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7
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1 // f-npsol.cc -*- C++ -*- |
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1
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2 /* |
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3 |
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296
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4 Copyright (C) 1993, 1994 John W. Eaton |
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5 |
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6 This file is part of Octave. |
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7 |
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8 Octave is free software; you can redistribute it and/or modify it |
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9 under the terms of the GNU General Public License as published by the |
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10 Free Software Foundation; either version 2, or (at your option) any |
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11 later version. |
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12 |
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13 Octave is distributed in the hope that it will be useful, but WITHOUT |
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14 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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15 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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16 for more details. |
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17 |
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18 You should have received a copy of the GNU General Public License |
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19 along with Octave; see the file COPYING. If not, write to the Free |
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20 Software Foundation, 675 Mass Ave, Cambridge, MA 02139, USA. |
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21 |
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22 */ |
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23 |
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240
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24 #ifdef HAVE_CONFIG_H |
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25 #include "config.h" |
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1
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26 #endif |
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27 |
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28 #ifndef NPSOL_MISSING |
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29 |
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287
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30 #include <strstream.h> |
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31 |
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1
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32 #include "NPSOL.h" |
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33 |
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34 #include "tree-const.h" |
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35 #include "variables.h" |
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287
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36 #include "builtins.h" |
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1
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37 #include "gripes.h" |
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38 #include "error.h" |
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287
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39 #include "pager.h" |
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1
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40 #include "utils.h" |
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7
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41 #include "f-npsol.h" |
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1
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42 |
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43 // Global pointers for user defined functions required by npsol. |
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44 static tree *npsol_objective; |
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45 static tree *npsol_constraints; |
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46 |
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47 #ifdef WITH_DLD |
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48 tree_constant * |
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162
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49 builtin_npsol_2 (const tree_constant *args, int nargin, int nargout) |
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1
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50 { |
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51 return npsol (args, nargin, nargout); |
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52 } |
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272
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53 |
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54 tree_constant * |
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55 builtin_npsol_options_2 (const tree_constant *args, int nargin, int nargout) |
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56 { |
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57 return npsol_options (args, nargin, nargout); |
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58 } |
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1
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59 #endif |
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60 |
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287
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61 static NPSOL_options npsol_opts; |
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62 |
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1
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63 double |
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162
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64 npsol_objective_function (const ColumnVector& x) |
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1
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65 { |
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66 int n = x.capacity (); |
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67 |
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68 tree_constant decision_vars; |
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69 if (n > 1) |
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70 { |
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71 Matrix m (n, 1); |
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72 for (int i = 0; i < n; i++) |
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73 m (i, 0) = x.elem (i); |
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74 decision_vars = tree_constant (m); |
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75 } |
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76 else |
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77 { |
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78 double d = x.elem (0); |
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79 decision_vars = tree_constant (d); |
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80 } |
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81 |
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82 // tree_constant name = tree_constant (npsol_objective->name ()); |
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83 tree_constant *args = new tree_constant [2]; |
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84 // args[0] = name; |
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85 args[1] = decision_vars; |
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86 |
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255
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87 static double retval; |
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88 retval = 0.0; |
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89 |
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1
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90 tree_constant objective_value; |
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91 if (npsol_objective != NULL_TREE) |
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92 { |
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93 tree_constant *tmp = npsol_objective->eval (args, 2, 1, 0); |
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255
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94 |
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1
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95 delete [] args; |
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255
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96 |
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97 if (error_state) |
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98 { |
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99 error ("npsol: error evaluating objective function"); |
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100 npsol_objective_error = 1; // XXX FIXME XXX |
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260
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101 delete [] tmp; |
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255
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102 return retval; |
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103 } |
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104 |
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1
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105 if (tmp != NULL_TREE_CONST && tmp[0].is_defined ()) |
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106 { |
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107 objective_value = tmp[0]; |
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108 delete [] tmp; |
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109 } |
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110 else |
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111 { |
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112 delete [] tmp; |
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158
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113 error ("npsol: error evaluating objective function"); |
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255
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114 npsol_objective_error = 1; // XXX FIXME XXX |
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115 return retval; |
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1
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116 } |
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117 } |
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118 |
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119 switch (objective_value.const_type ()) |
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120 { |
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121 case tree_constant_rep::matrix_constant: |
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122 { |
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123 Matrix m = objective_value.matrix_value (); |
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124 if (m.rows () == 1 && m.columns () == 1) |
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125 retval = m.elem (0, 0); |
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126 else |
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255
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127 { |
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128 gripe_user_returned_invalid ("npsol_objective"); |
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129 npsol_objective_error = 1; // XXX FIXME XXX |
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130 } |
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1
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131 } |
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132 break; |
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133 case tree_constant_rep::scalar_constant: |
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134 retval = objective_value.double_value (); |
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135 break; |
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136 default: |
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137 gripe_user_returned_invalid ("npsol_objective"); |
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255
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138 npsol_objective_error = 1; // XXX FIXME XXX |
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139 break; |
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140 } |
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141 |
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142 return retval; |
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143 } |
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144 |
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145 ColumnVector |
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162
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146 npsol_constraint_function (const ColumnVector& x) |
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1
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147 { |
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148 ColumnVector retval; |
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149 |
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150 int n = x.capacity (); |
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151 |
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152 tree_constant decision_vars; |
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153 if (n > 1) |
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154 { |
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155 Matrix m (n, 1); |
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156 for (int i = 0; i < n; i++) |
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157 m (i, 0) = x.elem (i); |
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158 decision_vars = tree_constant (m); |
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159 } |
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160 else |
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161 { |
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162 double d = x.elem (0); |
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163 decision_vars = tree_constant (d); |
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164 } |
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165 |
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166 // tree_constant name = tree_constant (npsol_constraints->name ()); |
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167 tree_constant *args = new tree_constant [2]; |
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168 // args[0] = name; |
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169 args[1] = decision_vars; |
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170 |
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171 if (npsol_constraints != NULL_TREE) |
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172 { |
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173 tree_constant *tmp = npsol_constraints->eval (args, 2, 1, 0); |
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255
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174 |
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1
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175 delete [] args; |
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255
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176 |
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177 if (error_state) |
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178 { |
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260
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179 delete [] tmp; |
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255
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180 error ("npsol: error evaluating constraints"); |
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181 return retval; |
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182 } |
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183 |
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1
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184 if (tmp != NULL_TREE_CONST && tmp[0].is_defined ()) |
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185 { |
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186 retval = tmp[0].to_vector (); |
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255
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187 |
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1
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188 delete [] tmp; |
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255
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189 |
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190 if (retval.length () <= 0) |
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191 error ("npsol: error evaluating constraints"); |
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1
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192 } |
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193 else |
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194 { |
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195 delete [] tmp; |
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158
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196 error ("npsol: error evaluating constraints"); |
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1
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197 } |
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198 } |
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199 |
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200 return retval; |
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201 } |
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202 |
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203 int |
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204 linear_constraints_ok (const ColumnVector& x, const ColumnVector& llb, |
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205 const Matrix& c, const ColumnVector& lub, |
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206 char *warn_for, int warn) |
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207 { |
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208 int x_len = x.capacity (); |
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209 int llb_len = llb.capacity (); |
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210 int lub_len = lub.capacity (); |
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211 int c_rows = c.rows (); |
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212 int c_cols = c.columns (); |
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213 |
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132
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214 int ok = 1; |
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215 if (warn) |
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216 { |
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217 if (c_rows == 0 || c_cols == 0 || llb_len == 0 || lub_len == 0) |
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218 { |
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219 ok = 0; |
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158
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220 error ("%s: linear constraints must have nonzero dimensions", |
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221 warn_for); |
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132
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222 } |
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223 else if (x_len != c_cols || llb_len != lub_len || llb_len != c_rows) |
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224 { |
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225 ok = 0; |
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158
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226 error ("%s: linear constraints have inconsistent dimensions", |
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227 warn_for); |
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132
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228 } |
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229 } |
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1
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230 |
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231 return ok; |
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232 } |
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233 |
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234 int |
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235 nonlinear_constraints_ok (const ColumnVector& x, const ColumnVector& nllb, |
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236 nonlinear_fcn g, const ColumnVector& nlub, |
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237 char *warn_for, int warn) |
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238 { |
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239 int nllb_len = nllb.capacity (); |
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240 int nlub_len = nlub.capacity (); |
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241 ColumnVector c = (*g) (x); |
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242 int c_len = c.capacity (); |
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243 |
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132
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244 int ok = 1; |
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245 if (warn) |
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246 { |
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247 if (nllb_len == 0 || nlub_len == 0 || c_len == 0) |
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248 { |
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249 ok = 0; |
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158
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250 error ("%s: nonlinear constraints have nonzero dimensions", |
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251 warn_for); |
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132
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252 } |
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253 else if (nllb_len != nlub_len || nllb_len != c_len) |
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254 { |
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255 ok = 0; |
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162
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256 error ("%s: nonlinear constraints have inconsistent dimensions", |
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257 warn_for); |
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132
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258 } |
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135
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259 } |
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1
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260 return ok; |
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261 } |
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262 |
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263 tree_constant * |
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162
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264 npsol (const tree_constant *args, int nargin, int nargout) |
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1
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265 { |
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266 /* |
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267 |
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268 Handle all of the following: |
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269 |
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270 1. npsol (x, phi) |
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271 2. npsol (x, phi, lb, ub) |
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272 3. npsol (x, phi, lb, ub, llb, c, lub) |
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273 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
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274 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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275 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
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276 7. npsol (x, phi, llb, c, lub) |
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277 8. npsol (x, phi, nllb, g, nlub) |
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278 |
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279 */ |
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280 |
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281 // Assumes that we have been given the correct number of arguments. |
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282 |
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283 tree_constant *retval = NULL_TREE_CONST; |
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284 |
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285 ColumnVector x = args[1].to_vector (); |
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286 |
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287 if (x.capacity () == 0) |
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288 { |
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158
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289 error ("npsol: expecting vector as first argument"); |
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1
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290 return retval; |
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291 } |
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292 |
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293 npsol_objective = is_valid_function (args[2], "npsol", 1); |
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294 if (npsol_objective == NULL_TREE |
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295 || takes_correct_nargs (npsol_objective, 2, "npsol", 1) != 1) |
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296 return retval; |
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297 |
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298 Objective func (npsol_objective_function); |
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299 |
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300 ColumnVector soln; |
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301 |
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302 Bounds bounds; |
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303 if (nargin == 5 || nargin == 8 || nargin == 11) |
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304 { |
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305 ColumnVector lb = args[3].to_vector (); |
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306 ColumnVector ub = args[4].to_vector (); |
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307 |
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308 int lb_len = lb.capacity (); |
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309 int ub_len = ub.capacity (); |
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310 if (lb_len != ub_len || lb_len != x.capacity ()) |
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311 { |
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214
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312 error ("npsol: lower and upper bounds and decision variable vector"); |
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313 error ("must all have the same number of elements"); |
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1
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314 return retval; |
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315 } |
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316 |
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317 bounds.resize (lb_len); |
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318 bounds.set_lower_bounds (lb); |
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319 bounds.set_upper_bounds (ub); |
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320 } |
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321 |
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322 double objf; |
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323 ColumnVector lambda; |
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324 int inform; |
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325 |
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326 if (nargin == 3) |
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327 { |
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328 // 1. npsol (x, phi) |
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329 |
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330 NPSOL nlp (x, func); |
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287
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331 nlp.copy (npsol_opts); |
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1
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332 soln = nlp.minimize (objf, inform, lambda); |
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333 |
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334 goto solved; |
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335 } |
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336 |
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337 if (nargin == 5) |
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338 { |
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339 // 2. npsol (x, phi, lb, ub) |
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340 |
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341 NPSOL nlp (x, func, bounds); |
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287
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342 nlp.copy (npsol_opts); |
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1
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343 soln = nlp.minimize (objf, inform, lambda); |
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344 |
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345 goto solved; |
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346 } |
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347 |
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348 npsol_constraints = NULL_TREE; |
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349 if (nargin == 6 || nargin == 8 || nargin == 9 || nargin == 11) |
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350 npsol_constraints = is_valid_function (args[nargin-2], "npsol", 0); |
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351 |
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352 if (nargin == 8 || nargin == 6) |
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353 { |
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354 if (npsol_constraints == NULL_TREE) |
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355 { |
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356 ColumnVector lub = args[nargin-1].to_vector (); |
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357 Matrix c = args[nargin-2].to_matrix (); |
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358 ColumnVector llb = args[nargin-3].to_vector (); |
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359 |
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215
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360 if (llb.capacity () == 0 || lub.capacity () == 0) |
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361 { |
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362 error ("npsol: bounds for linear constraints must be vectors"); |
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363 return retval; |
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364 } |
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1
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365 |
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366 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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367 return retval; |
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368 |
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215
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369 LinConst linear_constraints (llb, c, lub); |
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370 |
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1
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371 if (nargin == 6) |
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372 { |
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373 // 7. npsol (x, phi, llb, c, lub) |
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374 |
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375 NPSOL nlp (x, func, linear_constraints); |
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287
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376 nlp.copy (npsol_opts); |
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1
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377 soln = nlp.minimize (objf, inform, lambda); |
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378 } |
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379 else |
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380 { |
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381 // 3. npsol (x, phi, lb, ub, llb, c, lub) |
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382 |
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383 NPSOL nlp (x, func, bounds, linear_constraints); |
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287
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384 nlp.copy (npsol_opts); |
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1
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385 soln = nlp.minimize (objf, inform, lambda); |
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386 } |
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387 goto solved; |
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388 } |
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389 else |
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390 { |
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391 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
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392 { |
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393 ColumnVector nlub = args[nargin-1].to_vector (); |
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394 ColumnVector nllb = args[nargin-3].to_vector (); |
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395 |
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396 NLFunc const_func (npsol_constraint_function); |
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397 |
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398 if (! nonlinear_constraints_ok |
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399 (x, nllb, npsol_constraint_function, nlub, "npsol", 1)) |
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400 return retval; |
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401 |
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402 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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403 |
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404 if (nargin == 6) |
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405 { |
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406 // 8. npsol (x, phi, nllb, g, nlub) |
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407 |
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408 NPSOL nlp (x, func, nonlinear_constraints); |
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287
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409 nlp.copy (npsol_opts); |
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1
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410 soln = nlp.minimize (objf, inform, lambda); |
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411 } |
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412 else |
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413 { |
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414 // 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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415 |
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416 NPSOL nlp (x, func, bounds, nonlinear_constraints); |
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287
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417 nlp.copy (npsol_opts); |
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1
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418 soln = nlp.minimize (objf, inform, lambda); |
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419 } |
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420 goto solved; |
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421 } |
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422 } |
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423 } |
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424 |
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425 if (nargin == 9 || nargin == 11) |
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426 { |
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427 if (npsol_constraints == NULL_TREE) |
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428 { |
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429 // Produce error message. |
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430 is_valid_function (args[nargin-2], "npsol", 1); |
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431 } |
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432 else |
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433 { |
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434 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
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435 { |
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436 ColumnVector nlub = args[nargin-1].to_vector (); |
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437 ColumnVector nllb = args[nargin-3].to_vector (); |
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438 |
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439 NLFunc const_func (npsol_constraint_function); |
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440 |
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441 if (! nonlinear_constraints_ok |
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442 (x, nllb, npsol_constraint_function, nlub, "npsol", 1)) |
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443 return retval; |
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444 |
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445 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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446 |
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447 ColumnVector lub = args[nargin-4].to_vector (); |
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448 Matrix c = args[nargin-5].to_matrix (); |
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449 ColumnVector llb = args[nargin-6].to_vector (); |
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450 |
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215
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451 if (llb.capacity () == 0 || lub.capacity () == 0) |
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452 { |
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453 error ("npsol: bounds for linear constraints must be vectors"); |
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454 return retval; |
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455 } |
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456 |
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1
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457 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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458 return retval; |
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459 |
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460 LinConst linear_constraints (llb, c, lub); |
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461 |
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462 if (nargin == 9) |
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463 { |
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464 // 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
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465 |
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466 NPSOL nlp (x, func, linear_constraints, |
|
|
467 nonlinear_constraints); |
|
287
|
468 nlp.copy (npsol_opts); |
|
1
|
469 soln = nlp.minimize (objf, inform, lambda); |
|
|
470 } |
|
|
471 else |
|
|
472 { |
|
|
473 // 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
|
|
474 |
|
|
475 NPSOL nlp (x, func, bounds, linear_constraints, |
|
|
476 nonlinear_constraints); |
|
287
|
477 nlp.copy (npsol_opts); |
|
1
|
478 soln = nlp.minimize (objf, inform, lambda); |
|
|
479 } |
|
|
480 goto solved; |
|
|
481 } |
|
|
482 } |
|
|
483 } |
|
|
484 |
|
|
485 return retval; |
|
|
486 |
|
|
487 solved: |
|
|
488 |
|
|
489 retval = new tree_constant [nargout+1]; |
|
|
490 retval[0] = tree_constant (soln, 1); |
|
|
491 if (nargout > 1) |
|
|
492 retval[1] = tree_constant (objf); |
|
|
493 if (nargout > 2) |
|
|
494 retval[2] = tree_constant ((double) inform); |
|
|
495 if (nargout > 3) |
|
|
496 retval[3] = tree_constant (lambda); |
|
|
497 |
|
|
498 return retval; |
|
|
499 } |
|
|
500 |
|
287
|
501 typedef void (NPSOL_options::*d_set_opt_mf) (double); |
|
|
502 typedef void (NPSOL_options::*i_set_opt_mf) (int); |
|
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503 typedef double (NPSOL_options::*d_get_opt_mf) (void); |
|
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504 typedef int (NPSOL_options::*i_get_opt_mf) (void); |
|
|
505 |
|
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506 #define MAX_TOKENS 5 |
|
|
507 |
|
|
508 struct NPSOL_OPTIONS |
|
|
509 { |
|
|
510 char *keyword; |
|
|
511 char *kw_tok[MAX_TOKENS + 1]; |
|
|
512 int min_len[MAX_TOKENS + 1]; |
|
|
513 int min_toks_to_match; |
|
|
514 d_set_opt_mf d_set_fcn; |
|
|
515 i_set_opt_mf i_set_fcn; |
|
|
516 d_get_opt_mf d_get_fcn; |
|
|
517 i_get_opt_mf i_get_fcn; |
|
|
518 }; |
|
|
519 |
|
|
520 static NPSOL_OPTIONS npsol_option_table[] = |
|
|
521 { |
|
|
522 { "central difference interval", |
|
|
523 { "central", "difference", "interval", NULL, NULL, NULL, }, |
|
|
524 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
525 NPSOL_options::set_central_difference_interval, NULL, |
|
|
526 NPSOL_options::central_difference_interval, NULL, }, |
|
|
527 |
|
|
528 { "crash tolerance", |
|
|
529 { "crash", "tolerance", NULL, NULL, NULL, NULL, }, |
|
|
530 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
531 NPSOL_options::set_crash_tolerance, NULL, |
|
|
532 NPSOL_options::crash_tolerance, NULL, }, |
|
|
533 |
|
|
534 { "derivative level", |
|
|
535 { "derivative", "level", NULL, NULL, NULL, NULL, }, |
|
|
536 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
537 NULL, NPSOL_options::set_derivative_level, |
|
|
538 NULL, NPSOL_options::derivative_level, }, |
|
|
539 |
|
|
540 { "difference interval", |
|
|
541 { "difference", "interval", NULL, NULL, NULL, NULL, }, |
|
|
542 { 3, 0, 0, 0, 0, 0, }, 1, |
|
|
543 NPSOL_options::set_difference_interval, NULL, |
|
|
544 NPSOL_options::difference_interval, NULL, }, |
|
|
545 |
|
|
546 { "function precision", |
|
|
547 { "function", "precision", NULL, NULL, NULL, NULL, }, |
|
|
548 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
549 NPSOL_options::set_function_precision, NULL, |
|
|
550 NPSOL_options::function_precision, NULL, }, |
|
|
551 |
|
|
552 { "infinite bound size", |
|
|
553 { "infinite", "bound", "size", NULL, NULL, NULL, }, |
|
|
554 { 1, 1, 0, 0, 0, 0, }, 2, |
|
|
555 NPSOL_options::set_infinite_bound, NULL, |
|
|
556 NPSOL_options::infinite_bound, NULL, }, |
|
|
557 |
|
|
558 { "infinite step size", |
|
|
559 { "infinite", "step", "size", NULL, NULL, NULL, }, |
|
|
560 { 1, 1, 0, 0, 0, 0, }, 2, |
|
|
561 NPSOL_options::set_infinite_step, NULL, |
|
|
562 NPSOL_options::infinite_step, NULL, }, |
|
|
563 |
|
|
564 { "linear feasibility tolerance", |
|
|
565 { "linear", "feasibility", "tolerance", NULL, NULL, NULL, }, |
|
|
566 { 5, 0, 0, 0, 0, 0, }, 1, |
|
|
567 NPSOL_options::set_linear_feasibility_tolerance, NULL, |
|
|
568 NPSOL_options::linear_feasibility_tolerance, NULL, }, |
|
|
569 |
|
|
570 { "linesearch tolerance", |
|
|
571 { "linesearch", "tolerance", NULL, NULL, NULL, NULL, }, |
|
|
572 { 5, 0, 0, 0, 0, 0, }, 1, |
|
|
573 NPSOL_options::set_linesearch_tolerance, NULL, |
|
|
574 NPSOL_options::linesearch_tolerance, NULL, }, |
|
|
575 |
|
|
576 { "major iteration limit", |
|
|
577 { "major", "iteration", "limit", NULL, NULL, NULL, }, |
|
|
578 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
579 NULL, NPSOL_options::set_major_iteration_limit, |
|
|
580 NULL, NPSOL_options::major_iteration_limit, }, |
|
|
581 |
|
|
582 { "minor iteration limit", |
|
|
583 { "minor", "iteration", "limit", NULL, NULL, NULL, }, |
|
|
584 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
585 NULL, NPSOL_options::set_minor_iteration_limit, |
|
|
586 NULL, NPSOL_options::minor_iteration_limit, }, |
|
|
587 |
|
|
588 { "major print level", |
|
|
589 { "major", "print", "level", NULL, NULL, NULL, }, |
|
|
590 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
591 NULL, NPSOL_options::set_major_print_level, |
|
|
592 NULL, NPSOL_options::major_print_level, }, |
|
|
593 |
|
|
594 { "minor print level", |
|
|
595 { "minor", "print", "level", NULL, NULL, NULL, }, |
|
|
596 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
597 NULL, NPSOL_options::set_minor_print_level, |
|
|
598 NULL, NPSOL_options::minor_print_level, }, |
|
|
599 |
|
|
600 { "nonlinear feasibility tolerance", |
|
|
601 { "nonlinear", "feasibility", "tolerance", NULL, NULL, }, |
|
|
602 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
603 NPSOL_options::set_nonlinear_feasibility_tolerance, NULL, |
|
|
604 NPSOL_options::nonlinear_feasibility_tolerance, NULL, }, |
|
|
605 |
|
|
606 { "optimality tolerance", |
|
|
607 { "optimality", "tolerance", NULL, NULL, NULL, NULL, }, |
|
|
608 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
609 NPSOL_options::set_optimality_tolerance, NULL, |
|
|
610 NPSOL_options::optimality_tolerance, NULL, }, |
|
|
611 |
|
|
612 { "start objective check at variable", |
|
|
613 { "start", "objective", "check", "at", "variable", NULL, }, |
|
|
614 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
615 NULL, NPSOL_options::set_start_objective_check, |
|
|
616 NULL, NPSOL_options::start_objective_check, }, |
|
|
617 |
|
|
618 { "start constraint check at variable", |
|
|
619 { "start", "constraint", "check", "at", "variable", NULL, }, |
|
|
620 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
621 NULL, NPSOL_options::set_start_constraint_check, |
|
|
622 NULL, NPSOL_options::start_constraint_check, }, |
|
|
623 |
|
|
624 { "stop objective check at variable", |
|
|
625 { "stop", "objective", "check", "at", "variable", NULL, }, |
|
|
626 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
627 NULL, NPSOL_options::set_stop_objective_check, |
|
|
628 NULL, NPSOL_options::stop_objective_check, }, |
|
|
629 |
|
|
630 { "stop constraint check at variable", |
|
|
631 { "stop", "constraint", "check", "at", "variable", NULL, }, |
|
|
632 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
633 NULL, NPSOL_options::set_stop_constraint_check, |
|
|
634 NULL, NPSOL_options::stop_constraint_check, }, |
|
|
635 |
|
|
636 { "verify level", |
|
|
637 { "verify", "level", NULL, NULL, NULL, NULL, }, |
|
|
638 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
639 NULL, NPSOL_options::set_verify_level, |
|
|
640 NULL, NPSOL_options::verify_level, }, |
|
|
641 |
|
|
642 { NULL, |
|
|
643 { NULL, NULL, NULL, NULL, NULL, NULL, }, |
|
|
644 { 0, 0, 0, 0, 0, 0, }, 0, |
|
|
645 NULL, NULL, NULL, NULL, }, |
|
|
646 }; |
|
|
647 |
|
|
648 static void |
|
|
649 print_npsol_option_list (void) |
|
|
650 { |
|
|
651 ostrstream output_buf; |
|
|
652 |
|
|
653 print_usage ("npsol_options", 1); |
|
|
654 |
|
|
655 output_buf << "\n" |
|
|
656 << "Options for npsol include:\n\n" |
|
|
657 << " keyword value\n" |
|
|
658 << " ------- -----\n\n"; |
|
|
659 |
|
|
660 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
661 |
|
|
662 char *keyword; |
|
|
663 while ((keyword = list->keyword) != (char *) NULL) |
|
|
664 { |
|
|
665 output_buf.form (" %-40s ", keyword); |
|
|
666 if (list->d_get_fcn) |
|
|
667 { |
|
|
668 double val = (npsol_opts.*list->d_get_fcn) (); |
|
|
669 if (val < 0.0) |
|
|
670 output_buf << "computed automatically"; |
|
|
671 else |
|
|
672 output_buf << val; |
|
|
673 } |
|
|
674 else |
|
|
675 { |
|
|
676 int val = (npsol_opts.*list->i_get_fcn) (); |
|
|
677 if (val < 0) |
|
|
678 output_buf << "depends on problem size"; |
|
|
679 else |
|
|
680 output_buf << val; |
|
|
681 } |
|
|
682 output_buf << "\n"; |
|
|
683 list++; |
|
|
684 } |
|
|
685 |
|
|
686 output_buf << "\n" << ends; |
|
|
687 maybe_page_output (output_buf); |
|
|
688 } |
|
|
689 |
|
|
690 static void |
|
|
691 do_npsol_option (char *keyword, double val) |
|
|
692 { |
|
|
693 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
694 |
|
|
695 while (list->keyword != (char *) NULL) |
|
|
696 { |
|
|
697 if (keyword_almost_match (list->kw_tok, list->min_len, keyword, |
|
|
698 list->min_toks_to_match, MAX_TOKENS)) |
|
|
699 { |
|
|
700 if (list->d_set_fcn) |
|
|
701 (npsol_opts.*list->d_set_fcn) (val); |
|
|
702 else |
|
|
703 (npsol_opts.*list->i_set_fcn) (NINT (val)); |
|
|
704 |
|
|
705 return; |
|
|
706 } |
|
|
707 list++; |
|
|
708 } |
|
|
709 |
|
|
710 warning ("npsol_options: no match for `%s'", keyword); |
|
|
711 } |
|
|
712 |
|
272
|
713 tree_constant * |
|
|
714 npsol_options (const tree_constant *args, int nargin, int nargout) |
|
|
715 { |
|
287
|
716 tree_constant *retval = NULL_TREE_CONST; |
|
272
|
717 |
|
287
|
718 if (nargin == 1) |
|
|
719 { |
|
|
720 print_npsol_option_list (); |
|
|
721 } |
|
|
722 else if (nargin == 3) |
|
|
723 { |
|
|
724 if (args[1].is_string_type ()) |
|
|
725 { |
|
|
726 char *keyword = args[1].string_value (); |
|
|
727 double val = args[2].double_value (); |
|
|
728 do_npsol_option (keyword, val); |
|
|
729 } |
|
|
730 else |
|
|
731 print_usage ("npsol_options"); |
|
|
732 } |
|
|
733 else |
|
|
734 { |
|
|
735 print_usage ("npsol_options"); |
|
|
736 } |
|
|
737 |
|
272
|
738 return retval; |
|
|
739 } |
|
|
740 |
|
1
|
741 #endif |
|
|
742 |
|
|
743 /* |
|
|
744 ;;; Local Variables: *** |
|
|
745 ;;; mode: C++ *** |
|
|
746 ;;; page-delimiter: "^/\\*" *** |
|
|
747 ;;; End: *** |
|
|
748 */ |
