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1 /* glpspm.c */ |
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2 |
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3 /*********************************************************************** |
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4 * This code is part of GLPK (GNU Linear Programming Kit). |
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5 * |
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6 * Copyright (C) 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, |
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7 * 2009, 2010 Andrew Makhorin, Department for Applied Informatics, |
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8 * Moscow Aviation Institute, Moscow, Russia. All rights reserved. |
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9 * E-mail: <mao@gnu.org>. |
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10 * |
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11 * GLPK is free software: you can redistribute it and/or modify it |
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12 * under the terms of the GNU General Public License as published by |
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13 * the Free Software Foundation, either version 3 of the License, or |
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14 * (at your option) any later version. |
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15 * |
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16 * GLPK is distributed in the hope that it will be useful, but WITHOUT |
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17 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY |
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18 * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public |
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19 * License for more details. |
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20 * |
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21 * You should have received a copy of the GNU General Public License |
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22 * along with GLPK. If not, see <http://www.gnu.org/licenses/>. |
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23 ***********************************************************************/ |
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24 |
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25 #include "glphbm.h" |
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26 #include "glprgr.h" |
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27 #include "glpspm.h" |
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28 |
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29 /*********************************************************************** |
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30 * NAME |
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31 * |
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32 * spm_create_mat - create general sparse matrix |
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33 * |
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34 * SYNOPSIS |
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35 * |
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36 * #include "glpspm.h" |
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37 * SPM *spm_create_mat(int m, int n); |
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38 * |
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39 * DESCRIPTION |
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40 * |
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41 * The routine spm_create_mat creates a general sparse matrix having |
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42 * m rows and n columns. Being created the matrix is zero (empty), i.e. |
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43 * has no elements. |
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44 * |
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45 * RETURNS |
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46 * |
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47 * The routine returns a pointer to the matrix created. */ |
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48 |
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49 SPM *spm_create_mat(int m, int n) |
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50 { SPM *A; |
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51 xassert(0 <= m && m < INT_MAX); |
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52 xassert(0 <= n && n < INT_MAX); |
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53 A = xmalloc(sizeof(SPM)); |
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54 A->m = m; |
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55 A->n = n; |
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56 if (m == 0 || n == 0) |
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57 { A->pool = NULL; |
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58 A->row = NULL; |
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59 A->col = NULL; |
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60 } |
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61 else |
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62 { int i, j; |
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63 A->pool = dmp_create_pool(); |
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64 A->row = xcalloc(1+m, sizeof(SPME *)); |
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65 for (i = 1; i <= m; i++) A->row[i] = NULL; |
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66 A->col = xcalloc(1+n, sizeof(SPME *)); |
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67 for (j = 1; j <= n; j++) A->col[j] = NULL; |
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68 } |
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69 return A; |
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70 } |
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71 |
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72 /*********************************************************************** |
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73 * NAME |
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74 * |
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75 * spm_new_elem - add new element to sparse matrix |
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76 * |
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77 * SYNOPSIS |
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78 * |
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79 * #include "glpspm.h" |
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80 * SPME *spm_new_elem(SPM *A, int i, int j, double val); |
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81 * |
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82 * DESCRIPTION |
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83 * |
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84 * The routine spm_new_elem adds a new element to the specified sparse |
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85 * matrix. Parameters i, j, and val specify the row number, the column |
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86 * number, and a numerical value of the element, respectively. |
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87 * |
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88 * RETURNS |
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89 * |
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90 * The routine returns a pointer to the new element added. */ |
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91 |
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92 SPME *spm_new_elem(SPM *A, int i, int j, double val) |
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93 { SPME *e; |
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94 xassert(1 <= i && i <= A->m); |
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95 xassert(1 <= j && j <= A->n); |
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96 e = dmp_get_atom(A->pool, sizeof(SPME)); |
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97 e->i = i; |
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98 e->j = j; |
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99 e->val = val; |
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100 e->r_prev = NULL; |
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101 e->r_next = A->row[i]; |
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102 if (e->r_next != NULL) e->r_next->r_prev = e; |
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103 e->c_prev = NULL; |
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104 e->c_next = A->col[j]; |
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105 if (e->c_next != NULL) e->c_next->c_prev = e; |
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106 A->row[i] = A->col[j] = e; |
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107 return e; |
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108 } |
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109 |
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110 /*********************************************************************** |
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111 * NAME |
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112 * |
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113 * spm_delete_mat - delete general sparse matrix |
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114 * |
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115 * SYNOPSIS |
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116 * |
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117 * #include "glpspm.h" |
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118 * void spm_delete_mat(SPM *A); |
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119 * |
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120 * DESCRIPTION |
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121 * |
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122 * The routine deletes the specified general sparse matrix freeing all |
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123 * the memory allocated to this object. */ |
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124 |
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125 void spm_delete_mat(SPM *A) |
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126 { /* delete sparse matrix */ |
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127 if (A->pool != NULL) dmp_delete_pool(A->pool); |
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128 if (A->row != NULL) xfree(A->row); |
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129 if (A->col != NULL) xfree(A->col); |
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130 xfree(A); |
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131 return; |
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132 } |
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133 |
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134 /*********************************************************************** |
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135 * NAME |
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136 * |
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137 * spm_test_mat_e - create test sparse matrix of E(n,c) class |
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138 * |
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139 * SYNOPSIS |
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140 * |
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141 * #include "glpspm.h" |
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142 * SPM *spm_test_mat_e(int n, int c); |
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143 * |
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144 * DESCRIPTION |
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145 * |
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146 * The routine spm_test_mat_e creates a test sparse matrix of E(n,c) |
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147 * class as described in the book: Ole 0sterby, Zahari Zlatev. Direct |
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148 * Methods for Sparse Matrices. Springer-Verlag, 1983. |
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149 * |
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150 * Matrix of E(n,c) class is a symmetric positive definite matrix of |
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151 * the order n. It has the number 4 on its main diagonal and the number |
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152 * -1 on its four co-diagonals, two of which are neighbour to the main |
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153 * diagonal and two others are shifted from the main diagonal on the |
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154 * distance c. |
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155 * |
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156 * It is necessary that n >= 3 and 2 <= c <= n-1. |
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157 * |
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158 * RETURNS |
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159 * |
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160 * The routine returns a pointer to the matrix created. */ |
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161 |
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162 SPM *spm_test_mat_e(int n, int c) |
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163 { SPM *A; |
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164 int i; |
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165 xassert(n >= 3 && 2 <= c && c <= n-1); |
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166 A = spm_create_mat(n, n); |
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167 for (i = 1; i <= n; i++) |
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168 spm_new_elem(A, i, i, 4.0); |
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169 for (i = 1; i <= n-1; i++) |
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170 { spm_new_elem(A, i, i+1, -1.0); |
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171 spm_new_elem(A, i+1, i, -1.0); |
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172 } |
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173 for (i = 1; i <= n-c; i++) |
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174 { spm_new_elem(A, i, i+c, -1.0); |
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175 spm_new_elem(A, i+c, i, -1.0); |
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176 } |
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177 return A; |
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178 } |
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179 |
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180 /*********************************************************************** |
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181 * NAME |
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182 * |
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183 * spm_test_mat_d - create test sparse matrix of D(n,c) class |
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184 * |
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185 * SYNOPSIS |
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186 * |
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187 * #include "glpspm.h" |
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188 * SPM *spm_test_mat_d(int n, int c); |
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189 * |
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190 * DESCRIPTION |
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191 * |
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192 * The routine spm_test_mat_d creates a test sparse matrix of D(n,c) |
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193 * class as described in the book: Ole 0sterby, Zahari Zlatev. Direct |
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194 * Methods for Sparse Matrices. Springer-Verlag, 1983. |
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195 * |
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196 * Matrix of D(n,c) class is a non-singular matrix of the order n. It |
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197 * has unity main diagonal, three co-diagonals above the main diagonal |
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198 * on the distance c, which are cyclically continued below the main |
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199 * diagonal, and a triangle block of the size 10x10 in the upper right |
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200 * corner. |
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201 * |
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202 * It is necessary that n >= 14 and 1 <= c <= n-13. |
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203 * |
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204 * RETURNS |
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205 * |
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206 * The routine returns a pointer to the matrix created. */ |
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207 |
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208 SPM *spm_test_mat_d(int n, int c) |
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209 { SPM *A; |
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210 int i, j; |
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211 xassert(n >= 14 && 1 <= c && c <= n-13); |
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212 A = spm_create_mat(n, n); |
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213 for (i = 1; i <= n; i++) |
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214 spm_new_elem(A, i, i, 1.0); |
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215 for (i = 1; i <= n-c; i++) |
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216 spm_new_elem(A, i, i+c, (double)(i+1)); |
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217 for (i = n-c+1; i <= n; i++) |
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218 spm_new_elem(A, i, i-n+c, (double)(i+1)); |
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219 for (i = 1; i <= n-c-1; i++) |
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220 spm_new_elem(A, i, i+c+1, (double)(-i)); |
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221 for (i = n-c; i <= n; i++) |
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222 spm_new_elem(A, i, i-n+c+1, (double)(-i)); |
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223 for (i = 1; i <= n-c-2; i++) |
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224 spm_new_elem(A, i, i+c+2, 16.0); |
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225 for (i = n-c-1; i <= n; i++) |
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226 spm_new_elem(A, i, i-n+c+2, 16.0); |
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227 for (j = 1; j <= 10; j++) |
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228 for (i = 1; i <= 11-j; i++) |
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229 spm_new_elem(A, i, n-11+i+j, 100.0 * (double)j); |
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230 return A; |
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231 } |
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232 |
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233 /*********************************************************************** |
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234 * NAME |
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235 * |
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236 * spm_show_mat - write sparse matrix pattern in BMP file format |
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237 * |
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238 * SYNOPSIS |
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239 * |
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240 * #include "glpspm.h" |
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241 * int spm_show_mat(const SPM *A, const char *fname); |
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242 * |
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243 * DESCRIPTION |
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244 * |
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245 * The routine spm_show_mat writes pattern of the specified sparse |
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246 * matrix in uncompressed BMP file format (Windows bitmap) to a binary |
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247 * file whose name is specified by the character string fname. |
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248 * |
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249 * Each pixel corresponds to one matrix element. The pixel colors have |
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250 * the following meaning: |
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251 * |
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252 * Black structurally zero element |
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253 * White positive element |
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254 * Cyan negative element |
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255 * Green zero element |
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256 * Red duplicate element |
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257 * |
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258 * RETURNS |
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259 * |
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260 * If no error occured, the routine returns zero. Otherwise, it prints |
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261 * an appropriate error message and returns non-zero. */ |
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262 |
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263 int spm_show_mat(const SPM *A, const char *fname) |
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264 { int m = A->m; |
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265 int n = A->n; |
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266 int i, j, k, ret; |
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267 char *map; |
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268 xprintf("spm_show_mat: writing matrix pattern to `%s'...\n", |
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269 fname); |
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270 xassert(1 <= m && m <= 32767); |
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271 xassert(1 <= n && n <= 32767); |
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272 map = xmalloc(m * n); |
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273 memset(map, 0x08, m * n); |
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274 for (i = 1; i <= m; i++) |
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275 { SPME *e; |
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276 for (e = A->row[i]; e != NULL; e = e->r_next) |
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277 { j = e->j; |
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278 xassert(1 <= j && j <= n); |
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279 k = n * (i - 1) + (j - 1); |
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280 if (map[k] != 0x08) |
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281 map[k] = 0x0C; |
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282 else if (e->val > 0.0) |
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283 map[k] = 0x0F; |
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284 else if (e->val < 0.0) |
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285 map[k] = 0x0B; |
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286 else |
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287 map[k] = 0x0A; |
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288 } |
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289 } |
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290 ret = rgr_write_bmp16(fname, m, n, map); |
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291 xfree(map); |
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292 return ret; |
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293 } |
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294 |
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295 /*********************************************************************** |
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296 * NAME |
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297 * |
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298 * spm_read_hbm - read sparse matrix in Harwell-Boeing format |
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299 * |
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300 * SYNOPSIS |
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301 * |
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302 * #include "glpspm.h" |
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303 * SPM *spm_read_hbm(const char *fname); |
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304 * |
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305 * DESCRIPTION |
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306 * |
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307 * The routine spm_read_hbm reads a sparse matrix in the Harwell-Boeing |
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308 * format from a text file whose name is the character string fname. |
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309 * |
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310 * Detailed description of the Harwell-Boeing format recognised by this |
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311 * routine can be found in the following report: |
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312 * |
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313 * I.S.Duff, R.G.Grimes, J.G.Lewis. User's Guide for the Harwell-Boeing |
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314 * Sparse Matrix Collection (Release I), TR/PA/92/86, October 1992. |
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315 * |
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316 * NOTE |
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317 * |
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318 * The routine spm_read_hbm reads the matrix "as is", due to which zero |
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319 * and/or duplicate elements can appear in the matrix. |
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320 * |
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321 * RETURNS |
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322 * |
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323 * If no error occured, the routine returns a pointer to the matrix |
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324 * created. Otherwise, the routine prints an appropriate error message |
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325 * and returns NULL. */ |
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326 |
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327 SPM *spm_read_hbm(const char *fname) |
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328 { SPM *A = NULL; |
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329 HBM *hbm; |
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330 int nrow, ncol, nnzero, i, j, beg, end, ptr, *colptr, *rowind; |
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331 double val, *values; |
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332 char *mxtype; |
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333 hbm = hbm_read_mat(fname); |
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334 if (hbm == NULL) |
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335 { xprintf("spm_read_hbm: unable to read matrix\n"); |
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336 goto fini; |
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337 } |
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338 mxtype = hbm->mxtype; |
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339 nrow = hbm->nrow; |
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340 ncol = hbm->ncol; |
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341 nnzero = hbm->nnzero; |
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342 colptr = hbm->colptr; |
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343 rowind = hbm->rowind; |
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344 values = hbm->values; |
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345 if (!(strcmp(mxtype, "RSA") == 0 || strcmp(mxtype, "PSA") == 0 || |
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346 strcmp(mxtype, "RUA") == 0 || strcmp(mxtype, "PUA") == 0 || |
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347 strcmp(mxtype, "RRA") == 0 || strcmp(mxtype, "PRA") == 0)) |
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348 { xprintf("spm_read_hbm: matrix type `%s' not supported\n", |
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349 mxtype); |
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350 goto fini; |
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351 } |
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352 A = spm_create_mat(nrow, ncol); |
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353 if (mxtype[1] == 'S' || mxtype[1] == 'U') |
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354 xassert(nrow == ncol); |
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355 for (j = 1; j <= ncol; j++) |
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356 { beg = colptr[j]; |
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357 end = colptr[j+1]; |
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358 xassert(1 <= beg && beg <= end && end <= nnzero + 1); |
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359 for (ptr = beg; ptr < end; ptr++) |
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360 { i = rowind[ptr]; |
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361 xassert(1 <= i && i <= nrow); |
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362 if (mxtype[0] == 'R') |
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363 val = values[ptr]; |
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364 else |
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365 val = 1.0; |
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366 spm_new_elem(A, i, j, val); |
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367 if (mxtype[1] == 'S' && i != j) |
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368 spm_new_elem(A, j, i, val); |
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369 } |
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370 } |
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371 fini: if (hbm != NULL) hbm_free_mat(hbm); |
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372 return A; |
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373 } |
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374 |
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375 /*********************************************************************** |
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376 * NAME |
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377 * |
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378 * spm_count_nnz - determine number of non-zeros in sparse matrix |
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379 * |
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380 * SYNOPSIS |
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381 * |
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382 * #include "glpspm.h" |
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383 * int spm_count_nnz(const SPM *A); |
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384 * |
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385 * RETURNS |
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386 * |
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387 * The routine spm_count_nnz returns the number of structural non-zero |
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388 * elements in the specified sparse matrix. */ |
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389 |
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390 int spm_count_nnz(const SPM *A) |
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391 { SPME *e; |
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392 int i, nnz = 0; |
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393 for (i = 1; i <= A->m; i++) |
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394 for (e = A->row[i]; e != NULL; e = e->r_next) nnz++; |
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395 return nnz; |
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396 } |
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397 |
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398 /*********************************************************************** |
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399 * NAME |
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400 * |
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401 * spm_drop_zeros - remove zero elements from sparse matrix |
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402 * |
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403 * SYNOPSIS |
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404 * |
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405 * #include "glpspm.h" |
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406 * int spm_drop_zeros(SPM *A, double eps); |
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407 * |
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408 * DESCRIPTION |
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409 * |
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410 * The routine spm_drop_zeros removes all elements from the specified |
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411 * sparse matrix, whose absolute value is less than eps. |
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412 * |
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413 * If the parameter eps is 0, only zero elements are removed from the |
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414 * matrix. |
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415 * |
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416 * RETURNS |
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417 * |
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418 * The routine returns the number of elements removed. */ |
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419 |
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420 int spm_drop_zeros(SPM *A, double eps) |
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421 { SPME *e, *next; |
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422 int i, count = 0; |
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423 for (i = 1; i <= A->m; i++) |
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424 { for (e = A->row[i]; e != NULL; e = next) |
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425 { next = e->r_next; |
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426 if (e->val == 0.0 || fabs(e->val) < eps) |
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427 { /* remove element from the row list */ |
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428 if (e->r_prev == NULL) |
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429 A->row[e->i] = e->r_next; |
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430 else |
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431 e->r_prev->r_next = e->r_next; |
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432 if (e->r_next == NULL) |
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433 ; |
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434 else |
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435 e->r_next->r_prev = e->r_prev; |
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436 /* remove element from the column list */ |
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437 if (e->c_prev == NULL) |
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438 A->col[e->j] = e->c_next; |
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439 else |
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440 e->c_prev->c_next = e->c_next; |
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441 if (e->c_next == NULL) |
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442 ; |
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443 else |
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444 e->c_next->c_prev = e->c_prev; |
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445 /* return element to the memory pool */ |
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446 dmp_free_atom(A->pool, e, sizeof(SPME)); |
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447 count++; |
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448 } |
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449 } |
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450 } |
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451 return count; |
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452 } |
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453 |
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454 /*********************************************************************** |
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455 * NAME |
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456 * |
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457 * spm_read_mat - read sparse matrix from text file |
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458 * |
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459 * SYNOPSIS |
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460 * |
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461 * #include "glpspm.h" |
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462 * SPM *spm_read_mat(const char *fname); |
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463 * |
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464 * DESCRIPTION |
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465 * |
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466 * The routine reads a sparse matrix from a text file whose name is |
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467 * specified by the parameter fname. |
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468 * |
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469 * For the file format see description of the routine spm_write_mat. |
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470 * |
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471 * RETURNS |
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472 * |
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473 * On success the routine returns a pointer to the matrix created, |
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474 * otherwise NULL. */ |
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475 |
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476 #if 1 |
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477 SPM *spm_read_mat(const char *fname) |
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478 { xassert(fname != fname); |
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479 return NULL; |
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480 } |
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481 #else |
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482 SPM *spm_read_mat(const char *fname) |
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483 { SPM *A = NULL; |
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484 PDS *pds; |
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485 jmp_buf jump; |
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486 int i, j, k, m, n, nnz, fail = 0; |
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487 double val; |
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488 xprintf("spm_read_mat: reading matrix from `%s'...\n", fname); |
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489 pds = pds_open_file(fname); |
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490 if (pds == NULL) |
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491 { xprintf("spm_read_mat: unable to open `%s' - %s\n", fname, |
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492 strerror(errno)); |
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493 fail = 1; |
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494 goto done; |
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495 } |
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496 if (setjmp(jump)) |
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497 { fail = 1; |
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498 goto done; |
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499 } |
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500 pds_set_jump(pds, jump); |
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501 /* number of rows, number of columns, number of non-zeros */ |
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502 m = pds_scan_int(pds); |
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503 if (m < 0) |
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504 pds_error(pds, "invalid number of rows\n"); |
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505 n = pds_scan_int(pds); |
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506 if (n < 0) |
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507 pds_error(pds, "invalid number of columns\n"); |
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508 nnz = pds_scan_int(pds); |
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509 if (nnz < 0) |
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510 pds_error(pds, "invalid number of non-zeros\n"); |
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511 /* create matrix */ |
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512 xprintf("spm_read_mat: %d rows, %d columns, %d non-zeros\n", |
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513 m, n, nnz); |
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514 A = spm_create_mat(m, n); |
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515 /* read matrix elements */ |
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516 for (k = 1; k <= nnz; k++) |
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517 { /* row index, column index, element value */ |
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518 i = pds_scan_int(pds); |
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519 if (!(1 <= i && i <= m)) |
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520 pds_error(pds, "row index out of range\n"); |
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521 j = pds_scan_int(pds); |
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522 if (!(1 <= j && j <= n)) |
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523 pds_error(pds, "column index out of range\n"); |
|
524 val = pds_scan_num(pds); |
|
525 /* add new element to the matrix */ |
|
526 spm_new_elem(A, i, j, val); |
|
527 } |
|
528 xprintf("spm_read_mat: %d lines were read\n", pds->count); |
|
529 done: if (pds != NULL) pds_close_file(pds); |
|
530 if (fail && A != NULL) spm_delete_mat(A), A = NULL; |
|
531 return A; |
|
532 } |
|
533 #endif |
|
534 |
|
535 /*********************************************************************** |
|
536 * NAME |
|
537 * |
|
538 * spm_write_mat - write sparse matrix to text file |
|
539 * |
|
540 * SYNOPSIS |
|
541 * |
|
542 * #include "glpspm.h" |
|
543 * int spm_write_mat(const SPM *A, const char *fname); |
|
544 * |
|
545 * DESCRIPTION |
|
546 * |
|
547 * The routine spm_write_mat writes the specified sparse matrix to a |
|
548 * text file whose name is specified by the parameter fname. This file |
|
549 * can be read back with the routine spm_read_mat. |
|
550 * |
|
551 * RETURNS |
|
552 * |
|
553 * On success the routine returns zero, otherwise non-zero. |
|
554 * |
|
555 * FILE FORMAT |
|
556 * |
|
557 * The file created by the routine spm_write_mat is a plain text file, |
|
558 * which contains the following information: |
|
559 * |
|
560 * m n nnz |
|
561 * row[1] col[1] val[1] |
|
562 * row[2] col[2] val[2] |
|
563 * . . . |
|
564 * row[nnz] col[nnz] val[nnz] |
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565 * |
|
566 * where: |
|
567 * m is the number of rows; |
|
568 * n is the number of columns; |
|
569 * nnz is the number of non-zeros; |
|
570 * row[k], k = 1,...,nnz, are row indices; |
|
571 * col[k], k = 1,...,nnz, are column indices; |
|
572 * val[k], k = 1,...,nnz, are element values. */ |
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573 |
|
574 #if 1 |
|
575 int spm_write_mat(const SPM *A, const char *fname) |
|
576 { xassert(A != A); |
|
577 xassert(fname != fname); |
|
578 return 0; |
|
579 } |
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580 #else |
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581 int spm_write_mat(const SPM *A, const char *fname) |
|
582 { FILE *fp; |
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583 int i, nnz, ret = 0; |
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584 xprintf("spm_write_mat: writing matrix to `%s'...\n", fname); |
|
585 fp = fopen(fname, "w"); |
|
586 if (fp == NULL) |
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587 { xprintf("spm_write_mat: unable to create `%s' - %s\n", fname, |
|
588 strerror(errno)); |
|
589 ret = 1; |
|
590 goto done; |
|
591 } |
|
592 /* number of rows, number of columns, number of non-zeros */ |
|
593 nnz = spm_count_nnz(A); |
|
594 fprintf(fp, "%d %d %d\n", A->m, A->n, nnz); |
|
595 /* walk through rows of the matrix */ |
|
596 for (i = 1; i <= A->m; i++) |
|
597 { SPME *e; |
|
598 /* walk through elements of i-th row */ |
|
599 for (e = A->row[i]; e != NULL; e = e->r_next) |
|
600 { /* row index, column index, element value */ |
|
601 fprintf(fp, "%d %d %.*g\n", e->i, e->j, DBL_DIG, e->val); |
|
602 } |
|
603 } |
|
604 fflush(fp); |
|
605 if (ferror(fp)) |
|
606 { xprintf("spm_write_mat: writing error on `%s' - %s\n", fname, |
|
607 strerror(errno)); |
|
608 ret = 1; |
|
609 goto done; |
|
610 } |
|
611 xprintf("spm_write_mat: %d lines were written\n", 1 + nnz); |
|
612 done: if (fp != NULL) fclose(fp); |
|
613 return ret; |
|
614 } |
|
615 #endif |
|
616 |
|
617 /*********************************************************************** |
|
618 * NAME |
|
619 * |
|
620 * spm_transpose - transpose sparse matrix |
|
621 * |
|
622 * SYNOPSIS |
|
623 * |
|
624 * #include "glpspm.h" |
|
625 * SPM *spm_transpose(const SPM *A); |
|
626 * |
|
627 * RETURNS |
|
628 * |
|
629 * The routine computes and returns sparse matrix B, which is a matrix |
|
630 * transposed to sparse matrix A. */ |
|
631 |
|
632 SPM *spm_transpose(const SPM *A) |
|
633 { SPM *B; |
|
634 int i; |
|
635 B = spm_create_mat(A->n, A->m); |
|
636 for (i = 1; i <= A->m; i++) |
|
637 { SPME *e; |
|
638 for (e = A->row[i]; e != NULL; e = e->r_next) |
|
639 spm_new_elem(B, e->j, i, e->val); |
|
640 } |
|
641 return B; |
|
642 } |
|
643 |
|
644 SPM *spm_add_sym(const SPM *A, const SPM *B) |
|
645 { /* add two sparse matrices (symbolic phase) */ |
|
646 SPM *C; |
|
647 int i, j, *flag; |
|
648 xassert(A->m == B->m); |
|
649 xassert(A->n == B->n); |
|
650 /* create resultant matrix */ |
|
651 C = spm_create_mat(A->m, A->n); |
|
652 /* allocate and clear the flag array */ |
|
653 flag = xcalloc(1+C->n, sizeof(int)); |
|
654 for (j = 1; j <= C->n; j++) |
|
655 flag[j] = 0; |
|
656 /* compute pattern of C = A + B */ |
|
657 for (i = 1; i <= C->m; i++) |
|
658 { SPME *e; |
|
659 /* at the beginning i-th row of C is empty */ |
|
660 /* (i-th row of C) := (i-th row of C) union (i-th row of A) */ |
|
661 for (e = A->row[i]; e != NULL; e = e->r_next) |
|
662 { /* (note that i-th row of A may have duplicate elements) */ |
|
663 j = e->j; |
|
664 if (!flag[j]) |
|
665 { spm_new_elem(C, i, j, 0.0); |
|
666 flag[j] = 1; |
|
667 } |
|
668 } |
|
669 /* (i-th row of C) := (i-th row of C) union (i-th row of B) */ |
|
670 for (e = B->row[i]; e != NULL; e = e->r_next) |
|
671 { /* (note that i-th row of B may have duplicate elements) */ |
|
672 j = e->j; |
|
673 if (!flag[j]) |
|
674 { spm_new_elem(C, i, j, 0.0); |
|
675 flag[j] = 1; |
|
676 } |
|
677 } |
|
678 /* reset the flag array */ |
|
679 for (e = C->row[i]; e != NULL; e = e->r_next) |
|
680 flag[e->j] = 0; |
|
681 } |
|
682 /* check and deallocate the flag array */ |
|
683 for (j = 1; j <= C->n; j++) |
|
684 xassert(!flag[j]); |
|
685 xfree(flag); |
|
686 return C; |
|
687 } |
|
688 |
|
689 void spm_add_num(SPM *C, double alfa, const SPM *A, double beta, |
|
690 const SPM *B) |
|
691 { /* add two sparse matrices (numeric phase) */ |
|
692 int i, j; |
|
693 double *work; |
|
694 /* allocate and clear the working array */ |
|
695 work = xcalloc(1+C->n, sizeof(double)); |
|
696 for (j = 1; j <= C->n; j++) |
|
697 work[j] = 0.0; |
|
698 /* compute matrix C = alfa * A + beta * B */ |
|
699 for (i = 1; i <= C->n; i++) |
|
700 { SPME *e; |
|
701 /* work := alfa * (i-th row of A) + beta * (i-th row of B) */ |
|
702 /* (note that A and/or B may have duplicate elements) */ |
|
703 for (e = A->row[i]; e != NULL; e = e->r_next) |
|
704 work[e->j] += alfa * e->val; |
|
705 for (e = B->row[i]; e != NULL; e = e->r_next) |
|
706 work[e->j] += beta * e->val; |
|
707 /* (i-th row of C) := work, work := 0 */ |
|
708 for (e = C->row[i]; e != NULL; e = e->r_next) |
|
709 { j = e->j; |
|
710 e->val = work[j]; |
|
711 work[j] = 0.0; |
|
712 } |
|
713 } |
|
714 /* check and deallocate the working array */ |
|
715 for (j = 1; j <= C->n; j++) |
|
716 xassert(work[j] == 0.0); |
|
717 xfree(work); |
|
718 return; |
|
719 } |
|
720 |
|
721 SPM *spm_add_mat(double alfa, const SPM *A, double beta, const SPM *B) |
|
722 { /* add two sparse matrices (driver routine) */ |
|
723 SPM *C; |
|
724 C = spm_add_sym(A, B); |
|
725 spm_add_num(C, alfa, A, beta, B); |
|
726 return C; |
|
727 } |
|
728 |
|
729 SPM *spm_mul_sym(const SPM *A, const SPM *B) |
|
730 { /* multiply two sparse matrices (symbolic phase) */ |
|
731 int i, j, k, *flag; |
|
732 SPM *C; |
|
733 xassert(A->n == B->m); |
|
734 /* create resultant matrix */ |
|
735 C = spm_create_mat(A->m, B->n); |
|
736 /* allocate and clear the flag array */ |
|
737 flag = xcalloc(1+C->n, sizeof(int)); |
|
738 for (j = 1; j <= C->n; j++) |
|
739 flag[j] = 0; |
|
740 /* compute pattern of C = A * B */ |
|
741 for (i = 1; i <= C->m; i++) |
|
742 { SPME *e, *ee; |
|
743 /* compute pattern of i-th row of C */ |
|
744 for (e = A->row[i]; e != NULL; e = e->r_next) |
|
745 { k = e->j; |
|
746 for (ee = B->row[k]; ee != NULL; ee = ee->r_next) |
|
747 { j = ee->j; |
|
748 /* if a[i,k] != 0 and b[k,j] != 0 then c[i,j] != 0 */ |
|
749 if (!flag[j]) |
|
750 { /* c[i,j] does not exist, so create it */ |
|
751 spm_new_elem(C, i, j, 0.0); |
|
752 flag[j] = 1; |
|
753 } |
|
754 } |
|
755 } |
|
756 /* reset the flag array */ |
|
757 for (e = C->row[i]; e != NULL; e = e->r_next) |
|
758 flag[e->j] = 0; |
|
759 } |
|
760 /* check and deallocate the flag array */ |
|
761 for (j = 1; j <= C->n; j++) |
|
762 xassert(!flag[j]); |
|
763 xfree(flag); |
|
764 return C; |
|
765 } |
|
766 |
|
767 void spm_mul_num(SPM *C, const SPM *A, const SPM *B) |
|
768 { /* multiply two sparse matrices (numeric phase) */ |
|
769 int i, j; |
|
770 double *work; |
|
771 /* allocate and clear the working array */ |
|
772 work = xcalloc(1+A->n, sizeof(double)); |
|
773 for (j = 1; j <= A->n; j++) |
|
774 work[j] = 0.0; |
|
775 /* compute matrix C = A * B */ |
|
776 for (i = 1; i <= C->m; i++) |
|
777 { SPME *e, *ee; |
|
778 double temp; |
|
779 /* work := (i-th row of A) */ |
|
780 /* (note that A may have duplicate elements) */ |
|
781 for (e = A->row[i]; e != NULL; e = e->r_next) |
|
782 work[e->j] += e->val; |
|
783 /* compute i-th row of C */ |
|
784 for (e = C->row[i]; e != NULL; e = e->r_next) |
|
785 { j = e->j; |
|
786 /* c[i,j] := work * (j-th column of B) */ |
|
787 temp = 0.0; |
|
788 for (ee = B->col[j]; ee != NULL; ee = ee->c_next) |
|
789 temp += work[ee->i] * ee->val; |
|
790 e->val = temp; |
|
791 } |
|
792 /* reset the working array */ |
|
793 for (e = A->row[i]; e != NULL; e = e->r_next) |
|
794 work[e->j] = 0.0; |
|
795 } |
|
796 /* check and deallocate the working array */ |
|
797 for (j = 1; j <= A->n; j++) |
|
798 xassert(work[j] == 0.0); |
|
799 xfree(work); |
|
800 return; |
|
801 } |
|
802 |
|
803 SPM *spm_mul_mat(const SPM *A, const SPM *B) |
|
804 { /* multiply two sparse matrices (driver routine) */ |
|
805 SPM *C; |
|
806 C = spm_mul_sym(A, B); |
|
807 spm_mul_num(C, A, B); |
|
808 return C; |
|
809 } |
|
810 |
|
811 PER *spm_create_per(int n) |
|
812 { /* create permutation matrix */ |
|
813 PER *P; |
|
814 int k; |
|
815 xassert(n >= 0); |
|
816 P = xmalloc(sizeof(PER)); |
|
817 P->n = n; |
|
818 P->row = xcalloc(1+n, sizeof(int)); |
|
819 P->col = xcalloc(1+n, sizeof(int)); |
|
820 /* initially it is identity matrix */ |
|
821 for (k = 1; k <= n; k++) |
|
822 P->row[k] = P->col[k] = k; |
|
823 return P; |
|
824 } |
|
825 |
|
826 void spm_check_per(PER *P) |
|
827 { /* check permutation matrix for correctness */ |
|
828 int i, j; |
|
829 xassert(P->n >= 0); |
|
830 for (i = 1; i <= P->n; i++) |
|
831 { j = P->row[i]; |
|
832 xassert(1 <= j && j <= P->n); |
|
833 xassert(P->col[j] == i); |
|
834 } |
|
835 return; |
|
836 } |
|
837 |
|
838 void spm_delete_per(PER *P) |
|
839 { /* delete permutation matrix */ |
|
840 xfree(P->row); |
|
841 xfree(P->col); |
|
842 xfree(P); |
|
843 return; |
|
844 } |
|
845 |
|
846 /* eof */ |