Cross Reference: /external/eigen/Eigen/src/SparseCore/SparseSparseProductWithPruning.h

Lines Matching defs:rhs
20 static void sparse_sparse_product_with_pruning_impl(const Lhs& lhs, const Rhs& rhs, ResultType& res, const typename ResultType::RealScalar& tolerance)
22   // return sparse_sparse_product_with_pruning_impl2(lhs,rhs,res);
29   Index cols = rhs.outerSize();
31   eigen_assert(lhs.outerSize() == rhs.innerSize());
37   // given a rhs column containing Y non zeros, we assume that the respective Y columns
39   // the product of a rhs column with the lhs is X+Y where X is the average number of non zero
41   // Therefore, we have nnz(lhs*rhs) = nnz(lhs) + nnz(rhs)
42   Index estimated_nnz_prod = lhs.nonZeros() + rhs.nonZeros();
51   double ratioColRes = double(estimated_nnz_prod)/double(lhs.rows()*rhs.cols());
55     //double ratioColRes = (double(rhs.innerVector(j).nonZeros()) + double(lhs.nonZeros())/double(lhs.cols()))/double(lhs.rows());
59     for (typename Rhs::InnerIterator rhsIt(rhs, j); rhsIt; ++rhsIt)
88   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
91     internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,ResultType>(lhs, rhs, _res, tolerance);
100   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
105     internal::sparse_sparse_product_with_pruning_impl<Lhs,Rhs,SparseTemporaryType>(lhs, rhs, _res, tolerance);
114   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
118     internal::sparse_sparse_product_with_pruning_impl<Rhs,Lhs,ResultType>(rhs, lhs, _res, tolerance);
127   static void run(const Lhs& lhs, const Rhs& rhs, ResultType& res, const RealScalar& tolerance)
132     ColMajorMatrixRhs colRhs(rhs);
138 //     sparse_sparse_product_with_pruning_impl<Rhs,Lhs,SparseTemporaryType>(rhs, lhs, _res);
144 // by ProductReturnType which transforms it to (col col *) by evaluating rhs.