diff options
Diffstat (limited to 'Eigen/src/SparseCore/ConservativeSparseSparseProduct.h')
| -rw-r--r-- | Eigen/src/SparseCore/ConservativeSparseSparseProduct.h | 22 |
1 files changed, 14 insertions, 8 deletions
diff --git a/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h b/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h index 8067565f9..19d9eaa42 100644 --- a/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h +++ b/Eigen/src/SparseCore/ConservativeSparseSparseProduct.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008-2011 Gael Guennebaud <gael.guennebaud@inria.fr> +// 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 @@ -28,6 +28,8 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r ei_declare_aligned_stack_constructed_variable(bool, mask, rows, 0); ei_declare_aligned_stack_constructed_variable(Scalar, values, rows, 0); ei_declare_aligned_stack_constructed_variable(Index, indices, rows, 0); + + std::memset(mask,0,sizeof(bool)*rows); // estimate the number of non zero entries // given a rhs column containing Y non zeros, we assume that the respective Y columns @@ -36,6 +38,9 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r // per column of the lhs. // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs) Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros(); + + typename evaluator<Lhs>::type lhsEval(lhs); + typename evaluator<Rhs>::type rhsEval(rhs); res.setZero(); res.reserve(Index(estimated_nnz_prod)); @@ -45,11 +50,11 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r res.startVec(j); Index nnz = 0; - for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt) + for (typename evaluator<Rhs>::InnerIterator rhsIt(rhsEval, j); rhsIt; ++rhsIt) { Scalar y = rhsIt.value(); Index k = rhsIt.index(); - for (typename Lhs::InnerIterator lhsIt(lhs, k); lhsIt; ++lhsIt) + for (typename evaluator<Lhs>::InnerIterator lhsIt(lhsEval, k); lhsIt; ++lhsIt) { Index i = lhsIt.index(); Scalar x = lhsIt.value(); @@ -86,7 +91,7 @@ static void conservative_sparse_sparse_product_impl(const Lhs& lhs, const Rhs& r // otherwise => loop through the entire vector // In order to avoid to perform an expensive log2 when the // result is clearly very sparse we use a linear bound up to 200. - if((nnz<200 && nnz<t200) || nnz * log2(nnz) < t) + if((nnz<200 && nnz<t200) || nnz * numext::log2(int(nnz)) < t) { if(nnz>1) std::sort(indices,indices+nnz); for(Index k=0; k<nnz; ++k) @@ -136,20 +141,21 @@ struct conservative_sparse_sparse_product_selector<Lhs,Rhs,ResultType,ColMajor,C typedef SparseMatrix<typename ResultType::Scalar,ColMajor,typename ResultType::Index> ColMajorMatrixAux; typedef typename sparse_eval<ColMajorMatrixAux,ResultType::RowsAtCompileTime,ResultType::ColsAtCompileTime>::type ColMajorMatrix; - ColMajorMatrix resCol(lhs.rows(),rhs.cols()); // FIXME, the following heuristic is probably not very good. if(lhs.rows()>=rhs.cols()) { + ColMajorMatrix resCol(lhs.rows(),rhs.cols()); // perform sorted insertion internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol, true); - res.swap(resCol); + res = resCol.markAsRValue(); } else { + ColMajorMatrixAux resCol(lhs.rows(),rhs.cols()); // ressort to transpose to sort the entries - internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrix>(lhs, rhs, resCol, false); + internal::conservative_sparse_sparse_product_impl<Lhs,Rhs,ColMajorMatrixAux>(lhs, rhs, resCol, false); RowMajorMatrix resRow(resCol); - res = resRow; + res = resRow.markAsRValue(); } } }; |