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// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2015 Gael Guennebaud // // 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_SPARSEPRODUCT_H #define EIGEN_SPARSEPRODUCT_H // IWYU pragma: private #include "./InternalHeaderCheck.h" namespace Eigen { /** \returns an expression of the product of two sparse matrices. * By default a conservative product preserving the symbolic non zeros is performed. * The automatic pruning of the small values can be achieved by calling the pruned() function * in which case a totally different product algorithm is employed: * \code * C = (A*B).pruned(); // suppress numerical zeros (exact) * C = (A*B).pruned(ref); * C = (A*B).pruned(ref,epsilon); * \endcode * where \c ref is a meaningful non zero reference value. * */ template template inline const Product SparseMatrixBase::operator*( const SparseMatrixBase& other) const { return Product(derived(), other.derived()); } namespace internal { // sparse * sparse template struct generic_product_impl { template static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { evalTo(dst, lhs, rhs, typename evaluator_traits::Shape()); } // dense += sparse * sparse template static void addTo(Dest& dst, const ActualLhs& lhs, const Rhs& rhs, std::enable_if_t::Shape, DenseShape>::value, int*>* = 0) { typedef typename nested_eval::type LhsNested; typedef typename nested_eval::type RhsNested; LhsNested lhsNested(lhs); RhsNested rhsNested(rhs); internal::sparse_sparse_to_dense_product_selector, remove_all_t, Dest>::run( lhsNested, rhsNested, dst); } // dense -= sparse * sparse template static void subTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, std::enable_if_t::Shape, DenseShape>::value, int*>* = 0) { addTo(dst, -lhs, rhs); } protected: // sparse = sparse * sparse template static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, SparseShape) { typedef typename nested_eval::type LhsNested; typedef typename nested_eval::type RhsNested; LhsNested lhsNested(lhs); RhsNested rhsNested(rhs); internal::conservative_sparse_sparse_product_selector, remove_all_t, Dest>::run( lhsNested, rhsNested, dst); } // dense = sparse * sparse template static void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, DenseShape) { dst.setZero(); addTo(dst, lhs, rhs); } }; // sparse * sparse-triangular template struct generic_product_impl : public generic_product_impl {}; // sparse-triangular * sparse template struct generic_product_impl : public generic_product_impl {}; // dense = sparse-product (can be sparse*sparse, sparse*perm, etc.) template struct Assignment< DstXprType, Product, internal::assign_op::Scalar>, Sparse2Dense> { typedef Product SrcXprType; static void run(DstXprType& dst, const SrcXprType& src, const internal::assign_op&) { Index dstRows = src.rows(); Index dstCols = src.cols(); if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols); generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); } }; // dense += sparse-product (can be sparse*sparse, sparse*perm, etc.) template struct Assignment< DstXprType, Product, internal::add_assign_op::Scalar>, Sparse2Dense> { typedef Product SrcXprType; static void run(DstXprType& dst, const SrcXprType& src, const internal::add_assign_op&) { generic_product_impl::addTo(dst, src.lhs(), src.rhs()); } }; // dense -= sparse-product (can be sparse*sparse, sparse*perm, etc.) template struct Assignment< DstXprType, Product, internal::sub_assign_op::Scalar>, Sparse2Dense> { typedef Product SrcXprType; static void run(DstXprType& dst, const SrcXprType& src, const internal::sub_assign_op&) { generic_product_impl::subTo(dst, src.lhs(), src.rhs()); } }; template struct unary_evaluator >, IteratorBased> : public evaluator::PlainObject> { typedef SparseView > XprType; typedef typename XprType::PlainObject PlainObject; typedef evaluator Base; explicit unary_evaluator(const XprType& xpr) : m_result(xpr.rows(), xpr.cols()) { using std::abs; internal::construct_at(this, m_result); typedef typename nested_eval::type LhsNested; typedef typename nested_eval::type RhsNested; LhsNested lhsNested(xpr.nestedExpression().lhs()); RhsNested rhsNested(xpr.nestedExpression().rhs()); internal::sparse_sparse_product_with_pruning_selector, remove_all_t, PlainObject>::run(lhsNested, rhsNested, m_result, abs(xpr.reference()) * xpr.epsilon()); } protected: PlainObject m_result; }; } // end namespace internal // sparse matrix = sparse-product (can be sparse*sparse, sparse*perm, etc.) template template SparseMatrix& SparseMatrix::operator=( const Product& src) { // std::cout << "in Assignment : " << DstOptions << "\n"; SparseMatrix dst(src.rows(), src.cols()); internal::generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); this->swap(dst); return *this; } } // end namespace Eigen #endif // EIGEN_SPARSEPRODUCT_H