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7
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1 // f-npsol.cc -*- C++ -*- |
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1
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2 /* |
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3 |
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296
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4 Copyright (C) 1993, 1994 John W. Eaton |
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5 |
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6 This file is part of Octave. |
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7 |
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8 Octave is free software; you can redistribute it and/or modify it |
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9 under the terms of the GNU General Public License as published by the |
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10 Free Software Foundation; either version 2, or (at your option) any |
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11 later version. |
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12 |
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13 Octave is distributed in the hope that it will be useful, but WITHOUT |
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14 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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15 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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16 for more details. |
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17 |
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18 You should have received a copy of the GNU General Public License |
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19 along with Octave; see the file COPYING. If not, write to the Free |
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20 Software Foundation, 675 Mass Ave, Cambridge, MA 02139, USA. |
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21 |
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22 */ |
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23 |
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240
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24 #ifdef HAVE_CONFIG_H |
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25 #include "config.h" |
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1
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26 #endif |
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27 |
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28 #ifndef NPSOL_MISSING |
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29 |
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287
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30 #include <strstream.h> |
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31 |
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1
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32 #include "NPSOL.h" |
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33 |
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34 #include "tree-const.h" |
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35 #include "variables.h" |
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287
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36 #include "builtins.h" |
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1
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37 #include "gripes.h" |
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38 #include "error.h" |
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287
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39 #include "pager.h" |
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1
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40 #include "utils.h" |
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7
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41 #include "f-npsol.h" |
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1
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42 |
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43 // Global pointers for user defined functions required by npsol. |
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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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506
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49 builtin_npsol_2 (const Octave_object& args, int nargout) |
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1
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50 { |
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506
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51 return npsol (args, nargout); |
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1
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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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506
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55 builtin_npsol_options_2 (const Octave_object& args, int nargout) |
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272
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56 { |
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506
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57 return npsol_options (args, nargout); |
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272
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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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506
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93 Octave_object tmp = npsol_objective->eval (0, 1, args); |
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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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1
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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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506
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166 Octave_object tmp = npsol_constraints->eval (0, 1, args); |
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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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506
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249 npsol (const Octave_object& args, 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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506
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270 int nargin = args.length (); |
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271 |
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497
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272 ColumnVector x = args(1).to_vector (); |
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1
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273 |
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274 if (x.capacity () == 0) |
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275 { |
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158
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276 error ("npsol: expecting vector as first argument"); |
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1
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277 return retval; |
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278 } |
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279 |
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497
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280 npsol_objective = is_valid_function (args(2), "npsol", 1); |
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488
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281 if (npsol_objective == (tree_fvc *) NULL |
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1
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282 || takes_correct_nargs (npsol_objective, 2, "npsol", 1) != 1) |
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283 return retval; |
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284 |
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285 Objective func (npsol_objective_function); |
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286 |
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287 ColumnVector soln; |
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288 |
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289 Bounds bounds; |
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290 if (nargin == 5 || nargin == 8 || nargin == 11) |
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291 { |
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497
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292 ColumnVector lb = args(3).to_vector (); |
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293 ColumnVector ub = args(4).to_vector (); |
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1
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294 |
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295 int lb_len = lb.capacity (); |
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296 int ub_len = ub.capacity (); |
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297 if (lb_len != ub_len || lb_len != x.capacity ()) |
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298 { |
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214
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299 error ("npsol: lower and upper bounds and decision variable vector"); |
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300 error ("must all have the same number of elements"); |
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1
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301 return retval; |
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302 } |
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303 |
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304 bounds.resize (lb_len); |
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305 bounds.set_lower_bounds (lb); |
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306 bounds.set_upper_bounds (ub); |
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307 } |
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308 |
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309 double objf; |
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310 ColumnVector lambda; |
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311 int inform; |
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312 |
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313 if (nargin == 3) |
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314 { |
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315 // 1. npsol (x, phi) |
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316 |
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317 NPSOL nlp (x, func); |
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287
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318 nlp.copy (npsol_opts); |
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1
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319 soln = nlp.minimize (objf, inform, lambda); |
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320 |
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321 goto solved; |
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322 } |
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323 |
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324 if (nargin == 5) |
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325 { |
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326 // 2. npsol (x, phi, lb, ub) |
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327 |
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328 NPSOL nlp (x, func, bounds); |
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287
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329 nlp.copy (npsol_opts); |
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1
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330 soln = nlp.minimize (objf, inform, lambda); |
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331 |
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332 goto solved; |
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333 } |
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334 |
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488
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335 npsol_constraints = (tree_fvc *) NULL; |
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1
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336 if (nargin == 6 || nargin == 8 || nargin == 9 || nargin == 11) |
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497
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337 npsol_constraints = is_valid_function (args(nargin-2), "npsol", 0); |
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1
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338 |
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339 if (nargin == 8 || nargin == 6) |
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340 { |
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488
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341 if (npsol_constraints == (tree_fvc *) NULL) |
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1
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342 { |
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497
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343 ColumnVector lub = args(nargin-1).to_vector (); |
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344 Matrix c = args(nargin-2).to_matrix (); |
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345 ColumnVector llb = args(nargin-3).to_vector (); |
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1
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346 |
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215
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347 if (llb.capacity () == 0 || lub.capacity () == 0) |
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348 { |
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349 error ("npsol: bounds for linear constraints must be vectors"); |
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350 return retval; |
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351 } |
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1
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352 |
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353 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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354 return retval; |
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355 |
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215
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356 LinConst linear_constraints (llb, c, lub); |
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357 |
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1
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358 if (nargin == 6) |
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359 { |
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360 // 7. npsol (x, phi, llb, c, lub) |
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361 |
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362 NPSOL nlp (x, func, linear_constraints); |
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287
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363 nlp.copy (npsol_opts); |
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1
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364 soln = nlp.minimize (objf, inform, lambda); |
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365 } |
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366 else |
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367 { |
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368 // 3. npsol (x, phi, lb, ub, llb, c, lub) |
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369 |
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370 NPSOL nlp (x, func, bounds, linear_constraints); |
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287
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371 nlp.copy (npsol_opts); |
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1
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372 soln = nlp.minimize (objf, inform, lambda); |
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373 } |
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374 goto solved; |
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375 } |
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376 else |
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377 { |
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378 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
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379 { |
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497
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380 ColumnVector nlub = args(nargin-1).to_vector (); |
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381 ColumnVector nllb = args(nargin-3).to_vector (); |
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1
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382 |
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383 NLFunc const_func (npsol_constraint_function); |
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384 |
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385 if (! nonlinear_constraints_ok |
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386 (x, nllb, npsol_constraint_function, nlub, "npsol", 1)) |
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387 return retval; |
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388 |
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389 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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390 |
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391 if (nargin == 6) |
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392 { |
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393 // 8. npsol (x, phi, nllb, g, nlub) |
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394 |
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395 NPSOL nlp (x, func, nonlinear_constraints); |
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287
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396 nlp.copy (npsol_opts); |
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1
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397 soln = nlp.minimize (objf, inform, lambda); |
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398 } |
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399 else |
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400 { |
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401 // 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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402 |
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403 NPSOL nlp (x, func, bounds, nonlinear_constraints); |
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287
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404 nlp.copy (npsol_opts); |
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1
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405 soln = nlp.minimize (objf, inform, lambda); |
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406 } |
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407 goto solved; |
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408 } |
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409 } |
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410 } |
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411 |
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412 if (nargin == 9 || nargin == 11) |
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413 { |
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488
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414 if (npsol_constraints == (tree_fvc *) NULL) |
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1
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415 { |
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416 // Produce error message. |
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497
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417 is_valid_function (args(nargin-2), "npsol", 1); |
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1
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418 } |
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419 else |
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420 { |
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421 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
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422 { |
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497
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423 ColumnVector nlub = args(nargin-1).to_vector (); |
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424 ColumnVector nllb = args(nargin-3).to_vector (); |
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1
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425 |
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426 NLFunc const_func (npsol_constraint_function); |
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427 |
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428 if (! nonlinear_constraints_ok |
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429 (x, nllb, npsol_constraint_function, nlub, "npsol", 1)) |
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430 return retval; |
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431 |
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432 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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433 |
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497
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434 ColumnVector lub = args(nargin-4).to_vector (); |
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435 Matrix c = args(nargin-5).to_matrix (); |
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436 ColumnVector llb = args(nargin-6).to_vector (); |
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1
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437 |
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215
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438 if (llb.capacity () == 0 || lub.capacity () == 0) |
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439 { |
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440 error ("npsol: bounds for linear constraints must be vectors"); |
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441 return retval; |
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442 } |
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443 |
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1
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444 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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445 return retval; |
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446 |
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447 LinConst linear_constraints (llb, c, lub); |
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448 |
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449 if (nargin == 9) |
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450 { |
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451 // 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
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452 |
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453 NPSOL nlp (x, func, linear_constraints, |
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454 nonlinear_constraints); |
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287
|
455 nlp.copy (npsol_opts); |
|
1
|
456 soln = nlp.minimize (objf, inform, lambda); |
|
|
457 } |
|
|
458 else |
|
|
459 { |
|
|
460 // 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
|
|
461 |
|
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462 NPSOL nlp (x, func, bounds, linear_constraints, |
|
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463 nonlinear_constraints); |
|
287
|
464 nlp.copy (npsol_opts); |
|
1
|
465 soln = nlp.minimize (objf, inform, lambda); |
|
|
466 } |
|
|
467 goto solved; |
|
|
468 } |
|
|
469 } |
|
|
470 } |
|
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471 |
|
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472 return retval; |
|
|
473 |
|
|
474 solved: |
|
|
475 |
|
497
|
476 retval.resize (nargout ? nargout : 1); |
|
|
477 retval(0) = tree_constant (soln, 1); |
|
1
|
478 if (nargout > 1) |
|
497
|
479 retval(1) = tree_constant (objf); |
|
1
|
480 if (nargout > 2) |
|
497
|
481 retval(2) = tree_constant ((double) inform); |
|
1
|
482 if (nargout > 3) |
|
497
|
483 retval(3) = tree_constant (lambda); |
|
1
|
484 |
|
|
485 return retval; |
|
|
486 } |
|
|
487 |
|
287
|
488 typedef void (NPSOL_options::*d_set_opt_mf) (double); |
|
|
489 typedef void (NPSOL_options::*i_set_opt_mf) (int); |
|
|
490 typedef double (NPSOL_options::*d_get_opt_mf) (void); |
|
|
491 typedef int (NPSOL_options::*i_get_opt_mf) (void); |
|
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492 |
|
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493 #define MAX_TOKENS 5 |
|
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494 |
|
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495 struct NPSOL_OPTIONS |
|
|
496 { |
|
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497 char *keyword; |
|
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498 char *kw_tok[MAX_TOKENS + 1]; |
|
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499 int min_len[MAX_TOKENS + 1]; |
|
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500 int min_toks_to_match; |
|
|
501 d_set_opt_mf d_set_fcn; |
|
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502 i_set_opt_mf i_set_fcn; |
|
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503 d_get_opt_mf d_get_fcn; |
|
|
504 i_get_opt_mf i_get_fcn; |
|
|
505 }; |
|
|
506 |
|
497
|
507 static NPSOL_OPTIONS npsol_option_table [] = |
|
287
|
508 { |
|
|
509 { "central difference interval", |
|
|
510 { "central", "difference", "interval", NULL, NULL, NULL, }, |
|
|
511 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
512 NPSOL_options::set_central_difference_interval, NULL, |
|
|
513 NPSOL_options::central_difference_interval, NULL, }, |
|
|
514 |
|
|
515 { "crash tolerance", |
|
|
516 { "crash", "tolerance", NULL, NULL, NULL, NULL, }, |
|
|
517 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
518 NPSOL_options::set_crash_tolerance, NULL, |
|
|
519 NPSOL_options::crash_tolerance, NULL, }, |
|
|
520 |
|
|
521 { "derivative level", |
|
|
522 { "derivative", "level", NULL, NULL, NULL, NULL, }, |
|
|
523 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
524 NULL, NPSOL_options::set_derivative_level, |
|
|
525 NULL, NPSOL_options::derivative_level, }, |
|
|
526 |
|
|
527 { "difference interval", |
|
|
528 { "difference", "interval", NULL, NULL, NULL, NULL, }, |
|
|
529 { 3, 0, 0, 0, 0, 0, }, 1, |
|
|
530 NPSOL_options::set_difference_interval, NULL, |
|
|
531 NPSOL_options::difference_interval, NULL, }, |
|
|
532 |
|
|
533 { "function precision", |
|
|
534 { "function", "precision", NULL, NULL, NULL, NULL, }, |
|
|
535 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
536 NPSOL_options::set_function_precision, NULL, |
|
|
537 NPSOL_options::function_precision, NULL, }, |
|
|
538 |
|
|
539 { "infinite bound size", |
|
|
540 { "infinite", "bound", "size", NULL, NULL, NULL, }, |
|
|
541 { 1, 1, 0, 0, 0, 0, }, 2, |
|
|
542 NPSOL_options::set_infinite_bound, NULL, |
|
|
543 NPSOL_options::infinite_bound, NULL, }, |
|
|
544 |
|
|
545 { "infinite step size", |
|
|
546 { "infinite", "step", "size", NULL, NULL, NULL, }, |
|
|
547 { 1, 1, 0, 0, 0, 0, }, 2, |
|
|
548 NPSOL_options::set_infinite_step, NULL, |
|
|
549 NPSOL_options::infinite_step, NULL, }, |
|
|
550 |
|
|
551 { "linear feasibility tolerance", |
|
|
552 { "linear", "feasibility", "tolerance", NULL, NULL, NULL, }, |
|
|
553 { 5, 0, 0, 0, 0, 0, }, 1, |
|
|
554 NPSOL_options::set_linear_feasibility_tolerance, NULL, |
|
|
555 NPSOL_options::linear_feasibility_tolerance, NULL, }, |
|
|
556 |
|
|
557 { "linesearch tolerance", |
|
|
558 { "linesearch", "tolerance", NULL, NULL, NULL, NULL, }, |
|
|
559 { 5, 0, 0, 0, 0, 0, }, 1, |
|
|
560 NPSOL_options::set_linesearch_tolerance, NULL, |
|
|
561 NPSOL_options::linesearch_tolerance, NULL, }, |
|
|
562 |
|
|
563 { "major iteration limit", |
|
|
564 { "major", "iteration", "limit", NULL, NULL, NULL, }, |
|
|
565 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
566 NULL, NPSOL_options::set_major_iteration_limit, |
|
|
567 NULL, NPSOL_options::major_iteration_limit, }, |
|
|
568 |
|
|
569 { "minor iteration limit", |
|
|
570 { "minor", "iteration", "limit", NULL, NULL, NULL, }, |
|
|
571 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
572 NULL, NPSOL_options::set_minor_iteration_limit, |
|
|
573 NULL, NPSOL_options::minor_iteration_limit, }, |
|
|
574 |
|
|
575 { "major print level", |
|
|
576 { "major", "print", "level", NULL, NULL, NULL, }, |
|
|
577 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
578 NULL, NPSOL_options::set_major_print_level, |
|
|
579 NULL, NPSOL_options::major_print_level, }, |
|
|
580 |
|
|
581 { "minor print level", |
|
|
582 { "minor", "print", "level", NULL, NULL, NULL, }, |
|
|
583 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
584 NULL, NPSOL_options::set_minor_print_level, |
|
|
585 NULL, NPSOL_options::minor_print_level, }, |
|
|
586 |
|
|
587 { "nonlinear feasibility tolerance", |
|
|
588 { "nonlinear", "feasibility", "tolerance", NULL, NULL, }, |
|
|
589 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
590 NPSOL_options::set_nonlinear_feasibility_tolerance, NULL, |
|
|
591 NPSOL_options::nonlinear_feasibility_tolerance, NULL, }, |
|
|
592 |
|
|
593 { "optimality tolerance", |
|
|
594 { "optimality", "tolerance", NULL, NULL, NULL, NULL, }, |
|
|
595 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
596 NPSOL_options::set_optimality_tolerance, NULL, |
|
|
597 NPSOL_options::optimality_tolerance, NULL, }, |
|
|
598 |
|
|
599 { "start objective check at variable", |
|
|
600 { "start", "objective", "check", "at", "variable", NULL, }, |
|
|
601 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
602 NULL, NPSOL_options::set_start_objective_check, |
|
|
603 NULL, NPSOL_options::start_objective_check, }, |
|
|
604 |
|
|
605 { "start constraint check at variable", |
|
|
606 { "start", "constraint", "check", "at", "variable", NULL, }, |
|
|
607 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
608 NULL, NPSOL_options::set_start_constraint_check, |
|
|
609 NULL, NPSOL_options::start_constraint_check, }, |
|
|
610 |
|
|
611 { "stop objective check at variable", |
|
|
612 { "stop", "objective", "check", "at", "variable", NULL, }, |
|
|
613 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
614 NULL, NPSOL_options::set_stop_objective_check, |
|
|
615 NULL, NPSOL_options::stop_objective_check, }, |
|
|
616 |
|
|
617 { "stop constraint check at variable", |
|
|
618 { "stop", "constraint", "check", "at", "variable", NULL, }, |
|
|
619 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
620 NULL, NPSOL_options::set_stop_constraint_check, |
|
|
621 NULL, NPSOL_options::stop_constraint_check, }, |
|
|
622 |
|
|
623 { "verify level", |
|
|
624 { "verify", "level", NULL, NULL, NULL, NULL, }, |
|
|
625 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
626 NULL, NPSOL_options::set_verify_level, |
|
|
627 NULL, NPSOL_options::verify_level, }, |
|
|
628 |
|
|
629 { NULL, |
|
|
630 { NULL, NULL, NULL, NULL, NULL, NULL, }, |
|
|
631 { 0, 0, 0, 0, 0, 0, }, 0, |
|
|
632 NULL, NULL, NULL, NULL, }, |
|
|
633 }; |
|
|
634 |
|
|
635 static void |
|
|
636 print_npsol_option_list (void) |
|
|
637 { |
|
|
638 ostrstream output_buf; |
|
|
639 |
|
|
640 print_usage ("npsol_options", 1); |
|
|
641 |
|
|
642 output_buf << "\n" |
|
|
643 << "Options for npsol include:\n\n" |
|
|
644 << " keyword value\n" |
|
|
645 << " ------- -----\n\n"; |
|
|
646 |
|
|
647 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
648 |
|
|
649 char *keyword; |
|
|
650 while ((keyword = list->keyword) != (char *) NULL) |
|
|
651 { |
|
|
652 output_buf.form (" %-40s ", keyword); |
|
|
653 if (list->d_get_fcn) |
|
|
654 { |
|
|
655 double val = (npsol_opts.*list->d_get_fcn) (); |
|
|
656 if (val < 0.0) |
|
|
657 output_buf << "computed automatically"; |
|
|
658 else |
|
|
659 output_buf << val; |
|
|
660 } |
|
|
661 else |
|
|
662 { |
|
|
663 int val = (npsol_opts.*list->i_get_fcn) (); |
|
|
664 if (val < 0) |
|
|
665 output_buf << "depends on problem size"; |
|
|
666 else |
|
|
667 output_buf << val; |
|
|
668 } |
|
|
669 output_buf << "\n"; |
|
|
670 list++; |
|
|
671 } |
|
|
672 |
|
|
673 output_buf << "\n" << ends; |
|
|
674 maybe_page_output (output_buf); |
|
|
675 } |
|
|
676 |
|
|
677 static void |
|
|
678 do_npsol_option (char *keyword, double val) |
|
|
679 { |
|
|
680 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
681 |
|
|
682 while (list->keyword != (char *) NULL) |
|
|
683 { |
|
|
684 if (keyword_almost_match (list->kw_tok, list->min_len, keyword, |
|
|
685 list->min_toks_to_match, MAX_TOKENS)) |
|
|
686 { |
|
|
687 if (list->d_set_fcn) |
|
|
688 (npsol_opts.*list->d_set_fcn) (val); |
|
|
689 else |
|
|
690 (npsol_opts.*list->i_set_fcn) (NINT (val)); |
|
|
691 |
|
|
692 return; |
|
|
693 } |
|
|
694 list++; |
|
|
695 } |
|
|
696 |
|
|
697 warning ("npsol_options: no match for `%s'", keyword); |
|
|
698 } |
|
|
699 |
|
497
|
700 Octave_object |
|
506
|
701 npsol_options (const Octave_object& args, int nargout) |
|
272
|
702 { |
|
497
|
703 Octave_object retval; |
|
272
|
704 |
|
506
|
705 int nargin = args.length (); |
|
|
706 |
|
287
|
707 if (nargin == 1) |
|
|
708 { |
|
|
709 print_npsol_option_list (); |
|
|
710 } |
|
|
711 else if (nargin == 3) |
|
|
712 { |
|
497
|
713 if (args(1).is_string_type ()) |
|
287
|
714 { |
|
497
|
715 char *keyword = args(1).string_value (); |
|
|
716 double val = args(2).double_value (); |
|
287
|
717 do_npsol_option (keyword, val); |
|
|
718 } |
|
|
719 else |
|
|
720 print_usage ("npsol_options"); |
|
|
721 } |
|
|
722 else |
|
|
723 { |
|
|
724 print_usage ("npsol_options"); |
|
|
725 } |
|
|
726 |
|
272
|
727 return retval; |
|
|
728 } |
|
|
729 |
|
1
|
730 #endif |
|
|
731 |
|
|
732 /* |
|
|
733 ;;; Local Variables: *** |
|
|
734 ;;; mode: C++ *** |
|
|
735 ;;; page-delimiter: "^/\\*" *** |
|
|
736 ;;; End: *** |
|
|
737 */ |
