| // 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) |
| { |
| // TODO use the evaluator mechanism |
| other.derived().evalTo(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) |
| { |
| // FIXME, by default sparse evaluation do not alias, so we should be able to bypass the generic call_assignment |
| internal::call_assignment/*_no_alias*/(derived(), other.derived()); |
| 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) |
| { |
| eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); |
| |
| typedef typename DstXprType::Index Index; |
| 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*/) |
| { |
| eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); |
| |
| 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()); |
| typedef typename SrcXprType::Index Index; |
| |
| 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()); |
| typedef typename SrcXprType::Index Index; |
| |
| 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); |
| } |
| }; |
| |
| } // end namespace internal |
| |
| } // end namespace Eigen |
| |
| #endif // EIGEN_SPARSEASSIGN_H |