \a other
+  *
+  * \sa class CwiseBinaryOp, min()
+  */
+EIGEN_STRONG_INLINE const CwiseBinaryOp<internal::scalar_max_op<Scalar>, const Derived, const ConstantReturnType>
+cwiseMax(const Scalar &other) const
+{
+  return cwiseMax(Derived::PlainObject::Constant(rows(), cols(), other));
+}
+
+
 /** \returns an expression of the coefficient-wise quotient of *this and \a other
   *
   * Example: \include MatrixBase_cwiseQuotient.cpp
diff --git a/extern/Eigen3/Eigen/src/plugins/MatrixCwiseUnaryOps.h b/extern/Eigen3/Eigen/src/plugins/MatrixCwiseUnaryOps.h
index a3d9a0e1465..0cf0640bae6 100644
--- a/extern/Eigen3/Eigen/src/plugins/MatrixCwiseUnaryOps.h
+++ b/extern/Eigen3/Eigen/src/plugins/MatrixCwiseUnaryOps.h
@@ -4,24 +4,9 @@
 // Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
 // Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
-// Eigen is free software; you can redistribute it and/or
-// modify it under the terms of the GNU Lesser General Public
-// License as published by the Free Software Foundation; either
-// version 3 of the License, or (at your option) any later version.
-//
-// Alternatively, you can redistribute it and/or
-// modify it under the terms of the GNU General Public License as
-// published by the Free Software Foundation; either version 2 of
-// the License, or (at your option) any later version.
-//
-// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
-// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
-// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
-// GNU General Public License for more details.
-//
-// You should have received a copy of the GNU Lesser General Public
-// License and a copy of the GNU General Public License along with
-// Eigen. If not, see <http://www.gnu.org/licenses/>.
+// This Source Code Form is subject to the terms of the Mozilla
+// Public License v. 2.0. If a copy of the MPL was not distributed
+// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
 
 // This file is a base class plugin containing matrix specifics coefficient wise functions.
 
diff --git a/extern/bullet2/patches/convex_hull.patch b/extern/bullet2/patches/convex_hull.patch
new file mode 100644
index 00000000000..1b2978221fb
--- /dev/null
+++ b/extern/bullet2/patches/convex_hull.patch
@@ -0,0 +1,127 @@
+Index: extern/bullet2/src/Bullet-C-Api.h
+===================================================================
+--- extern/bullet2/src/Bullet-C-Api.h	(revision 51556)
++++ extern/bullet2/src/Bullet-C-Api.h	(working copy)
+@@ -167,6 +167,16 @@ extern "C" {
+ 	// needed for source/blender/blenkernel/intern/collision.c
+ 	double plNearestPoints(float p1[3], float p2[3], float p3[3], float q1[3], float q2[3], float q3[3], float *pa, float *pb, float normal[3]);
+ 
++
++	/* Convex Hull */
++	PL_DECLARE_HANDLE(plConvexHull);
++	plConvexHull plConvexHullCompute(float (*coords)[3], int count);
++	int plConvexHullNumVertices(plConvexHull hull);
++	int plConvexHullNumFaces(plConvexHull hull);
++	void plConvexHullGetVertex(plConvexHull hull, int n, float coords[3], int *original_index);
++	int plConvexHullGetFaceSize(plConvexHull hull, int n);
++	void plConvexHullGetFaceVertices(plConvexHull hull, int n, int *vertices);
++
+ #ifdef __cplusplus
+ }
+ #endif
+Index: extern/bullet2/src/BulletDynamics/Dynamics/Bullet-C-API.cpp
+===================================================================
+--- extern/bullet2/src/BulletDynamics/Dynamics/Bullet-C-API.cpp	(revision 51556)
++++ extern/bullet2/src/BulletDynamics/Dynamics/Bullet-C-API.cpp	(working copy)
+@@ -23,7 +23,7 @@ subject to the following restrictions:
+ #include "Bullet-C-Api.h"
+ #include "btBulletDynamicsCommon.h"
+ #include "LinearMath/btAlignedAllocator.h"
+-
++#include "LinearMath/btConvexHullComputer.h"
+ 
+ 
+ #include "LinearMath/btVector3.h"
+@@ -403,3 +403,60 @@ double plNearestPoints(float p1[3], float p2[3], float p3[3], float q1[3], float
+ 	return -1.0f;	
+ }
+ 
++// Convex hull
++plConvexHull plConvexHullCompute(float (*coords)[3], int count)
++{
++	btConvexHullComputer *computer = new btConvexHullComputer;
++	computer->compute(reinterpret_cast< float* >(coords),
++					  sizeof(*coords), count, 0, 0);
++	return reinterpret_cast<plConvexHull>(computer);
++}
++
++int plConvexHullNumVertices(plConvexHull hull)
++{
++	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
++	return computer->vertices.size();
++}
++
++int plConvexHullNumFaces(plConvexHull hull)
++{
++	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
++	return computer->faces.size();
++}
++
++void plConvexHullGetVertex(plConvexHull hull, int n, float coords[3],
++						   int *original_index)
++{
++	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
++	const btVector3 &v(computer->vertices[n]);
++	coords[0] = v[0];
++	coords[1] = v[1];
++	coords[2] = v[2];
++	(*original_index) = computer->original_vertex_index[n];
++}
++
++int plConvexHullGetFaceSize(plConvexHull hull, int n)
++{
++	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
++	const btConvexHullComputer::Edge *e_orig, *e;
++	int count;
++
++	for (e_orig = &computer->edges[computer->faces[n]], e = e_orig, count = 0;
++		 count == 0 || e != e_orig;
++		 e = e->getNextEdgeOfFace(), count++);
++	return count;
++}
++
++void plConvexHullGetFaceVertices(plConvexHull hull, int n, int *vertices)
++{
++	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
++	const btConvexHullComputer::Edge *e_orig, *e;
++	int count;
++
++	for (e_orig = &computer->edges[computer->faces[n]], e = e_orig, count = 0;
++		 count == 0 || e != e_orig;
++		 e = e->getNextEdgeOfFace(), count++)
++	{
++		vertices[count] = e->getTargetVertex();
++	}
++}
+Index: extern/bullet2/src/LinearMath/btConvexHullComputer.cpp
+===================================================================
+--- extern/bullet2/src/LinearMath/btConvexHullComputer.cpp	(revision 51556)
++++ extern/bullet2/src/LinearMath/btConvexHullComputer.cpp	(working copy)
+@@ -2661,6 +2661,7 @@ btScalar btConvexHullComputer::compute(const void* coords, bool doubleCoords, in
+ 	}
+ 
+ 	vertices.resize(0);
++	original_vertex_index.resize(0);
+ 	edges.resize(0);
+ 	faces.resize(0);
+ 
+@@ -2671,6 +2672,7 @@ btScalar btConvexHullComputer::compute(const void* coords, bool doubleCoords, in
+ 	{
+ 		btConvexHullInternal::Vertex* v = oldVertices[copied];
+ 		vertices.push_back(hull.getCoordinates(v));
++		original_vertex_index.push_back(v->point.index);
+ 		btConvexHullInternal::Edge* firstEdge = v->edges;
+ 		if (firstEdge)
+ 		{
+Index: extern/bullet2/src/LinearMath/btConvexHullComputer.h
+===================================================================
+--- extern/bullet2/src/LinearMath/btConvexHullComputer.h	(revision 51556)
++++ extern/bullet2/src/LinearMath/btConvexHullComputer.h	(working copy)
+@@ -67,6 +67,7 @@ class btConvexHullComputer
+ 
+ 		// Vertices of the output hull
+ 		btAlignedObjectArray<btVector3> vertices;
++		btAlignedObjectArray<int> original_vertex_index;
+ 
+ 		// Edges of the output hull
+ 		btAlignedObjectArray<Edge> edges;
diff --git a/extern/bullet2/readme.txt b/extern/bullet2/readme.txt
index 343cb104c4d..7f5a7f1e163 100644
--- a/extern/bullet2/readme.txt
+++ b/extern/bullet2/readme.txt
@@ -14,6 +14,8 @@ Apply patches/make_id.patch to prevent duplicated define of MAKE_ID macro in ble
 side and bullet side.
 Sergey
 
-Apply patches/ghost_character.path to prevent characters from colliding with ghost objects.
+Apply patches/ghost_character.patch to prevent characters from colliding with ghost objects.
 Mitchell
 
+Apply patches/convex_hull.patch to add access to the convex hull
+operation, used in the BMesh convex hull operator.
diff --git a/extern/bullet2/src/Bullet-C-Api.h b/extern/bullet2/src/Bullet-C-Api.h
index f27a17d51f7..2eabf3840e1 100644
--- a/extern/bullet2/src/Bullet-C-Api.h
+++ b/extern/bullet2/src/Bullet-C-Api.h
@@ -167,6 +167,16 @@ extern "C" {
 	// needed for source/blender/blenkernel/intern/collision.c
 	double plNearestPoints(float p1[3], float p2[3], float p3[3], float q1[3], float q2[3], float q3[3], float *pa, float *pb, float normal[3]);
 
+
+	/* Convex Hull */
+	PL_DECLARE_HANDLE(plConvexHull);
+	plConvexHull plConvexHullCompute(float (*coords)[3], int count);
+	int plConvexHullNumVertices(plConvexHull hull);
+	int plConvexHullNumFaces(plConvexHull hull);
+	void plConvexHullGetVertex(plConvexHull hull, int n, float coords[3], int *original_index);
+	int plConvexHullGetFaceSize(plConvexHull hull, int n);
+	void plConvexHullGetFaceVertices(plConvexHull hull, int n, int *vertices);
+
 #ifdef __cplusplus
 }
 #endif
diff --git a/extern/bullet2/src/BulletDynamics/Dynamics/Bullet-C-API.cpp b/extern/bullet2/src/BulletDynamics/Dynamics/Bullet-C-API.cpp
index bd8e2748383..cf735569a9d 100644
--- a/extern/bullet2/src/BulletDynamics/Dynamics/Bullet-C-API.cpp
+++ b/extern/bullet2/src/BulletDynamics/Dynamics/Bullet-C-API.cpp
@@ -23,7 +23,7 @@ subject to the following restrictions:
 #include "Bullet-C-Api.h"
 #include "btBulletDynamicsCommon.h"
 #include "LinearMath/btAlignedAllocator.h"
-
+#include "LinearMath/btConvexHullComputer.h"
 
 
 #include "LinearMath/btVector3.h"
@@ -403,3 +403,60 @@ double plNearestPoints(float p1[3], float p2[3], float p3[3], float q1[3], float
 	return -1.0f;	
 }
 
+// Convex hull
+plConvexHull plConvexHullCompute(float (*coords)[3], int count)
+{
+	btConvexHullComputer *computer = new btConvexHullComputer;
+	computer->compute(reinterpret_cast< float* >(coords),
+					  sizeof(*coords), count, 0, 0);
+	return reinterpret_cast<plConvexHull>(computer);
+}
+
+int plConvexHullNumVertices(plConvexHull hull)
+{
+	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
+	return computer->vertices.size();
+}
+
+int plConvexHullNumFaces(plConvexHull hull)
+{
+	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
+	return computer->faces.size();
+}
+
+void plConvexHullGetVertex(plConvexHull hull, int n, float coords[3],
+						   int *original_index)
+{
+	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
+	const btVector3 &v(computer->vertices[n]);
+	coords[0] = v[0];
+	coords[1] = v[1];
+	coords[2] = v[2];
+	(*original_index) = computer->original_vertex_index[n];
+}
+
+int plConvexHullGetFaceSize(plConvexHull hull, int n)
+{
+	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
+	const btConvexHullComputer::Edge *e_orig, *e;
+	int count;
+
+	for (e_orig = &computer->edges[computer->faces[n]], e = e_orig, count = 0;
+		 count == 0 || e != e_orig;
+		 e = e->getNextEdgeOfFace(), count++);
+	return count;
+}
+
+void plConvexHullGetFaceVertices(plConvexHull hull, int n, int *vertices)
+{
+	btConvexHullComputer *computer(reinterpret_cast< btConvexHullComputer* >(hull));
+	const btConvexHullComputer::Edge *e_orig, *e;
+	int count;
+
+	for (e_orig = &computer->edges[computer->faces[n]], e = e_orig, count = 0;
+		 count == 0 || e != e_orig;
+		 e = e->getNextEdgeOfFace(), count++)
+	{
+		vertices[count] = e->getTargetVertex();
+	}
+}
diff --git a/extern/bullet2/src/LinearMath/btConvexHullComputer.cpp b/extern/bullet2/src/LinearMath/btConvexHullComputer.cpp
index c03c901c051..4fd81dac107 100644
--- a/extern/bullet2/src/LinearMath/btConvexHullComputer.cpp
+++ b/extern/bullet2/src/LinearMath/btConvexHullComputer.cpp
@@ -2661,6 +2661,7 @@ btScalar btConvexHullComputer::compute(const void* coords, bool doubleCoords, in
 	}
 
 	vertices.resize(0);
+	original_vertex_index.resize(0);
 	edges.resize(0);
 	faces.resize(0);
 
@@ -2671,6 +2672,7 @@ btScalar btConvexHullComputer::compute(const void* coords, bool doubleCoords, in
 	{
 		btConvexHullInternal::Vertex* v = oldVertices[copied];
 		vertices.push_back(hull.getCoordinates(v));
+		original_vertex_index.push_back(v->point.index);
 		btConvexHullInternal::Edge* firstEdge = v->edges;
 		if (firstEdge)
 		{
diff --git a/extern/bullet2/src/LinearMath/btConvexHullComputer.h b/extern/bullet2/src/LinearMath/btConvexHullComputer.h
index 7240ac4fb52..6871ce80e00 100644
--- a/extern/bullet2/src/LinearMath/btConvexHullComputer.h
+++ b/extern/bullet2/src/LinearMath/btConvexHullComputer.h
@@ -67,6 +67,7 @@ class btConvexHullComputer
 
 		// Vertices of the output hull
 		btAlignedObjectArray<btVector3> vertices;
+		btAlignedObjectArray<int> original_vertex_index;
 
 		// Edges of the output hull
 		btAlignedObjectArray<Edge> edges;
diff --git a/extern/carve/CMakeLists.txt b/extern/carve/CMakeLists.txt
index 3916047ff32..5e917ac1e44 100644
--- a/extern/carve/CMakeLists.txt
+++ b/extern/carve/CMakeLists.txt
@@ -158,7 +158,7 @@ if(WITH_BOOST)
 		-DCARVE_SYSTEM_BOOST
 	)
 
-	list(APPEND INC
+	list(APPEND INC_SYS
 		${BOOST_INCLUDE_DIR}
 	)
 endif()
diff --git a/extern/libmv/CMakeLists.txt b/extern/libmv/CMakeLists.txt
index 60cd84d89d4..38be34add75 100644
--- a/extern/libmv/CMakeLists.txt
+++ b/extern/libmv/CMakeLists.txt
@@ -28,31 +28,18 @@
 
 set(INC
 	.
-	../Eigen3
-	third_party/ssba
-	third_party/ldl/Include
 	../colamd/Include
 	third_party/ceres/include
 )
 
 set(INC_SYS
+	../Eigen3
+	third_party/ssba
+	third_party/ldl/Include
 	${PNG_INCLUDE_DIR}
 	${ZLIB_INCLUDE_DIRS}
 )
 
-
-# XXX - FIXME
-# this is a momentary hack to find unwind.h in 10.6.sdk
-if(APPLE)
-	if(${CMAKE_OSX_DEPLOYMENT_TARGET} STREQUAL "10.6")
-		list(APPEND INC_SYS
-			${CMAKE_OSX_SYSROOT}/Developer/usr/llvm-gcc-4.2/lib/gcc/i686-apple-darwin10/4.2.1/include
-		)
-	endif()
-endif()
-# XXX - END
-
-
 set(SRC
 	libmv-capi.cpp
 	libmv/image/array_nd.cc
diff --git a/extern/libmv/bundle.sh b/extern/libmv/bundle.sh
index 3f877508c46..1e386ec8096 100755
--- a/extern/libmv/bundle.sh
+++ b/extern/libmv/bundle.sh
@@ -124,14 +124,14 @@ cat > CMakeLists.txt << EOF
 
 set(INC
 	.
-	../Eigen3
-	third_party/ssba
-	third_party/ldl/Include
 	../colamd/Include
 	third_party/ceres/include
 )
 
 set(INC_SYS
+	../Eigen3
+	third_party/ssba
+	third_party/ldl/Include
 	\${PNG_INCLUDE_DIR}
 	\${ZLIB_INCLUDE_DIRS}
 )
diff --git a/extern/libmv/libmv-capi.cpp b/extern/libmv/libmv-capi.cpp
index 3d3b7398c9b..a15927f881d 100644
--- a/extern/libmv/libmv-capi.cpp
+++ b/extern/libmv/libmv-capi.cpp
@@ -523,7 +523,7 @@ int libmv_refineParametersAreValid(int parameters) {
 	                       LIBMV_REFINE_RADIAL_DISTORTION_K1));
 }
 
-void libmv_solveRefineIntrinsics(libmv::Tracks *tracks, libmv::CameraIntrinsics *intrinsics,
+static void libmv_solveRefineIntrinsics(libmv::Tracks *tracks, libmv::CameraIntrinsics *intrinsics,
 			libmv::EuclideanReconstruction *reconstruction, int refine_intrinsics,
 			reconstruct_progress_update_cb progress_update_callback, void *callback_customdata)
 {
@@ -550,7 +550,8 @@ void libmv_solveRefineIntrinsics(libmv::Tracks *tracks, libmv::CameraIntrinsics
 }
 
 libmv_Reconstruction *libmv_solveReconstruction(libmv_Tracks *tracks, int keyframe1, int keyframe2,
-			int refine_intrinsics, double focal_length, double principal_x, double principal_y, double k1, double k2, double k3,
+			int refine_intrinsics, double focal_length, double principal_x, double principal_y,
+			double k1, double k2, double k3, struct libmv_reconstructionOptions *options,
 			reconstruct_progress_update_cb progress_update_callback, void *callback_customdata)
 {
 	/* Invert the camera intrinsics. */
@@ -558,6 +559,7 @@ libmv_Reconstruction *libmv_solveReconstruction(libmv_Tracks *tracks, int keyfra
 	libmv_Reconstruction *libmv_reconstruction = new libmv_Reconstruction();
 	libmv::EuclideanReconstruction *reconstruction = &libmv_reconstruction->reconstruction;
 	libmv::CameraIntrinsics *intrinsics = &libmv_reconstruction->intrinsics;
+	libmv::ReconstructionOptions reconstruction_options;
 
 	ReconstructUpdateCallback update_callback =
 		ReconstructUpdateCallback(progress_update_callback, callback_customdata);
@@ -566,6 +568,9 @@ libmv_Reconstruction *libmv_solveReconstruction(libmv_Tracks *tracks, int keyfra
 	intrinsics->SetPrincipalPoint(principal_x, principal_y);
 	intrinsics->SetRadialDistortion(k1, k2, k3);
 
+	reconstruction_options.success_threshold = options->success_threshold;
+	reconstruction_options.use_fallback_reconstruction = options->use_fallback_reconstruction;
+
 	for (int i = 0; i < markers.size(); ++i) {
 		intrinsics->InvertIntrinsics(markers[i].x,
 			markers[i].y,
@@ -584,7 +589,8 @@ libmv_Reconstruction *libmv_solveReconstruction(libmv_Tracks *tracks, int keyfra
 
 	libmv::EuclideanReconstructTwoFrames(keyframe_markers, reconstruction);
 	libmv::EuclideanBundle(normalized_tracks, reconstruction);
-	libmv::EuclideanCompleteReconstruction(normalized_tracks, reconstruction, &update_callback);
+	libmv::EuclideanCompleteReconstruction(reconstruction_options, normalized_tracks,
+	                                       reconstruction, &update_callback);
 
 	if (refine_intrinsics) {
 		libmv_solveRefineIntrinsics((libmv::Tracks *)tracks, intrinsics, reconstruction,
@@ -1027,7 +1033,7 @@ void libmv_InvertIntrinsics(double focal_length, double principal_x, double prin
 
 /* ************ point clouds ************ */
 
-void libmvTransformToMat4(libmv::Mat3 &R, libmv::Vec3 &S, libmv::Vec3 &t, double M[4][4])
+static void libmvTransformToMat4(libmv::Mat3 &R, libmv::Vec3 &S, libmv::Vec3 &t, double M[4][4])
 {
 	for (int j = 0; j < 3; ++j)
 		for (int k = 0; k < 3; ++k)
diff --git a/extern/libmv/libmv-capi.h b/extern/libmv/libmv-capi.h
index fc3b6f94f62..e5885e7addf 100644
--- a/extern/libmv/libmv-capi.h
+++ b/extern/libmv/libmv-capi.h
@@ -91,13 +91,20 @@ void libmv_tracksDestroy(struct libmv_Tracks *libmv_tracks);
 #define LIBMV_REFINE_RADIAL_DISTORTION_K1 (1<<2)
 #define LIBMV_REFINE_RADIAL_DISTORTION_K2 (1<<4)
 
+/* TODO: make keyframes/distortion model a part of options? */
+struct libmv_reconstructionOptions {
+	double success_threshold;
+	int use_fallback_reconstruction;
+};
+
 typedef void (*reconstruct_progress_update_cb) (void *customdata, double progress, const char *message);
 
 int libmv_refineParametersAreValid(int parameters);
 
 struct libmv_Reconstruction *libmv_solveReconstruction(struct libmv_Tracks *tracks, int keyframe1, int keyframe2,
 			int refine_intrinsics, double focal_length, double principal_x, double principal_y, double k1, double k2, double k3,
-			reconstruct_progress_update_cb progress_update_callback, void *callback_customdata);
+			struct libmv_reconstructionOptions *options, reconstruct_progress_update_cb progress_update_callback,
+			void *callback_customdata);
 struct libmv_Reconstruction *libmv_solveModal(struct libmv_Tracks *tracks, double focal_length,
 			double principal_x, double principal_y, double k1, double k2, double k3,
 			reconstruct_progress_update_cb progress_update_callback, void *callback_customdata);
@@ -147,14 +154,14 @@ void libmv_CameraIntrinsicsDistortFloat(struct libmv_CameraIntrinsics *libmvIntr
 
 /* dsitortion */
 void libmv_undistortByte(double focal_length, double principal_x, double principal_y, double k1, double k2, double k3,
-			unsigned char *src, unsigned char *dst, int width, int height, int channels);
+			unsigned char *src, unsigned char *dst, int width, int height, float overscan, int channels);
 void libmv_undistortFloat(double focal_length, double principal_x, double principal_y, double k1, double k2, double k3,
-			float *src, float *dst, int width, int height, int channels);
+			float *src, float *dst, int width, int height, float overscan, int channels);
 
 void libmv_distortByte(double focal_length, double principal_x, double principal_y, double k1, double k2, double k3,
-			unsigned char *src, unsigned char *dst, int width, int height, int channels);
+			unsigned char *src, unsigned char *dst, int width, int height, float overscan, int channels);
 void libmv_distortFloat(double focal_length, double principal_x, double principal_y, double k1, double k2, double k3,
-			float *src, float *dst, int width, int height, int channels);
+			float *src, float *dst, int width, int height, float overscan, int channels);
 
 /* utils */
 void libmv_applyCameraIntrinsics(double focal_length, double principal_x, double principal_y, double k1, double k2, double k3,
diff --git a/extern/libmv/libmv/multiview/euclidean_resection.cc b/extern/libmv/libmv/multiview/euclidean_resection.cc
index 92862515d7e..2605bf04622 100644
--- a/extern/libmv/libmv/multiview/euclidean_resection.cc
+++ b/extern/libmv/libmv/multiview/euclidean_resection.cc
@@ -37,13 +37,14 @@ typedef unsigned int uint;
 bool EuclideanResection(const Mat2X &x_camera, 
                         const Mat3X &X_world,
                         Mat3 *R, Vec3 *t,
-                        ResectionMethod method) {
+                        ResectionMethod method,
+                        double success_threshold) {
   switch (method) {
     case RESECTION_ANSAR_DANIILIDIS:
       EuclideanResectionAnsarDaniilidis(x_camera, X_world, R, t);
       break;
     case RESECTION_EPNP:
-      return EuclideanResectionEPnP(x_camera, X_world, R, t);      
+      return EuclideanResectionEPnP(x_camera, X_world, R, t, success_threshold);
       break;
     default:
       LOG(FATAL) << "Unknown resection method.";
@@ -351,9 +352,9 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera,
 }
 
 // Selects 4 virtual control points using mean and PCA.
-void SelectControlPoints(const Mat3X &X_world, 
-                         Mat *X_centered, 
-                         Mat34 *X_control_points) {
+static void SelectControlPoints(const Mat3X &X_world,
+                                Mat *X_centered,
+                                Mat34 *X_control_points) {
   size_t num_points = X_world.cols();
 
   // The first virtual control point, C0, is the centroid.
@@ -377,9 +378,9 @@ void SelectControlPoints(const Mat3X &X_world,
 }
 
 // Computes the barycentric coordinates for all real points
-void ComputeBarycentricCoordinates(const Mat3X &X_world_centered, 
-                                   const Mat34 &X_control_points,
-                                   Mat4X *alphas) {
+static void ComputeBarycentricCoordinates(const Mat3X &X_world_centered,
+                                          const Mat34 &X_control_points,
+                                          Mat4X *alphas) {
   size_t num_points = X_world_centered.cols();
   Mat3 C2 ;
   for (size_t c = 1; c < 4; c++) {
@@ -398,7 +399,7 @@ void ComputeBarycentricCoordinates(const Mat3X &X_world_centered,
 }
 
 // Estimates the coordinates of all real points in the camera coordinate frame
-void ComputePointsCoordinatesInCameraFrame(
+static void ComputePointsCoordinatesInCameraFrame(
     const Mat4X &alphas, 
     const Vec4 &betas,
     const Eigen::Matrix<double, 12, 12> &U,
@@ -435,8 +436,9 @@ void ComputePointsCoordinatesInCameraFrame(
 }
 
 bool EuclideanResectionEPnP(const Mat2X &x_camera,
-                            const Mat3X &X_world, 
-                            Mat3 *R, Vec3 *t) {
+                            const Mat3X &X_world,
+                            Mat3 *R, Vec3 *t,
+                            double success_threshold) {
   CHECK(x_camera.cols() == X_world.cols());
   CHECK(x_camera.cols() > 3);
   size_t num_points = X_world.cols();
@@ -535,7 +537,21 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   vector<Vec3> ts(3);
   Vec rmse(3);
 
-  // TODO(julien): Document where the "1e-3" magical constant comes from below.
+  // At one point this threshold was 1e-3, and caused no end of problems in
+  // Blender by causing frames to not resect when they would have worked fine.
+  // When the resect failed, the projective followup is run leading to worse
+  // results, and often the dreaded "flipping" where objects get flipped
+  // between frames. Instead, disable the check for now, always succeeding. The
+  // ultimate check is always reprojection error anyway.
+  //
+  // TODO(keir): Decide if setting this to infinity, effectively disabling the
+  // check, is the right approach. So far this seems the case.
+  //
+  // TODO(sergey): Made it an option for now, in some cases it makes sense to
+  // still fallback to reprojection solution (see bug [#32765] from Blender bug tracker)
+
+  // double kSuccessThreshold = std::numeric_limits<double>::max();
+  double kSuccessThreshold = success_threshold;
 
   // Find the first possible solution for R, t corresponding to:
   // Betas          = [b00 b01 b11 b02 b12 b22 b03 b13 b23 b33]
@@ -548,7 +564,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   Eigen::JacobiSVD<Mat> svd_of_l4(l_6x4, 
                                   Eigen::ComputeFullU | Eigen::ComputeFullV);
   Vec4 b4 = svd_of_l4.solve(rho);
-  if ((l_6x4 * b4).isApprox(rho, 1e-3)) {
+  if ((l_6x4 * b4).isApprox(rho, kSuccessThreshold)) {
     if (b4(0) < 0) {
       b4 = -b4;
     } 
@@ -574,7 +590,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   Vec3 b3 = svdOfL3.solve(rho);
   VLOG(2) << " rho = " << rho;
   VLOG(2) << " l_6x3 * b3 = " << l_6x3 * b3;
-  if ((l_6x3 * b3).isApprox(rho, 1e-3)) {
+  if ((l_6x3 * b3).isApprox(rho, kSuccessThreshold)) {
     if (b3(0) < 0) {
       betas(0) = std::sqrt(-b3(0));
       betas(1) = (b3(2) < 0) ? std::sqrt(-b3(2)) : 0;
@@ -605,7 +621,7 @@ bool EuclideanResectionEPnP(const Mat2X &x_camera,
   Eigen::JacobiSVD<Mat> svdOfL5(l_6x5, 
                                 Eigen::ComputeFullU | Eigen::ComputeFullV);
   Vec5 b5 = svdOfL5.solve(rho);
-  if ((l_6x5 * b5).isApprox(rho, 1e-3)) {
+  if ((l_6x5 * b5).isApprox(rho, kSuccessThreshold)) {
     if (b5(0) < 0) {
       betas(0) = std::sqrt(-b5(0));
       if (b5(2) < 0) {
diff --git a/extern/libmv/libmv/multiview/euclidean_resection.h b/extern/libmv/libmv/multiview/euclidean_resection.h
index 08fa3d90bd3..b0428ec61fd 100644
--- a/extern/libmv/libmv/multiview/euclidean_resection.h
+++ b/extern/libmv/libmv/multiview/euclidean_resection.h
@@ -29,6 +29,9 @@ namespace euclidean_resection {
   
 enum ResectionMethod {
   RESECTION_ANSAR_DANIILIDIS,
+
+  // The "EPnP" algorithm by Lepetit et al.
+  // http://cvlab.epfl.ch/~lepetit/papers/lepetit_ijcv08.pdf
   RESECTION_EPNP,
 };
 
@@ -42,11 +45,14 @@ enum ResectionMethod {
  * \param R         Solution for the camera rotation matrix
  * \param t         Solution for the camera translation vector
  * \param method    The resection method to use.
+ * \param success_threshold  Threshold of an error which is still considered a success
+ *                           (currently used by EPnP algorithm only)
  */
 bool EuclideanResection(const Mat2X &x_camera, 
                         const Mat3X &X_world,
                         Mat3 *R, Vec3 *t,
-                        ResectionMethod method = RESECTION_EPNP);
+                        ResectionMethod method = RESECTION_EPNP,
+                        double success_threshold = 1e-3);
 
 /**
  * Computes the extrinsic parameters, R and t for a calibrated camera
@@ -107,6 +113,7 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera,
  * \param X_world 3D points in the world coordinate system
  * \param R       Solution for the camera rotation matrix
  * \param t       Solution for the camera translation vector
+ * \param success_threshold  Threshold of an error which is still considered a success
  *
  * This is the algorithm described in:
  * "{EP$n$P: An Accurate $O(n)$ Solution to the P$n$P Problem", by V. Lepetit
@@ -115,7 +122,8 @@ void EuclideanResectionAnsarDaniilidis(const Mat2X &x_camera,
  */
 bool EuclideanResectionEPnP(const Mat2X &x_camera,
                             const Mat3X &X_world, 
-                            Mat3 *R, Vec3 *t);
+                            Mat3 *R, Vec3 *t,
+                            double success_threshold = 1e-3);
 
 } // namespace euclidean_resection
 } // namespace libmv
diff --git a/extern/libmv/libmv/multiview/fundamental.cc b/extern/libmv/libmv/multiview/fundamental.cc
index 7a6b4a08439..80f155e804d 100644
--- a/extern/libmv/libmv/multiview/fundamental.cc
+++ b/extern/libmv/libmv/multiview/fundamental.cc
@@ -28,7 +28,7 @@
 
 namespace libmv {
 
-void EliminateRow(const Mat34 &P, int row, Mat *X) {
+static void EliminateRow(const Mat34 &P, int row, Mat *X) {
   X->resize(2, 4);
 
   int first_row = (row + 1) % 3;
@@ -69,7 +69,7 @@ void FundamentalFromProjections(const Mat34 &P1, const Mat34 &P2, Mat3 *F) {
 
 // HZ 11.1 pag.279 (x1 = x, x2 = x')
 // http://www.cs.unc.edu/~marc/tutorial/node54.html
-double EightPointSolver(const Mat &x1, const Mat &x2, Mat3 *F) {
+static double EightPointSolver(const Mat &x1, const Mat &x2, Mat3 *F) {
   DCHECK_EQ(x1.rows(), 2);
   DCHECK_GE(x1.cols(), 8);
   DCHECK_EQ(x1.rows(), x2.rows());
diff --git a/extern/libmv/libmv/multiview/homography.cc b/extern/libmv/libmv/multiview/homography.cc
index 366392f3923..b5c483998d8 100644
--- a/extern/libmv/libmv/multiview/homography.cc
+++ b/extern/libmv/libmv/multiview/homography.cc
@@ -40,7 +40,7 @@ namespace libmv {
  * (a-x1*g)*y1     + (b-x1*h)*y2  + c-x1         = |0|
  * (-x2*a+x1*d)*y1 + (-x2*b+x1*e)*y2 + -x2*c+x1*f  |0|
  */
-bool Homography2DFromCorrespondencesLinearEuc(
+static bool Homography2DFromCorrespondencesLinearEuc(
     const Mat &x1,
     const Mat &x2,
     Mat3 *H,
diff --git a/extern/libmv/libmv/numeric/levenberg_marquardt.h b/extern/libmv/libmv/numeric/levenberg_marquardt.h
index 4473b72f156..a7877e0270b 100644
--- a/extern/libmv/libmv/numeric/levenberg_marquardt.h
+++ b/extern/libmv/libmv/numeric/levenberg_marquardt.h
@@ -124,11 +124,11 @@ class LevenbergMarquardt {
     Parameters dx, x_new;
     int i;
     for (i = 0; results.status == RUNNING && i < params.max_iterations; ++i) {
-      VLOG(1) << "iteration: " << i;
-      VLOG(1) << "||f(x)||: " << f_(x).norm();
-      VLOG(1) << "max(g): " << g.array().abs().maxCoeff();
-      VLOG(1) << "u: " << u;
-      VLOG(1) << "v: " << v;
+      VLOG(3) << "iteration: " << i;
+      VLOG(3) << "||f(x)||: " << f_(x).norm();
+      VLOG(3) << "max(g): " << g.array().abs().maxCoeff();
+      VLOG(3) << "u: " << u;
+      VLOG(3) << "v: " << v;
 
       AMatrixType A_augmented = A + u*AMatrixType::Identity(J.cols(), J.cols());
       Solver solver(A_augmented);
diff --git a/extern/libmv/libmv/simple_pipeline/detect.cc b/extern/libmv/libmv/simple_pipeline/detect.cc
index 8a093dadeca..9e3edf32d71 100644
--- a/extern/libmv/libmv/simple_pipeline/detect.cc
+++ b/extern/libmv/libmv/simple_pipeline/detect.cc
@@ -35,7 +35,7 @@ namespace libmv {
 
 typedef unsigned int uint;
 
-int featurecmp(const void *a_v, const void *b_v)
+static int featurecmp(const void *a_v, const void *b_v)
 {
   Feature *a = (Feature*)a_v;
   Feature *b = (Feature*)b_v;
diff --git a/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc b/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc
index 77fe2a530c4..9c06d1ef4e6 100644
--- a/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc
+++ b/extern/libmv/libmv/simple_pipeline/initialize_reconstruction.cc
@@ -24,6 +24,7 @@
 #include "libmv/multiview/projection.h"
 #include "libmv/numeric/levenberg_marquardt.h"
 #include "libmv/numeric/numeric.h"
+#include "libmv/simple_pipeline/initialize_reconstruction.h"
 #include "libmv/simple_pipeline/reconstruction.h"
 #include "libmv/simple_pipeline/tracks.h"
 
diff --git a/extern/libmv/libmv/simple_pipeline/intersect.cc b/extern/libmv/libmv/simple_pipeline/intersect.cc
index b1518e04651..0c2f744dc1c 100644
--- a/extern/libmv/libmv/simple_pipeline/intersect.cc
+++ b/extern/libmv/libmv/simple_pipeline/intersect.cc
@@ -26,6 +26,7 @@
 #include "libmv/multiview/projection.h"
 #include "libmv/numeric/numeric.h"
 #include "libmv/numeric/levenberg_marquardt.h"
+#include "libmv/simple_pipeline/intersect.h"
 #include "libmv/simple_pipeline/reconstruction.h"
 #include "libmv/simple_pipeline/tracks.h"
 
diff --git a/extern/libmv/libmv/simple_pipeline/pipeline.cc b/extern/libmv/libmv/simple_pipeline/pipeline.cc
index 2459d059114..efceda5c455 100644
--- a/extern/libmv/libmv/simple_pipeline/pipeline.cc
+++ b/extern/libmv/libmv/simple_pipeline/pipeline.cc
@@ -50,9 +50,10 @@ struct EuclideanPipelineRoutines {
     EuclideanBundle(tracks, reconstruction);
   }
 
-  static bool Resect(const vector<Marker> &markers,
+  static bool Resect(const ReconstructionOptions &options,
+                     const vector<Marker> &markers,
                      EuclideanReconstruction *reconstruction, bool final_pass) {
-    return EuclideanResect(markers, reconstruction, final_pass);
+    return EuclideanResect(options, markers, reconstruction, final_pass);
   }
 
   static bool Intersect(const vector<Marker> &markers,
@@ -88,7 +89,8 @@ struct ProjectivePipelineRoutines {
     ProjectiveBundle(tracks, reconstruction);
   }
 
-  static bool Resect(const vector<Marker> &markers,
+  static bool Resect(const ReconstructionOptions &options,
+                     const vector<Marker> &markers,
                      ProjectiveReconstruction *reconstruction, bool final_pass) {
     return ProjectiveResect(markers, reconstruction);
   }
@@ -136,6 +138,7 @@ static void CompleteReconstructionLogProress(ProgressUpdateCallback *update_call
 
 template<typename PipelineRoutines>
 void InternalCompleteReconstruction(
+    const ReconstructionOptions &options,
     const Tracks &tracks,
     typename PipelineRoutines::Reconstruction *reconstruction,
     ProgressUpdateCallback *update_callback = NULL) {
@@ -204,7 +207,7 @@ void InternalCompleteReconstruction(
       if (reconstructed_markers.size() >= 5) {
         CompleteReconstructionLogProress(update_callback,
                                          (double)tot_resects/(max_image));
-        if (PipelineRoutines::Resect(reconstructed_markers, reconstruction, false)) {
+        if (PipelineRoutines::Resect(options, reconstructed_markers, reconstruction, false)) {
           num_resects++;
           tot_resects++;
           LG << "Ran Resect() for image " << image;
@@ -240,11 +243,11 @@ void InternalCompleteReconstruction(
     if (reconstructed_markers.size() >= 5) {
       CompleteReconstructionLogProress(update_callback,
                                        (double)tot_resects/(max_image));
-      if (PipelineRoutines::Resect(reconstructed_markers, reconstruction, true)) {
+      if (PipelineRoutines::Resect(options, reconstructed_markers, reconstruction, true)) {
         num_resects++;
-        LG << "Ran Resect() for image " << image;
+        LG << "Ran final Resect() for image " << image;
       } else {
-        LG << "Failed Resect() for image " << image;
+        LG << "Failed final Resect() for image " << image;
       }
     }
   }
@@ -325,17 +328,21 @@ double ProjectiveReprojectionError(
                                                                intrinsics);
 }
 
-void EuclideanCompleteReconstruction(const Tracks &tracks,
+void EuclideanCompleteReconstruction(const ReconstructionOptions &options,
+                                     const Tracks &tracks,
                                      EuclideanReconstruction *reconstruction,
                                      ProgressUpdateCallback *update_callback) {
-  InternalCompleteReconstruction<EuclideanPipelineRoutines>(tracks,
+  InternalCompleteReconstruction<EuclideanPipelineRoutines>(options,
+                                                            tracks,
                                                             reconstruction,
                                                             update_callback);
 }
 
-void ProjectiveCompleteReconstruction(const Tracks &tracks,
+void ProjectiveCompleteReconstruction(const ReconstructionOptions &options,
+                                      const Tracks &tracks,
                                       ProjectiveReconstruction *reconstruction) {
-  InternalCompleteReconstruction<ProjectivePipelineRoutines>(tracks,
+  InternalCompleteReconstruction<ProjectivePipelineRoutines>(options,
+                                                             tracks,
                                                              reconstruction);
 }
 
diff --git a/extern/libmv/libmv/simple_pipeline/pipeline.h b/extern/libmv/libmv/simple_pipeline/pipeline.h
index e940b57bc0d..11c11297d78 100644
--- a/extern/libmv/libmv/simple_pipeline/pipeline.h
+++ b/extern/libmv/libmv/simple_pipeline/pipeline.h
@@ -39,6 +39,9 @@ namespace libmv {
     repeated until all points and cameras are estimated. Periodically, bundle
     adjustment is run to ensure a quality reconstruction.
 
+    \a options are used to define some specific befaviours based on settings
+    see documentation for ReconstructionOptions
+
     \a tracks should contain markers used in the reconstruction.
     \a reconstruction should contain at least some 3D points or some estimated
     cameras. The minimum number of cameras is two (with no 3D points) and the
@@ -46,7 +49,8 @@ namespace libmv {
 
     \sa EuclideanResect, EuclideanIntersect, EuclideanBundle
 */
-void EuclideanCompleteReconstruction(const Tracks &tracks,
+void EuclideanCompleteReconstruction(const ReconstructionOptions &options,
+                                     const Tracks &tracks,
                                      EuclideanReconstruction *reconstruction,
                                      ProgressUpdateCallback *update_callback = NULL);
 
@@ -63,6 +67,9 @@ void EuclideanCompleteReconstruction(const Tracks &tracks,
     repeated until all points and cameras are estimated. Periodically, bundle
     adjustment is run to ensure a quality reconstruction.
 
+    \a options are used to define some specific befaviours based on settings
+    see documentation for ReconstructionOptions
+
     \a tracks should contain markers used in the reconstruction.
     \a reconstruction should contain at least some 3D points or some estimated
     cameras. The minimum number of cameras is two (with no 3D points) and the
@@ -70,7 +77,8 @@ void EuclideanCompleteReconstruction(const Tracks &tracks,
 
     \sa ProjectiveResect, ProjectiveIntersect, ProjectiveBundle
 */
-void ProjectiveCompleteReconstruction(const Tracks &tracks,
+void ProjectiveCompleteReconstruction(const ReconstructionOptions &options,
+                                      const Tracks &tracks,
                                       ProjectiveReconstruction *reconstruction);
 
 
diff --git a/extern/libmv/libmv/simple_pipeline/reconstruction.h b/extern/libmv/libmv/simple_pipeline/reconstruction.h
index 947a0636476..71789e3a245 100644
--- a/extern/libmv/libmv/simple_pipeline/reconstruction.h
+++ b/extern/libmv/libmv/simple_pipeline/reconstruction.h
@@ -26,6 +26,17 @@
 
 namespace libmv {
 
+struct ReconstructionOptions {
+	// threshold value of reconstruction error which is still considered successful
+	// if reconstruction error bigger than this value, fallback reconstruction
+	// algorithm would be used (if enabled)
+	double success_threshold;
+
+	// use fallback reconstruction algorithm in cases main reconstruction algorithm
+	// failed to reconstruct
+	bool use_fallback_reconstruction;
+};
+
 /*!
     A EuclideanCamera is the location and rotation of the camera viewing \a image.
 
diff --git a/extern/libmv/libmv/simple_pipeline/resect.cc b/extern/libmv/libmv/simple_pipeline/resect.cc
index b30d959b512..4c9ca6d8677 100644
--- a/extern/libmv/libmv/simple_pipeline/resect.cc
+++ b/extern/libmv/libmv/simple_pipeline/resect.cc
@@ -27,6 +27,7 @@
 #include "libmv/multiview/projection.h"
 #include "libmv/numeric/numeric.h"
 #include "libmv/numeric/levenberg_marquardt.h"
+#include "libmv/simple_pipeline/resect.h"
 #include "libmv/simple_pipeline/reconstruction.h"
 #include "libmv/simple_pipeline/tracks.h"
 
@@ -89,7 +90,8 @@ struct EuclideanResectCostFunction {
 
 }  // namespace
 
-bool EuclideanResect(const vector<Marker> &markers,
+bool EuclideanResect(const ReconstructionOptions &options,
+                     const vector<Marker> &markers,
                      EuclideanReconstruction *reconstruction, bool final_pass) {
   if (markers.size() < 5) {
     return false;
@@ -103,10 +105,25 @@ bool EuclideanResect(const vector<Marker> &markers,
 
   Mat3 R;
   Vec3 t;
-  if (0 || !euclidean_resection::EuclideanResection(points_2d, points_3d, &R, &t)) {
+
+  double success_threshold = std::numeric_limits<double>::max();
+
+  if(options.use_fallback_reconstruction)
+    success_threshold = options.success_threshold;
+
+  if (0 || !euclidean_resection::EuclideanResection(points_2d, points_3d, &R, &t,
+                                                    euclidean_resection::RESECTION_EPNP,
+                                                    success_threshold))
+  {
     // printf("Resection for image %d failed\n", markers[0].image);
     LG << "Resection for image " << markers[0].image << " failed;"
        << " trying fallback projective resection.";
+
+    if (!options.use_fallback_reconstruction) {
+        LG << "No fallback; failing resection for " << markers[0].image;
+        return false;
+    }
+
     if (!final_pass) return false;
     // Euclidean resection failed. Fall back to projective resection, which is
     // less reliable but better conditioned when there are many points.
diff --git a/extern/libmv/libmv/simple_pipeline/resect.h b/extern/libmv/libmv/simple_pipeline/resect.h
index f8b5b9f68ee..1691e7ee245 100644
--- a/extern/libmv/libmv/simple_pipeline/resect.h
+++ b/extern/libmv/libmv/simple_pipeline/resect.h
@@ -35,6 +35,9 @@ namespace libmv {
     reconstruction object, and solves for the pose and orientation of the
     camera for that frame.
 
+    \a options are used to define some specific befaviours based on settings
+    see documentation for ReconstructionOptions
+
     \a markers should contain \l Marker markers \endlink belonging to tracks
     visible in the one frame to be resectioned. Each of the tracks associated
     with the markers must have a corresponding reconstructed 3D position in the
@@ -51,7 +54,8 @@ namespace libmv {
 
     \sa EuclideanIntersect, EuclideanReconstructTwoFrames
 */
-bool EuclideanResect(const vector<Marker> &markers,
+bool EuclideanResect(const ReconstructionOptions &options,
+                     const vector<Marker> &markers,
                      EuclideanReconstruction *reconstruction, bool final_pass);
 
 /*!
diff --git a/extern/libmv/libmv/tracking/track_region.cc b/extern/libmv/libmv/tracking/track_region.cc
index f52919b2a61..472d58a1547 100644
--- a/extern/libmv/libmv/tracking/track_region.cc
+++ b/extern/libmv/libmv/tracking/track_region.cc
@@ -18,7 +18,7 @@
 // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
 // IN THE SOFTWARE.
 //
-// Author: mierle@google.com (Keir Mierle)
+// Author: mierle@gmail.com (Keir Mierle)
 //
 // TODO(keir): While this tracking code works rather well, it has some
 // outragous inefficiencies. There is probably a 5-10x speedup to be had if a
@@ -41,6 +41,85 @@
 #include "libmv/multiview/homography.h"
 #include "libmv/numeric/numeric.h"
 
+// Expand the Jet functionality of Ceres to allow mixed numeric/autodiff.
+//
+// TODO(keir): Push this (or something similar) into upstream Ceres.
+namespace ceres {
+
+// A jet traits class to make it easier to work with mixed auto / numeric diff.
+template<typename T>
+struct JetOps {
+  static bool IsScalar() {
+    return true;
+  }
+  static T GetScalar(const T& t) {
+    return t;
+  }
+  static void SetScalar(const T& scalar, T* t) {
+    *t = scalar;
+  }
+  static void ScaleDerivative(double scale_by, T *value) {
+    // For double, there is no derivative to scale.
+  }
+};
+
+template<typename T, int N>
+struct JetOps<Jet<T, N> > {
+  static bool IsScalar() {
+    return false;
+  }
+  static T GetScalar(const Jet<T, N>& t) {
+    return t.a;
+  }
+  static void SetScalar(const T& scalar, Jet<T, N>* t) {
+    t->a = scalar;
+  }
+  static void ScaleDerivative(double scale_by, Jet<T, N> *value) {
+    value->v *= scale_by;
+  }
+};
+
+template<typename FunctionType, int kNumArgs, typename ArgumentType>
+struct Chain {
+  static ArgumentType Rule(const FunctionType &f,
+                           const FunctionType dfdx[kNumArgs],
+                           const ArgumentType x[kNumArgs]) {
+    // In the default case of scalars, there's nothing to do since there are no
+    // derivatives to propagate. 
+    return f;
+  }
+};
+
+// XXX Add documentation here!
+template<typename FunctionType, int kNumArgs, typename T, int N>
+struct Chain<FunctionType, kNumArgs, Jet<T, N> > {
+  static Jet<T, N> Rule(const FunctionType &f,
+                        const FunctionType dfdx[kNumArgs],
+                        const Jet<T, N> x[kNumArgs]) {
+    // x is itself a function of another variable ("z"); what this function
+    // needs to return is "f", but with the derivative with respect to z
+    // attached to the jet. So combine the derivative part of x's jets to form
+    // a Jacobian matrix between x and z (i.e. dx/dz).
+    Eigen::Matrix<T, kNumArgs, N> dxdz;
+    for (int i = 0; i < kNumArgs; ++i) {
+      dxdz.row(i) = x[i].v.transpose();
+    }
+
+    // Map the input gradient dfdx into an Eigen row vector.
+    Eigen::Map<const Eigen::Matrix<FunctionType, 1, kNumArgs> >
+        vector_dfdx(dfdx, 1, kNumArgs);
+
+    // Now apply the chain rule to obtain df/dz. Combine the derivative with
+    // the scalar part to obtain f with full derivative information.
+    Jet<T, N> jet_f;
+    jet_f.a = f;
+    jet_f.v = vector_dfdx.template cast<T>() * dxdz;  // Also known as dfdz.
+    return jet_f;
+  }
+};
+
+}  // namespace ceres
+
 namespace libmv {
 
 using ceres::Jet;
@@ -57,6 +136,7 @@ TrackRegionOptions::TrackRegionOptions()
       sigma(0.9),
       num_extra_points(0),
       regularization_coefficient(0.0),
+      minimum_corner_shift_tolerance_pixels(0.005),
       image1_mask(NULL) {
 }
 
@@ -108,45 +188,93 @@ static T SampleWithDerivative(const FloatImage &image_and_gradient,
 }
 
 template<typename Warp>
-class BoundaryCheckingCallback : public ceres::IterationCallback {
+class TerminationCheckingCallback : public ceres::IterationCallback {
  public:
-  BoundaryCheckingCallback(const FloatImage& image2,
-                           const Warp &warp,
-                           const double *x1, const double *y1)
-      : image2_(image2), warp_(warp), x1_(x1), y1_(y1) {}
+  TerminationCheckingCallback(const TrackRegionOptions &options,
+                              const FloatImage& image2,
+                              const Warp &warp,
+                              const double *x1, const double *y1)
+      : options_(options), image2_(image2), warp_(warp), x1_(x1), y1_(y1),
+        have_last_successful_step_(false) {}
 
   virtual ceres::CallbackReturnType operator()(
       const ceres::IterationSummary& summary) {
+    // If the step wasn't successful, there's nothing to do.
+    if (!summary.step_is_successful) {
+      return ceres::SOLVER_CONTINUE;
+    }
     // Warp the original 4 points with the current warp into image2.
     double x2[4];
     double y2[4];
     for (int i = 0; i < 4; ++i) {
       warp_.Forward(warp_.parameters, x1_[i], y1_[i], x2 + i, y2 + i);
     }
-    // Enusre they are all in bounds.
+    // Ensure the corners are all in bounds.
     if (!AllInBounds(image2_, x2, y2)) {
+      LG << "Successful step fell outside of the pattern bounds; aborting.";
       return ceres::SOLVER_ABORT;
     }
+
+    // Ensure the minimizer is making large enough shifts to bother continuing.
+    // Ideally, this check would happen on the parameters themselves which
+    // Ceres supports directly; however, the mapping from parameter change
+    // magnitude to corner movement in pixels is not a simple norm. Hence, the
+    // need for a stateful callback which tracks the last successful set of
+    // parameters (and the position of the projected patch corners).
+    if (have_last_successful_step_) {
+      // Compute the maximum shift of any corner in pixels since the last
+      // successful iteration.
+      double max_change_pixels = 0;
+      for (int i = 0; i < 4; ++i) {
+        double dx = x2[i] - x2_last_successful_[i];
+        double dy = y2[i] - y2_last_successful_[i];
+        double change_pixels = dx*dx + dy*dy;
+        if (change_pixels > max_change_pixels) {
+          max_change_pixels = change_pixels;
+        }
+      }
+      max_change_pixels = sqrt(max_change_pixels);
+      LG << "Max patch corner shift is " << max_change_pixels;
+
+      // Bail if the shift is too small.
+      if (max_change_pixels < options_.minimum_corner_shift_tolerance_pixels) {
+        LG << "Max patch corner shift is " << max_change_pixels
+           << " from the last iteration; returning success.";
+        return ceres::SOLVER_TERMINATE_SUCCESSFULLY;
+      }
+    }
+
+    // Save the projected corners for checking on the next successful iteration.
+    for (int i = 0; i < 4; ++i) {
+      x2_last_successful_[i] = x2[i];
+      y2_last_successful_[i] = y2[i];
+    }
+    have_last_successful_step_ = true;
     return ceres::SOLVER_CONTINUE;
   }
 
  private:
+  const TrackRegionOptions &options_;
   const FloatImage &image2_;
   const Warp &warp_;
   const double *x1_;
   const double *y1_;
+
+  bool have_last_successful_step_;
+  double x2_last_successful_[4];
+  double y2_last_successful_[4];
 };
 
 template<typename Warp>
 class PixelDifferenceCostFunctor {
  public:
   PixelDifferenceCostFunctor(const TrackRegionOptions &options,
-                  const FloatImage &image_and_gradient1,
-                  const FloatImage &image_and_gradient2,
-                  const Mat3 &canonical_to_image1,
-                  int num_samples_x,
-                  int num_samples_y,
-                  const Warp &warp)
+                             const FloatImage &image_and_gradient1,
+                             const FloatImage &image_and_gradient2,
+                             const Mat3 &canonical_to_image1,
+                             int num_samples_x,
+                             int num_samples_y,
+                             const Warp &warp)
       : options_(options),
         image_and_gradient1_(image_and_gradient1),       
         image_and_gradient2_(image_and_gradient2),       
@@ -1044,6 +1172,9 @@ void CreateBrutePattern(const double *x1, const double *y1,
 // correlation. Instead, this is a dumb implementation. Surprisingly, it is
 // fast enough in practice.
 //
+// Returns true if any alignment was found, and false if the projected pattern
+// is zero sized.
+//
 // TODO(keir): The normalization is less effective for the brute force search
 // than it is with the Ceres solver. It's unclear if this is a bug or due to
 // the original frame being too different from the reprojected reference in the
@@ -1054,7 +1185,7 @@ void CreateBrutePattern(const double *x1, const double *y1,
 // totally different warping interface, since access to more than a the source
 // and current destination frame is necessary.
 template<typename Warp>
-void BruteTranslationOnlyInitialize(const FloatImage &image1,
+bool BruteTranslationOnlyInitialize(const FloatImage &image1,
                                     const FloatImage *image1_mask,
                                     const FloatImage &image2,
                                     const int num_extra_points,
@@ -1100,6 +1231,7 @@ void BruteTranslationOnlyInitialize(const FloatImage &image1,
   int best_c = -1;
   int w = pattern.cols();
   int h = pattern.rows();
+
   for (int r = 0; r < (image2.Height() - h); ++r) {
     for (int c = 0; c < (image2.Width() - w); ++c) {
       // Compute the weighted sum of absolute differences, Eigen style. Note
@@ -1124,8 +1256,12 @@ void BruteTranslationOnlyInitialize(const FloatImage &image1,
       }
     }
   }
-  CHECK_NE(best_r, -1);
-  CHECK_NE(best_c, -1);
+
+  // This mean the effective pattern area is zero. This check could go earlier,
+  // but this is less code.
+  if (best_r == -1 || best_c == -1) {
+    return false;
+  }
 
   LG << "Brute force translation found a shift. "
      << "best_c: " << best_c << ", best_r: " << best_r << ", "
@@ -1140,6 +1276,7 @@ void BruteTranslationOnlyInitialize(const FloatImage &image1,
     x2[i] += best_c - origin_x;
     y2[i] += best_r - origin_y;
   }
+  return true;
 }
 
 }  // namespace
@@ -1191,12 +1328,19 @@ void TemplatedTrackRegion(const FloatImage &image1,
   if (SearchAreaTooBigForDescent(image2, x2, y2) &&
       options.use_brute_initialization) {
     LG << "Running brute initialization...";
-    BruteTranslationOnlyInitialize<Warp>(image_and_gradient1,
-                                         options.image1_mask,
-                                         image2,
-                                         options.num_extra_points,
-                                         options.use_normalized_intensities,
-                                         x1, y1, x2, y2);
+    bool found_any_alignment = BruteTranslationOnlyInitialize<Warp>(
+        image_and_gradient1,
+        options.image1_mask,
+        image2,
+        options.num_extra_points,
+        options.use_normalized_intensities,
+        x1, y1, x2, y2);
+    if (!found_any_alignment) {
+      LG << "Brute failed to find an alignment; pattern too small. "
+         << "Failing entire track operation.";
+      result->termination = TrackRegionResult::INSUFFICIENT_PATTERN_AREA;
+      return;
+    }
     for (int i = 0; i < 4; ++i) {
       LG << "P" << i << ": (" << x1[i] << ", " << y1[i] << "); brute ("
          << x2[i] << ", " << y2[i] << "); (dx, dy): (" << (x2[i] - x1[i])
@@ -1260,14 +1404,15 @@ void TemplatedTrackRegion(const FloatImage &image1,
 
   // Configure the solve.
   ceres::Solver::Options solver_options;
-  solver_options.linear_solver_type = ceres::DENSE_QR;
+  solver_options.linear_solver_type = ceres::DENSE_NORMAL_CHOLESKY;
   solver_options.max_num_iterations = options.max_iterations;
   solver_options.update_state_every_iteration = true;
   solver_options.parameter_tolerance = 1e-16;
   solver_options.function_tolerance = 1e-16;
 
-  // Prevent the corners from going outside the destination image.
-  BoundaryCheckingCallback<Warp> callback(image2, warp, x1, y1);
+  // Prevent the corners from going outside the destination image and
+  // terminate if the optimizer is making tiny moves (converged).
+  TerminationCheckingCallback<Warp> callback(options, image2, warp, x1, y1);
   solver_options.callbacks.push_back(&callback);
 
   // Run the solve.
@@ -1290,11 +1435,21 @@ void TemplatedTrackRegion(const FloatImage &image1,
   // TODO(keir): Update the result statistics.
   // TODO(keir): Add a normalize-cross-correlation variant.
 
-  CHECK_NE(summary.termination_type, ceres::USER_ABORT) << "Libmv bug.";
   if (summary.termination_type == ceres::USER_ABORT) {
     result->termination = TrackRegionResult::FELL_OUT_OF_BOUNDS;
     return;
   }
+
+  // This happens when the minimum corner shift tolerance is reached. Due to
+  // how the tolerance is computed this can't be done by Ceres. So return the
+  // same termination enum as Ceres, even though this is slightly different
+  // than Ceres's parameter tolerance, which operates on the raw parameter
+  // values rather than the pixel shifts of the patch corners.
+  if (summary.termination_type == ceres::USER_SUCCESS) {
+    result->termination = TrackRegionResult::PARAMETER_TOLERANCE;
+    return;
+  }
+
 #define HANDLE_TERMINATION(termination_enum) \
   if (summary.termination_type == ceres::termination_enum) { \
     result->termination = TrackRegionResult::termination_enum; \
@@ -1377,11 +1532,11 @@ bool SamplePlanarPatch(const FloatImage &image,
                    image_position(0),
                    &(*patch)(r, c, 0));
       if (mask) {
-        float maskValue = SampleLinear(*mask, image_position(1),
-                                       image_position(0), 0);
+        float mask_value = SampleLinear(*mask, image_position(1),
+                                        image_position(0), 0);
 
         for (int d = 0; d < image.Depth(); d++)
-          (*patch)(r, c, d) *= maskValue;
+          (*patch)(r, c, d) *= mask_value;
       }
     }
   }
diff --git a/extern/libmv/libmv/tracking/track_region.h b/extern/libmv/libmv/tracking/track_region.h
index 22ecfc54a15..cd7ee0aa2ba 100644
--- a/extern/libmv/libmv/tracking/track_region.h
+++ b/extern/libmv/libmv/tracking/track_region.h
@@ -90,6 +90,11 @@ struct TrackRegionOptions {
   // If zero, no regularization is used.
   double regularization_coefficient;
 
+  // If the maximum shift of any patch corner between successful iterations of
+  // the solver is less than this amount, then the tracking is declared
+  // successful. The solver termination becomes PARAMETER_TOLERANCE.
+  double minimum_corner_shift_tolerance_pixels;
+
   // If non-null, this is used as the pattern mask. It should match the size of
   // image1, even though only values inside the image1 quad are examined. The
   // values must be in the range 0.0 to 0.1.
@@ -111,6 +116,7 @@ struct TrackRegionResult {
     DESTINATION_OUT_OF_BOUNDS,
     FELL_OUT_OF_BOUNDS,
     INSUFFICIENT_CORRELATION,
+    INSUFFICIENT_PATTERN_AREA,
     CONFIGURATION_ERROR,
   };
   Termination termination;
diff --git a/extern/libmv/third_party/ceres/CMakeLists.txt b/extern/libmv/third_party/ceres/CMakeLists.txt
index e6a9e430c47..e2f06d74646 100644
--- a/extern/libmv/third_party/ceres/CMakeLists.txt
+++ b/extern/libmv/third_party/ceres/CMakeLists.txt
@@ -28,16 +28,17 @@
 
 set(INC
 	.
-	../../../Eigen3
 	include
 	internal
 	../gflags
 )
 
 set(INC_SYS
+	../../../Eigen3
 )
 
 set(SRC
+	internal/ceres/array_utils.cc
 	internal/ceres/block_evaluate_preparer.cc
 	internal/ceres/block_jacobian_writer.cc
 	internal/ceres/block_jacobi_preconditioner.cc
@@ -53,16 +54,19 @@ set(SRC
 	internal/ceres/conditioned_cost_function.cc
 	internal/ceres/conjugate_gradients_solver.cc
 	internal/ceres/corrector.cc
+	internal/ceres/cxsparse.cc
+	internal/ceres/dense_normal_cholesky_solver.cc
 	internal/ceres/dense_qr_solver.cc
 	internal/ceres/dense_sparse_matrix.cc
 	internal/ceres/detect_structure.cc
+	internal/ceres/dogleg_strategy.cc
 	internal/ceres/evaluator.cc
 	internal/ceres/file.cc
 	internal/ceres/generated/schur_eliminator_d_d_d.cc
 	internal/ceres/gradient_checking_cost_function.cc
 	internal/ceres/implicit_schur_complement.cc
 	internal/ceres/iterative_schur_complement_solver.cc
-	internal/ceres/levenberg_marquardt.cc
+	internal/ceres/levenberg_marquardt_strategy.cc
 	internal/ceres/linear_least_squares_problems.cc
 	internal/ceres/linear_operator.cc
 	internal/ceres/linear_solver.cc
@@ -70,6 +74,7 @@ set(SRC
 	internal/ceres/loss_function.cc
 	internal/ceres/normal_prior.cc
 	internal/ceres/partitioned_matrix_view.cc
+	internal/ceres/polynomial_solver.cc
 	internal/ceres/problem.cc
 	internal/ceres/problem_impl.cc
 	internal/ceres/program.cc
@@ -88,6 +93,8 @@ set(SRC
 	internal/ceres/stringprintf.cc
 	internal/ceres/suitesparse.cc
 	internal/ceres/triplet_sparse_matrix.cc
+	internal/ceres/trust_region_minimizer.cc
+	internal/ceres/trust_region_strategy.cc
 	internal/ceres/types.cc
 	internal/ceres/visibility_based_preconditioner.cc
 	internal/ceres/visibility.cc
@@ -96,6 +103,8 @@ set(SRC
 	include/ceres/ceres.h
 	include/ceres/conditioned_cost_function.h
 	include/ceres/cost_function.h
+	include/ceres/crs_matrix.h
+	include/ceres/fpclassify.h
 	include/ceres/internal/autodiff.h
 	include/ceres/internal/eigen.h
 	include/ceres/internal/fixed_array.h
@@ -114,6 +123,7 @@ set(SRC
 	include/ceres/sized_cost_function.h
 	include/ceres/solver.h
 	include/ceres/types.h
+	internal/ceres/array_utils.h
 	internal/ceres/block_evaluate_preparer.h
 	internal/ceres/block_jacobian_writer.h
 	internal/ceres/block_jacobi_preconditioner.h
@@ -131,10 +141,13 @@ set(SRC
 	internal/ceres/compressed_row_sparse_matrix.h
 	internal/ceres/conjugate_gradients_solver.h
 	internal/ceres/corrector.h
+	internal/ceres/cxsparse.h
 	internal/ceres/dense_jacobian_writer.h
+	internal/ceres/dense_normal_cholesky_solver.h
 	internal/ceres/dense_qr_solver.h
 	internal/ceres/dense_sparse_matrix.h
 	internal/ceres/detect_structure.h
+	internal/ceres/dogleg_strategy.h
 	internal/ceres/evaluator.h
 	internal/ceres/file.h
 	internal/ceres/gradient_checking_cost_function.h
@@ -143,7 +156,7 @@ set(SRC
 	internal/ceres/implicit_schur_complement.h
 	internal/ceres/integral_types.h
 	internal/ceres/iterative_schur_complement_solver.h
-	internal/ceres/levenberg_marquardt.h
+	internal/ceres/levenberg_marquardt_strategy.h
 	internal/ceres/linear_least_squares_problems.h
 	internal/ceres/linear_operator.h
 	internal/ceres/linear_solver.h
@@ -153,6 +166,7 @@ set(SRC
 	internal/ceres/mutex.h
 	internal/ceres/parameter_block.h
 	internal/ceres/partitioned_matrix_view.h
+	internal/ceres/polynomial_solver.h
 	internal/ceres/problem_impl.h
 	internal/ceres/program_evaluator.h
 	internal/ceres/program.h
@@ -168,10 +182,13 @@ set(SRC
 	internal/ceres/solver_impl.h
 	internal/ceres/sparse_matrix.h
 	internal/ceres/sparse_normal_cholesky_solver.h
+	internal/ceres/split.h
 	internal/ceres/stl_util.h
 	internal/ceres/stringprintf.h
 	internal/ceres/suitesparse.h
 	internal/ceres/triplet_sparse_matrix.h
+	internal/ceres/trust_region_minimizer.h
+	internal/ceres/trust_region_strategy.h
 	internal/ceres/visibility_based_preconditioner.h
 	internal/ceres/visibility.h
 )
@@ -203,7 +220,7 @@ if(WIN32)
 
 	if(NOT MINGW)
 		list(APPEND INC
-			third_party/msinttypes
+			../msinttypes
 		)
 	endif()
 else()
@@ -214,11 +231,30 @@ endif()
 
 add_definitions(
 	-DCERES_HAVE_PTHREAD
-	-D"CERES_HASH_NAMESPACE_START=namespace std { namespace tr1 {"
-	-D"CERES_HASH_NAMESPACE_END=}}"
 	-DCERES_NO_SUITESPARSE
-	-DCERES_DONT_HAVE_PROTOCOL_BUFFERS
+	-DCERES_NO_CXSPARSE
+	-DCERES_NO_PROTOCOL_BUFFERS
 	-DCERES_RESTRICT_SCHUR_SPECIALIZATION
 )
 
+if(MSVC10)
+	add_definitions(
+		-D"CERES_HASH_NAMESPACE_START=namespace std {"
+		-D"CERES_HASH_NAMESPACE_END=}"
+	)
+else()
+	add_definitions(
+		-D"CERES_HASH_NAMESPACE_START=namespace std { namespace tr1 {"
+		-D"CERES_HASH_NAMESPACE_END=}}"
+	)
+endif()
+
+if(APPLE)
+	if(CMAKE_OSX_DEPLOYMENT_TARGET STREQUAL "10.5")
+		add_definitions(
+			-DCERES_NO_TR1
+		)
+	endif()
+endif()
+
 blender_add_lib(extern_ceres "${SRC}" "${INC}" "${INC_SYS}")
diff --git a/extern/libmv/third_party/ceres/ChangeLog b/extern/libmv/third_party/ceres/ChangeLog
index 6e919658f13..8b84328cf98 100644
--- a/extern/libmv/third_party/ceres/ChangeLog
+++ b/extern/libmv/third_party/ceres/ChangeLog
@@ -1,324 +1,524 @@
-commit ca72152362ae1f4b9928c012e74b4d49d094a4ca
-Merge: d297f8d 0a04199
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Wed May 9 13:10:59 2012 -0700
+commit 552f9f85bba89f00ca307bc18fbda1dff23bd0e4
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Fri Aug 31 07:27:22 2012 -0700
 
-    Merge branch 'master' into windows
+    Various minor bug fixes to the solver logic.
+    
+    1. CostFunction returning false is handled better.
+    If only the cost is being evaluated, it is possible to
+    use the false value as an infinite value signal/outside
+    a region of validity. This allows a weak form of constraint
+    handling. Useful for example in handling infinities.
+    
+    2. Changed the way how the slop around zero when model_cost
+    is larger than the current cost. Relative instead of absolute
+    tolerances are used. The same logic is propagated how the
+    corresponding clamping of the model_cost is done.
+    
+    3. Fixed a minor indexing bug in nist.cc.
+    
+    4. Some minor logging fixes to nist.cc to make it more
+    compatible with the rest of ceres.
+    
+    Together these changes, take the successful solve count from
+    41/54 to 46/54 and eliminate all NUMERICAL_FAILURE problems.
+    
+    Change-Id: If94170ea4731af5b243805c0200963dd31aa94a7
 
-commit 0a04199ef279cc9ea97f665fed8e7fae717813c3
-Merge: fdeb577 f2571f1
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Wed May 9 12:54:56 2012 -0700
+commit 0b776b5cc9634d3b88d623905b96006f7647ce3e
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Thu Aug 30 15:26:17 2012 -0700
 
-    Merge branch 'master' of https://code.google.com/p/ceres-solver
+    Update docs.
+    
+    Change-Id: I69d50bcd37aed3bea2190ca614f023e83172901b
 
-commit fdeb5772cc5eeebca4d776d220d80cc91b6d0f74
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Wed May 9 07:38:07 2012 -0700
+commit 2d7176ad7c8fb7238ca8abd6de73415d95877494
+Author: Petter Strandmark <petter.strandmark@gmail.com>
+Date:   Thu Aug 30 19:51:24 2012 -0700
 
-    Support varying numbers of residuals in autodiff.
+    max_consecutive_nonmonotonic_steps should be int
     
-    This commit modifies the only function in autodiff that takes a
-    templated number of outputs (i.e. residuals) and makes that
-    template parameter a normal parameter. With that change, it
-    is a trivial matter to support a dynamic number of residuals.
+    Found via Visual Studio warning.
     
-    The API for dynamic residuals is to pass a fake number of
-    residuals as the second template argument to
-    AutoDiffCostFunction, and to pass the real number of
-    parameters as a second constructor argument.
+    Change-Id: Id2cd7de562dfc8cd35df5d5f5220dd2d7350eb2c
 
-commit da3e0563cc12e08e7b3e0fbf11d9cc8cfe9658aa
+commit 1a89bcc94e88933f89b20427a45bc40cdd23c056
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Wed May 9 11:57:47 2012 -0700
+Date:   Thu Aug 30 15:26:17 2012 -0700
 
-    Typo corrections in the documentation from Bing
+    Better reporting on the NIST problems.
+    
+    Change-Id: I7cf774ec3242c0612dbe52fc233c3fc6cff3f031
 
-commit aa9526d8e8fb34c23d63e3af5bf9239b0c4ea603
+commit ea11704857a1e4a735e096896e4d775d83981499
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Tue May 8 21:22:09 2012 -0700
+Date:   Wed Aug 29 18:18:48 2012 -0700
 
-    Share search paths across various library searches.
-    Fix typos in glog search.
-    Split the error messages for include and lib.
-    Enable building of tests by default.
-    Made building on homebrew installations a bit better.
-    Remove temporary variables for glog and gflags.
+    Basic harness for testing NIST problems.
+    
+    Change-Id: I5baaa24dbf0506ceedf4a9be4ed17c84974d71a1
 
-commit f2571f186850ed3dd316236ac4be488979df7d30
+commit 98bf14d2b95386c2c4a6c29154637943dae4c36c
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Wed May 9 11:57:47 2012 -0700
+Date:   Thu Aug 30 10:26:44 2012 -0700
 
-    Typo corrections in the documentation from Bing
+    Miscellaneous fixes.
+    
+    Change-Id: I521e11f2d20bf24960bbc6b5dab4ec8bb1503d23
 
-commit 8f7f11ff7d07737435428a2620c52419cf99f98e
-Merge: e6c17c4 eaccbb3
-Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Wed May 9 11:34:15 2012 -0700
+commit 1e3cbd9a4442cdd8fda43a7fb452f19dac8c74af
+Author: Petter Strandmark <strandmark@google.com>
+Date:   Wed Aug 29 09:39:56 2012 -0700
 
-    Merge branch 'master' of https://code.google.com/p/ceres-solver
+    Caching the symbolic Cholesky factorization when using CXSparse
+    
+    Average factorization times for bundle adjustment test problem:
+    SuiteSparse: 0.2794 s.
+    CXSparse: 0.4039 s.
+    CXSparse cached: 0.2399 s.
+    
+    CXSparse will still be slower, though, because it has to compute
+    the transpose and J^T * J.
+    
+    Change-Id: If9cdaa3dd520bee84b56e5fd4953b56a93db6bde
 
-commit e6c17c4c9d9307218f6f739cea39bc2d87733d4d
+commit 8b64140878ccd1e183d3715c38942a81fdecefde
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Tue May 8 21:22:09 2012 -0700
+Date:   Wed Aug 29 05:41:22 2012 -0700
 
-    Share search paths across various library searches.
-    Fix typos in glog search.
-    Split the error messages for include and lib.
-    Enable building of tests by default.
-    Made building on homebrew installations a bit better.
-    Remove temporary variables for glog and gflags.
+    Documentation update
+    
+    Change-Id: I271a0422e7f6f42bcfd1dc6b5dc10c7a18f6a179
 
-commit eaccbb345614c0d24c5e21fa931f470cfda874df
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Wed May 9 05:31:29 2012 -0700
+commit a5353acd85a9fd19370b3d74035d87b0f0bac230
+Author: Petter Strandmark <petter.strandmark@gmail.com>
+Date:   Tue Aug 28 18:16:41 2012 -0700
 
-    Remove unused template parameter from VariadicEvaluate.
+    Adding gflags include to test_util.cc
+    
+    test_util seems to need gflags.
+    
+    Change-Id: I0c4757960f8ac69ad599c138aea58e3c88a4ea28
 
-commit 82f4b88c34b0b2cf85064e5fc20e374e978b2e3b
-Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Sun May 6 21:05:28 2012 -0700
+commit 87ca1b2ba28ec512752bbcf5fc994ce1434eb765
+Author: Petter Strandmark <petter.strandmark@gmail.com>
+Date:   Tue Aug 28 18:05:20 2012 -0700
 
-    Extend support writing linear least squares problems to disk.
+    Changing random.h to use cstdlib for Windows compability.
     
-    1. Make the mechanism for writing problems to disk, generic and
-    controllable using an enum DumpType visible in the API.
+    As discussed with Sameer today.
     
-    2. Instead of single file containing protocol buffers, now matrices can
-    be written in a matlab/octave friendly format. This is now the default.
+    Change-Id: If3d0284830c6591c71cc77b8400cafb45c0da61f
+
+commit aeb00a07323808a0a1816e733ad18a87d5109ea3
+Author: Petter Strandmark <strandmark@google.com>
+Date:   Mon Aug 27 22:22:57 2012 -0700
+
+    Removing gomp for Visual Studio
     
-    3. The support for writing problems to disk is moved into
-    linear_least_squares_problem.cc/h
+    Linking currently fails in Visual Studio due to a missing library
+    "gomp.lib". This is not needed in Visual Studio. OpenMP works
+    without it.
+    
+    Change-Id: I39e204a8dd4f1b7425df7d4b222d86a8bb961432
+
+commit 6f362464ba99b800494d2f15c27768a342ddaa68
+Author: Markus Moll <markus.moll@esat.kuleuven.be>
+Date:   Tue Aug 28 01:03:38 2012 +0200
+
+    Add some tests for DoglegStrategy.
     
-    4. SparseMatrix now has a ToTextFile virtual method which is
-    implemented by each of its subclasses to write a (i,j,s) triplets.
+    Not necessarily a complete set.
     
-    5. Minor changes to simple_bundle_adjuster to enable logging at startup.
+    Change-Id: I14eb3a38c6fe976c8212f3934655411b6d1e0aa4
 
-commit d297f8d3d3f5025c24752f0f4c1ec2469a769f99
-Merge: 7e74d81 f8bd7fa
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Tue May 8 05:39:56 2012 -0700
+commit 122cf836a6dc9726489ce2fbecc6143bddc1caaf
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Fri Aug 24 16:28:27 2012 -0700
 
-    Merge branch 'master' into windows
+    Documentation update.
+    
+    Change-Id: I0a3c5ae4bc981a8f5bdd5a8905f923dc5f09a024
 
-commit f8bd7fa9aa9dbf64b6165606630287cf8cf21194
+commit 69081719f73da8de2935774a42d237837a91952a
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Tue May 8 05:39:32 2012 -0700
+Date:   Mon Aug 27 13:28:56 2012 -0700
 
-    Small tweaks to the block jacobi preconditioner.
+    Remove unnecessary overload for hash<>
+    
+    The overload for pointers in hash tables was applied in normal
+    usage of schur_ordering.cc. However, the tests did not include the
+    overload since they only included collections_port.h. As a result,
+    the routines in schur_ordering.cc were using a different hash
+    function than that inside the tests.
+    
+    The fix is to remove the specialization. If this breaks one of the
+    compiler configurations, we will find a workaround at that time.
+    
+    Change-Id: Idbf60415d5e2aec0c865b514ad0c577d21b91405
 
-commit 7e74d81ad57a159f14110eb5348b3bc7990b8bd4
-Merge: ecd7c8d e2a6cdc
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Mon May 7 07:02:49 2012 -0700
+commit 1762420b6ed76b1c4d30b913b2cac1927b666534
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Wed Aug 22 10:01:31 2012 -0700
 
-    Merge branch 'master' into windows
+    Update changelog.
+    
+    Change-Id: Idf5af69d5a9dbe35f58e30a8afcbfcd29bb7ebfe
 
-commit e2a6cdc0816af9d0c77933f5017f137da3d52a35
+commit 976ab7aca908309b8282cb40bc080ca859136854
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Mon May 7 06:39:56 2012 -0700
+Date:   Thu Aug 23 18:21:36 2012 -0700
 
-    Address some of the comments on CGNR patch
+    Remove Google-era vestigial unit test.
     
-    - Rename BlockDiagonalPreconditioner to BlockJacobiPreconditioner
-    - Include the diagonal in the block jacobi preconditioner.
-    - Better flag help for eta.
-    - Enable test for CGNR
-    - Rename CONJUGATE_GRADIENTS to CGNR.
-    - etc.
+    Change-Id: Ia7a295a5c759a17c1675a3055d287d3e40e9e0fe
 
-commit 1b95dc580aa5d89be021c0915e26df83f18013bb
-Merge: 211812a 7646039
+commit 6ad6257de0e2152ac5e77dc003758de45187d6ea
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Mon May 7 04:34:10 2012 -0700
+Date:   Wed Aug 22 11:10:31 2012 -0700
 
-    Merge branch 'master' of https://code.google.com/p/ceres-solver
+    Add a workaround for an Android NDK compiler bug.
+    
+    On certain NDK build configurations, one of the innermost
+    parts of the Schur eliminator would get compiled
+    incorrectly. The compiler changed a -= to a +=.
+    
+    The normal Ceres unit tests caught the problem; however,
+    since it is not possible to build the tests with the NDK
+    (only with the standalone toolchain) this was difficult to
+    track down. Finding the issue involved pasting the schur
+    eliminator unit test inside of solver_impl.cc and other such
+    hacks.
+    
+    Change-Id: Ie91bb545d74fe39f0c8cbd1a6eb69ee4d8b25fb2
 
-commit 211812a57360d2011cbcfd115cd55e0eb73600db
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Mon May 7 04:33:50 2012 -0700
+commit aecb2dc92b4aa7f3bf77a1ac918e62953602392b
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Wed Aug 22 10:08:17 2012 -0700
 
-    Better error handling in bundle_adjuster.cc
+    Fix relative path bug in bibtex call.
+    
+    Change-Id: I0d31786564320a6831259bcdf4c75a6b665c43ad
 
-commit 7646039ad9672b267495f5b31925473ad3022ac8
+commit 1e2892009e591804df6286caebd5c960e7e3b099
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Sun May 6 22:02:19 2012 -0700
+Date:   Tue Aug 21 18:00:54 2012 -0700
 
-    Kashif's corrections to the docs
+    Update Summary::FullReport to report dogleg type.
+    
+    Change-Id: I0b4be8d7486c1c4b36b299693b3fe8b0d3426537
 
-commit 0d2d34148d10c5c7e924b3ca82ad2b237573ef64
+commit 295ade1122a86b83e1ea605d5ca394f315874717
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Sun May 6 21:16:03 2012 -0700
+Date:   Wed Aug 22 06:51:22 2012 -0700
 
-    glog minimum version requirements
+    Fix Eigen3 Row/Column Major storage issue.
     
-    Building Ceres requires version 0.3.1 or better of glog.
-    Fedora 16 ships with a busted version 0.3.
+    Eigen3 does not allow column vectors to be stored in row-major
+    format. NumericDiffCostFunction by default stores its Jacobian
+    matrices in row-major format. This works fine if the residual
+    contains more than one variable. But if the residual block
+    depends on one variable and has more than one residuals, the
+    resulting Jacobian matrix is a column matrix in row-major format
+    resulting in a compile time error.
     
-    issue 15 contains the gory details.
+    The fix is to check the template parameters and switch to column-major
+    storage as needed.
     
-    Added a note to the build documentation to this effect.
+    Thanks to Lena Gieseke for reporting this.
+    
+    Change-Id: Icc51c5b38e1f3609e0e1ecb3c4e4a02aecd72c3b
 
-commit 39efc5ec4b64b8f5a2c5a3dbacdbc45421221547
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Sun May 6 16:09:52 2012 -0700
+commit 9ad27e8e9fb1bbd2054e2f6ae37623e01428f1c0
+Author: Arnaud Gelas <arnaudgelas@gmail.com>
+Date:   Tue Aug 21 09:56:30 2012 +0200
 
-    Fix tests broken by the CGNR change.
+    Add one uninstall target to remove all installed files
+    
+    Change-Id: Ifcf89a6c27b25f28403d95a50e29c093a525298f
 
-commit 3faa08b7f7c4ac73661c6a15a6824c12080dfcb1
-Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Sun May 6 16:08:22 2012 -0700
+commit 0c3a748ee49e04fe334f8f5a433649d18003d550
+Author: Markus Moll <markus.moll@esat.kuleuven.be>
+Date:   Tue Aug 21 14:44:59 2012 +0200
 
-    Formatting fixed based on Keir's comments and extended the tests
+    Allow equal lower and upper bound for diagonal scaling.
+    
+    This way, setting the lower and upper bound both to 1.0, one can disable
+    the automatic trust region scaling.
+    
+    Change-Id: Ifa317a6911b813a89c1cf7fdfde25af603705319
 
-commit 4f21c68409bc478c431a9b6aedf9e5cfdf11d2f3
-Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Sun May 6 15:33:47 2012 -0700
+commit 3d644b76adefac6475b91dc53c3ae5e01c4f4d66
+Author: Arnaud Gelas <arnaudgelas@gmail.com>
+Date:   Thu Aug 16 17:33:21 2012 +0200
 
-    Fix the struct weak ordering used by independent set ordering, tests for it
+    Install headers, libraries and pdf
+    
+    Headers are installed in ${CMAKE_INSTALL_PREFIX}/include/ceres
+    Libraries are installed in ${CMAKE_INSTALL_PREFIX}/lib
+    pdf is installed in ${CMAKE_INSTALL_PREFIX}/share/ceres/docs
+    
+    Change-Id: Ic175f2c2f5fa86820a1e8c64c2ed171f4a302a68
 
-commit 887b156b917ccd4c172484452b059d33ea45f4f0
-Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Sun May 6 15:14:47 2012 -0700
+commit d2fb5adea4d8c2aeb43c4289c6976798a54d3cf1
+Author: Arnaud Gelas <arnaudgelas@gmail.com>
+Date:   Fri Aug 17 10:11:02 2012 +0200
 
-    fix he degree ordering routine
+    Configure gerrit hook at CMake time
+    
+    If the source directory is a clone, at CMake time the commit-msg hook gets
+    downloaded and installed in the right location.
+    
+    Change-Id: I5fee17d050ca22d8b92a49fdcc2a1cd6659f209b
 
-commit ecd7c8df2af19404dc394b36bbe96e9db3bce840
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Sun May 6 00:09:41 2012 -0700
+commit 73166098fc4b1072adc30321c666188a3909c43c
+Author: Arnaud Gelas <arnaudgelas@gmail.com>
+Date:   Mon Aug 20 15:40:41 2012 +0200
 
-    First step towards windows compatibilty
+    Add one CMake option to build the examples.
+    
+    Currently the examples are always built. For external projects, it is useful
+    not to compile the examples.
     
-    This adds some small changes to Ceres to make it mostly
-    compile on Windows. There are still issues with the
-    hash map use in schur_ordering.cc but I will fix those
-    shortly.
+    Change-Id: I41d3bde19c7e742818e60f78222d39c43992ca8b
 
-commit f7898fba1b92f0e996571b5bfa22a37f5e3644de
+commit 86d4f1ba41ef14eb1b6b61a7936af83387b35eb2
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Sat May 5 20:55:08 2012 -0700
+Date:   Mon Aug 20 11:52:04 2012 -0700
 
-    Add a general sparse iterative solver: CGNR
+    Add missing return statement.
     
-    This adds a new LinearOperator which implements symmetric
-    products of a matrix, and a new CGNR solver to leverage
-    CG to directly solve the normal equations. This also
-    includes a block diagonal preconditioner. In experiments
-    on problem-16, the non-preconditioned version is about
-    1/5 the speed of SPARSE_SCHUR, and the preconditioned
-    version using block cholesky is about 20% slower than
-    SPARSE_SCHUR.
+    Change-Id: I5eaf718318e27040e3c97e32ee46cf0a11176a37
 
-commit 0a359d6198d257776a8831c3eb98f64ee91cf836
+commit 51eb229da34187a4e8ce73ed9cc0e731998bb2be
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Sat May 5 20:33:46 2012 -0700
+Date:   Mon Aug 20 11:46:12 2012 -0700
 
-    Comment formatting.
+    Add Program::ToString() to aid debugging.
+    
+    Change-Id: I0ab37ed2fe0947ca87a152919d4e7dc9b56dedc6
 
-commit db4ec9312bb2f1ca7b2337812f6bad6cdd75b227
+commit bcc7100635e2047dc2b77df19a4ded8a6ab4d4b9
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Sat May 5 20:33:16 2012 -0700
+Date:   Mon Aug 20 11:45:04 2012 -0700
 
-    Comment formatting
+    Ignore minted.sty.
+    
+    Change-Id: I2467a6f801812b9007b51bf14b00757f026e4322
 
-commit f10163aaf3e57f52551bcd60bbdae873890a49dd
+commit 9705a736dd3d6fbead0d8a6ff77102c69bbcdc08
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Fri May 4 21:33:53 2012 -0700
+Date:   Mon Aug 20 11:24:05 2012 -0700
 
-    Warn about disabled schur specializations.
+    Add ParameterBlock::ToString() to aid debugging.
     
-    This commit brought to you from 30,000ft.
+    Change-Id: Id3f5cb27b855c536dd65a986f345bd8eb2799dfa
 
-commit ad7b2b4aaf3ccc51f2b854febd53a9df54686cfe
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Fri May 4 20:15:28 2012 -0700
+commit 0c714a70e6123ceb68e5cfcd3cfbee0d09deb1db
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Mon Aug 20 11:18:16 2012 -0700
+
+    Fix blanks before private in loss_function.h
+    
+    Change-Id: I068bed6431bc7c9b7958af391655df61499000b2
+
+commit 51cf7cbe3bac45c6807c2703a2fc3175d76a1b47
+Author: Markus Moll <markus.moll@esat.kuleuven.be>
+Date:   Mon Aug 20 20:10:20 2012 +0200
+
+    Add the two-dimensional subspace search to DoglegStrategy
+    
+    Change-Id: I5163744c100cdf07dd93343d0734ffe0e80364f3
 
-    Add vim swapfiles to .gitignore
+commit ad1f7b772e559a911ac3a3b078b0aee1836fe785
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Mon Aug 20 11:10:34 2012 -0700
+
+    Add ArcTanLoss, TolerantLoss and ComposedLossFunction.
+    
+    Based on work by James Roseborough.
+    
+    Change-Id: Idc4e0b099028f67702bfc7fe3e43dbd96b6f9256
 
-commit 6447219826bf6e47b0c99d9ff0eaf5e2ba573d79
+commit 05292bf8fc5208b86b4a13544615b584f6efa936
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Thu May 3 21:53:07 2012 -0700
+Date:   Mon Aug 20 07:40:45 2012 -0700
+
+    Add a TrustRegionStrategy::Summary object.
+    
+    Change-Id: I7caee35a3408ee4a0ec16ba407410d822929340d
 
-    1. Changes the tutorial to refer to BriefReport.
-    2. Some of the enums have commas at the end.
-    3. Fix a bug in the default value of circle_fit.cc in the examples.
+commit b12b906c4d21c3949f0dce62c4c0d083c8edecf1
+Author: Arnaud Gelas <arnaudgelas@gmail.com>
+Date:   Wed Aug 15 16:27:38 2012 +0200
 
-commit 30c5f93c7f88dec49f76168663372772e06f17f5
+    Add one option to generate the PDF from CMake at build time
+    
+    Make sure pygmentize is installed
+    
+    Change-Id: I068ba45c33a8e96acc906a464b12d10d58b3e231
+
+commit b9f15a59361c609ffc4a328aea9be3d265b5da81
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Thu May 3 10:44:43 2012 -0700
+Date:   Sat Aug 18 13:06:19 2012 -0700
+
+    Add a dense Cholesky factorization based linear solver.
+    
+    For problems with a small number of variables, but a large
+    number of residuals, it is sometimes beneficial to use the
+    Cholesky factorization on the normal equations, instead of
+    the dense QR factorization of the Jacobian, even though it
+    is numerically the better thing to do.
+    
+    Change-Id: I3506b006195754018deec964e6e190b7e8c9ac8f
 
-    Rework the glog and gtest path checking to be consistent with the rest of the file and disable the dashboard support enabled by the earlier ctesting related patch.
+commit b3fa009435acf476cd373052e62988f6437970b1
+Author: Arnaud Gelas <arnaudgelas@gmail.com>
+Date:   Fri Aug 17 10:31:41 2012 +0200
 
-commit f10b033eb4aca77919987bc551d16d8a88b10110
-Merge: cc38774 e0a52a9
+    Set CMAKE_*_OUTPUT_DIRECTORY
+    
+    Gather
+     * all executables in ${CMAKE_BINARY_DIR}/bin
+     * all libraries (static and dynamic) in ${CMAKE_BINARY_DIR}/lib
+    
+    Change-Id: Ibc2fa1adfb6f0aea65d66d570259b79546bf3b07
+
+commit 1b8a4d5d11671ed83cf6077e363dd95333f08ef8
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Thu May 3 08:45:20 2012 -0700
+Date:   Fri Aug 17 16:49:11 2012 -0700
+
+    Fix a minor bug in detect_structure logging.
+    
+    Change-Id: I117f7745e4c67595b3ff9244cde82b5b5b34ee4b
 
-    Merge branch 'ctest'
+commit 31c1e784ab2cb9294c6e05414cf06aae2b3766de
+Author: Keir Mierle <mierle@gmail.com>
+Date:   Fri Aug 17 16:16:32 2012 -0700
+
+    Minor cleanups.
+    
+    Change-Id: Ida4866997deeaa1bc2cebd6b69313a05ac82e457
 
-commit e0a52a993394e73bc7f7db8d520728926feab83e
+commit e83f7879a8b21c6976e116958caf35bcdcf41cb0
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Thu May 3 08:43:34 2012 -0700
+Date:   Fri Aug 17 15:34:42 2012 -0700
 
-    Arnaus Gelas' patch to add better path searching for gflags and glog
+    Fix SuiteSparse3 UFConfig.h detection really.
+    
+    Change-Id: Id187102e755b7d778dff4363f22f9a4697ed12dd
 
-commit a9b8e815e1c026599734510399b10f4cf014c9cd
+commit 96f25dc57658d296ee6b6633818b4f1e51d7d587
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Thu May 3 08:41:52 2012 -0700
+Date:   Fri Aug 17 15:34:42 2012 -0700
+
+    Fix SuiteSparse3 UFConfig.h detection.
+    
+    Change-Id: Ia59aefdb0ad7f713f76ed79692f2db4fa2821e5b
+
+commit c497bd6cd9aa944f518aa491d3bc645851ff9594
+Author: Markus Moll <markus.moll@esat.kuleuven.be>
+Date:   Fri Aug 17 14:40:13 2012 +0200
 
-    Arnaus Gelas' patch to add .gitignore
+    Add UFconfig and/or SuiteSparse_config test to CMakeLists.txt
+    
+    SuiteSparse 4 requires linking to libsuitesparseconfig.a.
+    Both SuiteSparse 3 and SuiteSparse 4 require an additional header
+    (either UFconfig.h or SuiteSparse_config.h) that is not found if it is
+    in a separate path. Therefore, add explicit checks.
+    
+    Change-Id: I699902b5db4f1b7f17134b5a54f9aa681445e294
 
-commit a0cefc3347c32b2065053bbaff4f34d11529d931
+commit 383c04f4236d92801c7c674892814362dedf7ad6
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Thu May 3 08:38:33 2012 -0700
+Date:   Fri Aug 17 10:14:04 2012 -0700
 
-    Arnaus Gelas' patch to move to Ctest
+    Fix QuaternionToAngleAxis to ensure rotations are between -pi and pi.
+    
+    Thanks to Guoxuan Zhang for reporting this.
+    
+    Change-Id: I2831ca3a04d5dc6467849c290461adbe23faaea3
 
-commit cc38774d74e287704915282425fbd16818a72ec3
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Thu May 3 01:27:50 2012 -0700
+commit dd2b17d7dd9750801ba4720bdece2062e59b7ae3
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Thu Aug 16 19:34:57 2012 -0700
 
-    Clarify ProgramEvaluator comments.
+    CERES_DONT_HAVE_PROTOCOL_BUFFERS -> CERES_NO_PROTOCOL_BUFFERS.
+    
+    Change-Id: I6c9f50e4c006faf4e75a8f417455db18357f3187
 
-commit 017c9530df557863f78212fb5ccd02814baa9fa8
+commit 8b4cb7aa2c74a0da62c638b2023566aa242af995
 Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Wed May 2 08:21:59 2012 -0700
+Date:   Thu Aug 16 19:26:55 2012 -0700
 
-    Mac OS X build instructions are much simpler, as homebrew takes care of gflags when glog is brought in. Also CMAKE does not need any flags to do the default thing
+    Fix sparse linear algebra library logging in Summary::FullReport.
+    
+    Change-Id: Id2c902dc86c00954fde7749c7b4a67dd94215a31
 
-commit 92d5ab5f8ae6fe355c30b606a5f230415ee0494b
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Tue May 1 18:33:08 2012 -0700
+commit 47d26bcd3b38b5ff53b34768c33b499d47b26bd0
+Author: Markus Moll <markus.moll@esat.kuleuven.be>
+Date:   Thu Aug 16 00:23:38 2012 +0200
 
-    Link BLAS explicitly on non-Mac platforms
+    Do not implicitly negate the step in the TrustRegionMinimizer.
     
-    Fixes issue #3.
+    In the TrustRegionMinimizer, the step is currently implicitly negated.
+    This is done so that the linearized residual is |r - J*step|^2, which
+    corresponds to J*step = r, so neither J nor r have to be modified.
+    However, it leads to the rather unintuitive situation that the strategy
+    returns a step in positive gradient direction, which you would expect to
+    increase the function value. One way is to rename the "step" parameter in
+    the strategy to "negative_step" and document it.
+    This patch instead moves the negation inside the strategy, just around
+    the linear solver call, so that it is done in a local context and easier
+    to document.
+    
+    Change-Id: Idb258149a01f61c64e22128ea221c5a30cd89c89
 
-commit df3e54eb4a6b001b7f0560a2da73a5bd7f18615e
-Author: Keir Mierle <mierle@gmail.com>
-Date:   Tue May 1 18:22:51 2012 -0700
+commit 51da590c8457e6664f76fe9813425a0c71351497
+Author: Markus Moll <markus.moll@esat.kuleuven.be>
+Date:   Fri Aug 17 12:56:09 2012 +0200
+
+    Remove tmp file
+    
+    Change-Id: I07496fafae7b0c5c12cc26ae336e0db3b5592735
+
+commit 7006a1f2b1701b8d89b8d1525fc0101943802221
+Author: Sameer Agarwal <sameeragarwal@google.com>
+Date:   Thu Aug 16 18:04:22 2012 -0700
 
-    Fix link order of CHOLMOD
+    Correct example code in Powell's function example.
+    
+    Thanks to Petter Strandmark for pointing this out.
     
-    This was working by accident due to dynamic linking. Fixes issue #2.
+    Change-Id: I967632235dccdb481396e94904bb911c9a1efe1e
 
-commit f477a3835329e2b48eb20c34c631a480b0f0d5bf
+commit 57a44b27bc6fc95b4e70fdc25c25c9925a2072a0
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Tue May 1 18:10:48 2012 -0700
+Date:   Thu Aug 16 17:04:50 2012 -0700
 
-    Fix Eigen search paths
+    Remove unnecessary flags in NDK build.
     
-    Fixes issue #1 on http://code.google.com/p/ceres-solver.
+    Change-Id: Ib5b4d0b7f2d898671252734978c789b8171d96a8
 
-commit 17fbc8ebb894c1d22bb3b0b02ea1394b580120f8
-Author: Sameer Agarwal <sameeragarwal@google.com>
-Date:   Tue May 1 00:21:19 2012 -0700
+commit f21bee247251a8b2e836c215a84c4668c31d75cd
+Author: Keir Mierle <mierle@gmail.com>
+Date:   Thu Aug 16 16:27:10 2012 -0700
 
-    Minor changes to the documentation. Formatting, and typos.
+    Fix for fpclassify.h NDK porting work.
+    
+    Change-Id: I69df1b4caf2941ed96a53e35e43ec54073f84f59
 
-commit 8ebb0730388045570f22b89fe8672c860cd2ad1b
+commit 8ceb02cb75b66602de44a35e413225386cb21c27
 Author: Keir Mierle <mierle@gmail.com>
-Date:   Mon Apr 30 23:09:08 2012 -0700
+Date:   Thu Aug 16 14:23:47 2012 -0700
 
-    Initial commit of Ceres Solver.
+    Add Android NDK build files.
+    
+    This adds a Android.mk build that builds a Ceres static library
+    suitable for embetting in larger Android applications. This is
+    useful when needing to build Ceres without GPL'd components, since
+    the standalone toolchain (needed for the CMake Android build) does
+    not work with STLPort.
+    
+    Change-Id: I8d857237f6f82658741017d161b2e31d9a20e5a7
diff --git a/extern/libmv/third_party/ceres/SConscript b/extern/libmv/third_party/ceres/SConscript
index c629fa00176..6d0d2cd5c40 100644
--- a/extern/libmv/third_party/ceres/SConscript
+++ b/extern/libmv/third_party/ceres/SConscript
@@ -20,9 +20,13 @@ defs.append('CERES_HAVE_PTHREAD')
 defs.append('CERES_HASH_NAMESPACE_START=namespace std { namespace tr1 {')
 defs.append('CERES_HASH_NAMESPACE_END=}}')
 defs.append('CERES_NO_SUITESPARSE')
-defs.append('CERES_DONT_HAVE_PROTOCOL_BUFFERS')
+defs.append('CERES_NO_CXSPARSE')
+defs.append('CERES_NO_PROTOCOL_BUFFERS')
 defs.append('CERES_RESTRICT_SCHUR_SPECIALIZATION')
 
+if 'Mac OS X 10.5' in env['MACOSX_SDK_CHECK']:
+    defs.append('CERES_NO_TR1')
+
 incs = '. ../../ ../../../Eigen3 ./include ./internal ../gflags'
 
 # work around broken hashtable in 10.5 SDK
diff --git a/extern/libmv/third_party/ceres/bundle.sh b/extern/libmv/third_party/ceres/bundle.sh
index 99aaadd8d87..ccf6d0aca16 100755
--- a/extern/libmv/third_party/ceres/bundle.sh
+++ b/extern/libmv/third_party/ceres/bundle.sh
@@ -1,6 +1,5 @@
 #!/bin/sh
 
-if false; then
 if [ "x$1" = "x--i-really-know-what-im-doing" ] ; then
   echo Proceeding as requested by command line ...
 else
@@ -8,16 +7,22 @@ else
   exit 1
 fi
 
-repo="https://code.google.com/p/ceres-solver/"
-branch="windows"
+repo="https://ceres-solver.googlesource.com/ceres-solver"
+branch="master"
+tag="1.3.0"
 tmp=`mktemp -d`
+checkout="$tmp/ceres"
 
-GIT="git --git-dir $tmp/ceres/.git --work-tree $tmp/ceres"
+GIT="git --git-dir $tmp/ceres/.git --work-tree $checkout"
 
-git clone $repo $tmp/ceres
+git clone $repo $checkout
 
 if [ $branch != "master" ]; then
     $GIT checkout -t remotes/origin/$branch
+else
+  if [ "x$tag" != "x" ]; then
+      $GIT checkout $tag
+  fi
 fi
 
 $GIT log -n 50 > ChangeLog
@@ -37,8 +42,6 @@ done
 
 rm -rf $tmp
 
-fi
-
 sources=`find ./include ./internal -type f -iname '*.cc' -or -iname '*.cpp' -or -iname '*.c' | sed -r 's/^\.\//\t/' | grep -v -E 'schur_eliminator_[0-9]_[0-9]_[0-9d].cc' | sort -d`
 generated_sources=`find ./include ./internal -type f -iname '*.cc' -or -iname '*.cpp' -or -iname '*.c' | sed -r 's/^\.\//#\t\t/' | grep -E 'schur_eliminator_[0-9]_[0-9]_[0-9d].cc' | sort -d`
 headers=`find ./include ./internal -type f -iname '*.h' | sed -r 's/^\.\//\t/' | sort -d`
@@ -114,13 +117,13 @@ cat > CMakeLists.txt << EOF
 
 set(INC
 	.
-	../../../Eigen3
 	include
 	internal
 	../gflags
 )
 
 set(INC_SYS
+	../../../Eigen3
 )
 
 set(SRC
@@ -142,7 +145,7 @@ if(WIN32)
 
 	if(NOT MINGW)
 		list(APPEND INC
-			third_party/msinttypes
+			../msinttypes
 		)
 	endif()
 else()
@@ -153,13 +156,32 @@ endif()
 
 add_definitions(
 	-DCERES_HAVE_PTHREAD
-	-D"CERES_HASH_NAMESPACE_START=namespace std { namespace tr1 {"
-	-D"CERES_HASH_NAMESPACE_END=}}"
 	-DCERES_NO_SUITESPARSE
-	-DCERES_DONT_HAVE_PROTOCOL_BUFFERS
+	-DCERES_NO_CXSPARSE
+	-DCERES_NO_PROTOCOL_BUFFERS
 	-DCERES_RESTRICT_SCHUR_SPECIALIZATION
 )
 
+if(MSVC10)
+	add_definitions(
+		-D"CERES_HASH_NAMESPACE_START=namespace std {"
+		-D"CERES_HASH_NAMESPACE_END=}"
+	)
+else()
+	add_definitions(
+		-D"CERES_HASH_NAMESPACE_START=namespace std { namespace tr1 {"
+		-D"CERES_HASH_NAMESPACE_END=}}"
+	)
+endif()
+
+if(APPLE)
+	if(CMAKE_OSX_DEPLOYMENT_TARGET STREQUAL "10.5")
+		add_definitions(
+			-DCERES_NO_TR1
+		)
+	endif()
+endif()
+
 blender_add_lib(extern_ceres "\${SRC}" "\${INC}" "\${INC_SYS}")
 EOF
 
@@ -186,11 +208,20 @@ defs.append('CERES_HAVE_PTHREAD')
 defs.append('CERES_HASH_NAMESPACE_START=namespace std { namespace tr1 {')
 defs.append('CERES_HASH_NAMESPACE_END=}}')
 defs.append('CERES_NO_SUITESPARSE')
-defs.append('CERES_DONT_HAVE_PROTOCOL_BUFFERS')
+defs.append('CERES_NO_CXSPARSE')
+defs.append('CERES_NO_PROTOCOL_BUFFERS')
 defs.append('CERES_RESTRICT_SCHUR_SPECIALIZATION')
 
+if 'Mac OS X 10.5' in env['MACOSX_SDK_CHECK']:
+    defs.append('CERES_NO_TR1')
+
 incs = '. ../../ ../../../Eigen3 ./include ./internal ../gflags'
 
+# work around broken hashtable in 10.5 SDK
+if env['OURPLATFORM'] == 'darwin' and env['WITH_BF_BOOST']:
+    incs += ' ' + env['BF_BOOST_INC']
+    defs.append('CERES_HASH_BOOST')
+
 if env['OURPLATFORM'] in ('win32-vc', 'win32-mingw', 'linuxcross', 'win64-vc', 'win64-mingw'):
     if env['OURPLATFORM'] in ('win32-vc', 'win64-vc'):
         incs += ' ../msinttypes'
diff --git a/extern/libmv/third_party/ceres/files.txt b/extern/libmv/third_party/ceres/files.txt
index e9d7f585260..55083572977 100644
--- a/extern/libmv/third_party/ceres/files.txt
+++ b/extern/libmv/third_party/ceres/files.txt
@@ -2,6 +2,8 @@ include/ceres/autodiff_cost_function.h
 include/ceres/ceres.h
 include/ceres/conditioned_cost_function.h
 include/ceres/cost_function.h
+include/ceres/crs_matrix.h
+include/ceres/fpclassify.h
 include/ceres/internal/autodiff.h
 include/ceres/internal/eigen.h
 include/ceres/internal/fixed_array.h
@@ -20,6 +22,8 @@ include/ceres/rotation.h
 include/ceres/sized_cost_function.h
 include/ceres/solver.h
 include/ceres/types.h
+internal/ceres/array_utils.cc
+internal/ceres/array_utils.h
 internal/ceres/block_evaluate_preparer.cc
 internal/ceres/block_evaluate_preparer.h
 internal/ceres/block_jacobian_writer.cc
@@ -52,13 +56,19 @@ internal/ceres/conjugate_gradients_solver.cc
 internal/ceres/conjugate_gradients_solver.h
 internal/ceres/corrector.cc
 internal/ceres/corrector.h
+internal/ceres/cxsparse.cc
+internal/ceres/cxsparse.h
 internal/ceres/dense_jacobian_writer.h
+internal/ceres/dense_normal_cholesky_solver.cc
+internal/ceres/dense_normal_cholesky_solver.h
 internal/ceres/dense_qr_solver.cc
 internal/ceres/dense_qr_solver.h
 internal/ceres/dense_sparse_matrix.cc
 internal/ceres/dense_sparse_matrix.h
 internal/ceres/detect_structure.cc
 internal/ceres/detect_structure.h
+internal/ceres/dogleg_strategy.cc
+internal/ceres/dogleg_strategy.h
 internal/ceres/evaluator.cc
 internal/ceres/evaluator.h
 internal/ceres/file.cc
@@ -79,6 +89,7 @@ internal/ceres/generated/schur_eliminator_4_4_3.cc
 internal/ceres/generated/schur_eliminator_4_4_4.cc
 internal/ceres/generated/schur_eliminator_4_4_d.cc
 internal/ceres/generated/schur_eliminator_d_d_d.cc
+internal/ceres/generate_eliminator_specialization.py
 internal/ceres/gradient_checking_cost_function.cc
 internal/ceres/gradient_checking_cost_function.h
 internal/ceres/graph_algorithms.h
@@ -88,8 +99,8 @@ internal/ceres/implicit_schur_complement.h
 internal/ceres/integral_types.h
 internal/ceres/iterative_schur_complement_solver.cc
 internal/ceres/iterative_schur_complement_solver.h
-internal/ceres/levenberg_marquardt.cc
-internal/ceres/levenberg_marquardt.h
+internal/ceres/levenberg_marquardt_strategy.cc
+internal/ceres/levenberg_marquardt_strategy.h
 internal/ceres/linear_least_squares_problems.cc
 internal/ceres/linear_least_squares_problems.h
 internal/ceres/linear_operator.cc
@@ -106,6 +117,8 @@ internal/ceres/normal_prior.cc
 internal/ceres/parameter_block.h
 internal/ceres/partitioned_matrix_view.cc
 internal/ceres/partitioned_matrix_view.h
+internal/ceres/polynomial_solver.cc
+internal/ceres/polynomial_solver.h
 internal/ceres/problem.cc
 internal/ceres/problem_impl.cc
 internal/ceres/problem_impl.h
@@ -136,6 +149,7 @@ internal/ceres/sparse_matrix.h
 internal/ceres/sparse_normal_cholesky_solver.cc
 internal/ceres/sparse_normal_cholesky_solver.h
 internal/ceres/split.cc
+internal/ceres/split.h
 internal/ceres/stl_util.h
 internal/ceres/stringprintf.cc
 internal/ceres/stringprintf.h
@@ -143,6 +157,10 @@ internal/ceres/suitesparse.cc
 internal/ceres/suitesparse.h
 internal/ceres/triplet_sparse_matrix.cc
 internal/ceres/triplet_sparse_matrix.h
+internal/ceres/trust_region_minimizer.cc
+internal/ceres/trust_region_minimizer.h
+internal/ceres/trust_region_strategy.cc
+internal/ceres/trust_region_strategy.h
 internal/ceres/types.cc
 internal/ceres/visibility_based_preconditioner.cc
 internal/ceres/visibility_based_preconditioner.h
diff --git a/extern/libmv/third_party/ceres/include/ceres/autodiff_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/autodiff_cost_function.h
index e86d6993864..da9ee2c7993 100644
--- a/extern/libmv/third_party/ceres/include/ceres/autodiff_cost_function.h
+++ b/extern/libmv/third_party/ceres/include/ceres/autodiff_cost_function.h
@@ -163,7 +163,7 @@ class AutoDiffCostFunction :
   explicit AutoDiffCostFunction(CostFunctor* functor)
       : functor_(functor) {
     CHECK_NE(M, DYNAMIC) << "Can't run the fixed-size constructor if the "
-                         << "number of residuals is set to ceres::DYNAMIC.";
+                          << "number of residuals is set to ceres::DYNAMIC.";
   }
 
   // Takes ownership of functor. Ignores the template-provided number of
@@ -174,7 +174,7 @@ class AutoDiffCostFunction :
   AutoDiffCostFunction(CostFunctor* functor, int num_residuals)
       : functor_(functor) {
     CHECK_EQ(M, DYNAMIC) << "Can't run the dynamic-size constructor if the "
-                         << "number of residuals is not ceres::DYNAMIC.";
+                          << "number of residuals is not ceres::DYNAMIC.";
     SizedCostFunction<M, N0, N1, N2, N3, N4, N5>::set_num_residuals(num_residuals);
   }
 
diff --git a/extern/libmv/third_party/ceres/include/ceres/cost_function.h b/extern/libmv/third_party/ceres/include/ceres/cost_function.h
index 84403d90636..9b010f78f9d 100644
--- a/extern/libmv/third_party/ceres/include/ceres/cost_function.h
+++ b/extern/libmv/third_party/ceres/include/ceres/cost_function.h
@@ -119,7 +119,7 @@ class CostFunction {
   // number of outputs (residuals).
   vector<int16> parameter_block_sizes_;
   int num_residuals_;
-  DISALLOW_COPY_AND_ASSIGN(CostFunction);
+  CERES_DISALLOW_COPY_AND_ASSIGN(CostFunction);
 };
 
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/include/ceres/crs_matrix.h b/extern/libmv/third_party/ceres/include/ceres/crs_matrix.h
new file mode 100644
index 00000000000..c9fe8f78b7c
--- /dev/null
+++ b/extern/libmv/third_party/ceres/include/ceres/crs_matrix.h
@@ -0,0 +1,65 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_PUBLIC_CRS_MATRIX_H_
+#define CERES_PUBLIC_CRS_MATRIX_H_
+
+#include <vector>
+#include "ceres/internal/port.h"
+
+namespace ceres {
+
+// A compressed row sparse matrix used primarily for communicating the
+// Jacobian matrix to the user.
+struct CRSMatrix {
+  CRSMatrix() : num_rows(0), num_cols(0) {}
+
+  int num_rows;
+  int num_cols;
+
+  // A compressed row matrix stores its contents in three arrays.
+  // The non-zero pattern of the i^th row is given by
+  //
+  //   rows[cols[i] ... cols[i + 1]]
+  //
+  // and the corresponding values by
+  //
+  //   values[cols[i] ... cols[i + 1]]
+  //
+  // Thus, cols is a vector of size num_cols + 1, and rows and values
+  // have as many entries as number of non-zeros in the matrix.
+  vector<int> cols;
+  vector<int> rows;
+  vector<double> values;
+};
+
+}  // namespace ceres
+
+#endif  // CERES_PUBLIC_CRS_MATRIX_H_
diff --git a/extern/libmv/third_party/ceres/include/ceres/fpclassify.h b/extern/libmv/third_party/ceres/include/ceres/fpclassify.h
new file mode 100644
index 00000000000..5a9ea1599d2
--- /dev/null
+++ b/extern/libmv/third_party/ceres/include/ceres/fpclassify.h
@@ -0,0 +1,88 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: keir@google.com (Keir Mierle)
+//
+// Portable floating point classification. The names are picked such that they
+// do not collide with macros. For example, "isnan" in C99 is a macro and hence
+// does not respect namespaces.
+//
+// TODO(keir): Finish porting!
+
+#ifndef CERES_PUBLIC_FPCLASSIFY_H_
+#define CERES_PUBLIC_FPCLASSIFY_H_
+
+#if defined(_MSC_VER)
+#include <float.h>
+#endif
+
+namespace ceres {
+
+#if defined(_MSC_VER)
+inline bool IsFinite  (double x) { return _finite(x);                }
+inline bool IsInfinite(double x) { return !_finite(x) && !_isnan(x); }
+inline bool IsNaN     (double x) { return _isnan(x);                 }
+inline bool IsNormal  (double x) {
+  int classification = _fpclass(x);
+  return classification == _FPCLASS_NN ||
+         classification == _FPCLASS_PN;
+}
+#elif defined(ANDROID)
+
+// On Android when using the GNU STL, the C++ fpclassify functions are not
+// available. Strictly speaking, the std functions are are not standard until
+// C++11. Instead use the C99 macros on Android.
+inline bool IsNaN     (double x) { return isnan(x);    }
+inline bool IsNormal  (double x) { return isnormal(x); }
+
+// On Android NDK r6, when using STLPort, the isinf and isfinite functions are
+// not available, so reimplement them.
+#  if defined(_STLPORT_VERSION)
+inline bool IsInfinite(double x) {
+  return x ==  std::numeric_limits<double>::infinity() ||
+         x == -std::numeric_limits<double>::infinity();
+}
+inline bool IsFinite(double x) {
+  return !isnan(x) && !IsInfinite(x);
+}
+#  else
+inline bool IsFinite  (double x) { return isfinite(x); }
+inline bool IsInfinite(double x) { return isinf(x);    }
+#  endif  // defined(_STLPORT_VERSION)
+#else
+// These definitions are for the normal Unix suspects.
+// TODO(keir): Test the "else" with more platforms.
+inline bool IsFinite  (double x) { return std::isfinite(x); }
+inline bool IsInfinite(double x) { return std::isinf(x);    }
+inline bool IsNaN     (double x) { return std::isnan(x);    }
+inline bool IsNormal  (double x) { return std::isnormal(x); }
+#endif
+
+}  // namespace ceres
+
+#endif  // CERES_PUBLIC_FPCLASSIFY_H_
diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/fixed_array.h b/extern/libmv/third_party/ceres/include/ceres/internal/fixed_array.h
index 84617c4fa06..ce777d22dc7 100644
--- a/extern/libmv/third_party/ceres/include/ceres/internal/fixed_array.h
+++ b/extern/libmv/third_party/ceres/include/ceres/internal/fixed_array.h
@@ -34,6 +34,8 @@
 
 #include <cstddef>
 #include <glog/logging.h>
+#include "Eigen/Core"
+#include "ceres/internal/macros.h"
 #include "ceres/internal/manual_constructor.h"
 
 namespace ceres {
@@ -136,7 +138,6 @@ class FixedArray {
   // and T must be the same, otherwise callers' assumptions about use
   // of this code will be broken.
   struct InnerContainer {
-    EIGEN_MAKE_ALIGNED_OPERATOR_NEW
     T element;
   };
 
diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/macros.h b/extern/libmv/third_party/ceres/include/ceres/internal/macros.h
index 0cfd773bcca..83ec31193e7 100644
--- a/extern/libmv/third_party/ceres/include/ceres/internal/macros.h
+++ b/extern/libmv/third_party/ceres/include/ceres/internal/macros.h
@@ -43,11 +43,13 @@
 //
 // For disallowing only assign or copy, write the code directly, but declare
 // the intend in a comment, for example:
-// void operator=(const TypeName&);  // DISALLOW_ASSIGN
-// Note, that most uses of DISALLOW_ASSIGN and DISALLOW_COPY are broken
-// semantically, one should either use disallow both or neither. Try to
-// avoid these in new code.
-#define DISALLOW_COPY_AND_ASSIGN(TypeName) \
+//
+//   void operator=(const TypeName&);  // _DISALLOW_ASSIGN
+
+// Note, that most uses of CERES_DISALLOW_ASSIGN and CERES_DISALLOW_COPY
+// are broken semantically, one should either use disallow both or
+// neither. Try to avoid these in new code.
+#define CERES_DISALLOW_COPY_AND_ASSIGN(TypeName) \
   TypeName(const TypeName&);               \
   void operator=(const TypeName&)
 
@@ -57,9 +59,9 @@
 // This should be used in the private: declarations for a class
 // that wants to prevent anyone from instantiating it. This is
 // especially useful for classes containing only static methods.
-#define DISALLOW_IMPLICIT_CONSTRUCTORS(TypeName) \
+#define CERES_DISALLOW_IMPLICIT_CONSTRUCTORS(TypeName) \
   TypeName();                                    \
-  DISALLOW_COPY_AND_ASSIGN(TypeName)
+  CERES_DISALLOW_COPY_AND_ASSIGN(TypeName)
 
 // The arraysize(arr) macro returns the # of elements in an array arr.
 // The expression is a compile-time constant, and therefore can be
@@ -151,4 +153,19 @@ char (&ArraySizeHelper(const T (&array)[N]))[N];
 #define MUST_USE_RESULT
 #endif
 
+// Platform independent macros to get aligned memory allocations.
+// For example
+//
+//   MyFoo my_foo CERES_ALIGN_ATTRIBUTE(16);
+//
+// Gives us an instance of MyFoo which is aligned at a 16 byte
+// boundary.
+#if defined(_MSC_VER)
+#define CERES_ALIGN_ATTRIBUTE(n) __declspec(align(n))
+#define CERES_ALIGN_OF(T) __alignof(T)
+#elif defined(__GNUC__)
+#define CERES_ALIGN_ATTRIBUTE(n) __attribute__((aligned(n)))
+#define CERES_ALIGN_OF(T) __alignof(T)
+#endif
+
 #endif  // CERES_PUBLIC_INTERNAL_MACROS_H_
diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/manual_constructor.h b/extern/libmv/third_party/ceres/include/ceres/internal/manual_constructor.h
index a1d1f444e36..174d35ee2bd 100644
--- a/extern/libmv/third_party/ceres/include/ceres/internal/manual_constructor.h
+++ b/extern/libmv/third_party/ceres/include/ceres/internal/manual_constructor.h
@@ -45,60 +45,49 @@
 namespace ceres {
 namespace internal {
 
-// ------- Define ALIGNED_CHAR_ARRAY --------------------------------
+// ------- Define CERES_ALIGNED_CHAR_ARRAY --------------------------------
 
-#ifndef ALIGNED_CHAR_ARRAY
+#ifndef CERES_ALIGNED_CHAR_ARRAY
 
 // Because MSVC and older GCCs require that the argument to their alignment
 // construct to be a literal constant integer, we use a template instantiated
 // at all the possible powers of two.
 template<int alignment, int size> struct AlignType { };
 template<int size> struct AlignType<0, size> { typedef char result[size]; };
-#if defined(_MSC_VER)
-#define BASE_PORT_H_ALIGN_ATTRIBUTE(X) __declspec(align(X))
-#define BASE_PORT_H_ALIGN_OF(T) __alignof(T)
-#elif defined(__GNUC__)
-#define BASE_PORT_H_ALIGN_ATTRIBUTE(X) __attribute__((aligned(X)))
-#define BASE_PORT_H_ALIGN_OF(T) __alignof__(T)
-#endif
 
-#if defined(BASE_PORT_H_ALIGN_ATTRIBUTE)
+#if !defined(CERES_ALIGN_ATTRIBUTE)
+#define CERES_ALIGNED_CHAR_ARRAY you_must_define_CERES_ALIGNED_CHAR_ARRAY_for_your_compiler
+#else  // !defined(CERES_ALIGN_ATTRIBUTE)
 
-#define BASE_PORT_H_ALIGNTYPE_TEMPLATE(X) \
+#define CERES_ALIGN_TYPE_TEMPLATE(X) \
   template<int size> struct AlignType<X, size> { \
-    typedef BASE_PORT_H_ALIGN_ATTRIBUTE(X) char result[size]; \
-  }
-
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(1);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(2);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(4);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(8);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(16);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(32);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(64);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(128);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(256);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(512);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(1024);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(2048);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(4096);
-BASE_PORT_H_ALIGNTYPE_TEMPLATE(8192);
+    typedef CERES_ALIGN_ATTRIBUTE(X) char result[size]; \
+  }
+
+CERES_ALIGN_TYPE_TEMPLATE(1);
+CERES_ALIGN_TYPE_TEMPLATE(2);
+CERES_ALIGN_TYPE_TEMPLATE(4);
+CERES_ALIGN_TYPE_TEMPLATE(8);
+CERES_ALIGN_TYPE_TEMPLATE(16);
+CERES_ALIGN_TYPE_TEMPLATE(32);
+CERES_ALIGN_TYPE_TEMPLATE(64);
+CERES_ALIGN_TYPE_TEMPLATE(128);
+CERES_ALIGN_TYPE_TEMPLATE(256);
+CERES_ALIGN_TYPE_TEMPLATE(512);
+CERES_ALIGN_TYPE_TEMPLATE(1024);
+CERES_ALIGN_TYPE_TEMPLATE(2048);
+CERES_ALIGN_TYPE_TEMPLATE(4096);
+CERES_ALIGN_TYPE_TEMPLATE(8192);
 // Any larger and MSVC++ will complain.
 
-#define ALIGNED_CHAR_ARRAY(T, Size) \
-  typename AlignType<BASE_PORT_H_ALIGN_OF(T), sizeof(T) * Size>::result
+#undef CERES_ALIGN_TYPE_TEMPLATE
 
-#undef BASE_PORT_H_ALIGNTYPE_TEMPLATE
-#undef BASE_PORT_H_ALIGN_ATTRIBUTE
+#define CERES_ALIGNED_CHAR_ARRAY(T, Size) \
+  typename AlignType<CERES_ALIGN_OF(T), sizeof(T) * Size>::result
 
-#else  // defined(BASE_PORT_H_ALIGN_ATTRIBUTE)
-#define ALIGNED_CHAR_ARRAY you_must_define_ALIGNED_CHAR_ARRAY_for_your_compiler
-#endif // defined(BASE_PORT_H_ALIGN_ATTRIBUTE)
+#endif  // !defined(CERES_ALIGN_ATTRIBUTE)
 
-#undef BASE_PORT_H_ALIGNTYPE_TEMPLATE
-#undef BASE_PORT_H_ALIGN_ATTRIBUTE
-
-#endif  // ALIGNED_CHAR_ARRAY
+#endif  // CERES_ALIGNED_CHAR_ARRAY
 
 template <typename Type>
 class ManualConstructor {
@@ -203,10 +192,10 @@ class ManualConstructor {
   }
 
  private:
-  ALIGNED_CHAR_ARRAY(Type, 1) space_;
+  CERES_ALIGNED_CHAR_ARRAY(Type, 1) space_;
 };
 
-#undef ALIGNED_CHAR_ARRAY
+#undef CERES_ALIGNED_CHAR_ARRAY
 
 }  // namespace internal
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/include/ceres/internal/port.h b/extern/libmv/third_party/ceres/include/ceres/internal/port.h
index 9a3e5cced58..a9fe247cef5 100644
--- a/extern/libmv/third_party/ceres/include/ceres/internal/port.h
+++ b/extern/libmv/third_party/ceres/include/ceres/internal/port.h
@@ -31,6 +31,8 @@
 #ifndef CERES_PUBLIC_INTERNAL_PORT_H_
 #define CERES_PUBLIC_INTERNAL_PORT_H_
 
+#include <string>
+
 namespace ceres {
 
 // It is unfortunate that this import of the entire standard namespace is
@@ -39,6 +41,10 @@ namespace ceres {
 // things outside of the Ceres optimization package.
 using namespace std;
 
+// This is necessary to properly handle the case that there is a different
+// "string" implementation in the global namespace.
+using std::string;
+
 }  // namespace ceres
 
 #endif  // CERES_PUBLIC_INTERNAL_PORT_H_
diff --git a/extern/libmv/third_party/ceres/include/ceres/iteration_callback.h b/extern/libmv/third_party/ceres/include/ceres/iteration_callback.h
index 88da992d0c5..29157d380f2 100644
--- a/extern/libmv/third_party/ceres/include/ceres/iteration_callback.h
+++ b/extern/libmv/third_party/ceres/include/ceres/iteration_callback.h
@@ -28,8 +28,9 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 //
-// When an iteration callback is specified, Ceres calls the callback after each
-// optimizer step and pass it an IterationSummary object, defined below.
+// When an iteration callback is specified, Ceres calls the callback
+// after each minimizer step (if the minimizer has not converged) and
+// passes it an IterationSummary object, defined below.
 
 #ifndef CERES_PUBLIC_ITERATION_CALLBACK_H_
 #define CERES_PUBLIC_ITERATION_CALLBACK_H_
@@ -44,7 +45,15 @@ struct IterationSummary {
   // Current iteration number.
   int32 iteration;
 
+  // Step was numerically valid, i.e., all values are finite and the
+  // step reduces the value of the linearized model.
+  //
+  // Note: step_is_valid is false when iteration = 0.
+  bool step_is_valid;
+
   // Whether or not the algorithm made progress in this iteration.
+  //
+  // Note: step_is_successful is false when iteration = 0.
   bool step_is_successful;
 
   // Value of the objective function.
@@ -66,9 +75,10 @@ struct IterationSummary {
   // cost and the change in the cost of the linearized approximation.
   double relative_decrease;
 
-  // Value of the regularization parameter for Levenberg-Marquardt
-  // algorithm at the end of the current iteration.
-  double mu;
+  // Size of the trust region at the end of the current iteration. For
+  // the Levenberg-Marquardt algorithm, the regularization parameter
+  // mu = 1.0 / trust_region_radius.
+  double trust_region_radius;
 
   // For the inexact step Levenberg-Marquardt algorithm, this is the
   // relative accuracy with which the Newton(LM) step is solved. This
@@ -81,13 +91,15 @@ struct IterationSummary {
   // Newton step.
   int linear_solver_iterations;
 
-  // TODO(sameeragarwal): Change to use a higher precision timer using
-  // clock_gettime.
-  // Time (in seconds) spent inside the linear least squares solver.
-  int iteration_time_sec;
+  // Time (in seconds) spent inside the minimizer loop in the current
+  // iteration.
+  double iteration_time_in_seconds;
+
+  // Time (in seconds) spent inside the trust region step solver.
+  double step_solver_time_in_seconds;
 
-  // Time (in seconds) spent inside the linear least squares solver.
-  int linear_solver_time_sec;
+  // Time (in seconds) since the user called Solve().
+  double cumulative_time_in_seconds;
 };
 
 // Interface for specifying callbacks that are executed at the end of
@@ -133,7 +145,7 @@ struct IterationSummary {
 //                                    summary.gradient_max_norm,
 //                                    summary.step_norm,
 //                                    summary.relative_decrease,
-//                                    summary.mu,
+//                                    summary.trust_region_radius,
 //                                    summary.eta,
 //                                    summary.linear_solver_iterations);
 //       if (log_to_stdout_) {
diff --git a/extern/libmv/third_party/ceres/include/ceres/jet.h b/extern/libmv/third_party/ceres/include/ceres/jet.h
index a37870210f1..96e2256fd02 100644
--- a/extern/libmv/third_party/ceres/include/ceres/jet.h
+++ b/extern/libmv/third_party/ceres/include/ceres/jet.h
@@ -162,16 +162,7 @@
 #include <string>
 
 #include "Eigen/Core"
-
-// Visual Studio 2012 or older version
-#if defined(_MSC_VER) && _MSC_VER <= 1700
-namespace std {
-inline bool isfinite(double x) { return _finite(x);                }
-inline bool isinf   (double x) { return !_finite(x) && !_isnan(x); }
-inline bool isnan   (double x) { return _isnan(x);                 }
-inline bool isnormal(double x) { return _finite(x) && x != 0.0;    }
-}  // namespace std
-#endif
+#include "ceres/fpclassify.h"
 
 namespace ceres {
 
@@ -184,7 +175,9 @@ struct Jet {
   // (where T is a Jet<T, N>). This usually only happens in opt mode. Note that
   // the C++ standard mandates that e.g. default constructed doubles are
   // initialized to 0.0; see sections 8.5 of the C++03 standard.
-  Jet() : a() {}
+  Jet() : a() {
+    v.setZero();
+  }
 
   // Constructor from scalar: a + 0.
   explicit Jet(const T& value) {
@@ -199,18 +192,6 @@ struct Jet {
     v[k] = T(1.0);
   }
 
-  /*
-
-  // Construct from an array where the first element is the scalar.
-  // This is templated to support converting from other data types.
-  template<typename D>
-  Jet(const D* scalar_and_derivatives) {
-    a = T(scalar_and_derivatives[0]);
-    v = Eigen::Map<const Eigen::Matrix<D, N, 1> >(
-        scalar_and_derivatives + 1, N).cast<T>();
-  }
-  */
-
   // Compound operators
   Jet<T, N>& operator+=(const Jet<T, N> &y) {
     *this = *this + y;
@@ -232,8 +213,25 @@ struct Jet {
     return *this;
   }
 
-  T a;  // The scalar part.
-  Eigen::Matrix<T, N, 1> v;  // The infinitesimal part.
+  // The scalar part.
+  T a;
+
+  // The infinitesimal part.
+  //
+  // Note the Eigen::DontAlign bit is needed here because this object
+  // gets allocated on the stack and as part of other arrays and
+  // structs. Forcing the right alignment there is the source of much
+  // pain and suffering. Even if that works, passing Jets around to
+  // functions by value has problems because the C++ ABI does not
+  // guarantee alignment for function arguments.
+  //
+  // Setting the DontAlign bit prevents Eigen from using SSE for the
+  // various operations on Jets. This is a small performance penalty
+  // since the AutoDiff code will still expose much of the code as
+  // statically sized loops to the compiler. But given the subtle
+  // issues that arise due to alignment, especially when dealing with
+  // multiple platforms, it seems to be a trade off worth making.
+  Eigen::Matrix<T, N, 1, Eigen::DontAlign> v;
 };
 
 // Unary +
@@ -411,10 +409,6 @@ inline double cos     (double x) { return std::cos(x);      }
 inline double acos    (double x) { return std::acos(x);     }
 inline double sin     (double x) { return std::sin(x);      }
 inline double asin    (double x) { return std::asin(x);     }
-inline bool   isfinite(double x) { return std::isfinite(x); }
-inline bool   isinf   (double x) { return std::isinf(x);    }
-inline bool   isnan   (double x) { return std::isnan(x);    }
-inline bool   isnormal(double x) { return std::isnormal(x); }
 inline double pow  (double x, double y) { return std::pow(x, y);   }
 inline double atan2(double y, double x) { return std::atan2(y, x); }
 
@@ -492,22 +486,23 @@ Jet<T, N> asin(const Jet<T, N>& f) {
 }
 
 // Jet Classification. It is not clear what the appropriate semantics are for
-// these classifications. This picks that isfinite and isnormal are "all"
-// operations, i.e. all elements of the jet must be finite for the jet itself to
-// be finite (or normal). For isnan and isinf, the answer is less clear. This
-// takes a "any" approach for isnan and isinf such that if any part of a jet is
-// nan or inf, then the entire jet is nan or inf. This leads to strange
-// situations like a jet can be both isinf and isnan, but in practice the "any"
-// semantics are the most useful for e.g. checking that derivatives are sane.
+// these classifications. This picks that IsFinite and isnormal are "all"
+// operations, i.e. all elements of the jet must be finite for the jet itself
+// to be finite (or normal). For IsNaN and IsInfinite, the answer is less
+// clear. This takes a "any" approach for IsNaN and IsInfinite such that if any
+// part of a jet is nan or inf, then the entire jet is nan or inf. This leads
+// to strange situations like a jet can be both IsInfinite and IsNaN, but in
+// practice the "any" semantics are the most useful for e.g. checking that
+// derivatives are sane.
 
 // The jet is finite if all parts of the jet are finite.
 template <typename T, int N> inline
-bool isfinite(const Jet<T, N>& f) {
-  if (!isfinite(f.a)) {
+bool IsFinite(const Jet<T, N>& f) {
+  if (!IsFinite(f.a)) {
     return false;
   }
   for (int i = 0; i < N; ++i) {
-    if (!isfinite(f.v[i])) {
+    if (!IsFinite(f.v[i])) {
       return false;
     }
   }
@@ -516,12 +511,12 @@ bool isfinite(const Jet<T, N>& f) {
 
 // The jet is infinite if any part of the jet is infinite.
 template <typename T, int N> inline
-bool isinf(const Jet<T, N>& f) {
-  if (isinf(f.a)) {
+bool IsInfinite(const Jet<T, N>& f) {
+  if (IsInfinite(f.a)) {
     return true;
   }
   for (int i = 0; i < N; i++) {
-    if (isinf(f.v[i])) {
+    if (IsInfinite(f.v[i])) {
       return true;
     }
   }
@@ -530,12 +525,12 @@ bool isinf(const Jet<T, N>& f) {
 
 // The jet is NaN if any part of the jet is NaN.
 template <typename T, int N> inline
-bool isnan(const Jet<T, N>& f) {
-  if (isnan(f.a)) {
+bool IsNaN(const Jet<T, N>& f) {
+  if (IsNaN(f.a)) {
     return true;
   }
   for (int i = 0; i < N; ++i) {
-    if (isnan(f.v[i])) {
+    if (IsNaN(f.v[i])) {
       return true;
     }
   }
@@ -544,12 +539,12 @@ bool isnan(const Jet<T, N>& f) {
 
 // The jet is normal if all parts of the jet are normal.
 template <typename T, int N> inline
-bool isnormal(const Jet<T, N>& f) {
-  if (!isnormal(f.a)) {
+bool IsNormal(const Jet<T, N>& f) {
+  if (!IsNormal(f.a)) {
     return false;
   }
   for (int i = 0; i < N; ++i) {
-    if (!isnormal(f.v[i])) {
+    if (!IsNormal(f.v[i])) {
       return false;
     }
   }
@@ -650,78 +645,6 @@ inline std::ostream &operator<<(std::ostream &s, const Jet<T, N>& z) {
   return s << "[" << z.a << " ; " << z.v.transpose() << "]";
 }
 
-// A jet traits class to make it easier to work with mixed auto / numeric diff.
-template<typename T>
-struct JetOps {
-  static bool IsScalar() {
-    return true;
-  }
-  static T GetScalar(const T& t) {
-    return t;
-  }
-  static void SetScalar(const T& scalar, T* t) {
-    *t = scalar;
-  }
-  static void ScaleDerivative(double scale_by, T *value) {
-    // For double, there is no derivative to scale.
-  }
-};
-
-template<typename T, int N>
-struct JetOps<Jet<T, N> > {
-  static bool IsScalar() {
-    return false;
-  }
-  static T GetScalar(const Jet<T, N>& t) {
-    return t.a;
-  }
-  static void SetScalar(const T& scalar, Jet<T, N>* t) {
-    t->a = scalar;
-  }
-  static void ScaleDerivative(double scale_by, Jet<T, N> *value) {
-    value->v *= scale_by;
-  }
-};
-
-template<typename FunctionType, int kNumArgs, typename ArgumentType>
-struct Chain {
-  static ArgumentType Rule(const FunctionType &f,
-                           const FunctionType dfdx[kNumArgs],
-                           const ArgumentType x[kNumArgs]) {
-    // In the default case of scalars, there's nothing to do since there are no
-    // derivatives to propagate. 
-    return f;
-  }
-};
-
-// XXX Add documentation here!
-template<typename FunctionType, int kNumArgs, typename T, int N>
-struct Chain<FunctionType, kNumArgs, Jet<T, N> > {
-  static Jet<T, N> Rule(const FunctionType &f,
-                        const FunctionType dfdx[kNumArgs],
-                        const Jet<T, N> x[kNumArgs]) {
-    // x is itself a function of another variable ("z"); what this function
-    // needs to return is "f", but with the derivative with respect to z
-    // attached to the jet. So combine the derivative part of x's jets to form
-    // a Jacobian matrix between x and z (i.e. dx/dz).
-    Eigen::Matrix<T, kNumArgs, N> dxdz;
-    for (int i = 0; i < kNumArgs; ++i) {
-      dxdz.row(i) = x[i].v.transpose();
-    }
-
-    // Map the input gradient dfdx into an Eigen row vector.
-    Eigen::Map<const Eigen::Matrix<FunctionType, 1, kNumArgs> >
-        vector_dfdx(dfdx, 1, kNumArgs);
-
-    // Now apply the chain rule to obtain df/dz. Combine the derivative with
-    // the scalar part to obtain f with full derivative information.
-    Jet<T, N> jet_f;
-    jet_f.a = f;
-    jet_f.v = vector_dfdx.template cast<T>() * dxdz;  // Also known as dfdz.
-    return jet_f;
-  }
-};
-
 }  // namespace ceres
 
 namespace Eigen {
diff --git a/extern/libmv/third_party/ceres/include/ceres/loss_function.h b/extern/libmv/third_party/ceres/include/ceres/loss_function.h
index 81add02cdee..0c0ceaaecd0 100644
--- a/extern/libmv/third_party/ceres/include/ceres/loss_function.h
+++ b/extern/libmv/third_party/ceres/include/ceres/loss_function.h
@@ -175,6 +175,7 @@ class HuberLoss : public LossFunction {
  public:
   explicit HuberLoss(double a) : a_(a), b_(a * a) { }
   virtual void Evaluate(double, double*) const;
+
  private:
   const double a_;
   // b = a^2.
@@ -190,6 +191,7 @@ class SoftLOneLoss : public LossFunction {
  public:
   explicit SoftLOneLoss(double a) : b_(a * a), c_(1 / b_) { }
   virtual void Evaluate(double, double*) const;
+
  private:
   // b = a^2.
   const double b_;
@@ -206,6 +208,7 @@ class CauchyLoss : public LossFunction {
  public:
   explicit CauchyLoss(double a) : b_(a * a), c_(1 / b_) { }
   virtual void Evaluate(double, double*) const;
+
  private:
   // b = a^2.
   const double b_;
@@ -213,6 +216,78 @@ class CauchyLoss : public LossFunction {
   const double c_;
 };
 
+// Loss that is capped beyond a certain level using the arc-tangent function.
+// The scaling parameter 'a' determines the level where falloff occurs.
+// For costs much smaller than 'a', the loss function is linear and behaves like
+// TrivialLoss, and for values much larger than 'a' the value asymptotically
+// approaches the constant value of a * PI / 2.
+//
+//   rho(s) = a atan(s / a).
+//
+// At s = 0: rho = [0, 1, 0].
+class ArctanLoss : public LossFunction {
+ public:
+  explicit ArctanLoss(double a) : a_(a), b_(1 / (a * a)) { }
+  virtual void Evaluate(double, double*) const;
+
+ private:
+  const double a_;
+  // b = 1 / a^2.
+  const double b_;
+};
+
+// Loss function that maps to approximately zero cost in a range around the
+// origin, and reverts to linear in error (quadratic in cost) beyond this range.
+// The tolerance parameter 'a' sets the nominal point at which the
+// transition occurs, and the transition size parameter 'b' sets the nominal
+// distance over which most of the transition occurs. Both a and b must be
+// greater than zero, and typically b will be set to a fraction of a.
+// The slope rho'[s] varies smoothly from about 0 at s <= a - b to
+// about 1 at s >= a + b.
+//
+// The term is computed as:
+//
+//   rho(s) = b log(1 + exp((s - a) / b)) - c0.
+//
+// where c0 is chosen so that rho(0) == 0
+//
+//   c0 = b log(1 + exp(-a / b)
+//
+// This has the following useful properties:
+//
+//   rho(s) == 0               for s = 0
+//   rho'(s) ~= 0              for s << a - b
+//   rho'(s) ~= 1              for s >> a + b
+//   rho''(s) > 0              for all s
+//
+// In addition, all derivatives are continuous, and the curvature is
+// concentrated in the range a - b to a + b.
+//
+// At s = 0: rho = [0, ~0, ~0].
+class TolerantLoss : public LossFunction {
+ public:
+  explicit TolerantLoss(double a, double b);
+  virtual void Evaluate(double, double*) const;
+
+ private:
+  const double a_, b_, c_;
+};
+
+// Composition of two loss functions.  The error is the result of first
+// evaluating g followed by f to yield the composition f(g(s)).
+// The loss functions must not be NULL.
+class ComposedLoss : public LossFunction {
+ public:
+  explicit ComposedLoss(const LossFunction* f, Ownership ownership_f,
+                        const LossFunction* g, Ownership ownership_g);
+  virtual ~ComposedLoss();
+  virtual void Evaluate(double, double*) const;
+
+ private:
+  internal::scoped_ptr<const LossFunction> f_, g_;
+  const Ownership ownership_f_, ownership_g_;
+};
+
 // The discussion above has to do with length scaling: it affects the space
 // in which s is measured. Sometimes you want to simply scale the output
 // value of the robustifier. For example, you might want to weight
@@ -249,7 +324,7 @@ class ScaledLoss : public LossFunction {
   internal::scoped_ptr<const LossFunction> rho_;
   const double a_;
   const Ownership ownership_;
-  DISALLOW_COPY_AND_ASSIGN(ScaledLoss);
+  CERES_DISALLOW_COPY_AND_ASSIGN(ScaledLoss);
 };
 
 // Sometimes after the optimization problem has been constructed, we
@@ -314,7 +389,7 @@ class LossFunctionWrapper : public LossFunction {
  private:
   internal::scoped_ptr<const LossFunction> rho_;
   Ownership ownership_;
-  DISALLOW_COPY_AND_ASSIGN(LossFunctionWrapper);
+  CERES_DISALLOW_COPY_AND_ASSIGN(LossFunctionWrapper);
 };
 
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/include/ceres/numeric_diff_cost_function.h b/extern/libmv/third_party/ceres/include/ceres/numeric_diff_cost_function.h
index bbaefca5b6c..8544e44d0bc 100644
--- a/extern/libmv/third_party/ceres/include/ceres/numeric_diff_cost_function.h
+++ b/extern/libmv/third_party/ceres/include/ceres/numeric_diff_cost_function.h
@@ -93,11 +93,13 @@ struct Differencer {
     using Eigen::Map;
     using Eigen::Matrix;
     using Eigen::RowMajor;
+    using Eigen::ColMajor;
 
     typedef Matrix<double, num_residuals, 1> ResidualVector;
     typedef Matrix<double, parameter_block_size, 1> ParameterVector;
-    typedef Matrix<double, num_residuals, parameter_block_size, RowMajor>
-        JacobianMatrix;
+    typedef Matrix<double, num_residuals, parameter_block_size,
+                   (parameter_block_size == 1 &&
+                    num_residuals > 1) ? ColMajor : RowMajor> JacobianMatrix;
 
     Map<JacobianMatrix> parameter_jacobian(jacobians[parameter_block],
                                            num_residuals,
diff --git a/extern/libmv/third_party/ceres/include/ceres/problem.h b/extern/libmv/third_party/ceres/include/ceres/problem.h
index 0ca61006bdb..2b08c6723e8 100644
--- a/extern/libmv/third_party/ceres/include/ceres/problem.h
+++ b/extern/libmv/third_party/ceres/include/ceres/problem.h
@@ -50,13 +50,13 @@ namespace ceres {
 class CostFunction;
 class LossFunction;
 class LocalParameterization;
+class Solver;
 
 namespace internal {
 class Preprocessor;
 class ProblemImpl;
 class ParameterBlock;
 class ResidualBlock;
-class SolverImpl;
 }  // namespace internal
 
 // A ResidualBlockId is a handle clients can use to delete residual
@@ -255,9 +255,9 @@ class Problem {
   int NumResiduals() const;
 
  private:
-  friend class internal::SolverImpl;
+  friend class Solver;
   internal::scoped_ptr<internal::ProblemImpl> problem_impl_;
-  DISALLOW_COPY_AND_ASSIGN(Problem);
+  CERES_DISALLOW_COPY_AND_ASSIGN(Problem);
 };
 
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/include/ceres/rotation.h b/extern/libmv/third_party/ceres/include/ceres/rotation.h
index e4227e78b9a..0d8a390d5d1 100644
--- a/extern/libmv/third_party/ceres/include/ceres/rotation.h
+++ b/extern/libmv/third_party/ceres/include/ceres/rotation.h
@@ -47,6 +47,7 @@
 
 #include <algorithm>
 #include <cmath>
+#include "glog/logging.h"
 
 namespace ceres {
 
@@ -145,18 +146,11 @@ void AngleAxisRotatePoint(const T angle_axis[3], const T pt[3], T result[3]);
 
 // --- IMPLEMENTATION
 
-// Duplicate rather than decorate every use of cmath with _USE_MATH_CONSTANTS.
-// Necessitated by Windows.
-#ifndef M_PI
-#define M_PI 3.14159265358979323846
-#define CERES_NEED_M_PI_UNDEF
-#endif
-
 template<typename T>
 inline void AngleAxisToQuaternion(const T* angle_axis, T* quaternion) {
-  const T &a0 = angle_axis[0];
-  const T &a1 = angle_axis[1];
-  const T &a2 = angle_axis[2];
+  const T& a0 = angle_axis[0];
+  const T& a1 = angle_axis[1];
+  const T& a2 = angle_axis[2];
   const T theta_squared = a0 * a0 + a1 * a1 + a2 * a2;
 
   // For points not at the origin, the full conversion is numerically stable.
@@ -183,16 +177,35 @@ inline void AngleAxisToQuaternion(const T* angle_axis, T* quaternion) {
 
 template<typename T>
 inline void QuaternionToAngleAxis(const T* quaternion, T* angle_axis) {
-  const T &q1 = quaternion[1];
-  const T &q2 = quaternion[2];
-  const T &q3 = quaternion[3];
-  const T sin_squared = q1 * q1 + q2 * q2 + q3 * q3;
+  const T& q1 = quaternion[1];
+  const T& q2 = quaternion[2];
+  const T& q3 = quaternion[3];
+  const T sin_squared_theta = q1 * q1 + q2 * q2 + q3 * q3;
 
   // For quaternions representing non-zero rotation, the conversion
   // is numerically stable.
-  if (sin_squared > T(0.0)) {
-    const T sin_theta = sqrt(sin_squared);
-    const T k = T(2.0) * atan2(sin_theta, quaternion[0]) / sin_theta;
+  if (sin_squared_theta > T(0.0)) {
+    const T sin_theta = sqrt(sin_squared_theta);
+    const T& cos_theta = quaternion[0];
+
+    // If cos_theta is negative, theta is greater than pi/2, which
+    // means that angle for the angle_axis vector which is 2 * theta
+    // would be greater than pi.
+    //
+    // While this will result in the correct rotation, it does not
+    // result in a normalized angle-axis vector.
+    //
+    // In that case we observe that 2 * theta ~ 2 * theta - 2 * pi,
+    // which is equivalent saying
+    //
+    //   theta - pi = atan(sin(theta - pi), cos(theta - pi))
+    //              = atan(-sin(theta), -cos(theta))
+    //
+    const T two_theta =
+        T(2.0) * ((cos_theta < 0.0)
+                  ? atan2(-sin_theta, -cos_theta)
+                  : atan2(sin_theta, cos_theta));
+    const T k = two_theta / sin_theta;
     angle_axis[0] = q1 * k;
     angle_axis[1] = q2 * k;
     angle_axis[2] = q3 * k;
@@ -259,7 +272,7 @@ inline void RotationMatrixToAngleAxis(const T * R, T * angle_axis) {
 
   // Case 2: theta ~ 0, means sin(theta) ~ theta to a good
   // approximation.
-  if (costheta > 0) {
+  if (costheta > 0.0) {
     const T kHalf = T(0.5);
     for (int i = 0; i < 3; ++i) {
       angle_axis[i] *= kHalf;
@@ -284,8 +297,8 @@ inline void RotationMatrixToAngleAxis(const T * R, T * angle_axis) {
   // angle_axis[i] should be positive, otherwise negative.
   for (int i = 0; i < 3; ++i) {
     angle_axis[i] = theta * sqrt((R[i*4] - costheta) * inv_one_minus_costheta);
-    if (((sintheta < 0) && (angle_axis[i] > 0)) ||
-        ((sintheta > 0) && (angle_axis[i] < 0))) {
+    if (((sintheta < 0.0) && (angle_axis[i] > 0.0)) ||
+        ((sintheta > 0.0) && (angle_axis[i] < 0.0))) {
       angle_axis[i] = -angle_axis[i];
     }
   }
@@ -334,7 +347,8 @@ template <typename T>
 inline void EulerAnglesToRotationMatrix(const T* euler,
                                         const int row_stride,
                                         T* R) {
-  const T degrees_to_radians(M_PI / 180.0);
+  const double kPi = 3.14159265358979323846;
+  const T degrees_to_radians(kPi / 180.0);
 
   const T pitch(euler[0] * degrees_to_radians);
   const T roll(euler[1] * degrees_to_radians);
@@ -517,10 +531,4 @@ void AngleAxisRotatePoint(const T angle_axis[3], const T pt[3], T result[3]) {
 
 }  // namespace ceres
 
-// Clean define pollution.
-#ifdef CERES_NEED_M_PI_UNDEF
-#undef CERES_NEED_M_PI_UNDEF
-#undef M_PI
-#endif
-
 #endif  // CERES_PUBLIC_ROTATION_H_
diff --git a/extern/libmv/third_party/ceres/include/ceres/solver.h b/extern/libmv/third_party/ceres/include/ceres/solver.h
index bd669272023..31d5e8d7987 100644
--- a/extern/libmv/third_party/ceres/include/ceres/solver.h
+++ b/extern/libmv/third_party/ceres/include/ceres/solver.h
@@ -34,10 +34,10 @@
 #include <cmath>
 #include <string>
 #include <vector>
-
-#include "ceres/iteration_callback.h"
+#include "ceres/crs_matrix.h"
 #include "ceres/internal/macros.h"
 #include "ceres/internal/port.h"
+#include "ceres/iteration_callback.h"
 #include "ceres/types.h"
 
 namespace ceres {
@@ -57,24 +57,47 @@ class Solver {
   struct Options {
     // Default constructor that sets up a generic sparse problem.
     Options() {
-      minimizer_type = LEVENBERG_MARQUARDT;
+      trust_region_strategy_type = LEVENBERG_MARQUARDT;
+      dogleg_type = TRADITIONAL_DOGLEG;
+      use_nonmonotonic_steps = false;
+      max_consecutive_nonmonotonic_steps = 5;
       max_num_iterations = 50;
-      max_solver_time_sec = 1.0e9;
+      max_solver_time_in_seconds = 1e9;
       num_threads = 1;
-      tau = 1e-4;
+      initial_trust_region_radius = 1e4;
+      max_trust_region_radius = 1e16;
+      min_trust_region_radius = 1e-32;
       min_relative_decrease = 1e-3;
+      lm_min_diagonal = 1e-6;
+      lm_max_diagonal = 1e32;
+      max_num_consecutive_invalid_steps = 5;
       function_tolerance = 1e-6;
       gradient_tolerance = 1e-10;
       parameter_tolerance = 1e-8;
-#ifndef CERES_NO_SUITESPARSE
-      linear_solver_type = SPARSE_NORMAL_CHOLESKY;
-#else
+
+#if defined(CERES_NO_SUITESPARSE) && defined(CERES_NO_CXSPARSE)
       linear_solver_type = DENSE_QR;
-#endif  // CERES_NO_SUITESPARSE
+#else
+      linear_solver_type = SPARSE_NORMAL_CHOLESKY;
+#endif
+
       preconditioner_type = JACOBI;
+
+      sparse_linear_algebra_library = SUITE_SPARSE;
+#if defined(CERES_NO_SUITESPARSE) && !defined(CERES_NO_CXSPARSE)
+      sparse_linear_algebra_library = CX_SPARSE;
+#endif
+
       num_linear_solver_threads = 1;
       num_eliminate_blocks = 0;
       ordering_type = NATURAL;
+
+#if defined(CERES_NO_SUITESPARSE)
+      use_block_amd = false;
+#else
+      use_block_amd = true;
+#endif
+
       linear_solver_min_num_iterations = 1;
       linear_solver_max_num_iterations = 500;
       eta = 1e-1;
@@ -82,10 +105,13 @@ class Solver {
       logging_type = PER_MINIMIZER_ITERATION;
       minimizer_progress_to_stdout = false;
       return_initial_residuals = false;
+      return_initial_gradient = false;
+      return_initial_jacobian = false;
       return_final_residuals = false;
+      return_final_gradient = false;
+      return_final_jacobian = false;
       lsqp_dump_directory = "/tmp";
       lsqp_dump_format_type = TEXTFILE;
-      crash_and_dump_lsqp_on_failure = false;
       check_gradients = false;
       gradient_check_relative_precision = 1e-8;
       numeric_derivative_relative_step_size = 1e-6;
@@ -94,27 +120,78 @@ class Solver {
 
     // Minimizer options ----------------------------------------
 
-    MinimizerType minimizer_type;
+    TrustRegionStrategyType trust_region_strategy_type;
+
+    // Type of dogleg strategy to use.
+    DoglegType dogleg_type;
+
+    // The classical trust region methods are descent methods, in that
+    // they only accept a point if it strictly reduces the value of
+    // the objective function.
+    //
+    // Relaxing this requirement allows the algorithm to be more
+    // efficient in the long term at the cost of some local increase
+    // in the value of the objective function.
+    //
+    // This is because allowing for non-decreasing objective function
+    // values in a princpled manner allows the algorithm to "jump over
+    // boulders" as the method is not restricted to move into narrow
+    // valleys while preserving its convergence properties.
+    //
+    // Setting use_nonmonotonic_steps to true enables the
+    // non-monotonic trust region algorithm as described by Conn,
+    // Gould & Toint in "Trust Region Methods", Section 10.1.
+    //
+    // The parameter max_consecutive_nonmonotonic_steps controls the
+    // window size used by the step selection algorithm to accept
+    // non-monotonic steps.
+    //
+    // Even though the value of the objective function may be larger
+    // than the minimum value encountered over the course of the
+    // optimization, the final parameters returned to the user are the
+    // ones corresponding to the minimum cost over all iterations.
+    bool use_nonmonotonic_steps;
+    int max_consecutive_nonmonotonic_steps;
 
     // Maximum number of iterations for the minimizer to run for.
     int max_num_iterations;
 
     // Maximum time for which the minimizer should run for.
-    double max_solver_time_sec;
+    double max_solver_time_in_seconds;
 
     // Number of threads used by Ceres for evaluating the cost and
     // jacobians.
     int num_threads;
 
-    // For Levenberg-Marquardt, the initial value for the
-    // regularizer. This is the inversely related to the size of the
-    // initial trust region.
-    double tau;
+    // Trust region minimizer settings.
+    double initial_trust_region_radius;
+    double max_trust_region_radius;
+
+    // Minimizer terminates when the trust region radius becomes
+    // smaller than this value.
+    double min_trust_region_radius;
 
-    // For trust region methods, this is lower threshold for the
-    // relative decrease before a step is accepted.
+    // Lower bound for the relative decrease before a step is
+    // accepted.
     double min_relative_decrease;
 
+    // For the Levenberg-Marquadt algorithm, the scaled diagonal of
+    // the normal equations J'J is used to control the size of the
+    // trust region. Extremely small and large values along the
+    // diagonal can make this regularization scheme
+    // fail. lm_max_diagonal and lm_min_diagonal, clamp the values of
+    // diag(J'J) from above and below. In the normal course of
+    // operation, the user should not have to modify these parameters.
+    double lm_min_diagonal;
+    double lm_max_diagonal;
+
+    // Sometimes due to numerical conditioning problems or linear
+    // solver flakiness, the trust region strategy may return a
+    // numerically invalid step that can be fixed by reducing the
+    // trust region size. So the TrustRegionMinimizer allows for a few
+    // successive invalid steps before it declares NUMERICAL_FAILURE.
+    int max_num_consecutive_invalid_steps;
+
     // Minimizer terminates when
     //
     //   (new_cost - old_cost) < function_tolerance * old_cost;
@@ -141,6 +218,12 @@ class Solver {
     // Type of preconditioner to use with the iterative linear solvers.
     PreconditionerType preconditioner_type;
 
+    // Ceres supports using multiple sparse linear algebra libraries
+    // for sparse matrix ordering and factorizations. Currently,
+    // SUITE_SPARSE and CX_SPARSE are the valid choices, depending on
+    // whether they are linked into Ceres at build time.
+    SparseLinearAlgebraLibraryType sparse_linear_algebra_library;
+
     // Number of threads used by Ceres to solve the Newton
     // step. Currently only the SPARSE_SCHUR solver is capable of
     // using this setting.
@@ -170,6 +253,19 @@ class Solver {
     // non-empty.
     vector<double*> ordering;
 
+    // By virtue of the modeling layer in Ceres being block oriented,
+    // all the matrices used by Ceres are also block oriented. When
+    // doing sparse direct factorization of these matrices (for
+    // SPARSE_NORMAL_CHOLESKY, SPARSE_SCHUR and ITERATIVE in
+    // conjunction with CLUSTER_TRIDIAGONAL AND CLUSTER_JACOBI
+    // preconditioners), the fill-reducing ordering algorithms can
+    // either be run on the block or the scalar form of these matrices.
+    // Running it on the block form exposes more of the super-nodal
+    // structure of the matrix to the factorization routines. Setting
+    // this parameter to true runs the ordering algorithms in block
+    // form. Currently this option only makes sense with
+    // sparse_linear_algebra_library = SUITE_SPARSE.
+    bool use_block_amd;
 
     // Minimum number of iterations for which the linear solver should
     // run, even if the convergence criterion is satisfied.
@@ -206,7 +302,12 @@ class Solver {
     bool minimizer_progress_to_stdout;
 
     bool return_initial_residuals;
+    bool return_initial_gradient;
+    bool return_initial_jacobian;
+
     bool return_final_residuals;
+    bool return_final_gradient;
+    bool return_final_jacobian;
 
     // List of iterations at which the optimizer should dump the
     // linear least squares problem to disk. Useful for testing and
@@ -217,15 +318,6 @@ class Solver {
     string lsqp_dump_directory;
     DumpFormatType lsqp_dump_format_type;
 
-    // Dump the linear least squares problem to disk if the minimizer
-    // fails due to NUMERICAL_FAILURE and crash the process. This flag
-    // is useful for generating debugging information. The problem is
-    // dumped in a file whose name is determined by
-    // Solver::Options::lsqp_dump_format.
-    //
-    // Note: This requires a version of Ceres built with protocol buffers.
-    bool crash_and_dump_lsqp_on_failure;
-
     // Finite differences options ----------------------------------------------
 
     // Check all jacobians computed by each residual block with finite
@@ -273,16 +365,25 @@ class Solver {
     bool update_state_every_iteration;
 
     // Callbacks that are executed at the end of each iteration of the
-    // Minimizer. They are executed in the order that they are
-    // specified in this vector. By default, parameter blocks are
-    // updated only at the end of the optimization, i.e when the
-    // Minimizer terminates. This behaviour is controlled by
+    // Minimizer. An iteration may terminate midway, either due to
+    // numerical failures or because one of the convergence tests has
+    // been satisfied. In this case none of the callbacks are
+    // executed.
+
+    // Callbacks are executed in the order that they are specified in
+    // this vector. By default, parameter blocks are updated only at
+    // the end of the optimization, i.e when the Minimizer
+    // terminates. This behaviour is controlled by
     // update_state_every_variable. If the user wishes to have access
     // to the update parameter blocks when his/her callbacks are
     // executed, then set update_state_every_iteration to true.
     //
     // The solver does NOT take ownership of these pointers.
     vector<IterationCallback*> callbacks;
+
+    // If non-empty, a summary of the execution of the solver is
+    // recorded to this file.
+    string solver_log;
   };
 
   struct Summary {
@@ -313,20 +414,74 @@ class Solver {
     // blocks that they depend on were fixed.
     double fixed_cost;
 
-    // Residuals before and after the optimization. Each vector
-    // contains problem.NumResiduals() elements. Residuals are in the
-    // same order in which they were added to the problem object when
-    // constructing this problem.
+    // Vectors of residuals before and after the optimization. The
+    // entries of these vectors are in the order in which
+    // ResidualBlocks were added to the Problem object.
+    //
+    // Whether the residual vectors are populated with values is
+    // controlled by Solver::Options::return_initial_residuals and
+    // Solver::Options::return_final_residuals respectively.
     vector<double> initial_residuals;
     vector<double> final_residuals;
 
+    // Gradient vectors, before and after the optimization.  The rows
+    // are in the same order in which the ParameterBlocks were added
+    // to the Problem object.
+    //
+    // NOTE: Since AddResidualBlock adds ParameterBlocks to the
+    // Problem automatically if they do not already exist, if you wish
+    // to have explicit control over the ordering of the vectors, then
+    // use Problem::AddParameterBlock to explicitly add the
+    // ParameterBlocks in the order desired.
+    //
+    // Whether the vectors are populated with values is controlled by
+    // Solver::Options::return_initial_gradient and
+    // Solver::Options::return_final_gradient respectively.
+    vector<double> initial_gradient;
+    vector<double> final_gradient;
+
+    // Jacobian matrices before and after the optimization. The rows
+    // of these matrices are in the same order in which the
+    // ResidualBlocks were added to the Problem object. The columns
+    // are in the same order in which the ParameterBlocks were added
+    // to the Problem object.
+    //
+    // NOTE: Since AddResidualBlock adds ParameterBlocks to the
+    // Problem automatically if they do not already exist, if you wish
+    // to have explicit control over the column ordering of the
+    // matrix, then use Problem::AddParameterBlock to explicitly add
+    // the ParameterBlocks in the order desired.
+    //
+    // The Jacobian matrices are stored as compressed row sparse
+    // matrices. Please see ceres/crs_matrix.h for more details of the
+    // format.
+    //
+    // Whether the Jacboan matrices are populated with values is
+    // controlled by Solver::Options::return_initial_jacobian and
+    // Solver::Options::return_final_jacobian respectively.
+    CRSMatrix initial_jacobian;
+    CRSMatrix final_jacobian;
+
     vector<IterationSummary> iterations;
 
     int num_successful_steps;
     int num_unsuccessful_steps;
 
+    // When the user calls Solve, before the actual optimization
+    // occurs, Ceres performs a number of preprocessing steps. These
+    // include error checks, memory allocations, and reorderings. This
+    // time is accounted for as preprocessing time.
     double preprocessor_time_in_seconds;
+
+    // Time spent in the TrustRegionMinimizer.
     double minimizer_time_in_seconds;
+
+    // After the Minimizer is finished, some time is spent in
+    // re-evaluating residuals etc. This time is accounted for in the
+    // postprocessor time.
+    double postprocessor_time_in_seconds;
+
+    // Some total of all time spent inside Ceres when Solve is called.
     double total_time_in_seconds;
 
     // Preprocessor summary.
@@ -354,6 +509,10 @@ class Solver {
 
     PreconditionerType preconditioner_type;
     OrderingType ordering_type;
+
+    TrustRegionStrategyType trust_region_strategy_type;
+    DoglegType dogleg_type;
+    SparseLinearAlgebraLibraryType sparse_linear_algebra_library;
   };
 
   // Once a least squares problem has been built, this function takes
diff --git a/extern/libmv/third_party/ceres/include/ceres/types.h b/extern/libmv/third_party/ceres/include/ceres/types.h
index a30c79029ac..3980885b53c 100644
--- a/extern/libmv/third_party/ceres/include/ceres/types.h
+++ b/extern/libmv/third_party/ceres/include/ceres/types.h
@@ -59,14 +59,18 @@ enum LinearSolverType {
   // normal equations A'A x = A'b. They are direct solvers and do not
   // assume any special problem structure.
 
-  // Solve the normal equations using a sparse cholesky solver; based
-  // on CHOLMOD.
-  SPARSE_NORMAL_CHOLESKY,
+  // Solve the normal equations using a dense Cholesky solver; based
+  // on Eigen.
+  DENSE_NORMAL_CHOLESKY,
 
   // Solve the normal equations using a dense QR solver; based on
   // Eigen.
   DENSE_QR,
 
+  // Solve the normal equations using a sparse cholesky solver; requires
+  // SuiteSparse or CXSparse.
+  SPARSE_NORMAL_CHOLESKY,
+
   // Specialized solvers, specific to problems with a generalized
   // bi-partitite structure.
 
@@ -110,6 +114,15 @@ enum PreconditionerType {
   CLUSTER_TRIDIAGONAL
 };
 
+enum SparseLinearAlgebraLibraryType {
+  // High performance sparse Cholesky factorization and approximate
+  // minimum degree ordering.
+  SUITE_SPARSE,
+
+  // A lightweight replacment for SuiteSparse.
+  CX_SPARSE
+};
+
 enum LinearSolverTerminationType {
   // Termination criterion was met. For factorization based solvers
   // the tolerance is assumed to be zero. Any user provided values are
@@ -149,8 +162,47 @@ enum LoggingType {
   PER_MINIMIZER_ITERATION
 };
 
-enum MinimizerType {
-  LEVENBERG_MARQUARDT
+// Ceres supports different strategies for computing the trust region
+// step.
+enum TrustRegionStrategyType {
+  // The default trust region strategy is to use the step computation
+  // used in the Levenberg-Marquardt algorithm. For more details see
+  // levenberg_marquardt_strategy.h
+  LEVENBERG_MARQUARDT,
+
+  // Powell's dogleg algorithm interpolates between the Cauchy point
+  // and the Gauss-Newton step. It is particularly useful if the
+  // LEVENBERG_MARQUARDT algorithm is making a large number of
+  // unsuccessful steps. For more details see dogleg_strategy.h.
+  //
+  // NOTES:
+  //
+  // 1. This strategy has not been experimented with or tested as
+  // extensively as LEVENBERG_MARQUARDT, and therefore it should be
+  // considered EXPERIMENTAL for now.
+  //
+  // 2. For now this strategy should only be used with exact
+  // factorization based linear solvers, i.e., SPARSE_SCHUR,
+  // DENSE_SCHUR, DENSE_QR and SPARSE_NORMAL_CHOLESKY.
+  DOGLEG
+};
+
+// Ceres supports two different dogleg strategies.
+// The "traditional" dogleg method by Powell and the
+// "subspace" method described in
+// R. H. Byrd, R. B. Schnabel, and G. A. Shultz,
+// "Approximate solution of the trust region problem by minimization
+//  over two-dimensional subspaces", Mathematical Programming,
+// 40 (1988), pp. 247--263
+enum DoglegType {
+  // The traditional approach constructs a dogleg path
+  // consisting of two line segments and finds the furthest
+  // point on that path that is still inside the trust region.
+  TRADITIONAL_DOGLEG,
+
+  // The subspace approach finds the exact minimum of the model
+  // constrained to the subspace spanned by the dogleg path.
+  SUBSPACE_DOGLEG
 };
 
 enum SolverTerminationType {
@@ -246,11 +298,15 @@ enum DimensionType {
 
 const char* LinearSolverTypeToString(LinearSolverType type);
 const char* PreconditionerTypeToString(PreconditionerType type);
+const char* SparseLinearAlgebraLibraryTypeToString(
+    SparseLinearAlgebraLibraryType type);
 const char* LinearSolverTerminationTypeToString(
     LinearSolverTerminationType type);
 const char* OrderingTypeToString(OrderingType type);
 const char* SolverTerminationTypeToString(SolverTerminationType type);
-
+const char* SparseLinearAlgebraLibraryTypeToString(
+    SparseLinearAlgebraLibraryType type);
+const char* TrustRegionStrategyTypeToString( TrustRegionStrategyType type);
 bool IsSchurType(LinearSolverType type);
 
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt.h b/extern/libmv/third_party/ceres/internal/ceres/array_utils.cc
index d00bb9095be..673baa4f70f 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/array_utils.cc
@@ -1,5 +1,5 @@
 // Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
+// Copyright 2012 Google Inc. All rights reserved.
 // http://code.google.com/p/ceres-solver/
 //
 // Redistribution and use in source and binary forms, with or without
@@ -27,39 +27,41 @@
 // POSSIBILITY OF SUCH DAMAGE.
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
-//
-// Implmentation of Levenberg Marquardt algorithm based on "Methods for
-// Nonlinear Least Squares" by K. Madsen, H.B. Nielsen and
-// O. Tingleff. Available to download from
-//
-// http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf
-//
 
-#ifndef CERES_INTERNAL_LEVENBERG_MARQUARDT_H_
-#define CERES_INTERNAL_LEVENBERG_MARQUARDT_H_
+#include "ceres/array_utils.h"
 
-#include "ceres/minimizer.h"
-#include "ceres/solver.h"
+#include <cmath>
+#include <cstddef>
+#include "ceres/fpclassify.h"
 
 namespace ceres {
 namespace internal {
 
-class Evaluator;
-class LinearSolver;
+// It is a near impossibility that user code generates this exact
+// value in normal operation, thus we will use it to fill arrays
+// before passing them to user code. If on return an element of the
+// array still contains this value, we will assume that the user code
+// did not write to that memory location.
+const double kImpossibleValue = 1e302;
 
-class LevenbergMarquardt : public Minimizer {
- public:
-  virtual ~LevenbergMarquardt();
+bool IsArrayValid(const int size, const double* x) {
+  if (x != NULL) {
+    for (int i = 0; i < size; ++i) {
+      if (!IsFinite(x[i]) || (x[i] == kImpossibleValue))  {
+        return false;
+      }
+    }
+  }
+  return true;
+}
 
-  virtual void Minimize(const Minimizer::Options& options,
-                        Evaluator* evaluator,
-                        LinearSolver* linear_solver,
-                        const double* initial_parameters,
-                        double* final_parameters,
-                        Solver::Summary* summary);
-};
+void InvalidateArray(const int size, double* x) {
+  if (x != NULL) {
+    for (int i = 0; i < size; ++i) {
+      x[i] = kImpossibleValue;
+    }
+  }
+}
 
 }  // namespace internal
 }  // namespace ceres
-
-#endif  // CERES_INTERNAL_LEVENBERG_MARQUARDT_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/array_utils.h b/extern/libmv/third_party/ceres/internal/ceres/array_utils.h
new file mode 100644
index 00000000000..99cc8d8ebbf
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/array_utils.h
@@ -0,0 +1,65 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+//
+// Utility routines for validating arrays. 
+//
+// These are useful for detecting two common class of errors.
+//
+// 1. Uninitialized memory - where the user for some reason did not
+// compute part of an array, but the code expects it.
+//
+// 2. Numerical failure while computing the cost/residual/jacobian,
+// e.g. NaN, infinities etc. This is particularly useful since the
+// automatic differentiation code does computations that are not
+// evident to the user and can silently generate hard to debug errors.
+
+#ifndef CERES_INTERNAL_ARRAY_UTILS_H_
+#define CERES_INTERNAL_ARRAY_UTILS_H_
+
+#include "ceres/internal/port.h"
+
+namespace ceres {
+namespace internal {
+
+// Fill the array x with an impossible value that the user code is
+// never expected to compute.
+void InvalidateArray(int size, double* x);
+
+// Check if all the entries of the array x are valid, i.e. all the
+// values in the array should be finite and none of them should be
+// equal to the "impossible" value used by InvalidateArray.
+bool IsArrayValid(int size, const double* x);
+
+extern const double kImpossibleValue;
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_ARRAY_UTILS_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.cc b/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.cc
index 05e63eb560b..9edc4fa23bd 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.cc
@@ -40,16 +40,26 @@
 namespace ceres {
 namespace internal {
 
-void BlockEvaluatePreparer::Init(int** jacobian_layout) {
+void BlockEvaluatePreparer::Init(int const* const* jacobian_layout,
+                                 int max_derivatives_per_residual_block) {
   jacobian_layout_ = jacobian_layout;
+  scratch_evaluate_preparer_.Init(max_derivatives_per_residual_block);
 }
 
 // Point the jacobian blocks directly into the block sparse matrix.
 void BlockEvaluatePreparer::Prepare(const ResidualBlock* residual_block,
                                     int residual_block_index,
                                     SparseMatrix* jacobian,
-                                    double** jacobians) const {
-  CHECK(jacobian != NULL);
+                                    double** jacobians) {
+  // If the overall jacobian is not available, use the scratch space.
+  if (jacobian == NULL) {
+    scratch_evaluate_preparer_.Prepare(residual_block,
+                                       residual_block_index,
+                                       jacobian,
+                                       jacobians);
+    return;
+  }
+
   double* jacobian_values =
       down_cast<BlockSparseMatrix*>(jacobian)->mutable_values();
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.h b/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.h
index a7869311e6e..354acc031f4 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_evaluate_preparer.h
@@ -36,6 +36,8 @@
 #ifndef CERES_INTERNAL_BLOCK_EVALUATE_PREPARER_H_
 #define CERES_INTERNAL_BLOCK_EVALUATE_PREPARER_H_
 
+#include "ceres/scratch_evaluate_preparer.h"
+
 namespace ceres {
 namespace internal {
 
@@ -47,18 +49,26 @@ class BlockEvaluatePreparer {
   // Using Init() instead of a constructor allows for allocating this structure
   // with new[]. This is because C++ doesn't allow passing arguments to objects
   // constructed with new[] (as opposed to plain 'new').
-  void Init(int** jacobian_layout);
+  void Init(int const* const* jacobian_layout,
+            int max_derivatives_per_residual_block);
 
   // EvaluatePreparer interface
 
-  // Point the jacobian blocks directly into the block sparse matrix.
+  // Point the jacobian blocks directly into the block sparse matrix, if
+  // jacobian is non-null. Otherwise, uses an internal per-thread buffer to
+  // store the jacobians temporarily.
   void Prepare(const ResidualBlock* residual_block,
                int residual_block_index,
                SparseMatrix* jacobian,
-               double** jacobians) const;
+               double** jacobians);
 
  private:
   int const* const* jacobian_layout_;
+
+  // For the case that the overall jacobian is not available, but the
+  // individual jacobians are requested, use a pass-through scratch evaluate
+  // preparer.
+  ScratchEvaluatePreparer scratch_evaluate_preparer_;
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.cc b/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.cc
index 1a5001f9c71..474c37f7ca4 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_jacobi_preconditioner.cc
@@ -40,11 +40,10 @@
 namespace ceres {
 namespace internal {
 
-BlockJacobiPreconditioner::BlockJacobiPreconditioner(
-    const LinearOperator& A)
-    : block_structure_(
-        *(down_cast<const BlockSparseMatrix*>(&A)->block_structure())),
-      num_rows_(A.num_rows()) {
+BlockJacobiPreconditioner::BlockJacobiPreconditioner(const LinearOperator& A)
+    : num_rows_(A.num_rows()),
+      block_structure_(
+        *(down_cast<const BlockSparseMatrix*>(&A)->block_structure())) {
   // Calculate the amount of storage needed.
   int storage_needed = 0;
   for (int c = 0; c < block_structure_.cols.size(); ++c) {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.cc b/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.cc
index 52a58bb43a6..f90c350cc80 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_jacobian_writer.cc
@@ -136,9 +136,12 @@ BlockJacobianWriter::BlockJacobianWriter(const Evaluator::Options& options,
 // makes the final Write() a nop.
 BlockEvaluatePreparer* BlockJacobianWriter::CreateEvaluatePreparers(
     int num_threads) {
+  int max_derivatives_per_residual_block =
+      program_->MaxDerivativesPerResidualBlock();
+
   BlockEvaluatePreparer* preparers = new BlockEvaluatePreparer[num_threads];
   for (int i = 0; i < num_threads; i++) {
-    preparers[i].Init(&jacobian_layout_[0]);
+    preparers[i].Init(&jacobian_layout_[0], max_derivatives_per_residual_block);
   }
   return preparers;
 }
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.cc
index 2afaf5e2ea2..0f95e8932b8 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.cc
@@ -28,10 +28,10 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 
+#include "glog/logging.h"
 #include "ceres/block_random_access_dense_matrix.h"
 
 #include <vector>
-#include <glog/logging.h>
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/scoped_ptr.h"
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.h
index 3a0096209f7..9f27a4c30f3 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_dense_matrix.h
@@ -89,7 +89,7 @@ class BlockRandomAccessDenseMatrix : public BlockRandomAccessMatrix {
   vector<int> block_layout_;
   scoped_array<double> values_;
 
-  DISALLOW_COPY_AND_ASSIGN(BlockRandomAccessDenseMatrix);
+  CERES_DISALLOW_COPY_AND_ASSIGN(BlockRandomAccessDenseMatrix);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.h
index f398af3be87..b76cb78b160 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_matrix.h
@@ -77,7 +77,7 @@ namespace internal {
 //
 //  if (cell != NULL) {
 //     MatrixRef m(cell->values, row_stride, col_stride);
-//     MutexLock l(&cell->m);
+//     CeresMutexLock l(&cell->m);
 //     m.block(row, col, row_block_size, col_block_size) = ...
 //  }
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.cc
index c496fcd13de..9ed62ce948b 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.cc
@@ -28,17 +28,17 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 
+#include "glog/logging.h"
 #include "ceres/block_random_access_sparse_matrix.h"
 
 #include <algorithm>
 #include <set>
 #include <utility>
 #include <vector>
-#include <glog/logging.h>
-#include "ceres/mutex.h"
-#include "ceres/triplet_sparse_matrix.h"
 #include "ceres/internal/port.h"
 #include "ceres/internal/scoped_ptr.h"
+#include "ceres/mutex.h"
+#include "ceres/triplet_sparse_matrix.h"
 #include "ceres/types.h"
 
 namespace ceres {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.h
index 12613c3daa0..48a00437cf6 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_random_access_sparse_matrix.h
@@ -38,6 +38,7 @@
 #include "ceres/block_random_access_matrix.h"
 #include "ceres/collections_port.h"
 #include "ceres/triplet_sparse_matrix.h"
+#include "ceres/integral_types.h"
 #include "ceres/internal/macros.h"
 #include "ceres/internal/port.h"
 #include "ceres/internal/scoped_ptr.h"
@@ -84,11 +85,11 @@ class BlockRandomAccessSparseMatrix : public BlockRandomAccessMatrix {
   TripletSparseMatrix* mutable_matrix() { return tsm_.get(); }
 
  private:
-  long int IntPairToLong(int a, int b) {
+  int64 IntPairToLong(int a, int b) {
     return a * kMaxRowBlocks + b;
   }
 
-  const int kMaxRowBlocks;
+  const int64 kMaxRowBlocks;
   // row/column block sizes.
   const vector<int> blocks_;
 
@@ -100,7 +101,8 @@ class BlockRandomAccessSparseMatrix : public BlockRandomAccessMatrix {
   // The underlying matrix object which actually stores the cells.
   scoped_ptr<TripletSparseMatrix> tsm_;
 
-  DISALLOW_COPY_AND_ASSIGN(BlockRandomAccessSparseMatrix);
+  friend class BlockRandomAccessSparseMatrixTest;
+  CERES_DISALLOW_COPY_AND_ASSIGN(BlockRandomAccessSparseMatrix);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.cc
index 7dd395e2975..dbe5ec93ef0 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.cc
@@ -33,11 +33,11 @@
 #include <cstddef>
 #include <algorithm>
 #include <vector>
-#include <glog/logging.h>
 #include "ceres/block_structure.h"
+#include "ceres/internal/eigen.h"
 #include "ceres/matrix_proto.h"
 #include "ceres/triplet_sparse_matrix.h"
-#include "ceres/internal/eigen.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -81,7 +81,7 @@ BlockSparseMatrix::BlockSparseMatrix(
   CHECK_NOTNULL(values_.get());
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 BlockSparseMatrix::BlockSparseMatrix(const SparseMatrixProto& outer_proto) {
   CHECK(outer_proto.has_block_matrix());
 
@@ -244,7 +244,7 @@ const CompressedRowBlockStructure* BlockSparseMatrix::block_structure()
   return block_structure_.get();
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 void BlockSparseMatrix::ToProto(SparseMatrixProto* outer_proto) const {
   outer_proto->Clear();
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.h
index f71446e8f58..513d398c54d 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_sparse_matrix.h
@@ -74,7 +74,7 @@ class BlockSparseMatrixBase : public SparseMatrix {
   virtual const double* RowBlockValues(int row_block_index) const = 0;
 
  private:
-  DISALLOW_COPY_AND_ASSIGN(BlockSparseMatrixBase);
+  CERES_DISALLOW_COPY_AND_ASSIGN(BlockSparseMatrixBase);
 };
 
 // This class implements the SparseMatrix interface for storing and
@@ -96,7 +96,7 @@ class BlockSparseMatrix : public BlockSparseMatrixBase {
   explicit BlockSparseMatrix(CompressedRowBlockStructure* block_structure);
 
   // Construct a block sparse matrix from a protocol buffer.
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   explicit BlockSparseMatrix(const SparseMatrixProto& proto);
 #endif
 
@@ -110,7 +110,7 @@ class BlockSparseMatrix : public BlockSparseMatrixBase {
   virtual void SquaredColumnNorm(double* x) const;
   virtual void ScaleColumns(const double* scale);
   virtual void ToDenseMatrix(Matrix* dense_matrix) const;
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   virtual void ToProto(SparseMatrixProto* proto) const;
 #endif
   virtual void ToTextFile(FILE* file) const;
@@ -135,7 +135,7 @@ class BlockSparseMatrix : public BlockSparseMatrixBase {
   int num_nonzeros_;
   scoped_array<double> values_;
   scoped_ptr<CompressedRowBlockStructure> block_structure_;
-  DISALLOW_COPY_AND_ASSIGN(BlockSparseMatrix);
+  CERES_DISALLOW_COPY_AND_ASSIGN(BlockSparseMatrix);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/block_structure.cc b/extern/libmv/third_party/ceres/internal/ceres/block_structure.cc
index 5add4f3b94d..e61131192af 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/block_structure.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/block_structure.cc
@@ -38,7 +38,7 @@ bool CellLessThan(const Cell& lhs, const Cell& rhs) {
   return (lhs.block_id < rhs.block_id);
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 void ProtoToBlockStructure(const BlockStructureProto &proto,
                            CompressedRowBlockStructure *block_structure) {
   // Decode the column blocks.
diff --git a/extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.cc b/extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.cc
index 53190ada6fc..d0dc1e670c2 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/canonical_views_clustering.cc
@@ -31,11 +31,11 @@
 
 #include "ceres/canonical_views_clustering.h"
 
-#include <glog/logging.h>
-#include "ceres/graph.h"
 #include "ceres/collections_port.h"
-#include "ceres/map_util.h"
+#include "ceres/graph.h"
 #include "ceres/internal/macros.h"
+#include "ceres/map_util.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -75,7 +75,7 @@ class CanonicalViewsClustering {
   IntMap view_to_canonical_view_;
   // Maps a view to its similarity to its current cluster center.
   HashMap<int, double> view_to_canonical_view_similarity_;
-  DISALLOW_COPY_AND_ASSIGN(CanonicalViewsClustering);
+  CERES_DISALLOW_COPY_AND_ASSIGN(CanonicalViewsClustering);
 };
 
 void ComputeCanonicalViewsClustering(
diff --git a/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.h b/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.h
index dd36f99006b..877b4c4ceea 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/cgnr_solver.h
@@ -57,7 +57,7 @@ class CgnrSolver : public LinearSolver {
  private:
   const LinearSolver::Options options_;
   scoped_ptr<BlockJacobiPreconditioner> jacobi_preconditioner_;
-  DISALLOW_COPY_AND_ASSIGN(CgnrSolver);
+  CERES_DISALLOW_COPY_AND_ASSIGN(CgnrSolver);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/collections_port.h b/extern/libmv/third_party/ceres/internal/ceres/collections_port.h
index 9dff0efe245..c2fce9033cd 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/collections_port.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/collections_port.h
@@ -33,31 +33,49 @@
 #ifndef CERES_INTERNAL_COLLECTIONS_PORT_H_
 #define CERES_INTERNAL_COLLECTIONS_PORT_H_
 
-#ifdef CERES_HASH_BOOST
-#include <boost/tr1/unordered_map.hpp>
-#include <boost/tr1/unordered_set.hpp>
+#if defined(CERES_NO_TR1)
+#  include <map>
+#  include <set>
 #else
-#if defined(_MSC_VER) && _MSC_VER <= 1700
-#include <unordered_map>
-#include <unordered_set>
-#else
-#include <tr1/unordered_map>
-#include <tr1/unordered_set>
-#endif
+#  if defined(_MSC_VER) && _MSC_VER <= 1600
+#    include <unordered_map>
+#    include <unordered_set>
+#  else
+#    include <tr1/unordered_map>
+#    include <tr1/unordered_set>
+#  endif
 #endif
-
 #include <utility>
 #include "ceres/integral_types.h"
 #include "ceres/internal/port.h"
 
+// Some systems don't have access to TR1. In that case, substitute the hash
+// map/set with normal map/set. The price to pay is slightly slower speed for
+// some operations.
+#if defined(CERES_NO_TR1)
+
 namespace ceres {
 namespace internal {
 
 template<typename K, typename V>
-struct HashMap : tr1::unordered_map<K, V> {};
+struct HashMap : map<K, V> {};
 
 template<typename K>
-struct HashSet : tr1::unordered_set<K> {};
+struct HashSet : set<K> {};
+
+}  // namespace internal
+}  // namespace ceres
+
+#else
+
+namespace ceres {
+namespace internal {
+
+template<typename K, typename V>
+struct HashMap : std::tr1::unordered_map<K, V> {};
+
+template<typename K>
+struct HashSet : std::tr1::unordered_set<K> {};
 
 #if defined(_WIN32) && !defined(__MINGW64__) && !defined(__MINGW32__)
 #define GG_LONGLONG(x) x##I64
@@ -124,11 +142,7 @@ CERES_HASH_NAMESPACE_START
 
 // Hasher for STL pairs. Requires hashers for both members to be defined.
 template<typename T>
-#ifdef CERES_HASH_BOOST
-struct hash {
-#else
 struct hash<pair<T, T> > {
-#endif
   size_t operator()(const pair<T, T>& p) const {
     size_t h1 = hash<T>()(p.first);
     size_t h2 = hash<T>()(p.second);
@@ -148,4 +162,6 @@ struct hash<pair<T, T> > {
 
 CERES_HASH_NAMESPACE_END
 
+#endif  // CERES_NO_TR1
+
 #endif  // CERES_INTERNAL_COLLECTIONS_PORT_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.cc b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.cc
index aa883b7d353..912c4845441 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_jacobian_writer.cc
@@ -130,8 +130,24 @@ SparseMatrix* CompressedRowJacobianWriter::CreateJacobian() const {
     }
     row_pos += num_residuals;
   }
-
   CHECK_EQ(num_jacobian_nonzeros, rows[total_num_residuals]);
+
+  // Populate the row and column block vectors for use by block
+  // oriented ordering algorithms. This is useful when
+  // Solver::Options::use_block_amd = true.
+  const vector<ParameterBlock*>& parameter_blocks = program_->parameter_blocks();
+  vector<int>& col_blocks = *(jacobian->mutable_col_blocks());
+  col_blocks.resize(parameter_blocks.size());
+  for (int i = 0; i <  parameter_blocks.size(); ++i) {
+    col_blocks[i] = parameter_blocks[i]->LocalSize();
+  }
+
+  vector<int>& row_blocks = *(jacobian->mutable_row_blocks());
+  row_blocks.resize(residual_blocks.size());
+  for (int i = 0; i <  residual_blocks.size(); ++i) {
+    row_blocks[i] = residual_blocks[i]->NumResiduals();
+  }
+
   return jacobian;
 }
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.cc
index 95edf5396af..1b61468aaae 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.cc
@@ -32,15 +32,22 @@
 
 #include <algorithm>
 #include <vector>
-#include "ceres/matrix_proto.h"
+#include "ceres/crs_matrix.h"
 #include "ceres/internal/port.h"
+#include "ceres/matrix_proto.h"
 
 namespace ceres {
 namespace internal {
 namespace {
 
 // Helper functor used by the constructor for reordering the contents
-// of a TripletSparseMatrix.
+// of a TripletSparseMatrix. This comparator assumes thay there are no
+// duplicates in the pair of arrays rows and cols, i.e., there is no
+// indices i and j (not equal to each other) s.t.
+//
+//  rows[i] == rows[j] && cols[i] == cols[j]
+//
+// If this is the case, this functor will not be a StrictWeakOrdering.
 struct RowColLessThan {
   RowColLessThan(const int* rows, const int* cols)
       : rows(rows), cols(cols) {
@@ -128,7 +135,7 @@ CompressedRowSparseMatrix::CompressedRowSparseMatrix(
   CHECK_EQ(num_nonzeros(), m.num_nonzeros());
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 CompressedRowSparseMatrix::CompressedRowSparseMatrix(
     const SparseMatrixProto& outer_proto) {
   CHECK(outer_proto.has_compressed_row_matrix());
@@ -241,7 +248,7 @@ void CompressedRowSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
   }
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 void CompressedRowSparseMatrix::ToProto(SparseMatrixProto* outer_proto) const {
   CHECK_NOTNULL(outer_proto);
 
@@ -330,5 +337,18 @@ void CompressedRowSparseMatrix::ToTextFile(FILE* file) const {
   }
 }
 
+void CompressedRowSparseMatrix::ToCRSMatrix(CRSMatrix* matrix) const {
+  matrix->num_rows = num_rows();
+  matrix->num_cols = num_cols();
+
+  matrix->rows.resize(matrix->num_rows + 1);
+  matrix->cols.resize(num_nonzeros());
+  matrix->values.resize(num_nonzeros());
+
+  copy(rows_.get(), rows_.get() + matrix->num_rows + 1, matrix->rows.begin());
+  copy(cols_.get(), cols_.get() + num_nonzeros(), matrix->cols.begin());
+  copy(values_.get(), values_.get() + num_nonzeros(), matrix->values.begin());
+}
+
 }  // namespace internal
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.h
index 9a39d28e111..6a9d82842e5 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/compressed_row_sparse_matrix.h
@@ -31,14 +31,19 @@
 #ifndef CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
 #define CERES_INTERNAL_COMPRESSED_ROW_SPARSE_MATRIX_H_
 
+#include <vector>
 #include <glog/logging.h>
 #include "ceres/sparse_matrix.h"
 #include "ceres/triplet_sparse_matrix.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/macros.h"
+#include "ceres/internal/port.h"
 #include "ceres/types.h"
 
 namespace ceres {
+
+class CRSMatrix;
+
 namespace internal {
 
 class SparseMatrixProto;
@@ -52,7 +57,7 @@ class CompressedRowSparseMatrix : public SparseMatrix {
   //
   // We assume that m does not have any repeated entries.
   explicit CompressedRowSparseMatrix(const TripletSparseMatrix& m);
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   explicit CompressedRowSparseMatrix(const SparseMatrixProto& proto);
 #endif
 
@@ -85,7 +90,7 @@ class CompressedRowSparseMatrix : public SparseMatrix {
   virtual void ScaleColumns(const double* scale);
 
   virtual void ToDenseMatrix(Matrix* dense_matrix) const;
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   virtual void ToProto(SparseMatrixProto* proto) const;
 #endif
   virtual void ToTextFile(FILE* file) const;
@@ -103,6 +108,8 @@ class CompressedRowSparseMatrix : public SparseMatrix {
   // have the same number of columns as this matrix.
   void AppendRows(const CompressedRowSparseMatrix& m);
 
+  void ToCRSMatrix(CRSMatrix* matrix) const;
+
   // Low level access methods that expose the structure of the matrix.
   const int* cols() const { return cols_.get(); }
   int* mutable_cols() { return cols_.get(); }
@@ -110,6 +117,12 @@ class CompressedRowSparseMatrix : public SparseMatrix {
   const int* rows() const { return rows_.get(); }
   int* mutable_rows() { return rows_.get(); }
 
+  const vector<int>& row_blocks() const { return row_blocks_; }
+  vector<int>* mutable_row_blocks() { return &row_blocks_; }
+
+  const vector<int>& col_blocks() const { return col_blocks_; }
+  vector<int>* mutable_col_blocks() { return &col_blocks_; }
+
  private:
   scoped_array<int> cols_;
   scoped_array<int> rows_;
@@ -117,10 +130,17 @@ class CompressedRowSparseMatrix : public SparseMatrix {
 
   int num_rows_;
   int num_cols_;
-
   int max_num_nonzeros_;
 
-  DISALLOW_COPY_AND_ASSIGN(CompressedRowSparseMatrix);
+  // If the matrix has an underlying block structure, then it can also
+  // carry with it row and column block sizes. This is auxilliary and
+  // optional information for use by algorithms operating on the
+  // matrix. The class itself does not make use of this information in
+  // any way.
+  vector<int> row_blocks_;
+  vector<int> col_blocks_;
+
+  CERES_DISALLOW_COPY_AND_ASSIGN(CompressedRowSparseMatrix);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/conditioned_cost_function.cc b/extern/libmv/third_party/ceres/internal/ceres/conditioned_cost_function.cc
index ca80bfb9c9d..7322790f717 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/conditioned_cost_function.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/conditioned_cost_function.cc
@@ -34,10 +34,10 @@
 
 #include <cstddef>
 
-#include <glog/logging.h>
-#include "ceres/stl_util.h"
 #include "ceres/internal/eigen.h"
+#include "ceres/stl_util.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.cc
index 75f9e043fa5..ae8e8774709 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.cc
@@ -41,18 +41,18 @@
 
 #include <cmath>
 #include <cstddef>
-#include <glog/logging.h>
-#include "ceres/linear_operator.h"
+#include "ceres/fpclassify.h"
 #include "ceres/internal/eigen.h"
+#include "ceres/linear_operator.h"
 #include "ceres/types.h"
-#include "ceres/jet.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
 namespace {
 
 bool IsZeroOrInfinity(double x) {
-  return ((x == 0.0) || (isinf(x)));
+  return ((x == 0.0) || (IsInfinite(x)));
 }
 
 // Constant used in the MATLAB implementation ~ 2 * eps.
@@ -115,7 +115,7 @@ LinearSolver::Summary ConjugateGradientsSolver::Solve(
   for (summary.num_iterations = 1;
        summary.num_iterations < options_.max_num_iterations;
        ++summary.num_iterations) {
-    VLOG(2) << "cg iteration " << summary.num_iterations;
+    VLOG(3) << "cg iteration " << summary.num_iterations;
 
     // Apply preconditioner
     if (per_solve_options.preconditioner != NULL) {
@@ -151,14 +151,14 @@ LinearSolver::Summary ConjugateGradientsSolver::Solve(
     A->RightMultiply(p.data(), q.data());
     double pq = p.dot(q);
 
-    if ((pq <= 0) || isinf(pq))  {
+    if ((pq <= 0) || IsInfinite(pq))  {
       LOG(ERROR) << "Numerical failure. pq = " << pq;
       summary.termination_type = FAILURE;
       break;
     }
 
     double alpha = rho / pq;
-    if (isinf(alpha)) {
+    if (IsInfinite(alpha)) {
       LOG(ERROR) << "Numerical failure. alpha " << alpha;
       summary.termination_type = FAILURE;
       break;
@@ -202,13 +202,13 @@ LinearSolver::Summary ConjugateGradientsSolver::Solve(
     //   1. Stephen G. Nash & Ariela Sofer, Assessing A Search
     //   Direction Within A Truncated Newton Method, Operation
     //   Research Letters 9(1990) 219-221.
-    //   
+    //
     //   2. Stephen G. Nash, A Survey of Truncated Newton Methods,
     //   Journal of Computational and Applied Mathematics,
     //   124(1-2), 45-59, 2000.
     //
     double zeta = summary.num_iterations * (Q1 - Q0) / Q1;
-    VLOG(2) << "Q termination: zeta " << zeta
+    VLOG(3) << "Q termination: zeta " << zeta
             << " " << per_solve_options.q_tolerance;
     if (zeta < per_solve_options.q_tolerance) {
       summary.termination_type = TOLERANCE;
@@ -218,7 +218,7 @@ LinearSolver::Summary ConjugateGradientsSolver::Solve(
 
     // Residual based termination.
     norm_r = r. norm();
-    VLOG(2) << "R termination: norm_r " << norm_r
+    VLOG(3) << "R termination: norm_r " << norm_r
             << " " << tol_r;
     if (norm_r <= tol_r) {
       summary.termination_type = TOLERANCE;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.h b/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.h
index 57f99e31db7..b8dfa56b526 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/conjugate_gradients_solver.h
@@ -65,7 +65,7 @@ class ConjugateGradientsSolver : public LinearSolver {
 
  private:
   const LinearSolver::Options options_;
-  DISALLOW_COPY_AND_ASSIGN(ConjugateGradientsSolver);
+  CERES_DISALLOW_COPY_AND_ASSIGN(ConjugateGradientsSolver);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/corrector.cc b/extern/libmv/third_party/ceres/internal/ceres/corrector.cc
index 4ca2c6f6c86..eff4dff8566 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/corrector.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/corrector.cc
@@ -32,8 +32,8 @@
 
 #include <cstddef>
 #include <cmath>
-#include <glog/logging.h>
 #include "ceres/internal/eigen.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc b/extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc
new file mode 100644
index 00000000000..ca36ce07614
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/cxsparse.cc
@@ -0,0 +1,130 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: strandmark@google.com (Petter Strandmark)
+
+#ifndef CERES_NO_CXSPARSE
+
+#include "ceres/cxsparse.h"
+
+#include "ceres/compressed_row_sparse_matrix.h"
+#include "ceres/triplet_sparse_matrix.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+
+CXSparse::CXSparse() : scratch_size_(0), scratch_(NULL) {
+}
+
+CXSparse::~CXSparse() {
+  if (scratch_size_ > 0) {
+    cs_free(scratch_);
+  }
+}
+
+bool CXSparse::SolveCholesky(cs_di* A,
+                             cs_dis* symbolic_factorization,
+                             double* b) {
+  // Make sure we have enough scratch space available.
+  if (scratch_size_ < A->n) {
+    if (scratch_size_ > 0) {
+      cs_free(scratch_);
+    }
+    scratch_ = reinterpret_cast<CS_ENTRY*>(cs_malloc(A->n, sizeof(CS_ENTRY)));
+  }
+
+  // Solve using Cholesky factorization
+  csn* numeric_factorization = cs_chol(A, symbolic_factorization);
+  if (numeric_factorization == NULL) {
+    LOG(WARNING) << "Cholesky factorization failed.";
+    return false;
+  }
+
+  // When the Cholesky factorization succeeded, these methods are guaranteed to
+  // succeeded as well. In the comments below, "x" refers to the scratch space.
+  //
+  // Set x = P * b.
+  cs_ipvec(symbolic_factorization->pinv, b, scratch_, A->n);
+
+  // Set x = L \ x.
+  cs_lsolve(numeric_factorization->L, scratch_);
+
+  // Set x = L' \ x.
+  cs_ltsolve(numeric_factorization->L, scratch_);
+
+  // Set b = P' * x.
+  cs_pvec(symbolic_factorization->pinv, scratch_, b, A->n);
+
+  // Free Cholesky factorization.
+  cs_nfree(numeric_factorization);
+  return true;
+}
+
+cs_dis* CXSparse::AnalyzeCholesky(cs_di* A) {
+  // order = 1 for Cholesky factorization.
+  return cs_schol(1, A);
+}
+
+cs_di CXSparse::CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A) {
+  cs_di At;
+  At.m = A->num_cols();
+  At.n = A->num_rows();
+  At.nz = -1;
+  At.nzmax = A->num_nonzeros();
+  At.p = A->mutable_rows();
+  At.i = A->mutable_cols();
+  At.x = A->mutable_values();
+  return At;
+}
+
+cs_di* CXSparse::CreateSparseMatrix(TripletSparseMatrix* tsm) {
+  cs_di_sparse tsm_wrapper;
+  tsm_wrapper.nzmax = tsm->num_nonzeros();;
+  tsm_wrapper.nz = tsm->num_nonzeros();;
+  tsm_wrapper.m = tsm->num_rows();
+  tsm_wrapper.n = tsm->num_cols();
+  tsm_wrapper.p = tsm->mutable_cols();
+  tsm_wrapper.i = tsm->mutable_rows();
+  tsm_wrapper.x = tsm->mutable_values();
+
+  return cs_compress(&tsm_wrapper);
+}
+
+void CXSparse::Free(cs_di* factor) {
+  cs_free(factor);
+}
+
+void CXSparse::Free(cs_dis* factor) {
+  cs_sfree(factor);
+}
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_NO_CXSPARSE
diff --git a/extern/libmv/third_party/ceres/internal/ceres/cxsparse.h b/extern/libmv/third_party/ceres/internal/ceres/cxsparse.h
new file mode 100644
index 00000000000..d3b64fcd1a5
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/cxsparse.h
@@ -0,0 +1,90 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: strandmark@google.com (Petter Strandmark)
+
+#ifndef CERES_INTERNAL_CXSPARSE_H_
+#define CERES_INTERNAL_CXSPARSE_H_
+
+#ifndef CERES_NO_CXSPARSE
+
+#include "cs.h"
+
+namespace ceres {
+namespace internal {
+
+class CompressedRowSparseMatrix;
+class TripletSparseMatrix;
+
+// This object provides access to solving linear systems using Cholesky
+// factorization with a known symbolic factorization. This features does not
+// explicity exist in CXSparse. The methods in the class are nonstatic because
+// the class manages internal scratch space.
+class CXSparse {
+ public:
+  CXSparse();
+  ~CXSparse();
+
+  // Solves a symmetric linear system A * x = b using Cholesky factorization.
+  //  A                      - The system matrix.
+  //  symbolic_factorization - The symbolic factorization of A. This is obtained
+  //                           from AnalyzeCholesky.
+  //  b                      - The right hand size of the linear equation. This
+  //                           array will also recieve the solution.
+  // Returns false if Cholesky factorization of A fails.
+  bool SolveCholesky(cs_di* A, cs_dis* symbolic_factorization, double* b);
+
+  // Creates a sparse matrix from a compressed-column form. No memory is
+  // allocated or copied; the structure A is filled out with info from the
+  // argument.
+  cs_di CreateSparseMatrixTransposeView(CompressedRowSparseMatrix* A);
+
+  // Creates a new matrix from a triplet form. Deallocate the returned matrix
+  // with Free. May return NULL if the compression or allocation fails.
+  cs_di* CreateSparseMatrix(TripletSparseMatrix* A);
+
+  // Computes a symbolic factorization of A that can be used in SolveCholesky.
+  // The returned matrix should be deallocated with Free when not used anymore.
+  cs_dis* AnalyzeCholesky(cs_di* A);
+
+  // Deallocates the memory of a matrix obtained from AnalyzeCholesky.
+  void Free(cs_di* factor);
+  void Free(cs_dis* factor);
+
+ private:
+  // Cached scratch space
+  CS_ENTRY* scratch_;
+  int scratch_size_;
+};
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_NO_CXSPARSE
+
+#endif  // CERES_INTERNAL_CXSPARSE_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.cc
new file mode 100644
index 00000000000..f6bb99abf63
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.cc
@@ -0,0 +1,86 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/dense_normal_cholesky_solver.h"
+
+#include <cstddef>
+
+#include "Eigen/Dense"
+#include "ceres/dense_sparse_matrix.h"
+#include "ceres/linear_solver.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
+#include "ceres/types.h"
+
+namespace ceres {
+namespace internal {
+
+DenseNormalCholeskySolver::DenseNormalCholeskySolver(
+    const LinearSolver::Options& options)
+    : options_(options) {}
+
+LinearSolver::Summary DenseNormalCholeskySolver::SolveImpl(
+    DenseSparseMatrix* A,
+    const double* b,
+    const LinearSolver::PerSolveOptions& per_solve_options,
+    double* x) {
+  const int num_rows = A->num_rows();
+  const int num_cols = A->num_cols();
+
+  ConstAlignedMatrixRef Aref = A->matrix();
+  Matrix lhs(num_cols, num_cols);
+  lhs.setZero();
+
+  //   lhs += A'A
+  //
+  // Using rankUpdate instead of GEMM, exposes the fact that its the
+  // same matrix being multiplied with itself and that the product is
+  // symmetric.
+  lhs.selfadjointView<Eigen::Upper>().rankUpdate(Aref.transpose());
+
+  //   rhs = A'b
+  Vector rhs = Aref.transpose() * ConstVectorRef(b, num_rows);
+
+  if (per_solve_options.D != NULL) {
+    ConstVectorRef D(per_solve_options.D, num_cols);
+    lhs += D.array().square().matrix().asDiagonal();
+  }
+
+  VectorRef(x, num_cols) =
+      lhs.selfadjointView<Eigen::Upper>().ldlt().solve(rhs);
+
+  LinearSolver::Summary summary;
+  summary.num_iterations = 1;
+  summary.termination_type = TOLERANCE;
+  return summary;
+}
+
+}   // namespace internal
+}   // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.h b/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.h
new file mode 100644
index 00000000000..de47740583d
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/dense_normal_cholesky_solver.h
@@ -0,0 +1,95 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+//
+// Solve dense rectangular systems Ax = b by forming the normal
+// equations and solving them using the Cholesky factorization.
+
+#ifndef CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_
+#define CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_
+
+#include "ceres/linear_solver.h"
+#include "ceres/internal/macros.h"
+
+namespace ceres {
+namespace internal {
+
+class DenseSparseMatrix;
+
+// This class implements the LinearSolver interface for solving
+// rectangular/unsymmetric (well constrained) linear systems of the
+// form
+//
+//   Ax = b
+//
+// Since there does not usually exist a solution that satisfies these
+// equations, the solver instead solves the linear least squares
+// problem
+//
+//   min_x |Ax - b|^2
+//
+// Setting the gradient of the above optimization problem to zero
+// gives us the normal equations
+//
+//   A'Ax = A'b
+//
+// A'A is a positive definite matrix (hopefully), and the resulting
+// linear system can be solved using Cholesky factorization.
+//
+// If the PerSolveOptions struct has a non-null array D, then the
+// augmented/regularized linear system
+//
+//   [    A    ]x = [b]
+//   [ diag(D) ]    [0]
+//
+// is solved.
+//
+// This class uses the LDLT factorization routines from the Eigen
+// library. This solver always returns a solution, it is the user's
+// responsibility to judge if the solution is good enough for their
+// purposes.
+class DenseNormalCholeskySolver: public DenseSparseMatrixSolver {
+ public:
+  explicit DenseNormalCholeskySolver(const LinearSolver::Options& options);
+
+ private:
+  virtual LinearSolver::Summary SolveImpl(
+      DenseSparseMatrix* A,
+      const double* b,
+      const LinearSolver::PerSolveOptions& per_solve_options,
+      double* x);
+
+  const LinearSolver::Options options_;
+  CERES_DISALLOW_COPY_AND_ASSIGN(DenseNormalCholeskySolver);
+};
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_DENSE_NORMAL_CHOLESKY_SOLVER_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.cc
index 328505404d7..2b329ee0e9c 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.cc
@@ -33,8 +33,8 @@
 #include <cstddef>
 
 #include "Eigen/Dense"
+#include "ceres/dense_sparse_matrix.h"
 #include "ceres/linear_solver.h"
-#include "ceres/triplet_sparse_matrix.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/scoped_ptr.h"
 #include "ceres/types.h"
@@ -62,7 +62,7 @@ LinearSolver::Summary DenseQRSolver::SolveImpl(
   }
 
   // rhs = [b;0] to account for the additional rows in the lhs.
-  Vector rhs(num_rows + ((per_solve_options.D !=NULL) ? num_cols : 0));
+  Vector rhs(num_rows + ((per_solve_options.D != NULL) ? num_cols : 0));
   rhs.setZero();
   rhs.head(num_rows) = ConstVectorRef(b, num_rows);
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.h b/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.h
index 990c8d445eb..dd683a8c4ea 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/dense_qr_solver.h
@@ -28,7 +28,7 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 //
-// Solve dense rectangular systems Ax = b using the QR factoriztion.
+// Solve dense rectangular systems Ax = b using the QR factorization.
 #ifndef CERES_INTERNAL_DENSE_QR_SOLVER_H_
 #define CERES_INTERNAL_DENSE_QR_SOLVER_H_
 
@@ -90,7 +90,7 @@ class DenseQRSolver: public DenseSparseMatrixSolver {
       double* x);
 
   const LinearSolver::Options options_;
-  DISALLOW_COPY_AND_ASSIGN(DenseQRSolver);
+  CERES_DISALLOW_COPY_AND_ASSIGN(DenseQRSolver);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.cc
index 5d392ba6c3b..86730cc101b 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.cc
@@ -67,7 +67,7 @@ DenseSparseMatrix::DenseSparseMatrix(const Matrix& m)
       has_diagonal_reserved_(false) {
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 DenseSparseMatrix::DenseSparseMatrix(const SparseMatrixProto& outer_proto)
     : m_(Eigen::MatrixXd::Zero(
         outer_proto.dense_matrix().num_rows(),
@@ -108,7 +108,7 @@ void DenseSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
   *dense_matrix = m_;
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 void DenseSparseMatrix::ToProto(SparseMatrixProto* outer_proto) const {
   CHECK(!has_diagonal_appended_) << "Not supported.";
   outer_proto->Clear();
@@ -183,7 +183,7 @@ void DenseSparseMatrix::ToTextFile(FILE* file) const {
   CHECK_NOTNULL(file);
   const int active_rows =
       (has_diagonal_reserved_ && !has_diagonal_appended_)
-      ? (m_.rows() - m_.cols()) 
+      ? (m_.rows() - m_.cols())
       : m_.rows();
 
   for (int r = 0; r < active_rows; ++r) {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.h
index 416c2143c2c..e7ad14d0ee6 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/dense_sparse_matrix.h
@@ -52,7 +52,7 @@ class DenseSparseMatrix : public SparseMatrix {
   // m. This assumes that m does not have any repeated entries.
   explicit DenseSparseMatrix(const TripletSparseMatrix& m);
   explicit DenseSparseMatrix(const Matrix& m);
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   explicit DenseSparseMatrix(const SparseMatrixProto& proto);
 #endif
 
@@ -67,7 +67,7 @@ class DenseSparseMatrix : public SparseMatrix {
   virtual void SquaredColumnNorm(double* x) const;
   virtual void ScaleColumns(const double* scale);
   virtual void ToDenseMatrix(Matrix* dense_matrix) const;
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   virtual void ToProto(SparseMatrixProto* proto) const;
 #endif
   virtual void ToTextFile(FILE* file) const;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.cc b/extern/libmv/third_party/ceres/internal/ceres/detect_structure.cc
index e9755043bab..ea5bf2e9690 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/detect_structure.cc
@@ -28,9 +28,9 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 
-#include <glog/logging.h>
 #include "ceres/detect_structure.h"
 #include "ceres/internal/eigen.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -60,10 +60,10 @@ void DetectStructure(const CompressedRowBlockStructure& bs,
       *row_block_size = row.block.size;
     } else if (*row_block_size != Eigen::Dynamic &&
                *row_block_size != row.block.size) {
-      *row_block_size = Eigen::Dynamic;
       VLOG(2) << "Dynamic row block size because the block size changed from "
               << *row_block_size << " to "
               << row.block.size;
+      *row_block_size = Eigen::Dynamic;
     }
 
 
@@ -71,10 +71,10 @@ void DetectStructure(const CompressedRowBlockStructure& bs,
       *e_block_size = bs.cols[e_block_id].size;
     } else if (*e_block_size != Eigen::Dynamic &&
                *e_block_size != bs.cols[e_block_id].size) {
-      *e_block_size = Eigen::Dynamic;
       VLOG(2) << "Dynamic e block size because the block size changed from "
               << *e_block_size << " to "
               << bs.cols[e_block_id].size;
+      *e_block_size = Eigen::Dynamic;
     }
 
     if (*f_block_size == 0) {
@@ -85,11 +85,11 @@ void DetectStructure(const CompressedRowBlockStructure& bs,
     } else if (*f_block_size != Eigen::Dynamic) {
       for (int c = 1; c < row.cells.size(); ++c) {
         if (*f_block_size != bs.cols[row.cells[c].block_id].size) {
-          *f_block_size = Eigen::Dynamic;
           VLOG(2) << "Dynamic f block size because the block size "
-                    << "changed from " << *f_block_size << " to "
-                    << bs.cols[row.cells[c].block_id].size;
-            break;
+                  << "changed from " << *f_block_size << " to "
+                  << bs.cols[row.cells[c].block_id].size;
+          *f_block_size = Eigen::Dynamic;
+          break;
         }
       }
     }
diff --git a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.h b/extern/libmv/third_party/ceres/internal/ceres/detect_structure.h
index 8af4f236690..5f8e1b4ff46 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/detect_structure.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/detect_structure.h
@@ -49,7 +49,7 @@ namespace internal {
 // is known as compile time.
 //
 // For more details about e_blocks and f_blocks, see
-// schur_complement.h. This information is used to initialized an
+// schur_eliminator.h. This information is used to initialized an
 // appropriate template specialization of SchurEliminator.
 void DetectStructure(const CompressedRowBlockStructure& bs,
                      const int num_eliminate_blocks,
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc
new file mode 100644
index 00000000000..668fa54b8b8
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.cc
@@ -0,0 +1,691 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/dogleg_strategy.h"
+
+#include <cmath>
+#include "Eigen/Dense"
+#include "ceres/array_utils.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/linear_solver.h"
+#include "ceres/polynomial_solver.h"
+#include "ceres/sparse_matrix.h"
+#include "ceres/trust_region_strategy.h"
+#include "ceres/types.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+namespace {
+const double kMaxMu = 1.0;
+const double kMinMu = 1e-8;
+}
+
+DoglegStrategy::DoglegStrategy(const TrustRegionStrategy::Options& options)
+    : linear_solver_(options.linear_solver),
+      radius_(options.initial_radius),
+      max_radius_(options.max_radius),
+      min_diagonal_(options.lm_min_diagonal),
+      max_diagonal_(options.lm_max_diagonal),
+      mu_(kMinMu),
+      min_mu_(kMinMu),
+      max_mu_(kMaxMu),
+      mu_increase_factor_(10.0),
+      increase_threshold_(0.75),
+      decrease_threshold_(0.25),
+      dogleg_step_norm_(0.0),
+      reuse_(false),
+      dogleg_type_(options.dogleg_type) {
+  CHECK_NOTNULL(linear_solver_);
+  CHECK_GT(min_diagonal_, 0.0);
+  CHECK_LE(min_diagonal_, max_diagonal_);
+  CHECK_GT(max_radius_, 0.0);
+}
+
+// If the reuse_ flag is not set, then the Cauchy point (scaled
+// gradient) and the new Gauss-Newton step are computed from
+// scratch. The Dogleg step is then computed as interpolation of these
+// two vectors.
+TrustRegionStrategy::Summary DoglegStrategy::ComputeStep(
+    const TrustRegionStrategy::PerSolveOptions& per_solve_options,
+    SparseMatrix* jacobian,
+    const double* residuals,
+    double* step) {
+  CHECK_NOTNULL(jacobian);
+  CHECK_NOTNULL(residuals);
+  CHECK_NOTNULL(step);
+
+  const int n = jacobian->num_cols();
+  if (reuse_) {
+    // Gauss-Newton and gradient vectors are always available, only a
+    // new interpolant need to be computed. For the subspace case,
+    // the subspace and the two-dimensional model are also still valid.
+    switch(dogleg_type_) {
+      case TRADITIONAL_DOGLEG:
+        ComputeTraditionalDoglegStep(step);
+        break;
+
+      case SUBSPACE_DOGLEG:
+        ComputeSubspaceDoglegStep(step);
+        break;
+    }
+    TrustRegionStrategy::Summary summary;
+    summary.num_iterations = 0;
+    summary.termination_type = TOLERANCE;
+    return summary;
+  }
+
+  reuse_ = true;
+  // Check that we have the storage needed to hold the various
+  // temporary vectors.
+  if (diagonal_.rows() != n) {
+    diagonal_.resize(n, 1);
+    gradient_.resize(n, 1);
+    gauss_newton_step_.resize(n, 1);
+  }
+
+  // Vector used to form the diagonal matrix that is used to
+  // regularize the Gauss-Newton solve and that defines the
+  // elliptical trust region
+  //
+  //   || D * step || <= radius_ .
+  //
+  jacobian->SquaredColumnNorm(diagonal_.data());
+  for (int i = 0; i < n; ++i) {
+    diagonal_[i] = min(max(diagonal_[i], min_diagonal_), max_diagonal_);
+  }
+  diagonal_ = diagonal_.array().sqrt();
+
+  ComputeGradient(jacobian, residuals);
+  ComputeCauchyPoint(jacobian);
+
+  LinearSolver::Summary linear_solver_summary =
+      ComputeGaussNewtonStep(jacobian, residuals);
+
+  TrustRegionStrategy::Summary summary;
+  summary.residual_norm = linear_solver_summary.residual_norm;
+  summary.num_iterations = linear_solver_summary.num_iterations;
+  summary.termination_type = linear_solver_summary.termination_type;
+
+  if (linear_solver_summary.termination_type != FAILURE) {
+    switch(dogleg_type_) {
+      // Interpolate the Cauchy point and the Gauss-Newton step.
+      case TRADITIONAL_DOGLEG:
+        ComputeTraditionalDoglegStep(step);
+        break;
+
+      // Find the minimum in the subspace defined by the
+      // Cauchy point and the (Gauss-)Newton step.
+      case SUBSPACE_DOGLEG:
+        if (!ComputeSubspaceModel(jacobian)) {
+          summary.termination_type = FAILURE;
+          break;
+        }
+        ComputeSubspaceDoglegStep(step);
+        break;
+    }
+  }
+
+  return summary;
+}
+
+// The trust region is assumed to be elliptical with the
+// diagonal scaling matrix D defined by sqrt(diagonal_).
+// It is implemented by substituting step' = D * step.
+// The trust region for step' is spherical.
+// The gradient, the Gauss-Newton step, the Cauchy point,
+// and all calculations involving the Jacobian have to
+// be adjusted accordingly.
+void DoglegStrategy::ComputeGradient(
+    SparseMatrix* jacobian,
+    const double* residuals) {
+  gradient_.setZero();
+  jacobian->LeftMultiply(residuals, gradient_.data());
+  gradient_.array() /= diagonal_.array();
+}
+
+// The Cauchy point is the global minimizer of the quadratic model
+// along the one-dimensional subspace spanned by the gradient.
+void DoglegStrategy::ComputeCauchyPoint(SparseMatrix* jacobian) {
+  // alpha * -gradient is the Cauchy point.
+  Vector Jg(jacobian->num_rows());
+  Jg.setZero();
+  // The Jacobian is scaled implicitly by computing J * (D^-1 * (D^-1 * g))
+  // instead of (J * D^-1) * (D^-1 * g).
+  Vector scaled_gradient =
+      (gradient_.array() / diagonal_.array()).matrix();
+  jacobian->RightMultiply(scaled_gradient.data(), Jg.data());
+  alpha_ = gradient_.squaredNorm() / Jg.squaredNorm();
+}
+
+// The dogleg step is defined as the intersection of the trust region
+// boundary with the piecewise linear path from the origin to the Cauchy
+// point and then from there to the Gauss-Newton point (global minimizer
+// of the model function). The Gauss-Newton point is taken if it lies
+// within the trust region.
+void DoglegStrategy::ComputeTraditionalDoglegStep(double* dogleg) {
+  VectorRef dogleg_step(dogleg, gradient_.rows());
+
+  // Case 1. The Gauss-Newton step lies inside the trust region, and
+  // is therefore the optimal solution to the trust-region problem.
+  const double gradient_norm = gradient_.norm();
+  const double gauss_newton_norm = gauss_newton_step_.norm();
+  if (gauss_newton_norm <= radius_) {
+    dogleg_step = gauss_newton_step_;
+    dogleg_step_norm_ = gauss_newton_norm;
+    dogleg_step.array() /= diagonal_.array();
+    VLOG(3) << "GaussNewton step size: " << dogleg_step_norm_
+            << " radius: " << radius_;
+    return;
+  }
+
+  // Case 2. The Cauchy point and the Gauss-Newton steps lie outside
+  // the trust region. Rescale the Cauchy point to the trust region
+  // and return.
+  if  (gradient_norm * alpha_ >= radius_) {
+    dogleg_step = -(radius_ / gradient_norm) * gradient_;
+    dogleg_step_norm_ = radius_;
+    dogleg_step.array() /= diagonal_.array();
+    VLOG(3) << "Cauchy step size: " << dogleg_step_norm_
+            << " radius: " << radius_;
+    return;
+  }
+
+  // Case 3. The Cauchy point is inside the trust region and the
+  // Gauss-Newton step is outside. Compute the line joining the two
+  // points and the point on it which intersects the trust region
+  // boundary.
+
+  // a = alpha * -gradient
+  // b = gauss_newton_step
+  const double b_dot_a = -alpha_ * gradient_.dot(gauss_newton_step_);
+  const double a_squared_norm = pow(alpha_ * gradient_norm, 2.0);
+  const double b_minus_a_squared_norm =
+      a_squared_norm - 2 * b_dot_a + pow(gauss_newton_norm, 2);
+
+  // c = a' (b - a)
+  //   = alpha * -gradient' gauss_newton_step - alpha^2 |gradient|^2
+  const double c = b_dot_a - a_squared_norm;
+  const double d = sqrt(c * c + b_minus_a_squared_norm *
+                        (pow(radius_, 2.0) - a_squared_norm));
+
+  double beta =
+      (c <= 0)
+      ? (d - c) /  b_minus_a_squared_norm
+      : (radius_ * radius_ - a_squared_norm) / (d + c);
+  dogleg_step = (-alpha_ * (1.0 - beta)) * gradient_
+      + beta * gauss_newton_step_;
+  dogleg_step_norm_ = dogleg_step.norm();
+  dogleg_step.array() /= diagonal_.array();
+  VLOG(3) << "Dogleg step size: " << dogleg_step_norm_
+          << " radius: " << radius_;
+}
+
+// The subspace method finds the minimum of the two-dimensional problem
+//
+//   min. 1/2 x' B' H B x + g' B x
+//   s.t. || B x ||^2 <= r^2
+//
+// where r is the trust region radius and B is the matrix with unit columns
+// spanning the subspace defined by the steepest descent and Newton direction.
+// This subspace by definition includes the Gauss-Newton point, which is
+// therefore taken if it lies within the trust region.
+void DoglegStrategy::ComputeSubspaceDoglegStep(double* dogleg) {
+  VectorRef dogleg_step(dogleg, gradient_.rows());
+
+  // The Gauss-Newton point is inside the trust region if |GN| <= radius_.
+  // This test is valid even though radius_ is a length in the two-dimensional
+  // subspace while gauss_newton_step_ is expressed in the (scaled)
+  // higher dimensional original space. This is because
+  //
+  //   1. gauss_newton_step_ by definition lies in the subspace, and
+  //   2. the subspace basis is orthonormal.
+  //
+  // As a consequence, the norm of the gauss_newton_step_ in the subspace is
+  // the same as its norm in the original space.
+  const double gauss_newton_norm = gauss_newton_step_.norm();
+  if (gauss_newton_norm <= radius_) {
+    dogleg_step = gauss_newton_step_;
+    dogleg_step_norm_ = gauss_newton_norm;
+    dogleg_step.array() /= diagonal_.array();
+    VLOG(3) << "GaussNewton step size: " << dogleg_step_norm_
+            << " radius: " << radius_;
+    return;
+  }
+
+  // The optimum lies on the boundary of the trust region. The above problem
+  // therefore becomes
+  //
+  //   min. 1/2 x^T B^T H B x + g^T B x
+  //   s.t. || B x ||^2 = r^2
+  //
+  // Notice the equality in the constraint.
+  //
+  // This can be solved by forming the Lagrangian, solving for x(y), where
+  // y is the Lagrange multiplier, using the gradient of the objective, and
+  // putting x(y) back into the constraint. This results in a fourth order
+  // polynomial in y, which can be solved using e.g. the companion matrix.
+  // See the description of MakePolynomialForBoundaryConstrainedProblem for
+  // details. The result is up to four real roots y*, not all of which
+  // correspond to feasible points. The feasible points x(y*) have to be
+  // tested for optimality.
+
+  if (subspace_is_one_dimensional_) {
+    // The subspace is one-dimensional, so both the gradient and
+    // the Gauss-Newton step point towards the same direction.
+    // In this case, we move along the gradient until we reach the trust
+    // region boundary.
+    dogleg_step = -(radius_ / gradient_.norm()) * gradient_;
+    dogleg_step_norm_ = radius_;
+    dogleg_step.array() /= diagonal_.array();
+    VLOG(3) << "Dogleg subspace step size (1D): " << dogleg_step_norm_
+            << " radius: " << radius_;
+    return;
+  }
+
+  Vector2d minimum(0.0, 0.0);
+  if (!FindMinimumOnTrustRegionBoundary(&minimum)) {
+    // For the positive semi-definite case, a traditional dogleg step
+    // is taken in this case.
+    LOG(WARNING) << "Failed to compute polynomial roots. "
+                 << "Taking traditional dogleg step instead.";
+    ComputeTraditionalDoglegStep(dogleg);
+    return;
+  }
+
+  // Test first order optimality at the minimum.
+  // The first order KKT conditions state that the minimum x*
+  // has to satisfy either || x* ||^2 < r^2 (i.e. has to lie within
+  // the trust region), or
+  //
+  //   (B x* + g) + y x* = 0
+  //
+  // for some positive scalar y.
+  // Here, as it is already known that the minimum lies on the boundary, the
+  // latter condition is tested. To allow for small imprecisions, we test if
+  // the angle between (B x* + g) and -x* is smaller than acos(0.99).
+  // The exact value of the cosine is arbitrary but should be close to 1.
+  //
+  // This condition should not be violated. If it is, the minimum was not
+  // correctly determined.
+  const double kCosineThreshold = 0.99;
+  const Vector2d grad_minimum = subspace_B_ * minimum + subspace_g_;
+  const double cosine_angle = -minimum.dot(grad_minimum) /
+      (minimum.norm() * grad_minimum.norm());
+  if (cosine_angle < kCosineThreshold) {
+    LOG(WARNING) << "First order optimality seems to be violated "
+                 << "in the subspace method!\n"
+                 << "Cosine of angle between x and B x + g is "
+                 << cosine_angle << ".\n"
+                 << "Taking a regular dogleg step instead.\n"
+                 << "Please consider filing a bug report if this "
+                 << "happens frequently or consistently.\n";
+    ComputeTraditionalDoglegStep(dogleg);
+    return;
+  }
+
+  // Create the full step from the optimal 2d solution.
+  dogleg_step = subspace_basis_ * minimum;
+  dogleg_step_norm_ = radius_;
+  dogleg_step.array() /= diagonal_.array();
+  VLOG(3) << "Dogleg subspace step size: " << dogleg_step_norm_
+          << " radius: " << radius_;
+}
+
+// Build the polynomial that defines the optimal Lagrange multipliers.
+// Let the Lagrangian be
+//
+//   L(x, y) = 0.5 x^T B x + x^T g + y (0.5 x^T x - 0.5 r^2).       (1)
+//
+// Stationary points of the Lagrangian are given by
+//
+//   0 = d L(x, y) / dx = Bx + g + y x                              (2)
+//   0 = d L(x, y) / dy = 0.5 x^T x - 0.5 r^2                       (3)
+//
+// For any given y, we can solve (2) for x as
+//
+//   x(y) = -(B + y I)^-1 g .                                       (4)
+//
+// As B + y I is 2x2, we form the inverse explicitly:
+//
+//   (B + y I)^-1 = (1 / det(B + y I)) adj(B + y I)                 (5)
+//
+// where adj() denotes adjugation. This should be safe, as B is positive
+// semi-definite and y is necessarily positive, so (B + y I) is indeed
+// invertible.
+// Plugging (5) into (4) and the result into (3), then dividing by 0.5 we
+// obtain
+//
+//   0 = (1 / det(B + y I))^2 g^T adj(B + y I)^T adj(B + y I) g - r^2
+//                                                                  (6)
+//
+// or
+//
+//   det(B + y I)^2 r^2 = g^T adj(B + y I)^T adj(B + y I) g         (7a)
+//                      = g^T adj(B)^T adj(B) g
+//                           + 2 y g^T adj(B)^T g + y^2 g^T g       (7b)
+//
+// as
+//
+//   adj(B + y I) = adj(B) + y I = adj(B)^T + y I .                 (8)
+//
+// The left hand side can be expressed explicitly using
+//
+//   det(B + y I) = det(B) + y tr(B) + y^2 .                        (9)
+//
+// So (7) is a polynomial in y of degree four.
+// Bringing everything back to the left hand side, the coefficients can
+// be read off as
+//
+//     y^4  r^2
+//   + y^3  2 r^2 tr(B)
+//   + y^2 (r^2 tr(B)^2 + 2 r^2 det(B) - g^T g)
+//   + y^1 (2 r^2 det(B) tr(B) - 2 g^T adj(B)^T g)
+//   + y^0 (r^2 det(B)^2 - g^T adj(B)^T adj(B) g)
+//
+Vector DoglegStrategy::MakePolynomialForBoundaryConstrainedProblem() const {
+  const double detB = subspace_B_.determinant();
+  const double trB = subspace_B_.trace();
+  const double r2 = radius_ * radius_;
+  Matrix2d B_adj;
+  B_adj <<  subspace_B_(1,1) , -subspace_B_(0,1),
+            -subspace_B_(1,0) ,  subspace_B_(0,0);
+
+  Vector polynomial(5);
+  polynomial(0) = r2;
+  polynomial(1) = 2.0 * r2 * trB;
+  polynomial(2) = r2 * ( trB * trB + 2.0 * detB ) - subspace_g_.squaredNorm();
+  polynomial(3) = -2.0 * ( subspace_g_.transpose() * B_adj * subspace_g_
+      - r2 * detB * trB );
+  polynomial(4) = r2 * detB * detB - (B_adj * subspace_g_).squaredNorm();
+
+  return polynomial;
+}
+
+// Given a Lagrange multiplier y that corresponds to a stationary point
+// of the Lagrangian L(x, y), compute the corresponding x from the
+// equation
+//
+//   0 = d L(x, y) / dx
+//     = B * x + g + y * x
+//     = (B + y * I) * x + g
+//
+DoglegStrategy::Vector2d DoglegStrategy::ComputeSubspaceStepFromRoot(
+    double y) const {
+  const Matrix2d B_i = subspace_B_ + y * Matrix2d::Identity();
+  return -B_i.partialPivLu().solve(subspace_g_);
+}
+
+// This function evaluates the quadratic model at a point x in the
+// subspace spanned by subspace_basis_.
+double DoglegStrategy::EvaluateSubspaceModel(const Vector2d& x) const {
+  return 0.5 * x.dot(subspace_B_ * x) + subspace_g_.dot(x);
+}
+
+// This function attempts to solve the boundary-constrained subspace problem
+//
+//   min. 1/2 x^T B^T H B x + g^T B x
+//   s.t. || B x ||^2 = r^2
+//
+// where B is an orthonormal subspace basis and r is the trust-region radius.
+//
+// This is done by finding the roots of a fourth degree polynomial. If the
+// root finding fails, the function returns false and minimum will be set
+// to (0, 0). If it succeeds, true is returned.
+//
+// In the failure case, another step should be taken, such as the traditional
+// dogleg step.
+bool DoglegStrategy::FindMinimumOnTrustRegionBoundary(Vector2d* minimum) const {
+  CHECK_NOTNULL(minimum);
+
+  // Return (0, 0) in all error cases.
+  minimum->setZero();
+
+  // Create the fourth-degree polynomial that is a necessary condition for
+  // optimality.
+  const Vector polynomial = MakePolynomialForBoundaryConstrainedProblem();
+
+  // Find the real parts y_i of its roots (not only the real roots).
+  Vector roots_real;
+  if (!FindPolynomialRoots(polynomial, &roots_real, NULL)) {
+    // Failed to find the roots of the polynomial, i.e. the candidate
+    // solutions of the constrained problem. Report this back to the caller.
+    return false;
+  }
+
+  // For each root y, compute B x(y) and check for feasibility.
+  // Notice that there should always be four roots, as the leading term of
+  // the polynomial is r^2 and therefore non-zero. However, as some roots
+  // may be complex, the real parts are not necessarily unique.
+  double minimum_value = std::numeric_limits<double>::max();
+  bool valid_root_found = false;
+  for (int i = 0; i < roots_real.size(); ++i) {
+    const Vector2d x_i = ComputeSubspaceStepFromRoot(roots_real(i));
+
+    // Not all roots correspond to points on the trust region boundary.
+    // There are at most four candidate solutions. As we are interested
+    // in the minimum, it is safe to consider all of them after projecting
+    // them onto the trust region boundary.
+    if (x_i.norm() > 0) {
+      const double f_i = EvaluateSubspaceModel((radius_ / x_i.norm()) * x_i);
+      valid_root_found = true;
+      if (f_i < minimum_value) {
+        minimum_value = f_i;
+        *minimum = x_i;
+      }
+    }
+  }
+
+  return valid_root_found;
+}
+
+LinearSolver::Summary DoglegStrategy::ComputeGaussNewtonStep(
+    SparseMatrix* jacobian,
+    const double* residuals) {
+  const int n = jacobian->num_cols();
+  LinearSolver::Summary linear_solver_summary;
+  linear_solver_summary.termination_type = FAILURE;
+
+  // The Jacobian matrix is often quite poorly conditioned. Thus it is
+  // necessary to add a diagonal matrix at the bottom to prevent the
+  // linear solver from failing.
+  //
+  // We do this by computing the same diagonal matrix as the one used
+  // by Levenberg-Marquardt (other choices are possible), and scaling
+  // it by a small constant (independent of the trust region radius).
+  //
+  // If the solve fails, the multiplier to the diagonal is increased
+  // up to max_mu_ by a factor of mu_increase_factor_ every time. If
+  // the linear solver is still not successful, the strategy returns
+  // with FAILURE.
+  //
+  // Next time when a new Gauss-Newton step is requested, the
+  // multiplier starts out from the last successful solve.
+  //
+  // When a step is declared successful, the multiplier is decreased
+  // by half of mu_increase_factor_.
+
+  while (mu_ < max_mu_) {
+    // Dogleg, as far as I (sameeragarwal) understand it, requires a
+    // reasonably good estimate of the Gauss-Newton step. This means
+    // that we need to solve the normal equations more or less
+    // exactly. This is reflected in the values of the tolerances set
+    // below.
+    //
+    // For now, this strategy should only be used with exact
+    // factorization based solvers, for which these tolerances are
+    // automatically satisfied.
+    //
+    // The right way to combine inexact solves with trust region
+    // methods is to use Stiehaug's method.
+    LinearSolver::PerSolveOptions solve_options;
+    solve_options.q_tolerance = 0.0;
+    solve_options.r_tolerance = 0.0;
+
+    lm_diagonal_ = diagonal_ * std::sqrt(mu_);
+    solve_options.D = lm_diagonal_.data();
+
+    // As in the LevenbergMarquardtStrategy, solve Jy = r instead
+    // of Jx = -r and later set x = -y to avoid having to modify
+    // either jacobian or residuals.
+    InvalidateArray(n, gauss_newton_step_.data());
+    linear_solver_summary = linear_solver_->Solve(jacobian,
+                                                  residuals,
+                                                  solve_options,
+                                                  gauss_newton_step_.data());
+
+    if (linear_solver_summary.termination_type == FAILURE ||
+        !IsArrayValid(n, gauss_newton_step_.data())) {
+      mu_ *= mu_increase_factor_;
+      VLOG(2) << "Increasing mu " << mu_;
+      linear_solver_summary.termination_type = FAILURE;
+      continue;
+    }
+    break;
+  }
+
+  if (linear_solver_summary.termination_type != FAILURE) {
+    // The scaled Gauss-Newton step is D * GN:
+    //
+    //     - (D^-1 J^T J D^-1)^-1 (D^-1 g)
+    //   = - D (J^T J)^-1 D D^-1 g
+    //   = D -(J^T J)^-1 g
+    //
+    gauss_newton_step_.array() *= -diagonal_.array();
+  }
+
+  return linear_solver_summary;
+}
+
+void DoglegStrategy::StepAccepted(double step_quality) {
+  CHECK_GT(step_quality, 0.0);
+
+  if (step_quality < decrease_threshold_) {
+    radius_ *= 0.5;
+  }
+
+  if (step_quality > increase_threshold_) {
+    radius_ = max(radius_, 3.0 * dogleg_step_norm_);
+  }
+
+  // Reduce the regularization multiplier, in the hope that whatever
+  // was causing the rank deficiency has gone away and we can return
+  // to doing a pure Gauss-Newton solve.
+  mu_ = max(min_mu_, 2.0 * mu_ / mu_increase_factor_ );
+  reuse_ = false;
+}
+
+void DoglegStrategy::StepRejected(double step_quality) {
+  radius_ *= 0.5;
+  reuse_ = true;
+}
+
+void DoglegStrategy::StepIsInvalid() {
+  mu_ *= mu_increase_factor_;
+  reuse_ = false;
+}
+
+double DoglegStrategy::Radius() const {
+  return radius_;
+}
+
+bool DoglegStrategy::ComputeSubspaceModel(SparseMatrix* jacobian) {
+  // Compute an orthogonal basis for the subspace using QR decomposition.
+  Matrix basis_vectors(jacobian->num_cols(), 2);
+  basis_vectors.col(0) = gradient_;
+  basis_vectors.col(1) = gauss_newton_step_;
+  Eigen::ColPivHouseholderQR<Matrix> basis_qr(basis_vectors);
+
+  switch (basis_qr.rank()) {
+    case 0:
+      // This should never happen, as it implies that both the gradient
+      // and the Gauss-Newton step are zero. In this case, the minimizer should
+      // have stopped due to the gradient being too small.
+      LOG(ERROR) << "Rank of subspace basis is 0. "
+                 << "This means that the gradient at the current iterate is "
+                 << "zero but the optimization has not been terminated. "
+                 << "You may have found a bug in Ceres.";
+      return false;
+
+    case 1:
+      // Gradient and Gauss-Newton step coincide, so we lie on one of the
+      // major axes of the quadratic problem. In this case, we simply move
+      // along the gradient until we reach the trust region boundary.
+      subspace_is_one_dimensional_ = true;
+      return true;
+
+    case 2:
+      subspace_is_one_dimensional_ = false;
+      break;
+
+    default:
+      LOG(ERROR) << "Rank of the subspace basis matrix is reported to be "
+                 << "greater than 2. As the matrix contains only two "
+                 << "columns this cannot be true and is indicative of "
+                 << "a bug.";
+      return false;
+  }
+
+  // The subspace is two-dimensional, so compute the subspace model.
+  // Given the basis U, this is
+  //
+  //   subspace_g_ = g_scaled^T U
+  //
+  // and
+  //
+  //   subspace_B_ = U^T (J_scaled^T J_scaled) U
+  //
+  // As J_scaled = J * D^-1, the latter becomes
+  //
+  //   subspace_B_ = ((U^T D^-1) J^T) (J (D^-1 U))
+  //               = (J (D^-1 U))^T (J (D^-1 U))
+
+  subspace_basis_ =
+      basis_qr.householderQ() * Matrix::Identity(jacobian->num_cols(), 2);
+
+  subspace_g_ = subspace_basis_.transpose() * gradient_;
+
+  Eigen::Matrix<double, 2, Eigen::Dynamic, Eigen::RowMajor>
+      Jb(2, jacobian->num_rows());
+  Jb.setZero();
+
+  Vector tmp;
+  tmp = (subspace_basis_.col(0).array() / diagonal_.array()).matrix();
+  jacobian->RightMultiply(tmp.data(), Jb.row(0).data());
+  tmp = (subspace_basis_.col(1).array() / diagonal_.array()).matrix();
+  jacobian->RightMultiply(tmp.data(), Jb.row(1).data());
+
+  subspace_B_ = Jb * Jb.transpose();
+
+  return true;
+}
+
+}  // namespace internal
+}  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.h b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.h
new file mode 100644
index 00000000000..bff1689aa4a
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/dogleg_strategy.h
@@ -0,0 +1,163 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_INTERNAL_DOGLEG_STRATEGY_H_
+#define CERES_INTERNAL_DOGLEG_STRATEGY_H_
+
+#include "ceres/linear_solver.h"
+#include "ceres/trust_region_strategy.h"
+
+namespace ceres {
+namespace internal {
+
+// Dogleg step computation and trust region sizing strategy based on
+// on "Methods for Nonlinear Least Squares" by K. Madsen, H.B. Nielsen
+// and O. Tingleff. Available to download from
+//
+// http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf
+//
+// One minor modification is that instead of computing the pure
+// Gauss-Newton step, we compute a regularized version of it. This is
+// because the Jacobian is often rank-deficient and in such cases
+// using a direct solver leads to numerical failure.
+//
+// If SUBSPACE is passed as the type argument to the constructor, the
+// DoglegStrategy follows the approach by Shultz, Schnabel, Byrd.
+// This finds the exact optimum over the two-dimensional subspace
+// spanned by the two Dogleg vectors.
+class DoglegStrategy : public TrustRegionStrategy {
+public:
+  DoglegStrategy(const TrustRegionStrategy::Options& options);
+  virtual ~DoglegStrategy() {}
+
+  // TrustRegionStrategy interface
+  virtual Summary ComputeStep(const PerSolveOptions& per_solve_options,
+                              SparseMatrix* jacobian,
+                              const double* residuals,
+                              double* step);
+  virtual void StepAccepted(double step_quality);
+  virtual void StepRejected(double step_quality);
+  virtual void StepIsInvalid();
+
+  virtual double Radius() const;
+
+  // These functions are predominantly for testing.
+  Vector gradient() const { return gradient_; }
+  Vector gauss_newton_step() const { return gauss_newton_step_; }
+  Matrix subspace_basis() const { return subspace_basis_; }
+  Vector subspace_g() const { return subspace_g_; }
+  Matrix subspace_B() const { return subspace_B_; }
+
+ private:
+  typedef Eigen::Matrix<double, 2, 1, Eigen::DontAlign> Vector2d;
+  typedef Eigen::Matrix<double, 2, 2, Eigen::DontAlign> Matrix2d;
+
+  LinearSolver::Summary ComputeGaussNewtonStep(SparseMatrix* jacobian,
+                                               const double* residuals);
+  void ComputeCauchyPoint(SparseMatrix* jacobian);
+  void ComputeGradient(SparseMatrix* jacobian, const double* residuals);
+  void ComputeTraditionalDoglegStep(double* step);
+  bool ComputeSubspaceModel(SparseMatrix* jacobian);
+  void ComputeSubspaceDoglegStep(double* step);
+
+  bool FindMinimumOnTrustRegionBoundary(Vector2d* minimum) const;
+  Vector MakePolynomialForBoundaryConstrainedProblem() const;
+  Vector2d ComputeSubspaceStepFromRoot(double lambda) const;
+  double EvaluateSubspaceModel(const Vector2d& x) const;
+
+  LinearSolver* linear_solver_;
+  double radius_;
+  const double max_radius_;
+
+  const double min_diagonal_;
+  const double max_diagonal_;
+
+  // mu is used to scale the diagonal matrix used to make the
+  // Gauss-Newton solve full rank. In each solve, the strategy starts
+  // out with mu = min_mu, and tries values upto max_mu. If the user
+  // reports an invalid step, the value of mu_ is increased so that
+  // the next solve starts with a stronger regularization.
+  //
+  // If a successful step is reported, then the value of mu_ is
+  // decreased with a lower bound of min_mu_.
+  double mu_;
+  const double min_mu_;
+  const double max_mu_;
+  const double mu_increase_factor_;
+  const double increase_threshold_;
+  const double decrease_threshold_;
+
+  Vector diagonal_;  // sqrt(diag(J^T J))
+  Vector lm_diagonal_;
+
+  Vector gradient_;
+  Vector gauss_newton_step_;
+
+  // cauchy_step = alpha * gradient
+  double alpha_;
+  double dogleg_step_norm_;
+
+  // When, ComputeStep is called, reuse_ indicates whether the
+  // Gauss-Newton and Cauchy steps from the last call to ComputeStep
+  // can be reused or not.
+  //
+  // If the user called StepAccepted, then it is expected that the
+  // user has recomputed the Jacobian matrix and new Gauss-Newton
+  // solve is needed and reuse is set to false.
+  //
+  // If the user called StepRejected, then it is expected that the
+  // user wants to solve the trust region problem with the same matrix
+  // but a different trust region radius and the Gauss-Newton and
+  // Cauchy steps can be reused to compute the Dogleg, thus reuse is
+  // set to true.
+  //
+  // If the user called StepIsInvalid, then there was a numerical
+  // problem with the step computed in the last call to ComputeStep,
+  // and the regularization used to do the Gauss-Newton solve is
+  // increased and a new solve should be done when ComputeStep is
+  // called again, thus reuse is set to false.
+  bool reuse_;
+
+  // The dogleg type determines how the minimum of the local
+  // quadratic model is found.
+  DoglegType dogleg_type_;
+
+  // If the type is SUBSPACE_DOGLEG, the two-dimensional
+  // model 1/2 x^T B x + g^T x has to be computed and stored.
+  bool subspace_is_one_dimensional_;
+  Matrix subspace_basis_;
+  Vector2d subspace_g_;
+  Matrix2d subspace_B_;
+};
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_DOGLEG_STRATEGY_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/evaluator.cc b/extern/libmv/third_party/ceres/internal/ceres/evaluator.cc
index ea05aefec8c..a3ce6f04bd4 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/evaluator.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/evaluator.cc
@@ -28,14 +28,18 @@
 //
 // Author: keir@google.com (Keir Mierle)
 
-#include <glog/logging.h>
-#include "ceres/evaluator.h"
+#include <vector>
 #include "ceres/block_evaluate_preparer.h"
 #include "ceres/block_jacobian_writer.h"
 #include "ceres/compressed_row_jacobian_writer.h"
-#include "ceres/scratch_evaluate_preparer.h"
+#include "ceres/compressed_row_sparse_matrix.h"
+#include "ceres/crs_matrix.h"
 #include "ceres/dense_jacobian_writer.h"
+#include "ceres/evaluator.h"
+#include "ceres/internal/port.h"
 #include "ceres/program_evaluator.h"
+#include "ceres/scratch_evaluate_preparer.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -47,6 +51,7 @@ Evaluator* Evaluator::Create(const Evaluator::Options& options,
                              string* error) {
   switch (options.linear_solver_type) {
     case DENSE_QR:
+    case DENSE_NORMAL_CHOLESKY:
       return new ProgramEvaluator<ScratchEvaluatePreparer,
                                   DenseJacobianWriter>(options,
                                                        program);
@@ -67,5 +72,76 @@ Evaluator* Evaluator::Create(const Evaluator::Options& options,
   }
 }
 
+bool Evaluator::Evaluate(Program* program,
+                         int num_threads,
+                         double* cost,
+                         vector<double>* residuals,
+                         vector<double>* gradient,
+                         CRSMatrix* output_jacobian) {
+  CHECK_GE(num_threads, 1)
+      << "This is a Ceres bug; please contact the developers!";
+  CHECK_NOTNULL(cost);
+
+  // Setup the Parameter indices and offsets before an evaluator can
+  // be constructed and used.
+  program->SetParameterOffsetsAndIndex();
+
+  Evaluator::Options evaluator_options;
+  evaluator_options.linear_solver_type = SPARSE_NORMAL_CHOLESKY;
+  evaluator_options.num_threads = num_threads;
+
+  string error;
+  scoped_ptr<Evaluator> evaluator(
+      Evaluator::Create(evaluator_options, program, &error));
+  if (evaluator.get() == NULL) {
+    LOG(ERROR) << "Unable to create an Evaluator object. "
+               << "Error: " << error
+               << "This is a Ceres bug; please contact the developers!";
+    return false;
+  }
+
+  if (residuals !=NULL) {
+    residuals->resize(evaluator->NumResiduals());
+  }
+
+  if (gradient != NULL) {
+    gradient->resize(evaluator->NumEffectiveParameters());
+  }
+
+  scoped_ptr<CompressedRowSparseMatrix> jacobian;
+  if (output_jacobian != NULL) {
+    jacobian.reset(
+        down_cast<CompressedRowSparseMatrix*>(evaluator->CreateJacobian()));
+  }
+
+  // Point the state pointers to the user state pointers. This is
+  // needed so that we can extract a parameter vector which is then
+  // passed to Evaluator::Evaluate.
+  program->SetParameterBlockStatePtrsToUserStatePtrs();
+
+  // Copy the value of the parameter blocks into a vector, since the
+  // Evaluate::Evaluate method needs its input as such. The previous
+  // call to SetParameterBlockStatePtrsToUserStatePtrs ensures that
+  // these values are the ones corresponding to the actual state of
+  // the parameter blocks, rather than the temporary state pointer
+  // used for evaluation.
+  Vector parameters(program->NumParameters());
+  program->ParameterBlocksToStateVector(parameters.data());
+
+  if (!evaluator->Evaluate(parameters.data(),
+                           cost,
+                           residuals != NULL ? &(*residuals)[0] : NULL,
+                           gradient != NULL ? &(*gradient)[0] : NULL,
+                           jacobian.get())) {
+    return false;
+  }
+
+  if (output_jacobian != NULL) {
+    jacobian->ToCRSMatrix(output_jacobian);
+  }
+
+  return true;
+}
+
 }  // namespace internal
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/evaluator.h b/extern/libmv/third_party/ceres/internal/ceres/evaluator.h
index adefdd26660..6aa30d7b739 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/evaluator.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/evaluator.h
@@ -33,10 +33,14 @@
 #define CERES_INTERNAL_EVALUATOR_H_
 
 #include <string>
+#include <vector>
 #include "ceres/internal/port.h"
 #include "ceres/types.h"
 
 namespace ceres {
+
+class CRSMatrix;
+
 namespace internal {
 
 class Program;
@@ -65,6 +69,32 @@ class Evaluator {
                            Program* program,
                            string* error);
 
+
+  // This is used for computing the cost, residual and Jacobian for
+  // returning to the user. For actually solving the optimization
+  // problem, the optimization algorithm uses the ProgramEvaluator
+  // objects directly.
+  //
+  // The residual, gradients and jacobian pointers can be NULL, in
+  // which case they will not be evaluated. cost cannot be NULL.
+  //
+  // The parallelism of the evaluator is controlled by num_threads; it
+  // should be at least 1.
+  //
+  // Note: That this function does not take a parameter vector as
+  // input. The parameter blocks are evaluated on the values contained
+  // in the arrays pointed to by their user_state pointers.
+  //
+  // Also worth noting is that this function mutates program by
+  // calling Program::SetParameterOffsetsAndIndex() on it so that an
+  // evaluator object can be constructed.
+  static bool Evaluate(Program* program,
+                       int num_threads,
+                       double* cost,
+                       vector<double>* residuals,
+                       vector<double>* gradient,
+                       CRSMatrix* jacobian);
+
   // Build and return a sparse matrix for storing and working with the Jacobian
   // of the objective function. The jacobian has dimensions
   // NumEffectiveParameters() by NumParameters(), and is typically extremely
@@ -95,6 +125,7 @@ class Evaluator {
   virtual bool Evaluate(const double* state,
                         double* cost,
                         double* residuals,
+                        double* gradient,
                         SparseMatrix* jacobian) = 0;
 
   // Make a change delta (of size NumEffectiveParameters()) to state (of size
diff --git a/extern/libmv/third_party/ceres/internal/ceres/file.cc b/extern/libmv/third_party/ceres/internal/ceres/file.cc
index 5fc9d220861..6fe7557246d 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/file.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/file.cc
@@ -31,7 +31,8 @@
 // Really simple file IO.
 
 #include <cstdio>
-#include <glog/logging.h>
+#include "file.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -48,7 +49,7 @@ void WriteStringToFileOrDie(const string &data, const string &filename) {
 }
 
 void ReadFileToStringOrDie(const string &filename, string *data) {
-  FILE* file_descriptor = file_descriptor = fopen(filename.c_str(), "r");
+  FILE* file_descriptor = fopen(filename.c_str(), "r");
 
   if (!file_descriptor) {
     LOG(FATAL) << "Couldn't read file: " << filename;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/generate_eliminator_specialization.py b/extern/libmv/third_party/ceres/internal/ceres/generate_eliminator_specialization.py
new file mode 100644
index 00000000000..af9873f94c0
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/generate_eliminator_specialization.py
@@ -0,0 +1,186 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+#
+# Copyright 2011 Google Inc. All Rights Reserved.
+# Author: sameeragarwal@google.com (Sameer Agarwal)
+#
+# Script for explicitly generating template specialization of the
+# SchurEliminator class. It is a rather large class
+# and the number of explicit instantiations is also large. Explicitly
+# generating these instantiations in separate .cc files breaks the
+# compilation into separate compilation unit rather than one large cc
+# file which takes 2+GB of RAM to compile.
+#
+# This script creates two sets of files.
+#
+# 1. schur_eliminator_x_x_x.cc
+# where, the x indicates the template parameters and
+#
+# 2. schur_eliminator.cc
+#
+# that contains a factory function for instantiating these classes
+# based on runtime parameters.
+#
+# The list of tuples, specializations indicates the set of
+# specializations that is generated.
+
+# Set of template specializations to generate
+SPECIALIZATIONS = [(2, 2, 2),
+                   (2, 2, 3),
+                   (2, 2, 4),
+                   (2, 2, "Dynamic"),
+                   (2, 3, 3),
+                   (2, 3, 4),
+                   (2, 3, 9),
+                   (2, 3, "Dynamic"),
+                   (2, 4, 3),
+                   (2, 4, 4),
+                   (2, 4, "Dynamic"),
+                   (4, 4, 2),
+                   (4, 4, 3),
+                   (4, 4, 4),
+                   (4, 4, "Dynamic"),
+                   ("Dynamic", "Dynamic", "Dynamic")]
+
+SPECIALIZATION_FILE = """// Copyright 2011 Google Inc. All Rights Reserved.
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+//
+// Template specialization of SchurEliminator.
+//
+// ========================================
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+//=========================================
+//
+// This file is generated using generate_eliminator_specializations.py.
+// Editing it manually is not recommended.
+
+#include "ceres/schur_eliminator_impl.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+template class SchurEliminator<%s, %s, %s>;
+
+}  // namespace internal
+}  // namespace ceres
+
+"""
+
+FACTORY_FILE_HEADER = """// Copyright 2011 Google Inc. All Rights Reserved.
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+//
+// ========================================
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+// THIS FILE IS AUTOGENERATED. DO NOT EDIT.
+//=========================================
+//
+// This file is generated using generate_template_specializations.py.
+// Editing it manually is not recommended.
+
+#include "ceres/linear_solver.h"
+#include "ceres/schur_eliminator.h"
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+SchurEliminatorBase*
+SchurEliminatorBase::Create(const LinearSolver::Options& options) {
+#ifndef CERES_RESTRICT_SCHUR_SPECIALIZATION
+"""
+
+FACTORY_CONDITIONAL = """  if ((options.row_block_size == %s) &&
+      (options.e_block_size == %s) &&
+      (options.f_block_size == %s)) {
+    return new SchurEliminator<%s, %s, %s>(options);
+  }
+"""
+
+FACTORY_FOOTER = """
+#endif
+  VLOG(1) << "Template specializations not found for <"
+          << options.row_block_size << ","
+          << options.e_block_size << ","
+          << options.f_block_size << ">";
+  return new SchurEliminator<Dynamic, Dynamic, Dynamic>(options);
+}
+
+}  // namespace internal
+}  // namespace ceres
+"""
+
+
+def SuffixForSize(size):
+  if size == "Dynamic":
+    return "d"
+  return str(size)
+
+
+def SpecializationFilename(prefix, row_block_size, e_block_size, f_block_size):
+  return "_".join([prefix] + map(SuffixForSize, (row_block_size,
+                                                 e_block_size,
+                                                 f_block_size)))
+
+
+def Specialize():
+  """
+  Generate specialization code and the conditionals to instantiate it.
+  """
+  f = open("schur_eliminator.cc", "w")
+  f.write(FACTORY_FILE_HEADER)
+
+  for row_block_size, e_block_size, f_block_size in SPECIALIZATIONS:
+    output = SpecializationFilename("generated/schur_eliminator",
+                                    row_block_size,
+                                    e_block_size,
+                                    f_block_size) + ".cc"
+    fptr = open(output, "w")
+    fptr.write(SPECIALIZATION_FILE % (row_block_size,
+                                      e_block_size,
+                                      f_block_size))
+    fptr.close()
+
+    f.write(FACTORY_CONDITIONAL % (row_block_size,
+                                   e_block_size,
+                                   f_block_size,
+                                   row_block_size,
+                                   e_block_size,
+                                   f_block_size))
+  f.write(FACTORY_FOOTER)
+  f.close()
+
+
+if __name__ == "__main__":
+  Specialize()
diff --git a/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.cc b/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.cc
index abba40824ef..7fb3ed7b3a8 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/gradient_checking_cost_function.cc
@@ -36,18 +36,18 @@
 #include <string>
 #include <vector>
 
-#include <glog/logging.h>
+#include "ceres/cost_function.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
 #include "ceres/parameter_block.h"
+#include "ceres/problem.h"
 #include "ceres/problem_impl.h"
 #include "ceres/program.h"
 #include "ceres/residual_block.h"
 #include "ceres/runtime_numeric_diff_cost_function.h"
 #include "ceres/stringprintf.h"
-#include "ceres/cost_function.h"
-#include "ceres/internal/eigen.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "ceres/problem.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/graph.h b/extern/libmv/third_party/ceres/internal/ceres/graph.h
index fd7a224f0aa..2c0f6d28e54 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/graph.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/graph.h
@@ -129,7 +129,7 @@ class Graph {
   HashMap<Vertex, HashSet<Vertex> > edges_;
   HashMap<pair<Vertex, Vertex>, double> edge_weights_;
 
-  DISALLOW_COPY_AND_ASSIGN(Graph);
+  CERES_DISALLOW_COPY_AND_ASSIGN(Graph);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.cc b/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.cc
index bd908846362..4af030a8535 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.cc
@@ -30,22 +30,20 @@
 
 #include "ceres/implicit_schur_complement.h"
 
-#include <glog/logging.h>
 #include "Eigen/Dense"
 #include "ceres/block_sparse_matrix.h"
 #include "ceres/block_structure.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/scoped_ptr.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
 
 ImplicitSchurComplement::ImplicitSchurComplement(int num_eliminate_blocks,
-                                                 bool constant_sparsity,
                                                  bool preconditioner)
     : num_eliminate_blocks_(num_eliminate_blocks),
-      constant_sparsity_(constant_sparsity),
       preconditioner_(preconditioner),
       A_(NULL),
       D_(NULL),
@@ -62,7 +60,7 @@ void ImplicitSchurComplement::Init(const BlockSparseMatrixBase& A,
                                    const double* b) {
   // Since initialization is reasonably heavy, perhaps we can save on
   // constructing a new object everytime.
-  if ((A_ == NULL) || !constant_sparsity_) {
+  if (A_ == NULL) {
     A_.reset(new PartitionedMatrixView(A, num_eliminate_blocks_));
   }
 
@@ -71,7 +69,7 @@ void ImplicitSchurComplement::Init(const BlockSparseMatrixBase& A,
 
   // Initialize temporary storage and compute the block diagonals of
   // E'E and F'E.
-  if ((!constant_sparsity_) || (block_diagonal_EtE_inverse_ == NULL)) {
+  if (block_diagonal_EtE_inverse_ == NULL) {
     block_diagonal_EtE_inverse_.reset(A_->CreateBlockDiagonalEtE());
     if (preconditioner_) {
       block_diagonal_FtF_inverse_.reset(A_->CreateBlockDiagonalFtF());
@@ -92,17 +90,10 @@ void ImplicitSchurComplement::Init(const BlockSparseMatrixBase& A,
   // The block diagonals of the augmented linear system contain
   // contributions from the diagonal D if it is non-null. Add that to
   // the block diagonals and invert them.
-  if (D_ != NULL)  {
-    AddDiagonalAndInvert(D_, block_diagonal_EtE_inverse_.get());
-    if (preconditioner_) {
-      AddDiagonalAndInvert(D_ + A_->num_cols_e(),
-                           block_diagonal_FtF_inverse_.get());
-    }
-  } else {
-    AddDiagonalAndInvert(NULL, block_diagonal_EtE_inverse_.get());
-    if (preconditioner_) {
-      AddDiagonalAndInvert(NULL, block_diagonal_FtF_inverse_.get());
-    }
+  AddDiagonalAndInvert(D_, block_diagonal_EtE_inverse_.get());
+  if (preconditioner_)  {
+    AddDiagonalAndInvert((D_ ==  NULL) ? NULL : D_ + A_->num_cols_e(),
+                         block_diagonal_FtF_inverse_.get());
   }
 
   // Compute the RHS of the Schur complement system.
diff --git a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.h b/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.h
index 37a319f9c57..b9ebaa4628e 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/implicit_schur_complement.h
@@ -91,20 +91,13 @@ class ImplicitSchurComplement : public LinearOperator {
   // num_eliminate_blocks is the number of E blocks in the matrix
   // A.
   //
-  // constant_sparsity indicates if across calls to Init, the sparsity
-  // structure of the matrix A remains constant or not. This makes for
-  // significant savings across multiple matrices A, e.g. when used in
-  // conjunction with an optimization algorithm.
-  //
   // preconditioner indicates whether the inverse of the matrix F'F
   // should be computed or not as a preconditioner for the Schur
   // Complement.
   //
   // TODO(sameeragarwal): Get rid of the two bools below and replace
   // them with enums.
-  ImplicitSchurComplement(int num_eliminate_blocks,
-                          bool constant_sparsity,
-                          bool preconditioner);
+  ImplicitSchurComplement(int num_eliminate_blocks, bool preconditioner);
   virtual ~ImplicitSchurComplement();
 
   // Initialize the Schur complement for a linear least squares
@@ -151,7 +144,6 @@ class ImplicitSchurComplement : public LinearOperator {
   void UpdateRhs();
 
   int num_eliminate_blocks_;
-  bool constant_sparsity_;
   bool preconditioner_;
 
   scoped_ptr<PartitionedMatrixView> A_;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.cc
index 51303195317..679c41f2431 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/iterative_schur_complement_solver.cc
@@ -33,22 +33,18 @@
 #include <algorithm>
 #include <cstring>
 #include <vector>
-
-#include <glog/logging.h>
 #include "Eigen/Dense"
 #include "ceres/block_sparse_matrix.h"
 #include "ceres/block_structure.h"
 #include "ceres/conjugate_gradients_solver.h"
 #include "ceres/implicit_schur_complement.h"
-#include "ceres/linear_solver.h"
-#include "ceres/triplet_sparse_matrix.h"
-#include "ceres/visibility_based_preconditioner.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/scoped_ptr.h"
 #include "ceres/linear_solver.h"
 #include "ceres/triplet_sparse_matrix.h"
 #include "ceres/types.h"
 #include "ceres/visibility_based_preconditioner.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -69,10 +65,9 @@ LinearSolver::Summary IterativeSchurComplementSolver::SolveImpl(
   CHECK_NOTNULL(A->block_structure());
 
   // Initialize a ImplicitSchurComplement object.
-  if ((schur_complement_ == NULL) || (!options_.constant_sparsity)) {
+  if (schur_complement_ == NULL) {
     schur_complement_.reset(
         new ImplicitSchurComplement(options_.num_eliminate_blocks,
-                                    options_.constant_sparsity,
                                     options_.preconditioner_type == JACOBI));
   }
   schur_complement_->Init(*A, per_solve_options.D, b);
@@ -119,7 +114,7 @@ LinearSolver::Summary IterativeSchurComplementSolver::SolveImpl(
             new VisibilityBasedPreconditioner(*A->block_structure(), options_));
       }
       is_preconditioner_good =
-          visibility_based_preconditioner_->Compute(*A, per_solve_options.D);
+          visibility_based_preconditioner_->Update(*A, per_solve_options.D);
       cg_per_solve_options.preconditioner =
           visibility_based_preconditioner_.get();
       break;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt.cc b/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt.cc
deleted file mode 100644
index b40a5162adc..00000000000
--- a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt.cc
+++ /dev/null
@@ -1,574 +0,0 @@
-// Ceres Solver - A fast non-linear least squares minimizer
-// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
-// http://code.google.com/p/ceres-solver/
-//
-// 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 Google Inc. 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.
-//
-// Author: sameeragarwal@google.com (Sameer Agarwal)
-//
-// Implementation of a simple LM algorithm which uses the step sizing
-// rule of "Methods for Nonlinear Least Squares" by K. Madsen,
-// H.B. Nielsen and O. Tingleff. Available to download from
-//
-// http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf
-//
-// The basic algorithm described in this note is an exact step
-// algorithm that depends on the Newton(LM) step being solved exactly
-// in each iteration. When a suitable iterative solver is available to
-// solve the Newton(LM) step, the algorithm will automatically switch
-// to an inexact step solution method. This trades some slowdown in
-// convergence for significant savings in solve time and memory
-// usage. Our implementation of the Truncated Newton algorithm follows
-// the discussion and recommendataions in "Stephen G. Nash, A Survey
-// of Truncated Newton Methods, Journal of Computational and Applied
-// Mathematics, 124(1-2), 45-59, 2000.
-
-#include "ceres/levenberg_marquardt.h"
-
-#include <algorithm>
-#include <cstdlib>
-#include <cmath>
-#include <cstring>
-#include <string>
-#include <vector>
-
-#include <glog/logging.h>
-#include "Eigen/Core"
-#include "ceres/evaluator.h"
-#include "ceres/file.h"
-#include "ceres/linear_least_squares_problems.h"
-#include "ceres/linear_solver.h"
-#include "ceres/matrix_proto.h"
-#include "ceres/sparse_matrix.h"
-#include "ceres/stringprintf.h"
-#include "ceres/internal/eigen.h"
-#include "ceres/internal/scoped_ptr.h"
-#include "ceres/types.h"
-
-namespace ceres {
-namespace internal {
-namespace {
-
-// Numbers for clamping the size of the LM diagonal. The size of these
-// numbers is heuristic. We will probably be adjusting them in the
-// future based on more numerical experience. With jacobi scaling
-// enabled, these numbers should be all but redundant.
-const double kMinLevenbergMarquardtDiagonal = 1e-6;
-const double kMaxLevenbergMarquardtDiagonal = 1e32;
-
-// Small constant for various floating point issues.
-const double kEpsilon = 1e-12;
-
-// Number of times the linear solver should be retried in case of
-// numerical failure. The retries are done by exponentially scaling up
-// mu at each retry. This leads to stronger and stronger
-// regularization making the linear least squares problem better
-// conditioned at each retry.
-const int kMaxLinearSolverRetries = 5;
-
-// D = 1/sqrt(diag(J^T * J))
-void EstimateScale(const SparseMatrix& jacobian, double* D) {
-  CHECK_NOTNULL(D);
-  jacobian.SquaredColumnNorm(D);
-  for (int i = 0; i < jacobian.num_cols(); ++i) {
-    D[i] = 1.0 / (kEpsilon + sqrt(D[i]));
-  }
-}
-
-// D = diag(J^T * J)
-void LevenbergMarquardtDiagonal(const SparseMatrix& jacobian,
-                                double* D) {
-  CHECK_NOTNULL(D);
-  jacobian.SquaredColumnNorm(D);
-  for (int i = 0; i < jacobian.num_cols(); ++i) {
-    D[i] = min(max(D[i], kMinLevenbergMarquardtDiagonal),
-               kMaxLevenbergMarquardtDiagonal);
-  }
-}
-
-bool RunCallback(IterationCallback* callback,
-                 const IterationSummary& iteration_summary,
-                 Solver::Summary* summary) {
-  const CallbackReturnType status = (*callback)(iteration_summary);
-  switch (status) {
-    case SOLVER_TERMINATE_SUCCESSFULLY:
-      summary->termination_type = USER_SUCCESS;
-      VLOG(1) << "Terminating on USER_SUCCESS.";
-      return false;
-    case SOLVER_ABORT:
-      summary->termination_type = USER_ABORT;
-      VLOG(1) << "Terminating on USER_ABORT.";
-      return false;
-    case SOLVER_CONTINUE:
-      return true;
-    default:
-      LOG(FATAL) << "Unknown status returned by callback: "
-                 << status;
-	  return NULL;
-  }
-}
-
-}  // namespace
-
-LevenbergMarquardt::~LevenbergMarquardt() {}
-
-void LevenbergMarquardt::Minimize(const Minimizer::Options& options,
-                                  Evaluator* evaluator,
-                                  LinearSolver* linear_solver,
-                                  const double* initial_parameters,
-                                  double* final_parameters,
-                                  Solver::Summary* summary) {
-  time_t start_time = time(NULL);
-  const int num_parameters = evaluator->NumParameters();
-  const int num_effective_parameters = evaluator->NumEffectiveParameters();
-  const int num_residuals = evaluator->NumResiduals();
-
-  summary->termination_type = NO_CONVERGENCE;
-  summary->num_successful_steps = 0;
-  summary->num_unsuccessful_steps = 0;
-
-  // Allocate the various vectors needed by the algorithm.
-  memcpy(final_parameters, initial_parameters,
-         num_parameters * sizeof(*initial_parameters));
-
-  VectorRef x(final_parameters, num_parameters);
-  Vector x_new(num_parameters);
-
-  Vector lm_step(num_effective_parameters);
-  Vector gradient(num_effective_parameters);
-  Vector scaled_gradient(num_effective_parameters);
-  // Jacobi scaling vector
-  Vector scale(num_effective_parameters);
-
-  Vector f_model(num_residuals);
-  Vector f(num_residuals);
-  Vector f_new(num_residuals);
-  Vector D(num_parameters);
-  Vector muD(num_parameters);
-
-  // Ask the Evaluator to create the jacobian matrix. The sparsity
-  // pattern of this matrix is going to remain constant, so we only do
-  // this once and then re-use this matrix for all subsequent Jacobian
-  // computations.
-  scoped_ptr<SparseMatrix> jacobian(evaluator->CreateJacobian());
-
-  double x_norm  = x.norm();
-
-  double cost = 0.0;
-  D.setOnes();
-  f.setZero();
-
-  // Do initial cost and Jacobian evaluation.
-  if (!evaluator->Evaluate(x.data(), &cost, f.data(), jacobian.get())) {
-    LOG(WARNING) << "Failed to compute residuals and Jacobian. "
-                 << "Terminating.";
-    summary->termination_type = NUMERICAL_FAILURE;
-    return;
-  }
-
-  if (options.jacobi_scaling) {
-    EstimateScale(*jacobian, scale.data());
-    jacobian->ScaleColumns(scale.data());
-  } else {
-    scale.setOnes();
-  }
-
-  // This is a poor way to do this computation. Even if fixed_cost is
-  // zero, because we are subtracting two possibly large numbers, we
-  // are depending on exact cancellation to give us a zero here. But
-  // initial_cost and cost have been computed by two different
-  // evaluators. One which runs on the whole problem (in
-  // solver_impl.cc) in single threaded mode and another which runs
-  // here on the reduced problem, so fixed_cost can (and does) contain
-  // some numerical garbage with a relative magnitude of 1e-14.
-  //
-  // The right way to do this, would be to compute the fixed cost on
-  // just the set of residual blocks which are held constant and were
-  // removed from the original problem when the reduced problem was
-  // constructed.
-  summary->fixed_cost = summary->initial_cost - cost;
-
-  double model_cost = f.squaredNorm() / 2.0;
-  double total_cost = summary->fixed_cost + cost;
-
-  scaled_gradient.setZero();
-  jacobian->LeftMultiply(f.data(), scaled_gradient.data());
-  gradient = scaled_gradient.array() / scale.array();
-
-  double gradient_max_norm = gradient.lpNorm<Eigen::Infinity>();
-  // We need the max here to guard againt the gradient being zero.
-  const double gradient_max_norm_0 = max(gradient_max_norm, kEpsilon);
-  double gradient_tolerance = options.gradient_tolerance * gradient_max_norm_0;
-
-  double mu = options.tau;
-  double nu = 2.0;
-  int iteration = 0;
-  double actual_cost_change = 0.0;
-  double step_norm = 0.0;
-  double relative_decrease = 0.0;
-
-  // Insane steps are steps which are not sane, i.e. there is some
-  // numerical kookiness going on with them. There are various reasons
-  // for this kookiness, some easier to diagnose then others. From the
-  // point of view of the non-linear solver, they are steps which
-  // cannot be used. We return with NUMERICAL_FAILURE after
-  // kMaxLinearSolverRetries consecutive insane steps.
-  bool step_is_sane = false;
-  int num_consecutive_insane_steps = 0;
-
-  // Whether the step resulted in a sufficient decrease in the
-  // objective function when compared to the decrease in the value of
-  // the lineariztion.
-  bool step_is_successful = false;
-
-  // Parse the iterations for which to dump the linear problem.
-  vector<int> iterations_to_dump = options.lsqp_iterations_to_dump;
-  sort(iterations_to_dump.begin(), iterations_to_dump.end());
-
-  IterationSummary iteration_summary;
-  iteration_summary.iteration = iteration;
-  iteration_summary.step_is_successful = false;
-  iteration_summary.cost = total_cost;
-  iteration_summary.cost_change = actual_cost_change;
-  iteration_summary.gradient_max_norm = gradient_max_norm;
-  iteration_summary.step_norm = step_norm;
-  iteration_summary.relative_decrease = relative_decrease;
-  iteration_summary.mu = mu;
-  iteration_summary.eta = options.eta;
-  iteration_summary.linear_solver_iterations = 0;
-  iteration_summary.linear_solver_time_sec = 0.0;
-  iteration_summary.iteration_time_sec = (time(NULL) - start_time);
-  if (options.logging_type >= PER_MINIMIZER_ITERATION) {
-    summary->iterations.push_back(iteration_summary);
-  }
-
-  // Check if the starting point is an optimum.
-  VLOG(2) << "Gradient max norm: " << gradient_max_norm
-          << " tolerance: " << gradient_tolerance
-          << " ratio: " << gradient_max_norm / gradient_max_norm_0
-          << " tolerance: " << options.gradient_tolerance;
-  if (gradient_max_norm <= gradient_tolerance) {
-    summary->termination_type = GRADIENT_TOLERANCE;
-    VLOG(1) << "Terminating on GRADIENT_TOLERANCE. "
-            << "Relative gradient max norm: "
-            << gradient_max_norm / gradient_max_norm_0
-            << " <= " << options.gradient_tolerance;
-    return;
-  }
-
-  // Call the various callbacks.
-  for (int i = 0; i < options.callbacks.size(); ++i) {
-    if (!RunCallback(options.callbacks[i], iteration_summary, summary)) {
-      return;
-    }
-  }
-
-  // We only need the LM diagonal if we are actually going to do at
-  // least one iteration of the optimization. So we wait to do it
-  // until now.
-  LevenbergMarquardtDiagonal(*jacobian, D.data());
-
-  while ((iteration < options.max_num_iterations) &&
-         (time(NULL) - start_time) <= options.max_solver_time_sec) {
-    time_t iteration_start_time = time(NULL);
-    step_is_sane = false;
-    step_is_successful = false;
-
-    IterationSummary iteration_summary;
-    // The while loop here is just to provide an easily breakable
-    // control structure. We are guaranteed to always exit this loop
-    // at the end of one iteration or before.
-    while (1) {
-      muD = (mu * D).array().sqrt();
-      LinearSolver::PerSolveOptions solve_options;
-      solve_options.D = muD.data();
-      solve_options.q_tolerance = options.eta;
-      // Disable r_tolerance checking. Since we only care about
-      // termination via the q_tolerance. As Nash and Sofer show,
-      // r_tolerance based termination is essentially useless in
-      // Truncated Newton methods.
-      solve_options.r_tolerance = -1.0;
-
-      const time_t linear_solver_start_time = time(NULL);
-      LinearSolver::Summary linear_solver_summary =
-          linear_solver->Solve(jacobian.get(),
-                               f.data(),
-                               solve_options,
-                               lm_step.data());
-      iteration_summary.linear_solver_time_sec =
-          (time(NULL) - linear_solver_start_time);
-      iteration_summary.linear_solver_iterations =
-          linear_solver_summary.num_iterations;
-
-      if (binary_search(iterations_to_dump.begin(),
-                        iterations_to_dump.end(),
-                        iteration)) {
-        CHECK(DumpLinearLeastSquaresProblem(options.lsqp_dump_directory,
-                                            iteration,
-                                            options.lsqp_dump_format_type,
-                                            jacobian.get(),
-                                            muD.data(),
-                                            f.data(),
-                                            lm_step.data(),
-                                            options.num_eliminate_blocks))
-            << "Tried writing linear least squares problem: " 
-            << options.lsqp_dump_directory
-            << " but failed.";
-      }
-
-      // We ignore the case where the linear solver did not converge,
-      // since the partial solution computed by it still maybe of use,
-      // and there is no reason to ignore it, especially since we
-      // spent so much time computing it.
-      if ((linear_solver_summary.termination_type != TOLERANCE) &&
-          (linear_solver_summary.termination_type != MAX_ITERATIONS)) {
-        VLOG(1) << "Linear solver failure: retrying with a higher mu";
-        break;
-      }
-
-      step_norm = (lm_step.array() * scale.array()).matrix().norm();
-
-      // Check step length based convergence. If the step length is
-      // too small, then we are done.
-      const double step_size_tolerance =  options.parameter_tolerance *
-          (x_norm + options.parameter_tolerance);
-
-      VLOG(2) << "Step size: " << step_norm
-              << " tolerance: " <<  step_size_tolerance
-              << " ratio: " << step_norm / step_size_tolerance
-              << " tolerance: " << options.parameter_tolerance;
-      if (step_norm <= options.parameter_tolerance *
-          (x_norm + options.parameter_tolerance)) {
-        summary->termination_type = PARAMETER_TOLERANCE;
-        VLOG(1) << "Terminating on PARAMETER_TOLERANCE."
-                << "Relative step size: " << step_norm / step_size_tolerance
-            << " <= " << options.parameter_tolerance;
-        return;
-      }
-
-      Vector delta =  -(lm_step.array() * scale.array()).matrix();
-      if (!evaluator->Plus(x.data(), delta.data(), x_new.data())) {
-        LOG(WARNING) << "Failed to compute Plus(x, delta, x_plus_delta). "
-                     << "Terminating.";
-        summary->termination_type = NUMERICAL_FAILURE;
-        return;
-      }
-
-      double cost_new = 0.0;
-      if (!evaluator->Evaluate(x_new.data(), &cost_new, NULL, NULL)) {
-        LOG(WARNING) << "Failed to compute the value of the objective "
-                     << "function. Terminating.";
-        summary->termination_type = NUMERICAL_FAILURE;
-        return;
-      }
-
-      f_model.setZero();
-      jacobian->RightMultiply(lm_step.data(), f_model.data());
-      const double model_cost_new =
-          (f.segment(0, num_residuals) - f_model).squaredNorm() / 2;
-
-      actual_cost_change = cost - cost_new;
-      double model_cost_change = model_cost - model_cost_new;
-
-      VLOG(2) << "[Model cost] current: " << model_cost
-              << " new : " << model_cost_new
-              << " change: " << model_cost_change;
-
-      VLOG(2) << "[Nonlinear cost] current: " << cost
-              << " new : " << cost_new
-              << " change: " << actual_cost_change
-              << " relative change: " << fabs(actual_cost_change) / cost
-              << " tolerance: " << options.function_tolerance;
-
-      // In exact arithmetic model_cost_change should never be
-      // negative. But due to numerical precision issues, we may end up
-      // with a small negative number. model_cost_change which are
-      // negative and large in absolute value are indicative of a
-      // numerical failure in the solver.
-      if (model_cost_change < -kEpsilon) {
-        VLOG(1) << "Model cost change is negative.\n"
-                << "Current : " << model_cost
-                << " new : " << model_cost_new
-                << " change: " << model_cost_change << "\n";
-        break;
-      }
-
-      // If we have reached this far, then we are willing to trust the
-      // numerical quality of the step.
-      step_is_sane = true;
-      num_consecutive_insane_steps = 0;
-
-      // Check function value based convergence.
-      if (fabs(actual_cost_change) < options.function_tolerance * cost) {
-        VLOG(1) << "Termination on FUNCTION_TOLERANCE."
-                << " Relative cost change: " << fabs(actual_cost_change) / cost
-                << " tolerance: " << options.function_tolerance;
-        summary->termination_type = FUNCTION_TOLERANCE;
-        return;
-      }
-
-      // Clamp model_cost_change at kEpsilon from below.
-      if (model_cost_change < kEpsilon) {
-        VLOG(1) << "Clamping model cost change " << model_cost_change
-                << " to " << kEpsilon;
-        model_cost_change = kEpsilon;
-      }
-
-      relative_decrease = actual_cost_change / model_cost_change;
-      VLOG(2) << "actual_cost_change / model_cost_change = "
-              << relative_decrease;
-
-      if (relative_decrease < options.min_relative_decrease) {
-        VLOG(2) << "Unsuccessful step.";
-        break;
-      }
-
-      VLOG(2) << "Successful step.";
-
-      ++summary->num_successful_steps;
-      x = x_new;
-      x_norm = x.norm();
-
-      if (!evaluator->Evaluate(x.data(), &cost, f.data(), jacobian.get())) {
-        LOG(WARNING) << "Failed to compute residuals and jacobian. "
-                     << "Terminating.";
-        summary->termination_type = NUMERICAL_FAILURE;
-        return;
-      }
-
-      if (options.jacobi_scaling) {
-        jacobian->ScaleColumns(scale.data());
-      }
-
-      model_cost = f.squaredNorm() / 2.0;
-      LevenbergMarquardtDiagonal(*jacobian, D.data());
-      scaled_gradient.setZero();
-      jacobian->LeftMultiply(f.data(), scaled_gradient.data());
-      gradient = scaled_gradient.array() / scale.array();
-      gradient_max_norm = gradient.lpNorm<Eigen::Infinity>();
-
-      // Check gradient based convergence.
-      VLOG(2) << "Gradient max norm: " << gradient_max_norm
-              << " tolerance: " << gradient_tolerance
-              << " ratio: " << gradient_max_norm / gradient_max_norm_0
-              << " tolerance: " << options.gradient_tolerance;
-      if (gradient_max_norm <= gradient_tolerance) {
-        summary->termination_type = GRADIENT_TOLERANCE;
-        VLOG(1) << "Terminating on GRADIENT_TOLERANCE. "
-                << "Relative gradient max norm: "
-                << gradient_max_norm / gradient_max_norm_0
-                << " <= " << options.gradient_tolerance
-                << " (tolerance).";
-        return;
-      }
-
-      mu = mu * max(1.0 / 3.0, 1 - pow(2 * relative_decrease - 1, 3));
-      nu = 2.0;
-      step_is_successful = true;
-      break;
-    }
-
-    if (!step_is_sane) {
-      ++num_consecutive_insane_steps;
-    }
-
-    if (num_consecutive_insane_steps == kMaxLinearSolverRetries) {
-      summary->termination_type = NUMERICAL_FAILURE;
-      VLOG(1) << "Too many consecutive retries; ending with numerical fail.";
-
-      if (!options.crash_and_dump_lsqp_on_failure) {
-        return;
-      }
-
-      // Dump debugging information to disk.
-      CHECK(options.lsqp_dump_format_type == TEXTFILE ||
-            options.lsqp_dump_format_type == PROTOBUF)
-          << "Dumping the linear least squares problem on crash "
-          << "requires Solver::Options::lsqp_dump_format_type to be "
-          << "PROTOBUF or TEXTFILE.";
-
-      if (DumpLinearLeastSquaresProblem(options.lsqp_dump_directory,
-                                        iteration,
-                                        options.lsqp_dump_format_type,
-                                        jacobian.get(),
-                                        muD.data(),
-                                        f.data(),
-                                        lm_step.data(),
-                                        options.num_eliminate_blocks)) {
-        LOG(FATAL) << "Linear least squares problem saved to: " 
-                   << options.lsqp_dump_directory
-                   << ". Please provide this to the Ceres developers for "
-                   << " debugging along with the v=2 log.";
-      } else {
-        LOG(FATAL) << "Tried writing linear least squares problem: " 
-                   << options.lsqp_dump_directory
-                   << " but failed.";
-      }
-    }
-
-    if (!step_is_successful) {
-      // Either the step did not lead to a decrease in cost or there
-      // was numerical failure. In either case we will scale mu up and
-      // retry. If it was a numerical failure, we hope that the
-      // stronger regularization will make the linear system better
-      // conditioned. If it was numerically sane, but there was no
-      // decrease in cost, then increasing mu reduces the size of the
-      // trust region and we look for a decrease closer to the
-      // linearization point.
-      ++summary->num_unsuccessful_steps;
-      mu = mu * nu;
-      nu = 2 * nu;
-    }
-
-    ++iteration;
-
-    total_cost = summary->fixed_cost + cost;
-
-    iteration_summary.iteration = iteration;
-    iteration_summary.step_is_successful = step_is_successful;
-    iteration_summary.cost = total_cost;
-    iteration_summary.cost_change = actual_cost_change;
-    iteration_summary.gradient_max_norm = gradient_max_norm;
-    iteration_summary.step_norm = step_norm;
-    iteration_summary.relative_decrease = relative_decrease;
-    iteration_summary.mu = mu;
-    iteration_summary.eta = options.eta;
-    iteration_summary.iteration_time_sec = (time(NULL) - iteration_start_time);
-
-    if (options.logging_type >= PER_MINIMIZER_ITERATION) {
-      summary->iterations.push_back(iteration_summary);
-    }
-
-    // Call the various callbacks.
-    for (int i = 0; i < options.callbacks.size(); ++i) {
-      if (!RunCallback(options.callbacks[i], iteration_summary, summary)) {
-        return;
-      }
-    }
-  }
-}
-
-}  // namespace internal
-}  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.cc b/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.cc
new file mode 100644
index 00000000000..9e6a59e3813
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.cc
@@ -0,0 +1,144 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/levenberg_marquardt_strategy.h"
+
+#include <cmath>
+#include "Eigen/Core"
+#include "ceres/array_utils.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/linear_solver.h"
+#include "ceres/sparse_matrix.h"
+#include "ceres/trust_region_strategy.h"
+#include "ceres/types.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+
+LevenbergMarquardtStrategy::LevenbergMarquardtStrategy(
+    const TrustRegionStrategy::Options& options)
+    : linear_solver_(options.linear_solver),
+      radius_(options.initial_radius),
+      max_radius_(options.max_radius),
+      min_diagonal_(options.lm_min_diagonal),
+      max_diagonal_(options.lm_max_diagonal),
+      decrease_factor_(2.0),
+      reuse_diagonal_(false) {
+  CHECK_NOTNULL(linear_solver_);
+  CHECK_GT(min_diagonal_, 0.0);
+  CHECK_LE(min_diagonal_, max_diagonal_);
+  CHECK_GT(max_radius_, 0.0);
+}
+
+LevenbergMarquardtStrategy::~LevenbergMarquardtStrategy() {
+}
+
+TrustRegionStrategy::Summary LevenbergMarquardtStrategy::ComputeStep(
+    const TrustRegionStrategy::PerSolveOptions& per_solve_options,
+    SparseMatrix* jacobian,
+    const double* residuals,
+    double* step) {
+  CHECK_NOTNULL(jacobian);
+  CHECK_NOTNULL(residuals);
+  CHECK_NOTNULL(step);
+
+  const int num_parameters = jacobian->num_cols();
+  if (!reuse_diagonal_) {
+    if (diagonal_.rows() != num_parameters) {
+      diagonal_.resize(num_parameters, 1);
+    }
+
+    jacobian->SquaredColumnNorm(diagonal_.data());
+    for (int i = 0; i < num_parameters; ++i) {
+      diagonal_[i] = min(max(diagonal_[i], min_diagonal_), max_diagonal_);
+    }
+  }
+
+  lm_diagonal_ = (diagonal_ / radius_).array().sqrt();
+
+  LinearSolver::PerSolveOptions solve_options;
+  solve_options.D = lm_diagonal_.data();
+  solve_options.q_tolerance = per_solve_options.eta;
+  // Disable r_tolerance checking. Since we only care about
+  // termination via the q_tolerance. As Nash and Sofer show,
+  // r_tolerance based termination is essentially useless in
+  // Truncated Newton methods.
+  solve_options.r_tolerance = -1.0;
+
+  // Invalidate the output array lm_step, so that we can detect if
+  // the linear solver generated numerical garbage.  This is known
+  // to happen for the DENSE_QR and then DENSE_SCHUR solver when
+  // the Jacobin is severly rank deficient and mu is too small.
+  InvalidateArray(num_parameters, step);
+
+  // Instead of solving Jx = -r, solve Jy = r.
+  // Then x can be found as x = -y, but the inputs jacobian and residuals
+  // do not need to be modified.
+  LinearSolver::Summary linear_solver_summary =
+      linear_solver_->Solve(jacobian, residuals, solve_options, step);
+  if (linear_solver_summary.termination_type == FAILURE ||
+      !IsArrayValid(num_parameters, step)) {
+    LOG(WARNING) << "Linear solver failure. Failed to compute a finite step.";
+    linear_solver_summary.termination_type = FAILURE;
+  } else {
+    VectorRef(step, num_parameters) *= -1.0;
+  }
+
+  reuse_diagonal_ = true;
+
+  TrustRegionStrategy::Summary summary;
+  summary.residual_norm = linear_solver_summary.residual_norm;
+  summary.num_iterations = linear_solver_summary.num_iterations;
+  summary.termination_type = linear_solver_summary.termination_type;
+  return summary;
+}
+
+void LevenbergMarquardtStrategy::StepAccepted(double step_quality) {
+  CHECK_GT(step_quality, 0.0);
+  radius_ = radius_ / std::max(1.0 / 3.0,
+                               1.0 - pow(2.0 * step_quality - 1.0, 3));
+  radius_ = std::min(max_radius_, radius_);
+  decrease_factor_ = 2.0;
+  reuse_diagonal_ = false;
+}
+
+void LevenbergMarquardtStrategy::StepRejected(double step_quality) {
+  radius_ = radius_ / decrease_factor_;
+  decrease_factor_ *= 2.0;
+  reuse_diagonal_ = true;
+}
+
+double LevenbergMarquardtStrategy::Radius() const {
+  return radius_;
+}
+
+}  // namespace internal
+}  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.h b/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.h
new file mode 100644
index 00000000000..90c21789797
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/levenberg_marquardt_strategy.h
@@ -0,0 +1,86 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_
+#define CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_
+
+#include "ceres/internal/eigen.h"
+#include "ceres/trust_region_strategy.h"
+
+namespace ceres {
+namespace internal {
+
+// Levenberg-Marquardt step computation and trust region sizing
+// strategy based on on "Methods for Nonlinear Least Squares" by
+// K. Madsen, H.B. Nielsen and O. Tingleff. Available to download from
+//
+// http://www2.imm.dtu.dk/pubdb/views/edoc_download.php/3215/pdf/imm3215.pdf
+class LevenbergMarquardtStrategy : public TrustRegionStrategy {
+public:
+  LevenbergMarquardtStrategy(const TrustRegionStrategy::Options& options);
+  virtual ~LevenbergMarquardtStrategy();
+
+  // TrustRegionStrategy interface
+  virtual TrustRegionStrategy::Summary ComputeStep(
+      const TrustRegionStrategy::PerSolveOptions& per_solve_options,
+      SparseMatrix* jacobian,
+      const double* residuals,
+      double* step);
+  virtual void StepAccepted(double step_quality);
+  virtual void StepRejected(double step_quality);
+  virtual void StepIsInvalid() {
+    // Treat the current step as a rejected step with no increase in
+    // solution quality. Since rejected steps lead to decrease in the
+    // size of the trust region, the next time ComputeStep is called,
+    // this will lead to a better conditioned system.
+    StepRejected(0.0);
+  }
+
+  virtual double Radius() const;
+
+ private:
+  LinearSolver* linear_solver_;
+  double radius_;
+  double max_radius_;
+  const double min_diagonal_;
+  const double max_diagonal_;
+  double decrease_factor_;
+  bool reuse_diagonal_;
+  Vector diagonal_;   // diagonal_ =  diag(J'J)
+  // Scaled copy of diagonal_. Stored here as optimization to prevent
+  // allocations in every iteration and reuse when a step fails and
+  // ComputeStep is called again.
+  Vector lm_diagonal_;  // lm_diagonal_ = diagonal_ / radius_;
+};
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_LEVENBERG_MARQUARDT_STRATEGY_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.cc b/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.cc
index cca9f442fe7..a91e254a663 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/linear_least_squares_problems.cc
@@ -33,17 +33,17 @@
 #include <cstdio>
 #include <string>
 #include <vector>
-#include <glog/logging.h>
 #include "ceres/block_sparse_matrix.h"
 #include "ceres/block_structure.h"
 #include "ceres/casts.h"
 #include "ceres/compressed_row_sparse_matrix.h"
 #include "ceres/file.h"
+#include "ceres/internal/scoped_ptr.h"
 #include "ceres/matrix_proto.h"
-#include "ceres/triplet_sparse_matrix.h"
 #include "ceres/stringprintf.h"
-#include "ceres/internal/scoped_ptr.h"
+#include "ceres/triplet_sparse_matrix.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -64,7 +64,7 @@ LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromId(int id) {
   return NULL;
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromFile(
     const string& filename) {
   LinearLeastSquaresProblemProto problem_proto;
@@ -130,7 +130,7 @@ LinearLeastSquaresProblem* CreateLinearLeastSquaresProblemFromFile(
       << "Ceres to be built with Protocol Buffers support.";
   return NULL;
 }
-#endif  // CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#endif  // CERES_NO_PROTOCOL_BUFFERS
 
 /*
 A = [1   2]
@@ -573,13 +573,13 @@ LinearLeastSquaresProblem* LinearLeastSquaresProblem3() {
   return problem;
 }
 
-bool DumpLinearLeastSquaresProblemToConsole(const string& directory,
-                                            int iteration,
-                                            const SparseMatrix* A,
-                                            const double* D,
-                                            const double* b,
-                                            const double* x,
-                                            int num_eliminate_blocks) {
+static bool DumpLinearLeastSquaresProblemToConsole(const string& directory,
+                                                   int iteration,
+                                                   const SparseMatrix* A,
+                                                   const double* D,
+                                                   const double* b,
+                                                   const double* x,
+                                                   int num_eliminate_blocks) {
   CHECK_NOTNULL(A);
   Matrix AA;
   A->ToDenseMatrix(&AA);
@@ -600,14 +600,14 @@ bool DumpLinearLeastSquaresProblemToConsole(const string& directory,
   return true;
 };
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
-bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
-                                                   int iteration,
-                                                   const SparseMatrix* A,
-                                                   const double* D,
-                                                   const double* b,
-                                                   const double* x,
-                                                   int num_eliminate_blocks) {
+#ifndef CERES_NO_PROTOCOL_BUFFERS
+static bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
+                                                          int iteration,
+                                                          const SparseMatrix* A,
+                                                          const double* D,
+                                                          const double* b,
+                                                          const double* x,
+                                                          int num_eliminate_blocks) {
   CHECK_NOTNULL(A);
   LinearLeastSquaresProblemProto lsqp;
   A->ToProto(lsqp.mutable_a());
@@ -641,13 +641,13 @@ bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
   return true;
 }
 #else
-bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
-                                                   int iteration,
-                                                   const SparseMatrix* A,
-                                                   const double* D,
-                                                   const double* b,
-                                                   const double* x,
-                                                   int num_eliminate_blocks) {
+static bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
+                                                          int iteration,
+                                                          const SparseMatrix* A,
+                                                          const double* D,
+                                                          const double* b,
+                                                          const double* x,
+                                                          int num_eliminate_blocks) {
   LOG(ERROR) << "Dumping least squares problems is only "
              << "supported when Ceres is compiled with "
              << "protocol buffer support.";
@@ -655,9 +655,9 @@ bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
 }
 #endif
 
-void WriteArrayToFileOrDie(const string& filename,
-                           const double* x,
-                           const int size) {
+static void WriteArrayToFileOrDie(const string& filename,
+                                  const double* x,
+                                  const int size) {
   CHECK_NOTNULL(x);
   VLOG(2) << "Writing array to: " << filename;
   FILE* fptr = fopen(filename.c_str(), "w");
@@ -668,43 +668,68 @@ void WriteArrayToFileOrDie(const string& filename,
   fclose(fptr);
 }
 
-bool DumpLinearLeastSquaresProblemToTextFile(const string& directory,
-                                             int iteration,
-                                             const SparseMatrix* A,
-                                             const double* D,
-                                             const double* b,
-                                             const double* x,
-                                             int num_eliminate_blocks) {
+static bool DumpLinearLeastSquaresProblemToTextFile(const string& directory,
+                                                    int iteration,
+                                                    const SparseMatrix* A,
+                                                    const double* D,
+                                                    const double* b,
+                                                    const double* x,
+                                                    int num_eliminate_blocks) {
   CHECK_NOTNULL(A);
   string format_string = JoinPath(directory,
                                   "lm_iteration_%03d");
   string filename_prefix =
       StringPrintf(format_string.c_str(), iteration);
 
+  LOG(INFO) << "writing to: " << filename_prefix << "*";
+
+  string matlab_script;
+  StringAppendF(&matlab_script,
+                "function lsqp = lm_iteration_%03d()\n", iteration);
+  StringAppendF(&matlab_script,
+                "lsqp.num_rows = %d;\n", A->num_rows());
+  StringAppendF(&matlab_script,
+                "lsqp.num_cols = %d;\n", A->num_cols());
+
   {
     string filename = filename_prefix + "_A.txt";
-    LOG(INFO) << "writing to: " << filename;
     FILE* fptr = fopen(filename.c_str(), "w");
     CHECK_NOTNULL(fptr);
     A->ToTextFile(fptr);
     fclose(fptr);
+    StringAppendF(&matlab_script,
+                  "tmp = load('%s', '-ascii');\n", filename.c_str());
+    StringAppendF(
+        &matlab_script,
+        "lsqp.A = sparse(tmp(:, 1) + 1, tmp(:, 2) + 1, tmp(:, 3), %d, %d);\n",
+        A->num_rows(),
+        A->num_cols());
   }
 
+
   if (D != NULL) {
     string filename = filename_prefix + "_D.txt";
     WriteArrayToFileOrDie(filename, D, A->num_cols());
+    StringAppendF(&matlab_script,
+                  "lsqp.D = load('%s', '-ascii');\n", filename.c_str());
   }
 
   if (b != NULL) {
     string filename = filename_prefix + "_b.txt";
     WriteArrayToFileOrDie(filename, b, A->num_rows());
+    StringAppendF(&matlab_script,
+                  "lsqp.b = load('%s', '-ascii');\n", filename.c_str());
   }
 
   if (x != NULL) {
     string filename = filename_prefix + "_x.txt";
     WriteArrayToFileOrDie(filename, x, A->num_cols());
+    StringAppendF(&matlab_script,
+                  "lsqp.x = load('%s', '-ascii');\n", filename.c_str());
   }
 
+  string matlab_filename = filename_prefix + ".m";
+  WriteStringToFileOrDie(matlab_script, matlab_filename);
   return true;
 }
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/linear_solver.cc
index b2e3941eea1..08c3ba110d0 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/linear_solver.cc
@@ -30,13 +30,14 @@
 
 #include "ceres/linear_solver.h"
 
-#include <glog/logging.h>
 #include "ceres/cgnr_solver.h"
+#include "ceres/dense_normal_cholesky_solver.h"
 #include "ceres/dense_qr_solver.h"
 #include "ceres/iterative_schur_complement_solver.h"
 #include "ceres/schur_complement_solver.h"
 #include "ceres/sparse_normal_cholesky_solver.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -50,22 +51,24 @@ LinearSolver* LinearSolver::Create(const LinearSolver::Options& options) {
       return new CgnrSolver(options);
 
     case SPARSE_NORMAL_CHOLESKY:
-#ifndef CERES_NO_SUITESPARSE
-      return new SparseNormalCholeskySolver(options);
-#else
+#if defined(CERES_NO_SUITESPARSE) && defined(CERES_NO_CXSPARSE)
       LOG(WARNING) << "SPARSE_NORMAL_CHOLESKY is not available. Please "
-                   << "build Ceres with SuiteSparse. Returning NULL.";
+                   << "build Ceres with SuiteSparse or CXSparse. "
+                   << "Returning NULL.";
       return NULL;
-#endif  // CERES_NO_SUITESPARSE
+#else
+      return new SparseNormalCholeskySolver(options);
+#endif
 
     case SPARSE_SCHUR:
-#ifndef CERES_NO_SUITESPARSE
-      return new SparseSchurComplementSolver(options);
-#else
+#if defined(CERES_NO_SUITESPARSE) && defined(CERES_NO_CXSPARSE)
       LOG(WARNING) << "SPARSE_SCHUR is not available. Please "
-                   << "build Ceres with SuiteSparse. Returning NULL.";
+                   << "build Ceres with SuiteSparse or CXSparse. "
+                   << "Returning NULL.";
       return NULL;
-#endif  // CERES_NO_SUITESPARSE
+#else
+      return new SparseSchurComplementSolver(options);
+#endif
 
     case DENSE_SCHUR:
       return new DenseSchurComplementSolver(options);
@@ -76,10 +79,13 @@ LinearSolver* LinearSolver::Create(const LinearSolver::Options& options) {
     case DENSE_QR:
       return new DenseQRSolver(options);
 
+    case DENSE_NORMAL_CHOLESKY:
+      return new DenseNormalCholeskySolver(options);
+
     default:
       LOG(FATAL) << "Unknown linear solver type :"
                  << options.type;
-	  return NULL;  // MSVC doesn't understand that LOG(FATAL) never returns.
+      return NULL;  // MSVC doesn't understand that LOG(FATAL) never returns.
   }
 }
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.h b/extern/libmv/third_party/ceres/internal/ceres/linear_solver.h
index 5860ecc8a77..31f88740b9f 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/linear_solver.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/linear_solver.h
@@ -55,10 +55,11 @@ class LinearOperator;
 //   Ax = b
 //
 // It is expected that a single instance of a LinearSolver object
-// maybe used multiple times for solving different linear
-// systems. This allows them to cache and reuse information across
-// solves if for example the sparsity of the linear system remains
-// constant.
+// maybe used multiple times for solving multiple linear systems with
+// the same sparsity structure. This allows them to cache and reuse
+// information across solves. This means that calling Solve on the
+// same LinearSolver instance with two different linear systems will
+// result in undefined behaviour.
 //
 // Subclasses of LinearSolver use two structs to configure themselves.
 // The Options struct configures the LinearSolver object for its
@@ -70,10 +71,11 @@ class LinearSolver {
     Options()
         : type(SPARSE_NORMAL_CHOLESKY),
           preconditioner_type(JACOBI),
+          sparse_linear_algebra_library(SUITE_SPARSE),
+          use_block_amd(true),
           min_num_iterations(1),
           max_num_iterations(1),
           num_threads(1),
-          constant_sparsity(false),
           num_eliminate_blocks(0),
           residual_reset_period(10),
           row_block_size(Dynamic),
@@ -85,6 +87,11 @@ class LinearSolver {
 
     PreconditionerType preconditioner_type;
 
+    SparseLinearAlgebraLibraryType sparse_linear_algebra_library;
+
+    // See solver.h for explanation of this option.
+    bool use_block_amd;
+
     // Number of internal iterations that the solver uses. This
     // parameter only makes sense for iterative solvers like CG.
     int min_num_iterations;
@@ -93,10 +100,6 @@ class LinearSolver {
     // If possible, how many threads can the solver use.
     int num_threads;
 
-    // If possible cache and reuse the symbolic factorization across
-    // multiple calls.
-    bool constant_sparsity;
-
     // Eliminate 0 to num_eliminate_blocks - 1 from the Normal
     // equations to form a schur complement. Only used by the Schur
     // complement based solver. The most common use for this parameter
@@ -121,8 +124,8 @@ class LinearSolver {
     // It is expected that these parameters are set programmatically
     // rather than manually.
     //
-    // Please see explicit_schur_complement_solver_impl.h for more
-    // details.
+    // Please see schur_complement_solver.h and schur_eliminator.h for
+    // more details.
     int row_block_size;
     int e_block_size;
     int f_block_size;
@@ -244,6 +247,7 @@ class LinearSolver {
                         const PerSolveOptions& per_solve_options,
                         double* x) = 0;
 
+  // Factory
   static LinearSolver* Create(const Options& options);
 };
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/local_parameterization.cc b/extern/libmv/third_party/ceres/internal/ceres/local_parameterization.cc
index eeae74e3f95..26e7f4908a4 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/local_parameterization.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/local_parameterization.cc
@@ -28,10 +28,11 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 
-#include <glog/logging.h>
-#include "ceres/internal/eigen.h"
 #include "ceres/local_parameterization.h"
+
+#include "ceres/internal/eigen.h"
 #include "ceres/rotation.h"
+#include "glog/logging.h"
 
 namespace ceres {
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/loss_function.cc b/extern/libmv/third_party/ceres/internal/ceres/loss_function.cc
index 00b2b184729..b948f289f21 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/loss_function.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/loss_function.cc
@@ -77,6 +77,70 @@ void CauchyLoss::Evaluate(double s, double rho[3]) const {
   rho[2] = - c_ * (inv * inv);
 }
 
+void ArctanLoss::Evaluate(double s, double rho[3]) const {
+  const double sum = 1 + s * s * b_;
+  const double inv = 1 / sum;
+  // 'sum' and 'inv' are always positive.
+  rho[0] = a_ * atan2(s, a_);
+  rho[1] = inv;
+  rho[2] = -2 * s * b_ * (inv * inv);
+}
+
+TolerantLoss::TolerantLoss(double a, double b)
+    : a_(a),
+      b_(b),
+      c_(b * log(1.0 + exp(-a / b))) {
+  CHECK_GE(a, 0.0);
+  CHECK_GT(b, 0.0);
+}
+
+void TolerantLoss::Evaluate(double s, double rho[3]) const {
+  const double x = (s - a_) / b_;
+  // The basic equation is rho[0] = b ln(1 + e^x).  However, if e^x is too
+  // large, it will overflow.  Since numerically 1 + e^x == e^x when the
+  // x is greater than about ln(2^53) for doubles, beyond this threshold
+  // we substitute x for ln(1 + e^x) as a numerically equivalent approximation.
+  static const double kLog2Pow53 = 36.7;  // ln(MathLimits<double>::kEpsilon).
+  if (x > kLog2Pow53) {
+    rho[0] = s - a_ - c_;
+    rho[1] = 1.0;
+    rho[2] = 0.0;
+  } else {
+    const double e_x = exp(x);
+    rho[0] = b_ * log(1.0 + e_x) - c_;
+    rho[1] = e_x / (1.0 + e_x);
+    rho[2] = 0.5 / (b_ * (1.0 + cosh(x)));
+  }
+}
+
+ComposedLoss::ComposedLoss(const LossFunction* f, Ownership ownership_f,
+                           const LossFunction* g, Ownership ownership_g)
+    : f_(CHECK_NOTNULL(f)),
+      g_(CHECK_NOTNULL(g)),
+      ownership_f_(ownership_f),
+      ownership_g_(ownership_g) {
+}
+
+ComposedLoss::~ComposedLoss() {
+  if (ownership_f_ == DO_NOT_TAKE_OWNERSHIP) {
+    f_.release();
+  }
+  if (ownership_g_ == DO_NOT_TAKE_OWNERSHIP) {
+    g_.release();
+  }
+}
+
+void ComposedLoss::Evaluate(double s, double rho[3]) const {
+  double rho_f[3], rho_g[3];
+  g_->Evaluate(s, rho_g);
+  f_->Evaluate(rho_g[0], rho_f);
+  rho[0] = rho_f[0];
+  // f'(g(s)) * g'(s).
+  rho[1] = rho_f[1] * rho_g[1];
+  // f''(g(s)) * g'(s) * g'(s) + f'(g(s)) * g''(s).
+  rho[2] = rho_f[2] * rho_g[1] * rho_g[1] + rho_f[1] * rho_g[2];
+}
+
 void ScaledLoss::Evaluate(double s, double rho[3]) const {
   if (rho_.get() == NULL) {
     rho[0] = a_ * s;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/matrix_proto.h b/extern/libmv/third_party/ceres/internal/ceres/matrix_proto.h
index b8a3a1a6de6..94b3076e3d7 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/matrix_proto.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/matrix_proto.h
@@ -33,7 +33,7 @@
 #ifndef CERES_INTERNAL_MATRIX_PROTO_H_
 #define CERES_INTERNAL_MATRIX_PROTO_H_
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 #include "ceres/matrix.pb.h"
 #endif
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/minimizer.h b/extern/libmv/third_party/ceres/internal/ceres/minimizer.h
index 77cb00cb6b4..cfc98a3ebd0 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/minimizer.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/minimizer.h
@@ -40,6 +40,8 @@ namespace internal {
 
 class Evaluator;
 class LinearSolver;
+class SparseMatrix;
+class TrustRegionStrategy;
 
 // Interface for non-linear least squares solvers.
 class Minimizer {
@@ -48,53 +50,93 @@ class Minimizer {
   // see solver.h for detailed information about the meaning and
   // default values of each of these parameters.
   struct Options {
+    Options() {
+      Init(Solver::Options());
+    }
+
     explicit Options(const Solver::Options& options) {
+      Init(options);
+    }
+
+    void Init(const Solver::Options& options) {
       max_num_iterations = options.max_num_iterations;
-      max_solver_time_sec = options.max_solver_time_sec;
+      max_solver_time_in_seconds = options.max_solver_time_in_seconds;
+      max_step_solver_retries = 5;
       gradient_tolerance = options.gradient_tolerance;
       parameter_tolerance = options.parameter_tolerance;
       function_tolerance = options.function_tolerance;
       min_relative_decrease = options.min_relative_decrease;
       eta = options.eta;
-      tau = options.tau;
       jacobi_scaling = options.jacobi_scaling;
-      crash_and_dump_lsqp_on_failure = options.crash_and_dump_lsqp_on_failure;
+      use_nonmonotonic_steps = options.use_nonmonotonic_steps;
+      max_consecutive_nonmonotonic_steps =
+          options.max_consecutive_nonmonotonic_steps;
       lsqp_dump_directory = options.lsqp_dump_directory;
       lsqp_iterations_to_dump = options.lsqp_iterations_to_dump;
       lsqp_dump_format_type = options.lsqp_dump_format_type;
       num_eliminate_blocks = options.num_eliminate_blocks;
-      logging_type = options.logging_type;
+      max_num_consecutive_invalid_steps =
+          options.max_num_consecutive_invalid_steps;
+      min_trust_region_radius = options.min_trust_region_radius;
+      evaluator = NULL;
+      trust_region_strategy = NULL;
+      jacobian = NULL;
+      callbacks = options.callbacks;
     }
 
     int max_num_iterations;
-    int max_solver_time_sec;
+    double max_solver_time_in_seconds;
+
+    // Number of times the linear solver should be retried in case of
+    // numerical failure. The retries are done by exponentially scaling up
+    // mu at each retry. This leads to stronger and stronger
+    // regularization making the linear least squares problem better
+    // conditioned at each retry.
+    int max_step_solver_retries;
     double gradient_tolerance;
     double parameter_tolerance;
     double function_tolerance;
     double min_relative_decrease;
     double eta;
-    double tau;
     bool jacobi_scaling;
-    bool crash_and_dump_lsqp_on_failure;
+    bool use_nonmonotonic_steps;
+    int max_consecutive_nonmonotonic_steps;
     vector<int> lsqp_iterations_to_dump;
     DumpFormatType lsqp_dump_format_type;
     string lsqp_dump_directory;
     int num_eliminate_blocks;
-    LoggingType logging_type;
+    int max_num_consecutive_invalid_steps;
+    int min_trust_region_radius;
 
     // List of callbacks that are executed by the Minimizer at the end
     // of each iteration.
     //
-    // Client owns these pointers.
+    // The Options struct does not own these pointers.
     vector<IterationCallback*> callbacks;
+
+    // Object responsible for evaluating the cost, residuals and
+    // Jacobian matrix. The Options struct does not own this pointer.
+    Evaluator* evaluator;
+
+    // Object responsible for actually computing the trust region
+    // step, and sizing the trust region radius. The Options struct
+    // does not own this pointer.
+    TrustRegionStrategy* trust_region_strategy;
+
+    // Object holding the Jacobian matrix. It is assumed that the
+    // sparsity structure of the matrix has already been initialized
+    // and will remain constant for the life time of the
+    // optimization. The Options struct does not own this pointer.
+    SparseMatrix* jacobian;
   };
 
   virtual ~Minimizer() {}
+
+  // Note: The minimizer is expected to update the state of the
+  // parameters array every iteration. This is required for the
+  // StateUpdatingCallback to work.
   virtual void Minimize(const Options& options,
-                        Evaluator* evaluator,
-                        LinearSolver* linear_solver,
-                        const double* initial_parameters,
-                        double* final_parameters,
+                        double* parameters,
                         Solver::Summary* summary) = 0;
 };
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/mutex.h b/extern/libmv/third_party/ceres/internal/ceres/mutex.h
index 6514b107041..5090a71b78d 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/mutex.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/mutex.h
@@ -95,11 +95,11 @@
 #ifndef CERES_INTERNAL_MUTEX_H_
 #define CERES_INTERNAL_MUTEX_H_
 
-#if defined(NO_THREADS)
+#if defined(CERES_NO_THREADS)
   typedef int MutexType;      // to keep a lock-count
 #elif defined(_WIN32) || defined(__CYGWIN32__) || defined(__CYGWIN64__)
-# define WIN32_LEAN_AND_MEAN  // We only need minimal includes
-# ifdef GMUTEX_TRYLOCK
+# define CERES_WIN32_LEAN_AND_MEAN  // We only need minimal includes
+# ifdef CERES_GMUTEX_TRYLOCK
   // We need Windows NT or later for TryEnterCriticalSection().  If you
   // don't need that functionality, you can remove these _WIN32_WINNT
   // lines, and change TryLock() to assert(0) or something.
@@ -108,9 +108,9 @@
 #   endif
 # endif
 // To avoid macro definition of ERROR.
-# define NOGDI
+# define CERES_NOGDI
 // To avoid macro definition of min/max.
-# define NOMINMAX
+# define CERES_NOMINMAX
 # include <windows.h>
   typedef CRITICAL_SECTION MutexType;
 #elif defined(CERES_HAVE_PTHREAD) && defined(CERES_HAVE_RWLOCK)
@@ -151,7 +151,7 @@ class Mutex {
 
   inline void Lock();    // Block if needed until free then acquire exclusively
   inline void Unlock();  // Release a lock acquired via Lock()
-#ifdef GMUTEX_TRYLOCK
+#ifdef CERES_GMUTEX_TRYLOCK
   inline bool TryLock(); // If free, Lock() and return true, else return false
 #endif
   // Note that on systems that don't support read-write locks, these may
@@ -183,7 +183,7 @@ class Mutex {
 };
 
 // Now the implementation of Mutex for various systems
-#if defined(NO_THREADS)
+#if defined(CERES_NO_THREADS)
 
 // When we don't have threads, we can be either reading or writing,
 // but not both.  We can have lots of readers at once (in no-threads
@@ -199,7 +199,7 @@ Mutex::Mutex() : mutex_(0) { }
 Mutex::~Mutex()            { assert(mutex_ == 0); }
 void Mutex::Lock()         { assert(--mutex_ == -1); }
 void Mutex::Unlock()       { assert(mutex_++ == -1); }
-#ifdef GMUTEX_TRYLOCK
+#ifdef CERES_GMUTEX_TRYLOCK
 bool Mutex::TryLock()      { if (mutex_) return false; Lock(); return true; }
 #endif
 void Mutex::ReaderLock()   { assert(++mutex_ > 0); }
@@ -220,91 +220,101 @@ void Mutex::ReaderUnlock() { Unlock(); }
 
 #elif defined(CERES_HAVE_PTHREAD) && defined(CERES_HAVE_RWLOCK)
 
-#define SAFE_PTHREAD(fncall)  do {   /* run fncall if is_safe_ is true */  \
-  if (is_safe_ && fncall(&mutex_) != 0) abort();                           \
+#define CERES_SAFE_PTHREAD(fncall) do { /* run fncall if is_safe_ is true */ \
+  if (is_safe_ && fncall(&mutex_) != 0) abort();                             \
 } while (0)
 
 Mutex::Mutex() {
   SetIsSafe();
   if (is_safe_ && pthread_rwlock_init(&mutex_, NULL) != 0) abort();
 }
-Mutex::~Mutex()            { SAFE_PTHREAD(pthread_rwlock_destroy); }
-void Mutex::Lock()         { SAFE_PTHREAD(pthread_rwlock_wrlock); }
-void Mutex::Unlock()       { SAFE_PTHREAD(pthread_rwlock_unlock); }
-#ifdef GMUTEX_TRYLOCK
+Mutex::~Mutex()            { CERES_SAFE_PTHREAD(pthread_rwlock_destroy); }
+void Mutex::Lock()         { CERES_SAFE_PTHREAD(pthread_rwlock_wrlock); }
+void Mutex::Unlock()       { CERES_SAFE_PTHREAD(pthread_rwlock_unlock); }
+#ifdef CERES_GMUTEX_TRYLOCK
 bool Mutex::TryLock()      { return is_safe_ ?
                                     pthread_rwlock_trywrlock(&mutex_) == 0 :
                                     true; }
 #endif
-void Mutex::ReaderLock()   { SAFE_PTHREAD(pthread_rwlock_rdlock); }
-void Mutex::ReaderUnlock() { SAFE_PTHREAD(pthread_rwlock_unlock); }
-#undef SAFE_PTHREAD
+void Mutex::ReaderLock()   { CERES_SAFE_PTHREAD(pthread_rwlock_rdlock); }
+void Mutex::ReaderUnlock() { CERES_SAFE_PTHREAD(pthread_rwlock_unlock); }
+#undef CERES_SAFE_PTHREAD
 
 #elif defined(CERES_HAVE_PTHREAD)
 
-#define SAFE_PTHREAD(fncall)  do {   /* run fncall if is_safe_ is true */  \
-  if (is_safe_ && fncall(&mutex_) != 0) abort();                           \
+#define CERES_SAFE_PTHREAD(fncall) do { /* run fncall if is_safe_ is true */  \
+  if (is_safe_ && fncall(&mutex_) != 0) abort();                              \
 } while (0)
 
 Mutex::Mutex()             {
   SetIsSafe();
   if (is_safe_ && pthread_mutex_init(&mutex_, NULL) != 0) abort();
 }
-Mutex::~Mutex()            { SAFE_PTHREAD(pthread_mutex_destroy); }
-void Mutex::Lock()         { SAFE_PTHREAD(pthread_mutex_lock); }
-void Mutex::Unlock()       { SAFE_PTHREAD(pthread_mutex_unlock); }
-#ifdef GMUTEX_TRYLOCK
+Mutex::~Mutex()            { CERES_SAFE_PTHREAD(pthread_mutex_destroy); }
+void Mutex::Lock()         { CERES_SAFE_PTHREAD(pthread_mutex_lock); }
+void Mutex::Unlock()       { CERES_SAFE_PTHREAD(pthread_mutex_unlock); }
+#ifdef CERES_GMUTEX_TRYLOCK
 bool Mutex::TryLock()      { return is_safe_ ?
                                  pthread_mutex_trylock(&mutex_) == 0 : true; }
 #endif
 void Mutex::ReaderLock()   { Lock(); }
 void Mutex::ReaderUnlock() { Unlock(); }
-#undef SAFE_PTHREAD
+#undef CERES_SAFE_PTHREAD
 
 #endif
 
 // --------------------------------------------------------------------------
 // Some helper classes
 
-// MutexLock(mu) acquires mu when constructed and releases it when destroyed.
-class MutexLock {
+// Note: The weird "Ceres" prefix for the class is a workaround for having two
+// similar mutex.h files included in the same translation unit. This is a
+// problem because macros do not respect C++ namespaces, and as a result, this
+// does not work well (e.g. inside Chrome). The offending macros are
+// "MutexLock(x) COMPILE_ASSERT(false)". To work around this, "Ceres" is
+// prefixed to the class names; this permits defining the classes.
+
+// CeresMutexLock(mu) acquires mu when constructed and releases it when destroyed.
+class CeresMutexLock {
  public:
-  explicit MutexLock(Mutex *mu) : mu_(mu) { mu_->Lock(); }
-  ~MutexLock() { mu_->Unlock(); }
+  explicit CeresMutexLock(Mutex *mu) : mu_(mu) { mu_->Lock(); }
+  ~CeresMutexLock() { mu_->Unlock(); }
  private:
   Mutex * const mu_;
   // Disallow "evil" constructors
-  MutexLock(const MutexLock&);
-  void operator=(const MutexLock&);
+  CeresMutexLock(const CeresMutexLock&);
+  void operator=(const CeresMutexLock&);
 };
 
-// ReaderMutexLock and WriterMutexLock do the same, for rwlocks
-class ReaderMutexLock {
+// CeresReaderMutexLock and CeresWriterMutexLock do the same, for rwlocks
+class CeresReaderMutexLock {
  public:
-  explicit ReaderMutexLock(Mutex *mu) : mu_(mu) { mu_->ReaderLock(); }
-  ~ReaderMutexLock() { mu_->ReaderUnlock(); }
+  explicit CeresReaderMutexLock(Mutex *mu) : mu_(mu) { mu_->ReaderLock(); }
+  ~CeresReaderMutexLock() { mu_->ReaderUnlock(); }
  private:
   Mutex * const mu_;
   // Disallow "evil" constructors
-  ReaderMutexLock(const ReaderMutexLock&);
-  void operator=(const ReaderMutexLock&);
+  CeresReaderMutexLock(const CeresReaderMutexLock&);
+  void operator=(const CeresReaderMutexLock&);
 };
 
-class WriterMutexLock {
+class CeresWriterMutexLock {
  public:
-  explicit WriterMutexLock(Mutex *mu) : mu_(mu) { mu_->WriterLock(); }
-  ~WriterMutexLock() { mu_->WriterUnlock(); }
+  explicit CeresWriterMutexLock(Mutex *mu) : mu_(mu) { mu_->WriterLock(); }
+  ~CeresWriterMutexLock() { mu_->WriterUnlock(); }
  private:
   Mutex * const mu_;
   // Disallow "evil" constructors
-  WriterMutexLock(const WriterMutexLock&);
-  void operator=(const WriterMutexLock&);
+  CeresWriterMutexLock(const CeresWriterMutexLock&);
+  void operator=(const CeresWriterMutexLock&);
 };
 
 // Catch bug where variable name is omitted, e.g. MutexLock (&mu);
-#define MutexLock(x) COMPILE_ASSERT(0, mutex_lock_decl_missing_var_name)
-#define ReaderMutexLock(x) COMPILE_ASSERT(0, rmutex_lock_decl_missing_var_name)
-#define WriterMutexLock(x) COMPILE_ASSERT(0, wmutex_lock_decl_missing_var_name)
+#define CeresMutexLock(x) \
+    COMPILE_ASSERT(0, ceres_mutex_lock_decl_missing_var_name)
+#define CeresReaderMutexLock(x) \
+    COMPILE_ASSERT(0, ceres_rmutex_lock_decl_missing_var_name)
+#define CeresWriterMutexLock(x) \
+    COMPILE_ASSERT(0, ceres_wmutex_lock_decl_missing_var_name)
 
 }  // namespace internal
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/normal_prior.cc b/extern/libmv/third_party/ceres/internal/ceres/normal_prior.cc
index f30bbc8b46b..392d728fb32 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/normal_prior.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/normal_prior.cc
@@ -32,11 +32,10 @@
 
 #include <cstddef>
 #include <vector>
-
-#include <glog/logging.h>
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/scoped_ptr.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/parameter_block.h b/extern/libmv/third_party/ceres/internal/ceres/parameter_block.h
index 4bac1a85828..f20805ca873 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/parameter_block.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/parameter_block.h
@@ -32,13 +32,15 @@
 #define CERES_INTERNAL_PARAMETER_BLOCK_H_
 
 #include <cstdlib>
+#include <string>
+#include "ceres/array_utils.h"
 #include "ceres/integral_types.h"
-#include <glog/logging.h>
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/port.h"
 #include "ceres/internal/scoped_ptr.h"
 #include "ceres/local_parameterization.h"
-#include "ceres/residual_block_utils.h"
+#include "ceres/stringprintf.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -172,6 +174,19 @@ class ParameterBlock {
     return local_parameterization_->Plus(x, delta, x_plus_delta);
   }
 
+  string ToString() const {
+    return StringPrintf("{ user_state=%p, state=%p, size=%d, "
+                        "constant=%d, index=%d, state_offset=%d, "
+                        "delta_offset=%d }",
+                        user_state_,
+                        state_,
+                        size_,
+                        is_constant_,
+                        index_,
+                        state_offset_,
+                        delta_offset_);
+  }
+
  private:
   void Init(double* user_state,
             int size,
diff --git a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.cc b/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.cc
index fcf8fd53aed..0722fc82c02 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/partitioned_matrix_view.cc
@@ -35,10 +35,10 @@
 #include <algorithm>
 #include <cstring>
 #include <vector>
-#include <glog/logging.h>
 #include "ceres/block_sparse_matrix.h"
 #include "ceres/block_structure.h"
 #include "ceres/internal/eigen.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/polynomial_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/polynomial_solver.cc
new file mode 100644
index 00000000000..20c01566a89
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/polynomial_solver.cc
@@ -0,0 +1,184 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: moll.markus@arcor.de (Markus Moll)
+
+#include "ceres/polynomial_solver.h"
+
+#include <cmath>
+#include <cstddef>
+#include "Eigen/Dense"
+#include "ceres/internal/port.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+namespace {
+
+// Balancing function as described by B. N. Parlett and C. Reinsch,
+// "Balancing a Matrix for Calculation of Eigenvalues and Eigenvectors".
+// In: Numerische Mathematik, Volume 13, Number 4 (1969), 293-304,
+// Springer Berlin / Heidelberg. DOI: 10.1007/BF02165404
+void BalanceCompanionMatrix(Matrix* companion_matrix_ptr) {
+  CHECK_NOTNULL(companion_matrix_ptr);
+  Matrix& companion_matrix = *companion_matrix_ptr;
+  Matrix companion_matrix_offdiagonal = companion_matrix;
+  companion_matrix_offdiagonal.diagonal().setZero();
+
+  const int degree = companion_matrix.rows();
+
+  // gamma <= 1 controls how much a change in the scaling has to
+  // lower the 1-norm of the companion matrix to be accepted.
+  //
+  // gamma = 1 seems to lead to cycles (numerical issues?), so
+  // we set it slightly lower.
+  const double gamma = 0.9;
+
+  // Greedily scale row/column pairs until there is no change.
+  bool scaling_has_changed;
+  do {
+    scaling_has_changed = false;
+
+    for (int i = 0; i < degree; ++i) {
+      const double row_norm = companion_matrix_offdiagonal.row(i).lpNorm<1>();
+      const double col_norm = companion_matrix_offdiagonal.col(i).lpNorm<1>();
+
+      // Decompose row_norm/col_norm into mantissa * 2^exponent,
+      // where 0.5 <= mantissa < 1. Discard mantissa (return value
+      // of frexp), as only the exponent is needed.
+      int exponent = 0;
+      std::frexp(row_norm / col_norm, &exponent);
+      exponent /= 2;
+
+      if (exponent != 0) {
+        const double scaled_col_norm = std::ldexp(col_norm, exponent);
+        const double scaled_row_norm = std::ldexp(row_norm, -exponent);
+        if (scaled_col_norm + scaled_row_norm < gamma * (col_norm + row_norm)) {
+          // Accept the new scaling. (Multiplication by powers of 2 should not
+          // introduce rounding errors (ignoring non-normalized numbers and
+          // over- or underflow))
+          scaling_has_changed = true;
+          companion_matrix_offdiagonal.row(i) *= std::ldexp(1.0, -exponent);
+          companion_matrix_offdiagonal.col(i) *= std::ldexp(1.0, exponent);
+        }
+      }
+    }
+  } while (scaling_has_changed);
+
+  companion_matrix_offdiagonal.diagonal() = companion_matrix.diagonal();
+  companion_matrix = companion_matrix_offdiagonal;
+  VLOG(3) << "Balanced companion matrix is\n" << companion_matrix;
+}
+
+void BuildCompanionMatrix(const Vector& polynomial,
+                          Matrix* companion_matrix_ptr) {
+  CHECK_NOTNULL(companion_matrix_ptr);
+  Matrix& companion_matrix = *companion_matrix_ptr;
+
+  const int degree = polynomial.size() - 1;
+
+  companion_matrix.resize(degree, degree);
+  companion_matrix.setZero();
+  companion_matrix.diagonal(-1).setOnes();
+  companion_matrix.col(degree - 1) = -polynomial.reverse().head(degree);
+}
+
+// Remove leading terms with zero coefficients.
+Vector RemoveLeadingZeros(const Vector& polynomial_in) {
+  int i = 0;
+  while (i < (polynomial_in.size() - 1) && polynomial_in(i) == 0.0) {
+    ++i;
+  }
+  return polynomial_in.tail(polynomial_in.size() - i);
+}
+}  // namespace
+
+bool FindPolynomialRoots(const Vector& polynomial_in,
+                         Vector* real,
+                         Vector* imaginary) {
+  if (polynomial_in.size() == 0) {
+    LOG(ERROR) << "Invalid polynomial of size 0 passed to FindPolynomialRoots";
+    return false;
+  }
+
+  Vector polynomial = RemoveLeadingZeros(polynomial_in);
+  const int degree = polynomial.size() - 1;
+
+  // Is the polynomial constant?
+  if (degree == 0) {
+    LOG(WARNING) << "Trying to extract roots from a constant "
+                 << "polynomial in FindPolynomialRoots";
+    return true;
+  }
+
+  // Divide by leading term
+  const double leading_term = polynomial(0);
+  polynomial /= leading_term;
+
+  // Separately handle linear polynomials.
+  if (degree == 1) {
+    if (real != NULL) {
+      real->resize(1);
+      (*real)(0) = -polynomial(1);
+    }
+    if (imaginary != NULL) {
+      imaginary->resize(1);
+      imaginary->setZero();
+    }
+  }
+
+  // The degree is now known to be at least 2.
+  // Build and balance the companion matrix to the polynomial.
+  Matrix companion_matrix(degree, degree);
+  BuildCompanionMatrix(polynomial, &companion_matrix);
+  BalanceCompanionMatrix(&companion_matrix);
+
+  // Find its (complex) eigenvalues.
+  Eigen::EigenSolver<Matrix> solver(companion_matrix,
+                                    Eigen::EigenvaluesOnly);
+  if (solver.info() != Eigen::Success) {
+    LOG(ERROR) << "Failed to extract eigenvalues from companion matrix.";
+    return false;
+  }
+
+  // Output roots
+  if (real != NULL) {
+    *real = solver.eigenvalues().real();
+  } else {
+    LOG(WARNING) << "NULL pointer passed as real argument to "
+                 << "FindPolynomialRoots. Real parts of the roots will not "
+                 << "be returned.";
+  }
+  if (imaginary != NULL) {
+    *imaginary = solver.eigenvalues().imag();
+  }
+  return true;
+}
+
+}  // namespace internal
+}  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/polynomial_solver.h b/extern/libmv/third_party/ceres/internal/ceres/polynomial_solver.h
new file mode 100644
index 00000000000..1cf07ddb549
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/polynomial_solver.h
@@ -0,0 +1,65 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: moll.markus@arcor.de (Markus Moll)
+
+#ifndef CERES_INTERNAL_POLYNOMIAL_SOLVER_H_
+#define CERES_INTERNAL_POLYNOMIAL_SOLVER_H_
+
+#include "ceres/internal/eigen.h"
+
+namespace ceres {
+namespace internal {
+
+// Use the companion matrix eigenvalues to determine the roots of the polynomial
+//
+//   sum_{i=0}^N polynomial(i) x^{N-i}.
+//
+// This function returns true on success, false otherwise.
+// Failure indicates that the polynomial is invalid (of size 0) or
+// that the eigenvalues of the companion matrix could not be computed.
+// On failure, a more detailed message will be written to LOG(ERROR).
+// If real is not NULL, the real parts of the roots will be returned in it.
+// Likewise, if imaginary is not NULL, imaginary parts will be returned in it.
+bool FindPolynomialRoots(const Vector& polynomial,
+                         Vector* real,
+                         Vector* imaginary);
+
+// Evaluate the polynomial at x using the Horner scheme.
+inline double EvaluatePolynomial(const Vector& polynomial, double x) {
+  double v = 0.0;
+  for (int i = 0; i < polynomial.size(); ++i) {
+    v = v * x + polynomial(i);
+  }
+  return v;
+}
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_POLYNOMIAL_SOLVER_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.cc b/extern/libmv/third_party/ceres/internal/ceres/problem_impl.cc
index 68242477d6f..c186f527be8 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/problem_impl.cc
@@ -37,16 +37,15 @@
 #include <string>
 #include <utility>
 #include <vector>
-
-#include <glog/logging.h>
+#include "ceres/cost_function.h"
+#include "ceres/loss_function.h"
+#include "ceres/map_util.h"
 #include "ceres/parameter_block.h"
 #include "ceres/program.h"
 #include "ceres/residual_block.h"
 #include "ceres/stl_util.h"
-#include "ceres/map_util.h"
 #include "ceres/stringprintf.h"
-#include "ceres/cost_function.h"
-#include "ceres/loss_function.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.h b/extern/libmv/third_party/ceres/internal/ceres/problem_impl.h
index 523860e652a..2ca055448c3 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/problem_impl.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/problem_impl.h
@@ -118,7 +118,7 @@ class ProblemImpl {
   map<double*, ParameterBlock*> parameter_block_map_;
 
   internal::scoped_ptr<internal::Program> program_;
-  DISALLOW_COPY_AND_ASSIGN(ProblemImpl);
+  CERES_DISALLOW_COPY_AND_ASSIGN(ProblemImpl);
 };
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/program.cc b/extern/libmv/third_party/ceres/internal/ceres/program.cc
index 444b1020253..82d76d39233 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/program.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/program.cc
@@ -32,14 +32,18 @@
 
 #include <map>
 #include <vector>
+#include "ceres/casts.h"
+#include "ceres/compressed_row_sparse_matrix.h"
+#include "ceres/cost_function.h"
+#include "ceres/evaluator.h"
+#include "ceres/internal/port.h"
+#include "ceres/local_parameterization.h"
+#include "ceres/loss_function.h"
+#include "ceres/map_util.h"
 #include "ceres/parameter_block.h"
+#include "ceres/problem.h"
 #include "ceres/residual_block.h"
 #include "ceres/stl_util.h"
-#include "ceres/map_util.h"
-#include "ceres/problem.h"
-#include "ceres/cost_function.h"
-#include "ceres/loss_function.h"
-#include "ceres/local_parameterization.h"
 
 namespace ceres {
 namespace internal {
@@ -69,7 +73,8 @@ vector<ResidualBlock*>* Program::mutable_residual_blocks() {
 
 bool Program::StateVectorToParameterBlocks(const double *state) {
   for (int i = 0; i < parameter_blocks_.size(); ++i) {
-    if (!parameter_blocks_[i]->SetState(state)) {
+    if (!parameter_blocks_[i]->IsConstant() &&
+        !parameter_blocks_[i]->SetState(state)) {
       return false;
     }
     state += parameter_blocks_[i]->Size();
@@ -86,9 +91,18 @@ void Program::ParameterBlocksToStateVector(double *state) const {
 
 void Program::CopyParameterBlockStateToUserState() {
   for (int i = 0; i < parameter_blocks_.size(); ++i) {
-    parameter_blocks_[i]->GetState(
-        parameter_blocks_[i]->mutable_user_state());
+    parameter_blocks_[i]->GetState(parameter_blocks_[i]->mutable_user_state());
+  }
+}
+
+bool Program::SetParameterBlockStatePtrsToUserStatePtrs() {
+  for (int i = 0; i < parameter_blocks_.size(); ++i) {
+    if (!parameter_blocks_[i]->IsConstant() &&
+        !parameter_blocks_[i]->SetState(parameter_blocks_[i]->user_state())) {
+      return false;
+    }
   }
+  return true;
 }
 
 bool Program::Plus(const double* state,
@@ -193,40 +207,25 @@ int Program::MaxParametersPerResidualBlock() const {
   return max_parameters;
 }
 
-bool Program::Evaluate(double* cost, double* residuals) {
-  *cost = 0.0;
-
-  // Scratch space is only needed if residuals is NULL.
-  scoped_array<double> scratch;
-  if (residuals == NULL) {
-    scratch.reset(new double[MaxScratchDoublesNeededForEvaluate()]);
-  } else {
-    // TODO(keir): Is this needed? Check by removing the equivalent statement in
-    // dense_evaluator.cc and running the tests.
-    VectorRef(residuals, NumResiduals()).setZero();
-  }
-
+int Program::MaxResidualsPerResidualBlock() const {
+  int max_residuals = 0;
   for (int i = 0; i < residual_blocks_.size(); ++i) {
-    ResidualBlock* residual_block = residual_blocks_[i];
-
-    // Evaluate the cost function for this residual.
-    double residual_cost;
-    if (!residual_block->Evaluate(&residual_cost,
-                                  residuals,
-                                  NULL,  // No jacobian.
-                                  scratch.get())) {
-      return false;
-    }
-
-    // Accumulate residual cost into the total cost.
-    *cost += residual_cost;
+    max_residuals = max(max_residuals,
+                        residual_blocks_[i]->NumResiduals());
+  }
+  return max_residuals;
+}
 
-    // Update the residuals cursor.
-    if (residuals != NULL) {
-      residuals += residual_block->NumResiduals();
-    }
+string Program::ToString() const {
+  string ret = "Program dump\n";
+  ret += StringPrintf("Number of parameter blocks: %d\n", NumParameterBlocks());
+  ret += StringPrintf("Number of parameters: %d\n", NumParameters());
+  ret += "Parameters:\n";
+  for (int i = 0; i < parameter_blocks_.size(); ++i) {
+    ret += StringPrintf("%d: %s\n",
+                        i, parameter_blocks_[i]->ToString().c_str());
   }
-  return true;
+  return ret;
 }
 
 }  // namespace internal
diff --git a/extern/libmv/third_party/ceres/internal/ceres/program.h b/extern/libmv/third_party/ceres/internal/ceres/program.h
index 113d352d562..5002b7e752e 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/program.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/program.h
@@ -31,6 +31,7 @@
 #ifndef CERES_INTERNAL_PROGRAM_H_
 #define CERES_INTERNAL_PROGRAM_H_
 
+#include <string>
 #include <vector>
 #include "ceres/internal/port.h"
 
@@ -71,9 +72,14 @@ class Program {
   bool StateVectorToParameterBlocks(const double *state);
   void ParameterBlocksToStateVector(double *state) const;
 
-  // Copy internal state out to the user's parameters.
+  // Copy internal state to the user's parameters.
   void CopyParameterBlockStateToUserState();
 
+  // Set the parameter block pointers to the user pointers. Since this
+  // runs parameter block set state internally, which may call local
+  // parameterizations, this can fail. False is returned on failure.
+  bool SetParameterBlockStatePtrsToUserStatePtrs();
+
   // Update a state vector for the program given a delta.
   bool Plus(const double* state,
             const double* delta,
@@ -103,16 +109,11 @@ class Program {
   int MaxScratchDoublesNeededForEvaluate() const;
   int MaxDerivativesPerResidualBlock() const;
   int MaxParametersPerResidualBlock() const;
+  int MaxResidualsPerResidualBlock() const;
 
-  // Evaluate the cost and maybe the residuals for the program. If residuals is
-  // NULL, then residuals are not calculated. If the jacobian is needed, instead
-  // use the various evaluators (e.g. dense_evaluator.h).
-  //
-  // This is a trivial implementation of evaluate not intended for use in the
-  // core solving loop. The other evaluators, which support constructing the
-  // jacobian in addition to the cost and residuals, are considerably
-  // complicated by the need to construct the jacobian.
-  bool Evaluate(double* cost, double* residuals);
+  // A human-readable dump of the parameter blocks for debugging.
+  // TODO(keir): If necessary, also dump the residual blocks.
+  string ToString() const;
 
  private:
   // The Program does not own the ParameterBlock or ResidualBlock objects.
diff --git a/extern/libmv/third_party/ceres/internal/ceres/program_evaluator.h b/extern/libmv/third_party/ceres/internal/ceres/program_evaluator.h
index 7ec74b1b269..6c48e7d7643 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/program_evaluator.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/program_evaluator.h
@@ -120,13 +120,18 @@ class ProgramEvaluator : public Evaluator {
   bool Evaluate(const double* state,
                 double* cost,
                 double* residuals,
+                double* gradient,
                 SparseMatrix* jacobian) {
     // The parameters are stateful, so set the state before evaluating.
     if (!program_->StateVectorToParameterBlocks(state)) {
       return false;
     }
 
-    if (jacobian) {
+    if (residuals != NULL) {
+      VectorRef(residuals, program_->NumResiduals()).setZero();
+    } 
+
+    if (jacobian != NULL) {
       jacobian->SetZero();
     }
 
@@ -158,13 +163,16 @@ class ProgramEvaluator : public Evaluator {
 
       // Prepare block residuals if requested.
       const ResidualBlock* residual_block = program_->residual_blocks()[i];
-      double* block_residuals = (residuals != NULL)
-                              ? (residuals + residual_layout_[i])
-                              : NULL;
+      double* block_residuals = NULL;
+      if (residuals != NULL) {
+        block_residuals = residuals + residual_layout_[i];
+      } else if (gradient != NULL) {
+        block_residuals = scratch->residual_block_residuals.get();
+      }
 
       // Prepare block jacobians if requested.
       double** block_jacobians = NULL;
-      if (jacobian != NULL) {
+      if (jacobian != NULL || gradient != NULL) {
         preparer->Prepare(residual_block,
                           i,
                           jacobian,
@@ -174,10 +182,11 @@ class ProgramEvaluator : public Evaluator {
 
       // Evaluate the cost, residuals, and jacobians.
       double block_cost;
-      if (!residual_block->Evaluate(&block_cost,
-                                    block_residuals,
-                                    block_jacobians,
-                                    scratch->scratch.get())) {
+      if (!residual_block->Evaluate(
+              &block_cost,
+              block_residuals,
+              block_jacobians,
+              scratch->residual_block_evaluate_scratch.get())) {
         abort = true;
 // This ensures that the OpenMP threads have a consistent view of 'abort'. Do
 // the flush inside the failure case so that there is usually only one
@@ -188,19 +197,49 @@ class ProgramEvaluator : public Evaluator {
 
       scratch->cost += block_cost;
 
+      // Store the jacobians, if they were requested.
       if (jacobian != NULL) {
         jacobian_writer_.Write(i,
                                residual_layout_[i],
                                block_jacobians,
                                jacobian);
       }
+
+      // Compute and store the gradient, if it was requested.
+      if (gradient != NULL) {
+        int num_residuals = residual_block->NumResiduals();
+        int num_parameter_blocks = residual_block->NumParameterBlocks();
+        for (int j = 0; j < num_parameter_blocks; ++j) {
+          const ParameterBlock* parameter_block =
+              residual_block->parameter_blocks()[j];
+          if (parameter_block->IsConstant()) {
+            continue;
+          }
+          MatrixRef block_jacobian(block_jacobians[j],
+                                   num_residuals,
+                                   parameter_block->LocalSize());
+          VectorRef block_gradient(scratch->gradient.get() +
+                                   parameter_block->delta_offset(),
+                                   parameter_block->LocalSize());
+          VectorRef block_residual(block_residuals, num_residuals);
+          block_gradient += block_residual.transpose() * block_jacobian;
+        }
+      }
     }
 
     if (!abort) {
-      // Sum the cost from each thread.
+      // Sum the cost and gradient (if requested) from each thread.
       (*cost) = 0.0;
+      int num_parameters = program_->NumEffectiveParameters();
+      if (gradient != NULL) {
+        VectorRef(gradient, num_parameters).setZero();
+      }
       for (int i = 0; i < options_.num_threads; ++i) {
         (*cost) += evaluate_scratch_[i].cost;
+        if (gradient != NULL) {
+          VectorRef(gradient, num_parameters) +=
+              VectorRef(evaluate_scratch_[i].gradient.get(), num_parameters);
+        }
       }
     }
     return !abort;
@@ -224,16 +263,28 @@ class ProgramEvaluator : public Evaluator {
   }
 
  private:
+  // Per-thread scratch space needed to evaluate and store each residual block.
   struct EvaluateScratch {
     void Init(int max_parameters_per_residual_block,
-              int max_scratch_doubles_needed_for_evaluate) {
+              int max_scratch_doubles_needed_for_evaluate,
+              int max_residuals_per_residual_block,
+              int num_parameters) {
+      residual_block_evaluate_scratch.reset(
+          new double[max_scratch_doubles_needed_for_evaluate]);
+      gradient.reset(new double[num_parameters]);
+      VectorRef(gradient.get(), num_parameters).setZero();
+      residual_block_residuals.reset(
+          new double[max_residuals_per_residual_block]);
       jacobian_block_ptrs.reset(
           new double*[max_parameters_per_residual_block]);
-      scratch.reset(new double[max_scratch_doubles_needed_for_evaluate]);
     }
 
     double cost;
-    scoped_array<double> scratch;
+    scoped_array<double> residual_block_evaluate_scratch;
+    // The gradient in the local parameterization.
+    scoped_array<double> gradient;
+    // Enough space to store the residual for the largest residual block.
+    scoped_array<double> residual_block_residuals;
     scoped_array<double*> jacobian_block_ptrs;
   };
 
@@ -256,11 +307,16 @@ class ProgramEvaluator : public Evaluator {
         program.MaxParametersPerResidualBlock();
     int max_scratch_doubles_needed_for_evaluate =
         program.MaxScratchDoublesNeededForEvaluate();
+    int max_residuals_per_residual_block =
+        program.MaxResidualsPerResidualBlock();
+    int num_parameters = program.NumEffectiveParameters();
 
     EvaluateScratch* evaluate_scratch = new EvaluateScratch[num_threads];
     for (int i = 0; i < num_threads; i++) {
       evaluate_scratch[i].Init(max_parameters_per_residual_block,
-                               max_scratch_doubles_needed_for_evaluate);
+                               max_scratch_doubles_needed_for_evaluate,
+                               max_residuals_per_residual_block,
+                               num_parameters);
     }
     return evaluate_scratch;
   }
diff --git a/extern/libmv/third_party/ceres/internal/ceres/random.h b/extern/libmv/third_party/ceres/internal/ceres/random.h
index 769e0b4dd27..352c0032b5a 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/random.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/random.h
@@ -27,21 +27,44 @@
 // POSSIBILITY OF SUCH DAMAGE.
 //
 // Author: keir@google.com (Keir Mierle)
+//         sameeragarwal@google.com (Sameer Agarwal)
 
 #ifndef CERES_INTERNAL_RANDOM_H_
 #define CERES_INTERNAL_RANDOM_H_
 
+#include <cmath>
+#include <cstdlib>
+#include "ceres/internal/port.h"
+
 namespace ceres {
 
-inline double RandDouble() {
-  double r = rand();
-  return r / RAND_MAX;
+inline void SetRandomState(int state) {
+  srand(state);
 }
 
 inline int Uniform(int n) {
   return rand() % n;
 }
 
+inline double RandDouble() {
+  double r = static_cast<double>(rand());
+  return r / RAND_MAX;
+}
+
+// Box-Muller algorithm for normal random number generation.
+// http://en.wikipedia.org/wiki/Box-Muller_transform
+inline double RandNormal() {
+  double x1, x2, w;
+  do {
+    x1 = 2.0 * RandDouble() - 1.0;
+    x2 = 2.0 * RandDouble() - 1.0;
+    w = x1 * x1 + x2 * x2;
+  } while ( w >= 1.0 || w == 0.0 );
+
+  w = sqrt((-2.0 * log(w)) / w);
+  return x1 * w;
+}
+
 }  // namespace ceres
 
 #endif  // CERES_INTERNAL_RANDOM_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/residual_block.cc b/extern/libmv/third_party/ceres/internal/ceres/residual_block.cc
index 03867891dba..bdb88b1dd97 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/residual_block.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/residual_block.cc
@@ -102,8 +102,11 @@ bool ResidualBlock::Evaluate(double* cost,
 
   InvalidateEvaluation(*this, cost, residuals, eval_jacobians);
 
-  if (!cost_function_->Evaluate(parameters.get(), residuals, eval_jacobians) ||
-      !IsEvaluationValid(*this,
+  if (!cost_function_->Evaluate(parameters.get(), residuals, eval_jacobians)) {
+    return false;
+  }
+
+  if (!IsEvaluationValid(*this,
                          parameters.get(),
                          cost,
                          residuals,
diff --git a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.cc b/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.cc
index 28e03130844..9442bb2a1c1 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.cc
@@ -33,46 +33,17 @@
 #include <cmath>
 #include <cstddef>
 #include <limits>
-#include <glog/logging.h>
-#include "ceres/residual_block.h"
-#include "ceres/parameter_block.h"
-#include "ceres/stringprintf.h"
+#include "ceres/array_utils.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/port.h"
-
-#ifdef _MSC_VER
-#  define isfinite _finite
-#endif
+#include "ceres/parameter_block.h"
+#include "ceres/residual_block.h"
+#include "ceres/stringprintf.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
 
-// It is a near impossibility that user code generates this exact
-// value in normal operation, thus we will use it to fill arrays
-// before passing them to user code. If on return an element of the
-// array still contains this value, we will assume that the user code
-// did not write to that memory location.
-static const double kImpossibleValue = 1e302;
-
-bool IsArrayValid(const int size, const double* x) {
-  if (x != NULL) {
-    for (int i = 0; i < size; ++i) {
-      if (!isfinite(x[i]) || (x[i] == kImpossibleValue))  {
-        return false;
-      }
-    }
-  }
-  return true;
-}
-
-void InvalidateArray(const int size, double* x) {
-  if (x != NULL) {
-    for (int i = 0; i < size; ++i) {
-      x[i] = kImpossibleValue;
-    }
-  }
-}
-
 void InvalidateEvaluation(const ResidualBlock& block,
                           double* cost,
                           double* residuals,
@@ -92,7 +63,7 @@ void InvalidateEvaluation(const ResidualBlock& block,
 
 // Utility routine to print an array of doubles to a string. If the
 // array pointer is NULL, it is treated as an array of zeros.
-void AppendArrayToString(const int size, const double* x, string* result) {
+static void AppendArrayToString(const int size, const double* x, string* result) {
   for (int i = 0; i < size; ++i) {
     if (x == NULL) {
       StringAppendF(result, "Not Computed  ");
diff --git a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.h b/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.h
index 228867cc60c..7051c2112fd 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/residual_block_utils.h
@@ -51,15 +51,6 @@ namespace internal {
 
 class ResidualBlock;
 
-// Fill the array x with an impossible value that the user code is
-// never expected to compute.
-void InvalidateArray(int size, double* x);
-
-// Check if all the entries of the array x are valid, i.e. all the
-// values in the array should be finite and none of them should be
-// equal to the "impossible" value used by InvalidateArray.
-bool IsArrayValid(int size, const double* x);
-
 // Invalidate cost, resdual and jacobian arrays (if not NULL).
 void InvalidateEvaluation(const ResidualBlock& block,
                           double* cost,
diff --git a/extern/libmv/third_party/ceres/internal/ceres/runtime_numeric_diff_cost_function.cc b/extern/libmv/third_party/ceres/internal/ceres/runtime_numeric_diff_cost_function.cc
index ac6d8aa279a..7af275c1dd8 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/runtime_numeric_diff_cost_function.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/runtime_numeric_diff_cost_function.cc
@@ -35,11 +35,10 @@
 #include <algorithm>
 #include <numeric>
 #include <vector>
-
-#include <glog/logging.h>
 #include "Eigen/Dense"
 #include "ceres/cost_function.h"
 #include "ceres/internal/scoped_ptr.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.cc
index 2bc8cdd6bec..2cbe78d133a 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.cc
@@ -32,7 +32,13 @@
 #include <ctime>
 #include <set>
 #include <vector>
+
+#ifndef CERES_NO_CXSPARSE
+#include "cs.h"
+#endif  // CERES_NO_CXSPARSE
+
 #include "Eigen/Dense"
+#include "glog/logging.h"
 #include "ceres/block_random_access_dense_matrix.h"
 #include "ceres/block_random_access_matrix.h"
 #include "ceres/block_random_access_sparse_matrix.h"
@@ -48,6 +54,7 @@
 #include "ceres/internal/scoped_ptr.h"
 #include "ceres/types.h"
 
+
 namespace ceres {
 namespace internal {
 
@@ -57,7 +64,7 @@ LinearSolver::Summary SchurComplementSolver::SolveImpl(
     const LinearSolver::PerSolveOptions& per_solve_options,
     double* x) {
   const time_t start_time = time(NULL);
-  if (!options_.constant_sparsity || (eliminator_.get() == NULL)) {
+  if (eliminator_.get() == NULL) {
     InitStorage(A->block_structure());
     DetectStructure(*A->block_structure(),
                     options_.num_eliminate_blocks,
@@ -88,11 +95,11 @@ LinearSolver::Summary SchurComplementSolver::SolveImpl(
   const time_t backsubstitute_time = time(NULL);
   summary.termination_type = TOLERANCE;
 
-  VLOG(2) << "time (sec) total: " << backsubstitute_time - start_time
-          << " init: " << init_time - start_time
-          << " eliminate: " << eliminate_time - init_time
-          << " solve: " << solve_time - eliminate_time
-          << " backsubstitute: " << backsubstitute_time - solve_time;
+  VLOG(2) << "time (sec) total: " << (backsubstitute_time - start_time)
+          << " init: " << (init_time - start_time)
+          << " eliminate: " << (eliminate_time - init_time)
+          << " solve: " << (solve_time - eliminate_time)
+          << " backsubstitute: " << (backsubstitute_time - solve_time);
   return summary;
 }
 
@@ -139,18 +146,33 @@ bool DenseSchurComplementSolver::SolveReducedLinearSystem(double* solution) {
   return true;
 }
 
-#ifndef CERES_NO_SUITESPARSE
+
 SparseSchurComplementSolver::SparseSchurComplementSolver(
     const LinearSolver::Options& options)
-    : SchurComplementSolver(options),
-      symbolic_factor_(NULL) {
+    : SchurComplementSolver(options) {
+#ifndef CERES_NO_SUITESPARSE
+  factor_ = NULL;
+#endif  // CERES_NO_SUITESPARSE
+
+#ifndef CERES_NO_CXSPARSE
+  cxsparse_factor_ = NULL;
+#endif  // CERES_NO_CXSPARSE
 }
 
 SparseSchurComplementSolver::~SparseSchurComplementSolver() {
-  if (symbolic_factor_ != NULL) {
-    ss_.Free(symbolic_factor_);
-    symbolic_factor_ = NULL;
+#ifndef CERES_NO_SUITESPARSE
+  if (factor_ != NULL) {
+    ss_.Free(factor_);
+    factor_ = NULL;
   }
+#endif  // CERES_NO_SUITESPARSE
+
+#ifndef CERES_NO_CXSPARSE
+  if (cxsparse_factor_ != NULL) {
+    cxsparse_.Free(cxsparse_factor_);
+    cxsparse_factor_ = NULL;
+  }
+#endif  // CERES_NO_CXSPARSE
 }
 
 // Determine the non-zero blocks in the Schur Complement matrix, and
@@ -161,13 +183,13 @@ void SparseSchurComplementSolver::InitStorage(
   const int num_col_blocks = bs->cols.size();
   const int num_row_blocks = bs->rows.size();
 
-  vector<int> blocks(num_col_blocks - num_eliminate_blocks, 0);
+  blocks_.resize(num_col_blocks - num_eliminate_blocks, 0);
   for (int i = num_eliminate_blocks; i < num_col_blocks; ++i) {
-    blocks[i - num_eliminate_blocks] = bs->cols[i].size;
+    blocks_[i - num_eliminate_blocks] = bs->cols[i].size;
   }
 
   set<pair<int, int> > block_pairs;
-  for (int i = 0; i < blocks.size(); ++i) {
+  for (int i = 0; i < blocks_.size(); ++i) {
     block_pairs.insert(make_pair(i, i));
   }
 
@@ -220,15 +242,34 @@ void SparseSchurComplementSolver::InitStorage(
     }
   }
 
-  set_lhs(new BlockRandomAccessSparseMatrix(blocks, block_pairs));
+  set_lhs(new BlockRandomAccessSparseMatrix(blocks_, block_pairs));
   set_rhs(new double[lhs()->num_rows()]);
 }
 
+bool SparseSchurComplementSolver::SolveReducedLinearSystem(double* solution) {
+  switch (options().sparse_linear_algebra_library) {
+    case SUITE_SPARSE:
+      return SolveReducedLinearSystemUsingSuiteSparse(solution);
+    case CX_SPARSE:
+      return SolveReducedLinearSystemUsingCXSparse(solution);
+    default:
+      LOG(FATAL) << "Unknown sparse linear algebra library : "
+                 << options().sparse_linear_algebra_library;
+  }
+
+  LOG(FATAL) << "Unknown sparse linear algebra library : "
+             << options().sparse_linear_algebra_library;
+  return false;
+}
+
+#ifndef CERES_NO_SUITESPARSE
 // Solve the system Sx = r, assuming that the matrix S is stored in a
 // BlockRandomAccessSparseMatrix.  The linear system is solved using
 // CHOLMOD's sparse cholesky factorization routines.
-bool SparseSchurComplementSolver::SolveReducedLinearSystem(double* solution) {
-  // Extract the TripletSparseMatrix that is used for actually storing S.
+bool SparseSchurComplementSolver::SolveReducedLinearSystemUsingSuiteSparse(
+    double* solution) {
+  const time_t start_time = time(NULL);
+
   TripletSparseMatrix* tsm =
       const_cast<TripletSparseMatrix*>(
           down_cast<const BlockRandomAccessSparseMatrix*>(lhs())->matrix());
@@ -245,30 +286,38 @@ bool SparseSchurComplementSolver::SolveReducedLinearSystem(double* solution) {
   // The matrix is symmetric, and the upper triangular part of the
   // matrix contains the values.
   cholmod_lhs->stype = 1;
+  const time_t lhs_time = time(NULL);
 
   cholmod_dense*  cholmod_rhs =
       ss_.CreateDenseVector(const_cast<double*>(rhs()), num_rows, num_rows);
+  const time_t rhs_time = time(NULL);
 
   // Symbolic factorization is computed if we don't already have one handy.
-  if (symbolic_factor_ == NULL) {
-    symbolic_factor_ = ss_.AnalyzeCholesky(cholmod_lhs);
+  if (factor_ == NULL) {
+    if (options().use_block_amd) {
+      factor_ = ss_.BlockAnalyzeCholesky(cholmod_lhs, blocks_, blocks_);
+    } else {
+      factor_ = ss_.AnalyzeCholesky(cholmod_lhs);
+    }
+
+    if (VLOG_IS_ON(2)) {
+      cholmod_print_common("Symbolic Analysis", ss_.mutable_cc());
+    }
   }
 
+  CHECK_NOTNULL(factor_);
+
+  const time_t symbolic_time = time(NULL);
   cholmod_dense* cholmod_solution =
-      ss_.SolveCholesky(cholmod_lhs, symbolic_factor_, cholmod_rhs);
+      ss_.SolveCholesky(cholmod_lhs, factor_, cholmod_rhs);
+
+  const time_t solve_time = time(NULL);
 
   ss_.Free(cholmod_lhs);
   cholmod_lhs = NULL;
   ss_.Free(cholmod_rhs);
   cholmod_rhs = NULL;
 
-  // If sparsity is not constant across calls, then reset the symbolic
-  // factorization.
-  if (!options().constant_sparsity) {
-    ss_.Free(symbolic_factor_);
-    symbolic_factor_ = NULL;
-  }
-
   if (cholmod_solution == NULL) {
     LOG(ERROR) << "CHOLMOD solve failed.";
     return false;
@@ -277,9 +326,63 @@ bool SparseSchurComplementSolver::SolveReducedLinearSystem(double* solution) {
   VectorRef(solution, num_rows)
       = VectorRef(static_cast<double*>(cholmod_solution->x), num_rows);
   ss_.Free(cholmod_solution);
+  const time_t final_time = time(NULL);
+  VLOG(2) << "time: " << (final_time - start_time)
+          << " lhs : " << (lhs_time - start_time)
+          << " rhs:  " << (rhs_time - lhs_time)
+          << " analyze: " <<  (symbolic_time - rhs_time)
+          << " factor_and_solve: " << (solve_time - symbolic_time)
+          << " cleanup: " << (final_time - solve_time);
   return true;
 }
+#else
+bool SparseSchurComplementSolver::SolveReducedLinearSystemUsingSuiteSparse(
+    double* solution) {
+  LOG(FATAL) << "No SuiteSparse support in Ceres.";
+  return false;
+}
 #endif  // CERES_NO_SUITESPARSE
 
+#ifndef CERES_NO_CXSPARSE
+// Solve the system Sx = r, assuming that the matrix S is stored in a
+// BlockRandomAccessSparseMatrix.  The linear system is solved using
+// CXSparse's sparse cholesky factorization routines.
+bool SparseSchurComplementSolver::SolveReducedLinearSystemUsingCXSparse(
+    double* solution) {
+  // Extract the TripletSparseMatrix that is used for actually storing S.
+  TripletSparseMatrix* tsm =
+      const_cast<TripletSparseMatrix*>(
+          down_cast<const BlockRandomAccessSparseMatrix*>(lhs())->matrix());
+
+  const int num_rows = tsm->num_rows();
+
+  // The case where there are no f blocks, and the system is block
+  // diagonal.
+  if (num_rows == 0) {
+    return true;
+  }
+
+  cs_di* lhs = CHECK_NOTNULL(cxsparse_.CreateSparseMatrix(tsm));
+  VectorRef(solution, num_rows) = ConstVectorRef(rhs(), num_rows);
+
+  // Compute symbolic factorization if not available.
+  if (cxsparse_factor_ == NULL) {
+    cxsparse_factor_ = CHECK_NOTNULL(cxsparse_.AnalyzeCholesky(lhs));
+  }
+
+  // Solve the linear system.
+  bool ok = cxsparse_.SolveCholesky(lhs, cxsparse_factor_, solution);
+
+  cxsparse_.Free(lhs);
+  return ok;
+}
+#else
+bool SparseSchurComplementSolver::SolveReducedLinearSystemUsingCXSparse(
+    double* solution) {
+  LOG(FATAL) << "No CXSparse support in Ceres.";
+  return false;
+}
+#endif  // CERES_NO_CXPARSE
+
 }  // namespace internal
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.h b/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.h
index 039bc09e3ce..ea1b3184c33 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/schur_complement_solver.h
@@ -31,9 +31,13 @@
 #ifndef CERES_INTERNAL_SCHUR_COMPLEMENT_SOLVER_H_
 #define CERES_INTERNAL_SCHUR_COMPLEMENT_SOLVER_H_
 
+#include <set>
+#include <utility>
+
 #include "ceres/block_random_access_matrix.h"
 #include "ceres/block_sparse_matrix.h"
 #include "ceres/block_structure.h"
+#include "ceres/cxsparse.h"
 #include "ceres/linear_solver.h"
 #include "ceres/schur_eliminator.h"
 #include "ceres/suitesparse.h"
@@ -128,7 +132,7 @@ class SchurComplementSolver : public BlockSparseMatrixBaseSolver {
   scoped_ptr<BlockRandomAccessMatrix> lhs_;
   scoped_array<double> rhs_;
 
-  DISALLOW_COPY_AND_ASSIGN(SchurComplementSolver);
+  CERES_DISALLOW_COPY_AND_ASSIGN(SchurComplementSolver);
 };
 
 // Dense Cholesky factorization based solver.
@@ -142,10 +146,10 @@ class DenseSchurComplementSolver : public SchurComplementSolver {
   virtual void InitStorage(const CompressedRowBlockStructure* bs);
   virtual bool SolveReducedLinearSystem(double* solution);
 
-  DISALLOW_COPY_AND_ASSIGN(DenseSchurComplementSolver);
+  CERES_DISALLOW_COPY_AND_ASSIGN(DenseSchurComplementSolver);
 };
 
-#ifndef CERES_NO_SUITESPARSE
+
 // Sparse Cholesky factorization based solver.
 class SparseSchurComplementSolver : public SchurComplementSolver {
  public:
@@ -155,26 +159,26 @@ class SparseSchurComplementSolver : public SchurComplementSolver {
  private:
   virtual void InitStorage(const CompressedRowBlockStructure* bs);
   virtual bool SolveReducedLinearSystem(double* solution);
+  bool SolveReducedLinearSystemUsingSuiteSparse(double* solution);
+  bool SolveReducedLinearSystemUsingCXSparse(double* solution);
 
+  // Size of the blocks in the Schur complement.
+  vector<int> blocks_;
 
+#ifndef CERES_NO_SUITESPARSE
   SuiteSparse ss_;
   // Symbolic factorization of the reduced linear system. Precomputed
-  // once and reused if constant_sparsity_ is true.
-  cholmod_factor* symbolic_factor_;
-  DISALLOW_COPY_AND_ASSIGN(SparseSchurComplementSolver);
-};
-#else  // CERES_NO_SUITESPARSE
-class SparseSchurComplementSolver : public SchurComplementSolver {
- public:
-  explicit SparseSchurComplementSolver(const LinearSolver::Options& options)
-      : SchurComplementSolver(options) {
-    LOG(FATAL) << "SPARSE_SCHUR is not available. Please "
-        "build Ceres with SuiteSparse.";
-  }
+  // once and reused in subsequent calls.
+  cholmod_factor* factor_;
+#endif  // CERES_NO_SUITESPARSE
 
-  virtual ~SparseSchurComplementSolver() {}
+#ifndef CERES_NO_CXSPARSE
+  CXSparse cxsparse_;
+  // Cached factorization
+  cs_dis* cxsparse_factor_;
+#endif  // CERES_NO_CXSPARSE
+  CERES_DISALLOW_COPY_AND_ASSIGN(SparseSchurComplementSolver);
 };
-#endif  // CERES_NO_SUITESPARSE
 
 }  // namespace internal
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator_impl.h b/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator_impl.h
index a388d005424..6120db9b009 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator_impl.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/schur_eliminator_impl.h
@@ -188,7 +188,7 @@ Eliminate(const BlockSparseMatrixBase* A,
         typename EigenTypes<kFBlockSize>::ConstVectorRef
             diag(D + bs->cols[i].position, block_size);
 
-        MutexLock l(&cell_info->m);
+        CeresMutexLock l(&cell_info->m);
         MatrixRef m(cell_info->values, row_stride, col_stride);
         m.block(r, c, block_size, block_size).diagonal()
             += diag.array().square().matrix();
@@ -387,7 +387,7 @@ UpdateRhs(const Chunk& chunk,
             row.block.size, block_size);
 
       const int block = block_id - num_eliminate_blocks_;
-      MutexLock l(rhs_locks_[block]);
+      CeresMutexLock l(rhs_locks_[block]);
       typename EigenTypes<kFBlockSize>::VectorRef
           (rhs + lhs_row_layout_[block], block_size).noalias()
           += b.transpose() * sj;
@@ -523,7 +523,7 @@ ChunkOuterProduct(const CompressedRowBlockStructure* bs,
       const typename EigenTypes<kEBlockSize, kFBlockSize>::ConstMatrixRef
           b2(buffer + it2->second, e_block_size, block2_size);
 
-      MutexLock l(&cell_info->m);
+      CeresMutexLock l(&cell_info->m);
       MatrixRef m(cell_info->values, row_stride, col_stride);
 
       // We explicitly construct a block object here instead of using
@@ -532,7 +532,29 @@ ChunkOuterProduct(const CompressedRowBlockStructure* bs,
       // like the Matrix class does.
       Eigen::Block<MatrixRef, kFBlockSize, kFBlockSize>
           block(m, r, c,  block1_size, block2_size);
-      block.noalias() -=  b1_transpose_inverse_ete * b2;
+#ifdef CERES_WORK_AROUND_ANDROID_NDK_COMPILER_BUG
+      // Removing the ".noalias()" annotation on the following statement is
+      // necessary to produce a correct build with the Android NDK, including
+      // versions 6, 7, 8, and 8b, when built with STLPort and the
+      // non-standalone toolchain (i.e. ndk-build). This appears to be a
+      // compiler bug; if the workaround is not in place, the line
+      //
+      //   block.noalias() -= b1_transpose_inverse_ete * b2;
+      //
+      // gets compiled to
+      //
+      //   block.noalias() += b1_transpose_inverse_ete * b2;
+      //
+      // which breaks schur elimination. Introducing a temporary by removing the
+      // .noalias() annotation causes the issue to disappear. Tracking this
+      // issue down was tricky, since the test suite doesn't run when built with
+      // the non-standalone toolchain.
+      //
+      // TODO(keir): Make a reproduction case for this and send it upstream.
+      block -= b1_transpose_inverse_ete * b2;
+#else
+      block.noalias() -= b1_transpose_inverse_ete * b2;
+#endif  // CERES_WORK_AROUND_ANDROID_NDK_COMPILER_BUG
     }
   }
 }
@@ -601,7 +623,7 @@ NoEBlockRowOuterProduct(const BlockSparseMatrixBase* A,
                                        &r, &c,
                                        &row_stride, &col_stride);
     if (cell_info != NULL) {
-      MutexLock l(&cell_info->m);
+      CeresMutexLock l(&cell_info->m);
       MatrixRef m(cell_info->values, row_stride, col_stride);
       m.block(r, c, block1_size, block1_size)
           .selfadjointView<Eigen::Upper>()
@@ -621,7 +643,7 @@ NoEBlockRowOuterProduct(const BlockSparseMatrixBase* A,
       }
 
       const int block2_size = bs->cols[row.cells[j].block_id].size;
-      MutexLock l(&cell_info->m);
+      CeresMutexLock l(&cell_info->m);
       MatrixRef m(cell_info->values, row_stride, col_stride);
       m.block(r, c, block1_size, block2_size).noalias() +=
           b1.transpose() * ConstMatrixRef(row_values + row.cells[j].position,
@@ -660,7 +682,7 @@ EBlockRowOuterProduct(const BlockSparseMatrixBase* A,
         continue;
       }
 
-      MutexLock l(&cell_info->m);
+      CeresMutexLock l(&cell_info->m);
       MatrixRef m(cell_info->values, row_stride, col_stride);
 
       Eigen::Block<MatrixRef, kFBlockSize, kFBlockSize>
@@ -687,7 +709,7 @@ EBlockRowOuterProduct(const BlockSparseMatrixBase* A,
              row.block.size,
              block2_size);
 
-      MutexLock l(&cell_info->m);
+      CeresMutexLock l(&cell_info->m);
       MatrixRef m(cell_info->values, row_stride, col_stride);
       Eigen::Block<MatrixRef, kFBlockSize, kFBlockSize>
           block(m, r, c,  block1_size, block2_size);
diff --git a/extern/libmv/third_party/ceres/internal/ceres/schur_ordering.cc b/extern/libmv/third_party/ceres/internal/ceres/schur_ordering.cc
index c4fc1da3c2f..1cdff4e6dec 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/schur_ordering.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/schur_ordering.cc
@@ -30,25 +30,14 @@
 
 #include "ceres/schur_ordering.h"
 
-#include <glog/logging.h>
 #include "ceres/graph.h"
 #include "ceres/graph_algorithms.h"
+#include "ceres/internal/scoped_ptr.h"
 #include "ceres/map_util.h"
 #include "ceres/parameter_block.h"
 #include "ceres/program.h"
 #include "ceres/residual_block.h"
-#include "ceres/internal/scoped_ptr.h"
-
-CERES_HASH_NAMESPACE_START
-
-// Allow us to hash pointers as if they were int's
-template<> struct hash< ::ceres::internal::ParameterBlock*> {
-  size_t operator()(::ceres::internal::ParameterBlock* x) const {
-    return reinterpret_cast<size_t>(x);
-  }
-};
-
-CERES_HASH_NAMESPACE_END
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -59,8 +48,7 @@ int ComputeSchurOrdering(const Program& program,
 
   scoped_ptr<Graph< ParameterBlock*> > graph(
       CHECK_NOTNULL(CreateHessianGraph(program)));
-  int independent_set_size =
-      IndependentSetOrdering<ParameterBlock*>(*graph, ordering);
+  int independent_set_size = IndependentSetOrdering(*graph, ordering);
   const vector<ParameterBlock*>& parameter_blocks = program.parameter_blocks();
 
   // Add the excluded blocks to back of the ordering vector.
diff --git a/extern/libmv/third_party/ceres/internal/ceres/solver.cc b/extern/libmv/third_party/ceres/internal/ceres/solver.cc
index 77f04d1d918..66ca93283a1 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/solver.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/solver.cc
@@ -32,36 +32,32 @@
 #include "ceres/solver.h"
 
 #include <vector>
-#include "ceres/levenberg_marquardt.h"
+#include "ceres/problem.h"
+#include "ceres/problem_impl.h"
 #include "ceres/program.h"
 #include "ceres/solver_impl.h"
 #include "ceres/stringprintf.h"
-#include "ceres/problem.h"
 
 namespace ceres {
 
 Solver::~Solver() {}
 
-// TODO(sameeragarwal): The timing code here should use a sub-second
-// timer.
+// TODO(sameeragarwal): Use subsecond timers.
 void Solver::Solve(const Solver::Options& options,
                    Problem* problem,
                    Solver::Summary* summary) {
   time_t start_time_seconds = time(NULL);
-  internal::SolverImpl::Solve(options, problem, summary);
+  internal::ProblemImpl* problem_impl =
+      CHECK_NOTNULL(problem)->problem_impl_.get();
+  internal::SolverImpl::Solve(options, problem_impl, summary);
   summary->total_time_in_seconds =  time(NULL) - start_time_seconds;
-  summary->preprocessor_time_in_seconds =
-      summary->total_time_in_seconds - summary->minimizer_time_in_seconds;
 }
 
 void Solve(const Solver::Options& options,
            Problem* problem,
            Solver::Summary* summary) {
-  time_t start_time_seconds = time(NULL);
-  internal::SolverImpl::Solve(options, problem, summary);
-  summary->total_time_in_seconds =  time(NULL) - start_time_seconds;
-  summary->preprocessor_time_in_seconds =
-      summary->total_time_in_seconds - summary->minimizer_time_in_seconds;
+  Solver solver;
+  solver.Solve(options, problem, summary);
 }
 
 Solver::Summary::Summary()
@@ -75,6 +71,7 @@ Solver::Summary::Summary()
       num_unsuccessful_steps(-1),
       preprocessor_time_in_seconds(-1.0),
       minimizer_time_in_seconds(-1.0),
+      postprocessor_time_in_seconds(-1.0),
       total_time_in_seconds(-1.0),
       num_parameter_blocks(-1),
       num_parameters(-1),
@@ -93,7 +90,9 @@ Solver::Summary::Summary()
       linear_solver_type_given(SPARSE_NORMAL_CHOLESKY),
       linear_solver_type_used(SPARSE_NORMAL_CHOLESKY),
       preconditioner_type(IDENTITY),
-      ordering_type(NATURAL) {
+      ordering_type(NATURAL),
+      trust_region_strategy_type(LEVENBERG_MARQUARDT),
+      sparse_linear_algebra_library(SUITE_SPARSE) {
 }
 
 string Solver::Summary::BriefReport() const {
@@ -136,7 +135,7 @@ string Solver::Summary::FullReport() const {
                             num_parameters);
     internal::StringAppendF(&report, "Residual blocks     % 10d\n",
                             num_residual_blocks);
-    internal::StringAppendF(&report, "Residual            % 10d\n\n",
+    internal::StringAppendF(&report, "Residuals           % 10d\n\n",
                             num_residuals);
   } else {
     internal::StringAppendF(&report, "%45s    %21s\n", "Original", "Reduced");
@@ -183,10 +182,33 @@ string Solver::Summary::FullReport() const {
 
   internal::StringAppendF(&report, "Threads:            % 25d% 25d\n",
                           num_threads_given, num_threads_used);
-  internal::StringAppendF(&report, "Linear Solver Threads:% 23d% 25d\n",
+  internal::StringAppendF(&report, "Linear solver threads % 23d% 25d\n",
                           num_linear_solver_threads_given,
                           num_linear_solver_threads_used);
 
+  if (linear_solver_type_used == SPARSE_NORMAL_CHOLESKY ||
+      linear_solver_type_used == SPARSE_SCHUR ||
+      (linear_solver_type_used == ITERATIVE_SCHUR &&
+       (preconditioner_type == SCHUR_JACOBI ||
+        preconditioner_type == CLUSTER_JACOBI ||
+        preconditioner_type == CLUSTER_TRIDIAGONAL))) {
+    internal::StringAppendF(&report, "\nSparse Linear Algebra Library %15s\n",
+                            SparseLinearAlgebraLibraryTypeToString(
+                                sparse_linear_algebra_library));
+  }
+
+  internal::StringAppendF(&report, "Trust Region Strategy     %19s",
+                          TrustRegionStrategyTypeToString(
+                              trust_region_strategy_type));
+  if (trust_region_strategy_type == DOGLEG) {
+    if (dogleg_type == TRADITIONAL_DOGLEG) {
+      internal::StringAppendF(&report, " (TRADITIONAL)");
+    } else {
+      internal::StringAppendF(&report, " (SUBSPACE)");
+    }
+  }
+  internal::StringAppendF(&report, "\n");
+
 
   if (termination_type == DID_NOT_RUN) {
     CHECK(!error.empty())
diff --git a/extern/libmv/third_party/ceres/internal/ceres/solver_impl.cc b/extern/libmv/third_party/ceres/internal/ceres/solver_impl.cc
index ed07d9dc6d7..8ef5b98e35f 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/solver_impl.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/solver_impl.cc
@@ -30,40 +30,29 @@
 
 #include "ceres/solver_impl.h"
 
+#include <cstdio>
 #include <iostream>  // NOLINT
 #include <numeric>
 #include "ceres/evaluator.h"
 #include "ceres/gradient_checking_cost_function.h"
-#include "ceres/levenberg_marquardt.h"
+#include "ceres/iteration_callback.h"
+#include "ceres/levenberg_marquardt_strategy.h"
 #include "ceres/linear_solver.h"
 #include "ceres/map_util.h"
 #include "ceres/minimizer.h"
 #include "ceres/parameter_block.h"
+#include "ceres/problem.h"
 #include "ceres/problem_impl.h"
 #include "ceres/program.h"
 #include "ceres/residual_block.h"
 #include "ceres/schur_ordering.h"
 #include "ceres/stringprintf.h"
-#include "ceres/iteration_callback.h"
-#include "ceres/problem.h"
+#include "ceres/trust_region_minimizer.h"
 
 namespace ceres {
 namespace internal {
 namespace {
 
-void EvaluateCostAndResiduals(ProblemImpl* problem_impl,
-                              double* cost,
-                              vector<double>* residuals) {
-  CHECK_NOTNULL(cost);
-  Program* program = CHECK_NOTNULL(problem_impl)->mutable_program();
-  if (residuals != NULL) {
-    residuals->resize(program->NumResiduals());
-    program->Evaluate(cost, &(*residuals)[0]);
-  } else {
-    program->Evaluate(cost, NULL);
-  }
-}
-
 // Callback for updating the user's parameter blocks. Updates are only
 // done if the step is successful.
 class StateUpdatingCallback : public IterationCallback {
@@ -96,7 +85,7 @@ class LoggingCallback : public IterationCallback {
   CallbackReturnType operator()(const IterationSummary& summary) {
     const char* kReportRowFormat =
         "% 4d: f:% 8e d:% 3.2e g:% 3.2e h:% 3.2e "
-        "rho:% 3.2e mu:% 3.2e li:% 3d";
+        "rho:% 3.2e mu:% 3.2e li:% 3d it:% 3.2e tt:% 3.2e";
     string output = StringPrintf(kReportRowFormat,
                                  summary.iteration,
                                  summary.cost,
@@ -104,8 +93,10 @@ class LoggingCallback : public IterationCallback {
                                  summary.gradient_max_norm,
                                  summary.step_norm,
                                  summary.relative_decrease,
-                                 summary.mu,
-                                 summary.linear_solver_iterations);
+                                 summary.trust_region_radius,
+                                 summary.linear_solver_iterations,
+                                 summary.iteration_time_in_seconds,
+                                 summary.cumulative_time_in_seconds);
     if (log_to_stdout_) {
       cout << output << endl;
     } else {
@@ -118,44 +109,101 @@ class LoggingCallback : public IterationCallback {
   const bool log_to_stdout_;
 };
 
+// Basic callback to record the execution of the solver to a file for
+// offline analysis.
+class FileLoggingCallback : public IterationCallback {
+ public:
+  explicit FileLoggingCallback(const string& filename)
+      : fptr_(NULL) {
+    fptr_ = fopen(filename.c_str(), "w");
+    CHECK_NOTNULL(fptr_);
+  }
+
+  virtual ~FileLoggingCallback() {
+    if (fptr_ != NULL) {
+      fclose(fptr_);
+    }
+  }
+
+  virtual CallbackReturnType operator()(const IterationSummary& summary) {
+    fprintf(fptr_,
+            "%4d %e %e\n",
+            summary.iteration,
+            summary.cost,
+            summary.cumulative_time_in_seconds);
+    return SOLVER_CONTINUE;
+  }
+ private:
+    FILE* fptr_;
+};
+
 }  // namespace
 
 void SolverImpl::Minimize(const Solver::Options& options,
                           Program* program,
                           Evaluator* evaluator,
                           LinearSolver* linear_solver,
-                          double* initial_parameters,
-                          double* final_parameters,
+                          double* parameters,
                           Solver::Summary* summary) {
   Minimizer::Options minimizer_options(options);
 
+  // TODO(sameeragarwal): Add support for logging the configuration
+  // and more detailed stats.
+  scoped_ptr<IterationCallback> file_logging_callback;
+  if (!options.solver_log.empty()) {
+    file_logging_callback.reset(new FileLoggingCallback(options.solver_log));
+    minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(),
+                                       file_logging_callback.get());
+  }
+
   LoggingCallback logging_callback(options.minimizer_progress_to_stdout);
   if (options.logging_type != SILENT) {
-    minimizer_options.callbacks.push_back(&logging_callback);
+    minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(),
+                                       &logging_callback);
   }
 
-  StateUpdatingCallback updating_callback(program, initial_parameters);
+  StateUpdatingCallback updating_callback(program, parameters);
   if (options.update_state_every_iteration) {
-    minimizer_options.callbacks.push_back(&updating_callback);
-  }
-
-  LevenbergMarquardt levenberg_marquardt;
-
-  time_t start_minimizer_time_seconds = time(NULL);
-  levenberg_marquardt.Minimize(minimizer_options,
-                               evaluator,
-                               linear_solver,
-                               initial_parameters,
-                               final_parameters,
-                               summary);
-  summary->minimizer_time_in_seconds =
-      time(NULL) - start_minimizer_time_seconds;
+    // This must get pushed to the front of the callbacks so that it is run
+    // before any of the user callbacks.
+    minimizer_options.callbacks.insert(minimizer_options.callbacks.begin(),
+                                       &updating_callback);
+  }
+
+  minimizer_options.evaluator = evaluator;
+  scoped_ptr<SparseMatrix> jacobian(evaluator->CreateJacobian());
+  minimizer_options.jacobian = jacobian.get();
+
+  TrustRegionStrategy::Options trust_region_strategy_options;
+  trust_region_strategy_options.linear_solver = linear_solver;
+  trust_region_strategy_options.initial_radius =
+      options.initial_trust_region_radius;
+  trust_region_strategy_options.max_radius = options.max_trust_region_radius;
+  trust_region_strategy_options.lm_min_diagonal = options.lm_min_diagonal;
+  trust_region_strategy_options.lm_max_diagonal = options.lm_max_diagonal;
+  trust_region_strategy_options.trust_region_strategy_type =
+      options.trust_region_strategy_type;
+  trust_region_strategy_options.dogleg_type = options.dogleg_type;
+  scoped_ptr<TrustRegionStrategy> strategy(
+      TrustRegionStrategy::Create(trust_region_strategy_options));
+  minimizer_options.trust_region_strategy = strategy.get();
+
+  TrustRegionMinimizer minimizer;
+  time_t minimizer_start_time = time(NULL);
+  minimizer.Minimize(minimizer_options, parameters, summary);
+  summary->minimizer_time_in_seconds = time(NULL) - minimizer_start_time;
 }
 
 void SolverImpl::Solve(const Solver::Options& original_options,
-                       Problem* problem,
+                       ProblemImpl* original_problem_impl,
                        Solver::Summary* summary) {
+  time_t solver_start_time = time(NULL);
   Solver::Options options(original_options);
+  Program* original_program = original_problem_impl->mutable_program();
+  ProblemImpl* problem_impl = original_problem_impl;
+  // Reset the summary object to its default values.
+  *CHECK_NOTNULL(summary) = Solver::Summary();
+
 
 #ifndef CERES_USE_OPENMP
   if (options.num_threads > 1) {
@@ -174,8 +222,6 @@ void SolverImpl::Solve(const Solver::Options& original_options,
   }
 #endif
 
-  // Reset the summary object to its default values;
-  *CHECK_NOTNULL(summary) = Solver::Summary();
   summary->linear_solver_type_given = options.linear_solver_type;
   summary->num_eliminate_blocks_given = original_options.num_eliminate_blocks;
   summary->num_threads_given = original_options.num_threads;
@@ -183,32 +229,38 @@ void SolverImpl::Solve(const Solver::Options& original_options,
       original_options.num_linear_solver_threads;
   summary->ordering_type = original_options.ordering_type;
 
-  ProblemImpl* problem_impl = CHECK_NOTNULL(problem)->problem_impl_.get();
-
   summary->num_parameter_blocks = problem_impl->NumParameterBlocks();
   summary->num_parameters = problem_impl->NumParameters();
   summary->num_residual_blocks = problem_impl->NumResidualBlocks();
   summary->num_residuals = problem_impl->NumResiduals();
 
   summary->num_threads_used = options.num_threads;
-
-  // Evaluate the initial cost and residual vector (if needed). The
-  // initial cost needs to be computed on the original unpreprocessed
-  // problem, as it is used to determine the value of the "fixed" part
-  // of the objective function after the problem has undergone
-  // reduction. Also the initial residuals are in the order in which
-  // the user added the ResidualBlocks to the optimization problem.
-  EvaluateCostAndResiduals(problem_impl,
-                           &summary->initial_cost,
-                           options.return_initial_residuals
-                           ? &summary->initial_residuals
-                           : NULL);
+  summary->sparse_linear_algebra_library =
+      options.sparse_linear_algebra_library;
+  summary->trust_region_strategy_type = options.trust_region_strategy_type;
+  summary->dogleg_type = options.dogleg_type;
+
+  // Evaluate the initial cost, residual vector and the jacobian
+  // matrix if requested by the user. The initial cost needs to be
+  // computed on the original unpreprocessed problem, as it is used to
+  // determine the value of the "fixed" part of the objective function
+  // after the problem has undergone reduction.
+  Evaluator::Evaluate(
+      original_program,
+      options.num_threads,
+      &(summary->initial_cost),
+      options.return_initial_residuals ? &summary->initial_residuals : NULL,
+      options.return_initial_gradient ? &summary->initial_gradient : NULL,
+      options.return_initial_jacobian ? &summary->initial_jacobian : NULL);
+   original_program->SetParameterBlockStatePtrsToUserStatePtrs();
 
   // If the user requests gradient checking, construct a new
   // ProblemImpl by wrapping the CostFunctions of problem_impl inside
   // GradientCheckingCostFunction and replacing problem_impl with
   // gradient_checking_problem_impl.
   scoped_ptr<ProblemImpl> gradient_checking_problem_impl;
+  // Save the original problem impl so we don't use the gradient
+  // checking one when computing the residuals.
   if (options.check_gradients) {
     VLOG(1) << "Checking Gradients";
     gradient_checking_problem_impl.reset(
@@ -224,8 +276,10 @@ void SolverImpl::Solve(const Solver::Options& original_options,
   // Create the three objects needed to minimize: the transformed program, the
   // evaluator, and the linear solver.
 
-  scoped_ptr<Program> reduced_program(
-      CreateReducedProgram(&options, problem_impl, &summary->error));
+  scoped_ptr<Program> reduced_program(CreateReducedProgram(&options,
+                                                           problem_impl,
+                                                           &summary->fixed_cost,
+                                                           &summary->error));
   if (reduced_program == NULL) {
     return;
   }
@@ -259,19 +313,21 @@ void SolverImpl::Solve(const Solver::Options& original_options,
   }
 
   // The optimizer works on contiguous parameter vectors; allocate some.
-  Vector initial_parameters(reduced_program->NumParameters());
-  Vector optimized_parameters(reduced_program->NumParameters());
+  Vector parameters(reduced_program->NumParameters());
 
   // Collect the discontiguous parameters into a contiguous state vector.
-  reduced_program->ParameterBlocksToStateVector(&initial_parameters[0]);
+  reduced_program->ParameterBlocksToStateVector(parameters.data());
+
+  time_t minimizer_start_time = time(NULL);
+  summary->preprocessor_time_in_seconds =
+      minimizer_start_time - solver_start_time;
 
   // Run the optimization.
   Minimize(options,
            reduced_program.get(),
            evaluator.get(),
            linear_solver.get(),
-           initial_parameters.data(),
-           optimized_parameters.data(),
+           parameters.data(),
            summary);
 
   // If the user aborted mid-optimization or the optimization
@@ -282,30 +338,45 @@ void SolverImpl::Solve(const Solver::Options& original_options,
     return;
   }
 
+  time_t post_process_start_time = time(NULL);
+
   // Push the contiguous optimized parameters back to the user's parameters.
-  reduced_program->StateVectorToParameterBlocks(&optimized_parameters[0]);
+  reduced_program->StateVectorToParameterBlocks(parameters.data());
   reduced_program->CopyParameterBlockStateToUserState();
 
-  // Return the final cost and residuals for the original problem.
-  EvaluateCostAndResiduals(problem->problem_impl_.get(),
-                           &summary->final_cost,
-                           options.return_final_residuals
-                           ? &summary->final_residuals
-                           : NULL);
-
+  // Evaluate the final cost, residual vector and the jacobian
+  // matrix if requested by the user.
+  Evaluator::Evaluate(
+      original_program,
+      options.num_threads,
+      &summary->final_cost,
+      options.return_final_residuals ? &summary->final_residuals : NULL,
+      options.return_final_gradient ? &summary->final_gradient : NULL,
+      options.return_final_jacobian ? &summary->final_jacobian : NULL);
+
+  // Ensure the program state is set to the user parameters on the way out.
+  original_program->SetParameterBlockStatePtrsToUserStatePtrs();
   // Stick a fork in it, we're done.
-  return;
+  summary->postprocessor_time_in_seconds = time(NULL) - post_process_start_time;
 }
 
 // Strips varying parameters and residuals, maintaining order, and updating
 // num_eliminate_blocks.
 bool SolverImpl::RemoveFixedBlocksFromProgram(Program* program,
                                               int* num_eliminate_blocks,
+                                              double* fixed_cost,
                                               string* error) {
   int original_num_eliminate_blocks = *num_eliminate_blocks;
   vector<ParameterBlock*>* parameter_blocks =
       program->mutable_parameter_blocks();
 
+  scoped_array<double> residual_block_evaluate_scratch;
+  if (fixed_cost != NULL) {
+    residual_block_evaluate_scratch.reset(
+        new double[program->MaxScratchDoublesNeededForEvaluate()]);
+    *fixed_cost = 0.0;
+  }
+
   // Mark all the parameters as unused. Abuse the index member of the parameter
   // blocks for the marking.
   for (int i = 0; i < parameter_blocks->size(); ++i) {
@@ -335,6 +406,17 @@ bool SolverImpl::RemoveFixedBlocksFromProgram(Program* program,
 
       if (!all_constant) {
         (*residual_blocks)[j++] = (*residual_blocks)[i];
+      } else if (fixed_cost != NULL) {
+        // The residual is constant and will be removed, so its cost is
+        // added to the variable fixed_cost.
+        double cost = 0.0;
+        if (!residual_block->Evaluate(
+              &cost, NULL, NULL, residual_block_evaluate_scratch.get())) {
+          *error = StringPrintf("Evaluation of the residual %d failed during "
+                                "removal of fixed residual blocks.", i);
+          return false;
+        }
+        *fixed_cost += cost;
       }
     }
     residual_blocks->resize(j);
@@ -367,6 +449,7 @@ bool SolverImpl::RemoveFixedBlocksFromProgram(Program* program,
 
 Program* SolverImpl::CreateReducedProgram(Solver::Options* options,
                                           ProblemImpl* problem_impl,
+                                          double* fixed_cost,
                                           string* error) {
   Program* original_program = problem_impl->mutable_program();
   scoped_ptr<Program> transformed_program(new Program(*original_program));
@@ -397,6 +480,7 @@ Program* SolverImpl::CreateReducedProgram(Solver::Options* options,
 
   if (!RemoveFixedBlocksFromProgram(transformed_program.get(),
                                     &num_eliminate_blocks,
+                                    fixed_cost,
                                     error)) {
     return NULL;
   }
@@ -431,13 +515,34 @@ Program* SolverImpl::CreateReducedProgram(Solver::Options* options,
 
 LinearSolver* SolverImpl::CreateLinearSolver(Solver::Options* options,
                                              string* error) {
+  if (options->trust_region_strategy_type == DOGLEG) {
+    if (options->linear_solver_type == ITERATIVE_SCHUR ||
+        options->linear_solver_type == CGNR) {
+      *error = "DOGLEG only supports exact factorization based linear "
+               "solvers. If you want to use an iterative solver please "
+               "use LEVENBERG_MARQUARDT as the trust_region_strategy_type";
+      return NULL;
+    }
+  }
+
 #ifdef CERES_NO_SUITESPARSE
-  if (options->linear_solver_type == SPARSE_NORMAL_CHOLESKY) {
-    *error = "Can't use SPARSE_NORMAL_CHOLESKY because SuiteSparse was not "
-        "enabled when Ceres was built.";
+  if (options->linear_solver_type == SPARSE_NORMAL_CHOLESKY &&
+      options->sparse_linear_algebra_library == SUITE_SPARSE) {
+    *error = "Can't use SPARSE_NORMAL_CHOLESKY with SUITESPARSE because "
+             "SuiteSparse was not enabled when Ceres was built.";
+    return NULL;
+  }
+#endif
+
+#ifdef CERES_NO_CXSPARSE
+  if (options->linear_solver_type == SPARSE_NORMAL_CHOLESKY &&
+      options->sparse_linear_algebra_library == CX_SPARSE) {
+    *error = "Can't use SPARSE_NORMAL_CHOLESKY with CXSPARSE because "
+             "CXSparse was not enabled when Ceres was built.";
     return NULL;
   }
-#endif  // CERES_NO_SUITESPARSE
+#endif
+
 
   if (options->linear_solver_max_num_iterations <= 0) {
     *error = "Solver::Options::linear_solver_max_num_iterations is 0.";
@@ -455,30 +560,32 @@ LinearSolver* SolverImpl::CreateLinearSolver(Solver::Options* options,
   }
 
   LinearSolver::Options linear_solver_options;
-  linear_solver_options.constant_sparsity = true;
   linear_solver_options.min_num_iterations =
         options->linear_solver_min_num_iterations;
   linear_solver_options.max_num_iterations =
       options->linear_solver_max_num_iterations;
   linear_solver_options.type = options->linear_solver_type;
   linear_solver_options.preconditioner_type = options->preconditioner_type;
+  linear_solver_options.sparse_linear_algebra_library =
+      options->sparse_linear_algebra_library;
+  linear_solver_options.use_block_amd = options->use_block_amd;
 
 #ifdef CERES_NO_SUITESPARSE
   if (linear_solver_options.preconditioner_type == SCHUR_JACOBI) {
     *error =  "SCHUR_JACOBI preconditioner not suppored. Please build Ceres "
-        "with SuiteSparse support";
+        "with SuiteSparse support.";
     return NULL;
   }
 
   if (linear_solver_options.preconditioner_type == CLUSTER_JACOBI) {
     *error =  "CLUSTER_JACOBI preconditioner not suppored. Please build Ceres "
-        "with SuiteSparse support";
+        "with SuiteSparse support.";
     return NULL;
   }
 
   if (linear_solver_options.preconditioner_type == CLUSTER_TRIDIAGONAL) {
     *error =  "CLUSTER_TRIDIAGONAL preconditioner not suppored. Please build "
-        "Ceres with SuiteSparse support";
+        "Ceres with SuiteSparse support.";
     return NULL;
   }
 #endif
@@ -489,23 +596,23 @@ LinearSolver* SolverImpl::CreateLinearSolver(Solver::Options* options,
 
   if ((linear_solver_options.num_eliminate_blocks == 0) &&
       IsSchurType(linear_solver_options.type)) {
-#ifndef CERES_NO_SUITESPARSE
+#if defined(CERES_NO_SUITESPARSE) && defined(CERES_NO_CXSPARSE)
+    LOG(INFO) << "No elimination block remaining switching to DENSE_QR.";
+    linear_solver_options.type = DENSE_QR;
+#else
     LOG(INFO) << "No elimination block remaining "
               << "switching to SPARSE_NORMAL_CHOLESKY.";
     linear_solver_options.type = SPARSE_NORMAL_CHOLESKY;
-#else
-    LOG(INFO) << "No elimination block remaining switching to DENSE_QR.";
-    linear_solver_options.type = DENSE_QR;
-#endif  // CERES_NO_SUITESPARSE
+#endif
   }
 
-#ifdef CERES_NO_SUITESPARSE
+#if defined(CERES_NO_SUITESPARSE) && defined(CERES_NO_CXSPARSE)
   if (linear_solver_options.type == SPARSE_SCHUR) {
-    *error = "Can't use SPARSE_SCHUR because SuiteSparse was not "
-        "enabled when Ceres was built.";
+    *error = "Can't use SPARSE_SCHUR because neither SuiteSparse nor"
+             "CXSparse was enabled when Ceres was compiled.";
     return NULL;
   }
-#endif  // CERES_NO_SUITESPARSE
+#endif
 
   // The matrix used for storing the dense Schur complement has a
   // single lock guarding the whole matrix. Running the
@@ -578,15 +685,18 @@ bool SolverImpl::ApplyUserOrdering(const ProblemImpl& problem_impl,
 // Find the minimum index of any parameter block to the given residual.
 // Parameter blocks that have indices greater than num_eliminate_blocks are
 // considered to have an index equal to num_eliminate_blocks.
-int MinParameterBlock(const ResidualBlock* residual_block,
-                      int num_eliminate_blocks) {
+static int MinParameterBlock(const ResidualBlock* residual_block,
+                             int num_eliminate_blocks) {
   int min_parameter_block_position = num_eliminate_blocks;
   for (int i = 0; i < residual_block->NumParameterBlocks(); ++i) {
     ParameterBlock* parameter_block = residual_block->parameter_blocks()[i];
-    DCHECK_NE(parameter_block->index(), -1)
-        << "Did you forget to call Program::SetParameterOffsetsAndIndex()?";
-    min_parameter_block_position = std::min(parameter_block->index(),
-                                            min_parameter_block_position);
+    if (!parameter_block->IsConstant()) {
+      CHECK_NE(parameter_block->index(), -1)
+          << "Did you forget to call Program::SetParameterOffsetsAndIndex()? "
+          << "This is a Ceres bug; please contact the developers!";
+      min_parameter_block_position = std::min(parameter_block->index(),
+                                              min_parameter_block_position);
+    }
   }
   return min_parameter_block_position;
 }
diff --git a/extern/libmv/third_party/ceres/internal/ceres/solver_impl.h b/extern/libmv/third_party/ceres/internal/ceres/solver_impl.h
index 957ebcc65df..11b44de6f42 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/solver_impl.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/solver_impl.h
@@ -31,6 +31,9 @@
 #ifndef CERES_INTERNAL_SOLVER_IMPL_H_
 #define CERES_INTERNAL_SOLVER_IMPL_H_
 
+#include <string>
+#include <vector>
+#include "ceres/internal/port.h"
 #include "ceres/solver.h"
 
 namespace ceres {
@@ -46,15 +49,18 @@ class SolverImpl {
   // Mirrors the interface in solver.h, but exposes implementation
   // details for testing internally.
   static void Solve(const Solver::Options& options,
-                    Problem* problem,
+                    ProblemImpl* problem_impl,
                     Solver::Summary* summary);
 
   // Create the transformed Program, which has all the fixed blocks
   // and residuals eliminated, and in the case of automatic schur
   // ordering, has the E blocks first in the resulting program, with
   // options.num_eliminate_blocks set appropriately.
+  // If fixed_cost is not NULL, the residual blocks that are removed
+  // are evaluated and the sum of their cost is returned in fixed_cost.
   static Program* CreateReducedProgram(Solver::Options* options,
                                        ProblemImpl* problem_impl,
+                                       double* fixed_cost,
                                        string* error);
 
   // Create the appropriate linear solver, taking into account any
@@ -92,16 +98,18 @@ class SolverImpl {
                        Program* program,
                        Evaluator* evaluator,
                        LinearSolver* linear_solver,
-                       double* initial_parameters,
-                       double* final_parameters,
+                       double* parameters,
                        Solver::Summary* summary);
 
   // Remove the fixed or unused parameter blocks and residuals
   // depending only on fixed parameters from the problem. Also updates
   // num_eliminate_blocks, since removed parameters changes the point
   // at which the eliminated blocks is valid.
+  // If fixed_cost is not NULL, the residual blocks that are removed
+  // are evaluated and the sum of their cost is returned in fixed_cost.
   static bool RemoveFixedBlocksFromProgram(Program* program,
                                            int* num_eliminate_blocks,
+                                           double* fixed_cost,
                                            string* error);
 };
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.h
index 562210dfec8..1b19f887946 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/sparse_matrix.h
@@ -86,7 +86,7 @@ class SparseMatrix : public LinearOperator {
   // sparse matrix.
   virtual void ToDenseMatrix(Matrix* dense_matrix) const = 0;
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   // Dump the sparse matrix to a proto. Destroys the contents of proto.
   virtual void ToProto(SparseMatrixProto* proto) const = 0;
 #endif
diff --git a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.cc b/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.cc
index 59222dc374d..9e00b4402dc 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.cc
@@ -28,13 +28,16 @@
 //
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 
-#ifndef CERES_NO_SUITESPARSE
-
 #include "ceres/sparse_normal_cholesky_solver.h"
 
 #include <algorithm>
 #include <cstring>
 #include <ctime>
+
+#ifndef CERES_NO_CXSPARSE
+#include "cs.h"
+#endif
+
 #include "ceres/compressed_row_sparse_matrix.h"
 #include "ceres/linear_solver.h"
 #include "ceres/suitesparse.h"
@@ -48,13 +51,30 @@ namespace internal {
 
 SparseNormalCholeskySolver::SparseNormalCholeskySolver(
     const LinearSolver::Options& options)
-    : options_(options), symbolic_factor_(NULL) {}
+    : options_(options) {
+#ifndef CERES_NO_SUITESPARSE
+  factor_ = NULL;
+#endif
+
+#ifndef CERES_NO_CXSPARSE
+  cxsparse_factor_ = NULL;
+#endif  // CERES_NO_CXSPARSE
+}
 
 SparseNormalCholeskySolver::~SparseNormalCholeskySolver() {
-  if (symbolic_factor_ != NULL) {
-    ss_.Free(symbolic_factor_);
-    symbolic_factor_ = NULL;
+#ifndef CERES_NO_SUITESPARSE
+  if (factor_ != NULL) {
+    ss_.Free(factor_);
+    factor_ = NULL;
   }
+#endif
+
+#ifndef CERES_NO_CXSPARSE
+  if (cxsparse_factor_ != NULL) {
+    cxsparse_.Free(cxsparse_factor_);
+    cxsparse_factor_ = NULL;
+  }
+#endif  // CERES_NO_CXSPARSE
 }
 
 LinearSolver::Summary SparseNormalCholeskySolver::SolveImpl(
@@ -62,6 +82,93 @@ LinearSolver::Summary SparseNormalCholeskySolver::SolveImpl(
     const double* b,
     const LinearSolver::PerSolveOptions& per_solve_options,
     double * x) {
+  switch (options_.sparse_linear_algebra_library) {
+    case SUITE_SPARSE:
+      return SolveImplUsingSuiteSparse(A, b, per_solve_options, x);
+    case CX_SPARSE:
+      return SolveImplUsingCXSparse(A, b, per_solve_options, x);
+    default:
+      LOG(FATAL) << "Unknown sparse linear algebra library : "
+                 << options_.sparse_linear_algebra_library;
+  }
+
+  LOG(FATAL) << "Unknown sparse linear algebra library : "
+             << options_.sparse_linear_algebra_library;
+  return LinearSolver::Summary();
+}
+
+#ifndef CERES_NO_CXSPARSE
+LinearSolver::Summary SparseNormalCholeskySolver::SolveImplUsingCXSparse(
+    CompressedRowSparseMatrix* A,
+    const double* b,
+    const LinearSolver::PerSolveOptions& per_solve_options,
+    double * x) {
+  LinearSolver::Summary summary;
+  summary.num_iterations = 1;
+  const int num_cols = A->num_cols();
+  Vector Atb = Vector::Zero(num_cols);
+  A->LeftMultiply(b, Atb.data());
+
+  if (per_solve_options.D != NULL) {
+    // Temporarily append a diagonal block to the A matrix, but undo
+    // it before returning the matrix to the user.
+    CompressedRowSparseMatrix D(per_solve_options.D, num_cols);
+    A->AppendRows(D);
+  }
+
+  VectorRef(x, num_cols).setZero();
+
+  // Wrap the augmented Jacobian in a compressed sparse column matrix.
+  cs_di At = cxsparse_.CreateSparseMatrixTransposeView(A);
+
+  // Compute the normal equations. J'J delta = J'f and solve them
+  // using a sparse Cholesky factorization. Notice that when compared
+  // to SuiteSparse we have to explicitly compute the transpose of Jt,
+  // and then the normal equations before they can be
+  // factorized. CHOLMOD/SuiteSparse on the other hand can just work
+  // off of Jt to compute the Cholesky factorization of the normal
+  // equations.
+  cs_di* A2 = cs_transpose(&At, 1);
+  cs_di* AtA = cs_multiply(&At,A2);
+
+  cxsparse_.Free(A2);
+  if (per_solve_options.D != NULL) {
+    A->DeleteRows(num_cols);
+  }
+
+  // Compute symbolic factorization if not available.
+  if (cxsparse_factor_ == NULL) {
+    cxsparse_factor_ = CHECK_NOTNULL(cxsparse_.AnalyzeCholesky(AtA));
+  }
+
+  // Solve the linear system.
+  if (cxsparse_.SolveCholesky(AtA, cxsparse_factor_, Atb.data())) {
+    VectorRef(x, Atb.rows()) = Atb;
+    summary.termination_type = TOLERANCE;
+  }
+
+  cxsparse_.Free(AtA);
+  return summary;
+}
+#else
+LinearSolver::Summary SparseNormalCholeskySolver::SolveImplUsingCXSparse(
+    CompressedRowSparseMatrix* A,
+    const double* b,
+    const LinearSolver::PerSolveOptions& per_solve_options,
+    double * x) {
+  LOG(FATAL) << "No CXSparse support in Ceres.";
+
+  // Unreachable but MSVC does not know this.
+  return LinearSolver::Summary();
+}
+#endif
+
+#ifndef CERES_NO_SUITESPARSE
+LinearSolver::Summary SparseNormalCholeskySolver::SolveImplUsingSuiteSparse(
+    CompressedRowSparseMatrix* A,
+    const double* b,
+    const LinearSolver::PerSolveOptions& per_solve_options,
+    double * x) {
   const time_t start_time = time(NULL);
   const int num_cols = A->num_cols();
 
@@ -84,13 +191,25 @@ LinearSolver::Summary SparseNormalCholeskySolver::SolveImpl(
   cholmod_dense* rhs = ss_.CreateDenseVector(Atb.data(), num_cols, num_cols);
   const time_t init_time = time(NULL);
 
-  if (symbolic_factor_ == NULL) {
-    symbolic_factor_ = CHECK_NOTNULL(ss_.AnalyzeCholesky(lhs.get()));
+  if (factor_ == NULL) {
+    if (options_.use_block_amd) {
+      factor_ = ss_.BlockAnalyzeCholesky(lhs.get(),
+                                         A->col_blocks(),
+                                         A->row_blocks());
+    } else {
+      factor_ = ss_.AnalyzeCholesky(lhs.get());
+    }
+
+    if (VLOG_IS_ON(2)) {
+      cholmod_print_common("Symbolic Analysis", ss_.mutable_cc());
+    }
   }
 
+  CHECK_NOTNULL(factor_);
+
   const time_t symbolic_time = time(NULL);
 
-  cholmod_dense* sol = ss_.SolveCholesky(lhs.get(), symbolic_factor_, rhs);
+  cholmod_dense* sol = ss_.SolveCholesky(lhs.get(), factor_, rhs);
   const time_t solve_time = time(NULL);
 
   ss_.Free(rhs);
@@ -100,11 +219,6 @@ LinearSolver::Summary SparseNormalCholeskySolver::SolveImpl(
     A->DeleteRows(num_cols);
   }
 
-  if (!options_.constant_sparsity) {
-    ss_.Free(symbolic_factor_);
-    symbolic_factor_ = NULL;
-  }
-
   summary.num_iterations = 1;
   if (sol != NULL) {
     memcpy(x, sol->x, num_cols * sizeof(*x));
@@ -115,15 +229,25 @@ LinearSolver::Summary SparseNormalCholeskySolver::SolveImpl(
   }
 
   const time_t cleanup_time = time(NULL);
-  VLOG(2) << "time (sec) total: " << cleanup_time - start_time
-          << " init: " << init_time - start_time
-          << " symbolic: " << symbolic_time - init_time
-          << " solve: " << solve_time - symbolic_time
-          << " cleanup: " << cleanup_time - solve_time;
+  VLOG(2) << "time (sec) total: " << (cleanup_time - start_time)
+          << " init: " << (init_time - start_time)
+          << " symbolic: " << (symbolic_time - init_time)
+          << " solve: " << (solve_time - symbolic_time)
+          << " cleanup: " << (cleanup_time - solve_time);
   return summary;
 }
+#else
+LinearSolver::Summary SparseNormalCholeskySolver::SolveImplUsingSuiteSparse(
+    CompressedRowSparseMatrix* A,
+    const double* b,
+    const LinearSolver::PerSolveOptions& per_solve_options,
+    double * x) {
+  LOG(FATAL) << "No SuiteSparse support in Ceres.";
+
+  // Unreachable but MSVC does not know this.
+  return LinearSolver::Summary();
+}
+#endif
 
 }   // namespace internal
 }   // namespace ceres
-
-#endif  // CERES_NO_SUITESPARSE
diff --git a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.h b/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.h
index ce1d6d285be..40d9e0a0327 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/sparse_normal_cholesky_solver.h
@@ -34,13 +34,10 @@
 #ifndef CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
 #define CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
 
-#ifndef CERES_NO_SUITESPARSE
-
-#include "cholmod.h"
-#include "cholmod_core.h"
+#include "ceres/cxsparse.h"
 #include "ceres/linear_solver.h"
-#include "ceres/suitesparse.h"
 #include "ceres/internal/macros.h"
+#include "ceres/suitesparse.h"
 
 namespace ceres {
 namespace internal {
@@ -61,17 +58,36 @@ class SparseNormalCholeskySolver : public CompressedRowSparseMatrixSolver {
       const LinearSolver::PerSolveOptions& options,
       double* x);
 
-  const LinearSolver::Options options_;
+  LinearSolver::Summary SolveImplUsingSuiteSparse(
+      CompressedRowSparseMatrix* A,
+      const double* b,
+      const LinearSolver::PerSolveOptions& options,
+      double* x);
+
+  // Crashes if CSparse is not installed.
+  LinearSolver::Summary SolveImplUsingCXSparse(
+      CompressedRowSparseMatrix* A,
+      const double* b,
+      const LinearSolver::PerSolveOptions& options,
+      double* x);
+
+#ifndef CERES_NO_SUITESPARSE
   SuiteSparse ss_;
+  // Cached factorization
+  cholmod_factor* factor_;
+#endif  // CERES_NO_SUITESPARSE
 
+#ifndef CERES_NO_CXSPARSE
+  CXSparse cxsparse_;
   // Cached factorization
-  cholmod_factor* symbolic_factor_;
-  DISALLOW_COPY_AND_ASSIGN(SparseNormalCholeskySolver);
+  cs_dis* cxsparse_factor_;
+#endif  // CERES_NO_CXSPARSE
+
+  const LinearSolver::Options options_;
+  CERES_DISALLOW_COPY_AND_ASSIGN(SparseNormalCholeskySolver);
 };
 
 }  // namespace internal
 }  // namespace ceres
 
-#endif  // CERES_NO_SUITESPARSE
-
 #endif  // CERES_INTERNAL_SPARSE_NORMAL_CHOLESKY_SOLVER_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/split.cc b/extern/libmv/third_party/ceres/internal/ceres/split.cc
index 4fa1bd468b9..c65c8a5bb5d 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/split.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/split.cc
@@ -31,6 +31,7 @@
 #include <string>
 #include <vector>
 #include <iterator>
+#include "ceres/split.h"
 #include "ceres/internal/port.h"
 
 namespace ceres {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/split.h b/extern/libmv/third_party/ceres/internal/ceres/split.h
new file mode 100644
index 00000000000..ec579e974da
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/split.h
@@ -0,0 +1,21 @@
+// Copyright 2011 Google Inc. All Rights Reserved.
+// Author: keir@google.com (Keir Mierle)
+
+#ifndef CERES_INTERNAL_SPLIT_H_
+#define VISION_OPTIMIZATION_LEAST_SQUARES_INTERNAL_SPLIT_H_
+
+#include <string>
+#include <vector>
+#include "ceres/internal/port.h"
+
+namespace ceres {
+
+// Split a string using one or more character delimiters, presented as a
+// nul-terminated c string. Append the components to 'result'. If there are
+// consecutive delimiters, this function skips over all of them.
+void SplitStringUsing(const string& full, const char* delim,
+                      vector<string>* res);
+
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_SPLIT_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.cc b/extern/libmv/third_party/ceres/internal/ceres/stringprintf.cc
index c0f35225bc3..396a48b7d97 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/stringprintf.cc
@@ -34,6 +34,7 @@
 #include <string>
 #include <vector>
 
+#include "ceres/stringprintf.h"
 #include "ceres/internal/port.h"
 
 namespace ceres {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.h b/extern/libmv/third_party/ceres/internal/ceres/stringprintf.h
index 30b974e7ae5..f2f907ab32d 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/stringprintf.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/stringprintf.h
@@ -54,34 +54,34 @@ namespace internal {
 // N.B.: As the GCC manual states, "[s]ince non-static C++ methods
 // have an implicit 'this' argument, the arguments of such methods
 // should be counted from two, not one."
-#define PRINTF_ATTRIBUTE(string_index, first_to_check) \
+#define CERES_PRINTF_ATTRIBUTE(string_index, first_to_check) \
     __attribute__((__format__ (__printf__, string_index, first_to_check)))
-#define SCANF_ATTRIBUTE(string_index, first_to_check) \
+#define CERES_SCANF_ATTRIBUTE(string_index, first_to_check) \
     __attribute__((__format__ (__scanf__, string_index, first_to_check)))
 #else
-#define PRINTF_ATTRIBUTE(string_index, first_to_check)
+#define CERES_PRINTF_ATTRIBUTE(string_index, first_to_check)
 #endif
 
 // Return a C++ string.
 extern string StringPrintf(const char* format, ...)
     // Tell the compiler to do printf format string checking.
-    PRINTF_ATTRIBUTE(1,2);
+    CERES_PRINTF_ATTRIBUTE(1,2);
 
 // Store result into a supplied string and return it.
 extern const string& SStringPrintf(string* dst, const char* format, ...)
     // Tell the compiler to do printf format string checking.
-    PRINTF_ATTRIBUTE(2,3);
+    CERES_PRINTF_ATTRIBUTE(2,3);
 
 // Append result to a supplied string.
 extern void StringAppendF(string* dst, const char* format, ...)
     // Tell the compiler to do printf format string checking.
-    PRINTF_ATTRIBUTE(2,3);
+    CERES_PRINTF_ATTRIBUTE(2,3);
 
 // Lower-level routine that takes a va_list and appends to a specified string.
 // All other routines are just convenience wrappers around it.
 extern void StringAppendV(string* dst, const char* format, va_list ap);
 
-#undef PRINTF_ATTRIBUTE
+#undef CERES_PRINTF_ATTRIBUTE
 
 }  // namespace internal
 }  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/suitesparse.cc b/extern/libmv/third_party/ceres/internal/ceres/suitesparse.cc
index 1cf6a7496a7..cf3c48f84e6 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/suitesparse.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/suitesparse.cc
@@ -29,15 +29,14 @@
 // Author: sameeragarwal@google.com (Sameer Agarwal)
 
 #ifndef CERES_NO_SUITESPARSE
-
 #include "ceres/suitesparse.h"
 
+#include <vector>
 #include "cholmod.h"
 #include "ceres/compressed_row_sparse_matrix.h"
 #include "ceres/triplet_sparse_matrix.h"
 namespace ceres {
 namespace internal {
-
 cholmod_sparse* SuiteSparse::CreateSparseMatrix(TripletSparseMatrix* A) {
   cholmod_triplet triplet;
 
@@ -111,6 +110,13 @@ cholmod_dense* SuiteSparse::CreateDenseVector(const double* x,
 }
 
 cholmod_factor* SuiteSparse::AnalyzeCholesky(cholmod_sparse* A) {
+  // Cholmod can try multiple re-ordering strategies to find a fill
+  // reducing ordering. Here we just tell it use AMD with automatic
+  // matrix dependence choice of supernodal versus simplicial
+  // factorization.
+  cc_.nmethods = 1;
+  cc_.method[0].ordering = CHOLMOD_AMD;
+  cc_.supernodal = CHOLMOD_AUTO;
   cholmod_factor* factor = cholmod_analyze(A, &cc_);
   CHECK_EQ(cc_.status, CHOLMOD_OK)
       << "Cholmod symbolic analysis failed " << cc_.status;
@@ -118,6 +124,153 @@ cholmod_factor* SuiteSparse::AnalyzeCholesky(cholmod_sparse* A) {
   return factor;
 }
 
+cholmod_factor* SuiteSparse::BlockAnalyzeCholesky(
+    cholmod_sparse* A,
+    const vector<int>& row_blocks,
+    const vector<int>& col_blocks) {
+  vector<int> ordering;
+  if (!BlockAMDOrdering(A, row_blocks, col_blocks, &ordering)) {
+    return NULL;
+  }
+  return AnalyzeCholeskyWithUserOrdering(A, ordering);
+}
+
+cholmod_factor* SuiteSparse::AnalyzeCholeskyWithUserOrdering(cholmod_sparse* A,
+                                                             const vector<int>& ordering) {
+  CHECK_EQ(ordering.size(), A->nrow);
+  cc_.nmethods = 1 ;
+  cc_.method[0].ordering = CHOLMOD_GIVEN;
+  cholmod_factor* factor  =
+      cholmod_analyze_p(A, const_cast<int*>(&ordering[0]), NULL, 0, &cc_);
+  CHECK_EQ(cc_.status, CHOLMOD_OK)
+      << "Cholmod symbolic analysis failed " << cc_.status;
+  CHECK_NOTNULL(factor);
+  return factor;
+}
+
+bool SuiteSparse::BlockAMDOrdering(const cholmod_sparse* A,
+                                   const vector<int>& row_blocks,
+                                   const vector<int>& col_blocks,
+                                   vector<int>* ordering) {
+  const int num_row_blocks = row_blocks.size();
+  const int num_col_blocks = col_blocks.size();
+
+  // Arrays storing the compressed column structure of the matrix
+  // incoding the block sparsity of A.
+  vector<int> block_cols;
+  vector<int> block_rows;
+
+  ScalarMatrixToBlockMatrix(A,
+                            row_blocks,
+                            col_blocks,
+                            &block_rows,
+                            &block_cols);
+
+  cholmod_sparse_struct block_matrix;
+  block_matrix.nrow = num_row_blocks;
+  block_matrix.ncol = num_col_blocks;
+  block_matrix.nzmax = block_rows.size();
+  block_matrix.p = reinterpret_cast<void*>(&block_cols[0]);
+  block_matrix.i = reinterpret_cast<void*>(&block_rows[0]);
+  block_matrix.x = NULL;
+  block_matrix.stype = A->stype;
+  block_matrix.itype = CHOLMOD_INT;
+  block_matrix.xtype = CHOLMOD_PATTERN;
+  block_matrix.dtype = CHOLMOD_DOUBLE;
+  block_matrix.sorted = 1;
+  block_matrix.packed = 1;
+
+  vector<int> block_ordering(num_row_blocks);
+  if (!cholmod_amd(&block_matrix, NULL, 0, &block_ordering[0], &cc_)) {
+    return false;
+  }
+
+  BlockOrderingToScalarOrdering(row_blocks, block_ordering, ordering);
+  return true;
+}
+
+void SuiteSparse::ScalarMatrixToBlockMatrix(const cholmod_sparse* A,
+                                            const vector<int>& row_blocks,
+                                            const vector<int>& col_blocks,
+                                            vector<int>* block_rows,
+                                            vector<int>* block_cols) {
+  CHECK_NOTNULL(block_rows)->clear();
+  CHECK_NOTNULL(block_cols)->clear();
+  const int num_row_blocks = row_blocks.size();
+  const int num_col_blocks = col_blocks.size();
+
+  vector<int> row_block_starts(num_row_blocks);
+  for (int i = 0, cursor = 0; i < num_row_blocks; ++i) {
+    row_block_starts[i] = cursor;
+    cursor += row_blocks[i];
+  }
+
+  // The reinterpret_cast is needed here because CHOLMOD stores arrays
+  // as void*.
+  const int* scalar_cols =  reinterpret_cast<const int*>(A->p);
+  const int* scalar_rows =  reinterpret_cast<const int*>(A->i);
+
+  // This loop extracts the block sparsity of the scalar sparse matrix
+  // A. It does so by iterating over the columns, but only considering
+  // the columns corresponding to the first element of each column
+  // block. Within each column, the inner loop iterates over the rows,
+  // and detects the presence of a row block by checking for the
+  // presence of a non-zero entry corresponding to its first element.
+  block_cols->push_back(0);
+  int c = 0;
+  for (int col_block = 0; col_block < num_col_blocks; ++col_block) {
+    int column_size = 0;
+    for (int idx = scalar_cols[c]; idx < scalar_cols[c + 1]; ++idx) {
+      vector<int>::const_iterator it = lower_bound(row_block_starts.begin(),
+                                                   row_block_starts.end(),
+                                                   scalar_rows[idx]);
+      // Since we are using lower_bound, it will return the row id
+      // where the row block starts. For everything but the first row
+      // of the block, where these values will be the same, we can
+      // skip, as we only need the first row to detect the presence of
+      // the block.
+      //
+      // For rows all but the first row in the last row block,
+      // lower_bound will return row_block_starts.end(), but those can
+      // be skipped like the rows in other row blocks too.
+      if (it == row_block_starts.end() || *it != scalar_rows[idx]) {
+        continue;
+      }
+
+      block_rows->push_back(it - row_block_starts.begin());
+      ++column_size;
+    }
+    block_cols->push_back(block_cols->back() + column_size);
+    c += col_blocks[col_block];
+  }
+}
+
+void SuiteSparse::BlockOrderingToScalarOrdering(
+    const vector<int>& blocks,
+    const vector<int>& block_ordering,
+    vector<int>* scalar_ordering) {
+  CHECK_EQ(blocks.size(), block_ordering.size());
+  const int num_blocks = blocks.size();
+
+  // block_starts = [0, block1, block1 + block2 ..]
+  vector<int> block_starts(num_blocks);
+  for (int i = 0, cursor = 0; i < num_blocks ; ++i) {
+    block_starts[i] = cursor;
+    cursor += blocks[i];
+  }
+
+  scalar_ordering->resize(block_starts.back() + blocks.back());
+  int cursor = 0;
+  for (int i = 0; i < num_blocks; ++i) {
+    const int block_id = block_ordering[i];
+    const int block_size = blocks[block_id];
+    int block_position = block_starts[block_id];
+    for (int j = 0; j < block_size; ++j) {
+      (*scalar_ordering)[cursor++] = block_position++;
+    }
+  }
+}
+
 bool SuiteSparse::Cholesky(cholmod_sparse* A, cholmod_factor* L) {
   CHECK_NOTNULL(A);
   CHECK_NOTNULL(L);
diff --git a/extern/libmv/third_party/ceres/internal/ceres/suitesparse.h b/extern/libmv/third_party/ceres/internal/ceres/suitesparse.h
index 091e67a69a9..eb691c0c0ed 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/suitesparse.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/suitesparse.h
@@ -37,6 +37,7 @@
 
 #include <cstring>
 #include <string>
+#include <vector>
 
 #include <glog/logging.h>
 #include "cholmod.h"
@@ -105,12 +106,35 @@ class SuiteSparse {
     cholmod_sdmult(A, 0, alpha_, beta_, x, y, &cc_);
   }
 
-  // Analyze the sparsity structure of the matrix A compute the
-  // symbolic factorization of A. A is not modified, only the pattern
-  // of non-zeros of A is used, the actual numerical values in A are
-  // of no consequence. Caller owns the result.
+  // Find an ordering of A or AA' (if A is unsymmetric) that minimizes
+  // the fill-in in the Cholesky factorization of the corresponding
+  // matrix. This is done by using the AMD algorithm.
+  //
+  // Using this ordering, the symbolic Cholesky factorization of A (or
+  // AA') is computed and returned.
+  //
+  // A is not modified, only the pattern of non-zeros of A is used,
+  // the actual numerical values in A are of no consequence.
+  //
+  // Caller owns the result.
   cholmod_factor* AnalyzeCholesky(cholmod_sparse* A);
 
+  cholmod_factor* BlockAnalyzeCholesky(cholmod_sparse* A,
+                                       const vector<int>& row_blocks,
+                                       const vector<int>& col_blocks);
+
+  // If A is symmetric, then compute the symbolic Cholesky
+  // factorization of A(ordering, ordering). If A is unsymmetric, then
+  // compute the symbolic factorization of
+  // A(ordering,:) A(ordering,:)'.
+  //
+  // A is not modified, only the pattern of non-zeros of A is used,
+  // the actual numerical values in A are of no consequence.
+  //
+  // Caller owns the result.
+  cholmod_factor* AnalyzeCholeskyWithUserOrdering(cholmod_sparse* A,
+                                                  const vector<int>& ordering);
+
   // Use the symbolic factorization in L, to find the numerical
   // factorization for the matrix A or AA^T. Return true if
   // successful, false otherwise. L contains the numeric factorization
@@ -129,6 +153,56 @@ class SuiteSparse {
                                cholmod_factor* L,
                                cholmod_dense* b);
 
+  // By virtue of the modeling layer in Ceres being block oriented,
+  // all the matrices used by Ceres are also block oriented. When
+  // doing sparse direct factorization of these matrices the
+  // fill-reducing ordering algorithms (in particular AMD) can either
+  // be run on the block or the scalar form of these matrices. The two
+  // SuiteSparse::AnalyzeCholesky methods allows the the client to
+  // compute the symbolic factorization of a matrix by either using
+  // AMD on the matrix or a user provided ordering of the rows.
+  //
+  // But since the underlying matrices are block oriented, it is worth
+  // running AMD on just the block structre of these matrices and then
+  // lifting these block orderings to a full scalar ordering. This
+  // preserves the block structure of the permuted matrix, and exposes
+  // more of the super-nodal structure of the matrix to the numerical
+  // factorization routines.
+  //
+  // Find the block oriented AMD ordering of a matrix A, whose row and
+  // column blocks are given by row_blocks, and col_blocks
+  // respectively. The matrix may or may not be symmetric. The entries
+  // of col_blocks do not need to sum to the number of columns in
+  // A. If this is the case, only the first sum(col_blocks) are used
+  // to compute the ordering.
+  bool BlockAMDOrdering(const cholmod_sparse* A,
+                        const vector<int>& row_blocks,
+                        const vector<int>& col_blocks,
+                        vector<int>* ordering);
+
+  // Given a set of blocks and a permutation of these blocks, compute
+  // the corresponding "scalar" ordering, where the scalar ordering of
+  // size sum(blocks).
+  static void BlockOrderingToScalarOrdering(const vector<int>& blocks,
+                                            const vector<int>& block_ordering,
+                                            vector<int>* scalar_ordering);
+
+  // Extract the block sparsity pattern of the scalar sparse matrix
+  // A and return it in compressed column form. The compressed column
+  // form is stored in two vectors block_rows, and block_cols, which
+  // correspond to the row and column arrays in a compressed column sparse
+  // matrix.
+  //
+  // If c_ij is the block in the matrix A corresponding to row block i
+  // and column block j, then it is expected that A contains at least
+  // one non-zero entry corresponding to the top left entry of c_ij,
+  // as that entry is used to detect the presence of a non-zero c_ij.
+  static void ScalarMatrixToBlockMatrix(const cholmod_sparse* A,
+                                        const vector<int>& row_blocks,
+                                        const vector<int>& col_blocks,
+                                        vector<int>* block_rows,
+                                        vector<int>* block_cols);
+
   void Free(cholmod_sparse* m) { cholmod_free_sparse(&m, &cc_); }
   void Free(cholmod_dense* m)  { cholmod_free_dense(&m, &cc_);  }
   void Free(cholmod_factor* m) { cholmod_free_factor(&m, &cc_); }
diff --git a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.cc b/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.cc
index 247ab2e697b..ed8677ea18a 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.cc
@@ -32,12 +32,12 @@
 
 #include <algorithm>
 #include <cstddef>
-#include <glog/logging.h>
-#include "ceres/matrix_proto.h"
 #include "ceres/internal/eigen.h"
 #include "ceres/internal/port.h"
 #include "ceres/internal/scoped_ptr.h"
+#include "ceres/matrix_proto.h"
 #include "ceres/types.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -82,7 +82,7 @@ TripletSparseMatrix::TripletSparseMatrix(const TripletSparseMatrix& orig)
   CopyData(orig);
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 TripletSparseMatrix::TripletSparseMatrix(const SparseMatrixProto& outer_proto) {
   CHECK(outer_proto.has_triplet_matrix());
 
@@ -130,7 +130,7 @@ bool TripletSparseMatrix::AllTripletsWithinBounds() const {
 
 void TripletSparseMatrix::Reserve(int new_max_num_nonzeros) {
   CHECK_LE(num_nonzeros_, new_max_num_nonzeros)
-    << "Reallocation will cause data loss";
+      << "Reallocation will cause data loss";
 
   // Nothing to do if we have enough space already.
   if (new_max_num_nonzeros <= max_num_nonzeros_)
@@ -214,7 +214,7 @@ void TripletSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
   }
 }
 
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
 void TripletSparseMatrix::ToProto(SparseMatrixProto *proto) const {
   proto->Clear();
 
diff --git a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.h b/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.h
index 300e74d0bbc..89a645bd879 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/triplet_sparse_matrix.h
@@ -50,7 +50,7 @@ class TripletSparseMatrix : public SparseMatrix {
   TripletSparseMatrix();
   TripletSparseMatrix(int num_rows, int num_cols, int max_num_nonzeros);
   explicit TripletSparseMatrix(const TripletSparseMatrix& orig);
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   explicit TripletSparseMatrix(const SparseMatrixProto& proto);
 #endif
 
@@ -65,7 +65,7 @@ class TripletSparseMatrix : public SparseMatrix {
   virtual void SquaredColumnNorm(double* x) const;
   virtual void ScaleColumns(const double* scale);
   virtual void ToDenseMatrix(Matrix* dense_matrix) const;
-#ifndef CERES_DONT_HAVE_PROTOCOL_BUFFERS
+#ifndef CERES_NO_PROTOCOL_BUFFERS
   virtual void ToProto(SparseMatrixProto *proto) const;
 #endif
   virtual void ToTextFile(FILE* file) const;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.cc b/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.cc
new file mode 100644
index 00000000000..76c4f8a7580
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.cc
@@ -0,0 +1,550 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#include "ceres/trust_region_minimizer.h"
+
+#include <algorithm>
+#include <cstdlib>
+#include <cmath>
+#include <cstring>
+#include <limits>
+#include <string>
+#include <vector>
+
+#include "Eigen/Core"
+#include "ceres/array_utils.h"
+#include "ceres/evaluator.h"
+#include "ceres/internal/eigen.h"
+#include "ceres/internal/scoped_ptr.h"
+#include "ceres/linear_least_squares_problems.h"
+#include "ceres/sparse_matrix.h"
+#include "ceres/trust_region_strategy.h"
+#include "ceres/types.h"
+#include "glog/logging.h"
+
+namespace ceres {
+namespace internal {
+namespace {
+// Small constant for various floating point issues.
+const double kEpsilon = 1e-12;
+}  // namespace
+
+// Execute the list of IterationCallbacks sequentially. If any one of
+// the callbacks does not return SOLVER_CONTINUE, then stop and return
+// its status.
+CallbackReturnType TrustRegionMinimizer::RunCallbacks(
+    const IterationSummary& iteration_summary) {
+  for (int i = 0; i < options_.callbacks.size(); ++i) {
+    const CallbackReturnType status =
+        (*options_.callbacks[i])(iteration_summary);
+    if (status != SOLVER_CONTINUE) {
+      return status;
+    }
+  }
+  return SOLVER_CONTINUE;
+}
+
+// Compute a scaling vector that is used to improve the conditioning
+// of the Jacobian.
+void TrustRegionMinimizer::EstimateScale(const SparseMatrix& jacobian,
+                                         double* scale) const {
+  jacobian.SquaredColumnNorm(scale);
+  for (int i = 0; i < jacobian.num_cols(); ++i) {
+    scale[i] = 1.0 / (kEpsilon + sqrt(scale[i]));
+  }
+}
+
+void TrustRegionMinimizer::Init(const Minimizer::Options& options) {
+  options_ = options;
+  sort(options_.lsqp_iterations_to_dump.begin(),
+       options_.lsqp_iterations_to_dump.end());
+}
+
+bool TrustRegionMinimizer::MaybeDumpLinearLeastSquaresProblem(
+    const int iteration,
+    const SparseMatrix* jacobian,
+    const double* residuals,
+    const double* step) const  {
+  // TODO(sameeragarwal): Since the use of trust_region_radius has
+  // moved inside TrustRegionStrategy, its not clear how we dump the
+  // regularization vector/matrix anymore.
+  //
+  // Doing this right requires either an API change to the
+  // TrustRegionStrategy and/or how LinearLeastSquares problems are
+  // stored on disk.
+  //
+  // For now, we will just not dump the regularizer.
+  return (!binary_search(options_.lsqp_iterations_to_dump.begin(),
+                         options_.lsqp_iterations_to_dump.end(),
+                         iteration) ||
+          DumpLinearLeastSquaresProblem(options_.lsqp_dump_directory,
+                                        iteration,
+                                        options_.lsqp_dump_format_type,
+                                        jacobian,
+                                        NULL,
+                                        residuals,
+                                        step,
+                                        options_.num_eliminate_blocks));
+}
+
+void TrustRegionMinimizer::Minimize(const Minimizer::Options& options,
+                                    double* parameters,
+                                    Solver::Summary* summary) {
+  time_t start_time = time(NULL);
+  time_t iteration_start_time =  start_time;
+  Init(options);
+
+  summary->termination_type = NO_CONVERGENCE;
+  summary->num_successful_steps = 0;
+  summary->num_unsuccessful_steps = 0;
+
+  Evaluator* evaluator = CHECK_NOTNULL(options_.evaluator);
+  SparseMatrix* jacobian = CHECK_NOTNULL(options_.jacobian);
+  TrustRegionStrategy* strategy = CHECK_NOTNULL(options_.trust_region_strategy);
+
+  const int num_parameters = evaluator->NumParameters();
+  const int num_effective_parameters = evaluator->NumEffectiveParameters();
+  const int num_residuals = evaluator->NumResiduals();
+
+  VectorRef x_min(parameters, num_parameters);
+  Vector x = x_min;
+  double x_norm = x.norm();
+
+  Vector residuals(num_residuals);
+  Vector trust_region_step(num_effective_parameters);
+  Vector delta(num_effective_parameters);
+  Vector x_plus_delta(num_parameters);
+  Vector gradient(num_effective_parameters);
+  Vector model_residuals(num_residuals);
+  Vector scale(num_effective_parameters);
+
+  IterationSummary iteration_summary;
+  iteration_summary.iteration = 0;
+  iteration_summary.step_is_valid = false;
+  iteration_summary.step_is_successful = false;
+  iteration_summary.cost = summary->initial_cost;
+  iteration_summary.cost_change = 0.0;
+  iteration_summary.gradient_max_norm = 0.0;
+  iteration_summary.step_norm = 0.0;
+  iteration_summary.relative_decrease = 0.0;
+  iteration_summary.trust_region_radius = strategy->Radius();
+  // TODO(sameeragarwal): Rename eta to linear_solver_accuracy or
+  // something similar across the board.
+  iteration_summary.eta = options_.eta;
+  iteration_summary.linear_solver_iterations = 0;
+  iteration_summary.step_solver_time_in_seconds = 0;
+
+  // Do initial cost and Jacobian evaluation.
+  double cost = 0.0;
+  if (!evaluator->Evaluate(x.data(), &cost, residuals.data(), NULL, jacobian)) {
+    LOG(WARNING) << "Terminating: Residual and Jacobian evaluation failed.";
+    summary->termination_type = NUMERICAL_FAILURE;
+    return;
+  }
+
+  int num_consecutive_nonmonotonic_steps = 0;
+  double minimum_cost = cost;
+  double reference_cost = cost;
+  double accumulated_reference_model_cost_change = 0.0;
+  double candidate_cost = cost;
+  double accumulated_candidate_model_cost_change = 0.0;
+
+  gradient.setZero();
+  jacobian->LeftMultiply(residuals.data(), gradient.data());
+  iteration_summary.gradient_max_norm = gradient.lpNorm<Eigen::Infinity>();
+
+  if (options_.jacobi_scaling) {
+    EstimateScale(*jacobian, scale.data());
+    jacobian->ScaleColumns(scale.data());
+  } else {
+    scale.setOnes();
+  }
+
+  // The initial gradient max_norm is bounded from below so that we do
+  // not divide by zero.
+  const double gradient_max_norm_0 =
+      max(iteration_summary.gradient_max_norm, kEpsilon);
+  const double absolute_gradient_tolerance =
+      options_.gradient_tolerance * gradient_max_norm_0;
+
+  if (iteration_summary.gradient_max_norm <= absolute_gradient_tolerance) {
+    summary->termination_type = GRADIENT_TOLERANCE;
+    VLOG(1) << "Terminating: Gradient tolerance reached."
+            << "Relative gradient max norm: "
+            << iteration_summary.gradient_max_norm / gradient_max_norm_0
+            << " <= " << options_.gradient_tolerance;
+    return;
+  }
+
+  iteration_summary.iteration_time_in_seconds =
+      time(NULL) - iteration_start_time;
+  iteration_summary.cumulative_time_in_seconds = time(NULL) - start_time +
+        summary->preprocessor_time_in_seconds;
+  summary->iterations.push_back(iteration_summary);
+
+  // Call the various callbacks.
+  switch (RunCallbacks(iteration_summary)) {
+    case SOLVER_TERMINATE_SUCCESSFULLY:
+      summary->termination_type = USER_SUCCESS;
+      VLOG(1) << "Terminating: User callback returned USER_SUCCESS.";
+      return;
+    case SOLVER_ABORT:
+      summary->termination_type = USER_ABORT;
+      VLOG(1) << "Terminating: User callback returned  USER_ABORT.";
+      return;
+    case SOLVER_CONTINUE:
+      break;
+    default:
+      LOG(FATAL) << "Unknown type of user callback status";
+  }
+
+  int num_consecutive_invalid_steps = 0;
+  while (true) {
+    iteration_start_time = time(NULL);
+    if (iteration_summary.iteration >= options_.max_num_iterations) {
+      summary->termination_type = NO_CONVERGENCE;
+      VLOG(1) << "Terminating: Maximum number of iterations reached.";
+      break;
+    }
+
+    const double total_solver_time = iteration_start_time - start_time +
+        summary->preprocessor_time_in_seconds;
+    if (total_solver_time >= options_.max_solver_time_in_seconds) {
+      summary->termination_type = NO_CONVERGENCE;
+      VLOG(1) << "Terminating: Maximum solver time reached.";
+      break;
+    }
+
+    iteration_summary = IterationSummary();
+    iteration_summary = summary->iterations.back();
+    iteration_summary.iteration = summary->iterations.back().iteration + 1;
+    iteration_summary.step_is_valid = false;
+    iteration_summary.step_is_successful = false;
+
+    const time_t strategy_start_time = time(NULL);
+    TrustRegionStrategy::PerSolveOptions per_solve_options;
+    per_solve_options.eta = options_.eta;
+    TrustRegionStrategy::Summary strategy_summary =
+        strategy->ComputeStep(per_solve_options,
+                              jacobian,
+                              residuals.data(),
+                              trust_region_step.data());
+
+    iteration_summary.step_solver_time_in_seconds =
+        time(NULL) - strategy_start_time;
+    iteration_summary.linear_solver_iterations =
+        strategy_summary.num_iterations;
+
+    if (!MaybeDumpLinearLeastSquaresProblem(iteration_summary.iteration,
+                                            jacobian,
+                                            residuals.data(),
+                                            trust_region_step.data())) {
+      LOG(FATAL) << "Tried writing linear least squares problem: "
+                 << options.lsqp_dump_directory << "but failed.";
+    }
+
+    double new_model_cost = 0.0;
+    if (strategy_summary.termination_type != FAILURE) {
+      // new_model_cost = 1/2 |f + J * step|^2
+      model_residuals = residuals;
+      jacobian->RightMultiply(trust_region_step.data(), model_residuals.data());
+      new_model_cost = model_residuals.squaredNorm() / 2.0;
+
+      // In exact arithmetic, this would never be the case. But poorly
+      // conditioned matrices can give rise to situations where the
+      // new_model_cost can actually be larger than half the squared
+      // norm of the residual vector. We allow for small tolerance
+      // around cost and beyond that declare the step to be invalid.
+      if ((1.0 - new_model_cost / cost) < -kEpsilon) {
+        VLOG(1) << "Invalid step: current_cost: " << cost
+                << " new_model_cost " << new_model_cost
+                << " absolute difference " << (cost - new_model_cost)
+                << " relative difference " << (1.0 - new_model_cost/cost);
+      } else {
+        iteration_summary.step_is_valid = true;
+      }
+    }
+
+    if (!iteration_summary.step_is_valid) {
+      // Invalid steps can happen due to a number of reasons, and we
+      // allow a limited number of successive failures, and return with
+      // NUMERICAL_FAILURE if this limit is exceeded.
+      if (++num_consecutive_invalid_steps >=
+          options_.max_num_consecutive_invalid_steps) {
+        summary->termination_type = NUMERICAL_FAILURE;
+        LOG(WARNING) << "Terminating. Number of successive invalid steps more "
+                     << "than "
+                     << "Solver::Options::max_num_consecutive_invalid_steps: "
+                     << options_.max_num_consecutive_invalid_steps;
+        return;
+      }
+
+      // We are going to try and reduce the trust region radius and
+      // solve again. To do this, we are going to treat this iteration
+      // as an unsuccessful iteration. Since the various callbacks are
+      // still executed, we are going to fill the iteration summary
+      // with data that assumes a step of length zero and no progress.
+      iteration_summary.cost = cost;
+      iteration_summary.cost_change = 0.0;
+      iteration_summary.gradient_max_norm =
+          summary->iterations.back().gradient_max_norm;
+      iteration_summary.step_norm = 0.0;
+      iteration_summary.relative_decrease = 0.0;
+      iteration_summary.eta = options_.eta;
+    } else {
+      // The step is numerically valid, so now we can judge its quality.
+      num_consecutive_invalid_steps = 0;
+
+      // We allow some slop around 0, and clamp the model_cost_change
+      // at kEpsilon * min(1.0, cost) from below.
+      //
+      // In exact arithmetic this should never be needed, as we are
+      // guaranteed to new_model_cost <= cost. However, due to various
+      // numerical issues, it is possible that new_model_cost is
+      // nearly equal to cost, and the difference is a small negative
+      // number. To make sure that the relative_decrease computation
+      // remains sane, as clamp the difference (cost - new_model_cost)
+      // from below at a small positive number.
+      //
+      // This number is the minimum of kEpsilon * (cost, 1.0), which
+      // ensures that it will never get too large in absolute value,
+      // while scaling down proportionally with the magnitude of the
+      // cost. This is important for problems where the minimum of the
+      // objective function is near zero.
+      const double model_cost_change =
+          max(kEpsilon * min(1.0, cost), cost - new_model_cost);
+
+      // Undo the Jacobian column scaling.
+      delta = (trust_region_step.array() * scale.array()).matrix();
+      iteration_summary.step_norm = delta.norm();
+
+      // Convergence based on parameter_tolerance.
+      const double step_size_tolerance =  options_.parameter_tolerance *
+          (x_norm + options_.parameter_tolerance);
+      if (iteration_summary.step_norm <= step_size_tolerance) {
+        VLOG(1) << "Terminating. Parameter tolerance reached. "
+                << "relative step_norm: "
+                << iteration_summary.step_norm /
+            (x_norm + options_.parameter_tolerance)
+                << " <= " << options_.parameter_tolerance;
+        summary->termination_type = PARAMETER_TOLERANCE;
+        return;
+      }
+
+      if (!evaluator->Plus(x.data(), delta.data(), x_plus_delta.data())) {
+        summary->termination_type = NUMERICAL_FAILURE;
+        LOG(WARNING) << "Terminating. Failed to compute "
+                     << "Plus(x, delta, x_plus_delta).";
+        return;
+      }
+
+      // Try this step.
+      double new_cost;
+      if (!evaluator->Evaluate(x_plus_delta.data(),
+                               &new_cost,
+                               NULL, NULL, NULL)) {
+        // If the evaluation of the new cost fails, treat it as a step
+        // with high cost.
+        LOG(WARNING) << "Step failed to evaluate. "
+                     << "Treating it as step with infinite cost";
+        new_cost = numeric_limits<double>::max();
+      }
+
+      VLOG(2) << "old cost: " << cost << " new cost: " << new_cost;
+      iteration_summary.cost_change =  cost - new_cost;
+      const double absolute_function_tolerance =
+          options_.function_tolerance * cost;
+      if (fabs(iteration_summary.cost_change) < absolute_function_tolerance) {
+        VLOG(1) << "Terminating. Function tolerance reached. "
+                << "|cost_change|/cost: "
+                << fabs(iteration_summary.cost_change) / cost
+                << " <= " << options_.function_tolerance;
+        summary->termination_type = FUNCTION_TOLERANCE;
+        return;
+      }
+
+      const double relative_decrease =
+          iteration_summary.cost_change / model_cost_change;
+
+      const double historical_relative_decrease =
+          (reference_cost - new_cost) /
+          (accumulated_reference_model_cost_change + model_cost_change);
+
+      // If monotonic steps are being used, then the relative_decrease
+      // is the usual ratio of the change in objective function value
+      // divided by the change in model cost.
+      //
+      // If non-monotonic steps are allowed, then we take the maximum
+      // of the relative_decrease and the
+      // historical_relative_decrease, which measures the increase
+      // from a reference iteration. The model cost change is
+      // estimated by accumulating the model cost changes since the
+      // reference iteration. The historical relative_decrease offers
+      // a boost to a step which is not too bad compared to the
+      // reference iteration, allowing for non-monotonic steps.
+      iteration_summary.relative_decrease =
+          options.use_nonmonotonic_steps
+          ? max(relative_decrease, historical_relative_decrease)
+          : relative_decrease;
+
+      iteration_summary.step_is_successful =
+          iteration_summary.relative_decrease > options_.min_relative_decrease;
+
+      if (iteration_summary.step_is_successful) {
+        accumulated_candidate_model_cost_change += model_cost_change;
+        accumulated_reference_model_cost_change += model_cost_change;
+        if (relative_decrease <= options_.min_relative_decrease) {
+          VLOG(2) << "Non-monotonic step! "
+                  << " relative_decrease: " << relative_decrease
+                  << " historical_relative_decrease: "
+                  << historical_relative_decrease;
+        }
+      }
+    }
+
+    if (iteration_summary.step_is_successful) {
+      ++summary->num_successful_steps;
+      strategy->StepAccepted(iteration_summary.relative_decrease);
+      x = x_plus_delta;
+      x_norm = x.norm();
+
+      // Step looks good, evaluate the residuals and Jacobian at this
+      // point.
+      if (!evaluator->Evaluate(x.data(),
+                               &cost,
+                               residuals.data(),
+                               NULL,
+                               jacobian)) {
+        summary->termination_type = NUMERICAL_FAILURE;
+        LOG(WARNING) << "Terminating: Residual and Jacobian evaluation failed.";
+        return;
+      }
+
+      gradient.setZero();
+      jacobian->LeftMultiply(residuals.data(), gradient.data());
+      iteration_summary.gradient_max_norm = gradient.lpNorm<Eigen::Infinity>();
+
+      if (iteration_summary.gradient_max_norm <= absolute_gradient_tolerance) {
+        summary->termination_type = GRADIENT_TOLERANCE;
+        VLOG(1) << "Terminating: Gradient tolerance reached."
+                << "Relative gradient max norm: "
+                << iteration_summary.gradient_max_norm / gradient_max_norm_0
+                << " <= " << options_.gradient_tolerance;
+        return;
+      }
+
+      if (options_.jacobi_scaling) {
+        jacobian->ScaleColumns(scale.data());
+      }
+
+      // Update the best, reference and candidate iterates.
+      //
+      // Based on algorithm 10.1.2 (page 357) of "Trust Region
+      // Methods" by Conn Gould & Toint, or equations 33-40 of
+      // "Non-monotone trust-region algorithms for nonlinear
+      // optimization subject to convex constraints" by Phil Toint,
+      // Mathematical Programming, 77, 1997.
+      if (cost < minimum_cost) {
+        // A step that improves solution quality was found.
+        x_min = x;
+        minimum_cost = cost;
+        // Set the candidate iterate to the current point.
+        candidate_cost = cost;
+        num_consecutive_nonmonotonic_steps = 0;
+        accumulated_candidate_model_cost_change = 0.0;
+      } else {
+        ++num_consecutive_nonmonotonic_steps;
+        if (cost > candidate_cost) {
+          // The current iterate is has a higher cost than the
+          // candidate iterate. Set the candidate to this point.
+          VLOG(2) << "Updating the candidate iterate to the current point.";
+          candidate_cost = cost;
+          accumulated_candidate_model_cost_change = 0.0;
+        }
+
+        // At this point we have made too many non-monotonic steps and
+        // we are going to reset the value of the reference iterate so
+        // as to force the algorithm to descend.
+        //
+        // This is the case because the candidate iterate has a value
+        // greater than minimum_cost but smaller than the reference
+        // iterate.
+        if (num_consecutive_nonmonotonic_steps ==
+            options.max_consecutive_nonmonotonic_steps) {
+          VLOG(2) << "Resetting the reference point to the candidate point";
+          reference_cost = candidate_cost;
+          accumulated_reference_model_cost_change =
+              accumulated_candidate_model_cost_change;
+        }
+      }
+    } else {
+      ++summary->num_unsuccessful_steps;
+      if (iteration_summary.step_is_valid) {
+        strategy->StepRejected(iteration_summary.relative_decrease);
+      } else {
+        strategy->StepIsInvalid();
+      }
+    }
+
+    iteration_summary.cost = cost + summary->fixed_cost;
+    iteration_summary.trust_region_radius = strategy->Radius();
+    if (iteration_summary.trust_region_radius <
+        options_.min_trust_region_radius) {
+      summary->termination_type = PARAMETER_TOLERANCE;
+      VLOG(1) << "Termination. Minimum trust region radius reached.";
+      return;
+    }
+
+    iteration_summary.iteration_time_in_seconds =
+        time(NULL) - iteration_start_time;
+    iteration_summary.cumulative_time_in_seconds = time(NULL) - start_time +
+        summary->preprocessor_time_in_seconds;
+    summary->iterations.push_back(iteration_summary);
+
+    switch (RunCallbacks(iteration_summary)) {
+      case SOLVER_TERMINATE_SUCCESSFULLY:
+        summary->termination_type = USER_SUCCESS;
+        VLOG(1) << "Terminating: User callback returned USER_SUCCESS.";
+        return;
+      case SOLVER_ABORT:
+        summary->termination_type = USER_ABORT;
+        VLOG(1) << "Terminating: User callback returned  USER_ABORT.";
+        return;
+      case SOLVER_CONTINUE:
+        break;
+      default:
+        LOG(FATAL) << "Unknown type of user callback status";
+    }
+  }
+}
+
+
+}  // namespace internal
+}  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.h b/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.h
new file mode 100644
index 00000000000..a4f5ba3674d
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/trust_region_minimizer.h
@@ -0,0 +1,67 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_
+#define CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_
+
+#include "ceres/minimizer.h"
+#include "ceres/solver.h"
+#include "ceres/types.h"
+
+namespace ceres {
+namespace internal {
+
+// Generic trust region minimization algorithm. The heavy lifting is
+// done by a TrustRegionStrategy object passed in as one of the
+// arguments to the Minimize method.
+//
+// For example usage, see SolverImpl::Minimize.
+class TrustRegionMinimizer : public Minimizer {
+ public:
+  ~TrustRegionMinimizer() {}
+  virtual void Minimize(const Minimizer::Options& options,
+                        double* parameters,
+                        Solver::Summary* summary);
+
+ private:
+  void Init(const Minimizer::Options& options);
+  void EstimateScale(const SparseMatrix& jacobian, double* scale) const;
+  CallbackReturnType RunCallbacks(const IterationSummary& iteration_summary);
+  bool MaybeDumpLinearLeastSquaresProblem( const int iteration,
+                                           const SparseMatrix* jacobian,
+                                           const double* residuals,
+                                           const double* step) const;
+
+  Minimizer::Options options_;
+};
+
+}  // namespace internal
+}  // namespace ceres
+#endif  // CERES_INTERNAL_TRUST_REGION_MINIMIZER_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.cc b/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.cc
new file mode 100644
index 00000000000..89bc19d084b
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.cc
@@ -0,0 +1,27 @@
+#include "ceres/trust_region_strategy.h"
+#include "ceres/dogleg_strategy.h"
+#include "ceres/levenberg_marquardt_strategy.h"
+
+namespace ceres {
+namespace internal {
+
+TrustRegionStrategy::~TrustRegionStrategy() {}
+
+TrustRegionStrategy* TrustRegionStrategy::Create(const Options& options) {
+  switch (options.trust_region_strategy_type) {
+    case LEVENBERG_MARQUARDT:
+      return new LevenbergMarquardtStrategy(options);
+    case DOGLEG:
+      return new DoglegStrategy(options);
+    default:
+      LOG(FATAL) << "Unknown trust region strategy: "
+                 << options.trust_region_strategy_type;
+  }
+
+  LOG(FATAL) << "Unknown trust region strategy: "
+             << options.trust_region_strategy_type;
+  return NULL;
+}
+
+}  // namespace internal
+}  // namespace ceres
diff --git a/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.h b/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.h
new file mode 100644
index 00000000000..391da97d5eb
--- /dev/null
+++ b/extern/libmv/third_party/ceres/internal/ceres/trust_region_strategy.h
@@ -0,0 +1,148 @@
+// Ceres Solver - A fast non-linear least squares minimizer
+// Copyright 2012 Google Inc. All rights reserved.
+// http://code.google.com/p/ceres-solver/
+//
+// 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 Google Inc. 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.
+//
+// Author: sameeragarwal@google.com (Sameer Agarwal)
+
+#ifndef CERES_INTERNAL_TRUST_REGION_STRATEGY_H_
+#define CERES_INTERNAL_TRUST_REGION_STRATEGY_H_
+
+#include "ceres/types.h"
+
+namespace ceres {
+namespace internal {
+
+class LinearSolver;
+class SparseMatrix;
+
+// Interface for classes implementing various trust region strategies
+// for nonlinear least squares problems.
+//
+// The object is expected to maintain and update a trust region
+// radius, which it then uses to solve for the trust region step using
+// the jacobian matrix and residual vector.
+//
+// Here the term trust region radius is used loosely, as the strategy
+// is free to treat it as guidance and violate it as need be. e.g.,
+// the LevenbergMarquardtStrategy uses the inverse of the trust region
+// radius to scale the damping term, which controls the step size, but
+// does not set a hard limit on its size.
+class TrustRegionStrategy {
+public:
+  struct Options {
+    Options()
+        : trust_region_strategy_type(LEVENBERG_MARQUARDT),
+          initial_radius(1e4),
+          max_radius(1e32),
+          lm_min_diagonal(1e-6),
+          lm_max_diagonal(1e32),
+          dogleg_type(TRADITIONAL_DOGLEG) {
+    }
+
+    TrustRegionStrategyType trust_region_strategy_type;
+    // Linear solver used for actually solving the trust region step.
+    LinearSolver* linear_solver;
+    double initial_radius;
+    double max_radius;
+
+    // Minimum and maximum values of the diagonal damping matrix used
+    // by LevenbergMarquardtStrategy. The DoglegStrategy also uses
+    // these bounds to construct a regularizing diagonal to ensure
+    // that the Gauss-Newton step computation is of full rank.
+    double lm_min_diagonal;
+    double lm_max_diagonal;
+
+    // Further specify which dogleg method to use
+    DoglegType dogleg_type;
+  };
+
+  // Per solve options.
+  struct PerSolveOptions {
+    // Forcing sequence for inexact solves.
+    double eta;
+  };
+
+  struct Summary {
+    Summary()
+        : residual_norm(0.0),
+          num_iterations(-1),
+          termination_type(FAILURE) {
+    }
+
+    // If the trust region problem is,
+    //
+    //   1/2 x'Ax + b'x + c,
+    //
+    // then
+    //
+    //   residual_norm = |Ax -b|
+    double residual_norm;
+
+    // Number of iterations used by the linear solver. If a linear
+    // solver was not called (e.g., DogLegStrategy after an
+    // unsuccessful step), then this would be zero.
+    int num_iterations;
+
+    // Status of the linear solver used to solve the Newton system.
+    LinearSolverTerminationType termination_type;
+  };
+
+  virtual ~TrustRegionStrategy();
+
+  // Use the current radius to solve for the trust region step.
+  virtual Summary ComputeStep(const PerSolveOptions& per_solve_options,
+                              SparseMatrix* jacobian,
+                              const double* residuals,
+                              double* step) = 0;
+
+  // Inform the strategy that the current step has been accepted, and
+  // that the ratio of the decrease in the non-linear objective to the
+  // decrease in the trust region model is step_quality.
+  virtual void StepAccepted(double step_quality) = 0;
+
+  // Inform the strategy that the current step has been rejected, and
+  // that the ratio of the decrease in the non-linear objective to the
+  // decrease in the trust region model is step_quality.
+  virtual void StepRejected(double step_quality) = 0;
+
+  // Inform the strategy that the current step has been rejected
+  // because it was found to be numerically invalid.
+  // StepRejected/StepAccepted will not be called for this step, and
+  // the strategy is free to do what it wants with this information.
+  virtual void StepIsInvalid() = 0;
+
+  // Current trust region radius.
+  virtual double Radius() const = 0;
+
+  // Factory.
+  static TrustRegionStrategy* Create(const Options& options);
+};
+
+}  // namespace internal
+}  // namespace ceres
+
+#endif  // CERES_INTERNAL_TRUST_REGION_STRATEGY_H_
diff --git a/extern/libmv/third_party/ceres/internal/ceres/types.cc b/extern/libmv/third_party/ceres/internal/ceres/types.cc
index 860f8a43f37..05e573ff6d5 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/types.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/types.cc
@@ -37,8 +37,9 @@ namespace ceres {
 
 const char* LinearSolverTypeToString(LinearSolverType solver_type) {
   switch (solver_type) {
-    CASESTR(SPARSE_NORMAL_CHOLESKY);
+    CASESTR(DENSE_NORMAL_CHOLESKY);
     CASESTR(DENSE_QR);
+    CASESTR(SPARSE_NORMAL_CHOLESKY);
     CASESTR(DENSE_SCHUR);
     CASESTR(SPARSE_SCHUR);
     CASESTR(ITERATIVE_SCHUR);
@@ -61,6 +62,16 @@ const char* PreconditionerTypeToString(
   }
 }
 
+const char* SparseLinearAlgebraLibraryTypeToString(
+    SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type) {
+  switch (sparse_linear_algebra_library_type) {
+    CASESTR(SUITE_SPARSE);
+    CASESTR(CX_SPARSE);
+    default:
+      return "UNKNOWN";
+  }
+}
+
 const char* OrderingTypeToString(OrderingType ordering_type) {
   switch (ordering_type) {
     CASESTR(NATURAL);
@@ -87,6 +98,28 @@ const char* SolverTerminationTypeToString(
   }
 }
 
+#if 0  /* UNUSED */
+static const char* SparseLinearAlgebraTypeToString(
+    SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type) {
+  switch (sparse_linear_algebra_library_type) {
+    CASESTR(CX_SPARSE);
+    CASESTR(SUITE_SPARSE);
+    default:
+      return "UNKNOWN";
+  }
+}
+#endif
+
+const char* TrustRegionStrategyTypeToString(
+    TrustRegionStrategyType trust_region_strategy_type) {
+  switch (trust_region_strategy_type) {
+    CASESTR(LEVENBERG_MARQUARDT);
+    CASESTR(DOGLEG);
+    default:
+      return "UNKNOWN";
+  }
+}
+
 #undef CASESTR
 
 bool IsSchurType(LinearSolverType type) {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/visibility.cc b/extern/libmv/third_party/ceres/internal/ceres/visibility.cc
index fd41648a7af..564cc54493e 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/visibility.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/visibility.cc
@@ -34,11 +34,11 @@
 #include <set>
 #include <vector>
 #include <utility>
-
-#include <glog/logging.h>
 #include "ceres/block_structure.h"
 #include "ceres/collections_port.h"
+#include "ceres/visibility.h"
 #include "ceres/graph.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
diff --git a/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.cc b/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.cc
index aca77528215..4caad03d7a1 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.cc
+++ b/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.cc
@@ -33,11 +33,9 @@
 #include <algorithm>
 #include <functional>
 #include <iterator>
-#include <numeric>
 #include <set>
 #include <utility>
 #include <vector>
-#include <glog/logging.h>
 #include "Eigen/Dense"
 #include "ceres/block_random_access_sparse_matrix.h"
 #include "ceres/block_sparse_matrix.h"
@@ -46,10 +44,11 @@
 #include "ceres/detect_structure.h"
 #include "ceres/graph.h"
 #include "ceres/graph_algorithms.h"
+#include "ceres/internal/scoped_ptr.h"
 #include "ceres/linear_solver.h"
 #include "ceres/schur_eliminator.h"
 #include "ceres/visibility.h"
-#include "ceres/internal/scoped_ptr.h"
+#include "glog/logging.h"
 
 namespace ceres {
 namespace internal {
@@ -253,7 +252,6 @@ void VisibilityBasedPreconditioner::ComputeBlockPairsInPreconditioner(
   }
 
   int r = 0;
-  set<pair<int, int> > skipped_pairs;
   const int num_row_blocks = bs.rows.size();
   const int num_eliminate_blocks = options_.num_eliminate_blocks;
 
@@ -304,8 +302,6 @@ void VisibilityBasedPreconditioner::ComputeBlockPairsInPreconditioner(
       for (; block2 != f_blocks.end(); ++block2) {
         if (IsBlockPairInPreconditioner(*block1, *block2)) {
           block_pairs_.insert(make_pair(*block1, *block2));
-        } else {
-          skipped_pairs.insert(make_pair(*block1, *block2));
         }
       }
     }
@@ -322,17 +318,13 @@ void VisibilityBasedPreconditioner::ComputeBlockPairsInPreconditioner(
         if (block1 <= block2) {
           if (IsBlockPairInPreconditioner(block1, block2)) {
             block_pairs_.insert(make_pair(block1, block2));
-          } else {
-            skipped_pairs.insert(make_pair(block1, block2));
           }
         }
       }
     }
   }
 
-  VLOG(1) << "Block pair stats: "
-          << block_pairs_.size() << " included "
-          << skipped_pairs.size() << " excluded";
+  VLOG(1) << "Block pair stats: " << block_pairs_.size();
 }
 
 // Initialize the SchurEliminator.
@@ -341,7 +333,6 @@ void VisibilityBasedPreconditioner::InitEliminator(
   LinearSolver::Options eliminator_options;
   eliminator_options.num_eliminate_blocks = options_.num_eliminate_blocks;
   eliminator_options.num_threads = options_.num_threads;
-  eliminator_options.constant_sparsity = true;
 
   DetectStructure(bs, options_.num_eliminate_blocks,
                   &eliminator_options.row_block_size,
@@ -352,9 +343,9 @@ void VisibilityBasedPreconditioner::InitEliminator(
   eliminator_->Init(options_.num_eliminate_blocks, &bs);
 }
 
-// Compute the values of the preconditioner matrix and factorize it.
-bool VisibilityBasedPreconditioner::Compute(const BlockSparseMatrixBase& A,
-                                            const double* D) {
+// Update the values of the preconditioner matrix and factorize it.
+bool VisibilityBasedPreconditioner::Update(const BlockSparseMatrixBase& A,
+                                           const double* D) {
   const time_t start_time = time(NULL);
   const int num_rows = m_->num_rows();
   CHECK_GT(num_rows, 0);
@@ -448,12 +439,21 @@ bool VisibilityBasedPreconditioner::Factorize() {
   // matrix contains the values.
   lhs->stype = 1;
 
-  // Symbolic factorization is computed if we don't already have one
-  // handy.
+  // Symbolic factorization is computed if we don't already have one handy.
   if (factor_ == NULL) {
-    factor_ = ss_.AnalyzeCholesky(lhs);
+    if (options_.use_block_amd) {
+      factor_ = ss_.BlockAnalyzeCholesky(lhs, block_size_, block_size_);
+    } else {
+      factor_ = ss_.AnalyzeCholesky(lhs);
+    }
+
+    if (VLOG_IS_ON(2)) {
+      cholmod_print_common("Symbolic Analysis", ss_.mutable_cc());
+    }
   }
 
+  CHECK_NOTNULL(factor_);
+
   bool status = ss_.Cholesky(lhs, factor_);
   ss_.Free(lhs);
   return status;
diff --git a/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.h b/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.h
index fa095ca1dd8..888c65eba3a 100644
--- a/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.h
+++ b/extern/libmv/third_party/ceres/internal/ceres/visibility_based_preconditioner.h
@@ -133,7 +133,7 @@ class SchurEliminatorBase;
 //   options.num_eliminate_blocks = num_points;
 //   VisibilityBasedPreconditioner preconditioner(
 //      *A.block_structure(), options);
-//   preconditioner.Compute(A, NULL);
+//   preconditioner.Update(A, NULL);
 //   preconditioner.RightMultiply(x, y);
 //
 
@@ -160,7 +160,7 @@ class VisibilityBasedPreconditioner : public LinearOperator {
                                 const LinearSolver::Options& options);
   virtual ~VisibilityBasedPreconditioner();
 
-  // Compute the numerical value of the preconditioner for the linear
+  // Update the numerical value of the preconditioner for the linear
   // system:
   //
   //  |   A   | x = |b|
@@ -171,12 +171,12 @@ class VisibilityBasedPreconditioner : public LinearOperator {
   //
   // D can be NULL, in which case its interpreted as a diagonal matrix
   // of size zero.
-  bool Compute(const BlockSparseMatrixBase& A,
-               const double* D);
+  bool Update(const BlockSparseMatrixBase& A, const double* D);
+
 
   // LinearOperator interface. Since the operator is symmetric,
   // LeftMultiply and num_cols are just calls to RightMultiply and
-  // num_rows respectively. Compute() must be called before
+  // num_rows respectively. Update() must be called before
   // RightMultiply can be called.
   virtual void RightMultiply(const double* x, double* y) const;
   virtual void LeftMultiply(const double* x, double* y) const {
@@ -244,7 +244,7 @@ class VisibilityBasedPreconditioner : public LinearOperator {
 
   // Temporary vector used by RightMultiply.
   cholmod_dense* tmp_rhs_;
-  DISALLOW_COPY_AND_ASSIGN(VisibilityBasedPreconditioner);
+  CERES_DISALLOW_COPY_AND_ASSIGN(VisibilityBasedPreconditioner);
 };
 #else  // SuiteSparse
 // If SuiteSparse is not compiled in, the preconditioner is not
@@ -261,7 +261,7 @@ class VisibilityBasedPreconditioner : public LinearOperator {
   virtual void LeftMultiply(const double* x, double* y) const {}
   virtual int num_rows() const { return -1; }
   virtual int num_cols() const { return -1; }
-  bool Compute(const BlockSparseMatrixBase& A, const double* D) {
+  bool Update(const BlockSparseMatrixBase& A, const double* D) {
     return false;
   }
 };
diff --git a/extern/libmv/third_party/ceres/patches/collections_port.h.mingw.patch b/extern/libmv/third_party/ceres/patches/collections_port.h.mingw.patch
index bbb366e22bc..c01a17c7992 100644
--- a/extern/libmv/third_party/ceres/patches/collections_port.h.mingw.patch
+++ b/extern/libmv/third_party/ceres/patches/collections_port.h.mingw.patch
@@ -1,10 +1,10 @@
-Index: internal/ceres/collections_port.h
-===================================================================
---- internal/ceres/collections_port.h	(revision 47730)
-+++ internal/ceres/collections_port.h	(working copy)
-@@ -53,7 +53,7 @@
+diff --git a/internal/ceres/collections_port.h b/internal/ceres/collections_port.h
+index a356cc0..c2fce90 100644
+--- a/internal/ceres/collections_port.h
++++ b/internal/ceres/collections_port.h
+@@ -77,7 +77,7 @@ struct HashMap : std::tr1::unordered_map<K, V> {};
  template<typename K>
- struct HashSet : tr1::unordered_set<K> {};
+ struct HashSet : std::tr1::unordered_set<K> {};
  
 -#ifdef _WIN32
 +#if defined(_WIN32) && !defined(__MINGW64__) && !defined(__MINGW32__)
diff --git a/extern/libmv/third_party/ceres/patches/msvc_glog_fix.patch b/extern/libmv/third_party/ceres/patches/msvc_glog_fix.patch
new file mode 100644
index 00000000000..f3200fb8e0a
--- /dev/null
+++ b/extern/libmv/third_party/ceres/patches/msvc_glog_fix.patch
@@ -0,0 +1,50 @@
+diff --git a/internal/ceres/block_random_access_dense_matrix.cc b/internal/ceres/block_random_access_dense_matrix.cc
+index aedfc74..0f95e89 100644
+--- a/internal/ceres/block_random_access_dense_matrix.cc
++++ b/internal/ceres/block_random_access_dense_matrix.cc
+@@ -28,12 +28,12 @@
+ //
+ // Author: sameeragarwal@google.com (Sameer Agarwal)
+ 
++#include "glog/logging.h"
+ #include "ceres/block_random_access_dense_matrix.h"
+ 
+ #include <vector>
+ #include "ceres/internal/eigen.h"
+ #include "ceres/internal/scoped_ptr.h"
+-#include "glog/logging.h"
+ 
+ namespace ceres {
+ namespace internal {
+diff --git a/internal/ceres/block_random_access_sparse_matrix.cc b/internal/ceres/block_random_access_sparse_matrix.cc
+index f789436..9ed62ce 100644
+--- a/internal/ceres/block_random_access_sparse_matrix.cc
++++ b/internal/ceres/block_random_access_sparse_matrix.cc
+@@ -28,6 +28,7 @@
+ //
+ // Author: sameeragarwal@google.com (Sameer Agarwal)
+ 
++#include "glog/logging.h"
+ #include "ceres/block_random_access_sparse_matrix.h"
+ 
+ #include <algorithm>
+@@ -39,7 +40,6 @@
+ #include "ceres/mutex.h"
+ #include "ceres/triplet_sparse_matrix.h"
+ #include "ceres/types.h"
+-#include "glog/logging.h"
+ 
+ namespace ceres {
+ namespace internal {
+diff --git a/internal/ceres/schur_complement_solver.cc b/internal/ceres/schur_complement_solver.cc
+index b9224d8..2cbe78d 100644
+--- a/internal/ceres/schur_complement_solver.cc
++++ b/internal/ceres/schur_complement_solver.cc
+@@ -38,6 +38,7 @@
+ #endif  // CERES_NO_CXSPARSE
+ 
+ #include "Eigen/Dense"
++#include "glog/logging.h"
+ #include "ceres/block_random_access_dense_matrix.h"
+ #include "ceres/block_random_access_matrix.h"
+ #include "ceres/block_random_access_sparse_matrix.h"
diff --git a/extern/libmv/third_party/ceres/patches/msvc_isfinite.patch b/extern/libmv/third_party/ceres/patches/msvc_isfinite.patch
deleted file mode 100644
index c3129d8e02b..00000000000
--- a/extern/libmv/third_party/ceres/patches/msvc_isfinite.patch
+++ /dev/null
@@ -1,15 +0,0 @@
-diff --git a/internal/ceres/residual_block_utils.cc b/internal/ceres/residual_block_utils.cc
-index ed3499b..28e0313 100644
---- a/internal/ceres/residual_block_utils.cc
-+++ b/internal/ceres/residual_block_utils.cc
-@@ -40,6 +40,10 @@
- #include "ceres/internal/eigen.h"
- #include "ceres/internal/port.h"
- 
-+#ifdef _MSC_VER
-+#  define isfinite _finite
-+#endif
-+
- namespace ceres {
- namespace internal {
- 
diff --git a/extern/libmv/third_party/ceres/patches/no_previous_declaration_fix.patch b/extern/libmv/third_party/ceres/patches/no_previous_declaration_fix.patch
new file mode 100644
index 00000000000..03f1c500d9a
--- /dev/null
+++ b/extern/libmv/third_party/ceres/patches/no_previous_declaration_fix.patch
@@ -0,0 +1,199 @@
+diff --git a/internal/ceres/file.cc b/internal/ceres/file.cc
+index 387f359..6fe7557 100644
+--- a/internal/ceres/file.cc
++++ b/internal/ceres/file.cc
+@@ -31,6 +31,7 @@
+ // Really simple file IO.
+ 
+ #include <cstdio>
++#include "file.h"
+ #include "glog/logging.h"
+ 
+ namespace ceres {
+diff --git a/internal/ceres/linear_least_squares_problems.cc b/internal/ceres/linear_least_squares_problems.cc
+index 3e3bcd0..a91e254 100644
+--- a/internal/ceres/linear_least_squares_problems.cc
++++ b/internal/ceres/linear_least_squares_problems.cc
+@@ -573,13 +573,13 @@ LinearLeastSquaresProblem* LinearLeastSquaresProblem3() {
+   return problem;
+ }
+ 
+-bool DumpLinearLeastSquaresProblemToConsole(const string& directory,
+-                                            int iteration,
+-                                            const SparseMatrix* A,
+-                                            const double* D,
+-                                            const double* b,
+-                                            const double* x,
+-                                            int num_eliminate_blocks) {
++static bool DumpLinearLeastSquaresProblemToConsole(const string& directory,
++                                                   int iteration,
++                                                   const SparseMatrix* A,
++                                                   const double* D,
++                                                   const double* b,
++                                                   const double* x,
++                                                   int num_eliminate_blocks) {
+   CHECK_NOTNULL(A);
+   Matrix AA;
+   A->ToDenseMatrix(&AA);
+@@ -601,13 +601,13 @@ bool DumpLinearLeastSquaresProblemToConsole(const string& directory,
+ };
+ 
+ #ifndef CERES_NO_PROTOCOL_BUFFERS
+-bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
+-                                                   int iteration,
+-                                                   const SparseMatrix* A,
+-                                                   const double* D,
+-                                                   const double* b,
+-                                                   const double* x,
+-                                                   int num_eliminate_blocks) {
++static bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
++                                                          int iteration,
++                                                          const SparseMatrix* A,
++                                                          const double* D,
++                                                          const double* b,
++                                                          const double* x,
++                                                          int num_eliminate_blocks) {
+   CHECK_NOTNULL(A);
+   LinearLeastSquaresProblemProto lsqp;
+   A->ToProto(lsqp.mutable_a());
+@@ -641,13 +641,13 @@ bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
+   return true;
+ }
+ #else
+-bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
+-                                                   int iteration,
+-                                                   const SparseMatrix* A,
+-                                                   const double* D,
+-                                                   const double* b,
+-                                                   const double* x,
+-                                                   int num_eliminate_blocks) {
++static bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
++                                                          int iteration,
++                                                          const SparseMatrix* A,
++                                                          const double* D,
++                                                          const double* b,
++                                                          const double* x,
++                                                          int num_eliminate_blocks) {
+   LOG(ERROR) << "Dumping least squares problems is only "
+              << "supported when Ceres is compiled with "
+              << "protocol buffer support.";
+@@ -655,9 +655,9 @@ bool DumpLinearLeastSquaresProblemToProtocolBuffer(const string& directory,
+ }
+ #endif
+ 
+-void WriteArrayToFileOrDie(const string& filename,
+-                           const double* x,
+-                           const int size) {
++static void WriteArrayToFileOrDie(const string& filename,
++                                  const double* x,
++                                  const int size) {
+   CHECK_NOTNULL(x);
+   VLOG(2) << "Writing array to: " << filename;
+   FILE* fptr = fopen(filename.c_str(), "w");
+@@ -668,13 +668,13 @@ void WriteArrayToFileOrDie(const string& filename,
+   fclose(fptr);
+ }
+ 
+-bool DumpLinearLeastSquaresProblemToTextFile(const string& directory,
+-                                             int iteration,
+-                                             const SparseMatrix* A,
+-                                             const double* D,
+-                                             const double* b,
+-                                             const double* x,
+-                                             int num_eliminate_blocks) {
++static bool DumpLinearLeastSquaresProblemToTextFile(const string& directory,
++                                                    int iteration,
++                                                    const SparseMatrix* A,
++                                                    const double* D,
++                                                    const double* b,
++                                                    const double* x,
++                                                    int num_eliminate_blocks) {
+   CHECK_NOTNULL(A);
+   string format_string = JoinPath(directory,
+                                   "lm_iteration_%03d");
+diff --git a/internal/ceres/residual_block_utils.cc b/internal/ceres/residual_block_utils.cc
+index ff18e21..9442bb2 100644
+--- a/internal/ceres/residual_block_utils.cc
++++ b/internal/ceres/residual_block_utils.cc
+@@ -63,7 +63,7 @@ void InvalidateEvaluation(const ResidualBlock& block,
+ 
+ // Utility routine to print an array of doubles to a string. If the
+ // array pointer is NULL, it is treated as an array of zeros.
+-void AppendArrayToString(const int size, const double* x, string* result) {
++static void AppendArrayToString(const int size, const double* x, string* result) {
+   for (int i = 0; i < size; ++i) {
+     if (x == NULL) {
+       StringAppendF(result, "Not Computed  ");
+diff --git a/internal/ceres/solver_impl.cc b/internal/ceres/solver_impl.cc
+index 2802a75..8ef5b98 100644
+--- a/internal/ceres/solver_impl.cc
++++ b/internal/ceres/solver_impl.cc
+@@ -685,8 +685,8 @@ bool SolverImpl::ApplyUserOrdering(const ProblemImpl& problem_impl,
+ // Find the minimum index of any parameter block to the given residual.
+ // Parameter blocks that have indices greater than num_eliminate_blocks are
+ // considered to have an index equal to num_eliminate_blocks.
+-int MinParameterBlock(const ResidualBlock* residual_block,
+-                      int num_eliminate_blocks) {
++static int MinParameterBlock(const ResidualBlock* residual_block,
++                             int num_eliminate_blocks) {
+   int min_parameter_block_position = num_eliminate_blocks;
+   for (int i = 0; i < residual_block->NumParameterBlocks(); ++i) {
+     ParameterBlock* parameter_block = residual_block->parameter_blocks()[i];
+diff --git a/internal/ceres/split.cc b/internal/ceres/split.cc
+index 4fa1bd4..c65c8a5 100644
+--- a/internal/ceres/split.cc
++++ b/internal/ceres/split.cc
+@@ -31,6 +31,7 @@
+ #include <string>
+ #include <vector>
+ #include <iterator>
++#include "ceres/split.h"
+ #include "ceres/internal/port.h"
+ 
+ namespace ceres {
+diff --git a/internal/ceres/stringprintf.cc b/internal/ceres/stringprintf.cc
+index c0f3522..396a48b 100644
+--- a/internal/ceres/stringprintf.cc
++++ b/internal/ceres/stringprintf.cc
+@@ -34,6 +34,7 @@
+ #include <string>
+ #include <vector>
+ 
++#include "ceres/stringprintf.h"
+ #include "ceres/internal/port.h"
+ 
+ namespace ceres {
+diff --git a/internal/ceres/types.cc b/internal/ceres/types.cc
+index 2e950c5..05e573f 100644
+--- a/internal/ceres/types.cc
++++ b/internal/ceres/types.cc
+@@ -98,7 +98,8 @@ const char* SolverTerminationTypeToString(
+   }
+ }
+ 
+-const char* SparseLinearAlgebraTypeToString(
++#if 0  /* UNUSED */
++static const char* SparseLinearAlgebraTypeToString(
+     SparseLinearAlgebraLibraryType sparse_linear_algebra_library_type) {
+   switch (sparse_linear_algebra_library_type) {
+     CASESTR(CX_SPARSE);
+@@ -107,6 +108,7 @@ const char* SparseLinearAlgebraTypeToString(
+       return "UNKNOWN";
+   }
+ }
++#endif
+ 
+ const char* TrustRegionStrategyTypeToString(
+     TrustRegionStrategyType trust_region_strategy_type) {
+diff --git a/internal/ceres/visibility.cc b/internal/ceres/visibility.cc
+index 9d80654..564cc54 100644
+--- a/internal/ceres/visibility.cc
++++ b/internal/ceres/visibility.cc
+@@ -36,6 +36,7 @@
+ #include <utility>
+ #include "ceres/block_structure.h"
+ #include "ceres/collections_port.h"
++#include "ceres/visibility.h"
+ #include "ceres/graph.h"
+ #include "glog/logging.h"
+ 
diff --git a/extern/libmv/third_party/ceres/patches/series b/extern/libmv/third_party/ceres/patches/series
index dbe955ae61e..a6874318923 100644
--- a/extern/libmv/third_party/ceres/patches/series
+++ b/extern/libmv/third_party/ceres/patches/series
@@ -1 +1,3 @@
-msvc_isfinite.patch
+collections_port.h.mingw.patch
+msvc_glog_fix.patch
+no_previous_declaration_fix.patch
\ No newline at end of file
diff --git a/extern/recastnavigation/Recast/Source/RecastMeshDetail.cpp b/extern/recastnavigation/Recast/Source/RecastMeshDetail.cpp
index 130c08ec369..b52da597675 100644
--- a/extern/recastnavigation/Recast/Source/RecastMeshDetail.cpp
+++ b/extern/recastnavigation/Recast/Source/RecastMeshDetail.cpp
@@ -1015,7 +1015,7 @@ bool rcBuildPolyMeshDetail(rcContext* ctx, const rcPolyMesh& mesh, const rcCompa
 		maxhh = rcMax(maxhh, ymax-ymin);
 	}
 	
-	hp.data = (unsigned short*)rcAlloc(sizeof(unsigned short)*maxhw*maxhh, RC_ALLOC_TEMP);
+	hp.data = (unsigned short *)rcAlloc(sizeof(unsigned short)*maxhw*maxhh, RC_ALLOC_TEMP);
 	if (!hp.data)
 	{
 		ctx->log(RC_LOG_ERROR, "rcBuildPolyMeshDetail: Out of memory 'hp.data' (%d).", maxhw*maxhh);