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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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4 Copyright (C) 1993 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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24 #ifdef __GNUG__ |
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25 #pragma implementation |
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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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30 #include "NPSOL.h" |
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31 |
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32 #include "tree-const.h" |
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33 #include "variables.h" |
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34 #include "gripes.h" |
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35 #include "error.h" |
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36 #include "utils.h" |
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7
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37 #include "f-npsol.h" |
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1
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38 |
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39 // Global pointers for user defined functions required by npsol. |
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40 static tree *npsol_objective; |
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41 static tree *npsol_constraints; |
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42 |
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43 #ifdef WITH_DLD |
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44 tree_constant * |
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162
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45 builtin_npsol_2 (const tree_constant *args, int nargin, int nargout) |
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1
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46 { |
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47 return npsol (args, nargin, nargout); |
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48 } |
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49 #endif |
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50 |
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51 double |
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162
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52 npsol_objective_function (const ColumnVector& x) |
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1
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53 { |
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54 int n = x.capacity (); |
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55 |
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56 tree_constant decision_vars; |
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57 if (n > 1) |
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58 { |
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59 Matrix m (n, 1); |
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60 for (int i = 0; i < n; i++) |
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61 m (i, 0) = x.elem (i); |
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62 decision_vars = tree_constant (m); |
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63 } |
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64 else |
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65 { |
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66 double d = x.elem (0); |
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67 decision_vars = tree_constant (d); |
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68 } |
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69 |
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70 // tree_constant name = tree_constant (npsol_objective->name ()); |
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71 tree_constant *args = new tree_constant [2]; |
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72 // args[0] = name; |
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73 args[1] = decision_vars; |
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74 |
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75 tree_constant objective_value; |
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76 if (npsol_objective != NULL_TREE) |
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77 { |
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78 tree_constant *tmp = npsol_objective->eval (args, 2, 1, 0); |
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79 delete [] args; |
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80 if (tmp != NULL_TREE_CONST && tmp[0].is_defined ()) |
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81 { |
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82 objective_value = tmp[0]; |
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83 delete [] tmp; |
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84 } |
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85 else |
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86 { |
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87 delete [] tmp; |
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158
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88 error ("npsol: error evaluating objective function"); |
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1
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89 jump_to_top_level (); |
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90 } |
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91 } |
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92 |
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93 static double retval; |
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94 retval = 0.0; |
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95 |
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96 switch (objective_value.const_type ()) |
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97 { |
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98 case tree_constant_rep::matrix_constant: |
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99 { |
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100 Matrix m = objective_value.matrix_value (); |
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101 if (m.rows () == 1 && m.columns () == 1) |
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102 retval = m.elem (0, 0); |
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103 else |
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104 gripe_user_returned_invalid ("npsol_objective"); |
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105 } |
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106 break; |
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107 case tree_constant_rep::scalar_constant: |
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108 retval = objective_value.double_value (); |
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109 break; |
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110 default: |
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111 gripe_user_returned_invalid ("npsol_objective"); |
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112 break; |
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113 } |
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114 |
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115 return retval; |
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116 } |
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117 |
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118 ColumnVector |
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162
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119 npsol_constraint_function (const ColumnVector& x) |
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1
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120 { |
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121 ColumnVector retval; |
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122 |
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123 int n = x.capacity (); |
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124 |
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125 tree_constant decision_vars; |
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126 if (n > 1) |
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127 { |
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128 Matrix m (n, 1); |
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129 for (int i = 0; i < n; i++) |
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130 m (i, 0) = x.elem (i); |
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131 decision_vars = tree_constant (m); |
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132 } |
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133 else |
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134 { |
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135 double d = x.elem (0); |
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136 decision_vars = tree_constant (d); |
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137 } |
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138 |
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139 // tree_constant name = tree_constant (npsol_constraints->name ()); |
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140 tree_constant *args = new tree_constant [2]; |
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141 // args[0] = name; |
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142 args[1] = decision_vars; |
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143 |
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144 if (npsol_constraints != NULL_TREE) |
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145 { |
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146 tree_constant *tmp = npsol_constraints->eval (args, 2, 1, 0); |
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147 delete [] args; |
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148 if (tmp != NULL_TREE_CONST && tmp[0].is_defined ()) |
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149 { |
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150 retval = tmp[0].to_vector (); |
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151 delete [] tmp; |
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152 } |
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153 else |
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154 { |
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155 delete [] tmp; |
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158
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156 error ("npsol: error evaluating constraints"); |
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1
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157 jump_to_top_level (); |
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158 } |
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159 } |
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160 |
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161 return retval; |
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162 } |
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163 |
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164 int |
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165 linear_constraints_ok (const ColumnVector& x, const ColumnVector& llb, |
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166 const Matrix& c, const ColumnVector& lub, |
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167 char *warn_for, int warn) |
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168 { |
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169 int x_len = x.capacity (); |
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170 int llb_len = llb.capacity (); |
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171 int lub_len = lub.capacity (); |
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172 int c_rows = c.rows (); |
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173 int c_cols = c.columns (); |
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174 |
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132
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175 int ok = 1; |
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176 if (warn) |
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177 { |
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178 if (c_rows == 0 || c_cols == 0 || llb_len == 0 || lub_len == 0) |
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179 { |
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180 ok = 0; |
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158
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181 error ("%s: linear constraints must have nonzero dimensions", |
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182 warn_for); |
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132
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183 } |
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184 else if (x_len != c_cols || llb_len != lub_len || llb_len != c_rows) |
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185 { |
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186 ok = 0; |
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158
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187 error ("%s: linear constraints have inconsistent dimensions", |
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188 warn_for); |
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132
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189 } |
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190 } |
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1
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191 |
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192 return ok; |
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193 } |
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194 |
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195 int |
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196 nonlinear_constraints_ok (const ColumnVector& x, const ColumnVector& nllb, |
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197 nonlinear_fcn g, const ColumnVector& nlub, |
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198 char *warn_for, int warn) |
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199 { |
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200 int nllb_len = nllb.capacity (); |
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201 int nlub_len = nlub.capacity (); |
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202 ColumnVector c = (*g) (x); |
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203 int c_len = c.capacity (); |
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204 |
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132
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205 int ok = 1; |
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206 if (warn) |
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207 { |
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208 if (nllb_len == 0 || nlub_len == 0 || c_len == 0) |
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209 { |
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210 ok = 0; |
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211 error ("%s: nonlinear constraints have nonzero dimensions", |
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212 warn_for); |
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132
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213 } |
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214 else if (nllb_len != nlub_len || nllb_len != c_len) |
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215 { |
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216 ok = 0; |
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162
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217 error ("%s: nonlinear constraints have inconsistent dimensions", |
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218 warn_for); |
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132
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219 } |
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135
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220 } |
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1
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221 return ok; |
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222 } |
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223 |
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224 tree_constant * |
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162
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225 npsol (const tree_constant *args, int nargin, int nargout) |
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1
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226 { |
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227 /* |
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228 |
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229 Handle all of the following: |
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230 |
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231 1. npsol (x, phi) |
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232 2. npsol (x, phi, lb, ub) |
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233 3. npsol (x, phi, lb, ub, llb, c, lub) |
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234 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
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235 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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236 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
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237 7. npsol (x, phi, llb, c, lub) |
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238 8. npsol (x, phi, nllb, g, nlub) |
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239 |
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240 */ |
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241 |
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242 // Assumes that we have been given the correct number of arguments. |
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243 |
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244 tree_constant *retval = NULL_TREE_CONST; |
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245 |
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246 ColumnVector x = args[1].to_vector (); |
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247 |
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248 if (x.capacity () == 0) |
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249 { |
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158
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250 error ("npsol: expecting vector as first argument"); |
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1
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251 return retval; |
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252 } |
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253 |
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254 npsol_objective = is_valid_function (args[2], "npsol", 1); |
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255 if (npsol_objective == NULL_TREE |
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256 || takes_correct_nargs (npsol_objective, 2, "npsol", 1) != 1) |
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257 return retval; |
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258 |
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259 Objective func (npsol_objective_function); |
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260 |
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261 ColumnVector soln; |
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262 |
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263 Bounds bounds; |
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264 if (nargin == 5 || nargin == 8 || nargin == 11) |
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265 { |
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266 ColumnVector lb = args[3].to_vector (); |
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267 ColumnVector ub = args[4].to_vector (); |
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268 |
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269 int lb_len = lb.capacity (); |
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270 int ub_len = ub.capacity (); |
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271 if (lb_len != ub_len || lb_len != x.capacity ()) |
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272 { |
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214
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273 error ("npsol: lower and upper bounds and decision variable vector"); |
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274 error ("must all have the same number of elements"); |
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1
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275 return retval; |
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276 } |
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277 |
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278 bounds.resize (lb_len); |
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279 bounds.set_lower_bounds (lb); |
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280 bounds.set_upper_bounds (ub); |
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281 } |
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282 |
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283 double objf; |
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284 ColumnVector lambda; |
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285 int inform; |
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286 |
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287 if (nargin == 3) |
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288 { |
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289 // 1. npsol (x, phi) |
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290 |
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291 NPSOL nlp (x, func); |
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292 soln = nlp.minimize (objf, inform, lambda); |
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293 |
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294 goto solved; |
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295 } |
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296 |
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297 if (nargin == 5) |
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298 { |
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299 // 2. npsol (x, phi, lb, ub) |
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300 |
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301 NPSOL nlp (x, func, bounds); |
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302 soln = nlp.minimize (objf, inform, lambda); |
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303 |
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304 goto solved; |
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305 } |
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306 |
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307 npsol_constraints = NULL_TREE; |
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308 if (nargin == 6 || nargin == 8 || nargin == 9 || nargin == 11) |
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309 npsol_constraints = is_valid_function (args[nargin-2], "npsol", 0); |
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310 |
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311 if (nargin == 8 || nargin == 6) |
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312 { |
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313 if (npsol_constraints == NULL_TREE) |
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314 { |
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315 ColumnVector lub = args[nargin-1].to_vector (); |
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316 Matrix c = args[nargin-2].to_matrix (); |
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317 ColumnVector llb = args[nargin-3].to_vector (); |
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318 |
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215
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319 if (llb.capacity () == 0 || lub.capacity () == 0) |
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320 { |
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321 error ("npsol: bounds for linear constraints must be vectors"); |
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322 return retval; |
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323 } |
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1
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324 |
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325 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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326 return retval; |
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327 |
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215
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328 LinConst linear_constraints (llb, c, lub); |
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329 |
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1
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330 if (nargin == 6) |
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331 { |
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332 // 7. npsol (x, phi, llb, c, lub) |
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333 |
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334 NPSOL nlp (x, func, linear_constraints); |
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335 soln = nlp.minimize (objf, inform, lambda); |
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336 } |
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337 else |
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338 { |
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339 // 3. npsol (x, phi, lb, ub, llb, c, lub) |
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340 |
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341 NPSOL nlp (x, func, bounds, linear_constraints); |
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342 soln = nlp.minimize (objf, inform, lambda); |
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343 } |
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344 goto solved; |
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345 } |
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346 else |
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347 { |
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348 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
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349 { |
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350 ColumnVector nlub = args[nargin-1].to_vector (); |
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351 ColumnVector nllb = args[nargin-3].to_vector (); |
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352 |
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353 NLFunc const_func (npsol_constraint_function); |
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354 |
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355 if (! nonlinear_constraints_ok |
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356 (x, nllb, npsol_constraint_function, nlub, "npsol", 1)) |
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357 return retval; |
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358 |
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359 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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360 |
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361 if (nargin == 6) |
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362 { |
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363 // 8. npsol (x, phi, nllb, g, nlub) |
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364 |
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365 NPSOL nlp (x, func, nonlinear_constraints); |
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366 soln = nlp.minimize (objf, inform, lambda); |
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367 } |
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368 else |
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369 { |
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370 // 5. npsol (x, phi, lb, ub, nllb, g, nlub) |
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371 |
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372 NPSOL nlp (x, func, bounds, nonlinear_constraints); |
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373 soln = nlp.minimize (objf, inform, lambda); |
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374 } |
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375 goto solved; |
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376 } |
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377 } |
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378 } |
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379 |
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380 if (nargin == 9 || nargin == 11) |
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381 { |
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382 if (npsol_constraints == NULL_TREE) |
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383 { |
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384 // Produce error message. |
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385 is_valid_function (args[nargin-2], "npsol", 1); |
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386 } |
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387 else |
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388 { |
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389 if (takes_correct_nargs (npsol_constraints, 2, "npsol", 1)) |
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390 { |
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391 ColumnVector nlub = args[nargin-1].to_vector (); |
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392 ColumnVector nllb = args[nargin-3].to_vector (); |
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393 |
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394 NLFunc const_func (npsol_constraint_function); |
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395 |
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396 if (! nonlinear_constraints_ok |
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397 (x, nllb, npsol_constraint_function, nlub, "npsol", 1)) |
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398 return retval; |
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399 |
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400 NLConst nonlinear_constraints (nllb, const_func, nlub); |
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401 |
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402 ColumnVector lub = args[nargin-4].to_vector (); |
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403 Matrix c = args[nargin-5].to_matrix (); |
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404 ColumnVector llb = args[nargin-6].to_vector (); |
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405 |
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215
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406 if (llb.capacity () == 0 || lub.capacity () == 0) |
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407 { |
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408 error ("npsol: bounds for linear constraints must be vectors"); |
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409 return retval; |
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410 } |
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411 |
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1
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412 if (! linear_constraints_ok (x, llb, c, lub, "npsol", 1)) |
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413 return retval; |
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414 |
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415 LinConst linear_constraints (llb, c, lub); |
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416 |
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417 if (nargin == 9) |
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418 { |
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419 // 6. npsol (x, phi, llb, c, lub, nllb, g, nlub) |
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420 |
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421 NPSOL nlp (x, func, linear_constraints, |
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422 nonlinear_constraints); |
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423 |
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424 soln = nlp.minimize (objf, inform, lambda); |
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425 } |
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426 else |
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427 { |
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428 // 4. npsol (x, phi, lb, ub, llb, c, lub, nllb, g, nlub) |
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429 |
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430 NPSOL nlp (x, func, bounds, linear_constraints, |
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431 nonlinear_constraints); |
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432 |
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433 soln = nlp.minimize (objf, inform, lambda); |
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434 } |
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435 goto solved; |
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436 } |
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437 } |
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438 } |
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439 |
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440 return retval; |
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441 |
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442 solved: |
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443 |
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444 retval = new tree_constant [nargout+1]; |
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445 retval[0] = tree_constant (soln, 1); |
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446 if (nargout > 1) |
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447 retval[1] = tree_constant (objf); |
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448 if (nargout > 2) |
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449 retval[2] = tree_constant ((double) inform); |
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450 if (nargout > 3) |
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451 retval[3] = tree_constant (lambda); |
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452 |
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453 return retval; |
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454 } |
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455 |
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456 #endif |
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457 |
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458 /* |
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459 ;;; Local Variables: *** |
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460 ;;; mode: C++ *** |
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461 ;;; page-delimiter: "^/\\*" *** |
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462 ;;; End: *** |
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463 */ |
