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1 /* |
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2 |
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3 Copyright (C) 1996, 1997 John W. Eaton |
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4 |
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5 This file is part of Octave. |
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6 |
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7 Octave is free software; you can redistribute it and/or modify it |
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8 under the terms of the GNU General Public License as published by the |
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9 Free Software Foundation; either version 2, or (at your option) any |
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10 later version. |
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11 |
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12 Octave is distributed in the hope that it will be useful, but WITHOUT |
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13 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or |
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14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License |
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15 for more details. |
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16 |
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17 You should have received a copy of the GNU General Public License |
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18 along with Octave; see the file COPYING. If not, write to the Free |
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19 Software Foundation, 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. |
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20 |
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21 */ |
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22 |
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23 #ifdef HAVE_CONFIG_H |
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24 #include <config.h> |
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25 #endif |
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26 |
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27 #include <string> |
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28 |
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29 #include <iostream.h> |
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30 |
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31 #include "NPSOL.h" |
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32 #include "lo-mappers.h" |
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33 |
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34 #include "defun-dld.h" |
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35 #include "error.h" |
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36 #include "gripes.h" |
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37 #include "help.h" |
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38 #include "oct-obj.h" |
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2968
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39 #include "ov-fcn.h" |
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2928
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40 #include "pager.h" |
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41 #include "utils.h" |
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42 #include "variables.h" |
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43 |
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44 #ifndef NPSOL_MISSING |
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45 |
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46 // Global pointers for user defined functions required by npsol. |
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2968
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47 static octave_function *npsol_objective; |
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48 static octave_function *npsol_constraints; |
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2928
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49 |
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50 static NPSOL_options npsol_opts; |
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51 |
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52 double |
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53 npsol_objective_function (const ColumnVector& x) |
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54 { |
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55 int n = x.capacity (); |
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56 |
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57 octave_value decision_vars; |
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58 if (n > 1) |
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59 { |
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60 Matrix m (n, 1); |
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61 for (int i = 0; i < n; i++) |
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62 m (i, 0) = x (i); |
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63 decision_vars = m; |
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64 } |
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65 else |
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66 { |
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67 double d = x (0); |
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68 decision_vars = d; |
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69 } |
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70 |
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71 octave_value_list args; |
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72 args(0) = decision_vars; |
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73 |
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74 static double retval; |
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75 retval = 0.0; |
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76 |
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77 octave_value objective_value; |
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78 if (npsol_objective) |
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79 { |
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2968
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80 octave_value_list tmp = npsol_objective->do_index_op (1, args); |
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2928
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81 |
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82 if (error_state) |
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83 { |
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84 error ("npsol: error evaluating objective function"); |
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85 npsol_objective_error = 1; // XXX FIXME XXX |
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86 return retval; |
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87 } |
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88 |
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89 if (tmp.length () > 0 && tmp(0).is_defined ()) |
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90 objective_value = tmp(0); |
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91 else |
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92 { |
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93 error ("npsol: error evaluating objective function"); |
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94 npsol_objective_error = 1; // XXX FIXME XXX |
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95 return retval; |
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96 } |
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97 } |
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98 |
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99 if (objective_value.is_real_matrix ()) |
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100 { |
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101 Matrix m = objective_value.matrix_value (); |
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102 if (m.rows () == 1 && m.columns () == 1) |
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103 retval = m (0, 0); |
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104 else |
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105 { |
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106 gripe_user_returned_invalid ("npsol_objective"); |
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107 npsol_objective_error = 1; // XXX FIXME XXX |
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108 } |
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109 } |
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110 else if (objective_value.is_real_scalar ()) |
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111 { |
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112 retval = objective_value.double_value (); |
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113 } |
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114 else |
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115 { |
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116 gripe_user_returned_invalid ("npsol_objective"); |
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117 npsol_objective_error = 1; // XXX FIXME XXX |
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118 } |
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119 |
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120 return retval; |
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121 } |
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122 |
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123 ColumnVector |
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124 npsol_constraint_function (const ColumnVector& x) |
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125 { |
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126 ColumnVector retval; |
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127 |
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128 int n = x.capacity (); |
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129 |
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130 octave_value decision_vars; |
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131 if (n > 1) |
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132 { |
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133 Matrix m (n, 1); |
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134 for (int i = 0; i < n; i++) |
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135 m (i, 0) = x (i); |
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136 decision_vars = m; |
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137 } |
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138 else |
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139 { |
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140 double d = x (0); |
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141 decision_vars = d; |
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142 } |
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143 |
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144 octave_value_list args; |
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145 args(0) = decision_vars; |
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146 |
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147 if (npsol_constraints) |
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148 { |
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2968
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149 octave_value_list tmp = npsol_constraints->do_index_op (1, args); |
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2928
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150 |
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151 if (error_state) |
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152 { |
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153 error ("npsol: error evaluating constraints"); |
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154 return retval; |
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155 } |
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156 |
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157 if (tmp.length () > 0 && tmp(0).is_defined ()) |
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158 { |
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159 retval = tmp(0).vector_value (); |
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160 |
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161 if (error_state || retval.length () <= 0) |
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162 error ("npsol: error evaluating constraints"); |
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163 } |
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164 else |
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165 error ("npsol: error evaluating constraints"); |
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166 } |
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167 |
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168 return retval; |
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169 } |
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170 |
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171 static int |
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172 linear_constraints_ok (const ColumnVector& x, const ColumnVector& llb, |
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173 const Matrix& c, const ColumnVector& lub, |
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174 char *warn_for, int warn) |
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175 { |
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176 int x_len = x.capacity (); |
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177 int llb_len = llb.capacity (); |
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178 int lub_len = lub.capacity (); |
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179 int c_rows = c.rows (); |
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180 int c_cols = c.columns (); |
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181 |
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182 int ok = 1; |
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183 if (warn) |
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184 { |
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185 if (c_rows == 0 || c_cols == 0 || llb_len == 0 || lub_len == 0) |
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186 { |
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187 ok = 0; |
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188 error ("%s: linear constraints must have nonzero dimensions", |
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189 warn_for); |
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190 } |
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191 else if (x_len != c_cols || llb_len != lub_len || llb_len != c_rows) |
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192 { |
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193 ok = 0; |
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194 error ("%s: linear constraints have inconsistent dimensions", |
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195 warn_for); |
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196 } |
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197 } |
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198 |
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199 return ok; |
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200 } |
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201 |
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202 static int |
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203 nonlinear_constraints_ok (const ColumnVector& x, const ColumnVector& nllb, |
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204 NLFunc::nonlinear_fcn g, const ColumnVector& nlub, |
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205 char *warn_for, int warn) |
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206 { |
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207 int nllb_len = nllb.capacity (); |
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208 int nlub_len = nlub.capacity (); |
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209 ColumnVector c = (*g) (x); |
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210 int c_len = c.capacity (); |
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211 |
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212 int ok = 1; |
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213 if (warn) |
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214 { |
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215 if (nllb_len == 0 || nlub_len == 0 || c_len == 0) |
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216 { |
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217 ok = 0; |
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218 error ("%s: nonlinear constraints have nonzero dimensions", |
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219 warn_for); |
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220 } |
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221 else if (nllb_len != nlub_len || nllb_len != c_len) |
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222 { |
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223 ok = 0; |
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224 error ("%s: nonlinear constraints have inconsistent dimensions", |
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225 warn_for); |
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226 } |
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227 } |
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228 return ok; |
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229 } |
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230 |
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231 #endif |
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232 |
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233 #if defined (NPSOL_MISSING) |
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234 DEFUN_DLD (npsol, , , |
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235 "This function requires NPSOL, which is not freely\n\ |
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236 redistributable. For more information, read the file\n\ |
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237 libcruft/npsol/README.MISSING in the source distribution.") |
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238 #else |
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239 DEFUN_DLD (npsol, args, nargout, |
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240 "[X, OBJ, INFO, LAMBDA] = npsol (X, PHI [, LB, UB] [, A_LB, A, A_UB]\n\ |
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241 [, G_LB, G, G_UB])\n\ |
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242 \n\ |
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243 Groups of arguments surrounded in `[]' are optional, but\n\ |
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244 must appear in the same relative order shown above.\n\ |
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245 \n\ |
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246 The second argument is a string containing the name of the objective\n\ |
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247 function to call. The objective function must be of the form\n\ |
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248 \n\ |
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249 y = phi (x)\n\ |
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250 \n\ |
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251 where x is a vector and y is a scalar.\n\ |
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252 \n\ |
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253 The argument G is a string containing the name of the function that\n\ |
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254 defines the nonlinear constraints. It must be of the form\n\ |
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255 \n\ |
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256 y = g (x)\n\ |
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257 \n\ |
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258 where x is a vector and y is a vector.") |
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259 #endif |
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260 { |
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261 /* |
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262 |
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263 Handle all of the following: |
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264 |
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265 1. npsol (x, phi) |
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266 2. npsol (x, phi, lb, ub) |
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267 3. npsol (x, phi, lb, ub, llb, c, lub) |
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268 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
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269 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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270 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
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271 7. npsol (x, phi, llb, c, lub) |
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272 8. npsol (x, phi, nllb, g, nlub) |
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273 |
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274 */ |
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275 |
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276 octave_value_list retval; |
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277 |
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278 #if defined (NPSOL_MISSING) |
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279 |
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280 // Force a bad value of inform, and empty matrices for x, phi, and |
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281 // lambda. |
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282 |
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283 retval.resize (4, Matrix ()); |
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284 |
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285 retval(2) = -1.0; |
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286 |
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287 print_usage ("npsol"); |
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288 |
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289 #else |
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290 |
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291 int nargin = args.length (); |
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292 |
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293 if (nargin < 2 || nargin == 3 || nargin == 6 || nargin == 9 |
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294 || nargin > 10 || nargout > 4) |
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295 { |
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296 print_usage ("npsol"); |
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297 return retval; |
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298 } |
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299 |
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300 ColumnVector x = args(0).vector_value (); |
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301 |
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302 if (error_state || x.capacity () == 0) |
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303 { |
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304 error ("npsol: expecting vector as first argument"); |
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305 return retval; |
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306 } |
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307 |
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308 npsol_objective = extract_function |
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309 (args(1), "npsol", "__npsol_obj__", |
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310 "function phi = __npsol_obj__ (x) phi = ", |
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311 "; endfunction"); |
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312 |
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313 if (! npsol_objective) |
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314 return retval; |
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315 |
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316 Objective func (npsol_objective_function); |
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317 |
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318 ColumnVector soln; |
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319 |
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320 Bounds bounds; |
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321 if (nargin == 4 || nargin == 7 || nargin == 10) |
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322 { |
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323 ColumnVector lb = args(2).vector_value (); |
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324 ColumnVector ub = args(3).vector_value (); |
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325 |
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326 int lb_len = lb.capacity (); |
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327 int ub_len = ub.capacity (); |
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328 |
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329 if (error_state || lb_len != ub_len || lb_len != x.capacity ()) |
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330 { |
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331 error ("npsol: lower and upper bounds and decision variable vector"); |
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332 error ("must all have the same number of elements"); |
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333 return retval; |
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334 } |
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335 |
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336 bounds.resize (lb_len); |
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337 bounds.set_lower_bounds (lb); |
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338 bounds.set_upper_bounds (ub); |
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339 } |
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340 |
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341 double objf; |
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342 ColumnVector lambda; |
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343 int inform; |
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344 |
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345 if (nargin == 2) |
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346 { |
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347 // 1. npsol (x, phi) |
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348 |
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349 NPSOL nlp (x, func); |
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350 nlp.set_options (npsol_opts); |
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351 soln = nlp.minimize (objf, inform, lambda); |
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352 |
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353 goto solved; |
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354 } |
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355 |
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356 if (nargin == 4) |
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357 { |
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358 // 2. npsol (x, phi, lb, ub) |
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359 |
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360 NPSOL nlp (x, func, bounds); |
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361 nlp.set_options (npsol_opts); |
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362 soln = nlp.minimize (objf, inform, lambda); |
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363 |
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364 goto solved; |
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365 } |
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366 |
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367 npsol_constraints = 0; |
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368 if (nargin == 5 || nargin == 7 || nargin == 8 || nargin == 10) |
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369 npsol_constraints = extract_function |
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370 (args(nargin-2), "npsol", "__npsol_constr__", |
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371 "function y = __npsol_constr__ (x) y = ", |
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372 "; endfunction"); |
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373 |
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374 if (nargin == 7 || nargin == 5) |
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375 { |
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376 if (! npsol_constraints) |
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377 { |
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378 ColumnVector lub = args(nargin-1).vector_value (); |
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379 ColumnVector llb = args(nargin-3).vector_value (); |
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380 |
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381 if (error_state || llb.capacity () == 0 || lub.capacity () == 0) |
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382 { |
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383 error ("npsol: bounds for linear constraints must be vectors"); |
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384 return retval; |
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385 } |
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386 |
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387 Matrix c = args(nargin-2).matrix_value (); |
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388 |
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389 if (error_state) |
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390 { |
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391 error ("npsol: invalid linear constraint matrix"); |
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392 return retval; |
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393 } |
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394 |
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395 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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396 return retval; |
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397 |
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398 LinConst linear_constraints (llb, c, lub); |
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399 |
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400 if (nargin == 5) |
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401 { |
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402 // 7. npsol (x, phi, llb, c, lub) |
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403 |
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404 NPSOL nlp (x, func, linear_constraints); |
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405 nlp.set_options (npsol_opts); |
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406 soln = nlp.minimize (objf, inform, lambda); |
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407 } |
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408 else |
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409 { |
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410 // 3. npsol (x, phi, lb, ub, llb, c, lub) |
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411 |
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412 NPSOL nlp (x, func, bounds, linear_constraints); |
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413 nlp.set_options (npsol_opts); |
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414 soln = nlp.minimize (objf, inform, lambda); |
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415 } |
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416 goto solved; |
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417 } |
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418 else |
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419 { |
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420 ColumnVector nlub = args(nargin-1).vector_value (); |
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421 ColumnVector nllb = args(nargin-3).vector_value (); |
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422 |
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423 if (error_state |
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424 || (! nonlinear_constraints_ok |
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425 (x, nllb, npsol_constraint_function, nlub, "npsol", 1))) |
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426 return retval; |
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427 |
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428 NLFunc const_func (npsol_constraint_function); |
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429 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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430 |
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431 if (nargin == 5) |
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432 { |
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433 // 8. npsol (x, phi, nllb, g, nlub) |
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434 |
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435 NPSOL nlp (x, func, nonlinear_constraints); |
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436 nlp.set_options (npsol_opts); |
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437 soln = nlp.minimize (objf, inform, lambda); |
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438 } |
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439 else |
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440 { |
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441 // 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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442 |
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443 NPSOL nlp (x, func, bounds, nonlinear_constraints); |
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444 nlp.set_options (npsol_opts); |
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445 soln = nlp.minimize (objf, inform, lambda); |
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446 } |
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447 goto solved; |
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448 } |
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449 } |
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450 |
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451 if (nargin == 8 || nargin == 10) |
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452 { |
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453 if (! npsol_constraints) |
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454 { |
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455 // Produce error message. |
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456 |
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457 is_valid_function (args(nargin-2), "npsol", 1); |
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458 } |
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459 else |
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460 { |
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461 ColumnVector nlub = args(nargin-1).vector_value (); |
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462 ColumnVector nllb = args(nargin-3).vector_value (); |
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463 |
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464 if (error_state |
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465 || (! nonlinear_constraints_ok |
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466 (x, nllb, npsol_constraint_function, nlub, "npsol", 1))) |
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467 return retval; |
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468 |
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469 NLFunc const_func (npsol_constraint_function); |
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470 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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471 |
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472 ColumnVector lub = args(nargin-4).vector_value (); |
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473 ColumnVector llb = args(nargin-6).vector_value (); |
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474 |
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475 if (error_state || llb.capacity () == 0 || lub.capacity () == 0) |
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476 { |
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477 error ("npsol: bounds for linear constraints must be vectors"); |
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478 return retval; |
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479 } |
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480 |
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|
481 Matrix c = args(nargin-5).matrix_value (); |
|
|
482 |
|
|
483 if (error_state) |
|
|
484 { |
|
|
485 error ("npsol: invalid linear constraint matrix"); |
|
|
486 return retval; |
|
|
487 } |
|
|
488 |
|
|
489 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
|
|
490 return retval; |
|
|
491 |
|
|
492 LinConst linear_constraints (llb, c, lub); |
|
|
493 |
|
|
494 if (nargin == 8) |
|
|
495 { |
|
|
496 // 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
|
|
497 |
|
|
498 NPSOL nlp (x, func, linear_constraints, |
|
|
499 nonlinear_constraints); |
|
|
500 nlp.set_options (npsol_opts); |
|
|
501 soln = nlp.minimize (objf, inform, lambda); |
|
|
502 } |
|
|
503 else |
|
|
504 { |
|
|
505 // 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
|
|
506 |
|
|
507 NPSOL nlp (x, func, bounds, linear_constraints, |
|
|
508 nonlinear_constraints); |
|
|
509 nlp.set_options (npsol_opts); |
|
|
510 soln = nlp.minimize (objf, inform, lambda); |
|
|
511 } |
|
|
512 goto solved; |
|
|
513 } |
|
|
514 } |
|
|
515 |
|
|
516 return retval; |
|
|
517 |
|
|
518 solved: |
|
|
519 |
|
|
520 retval.resize (nargout ? nargout : 1); |
|
|
521 retval(0) = soln, 1; |
|
|
522 if (nargout > 1) |
|
|
523 retval(1) = objf; |
|
|
524 if (nargout > 2) |
|
|
525 retval(2) = static_cast<double> (inform); |
|
|
526 if (nargout > 3) |
|
|
527 retval(3) = lambda; |
|
|
528 |
|
|
529 #endif |
|
|
530 |
|
|
531 return retval; |
|
|
532 } |
|
|
533 |
|
|
534 #ifndef NPSOL_MISSING |
|
|
535 |
|
|
536 typedef void (NPSOL_options::*d_set_opt_mf) (double); |
|
|
537 typedef void (NPSOL_options::*i_set_opt_mf) (int); |
|
|
538 typedef double (NPSOL_options::*d_get_opt_mf) (void); |
|
|
539 typedef int (NPSOL_options::*i_get_opt_mf) (void); |
|
|
540 |
|
|
541 #define MAX_TOKENS 5 |
|
|
542 |
|
|
543 struct NPSOL_OPTIONS |
|
|
544 { |
|
|
545 const char *keyword; |
|
|
546 const char *kw_tok[MAX_TOKENS + 1]; |
|
|
547 int min_len[MAX_TOKENS + 1]; |
|
|
548 int min_toks_to_match; |
|
|
549 d_set_opt_mf d_set_fcn; |
|
|
550 i_set_opt_mf i_set_fcn; |
|
|
551 d_get_opt_mf d_get_fcn; |
|
|
552 i_get_opt_mf i_get_fcn; |
|
|
553 }; |
|
|
554 |
|
|
555 static NPSOL_OPTIONS npsol_option_table [] = |
|
|
556 { |
|
|
557 { "central difference interval", |
|
|
558 { "central", "difference", "interval", 0, 0, 0, }, |
|
|
559 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
560 NPSOL_options::set_central_difference_interval, 0, |
|
|
561 NPSOL_options::central_difference_interval, 0, }, |
|
|
562 |
|
|
563 { "crash tolerance", |
|
|
564 { "crash", "tolerance", 0, 0, 0, 0, }, |
|
|
565 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
566 NPSOL_options::set_crash_tolerance, 0, |
|
|
567 NPSOL_options::crash_tolerance, 0, }, |
|
|
568 |
|
|
569 { "derivative level", |
|
|
570 { "derivative", "level", 0, 0, 0, 0, }, |
|
|
571 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
572 0, NPSOL_options::set_derivative_level, |
|
|
573 0, NPSOL_options::derivative_level, }, |
|
|
574 |
|
|
575 { "difference interval", |
|
|
576 { "difference", "interval", 0, 0, 0, 0, }, |
|
|
577 { 3, 0, 0, 0, 0, 0, }, 1, |
|
|
578 NPSOL_options::set_difference_interval, 0, |
|
|
579 NPSOL_options::difference_interval, 0, }, |
|
|
580 |
|
|
581 { "function precision", |
|
|
582 { "function", "precision", 0, 0, 0, 0, }, |
|
|
583 { 2, 0, 0, 0, 0, 0, }, 1, |
|
|
584 NPSOL_options::set_function_precision, 0, |
|
|
585 NPSOL_options::function_precision, 0, }, |
|
|
586 |
|
|
587 { "infinite bound size", |
|
|
588 { "infinite", "bound", "size", 0, 0, 0, }, |
|
|
589 { 1, 1, 0, 0, 0, 0, }, 2, |
|
|
590 NPSOL_options::set_infinite_bound, 0, |
|
|
591 NPSOL_options::infinite_bound, 0, }, |
|
|
592 |
|
|
593 { "infinite step size", |
|
|
594 { "infinite", "step", "size", 0, 0, 0, }, |
|
|
595 { 1, 1, 0, 0, 0, 0, }, 2, |
|
|
596 NPSOL_options::set_infinite_step, 0, |
|
|
597 NPSOL_options::infinite_step, 0, }, |
|
|
598 |
|
|
599 { "linear feasibility tolerance", |
|
|
600 { "linear", "feasibility", "tolerance", 0, 0, 0, }, |
|
|
601 { 5, 0, 0, 0, 0, 0, }, 1, |
|
|
602 NPSOL_options::set_linear_feasibility_tolerance, 0, |
|
|
603 NPSOL_options::linear_feasibility_tolerance, 0, }, |
|
|
604 |
|
|
605 { "linesearch tolerance", |
|
|
606 { "linesearch", "tolerance", 0, 0, 0, 0, }, |
|
|
607 { 5, 0, 0, 0, 0, 0, }, 1, |
|
|
608 NPSOL_options::set_linesearch_tolerance, 0, |
|
|
609 NPSOL_options::linesearch_tolerance, 0, }, |
|
|
610 |
|
|
611 { "major iteration limit", |
|
|
612 { "major", "iteration", "limit", 0, 0, 0, }, |
|
|
613 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
614 0, NPSOL_options::set_major_iteration_limit, |
|
|
615 0, NPSOL_options::major_iteration_limit, }, |
|
|
616 |
|
|
617 { "minor iteration limit", |
|
|
618 { "minor", "iteration", "limit", 0, 0, 0, }, |
|
|
619 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
620 0, NPSOL_options::set_minor_iteration_limit, |
|
|
621 0, NPSOL_options::minor_iteration_limit, }, |
|
|
622 |
|
|
623 { "major print level", |
|
|
624 { "major", "print", "level", 0, 0, 0, }, |
|
|
625 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
626 0, NPSOL_options::set_major_print_level, |
|
|
627 0, NPSOL_options::major_print_level, }, |
|
|
628 |
|
|
629 { "minor print level", |
|
|
630 { "minor", "print", "level", 0, 0, 0, }, |
|
|
631 { 2, 1, 0, 0, 0, 0, }, 2, |
|
|
632 0, NPSOL_options::set_minor_print_level, |
|
|
633 0, NPSOL_options::minor_print_level, }, |
|
|
634 |
|
|
635 { "nonlinear feasibility tolerance", |
|
|
636 { "nonlinear", "feasibility", "tolerance", 0, 0, }, |
|
|
637 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
638 NPSOL_options::set_nonlinear_feasibility_tolerance, 0, |
|
|
639 NPSOL_options::nonlinear_feasibility_tolerance, 0, }, |
|
|
640 |
|
|
641 { "optimality tolerance", |
|
|
642 { "optimality", "tolerance", 0, 0, 0, 0, }, |
|
|
643 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
644 NPSOL_options::set_optimality_tolerance, 0, |
|
|
645 NPSOL_options::optimality_tolerance, 0, }, |
|
|
646 |
|
|
647 { "start objective check at variable", |
|
|
648 { "start", "objective", "check", "at", "variable", 0, }, |
|
|
649 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
650 0, NPSOL_options::set_start_objective_check, |
|
|
651 0, NPSOL_options::start_objective_check, }, |
|
|
652 |
|
|
653 { "start constraint check at variable", |
|
|
654 { "start", "constraint", "check", "at", "variable", 0, }, |
|
|
655 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
656 0, NPSOL_options::set_start_constraint_check, |
|
|
657 0, NPSOL_options::start_constraint_check, }, |
|
|
658 |
|
|
659 { "stop objective check at variable", |
|
|
660 { "stop", "objective", "check", "at", "variable", 0, }, |
|
|
661 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
662 0, NPSOL_options::set_stop_objective_check, |
|
|
663 0, NPSOL_options::stop_objective_check, }, |
|
|
664 |
|
|
665 { "stop constraint check at variable", |
|
|
666 { "stop", "constraint", "check", "at", "variable", 0, }, |
|
|
667 { 3, 1, 0, 0, 0, 0, }, 2, |
|
|
668 0, NPSOL_options::set_stop_constraint_check, |
|
|
669 0, NPSOL_options::stop_constraint_check, }, |
|
|
670 |
|
|
671 { "verify level", |
|
|
672 { "verify", "level", 0, 0, 0, 0, }, |
|
|
673 { 1, 0, 0, 0, 0, 0, }, 1, |
|
|
674 0, NPSOL_options::set_verify_level, |
|
|
675 0, NPSOL_options::verify_level, }, |
|
|
676 |
|
|
677 { 0, |
|
|
678 { 0, 0, 0, 0, 0, 0, }, |
|
|
679 { 0, 0, 0, 0, 0, 0, }, 0, |
|
|
680 0, 0, 0, 0, }, |
|
|
681 }; |
|
|
682 |
|
|
683 static void |
|
|
684 print_npsol_option_list (ostream& os) |
|
|
685 { |
|
|
686 print_usage ("npsol_options", 1); |
|
|
687 |
|
|
688 os << "\n" |
|
|
689 << "Options for npsol include:\n\n" |
|
|
690 << " keyword value\n" |
|
|
691 << " ------- -----\n\n"; |
|
|
692 |
|
|
693 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
694 |
|
|
695 const char *keyword; |
|
|
696 while ((keyword = list->keyword) != 0) |
|
|
697 { |
|
|
698 os.form (" %-40s ", keyword); |
|
|
699 if (list->d_get_fcn) |
|
|
700 { |
|
|
701 double val = (npsol_opts.*list->d_get_fcn) (); |
|
|
702 if (val < 0.0) |
|
|
703 os << "computed automatically"; |
|
|
704 else |
|
|
705 os << val; |
|
|
706 } |
|
|
707 else |
|
|
708 { |
|
|
709 int val = (npsol_opts.*list->i_get_fcn) (); |
|
|
710 if (val < 0) |
|
|
711 os << "depends on problem size"; |
|
|
712 else |
|
|
713 os << val; |
|
|
714 } |
|
|
715 os << "\n"; |
|
|
716 list++; |
|
|
717 } |
|
|
718 |
|
|
719 os << "\n"; |
|
|
720 } |
|
|
721 |
|
|
722 static void |
|
|
723 set_npsol_option (const string& keyword, double val) |
|
|
724 { |
|
|
725 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
726 |
|
|
727 while (list->keyword != 0) |
|
|
728 { |
|
|
729 if (keyword_almost_match (list->kw_tok, list->min_len, keyword, |
|
|
730 list->min_toks_to_match, MAX_TOKENS)) |
|
|
731 { |
|
|
732 if (list->d_set_fcn) |
|
|
733 (npsol_opts.*list->d_set_fcn) (val); |
|
|
734 else |
|
|
735 { |
|
|
736 if (xisnan (val)) |
|
|
737 { |
|
|
738 error ("npsol_options: %s: expecting integer, found NaN", |
|
|
739 keyword.c_str ()); |
|
|
740 } |
|
|
741 else |
|
|
742 (npsol_opts.*list->i_set_fcn) (NINT (val)); |
|
|
743 } |
|
|
744 return; |
|
|
745 } |
|
|
746 list++; |
|
|
747 } |
|
|
748 |
|
|
749 warning ("npsol_options: no match for `%s'", keyword.c_str ()); |
|
|
750 } |
|
|
751 |
|
|
752 static octave_value_list |
|
|
753 show_npsol_option (const string& keyword) |
|
|
754 { |
|
|
755 octave_value retval; |
|
|
756 |
|
|
757 NPSOL_OPTIONS *list = npsol_option_table; |
|
|
758 |
|
|
759 while (list->keyword != 0) |
|
|
760 { |
|
|
761 if (keyword_almost_match (list->kw_tok, list->min_len, keyword, |
|
|
762 list->min_toks_to_match, MAX_TOKENS)) |
|
|
763 { |
|
|
764 if (list->d_get_fcn) |
|
|
765 { |
|
|
766 double val = (npsol_opts.*list->d_get_fcn) (); |
|
|
767 if (val < 0.0) |
|
|
768 retval = "computed automatically"; |
|
|
769 else |
|
|
770 retval = val; |
|
|
771 } |
|
|
772 else |
|
|
773 { |
|
|
774 int val = (npsol_opts.*list->i_get_fcn) (); |
|
|
775 if (val < 0) |
|
|
776 retval = "depends on problem size"; |
|
|
777 else |
|
|
778 retval = static_cast<double> (val); |
|
|
779 } |
|
|
780 |
|
|
781 return retval; |
|
|
782 } |
|
|
783 list++; |
|
|
784 } |
|
|
785 |
|
|
786 warning ("npsol_options: no match for `%s'", keyword.c_str ()); |
|
|
787 |
|
|
788 return retval; |
|
|
789 } |
|
|
790 |
|
|
791 #endif |
|
|
792 |
|
|
793 #if defined (NPSOL_MISSING) |
|
|
794 DEFUN_DLD (npsol_options, , , |
|
|
795 "This function requires NPSOL, which is not freely\n\ |
|
|
796 redistributable. For more information, read the file\n\ |
|
|
797 libcruft/npsol/README.MISSING in the source distribution.") |
|
|
798 #else |
|
|
799 DEFUN_DLD (npsol_options, args, , |
|
|
800 "npsol_options (KEYWORD, VALUE)\n\ |
|
|
801 \n\ |
|
|
802 Set or show options for npsol. Keywords may be abbreviated\n\ |
|
|
803 to the shortest match.") |
|
|
804 #endif |
|
|
805 { |
|
|
806 octave_value_list retval; |
|
|
807 |
|
|
808 #if defined (NPSOL_MISSING) |
|
|
809 |
|
|
810 print_usage ("npsol_options"); |
|
|
811 |
|
|
812 #else |
|
|
813 |
|
|
814 int nargin = args.length (); |
|
|
815 |
|
|
816 if (nargin == 0) |
|
|
817 { |
|
|
818 print_npsol_option_list (octave_stdout); |
|
|
819 return retval; |
|
|
820 } |
|
|
821 else if (nargin == 1 || nargin == 2) |
|
|
822 { |
|
|
823 string keyword = args(0).string_value (); |
|
|
824 |
|
|
825 if (! error_state) |
|
|
826 { |
|
|
827 if (nargin == 1) |
|
|
828 return show_npsol_option (keyword); |
|
|
829 else |
|
|
830 { |
|
|
831 double val = args(1).double_value (); |
|
|
832 |
|
|
833 if (! error_state) |
|
|
834 { |
|
|
835 set_npsol_option (keyword, val); |
|
|
836 return retval; |
|
|
837 } |
|
|
838 } |
|
|
839 } |
|
|
840 } |
|
|
841 |
|
|
842 print_usage ("npsol_options"); |
|
|
843 |
|
|
844 #endif |
|
|
845 |
|
|
846 return retval; |
|
|
847 } |
|
|
848 |
|
|
849 /* |
|
|
850 ;;; Local Variables: *** |
|
|
851 ;;; mode: C++ *** |
|
|
852 ;;; End: *** |
|
|
853 */ |
