1 | /* glpapi02.c (problem retrieving routines) */ |
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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 "glpapi.h" |
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26 | |
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27 | /*********************************************************************** |
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28 | * NAME |
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29 | * |
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30 | * glp_get_prob_name - retrieve problem name |
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31 | * |
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32 | * SYNOPSIS |
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33 | * |
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34 | * const char *glp_get_prob_name(glp_prob *lp); |
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35 | * |
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36 | * RETURNS |
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37 | * |
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38 | * The routine glp_get_prob_name returns a pointer to an internal |
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39 | * buffer, which contains symbolic name of the problem. However, if the |
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40 | * problem has no assigned name, the routine returns NULL. */ |
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41 | |
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42 | const char *glp_get_prob_name(glp_prob *lp) |
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43 | { char *name; |
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44 | name = lp->name; |
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45 | return name; |
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46 | } |
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47 | |
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48 | /*********************************************************************** |
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49 | * NAME |
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50 | * |
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51 | * glp_get_obj_name - retrieve objective function name |
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52 | * |
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53 | * SYNOPSIS |
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54 | * |
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55 | * const char *glp_get_obj_name(glp_prob *lp); |
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56 | * |
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57 | * RETURNS |
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58 | * |
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59 | * The routine glp_get_obj_name returns a pointer to an internal |
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60 | * buffer, which contains a symbolic name of the objective function. |
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61 | * However, if the objective function has no assigned name, the routine |
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62 | * returns NULL. */ |
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63 | |
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64 | const char *glp_get_obj_name(glp_prob *lp) |
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65 | { char *name; |
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66 | name = lp->obj; |
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67 | return name; |
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68 | } |
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69 | |
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70 | /*********************************************************************** |
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71 | * NAME |
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72 | * |
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73 | * glp_get_obj_dir - retrieve optimization direction flag |
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74 | * |
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75 | * SYNOPSIS |
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76 | * |
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77 | * int glp_get_obj_dir(glp_prob *lp); |
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78 | * |
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79 | * RETURNS |
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80 | * |
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81 | * The routine glp_get_obj_dir returns the optimization direction flag |
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82 | * (i.e. "sense" of the objective function): |
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83 | * |
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84 | * GLP_MIN - minimization; |
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85 | * GLP_MAX - maximization. */ |
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86 | |
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87 | int glp_get_obj_dir(glp_prob *lp) |
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88 | { int dir = lp->dir; |
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89 | return dir; |
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90 | } |
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91 | |
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92 | /*********************************************************************** |
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93 | * NAME |
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94 | * |
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95 | * glp_get_num_rows - retrieve number of rows |
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96 | * |
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97 | * SYNOPSIS |
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98 | * |
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99 | * int glp_get_num_rows(glp_prob *lp); |
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100 | * |
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101 | * RETURNS |
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102 | * |
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103 | * The routine glp_get_num_rows returns the current number of rows in |
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104 | * the specified problem object. */ |
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105 | |
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106 | int glp_get_num_rows(glp_prob *lp) |
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107 | { int m = lp->m; |
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108 | return m; |
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109 | } |
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110 | |
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111 | /*********************************************************************** |
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112 | * NAME |
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113 | * |
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114 | * glp_get_num_cols - retrieve number of columns |
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115 | * |
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116 | * SYNOPSIS |
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117 | * |
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118 | * int glp_get_num_cols(glp_prob *lp); |
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119 | * |
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120 | * RETURNS |
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121 | * |
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122 | * The routine glp_get_num_cols returns the current number of columns |
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123 | * in the specified problem object. */ |
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124 | |
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125 | int glp_get_num_cols(glp_prob *lp) |
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126 | { int n = lp->n; |
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127 | return n; |
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128 | } |
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129 | |
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130 | /*********************************************************************** |
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131 | * NAME |
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132 | * |
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133 | * glp_get_row_name - retrieve row name |
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134 | * |
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135 | * SYNOPSIS |
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136 | * |
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137 | * const char *glp_get_row_name(glp_prob *lp, int i); |
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138 | * |
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139 | * RETURNS |
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140 | * |
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141 | * The routine glp_get_row_name returns a pointer to an internal |
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142 | * buffer, which contains symbolic name of i-th row. However, if i-th |
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143 | * row has no assigned name, the routine returns NULL. */ |
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144 | |
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145 | const char *glp_get_row_name(glp_prob *lp, int i) |
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146 | { char *name; |
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147 | if (!(1 <= i && i <= lp->m)) |
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148 | xerror("glp_get_row_name: i = %d; row number out of range\n", |
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149 | i); |
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150 | name = lp->row[i]->name; |
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151 | return name; |
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152 | } |
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153 | |
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154 | /*********************************************************************** |
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155 | * NAME |
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156 | * |
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157 | * glp_get_col_name - retrieve column name |
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158 | * |
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159 | * SYNOPSIS |
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160 | * |
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161 | * const char *glp_get_col_name(glp_prob *lp, int j); |
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162 | * |
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163 | * RETURNS |
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164 | * |
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165 | * The routine glp_get_col_name returns a pointer to an internal |
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166 | * buffer, which contains symbolic name of j-th column. However, if j-th |
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167 | * column has no assigned name, the routine returns NULL. */ |
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168 | |
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169 | const char *glp_get_col_name(glp_prob *lp, int j) |
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170 | { char *name; |
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171 | if (!(1 <= j && j <= lp->n)) |
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172 | xerror("glp_get_col_name: j = %d; column number out of range\n" |
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173 | , j); |
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174 | name = lp->col[j]->name; |
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175 | return name; |
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176 | } |
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177 | |
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178 | /*********************************************************************** |
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179 | * NAME |
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180 | * |
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181 | * glp_get_row_type - retrieve row type |
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182 | * |
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183 | * SYNOPSIS |
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184 | * |
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185 | * int glp_get_row_type(glp_prob *lp, int i); |
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186 | * |
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187 | * RETURNS |
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188 | * |
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189 | * The routine glp_get_row_type returns the type of i-th row, i.e. the |
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190 | * type of corresponding auxiliary variable, as follows: |
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191 | * |
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192 | * GLP_FR - free (unbounded) variable; |
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193 | * GLP_LO - variable with lower bound; |
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194 | * GLP_UP - variable with upper bound; |
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195 | * GLP_DB - double-bounded variable; |
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196 | * GLP_FX - fixed variable. */ |
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197 | |
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198 | int glp_get_row_type(glp_prob *lp, int i) |
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199 | { if (!(1 <= i && i <= lp->m)) |
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200 | xerror("glp_get_row_type: i = %d; row number out of range\n", |
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201 | i); |
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202 | return lp->row[i]->type; |
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203 | } |
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204 | |
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205 | /*********************************************************************** |
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206 | * NAME |
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207 | * |
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208 | * glp_get_row_lb - retrieve row lower bound |
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209 | * |
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210 | * SYNOPSIS |
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211 | * |
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212 | * double glp_get_row_lb(glp_prob *lp, int i); |
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213 | * |
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214 | * RETURNS |
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215 | * |
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216 | * The routine glp_get_row_lb returns the lower bound of i-th row, i.e. |
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217 | * the lower bound of corresponding auxiliary variable. However, if the |
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218 | * row has no lower bound, the routine returns -DBL_MAX. */ |
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219 | |
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220 | double glp_get_row_lb(glp_prob *lp, int i) |
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221 | { double lb; |
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222 | if (!(1 <= i && i <= lp->m)) |
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223 | xerror("glp_get_row_lb: i = %d; row number out of range\n", i); |
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224 | switch (lp->row[i]->type) |
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225 | { case GLP_FR: |
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226 | case GLP_UP: |
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227 | lb = -DBL_MAX; break; |
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228 | case GLP_LO: |
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229 | case GLP_DB: |
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230 | case GLP_FX: |
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231 | lb = lp->row[i]->lb; break; |
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232 | default: |
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233 | xassert(lp != lp); |
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234 | } |
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235 | return lb; |
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236 | } |
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237 | |
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238 | /*********************************************************************** |
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239 | * NAME |
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240 | * |
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241 | * glp_get_row_ub - retrieve row upper bound |
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242 | * |
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243 | * SYNOPSIS |
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244 | * |
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245 | * double glp_get_row_ub(glp_prob *lp, int i); |
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246 | * |
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247 | * RETURNS |
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248 | * |
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249 | * The routine glp_get_row_ub returns the upper bound of i-th row, i.e. |
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250 | * the upper bound of corresponding auxiliary variable. However, if the |
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251 | * row has no upper bound, the routine returns +DBL_MAX. */ |
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252 | |
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253 | double glp_get_row_ub(glp_prob *lp, int i) |
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254 | { double ub; |
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255 | if (!(1 <= i && i <= lp->m)) |
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256 | xerror("glp_get_row_ub: i = %d; row number out of range\n", i); |
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257 | switch (lp->row[i]->type) |
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258 | { case GLP_FR: |
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259 | case GLP_LO: |
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260 | ub = +DBL_MAX; break; |
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261 | case GLP_UP: |
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262 | case GLP_DB: |
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263 | case GLP_FX: |
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264 | ub = lp->row[i]->ub; break; |
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265 | default: |
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266 | xassert(lp != lp); |
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267 | } |
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268 | return ub; |
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269 | } |
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270 | |
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271 | /*********************************************************************** |
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272 | * NAME |
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273 | * |
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274 | * glp_get_col_type - retrieve column type |
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275 | * |
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276 | * SYNOPSIS |
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277 | * |
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278 | * int glp_get_col_type(glp_prob *lp, int j); |
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279 | * |
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280 | * RETURNS |
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281 | * |
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282 | * The routine glp_get_col_type returns the type of j-th column, i.e. |
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283 | * the type of corresponding structural variable, as follows: |
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284 | * |
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285 | * GLP_FR - free (unbounded) variable; |
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286 | * GLP_LO - variable with lower bound; |
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287 | * GLP_UP - variable with upper bound; |
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288 | * GLP_DB - double-bounded variable; |
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289 | * GLP_FX - fixed variable. */ |
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290 | |
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291 | int glp_get_col_type(glp_prob *lp, int j) |
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292 | { if (!(1 <= j && j <= lp->n)) |
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293 | xerror("glp_get_col_type: j = %d; column number out of range\n" |
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294 | , j); |
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295 | return lp->col[j]->type; |
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296 | } |
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297 | |
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298 | /*********************************************************************** |
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299 | * NAME |
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300 | * |
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301 | * glp_get_col_lb - retrieve column lower bound |
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302 | * |
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303 | * SYNOPSIS |
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304 | * |
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305 | * double glp_get_col_lb(glp_prob *lp, int j); |
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306 | * |
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307 | * RETURNS |
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308 | * |
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309 | * The routine glp_get_col_lb returns the lower bound of j-th column, |
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310 | * i.e. the lower bound of corresponding structural variable. However, |
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311 | * if the column has no lower bound, the routine returns -DBL_MAX. */ |
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312 | |
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313 | double glp_get_col_lb(glp_prob *lp, int j) |
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314 | { double lb; |
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315 | if (!(1 <= j && j <= lp->n)) |
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316 | xerror("glp_get_col_lb: j = %d; column number out of range\n", |
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317 | j); |
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318 | switch (lp->col[j]->type) |
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319 | { case GLP_FR: |
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320 | case GLP_UP: |
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321 | lb = -DBL_MAX; break; |
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322 | case GLP_LO: |
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323 | case GLP_DB: |
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324 | case GLP_FX: |
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325 | lb = lp->col[j]->lb; break; |
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326 | default: |
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327 | xassert(lp != lp); |
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328 | } |
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329 | return lb; |
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330 | } |
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331 | |
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332 | /*********************************************************************** |
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333 | * NAME |
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334 | * |
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335 | * glp_get_col_ub - retrieve column upper bound |
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336 | * |
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337 | * SYNOPSIS |
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338 | * |
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339 | * double glp_get_col_ub(glp_prob *lp, int j); |
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340 | * |
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341 | * RETURNS |
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342 | * |
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343 | * The routine glp_get_col_ub returns the upper bound of j-th column, |
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344 | * i.e. the upper bound of corresponding structural variable. However, |
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345 | * if the column has no upper bound, the routine returns +DBL_MAX. */ |
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346 | |
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347 | double glp_get_col_ub(glp_prob *lp, int j) |
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348 | { double ub; |
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349 | if (!(1 <= j && j <= lp->n)) |
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350 | xerror("glp_get_col_ub: j = %d; column number out of range\n", |
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351 | j); |
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352 | switch (lp->col[j]->type) |
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353 | { case GLP_FR: |
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354 | case GLP_LO: |
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355 | ub = +DBL_MAX; break; |
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356 | case GLP_UP: |
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357 | case GLP_DB: |
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358 | case GLP_FX: |
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359 | ub = lp->col[j]->ub; break; |
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360 | default: |
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361 | xassert(lp != lp); |
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362 | } |
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363 | return ub; |
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364 | } |
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365 | |
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366 | /*********************************************************************** |
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367 | * NAME |
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368 | * |
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369 | * glp_get_obj_coef - retrieve obj. coefficient or constant term |
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370 | * |
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371 | * SYNOPSIS |
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372 | * |
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373 | * double glp_get_obj_coef(glp_prob *lp, int j); |
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374 | * |
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375 | * RETURNS |
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376 | * |
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377 | * The routine glp_get_obj_coef returns the objective coefficient at |
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378 | * j-th structural variable (column) of the specified problem object. |
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379 | * |
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380 | * If the parameter j is zero, the routine returns the constant term |
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381 | * ("shift") of the objective function. */ |
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382 | |
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383 | double glp_get_obj_coef(glp_prob *lp, int j) |
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384 | { if (!(0 <= j && j <= lp->n)) |
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385 | xerror("glp_get_obj_coef: j = %d; column number out of range\n" |
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386 | , j); |
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387 | return j == 0 ? lp->c0 : lp->col[j]->coef; |
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388 | } |
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389 | |
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390 | /*********************************************************************** |
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391 | * NAME |
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392 | * |
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393 | * glp_get_num_nz - retrieve number of constraint coefficients |
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394 | * |
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395 | * SYNOPSIS |
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396 | * |
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397 | * int glp_get_num_nz(glp_prob *lp); |
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398 | * |
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399 | * RETURNS |
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400 | * |
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401 | * The routine glp_get_num_nz returns the number of (non-zero) elements |
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402 | * in the constraint matrix of the specified problem object. */ |
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403 | |
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404 | int glp_get_num_nz(glp_prob *lp) |
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405 | { int nnz = lp->nnz; |
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406 | return nnz; |
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407 | } |
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408 | |
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409 | /*********************************************************************** |
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410 | * NAME |
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411 | * |
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412 | * glp_get_mat_row - retrieve row of the constraint matrix |
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413 | * |
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414 | * SYNOPSIS |
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415 | * |
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416 | * int glp_get_mat_row(glp_prob *lp, int i, int ind[], double val[]); |
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417 | * |
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418 | * DESCRIPTION |
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419 | * |
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420 | * The routine glp_get_mat_row scans (non-zero) elements of i-th row |
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421 | * of the constraint matrix of the specified problem object and stores |
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422 | * their column indices and numeric values to locations ind[1], ..., |
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423 | * ind[len] and val[1], ..., val[len], respectively, where 0 <= len <= n |
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424 | * is the number of elements in i-th row, n is the number of columns. |
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425 | * |
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426 | * The parameter ind and/or val can be specified as NULL, in which case |
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427 | * corresponding information is not stored. |
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428 | * |
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429 | * RETURNS |
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430 | * |
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431 | * The routine glp_get_mat_row returns the length len, i.e. the number |
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432 | * of (non-zero) elements in i-th row. */ |
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433 | |
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434 | int glp_get_mat_row(glp_prob *lp, int i, int ind[], double val[]) |
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435 | { GLPAIJ *aij; |
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436 | int len; |
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437 | if (!(1 <= i && i <= lp->m)) |
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438 | xerror("glp_get_mat_row: i = %d; row number out of range\n", |
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439 | i); |
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440 | len = 0; |
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441 | for (aij = lp->row[i]->ptr; aij != NULL; aij = aij->r_next) |
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442 | { len++; |
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443 | if (ind != NULL) ind[len] = aij->col->j; |
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444 | if (val != NULL) val[len] = aij->val; |
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445 | } |
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446 | xassert(len <= lp->n); |
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447 | return len; |
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448 | } |
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449 | |
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450 | /*********************************************************************** |
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451 | * NAME |
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452 | * |
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453 | * glp_get_mat_col - retrieve column of the constraint matrix |
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454 | * |
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455 | * SYNOPSIS |
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456 | * |
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457 | * int glp_get_mat_col(glp_prob *lp, int j, int ind[], double val[]); |
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458 | * |
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459 | * DESCRIPTION |
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460 | * |
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461 | * The routine glp_get_mat_col scans (non-zero) elements of j-th column |
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462 | * of the constraint matrix of the specified problem object and stores |
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463 | * their row indices and numeric values to locations ind[1], ..., |
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464 | * ind[len] and val[1], ..., val[len], respectively, where 0 <= len <= m |
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465 | * is the number of elements in j-th column, m is the number of rows. |
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466 | * |
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467 | * The parameter ind or/and val can be specified as NULL, in which case |
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468 | * corresponding information is not stored. |
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469 | * |
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470 | * RETURNS |
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471 | * |
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472 | * The routine glp_get_mat_col returns the length len, i.e. the number |
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473 | * of (non-zero) elements in j-th column. */ |
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474 | |
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475 | int glp_get_mat_col(glp_prob *lp, int j, int ind[], double val[]) |
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476 | { GLPAIJ *aij; |
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477 | int len; |
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478 | if (!(1 <= j && j <= lp->n)) |
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479 | xerror("glp_get_mat_col: j = %d; column number out of range\n", |
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480 | j); |
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481 | len = 0; |
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482 | for (aij = lp->col[j]->ptr; aij != NULL; aij = aij->c_next) |
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483 | { len++; |
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484 | if (ind != NULL) ind[len] = aij->row->i; |
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485 | if (val != NULL) val[len] = aij->val; |
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486 | } |
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487 | xassert(len <= lp->m); |
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488 | return len; |
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489 | } |
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490 | |
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491 | /* eof */ |
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