831 lines
32 KiB
Plaintext
831 lines
32 KiB
Plaintext
//
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// Copyright (c) 2000-2002
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// Joerg Walter, Mathias Koch
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//
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// Distributed under the Boost Software License, Version 1.0. (See
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// accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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//
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// The authors gratefully acknowledge the support of
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// GeNeSys mbH & Co. KG in producing this work.
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//
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#ifndef _BOOST_UBLAS_OPERATION_
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#define _BOOST_UBLAS_OPERATION_
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#include <boost/numeric/ublas/matrix_proxy.hpp>
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/** \file operation.hpp
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* \brief This file contains some specialized products.
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*/
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// axpy-based products
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// Alexei Novakov had a lot of ideas to improve these. Thanks.
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// Hendrik Kueck proposed some new kernel. Thanks again.
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namespace boost { namespace numeric { namespace ublas {
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template<class V, class T1, class L1, class IA1, class TA1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,
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const vector_expression<E2> &e2,
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V &v, row_major_tag) {
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typedef typename V::size_type size_type;
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typedef typename V::value_type value_type;
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for (size_type i = 0; i < e1.filled1 () -1; ++ i) {
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size_type begin = e1.index1_data () [i];
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size_type end = e1.index1_data () [i + 1];
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value_type t (v (i));
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for (size_type j = begin; j < end; ++ j)
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t += e1.value_data () [j] * e2 () (e1.index2_data () [j]);
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v (i) = t;
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}
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return v;
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}
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template<class V, class T1, class L1, class IA1, class TA1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,
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const vector_expression<E2> &e2,
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V &v, column_major_tag) {
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typedef typename V::size_type size_type;
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for (size_type j = 0; j < e1.filled1 () -1; ++ j) {
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size_type begin = e1.index1_data () [j];
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size_type end = e1.index1_data () [j + 1];
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for (size_type i = begin; i < end; ++ i)
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v (e1.index2_data () [i]) += e1.value_data () [i] * e2 () (j);
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}
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return v;
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}
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// Dispatcher
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template<class V, class T1, class L1, class IA1, class TA1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,
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const vector_expression<E2> &e2,
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V &v, bool init = true) {
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typedef typename V::value_type value_type;
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typedef typename L1::orientation_category orientation_category;
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if (init)
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v.assign (zero_vector<value_type> (e1.size1 ()));
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#if BOOST_UBLAS_TYPE_CHECK
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vector<value_type> cv (v);
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typedef typename type_traits<value_type>::real_type real_type;
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real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
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indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
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#endif
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axpy_prod (e1, e2, v, orientation_category ());
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#if BOOST_UBLAS_TYPE_CHECK
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BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
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#endif
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return v;
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}
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template<class V, class T1, class L1, class IA1, class TA1, class E2>
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BOOST_UBLAS_INLINE
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V
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axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,
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const vector_expression<E2> &e2) {
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typedef V vector_type;
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vector_type v (e1.size1 ());
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return axpy_prod (e1, e2, v, true);
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}
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template<class V, class T1, class L1, class IA1, class TA1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const coordinate_matrix<T1, L1, 0, IA1, TA1> &e1,
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const vector_expression<E2> &e2,
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V &v, bool init = true) {
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typedef typename V::size_type size_type;
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typedef typename V::value_type value_type;
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typedef L1 layout_type;
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size_type size1 = e1.size1();
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size_type size2 = e1.size2();
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if (init) {
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noalias(v) = zero_vector<value_type>(size1);
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}
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for (size_type i = 0; i < e1.nnz(); ++i) {
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size_type row_index = layout_type::index_M( e1.index1_data () [i], e1.index2_data () [i] );
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size_type col_index = layout_type::index_m( e1.index1_data () [i], e1.index2_data () [i] );
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v( row_index ) += e1.value_data () [i] * e2 () (col_index);
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}
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return v;
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}
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const matrix_expression<E1> &e1,
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const vector_expression<E2> &e2,
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V &v, packed_random_access_iterator_tag, row_major_tag) {
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typedef const E1 expression1_type;
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typedef typename V::size_type size_type;
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typename expression1_type::const_iterator1 it1 (e1 ().begin1 ());
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typename expression1_type::const_iterator1 it1_end (e1 ().end1 ());
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while (it1 != it1_end) {
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size_type index1 (it1.index1 ());
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#ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
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typename expression1_type::const_iterator2 it2 (it1.begin ());
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typename expression1_type::const_iterator2 it2_end (it1.end ());
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#else
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typename expression1_type::const_iterator2 it2 (boost::numeric::ublas::begin (it1, iterator1_tag ()));
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typename expression1_type::const_iterator2 it2_end (boost::numeric::ublas::end (it1, iterator1_tag ()));
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#endif
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while (it2 != it2_end) {
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v (index1) += *it2 * e2 () (it2.index2 ());
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++ it2;
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}
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++ it1;
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}
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return v;
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}
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const matrix_expression<E1> &e1,
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const vector_expression<E2> &e2,
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V &v, packed_random_access_iterator_tag, column_major_tag) {
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typedef const E1 expression1_type;
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typedef typename V::size_type size_type;
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typename expression1_type::const_iterator2 it2 (e1 ().begin2 ());
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typename expression1_type::const_iterator2 it2_end (e1 ().end2 ());
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while (it2 != it2_end) {
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size_type index2 (it2.index2 ());
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#ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
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typename expression1_type::const_iterator1 it1 (it2.begin ());
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typename expression1_type::const_iterator1 it1_end (it2.end ());
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#else
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typename expression1_type::const_iterator1 it1 (boost::numeric::ublas::begin (it2, iterator2_tag ()));
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typename expression1_type::const_iterator1 it1_end (boost::numeric::ublas::end (it2, iterator2_tag ()));
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#endif
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while (it1 != it1_end) {
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v (it1.index1 ()) += *it1 * e2 () (index2);
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++ it1;
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}
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++ it2;
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}
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return v;
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}
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const matrix_expression<E1> &e1,
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const vector_expression<E2> &e2,
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V &v, sparse_bidirectional_iterator_tag) {
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typedef const E2 expression2_type;
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typename expression2_type::const_iterator it (e2 ().begin ());
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typename expression2_type::const_iterator it_end (e2 ().end ());
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while (it != it_end) {
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v.plus_assign (column (e1 (), it.index ()) * *it);
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++ it;
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}
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return v;
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}
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// Dispatcher
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const matrix_expression<E1> &e1,
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const vector_expression<E2> &e2,
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V &v, packed_random_access_iterator_tag) {
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typedef typename E1::orientation_category orientation_category;
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return axpy_prod (e1, e2, v, packed_random_access_iterator_tag (), orientation_category ());
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}
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/** \brief computes <tt>v += A x</tt> or <tt>v = A x</tt> in an
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optimized fashion.
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\param e1 the matrix expression \c A
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\param e2 the vector expression \c x
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\param v the result vector \c v
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\param init a boolean parameter
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<tt>axpy_prod(A, x, v, init)</tt> implements the well known
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axpy-product. Setting \a init to \c true is equivalent to call
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<tt>v.clear()</tt> before <tt>axpy_prod</tt>. Currently \a init
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defaults to \c true, but this may change in the future.
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Up to now there are some specialisation for compressed
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matrices that give a large speed up compared to prod.
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\ingroup blas2
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\internal
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template parameters:
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\param V type of the result vector \c v
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\param E1 type of a matrix expression \c A
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\param E2 type of a vector expression \c x
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*/
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const matrix_expression<E1> &e1,
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const vector_expression<E2> &e2,
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V &v, bool init = true) {
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typedef typename V::value_type value_type;
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typedef typename E2::const_iterator::iterator_category iterator_category;
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if (init)
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v.assign (zero_vector<value_type> (e1 ().size1 ()));
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#if BOOST_UBLAS_TYPE_CHECK
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vector<value_type> cv (v);
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typedef typename type_traits<value_type>::real_type real_type;
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real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
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indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
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#endif
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axpy_prod (e1, e2, v, iterator_category ());
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#if BOOST_UBLAS_TYPE_CHECK
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BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
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#endif
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return v;
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}
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V
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axpy_prod (const matrix_expression<E1> &e1,
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const vector_expression<E2> &e2) {
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typedef V vector_type;
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vector_type v (e1 ().size1 ());
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return axpy_prod (e1, e2, v, true);
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}
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template<class V, class E1, class T2, class IA2, class TA2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const vector_expression<E1> &e1,
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const compressed_matrix<T2, column_major, 0, IA2, TA2> &e2,
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V &v, column_major_tag) {
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typedef typename V::size_type size_type;
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typedef typename V::value_type value_type;
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for (size_type j = 0; j < e2.filled1 () -1; ++ j) {
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size_type begin = e2.index1_data () [j];
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size_type end = e2.index1_data () [j + 1];
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value_type t (v (j));
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for (size_type i = begin; i < end; ++ i)
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t += e2.value_data () [i] * e1 () (e2.index2_data () [i]);
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v (j) = t;
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}
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return v;
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}
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template<class V, class E1, class T2, class IA2, class TA2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const vector_expression<E1> &e1,
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const compressed_matrix<T2, row_major, 0, IA2, TA2> &e2,
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V &v, row_major_tag) {
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typedef typename V::size_type size_type;
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for (size_type i = 0; i < e2.filled1 () -1; ++ i) {
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size_type begin = e2.index1_data () [i];
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size_type end = e2.index1_data () [i + 1];
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for (size_type j = begin; j < end; ++ j)
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v (e2.index2_data () [j]) += e2.value_data () [j] * e1 () (i);
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}
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return v;
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}
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// Dispatcher
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template<class V, class E1, class T2, class L2, class IA2, class TA2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const vector_expression<E1> &e1,
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const compressed_matrix<T2, L2, 0, IA2, TA2> &e2,
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V &v, bool init = true) {
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typedef typename V::value_type value_type;
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typedef typename L2::orientation_category orientation_category;
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if (init)
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v.assign (zero_vector<value_type> (e2.size2 ()));
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#if BOOST_UBLAS_TYPE_CHECK
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vector<value_type> cv (v);
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typedef typename type_traits<value_type>::real_type real_type;
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real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
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indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
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#endif
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axpy_prod (e1, e2, v, orientation_category ());
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#if BOOST_UBLAS_TYPE_CHECK
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BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
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#endif
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return v;
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}
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template<class V, class E1, class T2, class L2, class IA2, class TA2>
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BOOST_UBLAS_INLINE
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V
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axpy_prod (const vector_expression<E1> &e1,
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const compressed_matrix<T2, L2, 0, IA2, TA2> &e2) {
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typedef V vector_type;
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vector_type v (e2.size2 ());
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return axpy_prod (e1, e2, v, true);
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}
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const vector_expression<E1> &e1,
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const matrix_expression<E2> &e2,
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V &v, packed_random_access_iterator_tag, column_major_tag) {
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typedef const E2 expression2_type;
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typedef typename V::size_type size_type;
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typename expression2_type::const_iterator2 it2 (e2 ().begin2 ());
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typename expression2_type::const_iterator2 it2_end (e2 ().end2 ());
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while (it2 != it2_end) {
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size_type index2 (it2.index2 ());
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#ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
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typename expression2_type::const_iterator1 it1 (it2.begin ());
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typename expression2_type::const_iterator1 it1_end (it2.end ());
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#else
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typename expression2_type::const_iterator1 it1 (boost::numeric::ublas::begin (it2, iterator2_tag ()));
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typename expression2_type::const_iterator1 it1_end (boost::numeric::ublas::end (it2, iterator2_tag ()));
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#endif
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while (it1 != it1_end) {
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v (index2) += *it1 * e1 () (it1.index1 ());
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++ it1;
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}
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++ it2;
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}
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return v;
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}
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const vector_expression<E1> &e1,
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const matrix_expression<E2> &e2,
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V &v, packed_random_access_iterator_tag, row_major_tag) {
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typedef const E2 expression2_type;
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typedef typename V::size_type size_type;
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typename expression2_type::const_iterator1 it1 (e2 ().begin1 ());
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typename expression2_type::const_iterator1 it1_end (e2 ().end1 ());
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while (it1 != it1_end) {
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size_type index1 (it1.index1 ());
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#ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
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typename expression2_type::const_iterator2 it2 (it1.begin ());
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typename expression2_type::const_iterator2 it2_end (it1.end ());
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#else
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typename expression2_type::const_iterator2 it2 (boost::numeric::ublas::begin (it1, iterator1_tag ()));
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typename expression2_type::const_iterator2 it2_end (boost::numeric::ublas::end (it1, iterator1_tag ()));
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#endif
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while (it2 != it2_end) {
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v (it2.index2 ()) += *it2 * e1 () (index1);
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++ it2;
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}
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++ it1;
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}
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return v;
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}
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const vector_expression<E1> &e1,
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const matrix_expression<E2> &e2,
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V &v, sparse_bidirectional_iterator_tag) {
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typedef const E1 expression1_type;
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typename expression1_type::const_iterator it (e1 ().begin ());
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typename expression1_type::const_iterator it_end (e1 ().end ());
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while (it != it_end) {
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v.plus_assign (*it * row (e2 (), it.index ()));
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++ it;
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}
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return v;
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}
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// Dispatcher
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template<class V, class E1, class E2>
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BOOST_UBLAS_INLINE
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V &
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axpy_prod (const vector_expression<E1> &e1,
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const matrix_expression<E2> &e2,
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V &v, packed_random_access_iterator_tag) {
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typedef typename E2::orientation_category orientation_category;
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return axpy_prod (e1, e2, v, packed_random_access_iterator_tag (), orientation_category ());
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}
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/** \brief computes <tt>v += A<sup>T</sup> x</tt> or <tt>v = A<sup>T</sup> x</tt> in an
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optimized fashion.
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\param e1 the vector expression \c x
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\param e2 the matrix expression \c A
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\param v the result vector \c v
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\param init a boolean parameter
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<tt>axpy_prod(x, A, v, init)</tt> implements the well known
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axpy-product. Setting \a init to \c true is equivalent to call
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<tt>v.clear()</tt> before <tt>axpy_prod</tt>. Currently \a init
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|
defaults to \c true, but this may change in the future.
|
|
|
|
Up to now there are some specialisation for compressed
|
|
matrices that give a large speed up compared to prod.
|
|
|
|
\ingroup blas2
|
|
|
|
\internal
|
|
|
|
template parameters:
|
|
\param V type of the result vector \c v
|
|
\param E1 type of a vector expression \c x
|
|
\param E2 type of a matrix expression \c A
|
|
*/
|
|
template<class V, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
V &
|
|
axpy_prod (const vector_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
V &v, bool init = true) {
|
|
typedef typename V::value_type value_type;
|
|
typedef typename E1::const_iterator::iterator_category iterator_category;
|
|
|
|
if (init)
|
|
v.assign (zero_vector<value_type> (e2 ().size2 ()));
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
vector<value_type> cv (v);
|
|
typedef typename type_traits<value_type>::real_type real_type;
|
|
real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
|
|
indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
|
|
#endif
|
|
axpy_prod (e1, e2, v, iterator_category ());
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
|
|
#endif
|
|
return v;
|
|
}
|
|
template<class V, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
V
|
|
axpy_prod (const vector_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2) {
|
|
typedef V vector_type;
|
|
|
|
vector_type v (e2 ().size2 ());
|
|
return axpy_prod (e1, e2, v, true);
|
|
}
|
|
|
|
template<class M, class E1, class E2, class TRI>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m, TRI,
|
|
dense_proxy_tag, row_major_tag) {
|
|
|
|
typedef typename M::size_type size_type;
|
|
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
typedef typename M::value_type value_type;
|
|
matrix<value_type, row_major> cm (m);
|
|
typedef typename type_traits<value_type>::real_type real_type;
|
|
real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
|
indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), row_major_tag ());
|
|
#endif
|
|
size_type size1 (e1 ().size1 ());
|
|
size_type size2 (e1 ().size2 ());
|
|
for (size_type i = 0; i < size1; ++ i)
|
|
for (size_type j = 0; j < size2; ++ j)
|
|
row (m, i).plus_assign (e1 () (i, j) * row (e2 (), j));
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
|
#endif
|
|
return m;
|
|
}
|
|
template<class M, class E1, class E2, class TRI>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m, TRI,
|
|
sparse_proxy_tag, row_major_tag) {
|
|
|
|
typedef TRI triangular_restriction;
|
|
typedef const E1 expression1_type;
|
|
typedef const E2 expression2_type;
|
|
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
typedef typename M::value_type value_type;
|
|
matrix<value_type, row_major> cm (m);
|
|
typedef typename type_traits<value_type>::real_type real_type;
|
|
real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
|
indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), row_major_tag ());
|
|
#endif
|
|
typename expression1_type::const_iterator1 it1 (e1 ().begin1 ());
|
|
typename expression1_type::const_iterator1 it1_end (e1 ().end1 ());
|
|
while (it1 != it1_end) {
|
|
#ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
|
|
typename expression1_type::const_iterator2 it2 (it1.begin ());
|
|
typename expression1_type::const_iterator2 it2_end (it1.end ());
|
|
#else
|
|
typename expression1_type::const_iterator2 it2 (boost::numeric::ublas::begin (it1, iterator1_tag ()));
|
|
typename expression1_type::const_iterator2 it2_end (boost::numeric::ublas::end (it1, iterator1_tag ()));
|
|
#endif
|
|
while (it2 != it2_end) {
|
|
// row (m, it1.index1 ()).plus_assign (*it2 * row (e2 (), it2.index2 ()));
|
|
matrix_row<expression2_type> mr (e2 (), it2.index2 ());
|
|
typename matrix_row<expression2_type>::const_iterator itr (mr.begin ());
|
|
typename matrix_row<expression2_type>::const_iterator itr_end (mr.end ());
|
|
while (itr != itr_end) {
|
|
if (triangular_restriction::other (it1.index1 (), itr.index ()))
|
|
m (it1.index1 (), itr.index ()) += *it2 * *itr;
|
|
++ itr;
|
|
}
|
|
++ it2;
|
|
}
|
|
++ it1;
|
|
}
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
|
#endif
|
|
return m;
|
|
}
|
|
|
|
template<class M, class E1, class E2, class TRI>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m, TRI,
|
|
dense_proxy_tag, column_major_tag) {
|
|
typedef typename M::size_type size_type;
|
|
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
typedef typename M::value_type value_type;
|
|
matrix<value_type, column_major> cm (m);
|
|
typedef typename type_traits<value_type>::real_type real_type;
|
|
real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
|
indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), column_major_tag ());
|
|
#endif
|
|
size_type size1 (e2 ().size1 ());
|
|
size_type size2 (e2 ().size2 ());
|
|
for (size_type j = 0; j < size2; ++ j)
|
|
for (size_type i = 0; i < size1; ++ i)
|
|
column (m, j).plus_assign (e2 () (i, j) * column (e1 (), i));
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
|
#endif
|
|
return m;
|
|
}
|
|
template<class M, class E1, class E2, class TRI>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m, TRI,
|
|
sparse_proxy_tag, column_major_tag) {
|
|
typedef TRI triangular_restriction;
|
|
typedef const E1 expression1_type;
|
|
typedef const E2 expression2_type;
|
|
|
|
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
typedef typename M::value_type value_type;
|
|
matrix<value_type, column_major> cm (m);
|
|
typedef typename type_traits<value_type>::real_type real_type;
|
|
real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
|
indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), column_major_tag ());
|
|
#endif
|
|
typename expression2_type::const_iterator2 it2 (e2 ().begin2 ());
|
|
typename expression2_type::const_iterator2 it2_end (e2 ().end2 ());
|
|
while (it2 != it2_end) {
|
|
#ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
|
|
typename expression2_type::const_iterator1 it1 (it2.begin ());
|
|
typename expression2_type::const_iterator1 it1_end (it2.end ());
|
|
#else
|
|
typename expression2_type::const_iterator1 it1 (boost::numeric::ublas::begin (it2, iterator2_tag ()));
|
|
typename expression2_type::const_iterator1 it1_end (boost::numeric::ublas::end (it2, iterator2_tag ()));
|
|
#endif
|
|
while (it1 != it1_end) {
|
|
// column (m, it2.index2 ()).plus_assign (*it1 * column (e1 (), it1.index1 ()));
|
|
matrix_column<expression1_type> mc (e1 (), it1.index1 ());
|
|
typename matrix_column<expression1_type>::const_iterator itc (mc.begin ());
|
|
typename matrix_column<expression1_type>::const_iterator itc_end (mc.end ());
|
|
while (itc != itc_end) {
|
|
if(triangular_restriction::other (itc.index (), it2.index2 ()))
|
|
m (itc.index (), it2.index2 ()) += *it1 * *itc;
|
|
++ itc;
|
|
}
|
|
++ it1;
|
|
}
|
|
++ it2;
|
|
}
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
|
#endif
|
|
return m;
|
|
}
|
|
|
|
// Dispatcher
|
|
template<class M, class E1, class E2, class TRI>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m, TRI, bool init = true) {
|
|
typedef typename M::value_type value_type;
|
|
typedef typename M::storage_category storage_category;
|
|
typedef typename M::orientation_category orientation_category;
|
|
typedef TRI triangular_restriction;
|
|
|
|
if (init)
|
|
m.assign (zero_matrix<value_type> (e1 ().size1 (), e2 ().size2 ()));
|
|
return axpy_prod (e1, e2, m, triangular_restriction (), storage_category (), orientation_category ());
|
|
}
|
|
template<class M, class E1, class E2, class TRI>
|
|
BOOST_UBLAS_INLINE
|
|
M
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
TRI) {
|
|
typedef M matrix_type;
|
|
typedef TRI triangular_restriction;
|
|
|
|
matrix_type m (e1 ().size1 (), e2 ().size2 ());
|
|
return axpy_prod (e1, e2, m, triangular_restriction (), true);
|
|
}
|
|
|
|
/** \brief computes <tt>M += A X</tt> or <tt>M = A X</tt> in an
|
|
optimized fashion.
|
|
|
|
\param e1 the matrix expression \c A
|
|
\param e2 the matrix expression \c X
|
|
\param m the result matrix \c M
|
|
\param init a boolean parameter
|
|
|
|
<tt>axpy_prod(A, X, M, init)</tt> implements the well known
|
|
axpy-product. Setting \a init to \c true is equivalent to call
|
|
<tt>M.clear()</tt> before <tt>axpy_prod</tt>. Currently \a init
|
|
defaults to \c true, but this may change in the future.
|
|
|
|
Up to now there are no specialisations.
|
|
|
|
\ingroup blas3
|
|
|
|
\internal
|
|
|
|
template parameters:
|
|
\param M type of the result matrix \c M
|
|
\param E1 type of a matrix expression \c A
|
|
\param E2 type of a matrix expression \c X
|
|
*/
|
|
template<class M, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m, bool init = true) {
|
|
typedef typename M::value_type value_type;
|
|
typedef typename M::storage_category storage_category;
|
|
typedef typename M::orientation_category orientation_category;
|
|
|
|
if (init)
|
|
m.assign (zero_matrix<value_type> (e1 ().size1 (), e2 ().size2 ()));
|
|
return axpy_prod (e1, e2, m, full (), storage_category (), orientation_category ());
|
|
}
|
|
template<class M, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
M
|
|
axpy_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2) {
|
|
typedef M matrix_type;
|
|
|
|
matrix_type m (e1 ().size1 (), e2 ().size2 ());
|
|
return axpy_prod (e1, e2, m, full (), true);
|
|
}
|
|
|
|
|
|
template<class M, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
opb_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m,
|
|
dense_proxy_tag, row_major_tag) {
|
|
typedef typename M::size_type size_type;
|
|
typedef typename M::value_type value_type;
|
|
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
matrix<value_type, row_major> cm (m);
|
|
typedef typename type_traits<value_type>::real_type real_type;
|
|
real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
|
indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), row_major_tag ());
|
|
#endif
|
|
size_type size (BOOST_UBLAS_SAME (e1 ().size2 (), e2 ().size1 ()));
|
|
for (size_type k = 0; k < size; ++ k) {
|
|
vector<value_type> ce1 (column (e1 (), k));
|
|
vector<value_type> re2 (row (e2 (), k));
|
|
m.plus_assign (outer_prod (ce1, re2));
|
|
}
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
|
#endif
|
|
return m;
|
|
}
|
|
|
|
template<class M, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
opb_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m,
|
|
dense_proxy_tag, column_major_tag) {
|
|
typedef typename M::size_type size_type;
|
|
typedef typename M::value_type value_type;
|
|
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
matrix<value_type, column_major> cm (m);
|
|
typedef typename type_traits<value_type>::real_type real_type;
|
|
real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
|
indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), column_major_tag ());
|
|
#endif
|
|
size_type size (BOOST_UBLAS_SAME (e1 ().size2 (), e2 ().size1 ()));
|
|
for (size_type k = 0; k < size; ++ k) {
|
|
vector<value_type> ce1 (column (e1 (), k));
|
|
vector<value_type> re2 (row (e2 (), k));
|
|
m.plus_assign (outer_prod (ce1, re2));
|
|
}
|
|
#if BOOST_UBLAS_TYPE_CHECK
|
|
BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
|
#endif
|
|
return m;
|
|
}
|
|
|
|
// Dispatcher
|
|
|
|
/** \brief computes <tt>M += A X</tt> or <tt>M = A X</tt> in an
|
|
optimized fashion.
|
|
|
|
\param e1 the matrix expression \c A
|
|
\param e2 the matrix expression \c X
|
|
\param m the result matrix \c M
|
|
\param init a boolean parameter
|
|
|
|
<tt>opb_prod(A, X, M, init)</tt> implements the well known
|
|
axpy-product. Setting \a init to \c true is equivalent to call
|
|
<tt>M.clear()</tt> before <tt>opb_prod</tt>. Currently \a init
|
|
defaults to \c true, but this may change in the future.
|
|
|
|
This function may give a speedup if \c A has less columns than
|
|
rows, because the product is computed as a sum of outer
|
|
products.
|
|
|
|
\ingroup blas3
|
|
|
|
\internal
|
|
|
|
template parameters:
|
|
\param M type of the result matrix \c M
|
|
\param E1 type of a matrix expression \c A
|
|
\param E2 type of a matrix expression \c X
|
|
*/
|
|
template<class M, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
M &
|
|
opb_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2,
|
|
M &m, bool init = true) {
|
|
typedef typename M::value_type value_type;
|
|
typedef typename M::storage_category storage_category;
|
|
typedef typename M::orientation_category orientation_category;
|
|
|
|
if (init)
|
|
m.assign (zero_matrix<value_type> (e1 ().size1 (), e2 ().size2 ()));
|
|
return opb_prod (e1, e2, m, storage_category (), orientation_category ());
|
|
}
|
|
template<class M, class E1, class E2>
|
|
BOOST_UBLAS_INLINE
|
|
M
|
|
opb_prod (const matrix_expression<E1> &e1,
|
|
const matrix_expression<E2> &e2) {
|
|
typedef M matrix_type;
|
|
|
|
matrix_type m (e1 ().size1 (), e2 ().size2 ());
|
|
return opb_prod (e1, e2, m, true);
|
|
}
|
|
|
|
}}}
|
|
|
|
#endif
|