[857] | 1 | //
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| 2 | // Copyright (c) 2000-2002
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| 3 | // Joerg Walter, Mathias Koch
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| 4 | //
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| 5 | // Permission to use, copy, modify, distribute and sell this software
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| 6 | // and its documentation for any purpose is hereby granted without fee,
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| 7 | // provided that the above copyright notice appear in all copies and
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| 8 | // that both that copyright notice and this permission notice appear
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| 9 | // in supporting documentation. The authors make no representations
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| 10 | // about the suitability of this software for any purpose.
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| 11 | // It is provided "as is" without express or implied warranty.
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| 12 | //
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| 13 | // The authors gratefully acknowledge the support of
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| 14 | // GeNeSys mbH & Co. KG in producing this work.
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| 15 | //
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| 16 |
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| 17 | #ifndef _BOOST_UBLAS_OPERATION_
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| 18 | #define _BOOST_UBLAS_OPERATION_
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| 19 |
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| 20 | #include <boost/numeric/ublas/matrix_proxy.hpp>
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| 21 |
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| 22 | /** \file operation.hpp
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| 23 | * \brief This file contains some specialized products.
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| 24 | */
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| 25 |
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| 26 | // axpy-based products
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| 27 | // Alexei Novakov had a lot of ideas to improve these. Thanks.
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| 28 | // Hendrik Kueck proposed some new kernel. Thanks again.
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| 29 |
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| 30 | namespace boost { namespace numeric { namespace ublas {
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| 31 |
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| 32 | template<class V, class T1, class IA1, class TA1, class E2>
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| 33 | BOOST_UBLAS_INLINE
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| 34 | V &
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| 35 | axpy_prod (const compressed_matrix<T1, row_major, 0, IA1, TA1> &e1,
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| 36 | const vector_expression<E2> &e2,
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| 37 | V &v, row_major_tag) {
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| 38 | typedef typename V::size_type size_type;
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| 39 | typedef typename V::value_type value_type;
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| 40 |
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| 41 | for (size_type i = 0; i < e1.filled1 () -1; ++ i) {
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| 42 | size_type begin = e1.index1_data () [i];
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| 43 | size_type end = e1.index1_data () [i + 1];
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| 44 | value_type t (v (i));
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| 45 | for (size_type j = begin; j < end; ++ j)
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| 46 | t += e1.value_data () [j] * e2 () (e1.index2_data () [j]);
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| 47 | v (i) = t;
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| 48 | }
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| 49 | return v;
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| 50 | }
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| 51 |
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| 52 | template<class V, class T1, class IA1, class TA1, class E2>
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| 53 | BOOST_UBLAS_INLINE
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| 54 | V &
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| 55 | axpy_prod (const compressed_matrix<T1, column_major, 0, IA1, TA1> &e1,
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| 56 | const vector_expression<E2> &e2,
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| 57 | V &v, column_major_tag) {
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| 58 | typedef typename V::size_type size_type;
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| 59 |
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| 60 | for (size_type j = 0; j < e1.filled1 () -1; ++ j) {
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| 61 | size_type begin = e1.index1_data () [j];
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| 62 | size_type end = e1.index1_data () [j + 1];
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| 63 | for (size_type i = begin; i < end; ++ i)
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| 64 | v (e1.index2_data () [i]) += e1.value_data () [i] * e2 () (j);
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| 65 | }
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| 66 | return v;
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| 67 | }
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| 68 |
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| 69 | // Dispatcher
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| 70 | template<class V, class T1, class L1, class IA1, class TA1, class E2>
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| 71 | BOOST_UBLAS_INLINE
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| 72 | V &
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| 73 | axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,
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| 74 | const vector_expression<E2> &e2,
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| 75 | V &v, bool init = true) {
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| 76 | typedef typename V::value_type value_type;
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| 77 | typedef typename L1::orientation_category orientation_category;
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| 78 |
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| 79 | if (init)
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| 80 | v.assign (zero_vector<value_type> (e1.size1 ()));
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| 81 | #if BOOST_UBLAS_TYPE_CHECK
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| 82 | vector<value_type> cv (v);
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| 83 | typedef typename type_traits<value_type>::real_type real_type;
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| 84 | real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
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| 85 | indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
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| 86 | #endif
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| 87 | axpy_prod (e1, e2, v, orientation_category ());
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| 88 | #if BOOST_UBLAS_TYPE_CHECK
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| 89 | BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
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| 90 | #endif
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| 91 | return v;
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| 92 | }
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| 93 | template<class V, class T1, class L1, class IA1, class TA1, class E2>
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| 94 | BOOST_UBLAS_INLINE
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| 95 | V
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| 96 | axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,
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| 97 | const vector_expression<E2> &e2) {
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| 98 | typedef V vector_type;
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| 99 |
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| 100 | vector_type v (e1.size1 ());
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| 101 | return axpy_prod (e1, e2, v, true);
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| 102 | }
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| 103 |
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| 104 | template<class V, class T1, class L1, class IA1, class TA1, class E2>
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| 105 | BOOST_UBLAS_INLINE
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| 106 | V &
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| 107 | axpy_prod (const coordinate_matrix<T1, L1, 0, IA1, TA1> &e1,
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| 108 | const vector_expression<E2> &e2,
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| 109 | V &v, bool init = true) {
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| 110 | typedef typename V::size_type size_type;
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| 111 | typedef typename V::value_type value_type;
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| 112 | typedef L1 layout_type;
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| 113 |
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| 114 | size_type size1 = e1.size1();
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| 115 | size_type size2 = e1.size2();
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| 116 |
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| 117 | if (init) {
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| 118 | noalias(v) = zero_vector<value_type>(size1);
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| 119 | }
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| 120 |
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| 121 | for (size_type i = 0; i < e1.nnz(); ++i) {
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| 122 | size_type row_index = layout_type::element1( e1.index1_data () [i], size1, e1.index2_data () [i], size2 );
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| 123 | size_type col_index = layout_type::element2( e1.index1_data () [i], size1, e1.index2_data () [i], size2 );
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| 124 | v( row_index ) += e1.value_data () [i] * e2 () (col_index);
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| 125 | }
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| 126 | return v;
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| 127 | }
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| 128 |
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| 129 | template<class V, class E1, class E2>
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| 130 | BOOST_UBLAS_INLINE
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| 131 | V &
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| 132 | axpy_prod (const matrix_expression<E1> &e1,
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| 133 | const vector_expression<E2> &e2,
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| 134 | V &v, packed_random_access_iterator_tag, row_major_tag) {
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| 135 | typedef const E1 expression1_type;
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| 136 | typedef const E2 expression2_type;
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| 137 | typedef typename V::size_type size_type;
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| 138 |
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| 139 | typename expression1_type::const_iterator1 it1 (e1 ().begin1 ());
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| 140 | typename expression1_type::const_iterator1 it1_end (e1 ().end1 ());
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| 141 | while (it1 != it1_end) {
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| 142 | size_type index1 (it1.index1 ());
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| 143 | #ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
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| 144 | typename expression1_type::const_iterator2 it2 (it1.begin ());
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| 145 | typename expression1_type::const_iterator2 it2_end (it1.end ());
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| 146 | #else
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| 147 | typename expression1_type::const_iterator2 it2 (boost::numeric::ublas::begin (it1, iterator1_tag ()));
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| 148 | typename expression1_type::const_iterator2 it2_end (boost::numeric::ublas::end (it1, iterator1_tag ()));
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| 149 | #endif
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| 150 | while (it2 != it2_end) {
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| 151 | v (index1) += *it2 * e2 () (it2.index2 ());
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| 152 | ++ it2;
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| 153 | }
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| 154 | ++ it1;
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| 155 | }
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| 156 | return v;
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| 157 | }
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| 158 |
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| 159 | template<class V, class E1, class E2>
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| 160 | BOOST_UBLAS_INLINE
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| 161 | V &
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| 162 | axpy_prod (const matrix_expression<E1> &e1,
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| 163 | const vector_expression<E2> &e2,
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| 164 | V &v, packed_random_access_iterator_tag, column_major_tag) {
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| 165 | typedef const E1 expression1_type;
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| 166 | typedef const E2 expression2_type;
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| 167 | typedef typename V::size_type size_type;
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| 168 |
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| 169 | typename expression1_type::const_iterator2 it2 (e1 ().begin2 ());
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| 170 | typename expression1_type::const_iterator2 it2_end (e1 ().end2 ());
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| 171 | while (it2 != it2_end) {
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| 172 | size_type index2 (it2.index2 ());
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| 173 | #ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
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| 174 | typename expression1_type::const_iterator1 it1 (it2.begin ());
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| 175 | typename expression1_type::const_iterator1 it1_end (it2.end ());
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| 176 | #else
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| 177 | typename expression1_type::const_iterator1 it1 (boost::numeric::ublas::begin (it2, iterator2_tag ()));
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| 178 | typename expression1_type::const_iterator1 it1_end (boost::numeric::ublas::end (it2, iterator2_tag ()));
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| 179 | #endif
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| 180 | while (it1 != it1_end) {
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| 181 | v (it1.index1 ()) += *it1 * e2 () (index2);
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| 182 | ++ it1;
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| 183 | }
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| 184 | ++ it2;
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| 185 | }
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| 186 | return v;
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| 187 | }
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| 188 |
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| 189 | template<class V, class E1, class E2>
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| 190 | BOOST_UBLAS_INLINE
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| 191 | V &
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| 192 | axpy_prod (const matrix_expression<E1> &e1,
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| 193 | const vector_expression<E2> &e2,
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| 194 | V &v, sparse_bidirectional_iterator_tag) {
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| 195 | typedef const E1 expression1_type;
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| 196 | typedef const E2 expression2_type;
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| 197 | typedef typename V::size_type size_type;
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| 198 |
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| 199 | typename expression2_type::const_iterator it (e2 ().begin ());
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| 200 | typename expression2_type::const_iterator it_end (e2 ().end ());
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| 201 | while (it != it_end) {
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| 202 | v.plus_assign (column (e1 (), it.index ()) * *it);
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| 203 | ++ it;
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| 204 | }
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| 205 | return v;
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| 206 | }
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| 207 |
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| 208 | // Dispatcher
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| 209 | template<class V, class E1, class E2>
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| 210 | BOOST_UBLAS_INLINE
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| 211 | V &
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| 212 | axpy_prod (const matrix_expression<E1> &e1,
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| 213 | const vector_expression<E2> &e2,
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| 214 | V &v, packed_random_access_iterator_tag) {
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| 215 | typedef typename E1::orientation_category orientation_category;
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| 216 | return axpy_prod (e1, e2, v, packed_random_access_iterator_tag (), orientation_category ());
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| 217 | }
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| 218 |
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| 219 |
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| 220 | /** \brief computes <tt>v += A x</tt> or <tt>v = A x</tt> in an
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| 221 | optimized fashion.
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| 222 |
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| 223 | \param e1 the matrix expression \c A
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| 224 | \param e2 the vector expression \c x
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| 225 | \param v the result vector \c v
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| 226 | \param init a boolean parameter
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| 227 |
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| 228 | <tt>axpy_prod(A, x, v, init)</tt> implements the well known
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| 229 | axpy-product. Setting \a init to \c true is equivalent to call
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| 230 | <tt>v.clear()</tt> before <tt>axpy_prod</tt>. Currently \a init
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| 231 | defaults to \c true, but this may change in the future.
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| 232 |
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| 233 | Up to now there are some specialisation for compressed
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| 234 | matrices that give a large speed up compared to prod.
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| 235 |
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| 236 | \ingroup blas2
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| 237 |
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| 238 | \internal
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| 239 |
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| 240 | template parameters:
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| 241 | \param V type of the result vector \c v
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| 242 | \param E1 type of a matrix expression \c A
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| 243 | \param E2 type of a vector expression \c x
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| 244 | */
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| 245 | template<class V, class E1, class E2>
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| 246 | BOOST_UBLAS_INLINE
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| 247 | V &
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| 248 | axpy_prod (const matrix_expression<E1> &e1,
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| 249 | const vector_expression<E2> &e2,
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| 250 | V &v, bool init = true) {
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| 251 | typedef typename V::value_type value_type;
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| 252 | typedef typename E2::const_iterator::iterator_category iterator_category;
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| 253 |
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| 254 | if (init)
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| 255 | v.assign (zero_vector<value_type> (e1 ().size1 ()));
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| 256 | #if BOOST_UBLAS_TYPE_CHECK
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| 257 | vector<value_type> cv (v);
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| 258 | typedef typename type_traits<value_type>::real_type real_type;
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| 259 | real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
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| 260 | indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
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| 261 | #endif
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| 262 | axpy_prod (e1, e2, v, iterator_category ());
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| 263 | #if BOOST_UBLAS_TYPE_CHECK
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| 264 | BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
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| 265 | #endif
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| 266 | return v;
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| 267 | }
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| 268 | template<class V, class E1, class E2>
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| 269 | BOOST_UBLAS_INLINE
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| 270 | V
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| 271 | axpy_prod (const matrix_expression<E1> &e1,
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| 272 | const vector_expression<E2> &e2) {
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| 273 | typedef V vector_type;
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| 274 |
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| 275 | vector_type v (e1 ().size1 ());
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| 276 | return axpy_prod (e1, e2, v, true);
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| 277 | }
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| 278 |
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| 279 | template<class V, class E1, class T2, class IA2, class TA2>
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| 280 | BOOST_UBLAS_INLINE
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| 281 | V &
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| 282 | axpy_prod (const vector_expression<E1> &e1,
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| 283 | const compressed_matrix<T2, column_major, 0, IA2, TA2> &e2,
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| 284 | V &v, column_major_tag) {
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| 285 | typedef typename V::size_type size_type;
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| 286 | typedef typename V::value_type value_type;
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| 287 |
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| 288 | for (size_type j = 0; j < e2.filled1 () -1; ++ j) {
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| 289 | size_type begin = e2.index1_data () [j];
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| 290 | size_type end = e2.index1_data () [j + 1];
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| 291 | value_type t (v (j));
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| 292 | for (size_type i = begin; i < end; ++ i)
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| 293 | t += e2.value_data () [i] * e1 () (e2.index2_data () [i]);
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| 294 | v (j) = t;
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| 295 | }
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| 296 | return v;
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| 297 | }
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| 298 |
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| 299 | template<class V, class E1, class T2, class IA2, class TA2>
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| 300 | BOOST_UBLAS_INLINE
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| 301 | V &
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| 302 | axpy_prod (const vector_expression<E1> &e1,
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| 303 | const compressed_matrix<T2, row_major, 0, IA2, TA2> &e2,
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| 304 | V &v, row_major_tag) {
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| 305 | typedef typename V::size_type size_type;
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| 306 |
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| 307 | for (size_type i = 0; i < e2.filled1 () -1; ++ i) {
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| 308 | size_type begin = e2.index1_data () [i];
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| 309 | size_type end = e2.index1_data () [i + 1];
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| 310 | for (size_type j = begin; j < end; ++ j)
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| 311 | v (e2.index2_data () [j]) += e2.value_data () [j] * e1 () (i);
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| 312 | }
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| 313 | return v;
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| 314 | }
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| 315 |
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| 316 | // Dispatcher
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| 317 | template<class V, class E1, class T2, class L2, class IA2, class TA2>
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| 318 | BOOST_UBLAS_INLINE
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| 319 | V &
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| 320 | axpy_prod (const vector_expression<E1> &e1,
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| 321 | const compressed_matrix<T2, L2, 0, IA2, TA2> &e2,
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| 322 | V &v, bool init = true) {
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| 323 | typedef typename V::value_type value_type;
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| 324 | typedef typename L2::orientation_category orientation_category;
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| 325 |
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| 326 | if (init)
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| 327 | v.assign (zero_vector<value_type> (e2.size2 ()));
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| 328 | #if BOOST_UBLAS_TYPE_CHECK
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| 329 | vector<value_type> cv (v);
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| 330 | typedef typename type_traits<value_type>::real_type real_type;
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| 331 | real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
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| 332 | indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
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| 333 | #endif
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| 334 | axpy_prod (e1, e2, v, orientation_category ());
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| 335 | #if BOOST_UBLAS_TYPE_CHECK
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| 336 | BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
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| 337 | #endif
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| 338 | return v;
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| 339 | }
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| 340 | template<class V, class E1, class T2, class L2, class IA2, class TA2>
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| 341 | BOOST_UBLAS_INLINE
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| 342 | V
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| 343 | axpy_prod (const vector_expression<E1> &e1,
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| 344 | const compressed_matrix<T2, L2, 0, IA2, TA2> &e2) {
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| 345 | typedef V vector_type;
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| 346 |
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| 347 | vector_type v (e2.size2 ());
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| 348 | return axpy_prod (e1, e2, v, true);
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| 349 | }
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| 350 |
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| 351 | template<class V, class E1, class E2>
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| 352 | BOOST_UBLAS_INLINE
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| 353 | V &
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| 354 | axpy_prod (const vector_expression<E1> &e1,
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| 355 | const matrix_expression<E2> &e2,
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| 356 | V &v, packed_random_access_iterator_tag, column_major_tag) {
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| 357 | typedef const E1 expression1_type;
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| 358 | typedef const E2 expression2_type;
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| 359 | typedef typename V::size_type size_type;
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| 360 |
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| 361 | typename expression2_type::const_iterator2 it2 (e2 ().begin2 ());
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| 362 | typename expression2_type::const_iterator2 it2_end (e2 ().end2 ());
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| 363 | while (it2 != it2_end) {
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| 364 | size_type index2 (it2.index2 ());
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| 365 | #ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
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| 366 | typename expression2_type::const_iterator1 it1 (it2.begin ());
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| 367 | typename expression2_type::const_iterator1 it1_end (it2.end ());
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| 368 | #else
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| 369 | typename expression2_type::const_iterator1 it1 (boost::numeric::ublas::begin (it2, iterator2_tag ()));
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| 370 | typename expression2_type::const_iterator1 it1_end (boost::numeric::ublas::end (it2, iterator2_tag ()));
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| 371 | #endif
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| 372 | while (it1 != it1_end) {
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| 373 | v (index2) += *it1 * e1 () (it1.index1 ());
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| 374 | ++ it1;
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| 375 | }
|
---|
| 376 | ++ it2;
|
---|
| 377 | }
|
---|
| 378 | return v;
|
---|
| 379 | }
|
---|
| 380 |
|
---|
| 381 | template<class V, class E1, class E2>
|
---|
| 382 | BOOST_UBLAS_INLINE
|
---|
| 383 | V &
|
---|
| 384 | axpy_prod (const vector_expression<E1> &e1,
|
---|
| 385 | const matrix_expression<E2> &e2,
|
---|
| 386 | V &v, packed_random_access_iterator_tag, row_major_tag) {
|
---|
| 387 | typedef const E1 expression1_type;
|
---|
| 388 | typedef const E2 expression2_type;
|
---|
| 389 | typedef typename V::size_type size_type;
|
---|
| 390 |
|
---|
| 391 | typename expression2_type::const_iterator1 it1 (e2 ().begin1 ());
|
---|
| 392 | typename expression2_type::const_iterator1 it1_end (e2 ().end1 ());
|
---|
| 393 | while (it1 != it1_end) {
|
---|
| 394 | size_type index1 (it1.index1 ());
|
---|
| 395 | #ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
|
---|
| 396 | typename expression2_type::const_iterator2 it2 (it1.begin ());
|
---|
| 397 | typename expression2_type::const_iterator2 it2_end (it1.end ());
|
---|
| 398 | #else
|
---|
| 399 | typename expression2_type::const_iterator2 it2 (boost::numeric::ublas::begin (it1, iterator1_tag ()));
|
---|
| 400 | typename expression2_type::const_iterator2 it2_end (boost::numeric::ublas::end (it1, iterator1_tag ()));
|
---|
| 401 | #endif
|
---|
| 402 | while (it2 != it2_end) {
|
---|
| 403 | v (it2.index2 ()) += *it2 * e1 () (index1);
|
---|
| 404 | ++ it2;
|
---|
| 405 | }
|
---|
| 406 | ++ it1;
|
---|
| 407 | }
|
---|
| 408 | return v;
|
---|
| 409 | }
|
---|
| 410 |
|
---|
| 411 | template<class V, class E1, class E2>
|
---|
| 412 | BOOST_UBLAS_INLINE
|
---|
| 413 | V &
|
---|
| 414 | axpy_prod (const vector_expression<E1> &e1,
|
---|
| 415 | const matrix_expression<E2> &e2,
|
---|
| 416 | V &v, sparse_bidirectional_iterator_tag) {
|
---|
| 417 | typedef const E1 expression1_type;
|
---|
| 418 | typedef const E2 expression2_type;
|
---|
| 419 | typedef typename V::size_type size_type;
|
---|
| 420 |
|
---|
| 421 | typename expression1_type::const_iterator it (e1 ().begin ());
|
---|
| 422 | typename expression1_type::const_iterator it_end (e1 ().end ());
|
---|
| 423 | while (it != it_end) {
|
---|
| 424 | v.plus_assign (*it * row (e2 (), it.index ()));
|
---|
| 425 | ++ it;
|
---|
| 426 | }
|
---|
| 427 | return v;
|
---|
| 428 | }
|
---|
| 429 |
|
---|
| 430 | // Dispatcher
|
---|
| 431 | template<class V, class E1, class E2>
|
---|
| 432 | BOOST_UBLAS_INLINE
|
---|
| 433 | V &
|
---|
| 434 | axpy_prod (const vector_expression<E1> &e1,
|
---|
| 435 | const matrix_expression<E2> &e2,
|
---|
| 436 | V &v, packed_random_access_iterator_tag) {
|
---|
| 437 | typedef typename E2::orientation_category orientation_category;
|
---|
| 438 | return axpy_prod (e1, e2, v, packed_random_access_iterator_tag (), orientation_category ());
|
---|
| 439 | }
|
---|
| 440 |
|
---|
| 441 |
|
---|
| 442 | /** \brief computes <tt>v += A<sup>T</sup> x</tt> or <tt>v = A<sup>T</sup> x</tt> in an
|
---|
| 443 | optimized fashion.
|
---|
| 444 |
|
---|
| 445 | \param e1 the vector expression \c x
|
---|
| 446 | \param e2 the matrix expression \c A
|
---|
| 447 | \param v the result vector \c v
|
---|
| 448 | \param init a boolean parameter
|
---|
| 449 |
|
---|
| 450 | <tt>axpy_prod(x, A, v, init)</tt> implements the well known
|
---|
| 451 | axpy-product. Setting \a init to \c true is equivalent to call
|
---|
| 452 | <tt>v.clear()</tt> before <tt>axpy_prod</tt>. Currently \a init
|
---|
| 453 | defaults to \c true, but this may change in the future.
|
---|
| 454 |
|
---|
| 455 | Up to now there are some specialisation for compressed
|
---|
| 456 | matrices that give a large speed up compared to prod.
|
---|
| 457 |
|
---|
| 458 | \ingroup blas2
|
---|
| 459 |
|
---|
| 460 | \internal
|
---|
| 461 |
|
---|
| 462 | template parameters:
|
---|
| 463 | \param V type of the result vector \c v
|
---|
| 464 | \param E1 type of a vector expression \c x
|
---|
| 465 | \param E2 type of a matrix expression \c A
|
---|
| 466 | */
|
---|
| 467 | template<class V, class E1, class E2>
|
---|
| 468 | BOOST_UBLAS_INLINE
|
---|
| 469 | V &
|
---|
| 470 | axpy_prod (const vector_expression<E1> &e1,
|
---|
| 471 | const matrix_expression<E2> &e2,
|
---|
| 472 | V &v, bool init = true) {
|
---|
| 473 | typedef typename V::value_type value_type;
|
---|
| 474 | typedef typename E1::const_iterator::iterator_category iterator_category;
|
---|
| 475 |
|
---|
| 476 | if (init)
|
---|
| 477 | v.assign (zero_vector<value_type> (e2 ().size2 ()));
|
---|
| 478 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 479 | vector<value_type> cv (v);
|
---|
| 480 | typedef typename type_traits<value_type>::real_type real_type;
|
---|
| 481 | real_type verrorbound (norm_1 (v) + norm_1 (e1) * norm_1 (e2));
|
---|
| 482 | indexing_vector_assign<scalar_plus_assign> (cv, prod (e1, e2));
|
---|
| 483 | #endif
|
---|
| 484 | axpy_prod (e1, e2, v, iterator_category ());
|
---|
| 485 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 486 | BOOST_UBLAS_CHECK (norm_1 (v - cv) <= 2 * std::numeric_limits<real_type>::epsilon () * verrorbound, internal_logic ());
|
---|
| 487 | #endif
|
---|
| 488 | return v;
|
---|
| 489 | }
|
---|
| 490 | template<class V, class E1, class E2>
|
---|
| 491 | BOOST_UBLAS_INLINE
|
---|
| 492 | V
|
---|
| 493 | axpy_prod (const vector_expression<E1> &e1,
|
---|
| 494 | const matrix_expression<E2> &e2) {
|
---|
| 495 | typedef V vector_type;
|
---|
| 496 |
|
---|
| 497 | vector_type v (e2 ().size2 ());
|
---|
| 498 | return axpy_prod (e1, e2, v, true);
|
---|
| 499 | }
|
---|
| 500 |
|
---|
| 501 | template<class M, class E1, class E2, class TRI>
|
---|
| 502 | BOOST_UBLAS_INLINE
|
---|
| 503 | M &
|
---|
| 504 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 505 | const matrix_expression<E2> &e2,
|
---|
| 506 | M &m, TRI,
|
---|
| 507 | dense_proxy_tag, row_major_tag) {
|
---|
| 508 | typedef M matrix_type;
|
---|
| 509 | typedef const E1 expression1_type;
|
---|
| 510 | typedef const E2 expression2_type;
|
---|
| 511 | typedef typename M::size_type size_type;
|
---|
| 512 | typedef typename M::value_type value_type;
|
---|
| 513 |
|
---|
| 514 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 515 | matrix<value_type, row_major> cm (m);
|
---|
| 516 | typedef typename type_traits<value_type>::real_type real_type;
|
---|
| 517 | real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
---|
| 518 | indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), row_major_tag ());
|
---|
| 519 | #endif
|
---|
| 520 | size_type size1 (e1 ().size1 ());
|
---|
| 521 | size_type size2 (e1 ().size2 ());
|
---|
| 522 | for (size_type i = 0; i < size1; ++ i)
|
---|
| 523 | for (size_type j = 0; j < size2; ++ j)
|
---|
| 524 | row (m, i).plus_assign (e1 () (i, j) * row (e2 (), j));
|
---|
| 525 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 526 | BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
---|
| 527 | #endif
|
---|
| 528 | return m;
|
---|
| 529 | }
|
---|
| 530 | template<class M, class E1, class E2, class TRI>
|
---|
| 531 | BOOST_UBLAS_INLINE
|
---|
| 532 | M &
|
---|
| 533 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 534 | const matrix_expression<E2> &e2,
|
---|
| 535 | M &m, TRI,
|
---|
| 536 | sparse_proxy_tag, row_major_tag) {
|
---|
| 537 | typedef M matrix_type;
|
---|
| 538 | typedef TRI triangular_restriction;
|
---|
| 539 | typedef const E1 expression1_type;
|
---|
| 540 | typedef const E2 expression2_type;
|
---|
| 541 | typedef typename M::size_type size_type;
|
---|
| 542 | typedef typename M::value_type value_type;
|
---|
| 543 |
|
---|
| 544 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 545 | matrix<value_type, row_major> cm (m);
|
---|
| 546 | typedef typename type_traits<value_type>::real_type real_type;
|
---|
| 547 | real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
---|
| 548 | indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), row_major_tag ());
|
---|
| 549 | #endif
|
---|
| 550 | typename expression1_type::const_iterator1 it1 (e1 ().begin1 ());
|
---|
| 551 | typename expression1_type::const_iterator1 it1_end (e1 ().end1 ());
|
---|
| 552 | while (it1 != it1_end) {
|
---|
| 553 | #ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
|
---|
| 554 | typename expression1_type::const_iterator2 it2 (it1.begin ());
|
---|
| 555 | typename expression1_type::const_iterator2 it2_end (it1.end ());
|
---|
| 556 | #else
|
---|
| 557 | typename expression1_type::const_iterator2 it2 (boost::numeric::ublas::begin (it1, iterator1_tag ()));
|
---|
| 558 | typename expression1_type::const_iterator2 it2_end (boost::numeric::ublas::end (it1, iterator1_tag ()));
|
---|
| 559 | #endif
|
---|
| 560 | while (it2 != it2_end) {
|
---|
| 561 | // row (m, it1.index1 ()).plus_assign (*it2 * row (e2 (), it2.index2 ()));
|
---|
| 562 | matrix_row<expression2_type> mr (e2 (), it2.index2 ());
|
---|
| 563 | typename matrix_row<expression2_type>::const_iterator itr (mr.begin ());
|
---|
| 564 | typename matrix_row<expression2_type>::const_iterator itr_end (mr.end ());
|
---|
| 565 | while (itr != itr_end) {
|
---|
| 566 | if (triangular_restriction::other (it1.index1 (), itr.index ()))
|
---|
| 567 | m (it1.index1 (), itr.index ()) += *it2 * *itr;
|
---|
| 568 | ++ itr;
|
---|
| 569 | }
|
---|
| 570 | ++ it2;
|
---|
| 571 | }
|
---|
| 572 | ++ it1;
|
---|
| 573 | }
|
---|
| 574 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 575 | BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
---|
| 576 | #endif
|
---|
| 577 | return m;
|
---|
| 578 | }
|
---|
| 579 |
|
---|
| 580 | template<class M, class E1, class E2, class TRI>
|
---|
| 581 | BOOST_UBLAS_INLINE
|
---|
| 582 | M &
|
---|
| 583 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 584 | const matrix_expression<E2> &e2,
|
---|
| 585 | M &m, TRI,
|
---|
| 586 | dense_proxy_tag, column_major_tag) {
|
---|
| 587 | typedef M matrix_type;
|
---|
| 588 | typedef const E1 expression1_type;
|
---|
| 589 | typedef const E2 expression2_type;
|
---|
| 590 | typedef typename M::size_type size_type;
|
---|
| 591 | typedef typename M::value_type value_type;
|
---|
| 592 |
|
---|
| 593 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 594 | matrix<value_type, column_major> cm (m);
|
---|
| 595 | typedef typename type_traits<value_type>::real_type real_type;
|
---|
| 596 | real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
---|
| 597 | indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), column_major_tag ());
|
---|
| 598 | #endif
|
---|
| 599 | size_type size1 (e2 ().size1 ());
|
---|
| 600 | size_type size2 (e2 ().size2 ());
|
---|
| 601 | for (size_type j = 0; j < size2; ++ j)
|
---|
| 602 | for (size_type i = 0; i < size1; ++ i)
|
---|
| 603 | column (m, j).plus_assign (e2 () (i, j) * column (e1 (), i));
|
---|
| 604 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 605 | BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
---|
| 606 | #endif
|
---|
| 607 | return m;
|
---|
| 608 | }
|
---|
| 609 | template<class M, class E1, class E2, class TRI>
|
---|
| 610 | BOOST_UBLAS_INLINE
|
---|
| 611 | M &
|
---|
| 612 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 613 | const matrix_expression<E2> &e2,
|
---|
| 614 | M &m, TRI,
|
---|
| 615 | sparse_proxy_tag, column_major_tag) {
|
---|
| 616 | typedef M matrix_type;
|
---|
| 617 | typedef TRI triangular_restriction;
|
---|
| 618 | typedef const E1 expression1_type;
|
---|
| 619 | typedef const E2 expression2_type;
|
---|
| 620 | typedef typename M::size_type size_type;
|
---|
| 621 | typedef typename M::value_type value_type;
|
---|
| 622 |
|
---|
| 623 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 624 | matrix<value_type, column_major> cm (m);
|
---|
| 625 | typedef typename type_traits<value_type>::real_type real_type;
|
---|
| 626 | real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
---|
| 627 | indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), column_major_tag ());
|
---|
| 628 | #endif
|
---|
| 629 | typename expression2_type::const_iterator2 it2 (e2 ().begin2 ());
|
---|
| 630 | typename expression2_type::const_iterator2 it2_end (e2 ().end2 ());
|
---|
| 631 | while (it2 != it2_end) {
|
---|
| 632 | #ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION
|
---|
| 633 | typename expression2_type::const_iterator1 it1 (it2.begin ());
|
---|
| 634 | typename expression2_type::const_iterator1 it1_end (it2.end ());
|
---|
| 635 | #else
|
---|
| 636 | typename expression2_type::const_iterator1 it1 (boost::numeric::ublas::begin (it2, iterator2_tag ()));
|
---|
| 637 | typename expression2_type::const_iterator1 it1_end (boost::numeric::ublas::end (it2, iterator2_tag ()));
|
---|
| 638 | #endif
|
---|
| 639 | while (it1 != it1_end) {
|
---|
| 640 | // column (m, it2.index2 ()).plus_assign (*it1 * column (e1 (), it1.index1 ()));
|
---|
| 641 | matrix_column<expression1_type> mc (e1 (), it1.index1 ());
|
---|
| 642 | typename matrix_column<expression1_type>::const_iterator itc (mc.begin ());
|
---|
| 643 | typename matrix_column<expression1_type>::const_iterator itc_end (mc.end ());
|
---|
| 644 | while (itc != itc_end) {
|
---|
| 645 | if (triangular_restriction::functor_type ().other (itc.index (), it2.index2 ()))
|
---|
| 646 | m (itc.index (), it2.index2 ()) += *it1 * *itc;
|
---|
| 647 | ++ itc;
|
---|
| 648 | }
|
---|
| 649 | ++ it1;
|
---|
| 650 | }
|
---|
| 651 | ++ it2;
|
---|
| 652 | }
|
---|
| 653 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 654 | BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
---|
| 655 | #endif
|
---|
| 656 | return m;
|
---|
| 657 | }
|
---|
| 658 |
|
---|
| 659 | // Dispatcher
|
---|
| 660 | template<class M, class E1, class E2, class TRI>
|
---|
| 661 | BOOST_UBLAS_INLINE
|
---|
| 662 | M &
|
---|
| 663 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 664 | const matrix_expression<E2> &e2,
|
---|
| 665 | M &m, TRI, bool init = true) {
|
---|
| 666 | typedef typename M::value_type value_type;
|
---|
| 667 | typedef typename M::storage_category storage_category;
|
---|
| 668 | typedef typename M::orientation_category orientation_category;
|
---|
| 669 | typedef TRI triangular_restriction;
|
---|
| 670 |
|
---|
| 671 | if (init)
|
---|
| 672 | m.assign (zero_matrix<value_type> (e1 ().size1 (), e2 ().size2 ()));
|
---|
| 673 | return axpy_prod (e1, e2, m, triangular_restriction (), storage_category (), orientation_category ());
|
---|
| 674 | }
|
---|
| 675 | template<class M, class E1, class E2, class TRI>
|
---|
| 676 | BOOST_UBLAS_INLINE
|
---|
| 677 | M
|
---|
| 678 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 679 | const matrix_expression<E2> &e2,
|
---|
| 680 | TRI) {
|
---|
| 681 | typedef M matrix_type;
|
---|
| 682 | typedef TRI triangular_restriction;
|
---|
| 683 |
|
---|
| 684 | matrix_type m (e1 ().size1 (), e2 ().size2 ());
|
---|
| 685 | return axpy_prod (e1, e2, m, triangular_restriction (), true);
|
---|
| 686 | }
|
---|
| 687 |
|
---|
| 688 | /** \brief computes <tt>M += A X</tt> or <tt>M = A X</tt> in an
|
---|
| 689 | optimized fashion.
|
---|
| 690 |
|
---|
| 691 | \param e1 the matrix expression \c A
|
---|
| 692 | \param e2 the matrix expression \c X
|
---|
| 693 | \param m the result matrix \c M
|
---|
| 694 | \param init a boolean parameter
|
---|
| 695 |
|
---|
| 696 | <tt>axpy_prod(A, X, M, init)</tt> implements the well known
|
---|
| 697 | axpy-product. Setting \a init to \c true is equivalent to call
|
---|
| 698 | <tt>M.clear()</tt> before <tt>axpy_prod</tt>. Currently \a init
|
---|
| 699 | defaults to \c true, but this may change in the future.
|
---|
| 700 |
|
---|
| 701 | Up to now there are no specialisations.
|
---|
| 702 |
|
---|
| 703 | \ingroup blas3
|
---|
| 704 |
|
---|
| 705 | \internal
|
---|
| 706 |
|
---|
| 707 | template parameters:
|
---|
| 708 | \param M type of the result matrix \c M
|
---|
| 709 | \param E1 type of a matrix expression \c A
|
---|
| 710 | \param E2 type of a matrix expression \c X
|
---|
| 711 | */
|
---|
| 712 | template<class M, class E1, class E2>
|
---|
| 713 | BOOST_UBLAS_INLINE
|
---|
| 714 | M &
|
---|
| 715 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 716 | const matrix_expression<E2> &e2,
|
---|
| 717 | M &m, bool init = true) {
|
---|
| 718 | typedef typename M::value_type value_type;
|
---|
| 719 | typedef typename M::storage_category storage_category;
|
---|
| 720 | typedef typename M::orientation_category orientation_category;
|
---|
| 721 |
|
---|
| 722 | if (init)
|
---|
| 723 | m.assign (zero_matrix<value_type> (e1 ().size1 (), e2 ().size2 ()));
|
---|
| 724 | return axpy_prod (e1, e2, m, full (), storage_category (), orientation_category ());
|
---|
| 725 | }
|
---|
| 726 | template<class M, class E1, class E2>
|
---|
| 727 | BOOST_UBLAS_INLINE
|
---|
| 728 | M
|
---|
| 729 | axpy_prod (const matrix_expression<E1> &e1,
|
---|
| 730 | const matrix_expression<E2> &e2) {
|
---|
| 731 | typedef M matrix_type;
|
---|
| 732 |
|
---|
| 733 | matrix_type m (e1 ().size1 (), e2 ().size2 ());
|
---|
| 734 | return axpy_prod (e1, e2, m, full (), true);
|
---|
| 735 | }
|
---|
| 736 |
|
---|
| 737 |
|
---|
| 738 | template<class M, class E1, class E2>
|
---|
| 739 | BOOST_UBLAS_INLINE
|
---|
| 740 | M &
|
---|
| 741 | opb_prod (const matrix_expression<E1> &e1,
|
---|
| 742 | const matrix_expression<E2> &e2,
|
---|
| 743 | M &m,
|
---|
| 744 | dense_proxy_tag, row_major_tag) {
|
---|
| 745 | typedef M matrix_type;
|
---|
| 746 | typedef const E1 expression1_type;
|
---|
| 747 | typedef const E2 expression2_type;
|
---|
| 748 | typedef typename M::size_type size_type;
|
---|
| 749 | typedef typename M::value_type value_type;
|
---|
| 750 |
|
---|
| 751 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 752 | matrix<value_type, row_major> cm (m);
|
---|
| 753 | typedef typename type_traits<value_type>::real_type real_type;
|
---|
| 754 | real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
---|
| 755 | indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), row_major_tag ());
|
---|
| 756 | #endif
|
---|
| 757 | size_type size (BOOST_UBLAS_SAME (e1 ().size2 (), e2 ().size1 ()));
|
---|
| 758 | for (size_type k = 0; k < size; ++ k) {
|
---|
| 759 | vector<value_type> ce1 (column (e1 (), k));
|
---|
| 760 | vector<value_type> re2 (row (e2 (), k));
|
---|
| 761 | m.plus_assign (outer_prod (ce1, re2));
|
---|
| 762 | }
|
---|
| 763 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 764 | BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
---|
| 765 | #endif
|
---|
| 766 | return m;
|
---|
| 767 | }
|
---|
| 768 |
|
---|
| 769 | template<class M, class E1, class E2>
|
---|
| 770 | BOOST_UBLAS_INLINE
|
---|
| 771 | M &
|
---|
| 772 | opb_prod (const matrix_expression<E1> &e1,
|
---|
| 773 | const matrix_expression<E2> &e2,
|
---|
| 774 | M &m,
|
---|
| 775 | dense_proxy_tag, column_major_tag) {
|
---|
| 776 | typedef M matrix_type;
|
---|
| 777 | typedef const E1 expression1_type;
|
---|
| 778 | typedef const E2 expression2_type;
|
---|
| 779 | typedef typename M::size_type size_type;
|
---|
| 780 | typedef typename M::value_type value_type;
|
---|
| 781 |
|
---|
| 782 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 783 | matrix<value_type, column_major> cm (m);
|
---|
| 784 | typedef typename type_traits<value_type>::real_type real_type;
|
---|
| 785 | real_type merrorbound (norm_1 (m) + norm_1 (e1) * norm_1 (e2));
|
---|
| 786 | indexing_matrix_assign<scalar_plus_assign> (cm, prod (e1, e2), column_major_tag ());
|
---|
| 787 | #endif
|
---|
| 788 | size_type size (BOOST_UBLAS_SAME (e1 ().size2 (), e2 ().size1 ()));
|
---|
| 789 | for (size_type k = 0; k < size; ++ k) {
|
---|
| 790 | vector<value_type> ce1 (column (e1 (), k));
|
---|
| 791 | vector<value_type> re2 (row (e2 (), k));
|
---|
| 792 | m.plus_assign (outer_prod (ce1, re2));
|
---|
| 793 | }
|
---|
| 794 | #if BOOST_UBLAS_TYPE_CHECK
|
---|
| 795 | BOOST_UBLAS_CHECK (norm_1 (m - cm) <= 2 * std::numeric_limits<real_type>::epsilon () * merrorbound, internal_logic ());
|
---|
| 796 | #endif
|
---|
| 797 | return m;
|
---|
| 798 | }
|
---|
| 799 |
|
---|
| 800 | // Dispatcher
|
---|
| 801 |
|
---|
| 802 | /** \brief computes <tt>M += A X</tt> or <tt>M = A X</tt> in an
|
---|
| 803 | optimized fashion.
|
---|
| 804 |
|
---|
| 805 | \param e1 the matrix expression \c A
|
---|
| 806 | \param e2 the matrix expression \c X
|
---|
| 807 | \param m the result matrix \c M
|
---|
| 808 | \param init a boolean parameter
|
---|
| 809 |
|
---|
| 810 | <tt>opb_prod(A, X, M, init)</tt> implements the well known
|
---|
| 811 | axpy-product. Setting \a init to \c true is equivalent to call
|
---|
| 812 | <tt>M.clear()</tt> before <tt>opb_prod</tt>. Currently \a init
|
---|
| 813 | defaults to \c true, but this may change in the future.
|
---|
| 814 |
|
---|
| 815 | This function may give a speedup if \c A has less columns than
|
---|
| 816 | rows, because the product is computed as a sum of outer
|
---|
| 817 | products.
|
---|
| 818 |
|
---|
| 819 | \ingroup blas3
|
---|
| 820 |
|
---|
| 821 | \internal
|
---|
| 822 |
|
---|
| 823 | template parameters:
|
---|
| 824 | \param M type of the result matrix \c M
|
---|
| 825 | \param E1 type of a matrix expression \c A
|
---|
| 826 | \param E2 type of a matrix expression \c X
|
---|
| 827 | */
|
---|
| 828 | template<class M, class E1, class E2>
|
---|
| 829 | BOOST_UBLAS_INLINE
|
---|
| 830 | M &
|
---|
| 831 | opb_prod (const matrix_expression<E1> &e1,
|
---|
| 832 | const matrix_expression<E2> &e2,
|
---|
| 833 | M &m, bool init = true) {
|
---|
| 834 | typedef typename M::value_type value_type;
|
---|
| 835 | typedef typename M::storage_category storage_category;
|
---|
| 836 | typedef typename M::orientation_category orientation_category;
|
---|
| 837 |
|
---|
| 838 | if (init)
|
---|
| 839 | m.assign (zero_matrix<value_type> (e1 ().size1 (), e2 ().size2 ()));
|
---|
| 840 | return opb_prod (e1, e2, m, storage_category (), orientation_category ());
|
---|
| 841 | }
|
---|
| 842 | template<class M, class E1, class E2>
|
---|
| 843 | BOOST_UBLAS_INLINE
|
---|
| 844 | M
|
---|
| 845 | opb_prod (const matrix_expression<E1> &e1,
|
---|
| 846 | const matrix_expression<E2> &e2) {
|
---|
| 847 | typedef M matrix_type;
|
---|
| 848 |
|
---|
| 849 | matrix_type m (e1 ().size1 (), e2 ().size2 ());
|
---|
| 850 | return opb_prod (e1, e2, m, true);
|
---|
| 851 | }
|
---|
| 852 |
|
---|
| 853 | }}}
|
---|
| 854 |
|
---|
| 855 | #endif
|
---|