operation.hpp

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////  Copyright (c) 2000-2002//  Joerg Walter, Mathias Koch////  Distributed under the Boost Software License, Version 1.0. (See//  accompanying file LICENSE_1_0.txt or copy at//  http://www.boost.org/LICENSE_1_0.txt)////  The authors gratefully acknowledge the support of//  GeNeSys mbH & Co. KG in producing this work.//#ifndef _BOOST_UBLAS_OPERATION_#define _BOOST_UBLAS_OPERATION_#include <boost/numeric/ublas/matrix_proxy.hpp>/** \file operation.hpp *  \brief This file contains some specialized products. */// 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 L1, class IA1, class TA1, class E2>    BOOST_UBLAS_INLINE    V &    axpy_prod (const compressed_matrix<T1, L1, 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.filled1 () -1; ++ 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 L1, class IA1, class TA1, class E2>    BOOST_UBLAS_INLINE    V &    axpy_prod (const compressed_matrix<T1, L1, 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.filled1 () -1; ++ 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 L1, class IA1, class TA1, class E2>    BOOST_UBLAS_INLINE    V &    axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,               const vector_expression<E2> &e2,               V &v, bool init = true) {        typedef typename V::value_type value_type;        typedef typename L1::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> (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 L1, class IA1, class TA1, class E2>    BOOST_UBLAS_INLINE    V    axpy_prod (const compressed_matrix<T1, L1, 0, IA1, TA1> &e1,               const vector_expression<E2> &e2) {        typedef V vector_type;        vector_type v (e1.size1 ());        return axpy_prod (e1, e2, v, true);    }    template<class V, class T1, class L1, class IA1, class TA1, class E2>    BOOST_UBLAS_INLINE    V &    axpy_prod (const coordinate_matrix<T1, L1, 0, IA1, TA1> &e1,               const vector_expression<E2> &e2,               V &v, bool init = true) {        typedef typename V::size_type size_type;        typedef typename V::value_type value_type;        typedef L1 layout_type;        size_type size1 = e1.size1();        size_type size2 = e1.size2();        if (init) {            noalias(v) = zero_vector<value_type>(size1);        }        for (size_type i = 0; i < e1.nnz(); ++i) {            size_type row_index = layout_type::index_M( e1.index1_data () [i], e1.index2_data () [i] );            size_type col_index = layout_type::index_m( e1.index1_data () [i], e1.index2_data () [i] );            v( row_index ) += e1.value_data () [i] * e2 () (col_index);        }        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, 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> (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 ());        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.filled1 () -1; ++ j) {

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