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

 // IWYU pragma: private
 #include "./InternalHeaderCheck.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);

   constexpr bool transpose = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit);
   const Index outerEvaluationSize = (SrcEvaluatorType::Flags & RowMajorBit) ? src.rows() : src.cols();

   Index reserveSize = 0;
   for (Index j = 0; j < outerEvaluationSize; ++j)
     for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it) reserveSize++;

   if ((!transpose) && src.isRValue()) {
     // eval without temporary
     dst.resize(src.rows(), src.cols());
     dst.setZero();
     dst.reserve(reserveSize);
     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(reserveSize);
     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
       std::enable_if_t<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape, DenseShape>::value>
       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
       std::enable_if_t<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape, DenseShape>::value>
       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,                                   \
       std::enable_if_t<internal::is_same<typename internal::evaluator_traits<Lhs>::Shape, DenseShape>::value || \
                        internal::is_same<typename internal::evaluator_traits<Rhs>::Shape, DenseShape>::value>>  \
       : 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

	// IWYU pragma: private
	#include "./InternalHeaderCheck.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);

	constexpr bool transpose = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit);
	const Index outerEvaluationSize = (SrcEvaluatorType::Flags & RowMajorBit) ? src.rows() : src.cols();

	Index reserveSize = 0;
	for (Index j = 0; j < outerEvaluationSize; ++j)
	for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it) reserveSize++;

	if ((!transpose) && src.isRValue()) {
	// eval without temporary
	dst.resize(src.rows(), src.cols());
	dst.setZero();
	dst.reserve(reserveSize);
	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(reserveSize);
	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
	std::enable_if_t<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape, DenseShape>::value>
	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
	std::enable_if_t<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape, DenseShape>::value>
	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, \
	std::enable_if_t<internal::is_same<typename internal::evaluator_traits<Lhs>::Shape, DenseShape>::value \|\| \
	internal::is_same<typename internal::evaluator_traits<Rhs>::Shape, DenseShape>::value>> \
	: 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