|  | // 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> > | 
|  | ::run(derived(), other.derived(), internal::assign_op<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<typename DstXprType, typename SrcXprType> | 
|  | void assign_sparse_to_sparse(DstXprType &dst, const SrcXprType &src) | 
|  | { | 
|  | typedef typename DstXprType::Scalar Scalar; | 
|  | typedef typename internal::evaluator<DstXprType>::type DstEvaluatorType; | 
|  | typedef typename internal::evaluator<SrcXprType>::type 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::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::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, typename Scalar> | 
|  | struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Sparse, Scalar> | 
|  | { | 
|  | static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &/*func*/) | 
|  | { | 
|  | assign_sparse_to_sparse(dst.derived(), src.derived()); | 
|  | } | 
|  | }; | 
|  |  | 
|  | // Sparse to Dense assignment | 
|  | template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar> | 
|  | struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Dense, Scalar> | 
|  | { | 
|  | static void run(DstXprType &dst, const SrcXprType &src, const Functor &func) | 
|  | { | 
|  | eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); | 
|  |  | 
|  | typename internal::evaluator<SrcXprType>::type srcEval(src); | 
|  | typename internal::evaluator<DstXprType>::type 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()); | 
|  | } | 
|  | }; | 
|  |  | 
|  | template< typename DstXprType, typename SrcXprType, typename Scalar> | 
|  | struct Assignment<DstXprType, SrcXprType, internal::assign_op<typename DstXprType::Scalar>, Sparse2Dense, Scalar> | 
|  | { | 
|  | static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &) | 
|  | { | 
|  | eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); | 
|  |  | 
|  | dst.setZero(); | 
|  | typename internal::evaluator<SrcXprType>::type srcEval(src); | 
|  | typename internal::evaluator<DstXprType>::type 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) | 
|  | dstEval.coeffRef(i.row(),i.col()) = i.value(); | 
|  | } | 
|  | }; | 
|  |  | 
|  | // 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>, Sparse2Sparse, Scalar> | 
|  | { | 
|  | typedef Solve<DecType,RhsType> SrcXprType; | 
|  | static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar> &) | 
|  | { | 
|  | src.dec()._solve_impl(src.rhs(), dst); | 
|  | } | 
|  | }; | 
|  |  | 
|  | struct Diagonal2Sparse {}; | 
|  |  | 
|  | template<> struct AssignmentKind<SparseShape,DiagonalShape> { typedef Diagonal2Sparse Kind; }; | 
|  |  | 
|  | template< typename DstXprType, typename SrcXprType, typename Functor, typename Scalar> | 
|  | struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Sparse, Scalar> | 
|  | { | 
|  | typedef typename DstXprType::StorageIndex StorageIndex; | 
|  | typedef Array<StorageIndex,Dynamic,1> ArrayXI; | 
|  | typedef Array<Scalar,Dynamic,1> ArrayXS; | 
|  | template<int Options> | 
|  | static void run(SparseMatrix<Scalar,Options,StorageIndex> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &/*func*/) | 
|  | { | 
|  | Index size = src.diagonal().size(); | 
|  | dst.makeCompressed(); | 
|  | dst.resizeNonZeros(size); | 
|  | Map<ArrayXI>(dst.innerIndexPtr(), size).setLinSpaced(0,StorageIndex(size)-1); | 
|  | Map<ArrayXI>(dst.outerIndexPtr(), size+1).setLinSpaced(0,StorageIndex(size)); | 
|  | Map<ArrayXS>(dst.valuePtr(), size) = src.diagonal(); | 
|  | } | 
|  |  | 
|  | template<typename DstDerived> | 
|  | static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar> &/*func*/) | 
|  | { | 
|  | dst.diagonal() = src.diagonal(); | 
|  | } | 
|  |  | 
|  | static void run(DstXprType &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar> &/*func*/) | 
|  | { dst.diagonal() += src.diagonal(); } | 
|  |  | 
|  | static void run(DstXprType &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar> &/*func*/) | 
|  | { dst.diagonal() -= src.diagonal(); } | 
|  | }; | 
|  | } // end namespace internal | 
|  |  | 
|  | } // end namespace Eigen | 
|  |  | 
|  | #endif // EIGEN_SPARSEASSIGN_H |