📄 operation.hpp
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//// Copyright (c) 2000-2002// Joerg Walter, Mathias Koch//// Permission to use, copy, modify, distribute and sell this software// and its documentation for any purpose is hereby granted without fee,// provided that the above copyright notice appear in all copies and// that both that copyright notice and this permission notice appear// in supporting documentation. The authors make no representations// about the suitability of this software for any purpose.// It is provided "as is" without express or implied warranty.//// The authors gratefully acknowledge the support of// GeNeSys mbH & Co. KG in producing this work.///** \file operation.hpp * \brief This file contains some specialized products. */#ifndef BOOST_UBLAS_OPERATION_H#define BOOST_UBLAS_OPERATION_H// axpy-based products// Alexei Novakov had a lot of ideas to improve these. Thanks.// Hendrik Kueck proposed some new kernel. Thanks again.namespace boost { namespace numeric { namespace ublas { template<class V, class T1, class IA1, class TA1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const compressed_matrix<T1, row_major, 0, IA1, TA1> &e1, const vector_expression<E2> &e2, V &v, row_major_tag) { typedef typename V::size_type size_type; typedef typename V::value_type value_type; for (size_type i = 0; i < e1.size1 (); ++ i) { size_type begin = e1.index1_data () [i]; size_type end = e1.index1_data () [i + 1]; value_type t (v (i)); for (size_type j = begin; j < end; ++ j) t += e1.value_data () [j] * e2 () (e1.index2_data () [j]); v (i) = t; } return v; } template<class V, class T1, class IA1, class TA1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const compressed_matrix<T1, column_major, 0, IA1, TA1> &e1, const vector_expression<E2> &e2, V &v, column_major_tag) { typedef typename V::size_type size_type; for (size_type j = 0; j < e1.size2 (); ++ j) { size_type begin = e1.index1_data () [j]; size_type end = e1.index1_data () [j + 1]; for (size_type i = begin; i < end; ++ i) v (e1.index2_data () [i]) += e1.value_data () [i] * e2 () (j); } return v; } // Dispatcher template<class V, class T1, class F1, class IA1, class TA1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const compressed_matrix<T1, F1, 0, IA1, TA1> &e1, const vector_expression<E2> &e2, V &v, bool init = true) { typedef typename V::value_type value_type; typedef typename F1::orientation_category orientation_category; if (init) v.assign (zero_vector<value_type> (e1.size1 ()));#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<typename vector<value_type>::reference, value_type> (), cv, prod (e1, e2));#endif axpy_prod (e1, e2, v, orientation_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 T1, class F, class IA1, class TA1, class E2> BOOST_UBLAS_INLINE V axpy_prod (const compressed_matrix<T1, F, 0, IA1, TA1> &e1, const vector_expression<E2> &e2) { typedef V vector_type; vector_type v (e1.size1 ()); // FIXME: needed for c_matrix?! // return axpy_prod (e1, e2, v, false); return axpy_prod (e1, e2, v, true); } template<class V, class E1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const matrix_expression<E1> &e1, const vector_expression<E2> &e2, V &v, packed_random_access_iterator_tag, row_major_tag) { typedef const E1 expression1_type; typedef const E2 expression2_type; typedef typename V::size_type size_type; typename expression1_type::const_iterator1 it1 (e1 ().begin1 ()); typename expression1_type::const_iterator1 it1_end (e1 ().end1 ()); while (it1 != it1_end) { size_type index1 (it1.index1 ());#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) { v (index1) += *it2 * e2 () (it2.index2 ()); ++ it2; } ++ it1; } return v; } template<class V, class E1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const matrix_expression<E1> &e1, const vector_expression<E2> &e2, V &v, packed_random_access_iterator_tag, column_major_tag) { typedef const E1 expression1_type; typedef const E2 expression2_type; typedef typename V::size_type size_type; typename expression1_type::const_iterator2 it2 (e1 ().begin2 ()); typename expression1_type::const_iterator2 it2_end (e1 ().end2 ()); while (it2 != it2_end) { size_type index2 (it2.index2 ());#ifndef BOOST_UBLAS_NO_NESTED_CLASS_RELATION typename expression1_type::const_iterator1 it1 (it2.begin ()); typename expression1_type::const_iterator1 it1_end (it2.end ());#else typename expression1_type::const_iterator1 it1 (boost::numeric::ublas::begin (it2, iterator2_tag ())); typename expression1_type::const_iterator1 it1_end (boost::numeric::ublas::end (it2, iterator2_tag ()));#endif while (it1 != it1_end) { v (it1.index1 ()) += *it1 * e2 () (index2); ++ it1; } ++ it2; } return v; } template<class V, class E1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const matrix_expression<E1> &e1, const vector_expression<E2> &e2, V &v, sparse_bidirectional_iterator_tag) { typedef const E1 expression1_type; typedef const E2 expression2_type; typedef typename V::size_type size_type; typename expression2_type::const_iterator it (e2 ().begin ()); typename expression2_type::const_iterator it_end (e2 ().end ()); while (it != it_end) { v.plus_assign (column (e1 (), it.index ()) * *it); ++ it; } return v; } // Dispatcher template<class V, class E1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const matrix_expression<E1> &e1, const vector_expression<E2> &e2, V &v, packed_random_access_iterator_tag) { typedef typename E1::orientation_category orientation_category; return axpy_prod (e1, e2, v, packed_random_access_iterator_tag (), orientation_category ()); } /** \brief computes <tt>v += A x</tt> or <tt>v = A x</tt> in an optimized fashion. \param e1 the matrix expression \c A \param e2 the vector expression \c x \param v the result vector \c v \param init a boolean parameter <tt>axpy_prod(A, x, v, init)</tt> implements the well known axpy-product. Setting \a init to \c true is equivalent to call <tt>v.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 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 matrix expression \c A \param E2 type of a vector expression \c x */ template<class V, class E1, class E2> BOOST_UBLAS_INLINE V & axpy_prod (const matrix_expression<E1> &e1, const vector_expression<E2> &e2, V &v, bool init = true) { typedef typename V::value_type value_type; typedef typename E2::const_iterator::iterator_category iterator_category; if (init) v.assign (zero_vector<value_type> (e1 ().size1 ()));#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<typename vector<value_type>::reference, value_type> (), 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 matrix_expression<E1> &e1, const vector_expression<E2> &e2) { typedef V vector_type; vector_type v (e1 ().size1 ()); // FIXME: needed for c_matrix?! // return axpy_prod (e1, e2, v, false); return axpy_prod (e1, e2, v, true); } template<class V, class E1, class T2, class IA2, class TA2> BOOST_UBLAS_INLINE V & axpy_prod (const vector_expression<E1> &e1, const compressed_matrix<T2, column_major, 0, IA2, TA2> &e2, V &v, column_major_tag) { typedef typename V::size_type size_type; typedef typename V::value_type value_type; for (size_type j = 0; j < e2.size2 (); ++ j) { size_type begin = e2.index1_data () [j]; size_type end = e2.index1_data () [j + 1]; value_type t (v (j)); for (size_type i = begin; i < end; ++ i) t += e2.value_data () [i] * e1 () (e2.index2_data () [i]); v (j) = t; } return v; } template<class V, class E1, class T2, class IA2, class TA2> BOOST_UBLAS_INLINE V & axpy_prod (const vector_expression<E1> &e1, const compressed_matrix<T2, row_major, 0, IA2, TA2> &e2, V &v, row_major_tag) { typedef typename V::size_type size_type; for (size_type i = 0; i < e2.size1 (); ++ i) { size_type begin = e2.index1_data () [i]; size_type end = e2.index1_data () [i + 1]; for (size_type j = begin; j < end; ++ j) v (e2.index2_data () [j]) += e2.value_data () [j] * e1 () (i); } return v; }
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