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169 lines
7.2 KiB
C++
169 lines
7.2 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) 2012 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_SPARSE_PERMUTATION_H
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#define EIGEN_SPARSE_PERMUTATION_H
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// This file implements sparse * permutation products
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namespace Eigen {
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namespace internal {
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template<typename MatrixType, int Side, bool Transposed>
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struct permutation_matrix_product<MatrixType, Side, Transposed, SparseShape>
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{
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typedef typename remove_all<typename MatrixType::Nested>::type MatrixTypeNestedCleaned;
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typedef typename MatrixTypeNestedCleaned::Scalar Scalar;
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typedef typename MatrixTypeNestedCleaned::StorageIndex StorageIndex;
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enum {
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SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
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MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
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};
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typedef typename internal::conditional<MoveOuter,
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SparseMatrix<Scalar,SrcStorageOrder,StorageIndex>,
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SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,StorageIndex> >::type ReturnType;
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template<typename Dest,typename PermutationType>
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static inline void run(Dest& dst, const PermutationType& perm, const MatrixType& mat)
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{
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if(MoveOuter)
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{
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SparseMatrix<Scalar,SrcStorageOrder,StorageIndex> tmp(mat.rows(), mat.cols());
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Matrix<StorageIndex,Dynamic,1> sizes(mat.outerSize());
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for(Index j=0; j<mat.outerSize(); ++j)
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{
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Index jp = perm.indices().coeff(j);
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sizes[((Side==OnTheLeft) ^ Transposed) ? jp : j] = StorageIndex(mat.innerVector(((Side==OnTheRight) ^ Transposed) ? jp : j).nonZeros());
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}
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tmp.reserve(sizes);
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for(Index j=0; j<mat.outerSize(); ++j)
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{
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Index jp = perm.indices().coeff(j);
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Index jsrc = ((Side==OnTheRight) ^ Transposed) ? jp : j;
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Index jdst = ((Side==OnTheLeft) ^ Transposed) ? jp : j;
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for(typename MatrixTypeNestedCleaned::InnerIterator it(mat,jsrc); it; ++it)
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tmp.insertByOuterInner(jdst,it.index()) = it.value();
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}
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dst = tmp;
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}
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else
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{
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SparseMatrix<Scalar,int(SrcStorageOrder)==RowMajor?ColMajor:RowMajor,StorageIndex> tmp(mat.rows(), mat.cols());
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Matrix<StorageIndex,Dynamic,1> sizes(tmp.outerSize());
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sizes.setZero();
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PermutationMatrix<Dynamic,Dynamic,StorageIndex> perm_cpy;
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if((Side==OnTheLeft) ^ Transposed)
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perm_cpy = perm;
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else
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perm_cpy = perm.transpose();
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for(Index j=0; j<mat.outerSize(); ++j)
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for(typename MatrixTypeNestedCleaned::InnerIterator it(mat,j); it; ++it)
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sizes[perm_cpy.indices().coeff(it.index())]++;
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tmp.reserve(sizes);
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for(Index j=0; j<mat.outerSize(); ++j)
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for(typename MatrixTypeNestedCleaned::InnerIterator it(mat,j); it; ++it)
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tmp.insertByOuterInner(perm_cpy.indices().coeff(it.index()),j) = it.value();
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dst = tmp;
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}
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}
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};
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}
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namespace internal {
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template <int ProductTag> struct product_promote_storage_type<Sparse, PermutationStorage, ProductTag> { typedef Sparse ret; };
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template <int ProductTag> struct product_promote_storage_type<PermutationStorage, Sparse, ProductTag> { typedef Sparse ret; };
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// TODO, the following two overloads are only needed to define the right temporary type through
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// typename traits<permutation_sparse_matrix_product<Rhs,Lhs,OnTheRight,false> >::ReturnType
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// whereas it should be correctly handled by traits<Product<> >::PlainObject
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template<typename Lhs, typename Rhs, int ProductTag>
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struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, PermutationShape, SparseShape, typename traits<Lhs>::Scalar, typename traits<Rhs>::Scalar>
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: public evaluator<typename permutation_matrix_product<Rhs,OnTheRight,false,SparseShape>::ReturnType>::type
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{
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typedef Product<Lhs, Rhs, AliasFreeProduct> XprType;
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typedef typename permutation_matrix_product<Rhs,OnTheRight,false,SparseShape>::ReturnType PlainObject;
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typedef typename evaluator<PlainObject>::type Base;
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explicit product_evaluator(const XprType& xpr)
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: m_result(xpr.rows(), xpr.cols())
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{
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::new (static_cast<Base*>(this)) Base(m_result);
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generic_product_impl<Lhs, Rhs, PermutationShape, SparseShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
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}
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protected:
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PlainObject m_result;
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};
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template<typename Lhs, typename Rhs, int ProductTag>
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struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, SparseShape, PermutationShape, typename traits<Lhs>::Scalar, typename traits<Rhs>::Scalar>
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: public evaluator<typename permutation_matrix_product<Lhs,OnTheRight,false,SparseShape>::ReturnType>::type
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{
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typedef Product<Lhs, Rhs, AliasFreeProduct> XprType;
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typedef typename permutation_matrix_product<Lhs,OnTheRight,false,SparseShape>::ReturnType PlainObject;
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typedef typename evaluator<PlainObject>::type Base;
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explicit product_evaluator(const XprType& xpr)
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: m_result(xpr.rows(), xpr.cols())
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{
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::new (static_cast<Base*>(this)) Base(m_result);
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generic_product_impl<Lhs, Rhs, SparseShape, PermutationShape, ProductTag>::evalTo(m_result, xpr.lhs(), xpr.rhs());
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}
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protected:
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PlainObject m_result;
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};
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} // end namespace internal
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/** \returns the matrix with the permutation applied to the columns
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*/
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template<typename SparseDerived, typename PermDerived>
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inline const Product<SparseDerived, PermDerived>
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operator*(const SparseMatrixBase<SparseDerived>& matrix, const PermutationBase<PermDerived>& perm)
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{ return Product<SparseDerived, PermDerived>(matrix.derived(), perm.derived()); }
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/** \returns the matrix with the permutation applied to the rows
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*/
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template<typename SparseDerived, typename PermDerived>
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inline const Product<PermDerived, SparseDerived>
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operator*( const PermutationBase<PermDerived>& perm, const SparseMatrixBase<SparseDerived>& matrix)
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{ return Product<PermDerived, SparseDerived>(perm.derived(), matrix.derived()); }
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// TODO, the following specializations should not be needed as Transpose<Permutation*> should be a PermutationBase.
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/** \returns the matrix with the inverse permutation applied to the columns.
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*/
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template<typename SparseDerived, typename PermDerived>
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inline const Product<SparseDerived, Transpose<PermutationBase<PermDerived> > >
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operator*(const SparseMatrixBase<SparseDerived>& matrix, const Transpose<PermutationBase<PermDerived> >& tperm)
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{
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return Product<SparseDerived, Transpose<PermutationBase<PermDerived> > >(matrix.derived(), tperm);
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}
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/** \returns the matrix with the inverse permutation applied to the rows.
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*/
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template<typename SparseDerived, typename PermDerived>
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inline const Product<Transpose<PermutationBase<PermDerived> >, SparseDerived>
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operator*(const Transpose<PermutationBase<PermDerived> >& tperm, const SparseMatrixBase<SparseDerived>& matrix)
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{
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return Product<Transpose<PermutationBase<PermDerived> >, SparseDerived>(tperm, matrix.derived());
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}
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} // end namespace Eigen
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#endif // EIGEN_SPARSE_SELFADJOINTVIEW_H
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