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https://gitlab.com/libeigen/eigen.git
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Fix perm*sparse return type and nesting, and add several sanity checks for perm*sparse
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@ -1045,6 +1045,9 @@ EIGEN_DONT_INLINE SparseMatrix<Scalar,_Options,_Index>& SparseMatrix<Scalar,_Opt
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const bool needToTranspose = (Flags & RowMajorBit) != (internal::evaluator<OtherDerived>::Flags & RowMajorBit);
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if (needToTranspose)
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{
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#ifdef EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN
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EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN
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#endif
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// two passes algorithm:
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// 1 - compute the number of coeffs per dest inner vector
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// 2 - do the actual copy/eval
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@ -16,15 +16,17 @@ 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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template<typename ExpressionType, int Side, bool Transposed>
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struct permutation_matrix_product<ExpressionType, 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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typedef typename nested_eval<ExpressionType, 1>::type MatrixType;
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typedef typename remove_all<MatrixType>::type MatrixTypeCleaned;
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typedef typename MatrixTypeCleaned::Scalar Scalar;
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typedef typename MatrixTypeCleaned::StorageIndex StorageIndex;
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enum {
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SrcStorageOrder = MatrixTypeNestedCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
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SrcStorageOrder = MatrixTypeCleaned::Flags&RowMajorBit ? RowMajor : ColMajor,
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MoveOuter = SrcStorageOrder==RowMajor ? Side==OnTheLeft : Side==OnTheRight
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};
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@ -33,8 +35,9 @@ struct permutation_matrix_product<MatrixType, Side, Transposed, SparseShape>
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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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static inline void run(Dest& dst, const PermutationType& perm, const ExpressionType& xpr)
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{
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MatrixType mat(xpr);
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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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@ -50,7 +53,7 @@ struct permutation_matrix_product<MatrixType, Side, Transposed, SparseShape>
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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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for(typename MatrixTypeCleaned::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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@ -67,11 +70,11 @@ struct permutation_matrix_product<MatrixType, Side, Transposed, SparseShape>
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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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for(typename MatrixTypeCleaned::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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for(typename MatrixTypeCleaned::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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@ -90,40 +93,48 @@ template <int ProductTag> struct product_promote_storage_type<PermutationStorage
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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>
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struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, PermutationShape, SparseShape>
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: public evaluator<typename permutation_matrix_product<Rhs,OnTheLeft,false,SparseShape>::ReturnType>
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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 permutation_matrix_product<Rhs,OnTheLeft,false,SparseShape>::ReturnType PlainObject;
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typedef evaluator<PlainObject> Base;
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enum {
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Flags = Base::Flags | EvalBeforeNestingBit
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};
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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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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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struct product_evaluator<Product<Lhs, Rhs, AliasFreeProduct>, ProductTag, SparseShape, PermutationShape >
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: public evaluator<typename permutation_matrix_product<Lhs,OnTheRight,false,SparseShape>::ReturnType>
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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 evaluator<PlainObject> Base;
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enum {
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Flags = Base::Flags | EvalBeforeNestingBit
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};
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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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protected:
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PlainObject m_result;
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};
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@ -132,34 +143,34 @@ protected:
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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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inline const Product<SparseDerived, PermDerived, AliasFreeProduct>
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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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{ return Product<SparseDerived, PermDerived, AliasFreeProduct>(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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inline const Product<PermDerived, SparseDerived, AliasFreeProduct>
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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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{ return Product<PermDerived, SparseDerived, AliasFreeProduct>(perm.derived(), matrix.derived()); }
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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 PermutationType>
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inline const Product<SparseDerived, Inverse<PermutationType > >
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inline const Product<SparseDerived, Inverse<PermutationType>, AliasFreeProduct>
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operator*(const SparseMatrixBase<SparseDerived>& matrix, const InverseImpl<PermutationType, PermutationStorage>& tperm)
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{
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return Product<SparseDerived, Inverse<PermutationType> >(matrix.derived(), tperm.derived());
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return Product<SparseDerived, Inverse<PermutationType>, AliasFreeProduct>(matrix.derived(), tperm.derived());
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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 PermutationType>
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inline const Product<Inverse<PermutationType>, SparseDerived>
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inline const Product<Inverse<PermutationType>, SparseDerived, AliasFreeProduct>
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operator*(const InverseImpl<PermutationType,PermutationStorage>& tperm, const SparseMatrixBase<SparseDerived>& matrix)
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{
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return Product<Inverse<PermutationType>, SparseDerived>(tperm.derived(), matrix.derived());
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return Product<Inverse<PermutationType>, SparseDerived, AliasFreeProduct>(tperm.derived(), matrix.derived());
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}
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} // end namespace Eigen
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@ -1,14 +1,46 @@
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// 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) 2011 Gael Guennebaud <gael.guennebaud@inria.fr>
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// Copyright (C) 2011-2015 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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static long int nb_transposed_copies;
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#define EIGEN_SPARSE_TRANSPOSED_COPY_PLUGIN {nb_transposed_copies++;}
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#define VERIFY_TRANSPOSITION_COUNT(XPR,N) {\
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nb_transposed_copies = 0; \
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XPR; \
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if(nb_transposed_copies!=N) std::cerr << "nb_transposed_copies == " << nb_transposed_copies << "\n"; \
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VERIFY( (#XPR) && nb_transposed_copies==N ); \
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}
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#include "sparse.h"
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template<typename T>
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bool is_sorted(const T& mat) {
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for(Index k = 0; k<mat.outerSize(); ++k)
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{
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Index prev = -1;
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for(typename T::InnerIterator it(mat,k); it; ++it)
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{
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if(prev>=it.index())
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return false;
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prev = it.index();
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}
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}
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return true;
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}
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template<typename T>
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typename internal::nested_eval<T,1>::type eval(const T &xpr)
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{
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VERIFY( int(internal::nested_eval<T,1>::type::Flags&RowMajorBit) == int(internal::evaluator<T>::Flags&RowMajorBit) );
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return xpr;
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}
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template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(const SparseMatrixType& ref)
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{
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const Index rows = ref.rows();
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@ -18,6 +50,8 @@ template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(c
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typedef SparseMatrix<Scalar, OtherStorage, StorageIndex> OtherSparseMatrixType;
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typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
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typedef Matrix<StorageIndex,Dynamic,1> VectorI;
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// bool IsRowMajor1 = SparseMatrixType::IsRowMajor;
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// bool IsRowMajor2 = OtherSparseMatrixType::IsRowMajor;
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double density = (std::max)(8./(rows*cols), 0.01);
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@ -42,58 +76,69 @@ template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(c
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randomPermutationVector(pi, cols);
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p.indices() = pi;
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res = mat*p;
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VERIFY( is_sorted( eval(mat*p) ));
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VERIFY( is_sorted( res = mat*p ));
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VERIFY_TRANSPOSITION_COUNT( eval(mat*p), 0);
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//VERIFY_TRANSPOSITION_COUNT( res = mat*p, IsRowMajor ? 1 : 0 );
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res_d = mat_d*p;
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VERIFY(res.isApprox(res_d) && "mat*p");
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res = p*mat;
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VERIFY( is_sorted( eval(p*mat) ));
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VERIFY( is_sorted( res = p*mat ));
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VERIFY_TRANSPOSITION_COUNT( eval(p*mat), 0);
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res_d = p*mat_d;
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VERIFY(res.isApprox(res_d) && "p*mat");
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res = mat*p.inverse();
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VERIFY( is_sorted( (mat*p).eval() ));
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VERIFY( is_sorted( res = mat*p.inverse() ));
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VERIFY_TRANSPOSITION_COUNT( eval(mat*p.inverse()), 0);
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res_d = mat*p.inverse();
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VERIFY(res.isApprox(res_d) && "mat*inv(p)");
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res = p.inverse()*mat;
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VERIFY( is_sorted( (p*mat+p*mat).eval() ));
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VERIFY( is_sorted( res = p.inverse()*mat ));
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VERIFY_TRANSPOSITION_COUNT( eval(p.inverse()*mat), 0);
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res_d = p.inverse()*mat_d;
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VERIFY(res.isApprox(res_d) && "inv(p)*mat");
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res = mat.twistedBy(p);
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VERIFY( is_sorted( (p * mat * p.inverse()).eval() ));
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VERIFY( is_sorted( res = mat.twistedBy(p) ));
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VERIFY_TRANSPOSITION_COUNT( eval(p * mat * p.inverse()), 0);
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res_d = (p * mat_d) * p.inverse();
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VERIFY(res.isApprox(res_d) && "p*mat*inv(p)");
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res = mat.template selfadjointView<Upper>().twistedBy(p_null);
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VERIFY( is_sorted( res = mat.template selfadjointView<Upper>().twistedBy(p_null) ));
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res_d = up_sym_d;
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VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
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res = mat.template selfadjointView<Lower>().twistedBy(p_null);
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VERIFY( is_sorted( res = mat.template selfadjointView<Lower>().twistedBy(p_null) ));
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res_d = lo_sym_d;
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VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
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res = up.template selfadjointView<Upper>().twistedBy(p_null);
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VERIFY( is_sorted( res = up.template selfadjointView<Upper>().twistedBy(p_null) ));
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res_d = up_sym_d;
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VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
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res = lo.template selfadjointView<Lower>().twistedBy(p_null);
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VERIFY( is_sorted( res = lo.template selfadjointView<Lower>().twistedBy(p_null) ));
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res_d = lo_sym_d;
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VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
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res = mat.template selfadjointView<Upper>();
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VERIFY( is_sorted( res = mat.template selfadjointView<Upper>() ));
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res_d = up_sym_d;
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VERIFY(res.isApprox(res_d) && "full selfadjoint upper to full");
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res = mat.template selfadjointView<Lower>();
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VERIFY( is_sorted( res = mat.template selfadjointView<Lower>() ));
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res_d = lo_sym_d;
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VERIFY(res.isApprox(res_d) && "full selfadjoint lower to full");
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res = up.template selfadjointView<Upper>();
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VERIFY( is_sorted( res = up.template selfadjointView<Upper>() ));
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res_d = up_sym_d;
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VERIFY(res.isApprox(res_d) && "upper selfadjoint to full");
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res = lo.template selfadjointView<Lower>();
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VERIFY( is_sorted( res = lo.template selfadjointView<Lower>() ));
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res_d = lo_sym_d;
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VERIFY(res.isApprox(res_d) && "lower selfadjoint full");
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@ -150,19 +195,19 @@ template<int OtherStorage, typename SparseMatrixType> void sparse_permutations(c
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VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to lower");
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res = mat.template selfadjointView<Upper>().twistedBy(p);
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VERIFY( is_sorted( res = mat.template selfadjointView<Upper>().twistedBy(p) ));
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res_d = (p * up_sym_d) * p.inverse();
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VERIFY(res.isApprox(res_d) && "full selfadjoint upper twisted to full");
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res = mat.template selfadjointView<Lower>().twistedBy(p);
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VERIFY( is_sorted( res = mat.template selfadjointView<Lower>().twistedBy(p) ));
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res_d = (p * lo_sym_d) * p.inverse();
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VERIFY(res.isApprox(res_d) && "full selfadjoint lower twisted to full");
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res = up.template selfadjointView<Upper>().twistedBy(p);
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VERIFY( is_sorted( res = up.template selfadjointView<Upper>().twistedBy(p) ));
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res_d = (p * up_sym_d) * p.inverse();
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VERIFY(res.isApprox(res_d) && "upper selfadjoint twisted to full");
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res = lo.template selfadjointView<Lower>().twistedBy(p);
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VERIFY( is_sorted( res = lo.template selfadjointView<Lower>().twistedBy(p) ));
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res_d = (p * lo_sym_d) * p.inverse();
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VERIFY(res.isApprox(res_d) && "lower selfadjoint twisted to full");
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}
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@ -182,4 +227,10 @@ void test_sparse_permutations()
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CALL_SUBTEST_1(( sparse_permutations_all<double>(s) ));
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CALL_SUBTEST_2(( sparse_permutations_all<std::complex<double> >(s) ));
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}
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VERIFY((internal::is_same<typename internal::permutation_matrix_product<SparseMatrix<double>,OnTheRight,false,SparseShape>::ReturnType,
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typename internal::nested_eval<Product<SparseMatrix<double>,PermutationMatrix<Dynamic,Dynamic>,AliasFreeProduct>,1>::type>::value));
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VERIFY((internal::is_same<typename internal::permutation_matrix_product<SparseMatrix<double>,OnTheLeft,false,SparseShape>::ReturnType,
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typename internal::nested_eval<Product<PermutationMatrix<Dynamic,Dynamic>,SparseMatrix<double>,AliasFreeProduct>,1>::type>::value));
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}
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