Eigen/src/SparseCore/SparseAssign.h - eigen - Git at Google

 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2008-2014 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_SPARSEASSIGN_H
 #define EIGEN_SPARSEASSIGN_H

 namespace Eigen {

 template<typename Derived>
 template<typename OtherDerived>
 Derived& SparseMatrixBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
 {
   internal::call_assignment_no_alias(derived(), other.derived());
   return derived();
 }

 template<typename Derived>
 template<typename OtherDerived>
 Derived& SparseMatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
 {
   // TODO use the evaluator mechanism
   other.evalTo(derived());
   return derived();
 }

 template<typename Derived>
 template<typename OtherDerived>
 inline Derived& SparseMatrixBase<Derived>::operator=(const SparseMatrixBase<OtherDerived>& other)
 {
   // by default sparse evaluation do not alias, so we can safely bypass the generic call_assignment routine
   internal::Assignment<Derived,OtherDerived,internal::assign_op<Scalar,typename OtherDerived::Scalar> >
           ::run(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
   return derived();
 }

 template<typename Derived>
 inline Derived& SparseMatrixBase<Derived>::operator=(const Derived& other)
 {
   internal::call_assignment_no_alias(derived(), other.derived());
   return derived();
 }

 namespace internal {

 template<>
 struct storage_kind_to_evaluator_kind<Sparse> {
   typedef IteratorBased Kind;
 };

 template<>
 struct storage_kind_to_shape<Sparse> {
   typedef SparseShape Shape;
 };

 struct Sparse2Sparse {};
 struct Sparse2Dense  {};

 template<> struct AssignmentKind<SparseShape, SparseShape>           { typedef Sparse2Sparse Kind; };
 template<> struct AssignmentKind<SparseShape, SparseTriangularShape> { typedef Sparse2Sparse Kind; };
 template<> struct AssignmentKind<DenseShape,  SparseShape>           { typedef Sparse2Dense  Kind; };
 template<> struct AssignmentKind<DenseShape,  SparseTriangularShape> { typedef Sparse2Dense  Kind; };


 template<typename DstXprType, typename SrcXprType>
 void assign_sparse_to_sparse(DstXprType &dst, const SrcXprType &src)
 {
   typedef typename DstXprType::Scalar Scalar;
   typedef internal::evaluator<DstXprType> DstEvaluatorType;
   typedef internal::evaluator<SrcXprType> SrcEvaluatorType;

   SrcEvaluatorType srcEvaluator(src);

   const bool transpose = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit);
   const Index outerEvaluationSize = (SrcEvaluatorType::Flags&RowMajorBit) ? src.rows() : src.cols();
   if ((!transpose) && src.isRValue())
   {
     // eval without temporary
     dst.resize(src.rows(), src.cols());
     dst.setZero();
     dst.reserve((std::min)(src.rows()*src.cols(), (std::max)(src.rows(),src.cols())*2));
     for (Index j=0; j<outerEvaluationSize; ++j)
     {
       dst.startVec(j);
       for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
       {
         Scalar v = it.value();
         dst.insertBackByOuterInner(j,it.index()) = v;
       }
     }
     dst.finalize();
   }
   else
   {
     // eval through a temporary
     eigen_assert(( ((internal::traits<DstXprType>::SupportedAccessPatterns & OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
               (!((DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit)))) &&
               "the transpose operation is supposed to be handled in SparseMatrix::operator=");

     enum { Flip = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit) };


     DstXprType temp(src.rows(), src.cols());

     temp.reserve((std::min)(src.rows()*src.cols(), (std::max)(src.rows(),src.cols())*2));
     for (Index j=0; j<outerEvaluationSize; ++j)
     {
       temp.startVec(j);
       for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
       {
         Scalar v = it.value();
         temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
       }
     }
     temp.finalize();

     dst = temp.markAsRValue();
   }
 }

 // Generic Sparse to Sparse assignment
 template< typename DstXprType, typename SrcXprType, typename Functor>
 struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Sparse>
 {
   static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
   {
     assign_sparse_to_sparse(dst.derived(), src.derived());
   }
 };

 // Generic Sparse to Dense assignment
 template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
 struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Dense, Weak>
 {
   static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
   {
     if(internal::is_same<Functor,internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> >::value)
       dst.setZero();

     internal::evaluator<SrcXprType> srcEval(src);
     resize_if_allowed(dst, src, func);
     internal::evaluator<DstXprType> dstEval(dst);

     const Index outerEvaluationSize = (internal::evaluator<SrcXprType>::Flags&RowMajorBit) ? src.rows() : src.cols();
     for (Index j=0; j<outerEvaluationSize; ++j)
       for (typename internal::evaluator<SrcXprType>::InnerIterator i(srcEval,j); i; ++i)
         func.assignCoeff(dstEval.coeffRef(i.row(),i.col()), i.value());
   }
 };

 // Specialization for dense ?= dense +/- sparse and dense ?= sparse +/- dense
 template<typename DstXprType, typename Func1, typename Func2>
 struct assignment_from_dense_op_sparse
 {
   template<typename SrcXprType, typename InitialFunc>
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
   void run(DstXprType &dst, const SrcXprType &src, const InitialFunc& /*func*/)
   {
     #ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
     EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
     #endif

     call_assignment_no_alias(dst, src.lhs(), Func1());
     call_assignment_no_alias(dst, src.rhs(), Func2());
   }

   // Specialization for dense1 = sparse + dense2; -> dense1 = dense2; dense1 += sparse;
   template<typename Lhs, typename Rhs, typename Scalar>
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
   typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
   run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_sum_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
       const internal::assign_op<typename DstXprType::Scalar,Scalar>& /*func*/)
   {
     #ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
     EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
     #endif

     // Apply the dense matrix first, then the sparse one.
     call_assignment_no_alias(dst, src.rhs(), Func1());
     call_assignment_no_alias(dst, src.lhs(), Func2());
   }

   // Specialization for dense1 = sparse - dense2; -> dense1 = -dense2; dense1 += sparse;
   template<typename Lhs, typename Rhs, typename Scalar>
   static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
   typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
   run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_difference_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
       const internal::assign_op<typename DstXprType::Scalar,Scalar>& /*func*/)
   {
     #ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
     EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
     #endif

     // Apply the dense matrix first, then the sparse one.
     call_assignment_no_alias(dst, -src.rhs(), Func1());
     call_assignment_no_alias(dst,  src.lhs(), add_assign_op<typename DstXprType::Scalar,typename Lhs::Scalar>());
   }
 };

 #define EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(ASSIGN_OP,BINOP,ASSIGN_OP2) \
   template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar> \
   struct Assignment<DstXprType, CwiseBinaryOp<internal::BINOP<Scalar,Scalar>, const Lhs, const Rhs>, internal::ASSIGN_OP<typename DstXprType::Scalar,Scalar>, \
                     Sparse2Dense, \
                     typename internal::enable_if<   internal::is_same<typename internal::evaluator_traits<Lhs>::Shape,DenseShape>::value \
                                                  || internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type> \
     : assignment_from_dense_op_sparse<DstXprType, internal::ASSIGN_OP<typename DstXprType::Scalar,typename Lhs::Scalar>, internal::ASSIGN_OP2<typename DstXprType::Scalar,typename Rhs::Scalar> > \
   {}

 EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op,    scalar_sum_op,add_assign_op);
 EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_sum_op,add_assign_op);
 EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_sum_op,sub_assign_op);

 EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op,    scalar_difference_op,sub_assign_op);
 EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_difference_op,sub_assign_op);
 EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_difference_op,add_assign_op);


 // Specialization for "dst = dec.solve(rhs)"
 // NOTE we need to specialize it for Sparse2Sparse to avoid ambiguous specialization error
 template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
 struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar,Scalar>, Sparse2Sparse>
 {
   typedef Solve<DecType,RhsType> SrcXprType;
   static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
   {
     Index dstRows = src.rows();
     Index dstCols = src.cols();
     if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
       dst.resize(dstRows, dstCols);

     src.dec()._solve_impl(src.rhs(), dst);
   }
 };

 struct Diagonal2Sparse {};

 template<> struct AssignmentKind<SparseShape,DiagonalShape> { typedef Diagonal2Sparse Kind; };

 template< typename DstXprType, typename SrcXprType, typename Functor>
 struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Sparse>
 {
   typedef typename DstXprType::StorageIndex StorageIndex;
   typedef typename DstXprType::Scalar Scalar;

   template<int Options, typename AssignFunc>
   static void run(SparseMatrix<Scalar,Options,StorageIndex> &dst, const SrcXprType &src, const AssignFunc &func)
   { dst.assignDiagonal(src.diagonal(), func); }

   template<typename DstDerived>
   static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
   { dst.derived().diagonal() = src.diagonal(); }

   template<typename DstDerived>
   static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
   { dst.derived().diagonal() += src.diagonal(); }

   template<typename DstDerived>
   static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
   { dst.derived().diagonal() -= src.diagonal(); }
 };
 } // end namespace internal

 } // end namespace Eigen

 #endif // EIGEN_SPARSEASSIGN_H
	// This file is part of Eigen, a lightweight C++ template library
	// for linear algebra.
	//
	// Copyright (C) 2008-2014 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_SPARSEASSIGN_H
	#define EIGEN_SPARSEASSIGN_H

	namespace Eigen {

	template<typename Derived>
	template<typename OtherDerived>
	Derived& SparseMatrixBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
	{
	internal::call_assignment_no_alias(derived(), other.derived());
	return derived();
	}

	template<typename Derived>
	template<typename OtherDerived>
	Derived& SparseMatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
	{
	// TODO use the evaluator mechanism
	other.evalTo(derived());
	return derived();
	}

	template<typename Derived>
	template<typename OtherDerived>
	inline Derived& SparseMatrixBase<Derived>::operator=(const SparseMatrixBase<OtherDerived>& other)
	{
	// by default sparse evaluation do not alias, so we can safely bypass the generic call_assignment routine
	internal::Assignment<Derived,OtherDerived,internal::assign_op<Scalar,typename OtherDerived::Scalar> >
	::run(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
	return derived();
	}

	template<typename Derived>
	inline Derived& SparseMatrixBase<Derived>::operator=(const Derived& other)
	{
	internal::call_assignment_no_alias(derived(), other.derived());
	return derived();
	}

	namespace internal {

	template<>
	struct storage_kind_to_evaluator_kind<Sparse> {
	typedef IteratorBased Kind;
	};

	template<>
	struct storage_kind_to_shape<Sparse> {
	typedef SparseShape Shape;
	};

	struct Sparse2Sparse {};
	struct Sparse2Dense {};

	template<> struct AssignmentKind<SparseShape, SparseShape> { typedef Sparse2Sparse Kind; };
	template<> struct AssignmentKind<SparseShape, SparseTriangularShape> { typedef Sparse2Sparse Kind; };
	template<> struct AssignmentKind<DenseShape, SparseShape> { typedef Sparse2Dense Kind; };
	template<> struct AssignmentKind<DenseShape, SparseTriangularShape> { typedef Sparse2Dense Kind; };


	template<typename DstXprType, typename SrcXprType>
	void assign_sparse_to_sparse(DstXprType &dst, const SrcXprType &src)
	{
	typedef typename DstXprType::Scalar Scalar;
	typedef internal::evaluator<DstXprType> DstEvaluatorType;
	typedef internal::evaluator<SrcXprType> SrcEvaluatorType;

	SrcEvaluatorType srcEvaluator(src);

	const bool transpose = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit);
	const Index outerEvaluationSize = (SrcEvaluatorType::Flags&RowMajorBit) ? src.rows() : src.cols();
	if ((!transpose) && src.isRValue())
	{
	// eval without temporary
	dst.resize(src.rows(), src.cols());
	dst.setZero();
	dst.reserve((std::min)(src.rows()src.cols(), (std::max)(src.rows(),src.cols())2));
	for (Index j=0; j<outerEvaluationSize; ++j)
	{
	dst.startVec(j);
	for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
	{
	Scalar v = it.value();
	dst.insertBackByOuterInner(j,it.index()) = v;
	}
	}
	dst.finalize();
	}
	else
	{
	// eval through a temporary
	eigen_assert(( ((internal::traits<DstXprType>::SupportedAccessPatterns & OuterRandomAccessPattern)==OuterRandomAccessPattern) \|\|
	(!((DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit)))) &&
	"the transpose operation is supposed to be handled in SparseMatrix::operator=");

	enum { Flip = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit) };


	DstXprType temp(src.rows(), src.cols());

	temp.reserve((std::min)(src.rows()src.cols(), (std::max)(src.rows(),src.cols())2));
	for (Index j=0; j<outerEvaluationSize; ++j)
	{
	temp.startVec(j);
	for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
	{
	Scalar v = it.value();
	temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
	}
	}
	temp.finalize();

	dst = temp.markAsRValue();
	}
	}

	// Generic Sparse to Sparse assignment
	template< typename DstXprType, typename SrcXprType, typename Functor>
	struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Sparse>
	{
	static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/func/)
	{
	assign_sparse_to_sparse(dst.derived(), src.derived());
	}
	};

	// Generic Sparse to Dense assignment
	template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
	struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Dense, Weak>
	{
	static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
	{
	if(internal::is_same<Functor,internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> >::value)
	dst.setZero();

	internal::evaluator<SrcXprType> srcEval(src);
	resize_if_allowed(dst, src, func);
	internal::evaluator<DstXprType> dstEval(dst);

	const Index outerEvaluationSize = (internal::evaluator<SrcXprType>::Flags&RowMajorBit) ? src.rows() : src.cols();
	for (Index j=0; j<outerEvaluationSize; ++j)
	for (typename internal::evaluator<SrcXprType>::InnerIterator i(srcEval,j); i; ++i)
	func.assignCoeff(dstEval.coeffRef(i.row(),i.col()), i.value());
	}
	};

	// Specialization for dense ?= dense +/- sparse and dense ?= sparse +/- dense
	template<typename DstXprType, typename Func1, typename Func2>
	struct assignment_from_dense_op_sparse
	{
	template<typename SrcXprType, typename InitialFunc>
	static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
	void run(DstXprType &dst, const SrcXprType &src, const InitialFunc& /func/)
	{
	#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
	EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
	#endif

	call_assignment_no_alias(dst, src.lhs(), Func1());
	call_assignment_no_alias(dst, src.rhs(), Func2());
	}

	// Specialization for dense1 = sparse + dense2; -> dense1 = dense2; dense1 += sparse;
	template<typename Lhs, typename Rhs, typename Scalar>
	static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
	typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
	run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_sum_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
	const internal::assign_op<typename DstXprType::Scalar,Scalar>& /func/)
	{
	#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
	EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
	#endif

	// Apply the dense matrix first, then the sparse one.
	call_assignment_no_alias(dst, src.rhs(), Func1());
	call_assignment_no_alias(dst, src.lhs(), Func2());
	}

	// Specialization for dense1 = sparse - dense2; -> dense1 = -dense2; dense1 += sparse;
	template<typename Lhs, typename Rhs, typename Scalar>
	static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
	typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
	run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_difference_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
	const internal::assign_op<typename DstXprType::Scalar,Scalar>& /func/)
	{
	#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
	EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
	#endif

	// Apply the dense matrix first, then the sparse one.
	call_assignment_no_alias(dst, -src.rhs(), Func1());
	call_assignment_no_alias(dst, src.lhs(), add_assign_op<typename DstXprType::Scalar,typename Lhs::Scalar>());
	}
	};

	#define EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(ASSIGN_OP,BINOP,ASSIGN_OP2) \
	template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar> \
	struct Assignment<DstXprType, CwiseBinaryOp<internal::BINOP<Scalar,Scalar>, const Lhs, const Rhs>, internal::ASSIGN_OP<typename DstXprType::Scalar,Scalar>, \
	Sparse2Dense, \
	typename internal::enable_if< internal::is_same<typename internal::evaluator_traits<Lhs>::Shape,DenseShape>::value \
	\|\| internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type> \
	: assignment_from_dense_op_sparse<DstXprType, internal::ASSIGN_OP<typename DstXprType::Scalar,typename Lhs::Scalar>, internal::ASSIGN_OP2<typename DstXprType::Scalar,typename Rhs::Scalar> > \
	{}

	EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op, scalar_sum_op,add_assign_op);
	EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_sum_op,add_assign_op);
	EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_sum_op,sub_assign_op);

	EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op, scalar_difference_op,sub_assign_op);
	EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_difference_op,sub_assign_op);
	EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_difference_op,add_assign_op);


	// Specialization for "dst = dec.solve(rhs)"
	// NOTE we need to specialize it for Sparse2Sparse to avoid ambiguous specialization error
	template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
	struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar,Scalar>, Sparse2Sparse>
	{
	typedef Solve<DecType,RhsType> SrcXprType;
	static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
	{
	Index dstRows = src.rows();
	Index dstCols = src.cols();
	if((dst.rows()!=dstRows) \|\| (dst.cols()!=dstCols))
	dst.resize(dstRows, dstCols);

	src.dec()._solve_impl(src.rhs(), dst);
	}
	};

	struct Diagonal2Sparse {};

	template<> struct AssignmentKind<SparseShape,DiagonalShape> { typedef Diagonal2Sparse Kind; };

	template< typename DstXprType, typename SrcXprType, typename Functor>
	struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Sparse>
	{
	typedef typename DstXprType::StorageIndex StorageIndex;
	typedef typename DstXprType::Scalar Scalar;

	template<int Options, typename AssignFunc>
	static void run(SparseMatrix<Scalar,Options,StorageIndex> &dst, const SrcXprType &src, const AssignFunc &func)
	{ dst.assignDiagonal(src.diagonal(), func); }

	template<typename DstDerived>
	static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/func/)
	{ dst.derived().diagonal() = src.diagonal(); }

	template<typename DstDerived>
	static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/func/)
	{ dst.derived().diagonal() += src.diagonal(); }

	template<typename DstDerived>
	static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/func/)
	{ dst.derived().diagonal() -= src.diagonal(); }
	};
	} // end namespace internal

	} // end namespace Eigen

	#endif // EIGEN_SPARSEASSIGN_H