diff --git a/CMakeLists.txt b/CMakeLists.txt
index 1d84e91..dc26e71 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -37,6 +37,9 @@
   option(EIGEN_BUILD_LIB "Build the binary shared library" OFF)
 endif(NOT WIN32)
 option(EIGEN_BUILD_BTL "Build benchmark suite" OFF)
+if(NOT WIN32)
+  option(EIGEN_BUILD_PKGCONFIG "Build pkg-config .pc file for Eigen" ON)
+endif(NOT WIN32)
 
 if(EIGEN_BUILD_LIB)
   option(EIGEN_TEST_LIB "Build the unit tests using the library (disable -pedantic)" OFF)
@@ -108,6 +111,13 @@
     "The directory where we install the header files"
     FORCE)
 
+if(EIGEN_BUILD_PKGCONFIG)
+    configure_file(eigen2.pc.in eigen2.pc)
+    install(FILES eigen2.pc
+        DESTINATION lib/pkgconfig
+        )
+endif(EIGEN_BUILD_PKGCONFIG)
+
 add_subdirectory(Eigen)
 
 add_subdirectory(doc)
@@ -129,4 +139,4 @@
 
 if(EIGEN_BUILD_TESTS)
   ei_testing_print_summary()
-endif(EIGEN_BUILD_TESTS)
\ No newline at end of file
+endif(EIGEN_BUILD_TESTS)
diff --git a/CTestConfig.cmake b/CTestConfig.cmake
index be43dac..263cda4 100644
--- a/CTestConfig.cmake
+++ b/CTestConfig.cmake
@@ -3,11 +3,11 @@
 ## project to incorporate the testing dashboard.
 ## # The following are required to uses Dart and the Cdash dashboard
 ##   ENABLE_TESTING()
-##   INCLUDE(Dart)
+##   INCLUDE(CTest)
 set(CTEST_PROJECT_NAME "Eigen")
 set(CTEST_NIGHTLY_START_TIME "05:00:00 UTC")
 
 set(CTEST_DROP_METHOD "http")
-set(CTEST_DROP_SITE "www.cdash.org")
-set(CTEST_DROP_LOCATION "/CDashPublic/submit.php?project=Eigen")
+set(CTEST_DROP_SITE "my.cdash.org")
+set(CTEST_DROP_LOCATION "/submit.php?project=Eigen")
 set(CTEST_DROP_SITE_CDASH TRUE)
diff --git a/Eigen/src/LU/PartialLU.h b/Eigen/src/LU/PartialLU.h
index 7fdbeac..3a6e9f2 100644
--- a/Eigen/src/LU/PartialLU.h
+++ b/Eigen/src/LU/PartialLU.h
@@ -225,8 +225,8 @@
   /* The decomposition PA = LU can be rewritten as A = P^{-1} L U.
    * So we proceed as follows:
    * Step 1: compute c = Pb.
-   * Step 2: replace c by the solution x to Lx = c. Exists because L is invertible.
-   * Step 3: replace c by the solution x to Ux = c. Check if a solution really exists.
+   * Step 2: replace c by the solution x to Lx = c.
+   * Step 3: replace c by the solution x to Ux = c.
    */
 
   const int size = m_lu.rows();
diff --git a/Eigen/src/Sparse/DynamicSparseMatrix.h b/Eigen/src/Sparse/DynamicSparseMatrix.h
index 2927cd5..ec730dd 100644
--- a/Eigen/src/Sparse/DynamicSparseMatrix.h
+++ b/Eigen/src/Sparse/DynamicSparseMatrix.h
@@ -35,7 +35,7 @@
   * 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.
@@ -67,23 +67,23 @@
     // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, +=)
     // EIGEN_SPARSE_INHERIT_ASSIGNMENT_OPERATOR(DynamicSparseMatrix, -=)
     typedef MappedSparseMatrix<Scalar,Flags> Map;
+    using Base::IsRowMajor;
 
   protected:
 
-    enum { IsRowMajor = Base::IsRowMajor };
     typedef DynamicSparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
 
     int m_innerSize;
     std::vector<CompressedStorage<Scalar> > m_data;
 
   public:
-  
+
     inline int rows() const { return IsRowMajor ? outerSize() : m_innerSize; }
     inline int cols() const { return IsRowMajor ? m_innerSize : outerSize(); }
     inline int innerSize() const { return m_innerSize; }
     inline int outerSize() const { return m_data.size(); }
     inline int innerNonZeros(int j) const { return m_data[j].size(); }
-    
+
     std::vector<CompressedStorage<Scalar> >& _data() { return m_data; }
     const std::vector<CompressedStorage<Scalar> >& _data() const { return m_data; }
 
@@ -132,7 +132,7 @@
       setZero();
       reserve(reserveSize);
     }
-    
+
     void reserve(int reserveSize = 1000)
     {
       if (outerSize()>0)
@@ -144,13 +144,13 @@
         }
       }
     }
-    
+
     inline void startVec(int /*outer*/) {}
-    
+
     inline Scalar& insertBack(int outer, int inner)
     {
       ei_assert(outer<int(m_data.size()) && inner<m_innerSize && "out of range");
-      ei_assert(((m_data[outer].size()==0) || (m_data[outer].index(m_data[outer].size()-1)<inner)) 
+      ei_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);
@@ -162,7 +162,7 @@
       *  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(int row, int col)
@@ -181,12 +181,12 @@
     {
       return insert(row,col);
     }
-    
+
     inline Scalar& insert(int row, int col)
     {
       const int outer = IsRowMajor ? row : col;
       const int inner = IsRowMajor ? col : row;
-      
+
       int startId = 0;
       int id = m_data[outer].size() - 1;
       m_data[outer].resize(id+2,1);
@@ -205,9 +205,9 @@
     /** \deprecated use finalize()
       * Does nothing. Provided for compatibility with SparseMatrix. */
     EIGEN_DEPRECATED void endFill() {}
-    
+
     inline void finalize() {}
-    
+
     void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
     {
       for (int j=0; j<outerSize(); ++j)
@@ -226,7 +226,7 @@
         m_data.resize(outerSize);
       }
     }
-    
+
     void resizeAndKeepData(int rows, int cols)
     {
       const int outerSize = IsRowMajor ? rows : cols;
@@ -309,7 +309,7 @@
     InnerIterator(const DynamicSparseMatrix& mat, int outer)
       : Base(mat.m_data[outer]), m_outer(outer)
     {}
-    
+
     inline int row() const { return IsRowMajor ? m_outer : Base::index(); }
     inline int col() const { return IsRowMajor ? Base::index() : m_outer; }
 
diff --git a/Eigen/src/Sparse/SparseBlock.h b/Eigen/src/Sparse/SparseBlock.h
index 72589d0..655ba6d 100644
--- a/Eigen/src/Sparse/SparseBlock.h
+++ b/Eigen/src/Sparse/SparseBlock.h
@@ -43,16 +43,21 @@
 class SparseInnerVectorSet : ei_no_assignment_operator,
   public SparseMatrixBase<SparseInnerVectorSet<MatrixType, Size> >
 {
-    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
   public:
 
+    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
+
     EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseInnerVectorSet)
     class InnerIterator: public MatrixType::InnerIterator
     {
       public:
         inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
-          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer)
+          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
         {}
+        inline int row() const { return IsRowMajor ? m_outer : this->index(); }
+        inline int col() const { return IsRowMajor ? this->index() : m_outer; }
+      protected:
+        int m_outer;
     };
 
     inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
@@ -100,16 +105,21 @@
   : public SparseMatrixBase<SparseInnerVectorSet<DynamicSparseMatrix<_Scalar, _Options>, Size> >
 {
     typedef DynamicSparseMatrix<_Scalar, _Options> MatrixType;
-    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
   public:
 
+    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
+
     EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseInnerVectorSet)
     class InnerIterator: public MatrixType::InnerIterator
     {
       public:
         inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
-          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer)
+          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
         {}
+        inline int row() const { return IsRowMajor ? m_outer : this->index(); }
+        inline int col() const { return IsRowMajor ? this->index() : m_outer; }
+      protected:
+        int m_outer;
     };
 
     inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
@@ -193,16 +203,21 @@
   : public SparseMatrixBase<SparseInnerVectorSet<SparseMatrix<_Scalar, _Options>, Size> >
 {
     typedef SparseMatrix<_Scalar, _Options> MatrixType;
-    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
   public:
 
+    enum { IsRowMajor = ei_traits<SparseInnerVectorSet>::IsRowMajor };
+
     EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseInnerVectorSet)
     class InnerIterator: public MatrixType::InnerIterator
     {
       public:
         inline InnerIterator(const SparseInnerVectorSet& xpr, int outer)
-          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer)
+          : MatrixType::InnerIterator(xpr.m_matrix, xpr.m_outerStart + outer), m_outer(outer)
         {}
+        inline int row() const { return IsRowMajor ? m_outer : this->index(); }
+        inline int col() const { return IsRowMajor ? this->index() : m_outer; }
+      protected:
+        int m_outer;
     };
 
     inline SparseInnerVectorSet(const MatrixType& matrix, int outerStart, int outerSize)
diff --git a/Eigen/src/Sparse/SparseCwiseBinaryOp.h b/Eigen/src/Sparse/SparseCwiseBinaryOp.h
index d19970e..96fd1d3 100644
--- a/Eigen/src/Sparse/SparseCwiseBinaryOp.h
+++ b/Eigen/src/Sparse/SparseCwiseBinaryOp.h
@@ -186,8 +186,8 @@
     EIGEN_STRONG_INLINE Scalar value() const { return m_value; }
 
     EIGEN_STRONG_INLINE int index() const { return m_id; }
-    EIGEN_STRONG_INLINE int row() const { return m_lhsIter.row(); }
-    EIGEN_STRONG_INLINE int col() const { return m_lhsIter.col(); }
+    EIGEN_STRONG_INLINE int row() const { return Lhs::IsRowMajor ? m_lhsIter.row() : index(); }
+    EIGEN_STRONG_INLINE int col() const { return Lhs::IsRowMajor ? index() : m_lhsIter.col(); }
 
     EIGEN_STRONG_INLINE operator bool() const { return m_id>=0; }
 
diff --git a/Eigen/src/Sparse/SparseMatrix.h b/Eigen/src/Sparse/SparseMatrix.h
index 8bcf3c8..65cee69 100644
--- a/Eigen/src/Sparse/SparseMatrix.h
+++ b/Eigen/src/Sparse/SparseMatrix.h
@@ -25,17 +25,24 @@
 #ifndef EIGEN_SPARSEMATRIX_H
 #define EIGEN_SPARSEMATRIX_H
 
-/** \class SparseMatrix
+/** \ingroup Sparse_Module
   *
-  * \brief Sparse matrix
+  * \class SparseMatrix
+  *
+  * \brief The main sparse matrix class
+  *
+  * This class implements a sparse matrix using the very common compressed row/column storage
+  * scheme.
   *
   * \param _Scalar the scalar type, i.e. the type of the coefficients
+  * \param _Options Union of bit flags controlling the storage scheme. Currently the only possibility
+  *                 is RowMajor. The default is 0 which means column-major.
   *
   * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
   *
   */
-template<typename _Scalar, int _Flags>
-struct ei_traits<SparseMatrix<_Scalar, _Flags> >
+template<typename _Scalar, int _Options>
+struct ei_traits<SparseMatrix<_Scalar, _Options> >
 {
   typedef _Scalar Scalar;
   enum {
@@ -43,17 +50,15 @@
     ColsAtCompileTime = Dynamic,
     MaxRowsAtCompileTime = Dynamic,
     MaxColsAtCompileTime = Dynamic,
-    Flags = SparseBit | _Flags,
+    Flags = SparseBit | _Options,
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
     SupportedAccessPatterns = InnerRandomAccessPattern
   };
 };
 
-
-
-template<typename _Scalar, int _Flags>
+template<typename _Scalar, int _Options>
 class SparseMatrix
-  : public SparseMatrixBase<SparseMatrix<_Scalar, _Flags> >
+  : public SparseMatrixBase<SparseMatrix<_Scalar, _Options> >
 {
   public:
     EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseMatrix)
@@ -64,10 +69,10 @@
     // EIGEN_SPARSE_INHERIT_SCALAR_ASSIGNMENT_OPERATOR(SparseMatrix, /=)
 
     typedef MappedSparseMatrix<Scalar,Flags> Map;
+    using Base::IsRowMajor;
 
   protected:
 
-    enum { IsRowMajor = Base::IsRowMajor };
     typedef SparseMatrix<Scalar,(Flags&~RowMajorBit)|(IsRowMajor?RowMajorBit:0)> TransposedSparseMatrix;
 
     int m_outerSize;
@@ -508,10 +513,13 @@
     {
       delete[] m_outerIndex;
     }
+
+    /** Overloaded for performance */
+    Scalar sum() const;
 };
 
-template<typename Scalar, int _Flags>
-class SparseMatrix<Scalar,_Flags>::InnerIterator
+template<typename Scalar, int _Options>
+class SparseMatrix<Scalar,_Options>::InnerIterator
 {
   public:
     InnerIterator(const SparseMatrix& mat, int outer)
diff --git a/Eigen/src/Sparse/SparseMatrixBase.h b/Eigen/src/Sparse/SparseMatrixBase.h
index 948424f..34779d9 100644
--- a/Eigen/src/Sparse/SparseMatrixBase.h
+++ b/Eigen/src/Sparse/SparseMatrixBase.h
@@ -25,6 +25,17 @@
 #ifndef EIGEN_SPARSEMATRIXBASE_H
 #define EIGEN_SPARSEMATRIXBASE_H
 
+/** \ingroup Sparse_Module
+  *
+  * \class SparseMatrixBase
+  *
+  * \brief Base class of any sparse matrices or sparse expressions
+  *
+  * \param Derived
+  *
+  *
+  *
+  */
 template<typename Derived> class SparseMatrixBase
 {
   public:
@@ -69,7 +80,7 @@
         /**< This stores expression \ref flags flags which may or may not be inherited by new expressions
           * constructed from this one. See the \ref flags "list of flags".
           */
-      
+
       CoeffReadCost = ei_traits<Derived>::CoeffReadCost,
         /**< This is a rough measure of how expensive it is to read one coefficient from
           * this expression.
@@ -156,9 +167,9 @@
       ei_assert(( ((ei_traits<Derived>::SupportedAccessPatterns&OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
                   (!((Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit)))) &&
                   "the transpose operation is supposed to be handled in SparseMatrix::operator=");
-      
+
       enum { Flip = (Flags & RowMajorBit) != (OtherDerived::Flags & RowMajorBit) };
-      
+
       const int outerSize = other.outerSize();
       //typedef typename ei_meta_if<transpose, LinkedVectorMatrix<Scalar,Flags&RowMajorBit>, Derived>::ret TempType;
       // thanks to shallow copies, we always eval to a tempary
@@ -293,13 +304,13 @@
     template<typename OtherDerived>
     const typename SparseProductReturnType<Derived,OtherDerived>::Type
     operator*(const SparseMatrixBase<OtherDerived> &other) const;
-    
+
     // dense * sparse (return a dense object)
-    template<typename OtherDerived> friend 
+    template<typename OtherDerived> friend
     const typename SparseProductReturnType<OtherDerived,Derived>::Type
     operator*(const MatrixBase<OtherDerived>& lhs, const Derived& rhs)
     { return typename SparseProductReturnType<OtherDerived,Derived>::Type(lhs.derived(),rhs); }
-    
+
     template<typename OtherDerived>
     const typename SparseProductReturnType<Derived,OtherDerived>::Type
     operator*(const MatrixBase<OtherDerived> &other) const;
@@ -340,7 +351,7 @@
     const SparseInnerVectorSet<Derived,1> col(int j) const;
     SparseInnerVectorSet<Derived,1> innerVector(int outer);
     const SparseInnerVectorSet<Derived,1> innerVector(int outer) const;
-    
+
     // set of sub-vectors
     SparseInnerVectorSet<Derived,Dynamic> subrows(int start, int size);
     const SparseInnerVectorSet<Derived,Dynamic> subrows(int start, int size) const;
@@ -432,10 +443,16 @@
         for (int j=0; j<outerSize(); ++j)
         {
           for (typename Derived::InnerIterator i(derived(),j); i; ++i)
+          {
             if(IsRowMajor)
-              res.coeffRef(j,i.index()) = i.value();
+              std::cerr << i.row() << "," << i.col() << " == " << j << "," << i.index() << "\n";
             else
-              res.coeffRef(i.index(),j) = i.value();
+              std::cerr << i.row() << "," << i.col() << " == " << i.index() << "," << j << "\n";
+//             if(IsRowMajor)
+              res.coeffRef(i.row(),i.col()) = i.value();
+//             else
+//               res.coeffRef(i.index(),j) = i.value();
+          }
         }
         return res;
       }
diff --git a/Eigen/src/Sparse/SparseRedux.h b/Eigen/src/Sparse/SparseRedux.h
index f0d3705..e223c37 100644
--- a/Eigen/src/Sparse/SparseRedux.h
+++ b/Eigen/src/Sparse/SparseRedux.h
@@ -37,4 +37,20 @@
   return res;
 }
 
+template<typename _Scalar, int _Options>
+typename ei_traits<SparseMatrix<_Scalar,_Options> >::Scalar
+SparseMatrix<_Scalar,_Options>::sum() const
+{
+  ei_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
+  return Matrix<Scalar,1,Dynamic>::Map(m_data.value(0), m_data.size()).sum();
+}
+
+template<typename _Scalar, int _Options>
+typename ei_traits<SparseVector<_Scalar,_Options> >::Scalar
+SparseVector<_Scalar,_Options>::sum() const
+{
+  ei_assert(rows()>0 && cols()>0 && "you are using a non initialized matrix");
+  return Matrix<Scalar,1,Dynamic>::Map(m_data.value(0), m_data.size()).sum();
+}
+
 #endif // EIGEN_SPARSEREDUX_H
diff --git a/Eigen/src/Sparse/SparseTranspose.h b/Eigen/src/Sparse/SparseTranspose.h
index 89a14d7..879c377 100644
--- a/Eigen/src/Sparse/SparseTranspose.h
+++ b/Eigen/src/Sparse/SparseTranspose.h
@@ -66,20 +66,26 @@
 
 template<typename MatrixType> class SparseTranspose<MatrixType>::InnerIterator : public MatrixType::InnerIterator
 {
+    typedef typename MatrixType::InnerIterator Base;
   public:
 
     EIGEN_STRONG_INLINE InnerIterator(const SparseTranspose& trans, int outer)
-      : MatrixType::InnerIterator(trans.m_matrix, outer)
+      : Base(trans.m_matrix, outer)
     {}
+    inline int row() const { return Base::col(); }
+    inline int col() const { return Base::row(); }
 };
 
 template<typename MatrixType> class SparseTranspose<MatrixType>::ReverseInnerIterator : public MatrixType::ReverseInnerIterator
 {
+    typedef typename MatrixType::ReverseInnerIterator Base;
   public:
 
     EIGEN_STRONG_INLINE ReverseInnerIterator(const SparseTranspose& xpr, int outer)
-      : MatrixType::ReverseInnerIterator(xpr.m_matrix, outer)
+      : Base(xpr.m_matrix, outer)
     {}
+    inline int row() const { return Base::col(); }
+    inline int col() const { return Base::row(); }
 };
 
 #endif // EIGEN_SPARSETRANSPOSE_H
diff --git a/Eigen/src/Sparse/SparseVector.h b/Eigen/src/Sparse/SparseVector.h
index ac815e6..0535694 100644
--- a/Eigen/src/Sparse/SparseVector.h
+++ b/Eigen/src/Sparse/SparseVector.h
@@ -34,26 +34,26 @@
   * See http://www.netlib.org/linalg/html_templates/node91.html for details on the storage scheme.
   *
   */
-template<typename _Scalar, int _Flags>
-struct ei_traits<SparseVector<_Scalar, _Flags> >
+template<typename _Scalar, int _Options>
+struct ei_traits<SparseVector<_Scalar, _Options> >
 {
   typedef _Scalar Scalar;
   enum {
-    IsColVector = _Flags & RowMajorBit ? 0 : 1,
+    IsColVector = _Options & RowMajorBit ? 0 : 1,
 
     RowsAtCompileTime = IsColVector ? Dynamic : 1,
     ColsAtCompileTime = IsColVector ? 1 : Dynamic,
     MaxRowsAtCompileTime = RowsAtCompileTime,
     MaxColsAtCompileTime = ColsAtCompileTime,
-    Flags = SparseBit | _Flags,
+    Flags = SparseBit | _Options,
     CoeffReadCost = NumTraits<Scalar>::ReadCost,
     SupportedAccessPatterns = InnerRandomAccessPattern
   };
 };
 
-template<typename _Scalar, int _Flags>
+template<typename _Scalar, int _Options>
 class SparseVector
-  : public SparseMatrixBase<SparseVector<_Scalar, _Flags> >
+  : public SparseMatrixBase<SparseVector<_Scalar, _Options> >
 {
   public:
     EIGEN_SPARSE_GENERIC_PUBLIC_INTERFACE(SparseVector)
@@ -124,7 +124,7 @@
     {
       ei_assert(outer==0);
     }
-    
+
     inline Scalar& insertBack(int outer, int inner)
     {
       ei_assert(outer==0);
@@ -183,7 +183,7 @@
       m_data.append(0, i);
       return m_data.value(m_data.size()-1);
     }
-    
+
     /** \deprecated use insert(int,int) */
     EIGEN_DEPRECATED Scalar& fillrand(int r, int c)
     {
@@ -196,11 +196,11 @@
     {
       return insert(i);
     }
-    
+
     /** \deprecated use finalize() */
     EIGEN_DEPRECATED void endFill() {}
     inline void finalize() {}
-    
+
     void prune(Scalar reference, RealScalar epsilon = precision<RealScalar>())
     {
       m_data.prune(reference,epsilon);
@@ -357,10 +357,13 @@
 
     /** Destructor */
     inline ~SparseVector() {}
+
+    /** Overloaded for performance */
+    Scalar sum() const;
 };
 
-template<typename Scalar, int _Flags>
-class SparseVector<Scalar,_Flags>::InnerIterator
+template<typename Scalar, int _Options>
+class SparseVector<Scalar,_Options>::InnerIterator
 {
   public:
     InnerIterator(const SparseVector& vec, int outer=0)
diff --git a/eigen2.pc.in b/eigen2.pc.in
new file mode 100644
index 0000000..b508a58
--- /dev/null
+++ b/eigen2.pc.in
@@ -0,0 +1,7 @@
+
+Name: Eigen2
+Description: A C++ template library for linear algebra: vectors, matrices, and related algorithms
+Requires:
+Version: ${EIGEN_VERSION_NUMBER}
+Libs:
+Cflags: -I${INCLUDE_INSTALL_DIR}
diff --git a/test/testsuite.cmake b/test/testsuite.cmake
index 9bbe01d..f3b0e41 100644
--- a/test/testsuite.cmake
+++ b/test/testsuite.cmake
@@ -39,7 +39,7 @@
 # VERSION=opensuse-11.1
 # WORK_DIR=/home/gael/Coding/eigen2/cdash
 # # get the last version of the script
-# svn cat svn://anonsvn.kde.org/home/kde/trunk/kdesupport/eigen2/test/testsuite.cmake > $WORK_DIR/testsuite.cmake
+# wget http://bitbucket.org/eigen/eigen2/raw/tip/test/testsuite.cmake -o $WORK_DIR/testsuite.cmake
 # COMMON="ctest -S $WORK_DIR/testsuite.cmake,EIGEN_WORK_DIR=$WORK_DIR,EIGEN_SITE=$SITE,EIGEN_MODE=$1,EIGEN_BUILD_STRING=$OS_VERSION-$ARCH"
 # $COMMON-gcc-3.4.6,EIGEN_CXX=g++-3.4
 # $COMMON-gcc-4.0.1,EIGEN_CXX=g++-4.0.1
@@ -132,8 +132,8 @@
 
 ## mandatory variables (the default should be ok in most cases):
 
-SET (CTEST_CVS_COMMAND "svn")
-SET (CTEST_CVS_CHECKOUT "${CTEST_CVS_COMMAND} co svn://anonsvn.kde.org/home/kde/trunk/kdesupport/eigen2 \"${CTEST_SOURCE_DIRECTORY}\"")
+SET (CTEST_CVS_COMMAND "hg")
+SET (CTEST_CVS_CHECKOUT "${CTEST_CVS_COMMAND} clone http://bitbucket.org/eigen/eigen2 \"${CTEST_SOURCE_DIRECTORY}\"")
 
 # which ctest command to use for running the dashboard
 SET (CTEST_COMMAND "${EIGEN_CMAKE_DIR}ctest -D ${EIGEN_MODE}")
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h b/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
index bc1bcce..7950d22 100644
--- a/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
+++ b/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
@@ -72,7 +72,8 @@
 
   PlainMatrixType num, den, U, V;
   PlainMatrixType Id = PlainMatrixType::Identity(M.rows(), M.cols());
-  RealScalar l1norm = M.cwise().abs().colwise().sum().maxCoeff();
+  typename ei_eval<Derived>::type Meval = M.eval();
+  RealScalar l1norm = Meval.cwise().abs().colwise().sum().maxCoeff();
   int squarings = 0;
   
   // Choose degree of Pade approximant, depending on norm of M
@@ -81,9 +82,9 @@
     // Use (3,3)-Pade
     const Scalar b[] = {120., 60., 12., 1.};
     PlainMatrixType M2;
-    M2 = (M * M).lazy();
+    M2 = (Meval * Meval).lazy();
     num = b[3]*M2 + b[1]*Id;
-    U = (M * num).lazy();
+    U = (Meval * num).lazy();
     V = b[2]*M2 + b[0]*Id;
 
   } else if (l1norm < 2.539398330063230e-001) {
@@ -91,10 +92,10 @@
     // Use (5,5)-Pade
     const Scalar b[] = {30240., 15120., 3360., 420., 30., 1.};
     PlainMatrixType M2, M4;
-    M2 = (M * M).lazy();
+    M2 = (Meval * Meval).lazy();
     M4 = (M2 * M2).lazy();
     num = b[5]*M4 + b[3]*M2 + b[1]*Id;
-    U = (M * num).lazy();
+    U = (Meval * num).lazy();
     V = b[4]*M4 + b[2]*M2 + b[0]*Id;
 
   } else if (l1norm < 9.504178996162932e-001) {
@@ -102,11 +103,11 @@
     // Use (7,7)-Pade
     const Scalar b[] = {17297280., 8648640., 1995840., 277200., 25200., 1512., 56., 1.};
     PlainMatrixType M2, M4, M6;
-    M2 = (M * M).lazy();
+    M2 = (Meval * Meval).lazy();
     M4 = (M2 * M2).lazy();
     M6 = (M4 * M2).lazy();
     num = b[7]*M6 + b[5]*M4 + b[3]*M2 + b[1]*Id;
-    U = (M * num).lazy();
+    U = (Meval * num).lazy();
     V = b[6]*M6 + b[4]*M4 + b[2]*M2 + b[0]*Id;
 
   } else if (l1norm < 2.097847961257068e+000) {
@@ -115,12 +116,12 @@
     const Scalar b[] = {17643225600., 8821612800., 2075673600., 302702400., 30270240.,
                          2162160., 110880., 3960., 90., 1.};
     PlainMatrixType M2, M4, M6, M8;
-    M2 = (M * M).lazy();
+    M2 = (Meval * Meval).lazy();
     M4 = (M2 * M2).lazy();
     M6 = (M4 * M2).lazy();
     M8 = (M6 * M2).lazy();
     num = b[9]*M8 + b[7]*M6 + b[5]*M4 + b[3]*M2 + b[1]*Id;
-    U = (M * num).lazy();
+    U = (Meval * num).lazy();
     V = b[8]*M8 + b[6]*M6 + b[4]*M4 + b[2]*M2 + b[0]*Id;
 
   } else {
@@ -135,7 +136,7 @@
     
     squarings = std::max(0, (int)ceil(log2(l1norm / maxnorm)));
     PlainMatrixType A, A2, A4, A6;
-    A = M / pow(Scalar(2), squarings);
+    A = Meval / pow(Scalar(2), squarings);
     A2 = (A * A).lazy();
     A4 = (A2 * A2).lazy();
     A6 = (A4 * A2).lazy();