/usr/include/viennacl/linalg/row_scaling.hpp is in libviennacl-dev 1.5.2-2.
This file is owned by root:root, with mode 0o644.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 | #ifndef VIENNACL_LINALG_ROW_SCALING_HPP_
#define VIENNACL_LINALG_ROW_SCALING_HPP_
/* =========================================================================
Copyright (c) 2010-2014, Institute for Microelectronics,
Institute for Analysis and Scientific Computing,
TU Wien.
Portions of this software are copyright by UChicago Argonne, LLC.
-----------------
ViennaCL - The Vienna Computing Library
-----------------
Project Head: Karl Rupp rupp@iue.tuwien.ac.at
(A list of authors and contributors can be found in the PDF manual)
License: MIT (X11), see file LICENSE in the base directory
============================================================================= */
/** @file viennacl/linalg/row_scaling.hpp
@brief A row normalization preconditioner is implemented here
*/
#include <vector>
#include <cmath>
#include "viennacl/forwards.h"
#include "viennacl/vector.hpp"
#include "viennacl/compressed_matrix.hpp"
#include "viennacl/tools/tools.hpp"
#include <map>
namespace viennacl
{
namespace linalg
{
/** @brief A tag for a row scaling preconditioner which merely normalizes the equation system such that each row of the system matrix has unit norm. */
class row_scaling_tag
{
public:
/** @brief Constructor
*
* @param p Integer selecting the desired row norm.
*/
row_scaling_tag(unsigned int p = 2) : norm_(p) {}
/** @brief Returns the index p of the l^p-norm (0 ... ||x||_sup, 1... sum(abs(x)), 2... sqrt(sum(x_i^2))). Currently only p=0, p=1, and p=2 supported.*/
unsigned int norm() const { return norm_; }
private:
unsigned int norm_;
};
/** \cond */
namespace detail
{
template <typename T>
struct row_scaling_for_viennacl
{
enum { value = false };
};
template <typename ScalarType, unsigned int ALIGNMENT>
struct row_scaling_for_viennacl< viennacl::compressed_matrix<ScalarType, ALIGNMENT> >
{
enum { value = true };
};
template <typename ScalarType, unsigned int ALIGNMENT>
struct row_scaling_for_viennacl< viennacl::coordinate_matrix<ScalarType, ALIGNMENT> >
{
enum { value = true };
};
}
/** \endcond */
/** @brief Jacobi-type preconditioner class, can be supplied to solve()-routines. This is a diagonal preconditioner with the diagonal entries being (configurable) row norms of the matrix.
*
* Default implementation for non-native ViennaCL matrices (e.g. uBLAS)
*/
template <typename MatrixType,
bool is_viennacl = detail::row_scaling_for_viennacl<MatrixType>::value >
class row_scaling
{
typedef typename MatrixType::value_type ScalarType;
public:
/** @brief Constructor for the preconditioner
*
* @param mat The system matrix
* @param tag A row scaling tag holding the desired norm.
*/
row_scaling(MatrixType const & mat, row_scaling_tag const & tag) : diag_M(viennacl::traits::size1(mat))
{
assert(mat.size1() == mat.size2() && bool("Size mismatch"));
init(mat, tag);
}
void init(MatrixType const & mat, row_scaling_tag const & tag)
{
diag_M.resize(mat.size1()); //resize without preserving values
for (typename MatrixType::const_iterator1 row_it = mat.begin1();
row_it != mat.end1();
++row_it)
{
for (typename MatrixType::const_iterator2 col_it = row_it.begin();
col_it != row_it.end();
++col_it)
{
if (tag.norm() == 0)
diag_M[col_it.index1()] = std::max<ScalarType>(diag_M[col_it.index1()], std::fabs(*col_it));
else if (tag.norm() == 1)
diag_M[col_it.index1()] += std::fabs(*col_it);
else if (tag.norm() == 2)
diag_M[col_it.index1()] += (*col_it) * (*col_it);
}
if (diag_M[row_it.index1()] == 0)
throw "ViennaCL: Zero row encountered while setting up row scaling preconditioner!";
if (tag.norm() == 2)
diag_M[row_it.index1()] = std::sqrt(diag_M[row_it.index1()]);
}
}
/** @brief Apply to res = b - Ax, i.e. row applied vec (right hand side), */
template <typename VectorType>
void apply(VectorType & vec) const
{
assert(vec.size() == diag_M.size() && bool("Size mismatch"));
for (vcl_size_t i=0; i<vec.size(); ++i)
vec[i] /= diag_M[i];
}
private:
std::vector<ScalarType> diag_M;
};
/** @brief Jacobi preconditioner class, can be supplied to solve()-routines.
*
* Specialization for compressed_matrix
*/
template <typename MatrixType>
class row_scaling< MatrixType, true>
{
typedef typename viennacl::result_of::cpu_value_type<typename MatrixType::value_type>::type ScalarType;
public:
/** @brief Constructor for the preconditioner
*
* @param mat The system matrix
* @param tag A row scaling tag holding the desired norm.
*/
row_scaling(MatrixType const & mat, row_scaling_tag const & tag) : diag_M(mat.size1(), viennacl::traits::context(mat))
{
init(mat, tag);
}
void init(MatrixType const & mat, row_scaling_tag const & tag)
{
switch (tag.norm())
{
case 0:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_INF);
break;
case 1:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_1);
break;
case 2:
detail::row_info(mat, diag_M, detail::SPARSE_ROW_NORM_2);
break;
default:
throw "Unknown norm!";
}
}
template <unsigned int ALIGNMENT>
void apply(viennacl::vector<ScalarType, ALIGNMENT> & vec) const
{
assert(viennacl::traits::size(diag_M) == viennacl::traits::size(vec) && bool("Size mismatch"));
vec = element_div(vec, diag_M);
}
private:
viennacl::vector<ScalarType> diag_M;
};
}
}
#endif
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