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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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287
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28 #include <strstream.h> |
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29 |
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1
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30 #include "NPSOL.h" |
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31 |
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32 #include "tree-const.h" |
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33 #include "variables.h" |
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34 #include "gripes.h" |
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35 #include "error.h" |
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287
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36 #include "pager.h" |
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1
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37 #include "utils.h" |
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544
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38 #include "help.h" |
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519
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39 #include "defun-dld.h" |
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40 |
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646
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41 #ifndef NPSOL_MISSING |
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42 |
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1
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43 // Global pointers for user defined functions required by npsol. |
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488
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44 static tree_fvc *npsol_objective; |
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45 static tree_fvc *npsol_constraints; |
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1
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46 |
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287
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47 static NPSOL_options npsol_opts; |
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48 |
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1
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49 double |
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162
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50 npsol_objective_function (const ColumnVector& x) |
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1
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51 { |
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52 int n = x.capacity (); |
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53 |
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54 tree_constant decision_vars; |
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55 if (n > 1) |
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56 { |
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57 Matrix m (n, 1); |
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58 for (int i = 0; i < n; i++) |
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59 m (i, 0) = x.elem (i); |
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516
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60 decision_vars = m; |
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1
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61 } |
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62 else |
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63 { |
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64 double d = x.elem (0); |
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516
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65 decision_vars = d; |
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1
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66 } |
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67 |
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516
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68 // tree_constant name = npsol_objective->name (); |
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565
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69 Octave_object args; |
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70 args(1) = decision_vars; |
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497
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71 // args(0) = name; |
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72 |
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255
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73 static double retval; |
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74 retval = 0.0; |
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75 |
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1
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76 tree_constant objective_value; |
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519
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77 if (npsol_objective) |
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1
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78 { |
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506
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79 Octave_object tmp = npsol_objective->eval (0, 1, args); |
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255
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80 |
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81 if (error_state) |
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82 { |
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83 error ("npsol: error evaluating objective function"); |
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84 npsol_objective_error = 1; // XXX FIXME XXX |
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85 return retval; |
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86 } |
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87 |
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497
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88 if (tmp.length () > 0 && tmp(0).is_defined ()) |
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89 objective_value = tmp(0); |
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1
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90 else |
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91 { |
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158
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92 error ("npsol: error evaluating objective function"); |
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255
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93 npsol_objective_error = 1; // XXX FIXME XXX |
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94 return retval; |
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1
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95 } |
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96 } |
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97 |
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620
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98 if (objective_value.is_real_matrix ()) |
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1
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99 { |
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620
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100 Matrix m = objective_value.matrix_value (); |
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101 if (m.rows () == 1 && m.columns () == 1) |
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102 retval = m.elem (0, 0); |
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103 else |
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104 { |
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105 gripe_user_returned_invalid ("npsol_objective"); |
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106 npsol_objective_error = 1; // XXX FIXME XXX |
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107 } |
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108 } |
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109 else if (objective_value.is_real_scalar ()) |
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110 { |
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1
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111 retval = objective_value.double_value (); |
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620
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112 } |
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113 else |
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114 { |
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115 gripe_user_returned_invalid ("npsol_objective"); |
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255
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116 npsol_objective_error = 1; // XXX FIXME XXX |
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1
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117 } |
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118 |
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119 return retval; |
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120 } |
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121 |
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122 ColumnVector |
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162
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123 npsol_constraint_function (const ColumnVector& x) |
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1
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124 { |
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125 ColumnVector retval; |
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126 |
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127 int n = x.capacity (); |
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128 |
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129 tree_constant decision_vars; |
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130 if (n > 1) |
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131 { |
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132 Matrix m (n, 1); |
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133 for (int i = 0; i < n; i++) |
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134 m (i, 0) = x.elem (i); |
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516
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135 decision_vars = m; |
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1
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136 } |
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137 else |
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138 { |
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139 double d = x.elem (0); |
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516
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140 decision_vars = d; |
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1
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141 } |
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142 |
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516
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143 // tree_constant name = npsol_constraints->name (); |
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565
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144 Octave_object args; |
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145 args(1) = decision_vars; |
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497
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146 // args(0) = name; |
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147 |
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519
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148 if (npsol_constraints) |
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1
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149 { |
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506
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150 Octave_object tmp = npsol_constraints->eval (0, 1, args); |
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255
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151 |
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152 if (error_state) |
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153 { |
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154 error ("npsol: error evaluating constraints"); |
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155 return retval; |
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156 } |
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157 |
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497
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158 if (tmp.length () > 0 && tmp(0).is_defined ()) |
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1
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159 { |
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628
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160 retval = tmp(0).vector_value (); |
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255
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161 |
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636
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162 if (error_state || retval.length () <= 0) |
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255
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163 error ("npsol: error evaluating constraints"); |
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1
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164 } |
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165 else |
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497
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166 error ("npsol: error evaluating constraints"); |
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167 } |
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168 |
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169 return retval; |
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170 } |
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171 |
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172 int |
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173 linear_constraints_ok (const ColumnVector& x, const ColumnVector& llb, |
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174 const Matrix& c, const ColumnVector& lub, |
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175 char *warn_for, int warn) |
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176 { |
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177 int x_len = x.capacity (); |
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178 int llb_len = llb.capacity (); |
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179 int lub_len = lub.capacity (); |
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180 int c_rows = c.rows (); |
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181 int c_cols = c.columns (); |
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182 |
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132
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183 int ok = 1; |
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184 if (warn) |
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185 { |
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186 if (c_rows == 0 || c_cols == 0 || llb_len == 0 || lub_len == 0) |
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187 { |
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188 ok = 0; |
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158
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189 error ("%s: linear constraints must have nonzero dimensions", |
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190 warn_for); |
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132
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191 } |
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192 else if (x_len != c_cols || llb_len != lub_len || llb_len != c_rows) |
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193 { |
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194 ok = 0; |
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158
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195 error ("%s: linear constraints have inconsistent dimensions", |
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196 warn_for); |
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132
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197 } |
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198 } |
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1
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199 |
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200 return ok; |
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201 } |
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202 |
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203 int |
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204 nonlinear_constraints_ok (const ColumnVector& x, const ColumnVector& nllb, |
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205 nonlinear_fcn g, const ColumnVector& nlub, |
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206 char *warn_for, int warn) |
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207 { |
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208 int nllb_len = nllb.capacity (); |
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209 int nlub_len = nlub.capacity (); |
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210 ColumnVector c = (*g) (x); |
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211 int c_len = c.capacity (); |
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212 |
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132
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213 int ok = 1; |
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214 if (warn) |
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215 { |
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216 if (nllb_len == 0 || nlub_len == 0 || c_len == 0) |
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217 { |
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218 ok = 0; |
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158
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219 error ("%s: nonlinear constraints have nonzero dimensions", |
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220 warn_for); |
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132
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221 } |
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222 else if (nllb_len != nlub_len || nllb_len != c_len) |
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223 { |
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224 ok = 0; |
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162
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225 error ("%s: nonlinear constraints have inconsistent dimensions", |
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226 warn_for); |
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132
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227 } |
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135
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228 } |
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1
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229 return ok; |
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230 } |
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231 |
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646
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232 #endif |
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233 |
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519
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234 #if defined (NPSOL_MISSING) |
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701
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235 DEFUN_DLD_BUILTIN ("npsol", Fnpsol, Snpsol, 11, 3, |
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519
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236 "This function requires NPSOL, which is not freely\n\ |
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237 redistributable. For more information, read the file\n\ |
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238 libcruft/npsol/README.MISSING in the source distribution.") |
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239 #else |
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701
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240 DEFUN_DLD_BUILTIN ("npsol", Fnpsol, Snpsol, 11, 3, |
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519
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241 "[X, OBJ, INFO, LAMBDA] = npsol (X, PHI [, LB, UB] [, LB, A, UB] [, LB, G, UB])\n\ |
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242 \n\ |
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243 Groups of arguments surrounded in `[]' are optional, but\n\ |
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244 must appear in the same relative order shown above.\n\ |
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245 \n\ |
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246 The second argument is a string containing the name of the objective\n\ |
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247 function to call. The objective function must be of the form\n\ |
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248 \n\ |
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249 y = phi (x)\n\ |
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250 \n\ |
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251 where x is a vector and y is a scalar.\n\ |
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252 \n\ |
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253 The argument G is a string containing the name of the function that |
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254 defines the nonlinear constraints. It must be of the form\n\ |
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255 \n\ |
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256 y = g (x)\n\ |
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257 \n\ |
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258 where x is a vector and y is a vector.") |
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259 #endif |
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1
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260 { |
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261 /* |
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262 |
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263 Handle all of the following: |
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264 |
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265 1. npsol (x, phi) |
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266 2. npsol (x, phi, lb, ub) |
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267 3. npsol (x, phi, lb, ub, llb, c, lub) |
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268 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
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269 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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270 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
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271 7. npsol (x, phi, llb, c, lub) |
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272 8. npsol (x, phi, nllb, g, nlub) |
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273 |
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274 */ |
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275 |
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497
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276 Octave_object retval; |
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1
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277 |
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519
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278 #if defined (NPSOL_MISSING) |
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279 |
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280 // Force a bad value of inform, and empty matrices for x, phi, and lambda. |
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281 |
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282 retval.resize (4, Matrix ()); |
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283 |
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284 retval(2) = -1.0; |
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285 |
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286 print_usage ("npsol"); |
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287 |
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288 #else |
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289 |
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506
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290 int nargin = args.length (); |
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291 |
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519
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292 if (nargin < 3 || nargin == 4 || nargin == 7 || nargin == 10 |
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293 || nargin > 11 || nargout > 4) |
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294 { |
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295 print_usage ("npsol"); |
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296 return retval; |
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297 } |
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298 |
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628
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299 ColumnVector x = args(1).vector_value (); |
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1
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300 |
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636
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301 if (error_state || x.capacity () == 0) |
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1
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302 { |
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158
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303 error ("npsol: expecting vector as first argument"); |
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1
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304 return retval; |
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305 } |
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306 |
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497
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307 npsol_objective = is_valid_function (args(2), "npsol", 1); |
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519
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308 if (! npsol_objective |
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1
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309 || takes_correct_nargs (npsol_objective, 2, "npsol", 1) != 1) |
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310 return retval; |
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311 |
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312 Objective func (npsol_objective_function); |
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313 |
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314 ColumnVector soln; |
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315 |
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316 Bounds bounds; |
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317 if (nargin == 5 || nargin == 8 || nargin == 11) |
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318 { |
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628
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319 ColumnVector lb = args(3).vector_value (); |
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320 ColumnVector ub = args(4).vector_value (); |
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1
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321 |
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322 int lb_len = lb.capacity (); |
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323 int ub_len = ub.capacity (); |
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636
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324 |
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325 if (error_state || lb_len != ub_len || lb_len != x.capacity ()) |
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1
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326 { |
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214
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327 error ("npsol: lower and upper bounds and decision variable vector"); |
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328 error ("must all have the same number of elements"); |
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1
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329 return retval; |
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330 } |
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331 |
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332 bounds.resize (lb_len); |
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333 bounds.set_lower_bounds (lb); |
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334 bounds.set_upper_bounds (ub); |
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335 } |
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336 |
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337 double objf; |
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338 ColumnVector lambda; |
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339 int inform; |
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340 |
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341 if (nargin == 3) |
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342 { |
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343 // 1. npsol (x, phi) |
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344 |
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345 NPSOL nlp (x, func); |
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287
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346 nlp.copy (npsol_opts); |
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1
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347 soln = nlp.minimize (objf, inform, lambda); |
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348 |
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349 goto solved; |
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350 } |
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351 |
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352 if (nargin == 5) |
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353 { |
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354 // 2. npsol (x, phi, lb, ub) |
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355 |
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356 NPSOL nlp (x, func, bounds); |
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287
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357 nlp.copy (npsol_opts); |
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1
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358 soln = nlp.minimize (objf, inform, lambda); |
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359 |
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360 goto solved; |
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361 } |
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362 |
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519
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363 npsol_constraints = 0; |
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1
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364 if (nargin == 6 || nargin == 8 || nargin == 9 || nargin == 11) |
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497
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365 npsol_constraints = is_valid_function (args(nargin-2), "npsol", 0); |
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1
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366 |
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367 if (nargin == 8 || nargin == 6) |
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368 { |
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519
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369 if (! npsol_constraints) |
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1
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370 { |
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628
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371 ColumnVector lub = args(nargin-1).vector_value (); |
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372 ColumnVector llb = args(nargin-3).vector_value (); |
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1
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373 |
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636
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374 if (error_state || llb.capacity () == 0 || lub.capacity () == 0) |
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215
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375 { |
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376 error ("npsol: bounds for linear constraints must be vectors"); |
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377 return retval; |
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378 } |
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1
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379 |
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636
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380 Matrix c = args(nargin-2).matrix_value (); |
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381 |
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382 if (error_state) |
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383 { |
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384 error ("npsol: invalid linear constraint matrix"); |
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385 return retval; |
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386 } |
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387 |
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1
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388 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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389 return retval; |
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390 |
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215
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391 LinConst linear_constraints (llb, c, lub); |
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392 |
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1
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393 if (nargin == 6) |
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394 { |
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395 // 7. npsol (x, phi, llb, c, lub) |
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396 |
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397 NPSOL nlp (x, func, linear_constraints); |
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287
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398 nlp.copy (npsol_opts); |
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1
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399 soln = nlp.minimize (objf, inform, lambda); |
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400 } |
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401 else |
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402 { |
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403 // 3. npsol (x, phi, lb, ub, llb, c, lub) |
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404 |
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405 NPSOL nlp (x, func, bounds, linear_constraints); |
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287
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406 nlp.copy (npsol_opts); |
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1
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407 soln = nlp.minimize (objf, inform, lambda); |
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408 } |
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409 goto solved; |
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410 } |
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411 else |
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412 { |
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413 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
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414 { |
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628
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415 ColumnVector nlub = args(nargin-1).vector_value (); |
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416 ColumnVector nllb = args(nargin-3).vector_value (); |
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1
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417 |
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636
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418 if (error_state |
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419 || (! nonlinear_constraints_ok |
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420 (x, nllb, npsol_constraint_function, nlub, "npsol", 1))) |
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1
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421 return retval; |
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422 |
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636
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423 NLFunc const_func (npsol_constraint_function); |
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1
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424 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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425 |
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426 if (nargin == 6) |
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427 { |
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428 // 8. npsol (x, phi, nllb, g, nlub) |
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429 |
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430 NPSOL nlp (x, func, nonlinear_constraints); |
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287
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431 nlp.copy (npsol_opts); |
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1
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432 soln = nlp.minimize (objf, inform, lambda); |
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433 } |
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434 else |
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435 { |
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436 // 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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437 |
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438 NPSOL nlp (x, func, bounds, nonlinear_constraints); |
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287
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439 nlp.copy (npsol_opts); |
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1
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440 soln = nlp.minimize (objf, inform, lambda); |
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441 } |
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442 goto solved; |
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443 } |
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444 } |
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445 } |
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446 |
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447 if (nargin == 9 || nargin == 11) |
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448 { |
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519
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449 if (! npsol_constraints) |
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1
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450 { |
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451 // Produce error message. |
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497
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452 is_valid_function (args(nargin-2), "npsol", 1); |
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1
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453 } |
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454 else |
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455 { |
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|
456 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
|
|
457 { |
|
628
|
458 ColumnVector nlub = args(nargin-1).vector_value (); |
|
|
459 ColumnVector nllb = args(nargin-3).vector_value (); |
|
1
|
460 |
|
636
|
461 if (error_state |
|
|
462 || (! nonlinear_constraints_ok |
|
|
463 (x, nllb, npsol_constraint_function, nlub, "npsol", 1))) |
|
1
|
464 return retval; |
|
|
465 |
|
636
|
466 NLFunc const_func (npsol_constraint_function); |
|
1
|
467 NLConst nonlinear_constraints (nllb, const_func, nlub); |
|
|
468 |
|
628
|
469 ColumnVector lub = args(nargin-4).vector_value (); |
|
|
470 ColumnVector llb = args(nargin-6).vector_value (); |
|
1
|
471 |
|
636
|
472 if (error_state || llb.capacity () == 0 || lub.capacity () == 0) |
|
215
|
473 { |
|
|
474 error ("npsol: bounds for linear constraints must be vectors"); |
|
|
475 return retval; |
|
|
476 } |
|
636
|
477 |
|
|
478 Matrix c = args(nargin-5).matrix_value (); |
|
|
479 |
|
|
480 if (error_state) |
|
|
481 { |
|
|
482 error ("npsol: invalid linear constraint matrix"); |
|
|
483 return retval; |
|
|
484 } |
|
215
|
485 |
|
1
|
486 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
|
|
487 return retval; |
|
|
488 |
|
|
489 LinConst linear_constraints (llb, c, lub); |
|
|
490 |
|
|
491 if (nargin == 9) |
|
|
492 { |
|
|
493 // 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
|
|
494 |
|
|
495 NPSOL nlp (x, func, linear_constraints, |
|
|
496 nonlinear_constraints); |
|
287
|
497 nlp.copy (npsol_opts); |
|
1
|
498 soln = nlp.minimize (objf, inform, lambda); |
|
|
499 } |
|
|
500 else |
|
|
501 { |
|
|
502 // 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
|
|
503 |
|
|
504 NPSOL nlp (x, func, bounds, linear_constraints, |
|
|
505 nonlinear_constraints); |
|
287
|
506 nlp.copy (npsol_opts); |
|
1
|
507 soln = nlp.minimize (objf, inform, lambda); |
|
|
508 } |
|
|
509 goto solved; |
|
|
510 } |
|
|
511 } |
|
|
512 } |
|
|
513 |
|
|
514 return retval; |
|
|
515 |
|
|
516 solved: |
|
|
517 |
|
497
|
518 retval.resize (nargout ? nargout : 1); |
|
516
|
519 retval(0) = soln, 1; |
|
1
|
520 if (nargout > 1) |
|
516
|
521 retval(1) = objf; |
|
1
|
522 if (nargout > 2) |
|
516
|
523 retval(2) = (double) inform; |
|
1
|
524 if (nargout > 3) |
|
516
|
525 retval(3) = lambda; |
|
1
|
526 |
|
519
|
527 #endif |
|
|
528 |
|
1
|
529 return retval; |
|
|
530 } |
|
|
531 |
|
646
|
532 #ifndef NPSOL_MISSING |
|
|
533 |
|
287
|
534 typedef void (NPSOL_options::*d_set_opt_mf) (double); |
|
|
535 typedef void (NPSOL_options::*i_set_opt_mf) (int); |
|
|
536 typedef double (NPSOL_options::*d_get_opt_mf) (void); |
|
|
537 typedef int (NPSOL_options::*i_get_opt_mf) (void); |
|
|
538 |
|
|
539 #define MAX_TOKENS 5 |
|
|
540 |
|
|
541 struct NPSOL_OPTIONS |
|
|
542 { |
|
540
|
543 const char *keyword; |
|
|
544 const char *kw_tok[MAX_TOKENS + 1]; |
|
287
|
545 int min_len[MAX_TOKENS + 1]; |
|
|
546 int min_toks_to_match; |
|
|
547 d_set_opt_mf d_set_fcn; |
|
|
548 i_set_opt_mf i_set_fcn; |
|
|
549 d_get_opt_mf d_get_fcn; |
|
|
550 i_get_opt_mf i_get_fcn; |
|
|
551 }; |
|
|
552 |
|
497
|
553 static NPSOL_OPTIONS npsol_option_table [] = |
|
287
|
554 { |
|
|
555 { "central difference interval", |
|
519
|
556 { "central", "difference", "interval", 0, 0, 0, }, |
|
287
|
557 { 2, 0, 0, 0, 0, 0, }, 1, |
|
519
|
558 NPSOL_options::set_central_difference_interval, 0, |
|
|
559 NPSOL_options::central_difference_interval, 0, }, |
|
287
|
560 |
|
|
561 { "crash tolerance", |
|
519
|
562 { "crash", "tolerance", 0, 0, 0, 0, }, |
|
287
|
563 { 2, 0, 0, 0, 0, 0, }, 1, |
|
519
|
564 NPSOL_options::set_crash_tolerance, 0, |
|
|
565 NPSOL_options::crash_tolerance, 0, }, |
|
287
|
566 |
|
|
567 { "derivative level", |
|
519
|
568 { "derivative", "level", 0, 0, 0, 0, }, |
|
287
|
569 { 1, 0, 0, 0, 0, 0, }, 1, |
|
519
|
570 0, NPSOL_options::set_derivative_level, |
|
|
571 0, NPSOL_options::derivative_level, }, |
|
287
|
572 |
|
|
573 { "difference interval", |
|
519
|
574 { "difference", "interval", 0, 0, 0, 0, }, |
|
287
|
575 { 3, 0, 0, 0, 0, 0, }, 1, |
|
519
|
576 NPSOL_options::set_difference_interval, 0, |
|
|
577 NPSOL_options::difference_interval, 0, }, |
|
287
|
578 |
|
|
579 { "function precision", |
|
519
|
580 { "function", "precision", 0, 0, 0, 0, }, |
|
287
|
581 { 2, 0, 0, 0, 0, 0, }, 1, |
|
519
|
582 NPSOL_options::set_function_precision, 0, |
|
|
583 NPSOL_options::function_precision, 0, }, |
|
287
|
584 |
|
|
585 { "infinite bound size", |
|
519
|
586 { "infinite", "bound", "size", 0, 0, 0, }, |
|
287
|
587 { 1, 1, 0, 0, 0, 0, }, 2, |
|
519
|
588 NPSOL_options::set_infinite_bound, 0, |
|
|
589 NPSOL_options::infinite_bound, 0, }, |
|
287
|
590 |
|
|
591 { "infinite step size", |
|
519
|
592 { "infinite", "step", "size", 0, 0, 0, }, |
|
287
|
593 { 1, 1, 0, 0, 0, 0, }, 2, |
|
519
|
594 NPSOL_options::set_infinite_step, 0, |
|
|
595 NPSOL_options::infinite_step, 0, }, |
|
287
|
596 |
|
|
597 { "linear feasibility tolerance", |
|
519
|
598 { "linear", "feasibility", "tolerance", 0, 0, 0, }, |
|
287
|
599 { 5, 0, 0, 0, 0, 0, }, 1, |
|
519
|
600 NPSOL_options::set_linear_feasibility_tolerance, 0, |
|
|
601 NPSOL_options::linear_feasibility_tolerance, 0, }, |
|
287
|
602 |
|
|
603 { "linesearch tolerance", |
|
519
|
604 { "linesearch", "tolerance", 0, 0, 0, 0, }, |
|
287
|
605 { 5, 0, 0, 0, 0, 0, }, 1, |
|
519
|
606 NPSOL_options::set_linesearch_tolerance, 0, |
|
|
607 NPSOL_options::linesearch_tolerance, 0, }, |
|
287
|
608 |
|
|
609 { "major iteration limit", |
|
519
|
610 { "major", "iteration", "limit", 0, 0, 0, }, |
|
287
|
611 { 2, 1, 0, 0, 0, 0, }, 2, |
|
519
|
612 0, NPSOL_options::set_major_iteration_limit, |
|
|
613 0, NPSOL_options::major_iteration_limit, }, |
|
287
|
614 |
|
|
615 { "minor iteration limit", |
|
519
|
616 { "minor", "iteration", "limit", 0, 0, 0, }, |
|
287
|
617 { 2, 1, 0, 0, 0, 0, }, 2, |
|
519
|
618 0, NPSOL_options::set_minor_iteration_limit, |
|
|
619 0, NPSOL_options::minor_iteration_limit, }, |
|
287
|
620 |
|
|
621 { "major print level", |
|
519
|
622 { "major", "print", "level", 0, 0, 0, }, |
|
287
|
623 { 2, 1, 0, 0, 0, 0, }, 2, |
|
519
|
624 0, NPSOL_options::set_major_print_level, |
|
|
625 0, NPSOL_options::major_print_level, }, |
|
287
|
626 |
|
|
627 { "minor print level", |
|
519
|
628 { "minor", "print", "level", 0, 0, 0, }, |
|
287
|
629 { 2, 1, 0, 0, 0, 0, }, 2, |
|
519
|
630 0, NPSOL_options::set_minor_print_level, |
|
|
631 0, NPSOL_options::minor_print_level, }, |
|
287
|
632 |
|
|
633 { "nonlinear feasibility tolerance", |
|
519
|
634 { "nonlinear", "feasibility", "tolerance", 0, 0, }, |
|
287
|
635 { 1, 0, 0, 0, 0, 0, }, 1, |
|
519
|
636 NPSOL_options::set_nonlinear_feasibility_tolerance, 0, |
|
|
637 NPSOL_options::nonlinear_feasibility_tolerance, 0, }, |
|
287
|
638 |
|
|
639 { "optimality tolerance", |
|
519
|
640 { "optimality", "tolerance", 0, 0, 0, 0, }, |
|
287
|
641 { 1, 0, 0, 0, 0, 0, }, 1, |
|
519
|
642 NPSOL_options::set_optimality_tolerance, 0, |
|
|
643 NPSOL_options::optimality_tolerance, 0, }, |
|
287
|
644 |
|
|
645 { "start objective check at variable", |
|
519
|
646 { "start", "objective", "check", "at", "variable", 0, }, |
|
287
|
647 { 3, 1, 0, 0, 0, 0, }, 2, |
|
519
|
648 0, NPSOL_options::set_start_objective_check, |
|
|
649 0, NPSOL_options::start_objective_check, }, |
|
287
|
650 |
|
|
651 { "start constraint check at variable", |
|
519
|
652 { "start", "constraint", "check", "at", "variable", 0, }, |
|
287
|
653 { 3, 1, 0, 0, 0, 0, }, 2, |
|
519
|
654 0, NPSOL_options::set_start_constraint_check, |
|
|
655 0, NPSOL_options::start_constraint_check, }, |
|
287
|
656 |
|
|
657 { "stop objective check at variable", |
|
519
|
658 { "stop", "objective", "check", "at", "variable", 0, }, |
|
287
|
659 { 3, 1, 0, 0, 0, 0, }, 2, |
|
519
|
660 0, NPSOL_options::set_stop_objective_check, |
|
|
661 0, NPSOL_options::stop_objective_check, }, |
|
287
|
662 |
|
|
663 { "stop constraint check at variable", |
|
519
|
664 { "stop", "constraint", "check", "at", "variable", 0, }, |
|
287
|
665 { 3, 1, 0, 0, 0, 0, }, 2, |
|
519
|
666 0, NPSOL_options::set_stop_constraint_check, |
|
|
667 0, NPSOL_options::stop_constraint_check, }, |
|
287
|
668 |
|
|
669 { "verify level", |
|
519
|
670 { "verify", "level", 0, 0, 0, 0, }, |
|
287
|
671 { 1, 0, 0, 0, 0, 0, }, 1, |
|
519
|
672 0, NPSOL_options::set_verify_level, |
|
|
673 0, NPSOL_options::verify_level, }, |
|
287
|
674 |
|
519
|
675 { 0, |
|
|
676 { 0, 0, 0, 0, 0, 0, }, |
|
287
|
677 { 0, 0, 0, 0, 0, 0, }, 0, |
|
519
|
678 0, 0, 0, 0, }, |
|
287
|
679 }; |
|
|
680 |
|
|
681 static void |
|
|
682 print_npsol_option_list (void) |
|
|
683 { |
|
|
684 ostrstream output_buf; |
|
|
685 |
|
|
686 print_usage ("npsol_options", 1); |
|
|
687 |
|
|
688 output_buf << "\n" |
|
|
689 << "Options for npsol include:\n\n" |
|
|
690 << " keyword value\n" |
|
|
691 << " ------- -----\n\n"; |
|
|
692 |
|
|
693 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
694 |
|
540
|
695 const char *keyword; |
|
519
|
696 while ((keyword = list->keyword) != 0) |
|
287
|
697 { |
|
|
698 output_buf.form (" %-40s ", keyword); |
|
|
699 if (list->d_get_fcn) |
|
|
700 { |
|
|
701 double val = (npsol_opts.*list->d_get_fcn) (); |
|
|
702 if (val < 0.0) |
|
|
703 output_buf << "computed automatically"; |
|
|
704 else |
|
|
705 output_buf << val; |
|
|
706 } |
|
|
707 else |
|
|
708 { |
|
|
709 int val = (npsol_opts.*list->i_get_fcn) (); |
|
|
710 if (val < 0) |
|
|
711 output_buf << "depends on problem size"; |
|
|
712 else |
|
|
713 output_buf << val; |
|
|
714 } |
|
|
715 output_buf << "\n"; |
|
|
716 list++; |
|
|
717 } |
|
|
718 |
|
|
719 output_buf << "\n" << ends; |
|
|
720 maybe_page_output (output_buf); |
|
|
721 } |
|
|
722 |
|
|
723 static void |
|
|
724 do_npsol_option (char *keyword, double val) |
|
|
725 { |
|
|
726 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
727 |
|
519
|
728 while (list->keyword != 0) |
|
287
|
729 { |
|
|
730 if (keyword_almost_match (list->kw_tok, list->min_len, keyword, |
|
|
731 list->min_toks_to_match, MAX_TOKENS)) |
|
|
732 { |
|
|
733 if (list->d_set_fcn) |
|
|
734 (npsol_opts.*list->d_set_fcn) (val); |
|
|
735 else |
|
|
736 (npsol_opts.*list->i_set_fcn) (NINT (val)); |
|
|
737 |
|
|
738 return; |
|
|
739 } |
|
|
740 list++; |
|
|
741 } |
|
|
742 |
|
|
743 warning ("npsol_options: no match for `%s'", keyword); |
|
|
744 } |
|
|
745 |
|
646
|
746 #endif |
|
|
747 |
|
519
|
748 #if defined (NPSOL_MISSING) |
|
701
|
749 DEFUN_DLD_BUILTIN ("npsol_options", Fnpsol_options, Snpsol_options, -1, 1, |
|
519
|
750 "This function requires NPSOL, which is not freely\n\ |
|
|
751 redistributable. For more information, read the file\n\ |
|
|
752 libcruft/npsol/README.MISSING in the source distribution.") |
|
|
753 #else |
|
701
|
754 DEFUN_DLD_BUILTIN ("npsol_options", Fnpsol_options, Snpsol_options, -1, 1, |
|
519
|
755 "npsol_options (KEYWORD, VALUE)\n\ |
|
|
756 \n\ |
|
|
757 Set or show options for npsol. Keywords may be abbreviated\n\ |
|
|
758 to the shortest match.") |
|
|
759 #endif |
|
272
|
760 { |
|
497
|
761 Octave_object retval; |
|
272
|
762 |
|
519
|
763 #if defined (NPSOL_MISSING) |
|
|
764 |
|
|
765 print_usage ("npsol_options"); |
|
|
766 |
|
|
767 #else |
|
|
768 |
|
506
|
769 int nargin = args.length (); |
|
|
770 |
|
287
|
771 if (nargin == 1) |
|
|
772 { |
|
|
773 print_npsol_option_list (); |
|
636
|
774 return retval; |
|
287
|
775 } |
|
|
776 else if (nargin == 3) |
|
|
777 { |
|
636
|
778 char *keyword = args(1).string_value (); |
|
|
779 |
|
|
780 if (! error_state) |
|
287
|
781 { |
|
497
|
782 double val = args(2).double_value (); |
|
636
|
783 |
|
|
784 if (! error_state) |
|
|
785 { |
|
|
786 do_npsol_option (keyword, val); |
|
|
787 return retval; |
|
|
788 } |
|
287
|
789 } |
|
|
790 } |
|
636
|
791 |
|
|
792 print_usage ("npsol_options"); |
|
287
|
793 |
|
519
|
794 #endif |
|
|
795 |
|
272
|
796 return retval; |
|
|
797 } |
|
|
798 |
|
1
|
799 /* |
|
|
800 ;;; Local Variables: *** |
|
|
801 ;;; mode: C++ *** |
|
|
802 ;;; page-delimiter: "^/\\*" *** |
|
|
803 ;;; End: *** |
|
|
804 */ |
