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271 lines
11 KiB
C++
271 lines
11 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2008-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#ifndef EIGEN_SPARSEASSIGN_H
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#define EIGEN_SPARSEASSIGN_H
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namespace Eigen {
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template<typename Derived>
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template<typename OtherDerived>
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Derived& SparseMatrixBase<Derived>::operator=(const EigenBase<OtherDerived> &other)
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{
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internal::call_assignment_no_alias(derived(), other.derived());
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return derived();
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}
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template<typename Derived>
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template<typename OtherDerived>
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Derived& SparseMatrixBase<Derived>::operator=(const ReturnByValue<OtherDerived>& other)
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{
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// TODO use the evaluator mechanism
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other.evalTo(derived());
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return derived();
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}
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template<typename Derived>
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template<typename OtherDerived>
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inline Derived& SparseMatrixBase<Derived>::operator=(const SparseMatrixBase<OtherDerived>& other)
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{
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// by default sparse evaluation do not alias, so we can safely bypass the generic call_assignment routine
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internal::Assignment<Derived,OtherDerived,internal::assign_op<Scalar,typename OtherDerived::Scalar> >
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::run(derived(), other.derived(), internal::assign_op<Scalar,typename OtherDerived::Scalar>());
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return derived();
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}
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template<typename Derived>
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inline Derived& SparseMatrixBase<Derived>::operator=(const Derived& other)
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{
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internal::call_assignment_no_alias(derived(), other.derived());
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return derived();
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}
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namespace internal {
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template<>
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struct storage_kind_to_evaluator_kind<Sparse> {
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typedef IteratorBased Kind;
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};
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template<>
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struct storage_kind_to_shape<Sparse> {
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typedef SparseShape Shape;
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};
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struct Sparse2Sparse {};
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struct Sparse2Dense {};
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template<> struct AssignmentKind<SparseShape, SparseShape> { typedef Sparse2Sparse Kind; };
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template<> struct AssignmentKind<SparseShape, SparseTriangularShape> { typedef Sparse2Sparse Kind; };
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template<> struct AssignmentKind<DenseShape, SparseShape> { typedef Sparse2Dense Kind; };
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template<> struct AssignmentKind<DenseShape, SparseTriangularShape> { typedef Sparse2Dense Kind; };
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template<typename DstXprType, typename SrcXprType>
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void assign_sparse_to_sparse(DstXprType &dst, const SrcXprType &src)
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{
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typedef typename DstXprType::Scalar Scalar;
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typedef internal::evaluator<DstXprType> DstEvaluatorType;
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typedef internal::evaluator<SrcXprType> SrcEvaluatorType;
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SrcEvaluatorType srcEvaluator(src);
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const bool transpose = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit);
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const Index outerEvaluationSize = (SrcEvaluatorType::Flags&RowMajorBit) ? src.rows() : src.cols();
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if ((!transpose) && src.isRValue())
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{
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// eval without temporary
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dst.resize(src.rows(), src.cols());
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dst.setZero();
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dst.reserve((std::min)(src.rows()*src.cols(), (std::max)(src.rows(),src.cols())*2));
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for (Index j=0; j<outerEvaluationSize; ++j)
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{
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dst.startVec(j);
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for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
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{
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Scalar v = it.value();
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dst.insertBackByOuterInner(j,it.index()) = v;
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}
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}
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dst.finalize();
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}
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else
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{
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// eval through a temporary
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eigen_assert(( ((internal::traits<DstXprType>::SupportedAccessPatterns & OuterRandomAccessPattern)==OuterRandomAccessPattern) ||
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(!((DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit)))) &&
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"the transpose operation is supposed to be handled in SparseMatrix::operator=");
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enum { Flip = (DstEvaluatorType::Flags & RowMajorBit) != (SrcEvaluatorType::Flags & RowMajorBit) };
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DstXprType temp(src.rows(), src.cols());
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temp.reserve((std::min)(src.rows()*src.cols(), (std::max)(src.rows(),src.cols())*2));
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for (Index j=0; j<outerEvaluationSize; ++j)
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{
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temp.startVec(j);
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for (typename SrcEvaluatorType::InnerIterator it(srcEvaluator, j); it; ++it)
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{
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Scalar v = it.value();
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temp.insertBackByOuterInner(Flip?it.index():j,Flip?j:it.index()) = v;
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}
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}
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temp.finalize();
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dst = temp.markAsRValue();
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}
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}
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// Generic Sparse to Sparse assignment
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template< typename DstXprType, typename SrcXprType, typename Functor>
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struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Sparse>
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{
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static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
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{
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assign_sparse_to_sparse(dst.derived(), src.derived());
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}
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};
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// Generic Sparse to Dense assignment
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template< typename DstXprType, typename SrcXprType, typename Functor, typename Weak>
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struct Assignment<DstXprType, SrcXprType, Functor, Sparse2Dense, Weak>
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{
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static void run(DstXprType &dst, const SrcXprType &src, const Functor &func)
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{
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if(internal::is_same<Functor,internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> >::value)
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dst.setZero();
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internal::evaluator<SrcXprType> srcEval(src);
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resize_if_allowed(dst, src, func);
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internal::evaluator<DstXprType> dstEval(dst);
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const Index outerEvaluationSize = (internal::evaluator<SrcXprType>::Flags&RowMajorBit) ? src.rows() : src.cols();
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for (Index j=0; j<outerEvaluationSize; ++j)
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for (typename internal::evaluator<SrcXprType>::InnerIterator i(srcEval,j); i; ++i)
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func.assignCoeff(dstEval.coeffRef(i.row(),i.col()), i.value());
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}
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};
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// Specialization for dense ?= dense +/- sparse and dense ?= sparse +/- dense
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template<typename DstXprType, typename Func1, typename Func2>
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struct assignment_from_dense_op_sparse
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{
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template<typename SrcXprType, typename InitialFunc>
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static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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void run(DstXprType &dst, const SrcXprType &src, const InitialFunc& /*func*/)
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{
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#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
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EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN
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#endif
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call_assignment_no_alias(dst, src.lhs(), Func1());
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call_assignment_no_alias(dst, src.rhs(), Func2());
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}
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// Specialization for dense1 = sparse + dense2; -> dense1 = dense2; dense1 += sparse;
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template<typename Lhs, typename Rhs, typename Scalar>
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static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
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run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_sum_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
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const internal::assign_op<typename DstXprType::Scalar,Scalar>& /*func*/)
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{
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#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
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EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN
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#endif
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// Apply the dense matrix first, then the sparse one.
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call_assignment_no_alias(dst, src.rhs(), Func1());
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call_assignment_no_alias(dst, src.lhs(), Func2());
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}
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// Specialization for dense1 = sparse - dense2; -> dense1 = -dense2; dense1 += sparse;
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template<typename Lhs, typename Rhs, typename Scalar>
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static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
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typename internal::enable_if<internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type
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run(DstXprType &dst, const CwiseBinaryOp<internal::scalar_difference_op<Scalar,Scalar>, const Lhs, const Rhs> &src,
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const internal::assign_op<typename DstXprType::Scalar,Scalar>& /*func*/)
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{
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#ifdef EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
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EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN
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#endif
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// Apply the dense matrix first, then the sparse one.
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call_assignment_no_alias(dst, -src.rhs(), Func1());
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call_assignment_no_alias(dst, src.lhs(), add_assign_op<typename DstXprType::Scalar,typename Lhs::Scalar>());
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}
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};
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#define EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(ASSIGN_OP,BINOP,ASSIGN_OP2) \
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template< typename DstXprType, typename Lhs, typename Rhs, typename Scalar> \
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struct Assignment<DstXprType, CwiseBinaryOp<internal::BINOP<Scalar,Scalar>, const Lhs, const Rhs>, internal::ASSIGN_OP<typename DstXprType::Scalar,Scalar>, \
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Sparse2Dense, \
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typename internal::enable_if< internal::is_same<typename internal::evaluator_traits<Lhs>::Shape,DenseShape>::value \
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|| internal::is_same<typename internal::evaluator_traits<Rhs>::Shape,DenseShape>::value>::type> \
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: assignment_from_dense_op_sparse<DstXprType, internal::ASSIGN_OP<typename DstXprType::Scalar,typename Lhs::Scalar>, internal::ASSIGN_OP2<typename DstXprType::Scalar,typename Rhs::Scalar> > \
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{}
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EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op, scalar_sum_op,add_assign_op);
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EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_sum_op,add_assign_op);
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EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_sum_op,sub_assign_op);
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EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(assign_op, scalar_difference_op,sub_assign_op);
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EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(add_assign_op,scalar_difference_op,sub_assign_op);
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EIGEN_CATCH_ASSIGN_DENSE_OP_SPARSE(sub_assign_op,scalar_difference_op,add_assign_op);
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// Specialization for "dst = dec.solve(rhs)"
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// NOTE we need to specialize it for Sparse2Sparse to avoid ambiguous specialization error
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template<typename DstXprType, typename DecType, typename RhsType, typename Scalar>
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struct Assignment<DstXprType, Solve<DecType,RhsType>, internal::assign_op<Scalar,Scalar>, Sparse2Sparse>
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{
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typedef Solve<DecType,RhsType> SrcXprType;
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static void run(DstXprType &dst, const SrcXprType &src, const internal::assign_op<Scalar,Scalar> &)
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{
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Index dstRows = src.rows();
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Index dstCols = src.cols();
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if((dst.rows()!=dstRows) || (dst.cols()!=dstCols))
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dst.resize(dstRows, dstCols);
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src.dec()._solve_impl(src.rhs(), dst);
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}
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};
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struct Diagonal2Sparse {};
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template<> struct AssignmentKind<SparseShape,DiagonalShape> { typedef Diagonal2Sparse Kind; };
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template< typename DstXprType, typename SrcXprType, typename Functor>
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struct Assignment<DstXprType, SrcXprType, Functor, Diagonal2Sparse>
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{
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typedef typename DstXprType::StorageIndex StorageIndex;
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typedef typename DstXprType::Scalar Scalar;
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template<int Options, typename AssignFunc>
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static void run(SparseMatrix<Scalar,Options,StorageIndex> &dst, const SrcXprType &src, const AssignFunc &func)
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{ dst.assignDiagonal(src.diagonal(), func); }
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template<typename DstDerived>
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static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
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{ dst.derived().diagonal() = src.diagonal(); }
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template<typename DstDerived>
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static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::add_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
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{ dst.derived().diagonal() += src.diagonal(); }
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template<typename DstDerived>
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static void run(SparseMatrixBase<DstDerived> &dst, const SrcXprType &src, const internal::sub_assign_op<typename DstXprType::Scalar,typename SrcXprType::Scalar> &/*func*/)
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{ dst.derived().diagonal() -= src.diagonal(); }
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};
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} // end namespace internal
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} // end namespace Eigen
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#endif // EIGEN_SPARSEASSIGN_H
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