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Diffstat (limited to 'Eigen/src/SparseCore/SparseAssign.h')
| -rw-r--r-- | Eigen/src/SparseCore/SparseAssign.h | 192 |
1 files changed, 192 insertions, 0 deletions
diff --git a/Eigen/src/SparseCore/SparseAssign.h b/Eigen/src/SparseCore/SparseAssign.h new file mode 100644 index 000000000..97c079d3f --- /dev/null +++ b/Eigen/src/SparseCore/SparseAssign.h @@ -0,0 +1,192 @@ +// 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 |