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