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1 // NPSOL.cc -*- C++ -*- |
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2 /* |
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3 |
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4 Copyright (C) 1992, 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 #ifndef NPSOL_MISSING |
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25 |
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26 #ifdef __GNUG__ |
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27 #pragma implementation |
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28 #endif |
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29 |
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30 #include <iostream.h> |
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31 #include <math.h> |
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32 #include "NPSOL.h" |
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33 #include "f77-uscore.h" |
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34 #include "sun-utils.h" |
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35 |
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36 extern "C" |
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37 { |
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38 int F77_FCN (npoptn) (char *, long); |
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39 |
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40 int F77_FCN (npsol) (int *, int *, int *, int *, int *, int *, |
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41 double *, double *, double *, int (*)(), |
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42 int (*)(), int *, int *, int *, double *, |
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43 double *, double *, double *, double *, |
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44 double *, double *, int *, int *, double *, |
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45 int *); |
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46 } |
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47 |
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48 static objective_fcn user_phi; |
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49 static gradient_fcn user_grad; |
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50 static nonlinear_fcn user_g; |
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51 static jacobian_fcn user_jac; |
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52 |
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53 int |
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54 npsol_objfun (int *mode, int *n, double *xx, double *objf, |
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55 double *objgrd, int *nstate) |
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56 { |
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57 int nn = *n; |
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58 Vector tmp_x (nn); |
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59 |
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60 for (int i = 0; i < nn; i++) |
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61 tmp_x.elem (i) = xx[i]; |
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62 |
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63 if (*mode == 0 || *mode == 2) |
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64 { |
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65 double value = (*user_phi) (tmp_x); |
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66 #if defined (sun) && defined (__GNUC__) |
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67 assign_double (objf, value); |
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68 #else |
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69 *objf = value; |
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70 #endif |
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71 } |
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72 |
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73 if ((*mode == 1 || *mode == 2) && user_grad != NULL) |
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74 { |
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75 Vector tmp_grad (nn); |
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76 |
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77 tmp_grad = (*user_grad) (tmp_x); |
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78 |
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79 for (i = 0; i < nn; i++) |
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80 objgrd[i] = tmp_grad.elem (i); |
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81 } |
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82 |
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83 return 0; |
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84 } |
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85 |
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86 int |
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87 npsol_confun (int *mode, int *ncnln, int *n, int *nrowj, int *needc, |
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88 double *xx, double *cons, double *cjac, int *nstate) |
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89 { |
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90 int nn = *n, nncnln = *ncnln; |
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91 Vector tmp_x (nn); |
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92 Vector tmp_c (nncnln); |
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93 |
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94 for (int i = 0; i < nn; i++) |
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95 tmp_x.elem (i) = xx[i]; |
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96 |
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97 tmp_c = (*user_g) (tmp_x); |
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98 |
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99 for (i = 0; i < nncnln; i++) |
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100 cons[i] = tmp_c.elem (i); |
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101 |
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102 if (user_jac != NULL) |
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103 { |
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104 Matrix tmp_jac (nncnln, nn); |
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105 |
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106 tmp_jac = (*user_jac) (tmp_x); |
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107 |
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108 int ld = *nrowj; |
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109 for (int j = 0; j < nn; j++) |
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110 for (i = 0; i < nncnln; i++) |
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111 cjac[i+j*ld] = tmp_jac (i, j); |
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112 } |
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113 |
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114 return 0; |
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115 } |
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116 |
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117 Vector |
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118 NPSOL::minimize (void) |
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119 { |
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120 double objf; |
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121 int inform; |
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122 Vector lambda; |
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123 return minimize (objf, inform, lambda); |
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124 } |
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125 |
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126 Vector |
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127 NPSOL::minimize (double& objf) |
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128 { |
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129 int inform; |
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130 Vector lambda; |
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131 return minimize (objf, inform, lambda); |
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132 } |
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133 |
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134 Vector |
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135 NPSOL::minimize (double& objf, int& inform) |
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136 { |
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137 Vector lambda; |
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138 return minimize (objf, inform, lambda); |
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139 } |
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140 |
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141 Vector |
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142 NPSOL::minimize (double& objf, int& inform, Vector& lambda) |
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143 { |
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144 // Dimensions of various things. |
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145 |
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146 int n = x.capacity (); |
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147 int nclin = lc.size (); |
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148 int ncnln = nlc.size (); |
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149 int nrowa = 1 > nclin ? 1 : nclin; |
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150 int nrowj = 1 > ncnln ? 1 : ncnln; |
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151 int nrowr = n; |
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152 |
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153 // Informative stuff. |
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154 |
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155 int iter; |
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156 int *istate = new int [n+nclin+ncnln]; |
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157 |
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158 // User defined function stuff is defined above in the functions |
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159 // npsol_confun() and npsol_objfun(); |
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160 |
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161 // Constraint stuff. |
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162 |
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163 double dummy; |
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164 double *pclin = &dummy; |
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165 Matrix clin; |
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166 if (nclin > 0) |
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167 { |
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168 clin = lc.constraint_matrix (); |
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169 pclin = clin.fortran_vec (); |
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170 } |
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171 |
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172 double *clow = new double [n+nclin+ncnln]; |
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173 double *cup = new double [n+nclin+ncnln]; |
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174 |
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175 if (bnds.size () > 0) |
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176 { |
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177 for (int i = 0; i < n; i++) |
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178 { |
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179 clow[i] = bnds.lower_bound (i); |
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180 cup[i] = bnds.upper_bound (i); |
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181 } |
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182 } |
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183 else |
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184 { |
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185 double huge = 1.0e30; |
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186 for (int i = 0; i < n; i++) |
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187 { |
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188 clow[i] = -huge; |
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189 cup[i] = huge; |
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190 } |
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191 } |
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192 |
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193 for (int i = 0; i < nclin; i++) |
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194 { |
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195 clow[i+n] = lc.lower_bound (i); |
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196 cup[i+n] = lc.upper_bound (i); |
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197 } |
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198 |
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199 for (i = 0; i < ncnln; i++) |
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200 { |
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201 clow[i+n+nclin] = nlc.lower_bound (i); |
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202 cup[i+n+nclin] = nlc.upper_bound (i); |
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203 } |
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204 |
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205 double *c = &dummy; |
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206 double *cjac = &dummy; |
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207 if (ncnln > 0) |
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208 { |
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209 c = new double [ncnln]; |
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210 cjac = new double [nrowj*n]; |
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211 } |
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212 |
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213 // Objective stuff. |
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214 |
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215 double *objgrd = new double [n]; |
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216 |
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217 // Other stuff. |
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218 |
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219 double *r = new double [n*n]; |
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220 |
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221 lambda.resize (n+nclin+ncnln); |
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222 double *pclambda = lambda.fortran_vec (); |
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223 |
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224 // Decision variable stuff. |
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225 |
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226 double *px = x.fortran_vec (); |
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227 |
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228 // Workspace parameters. |
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229 |
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230 int lenw; |
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231 int leniw = 3 * n + nclin + 2 * ncnln; |
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232 if (nclin == 0 && ncnln == 0) |
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233 lenw = 20*n; |
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234 else if (ncnln == 0) |
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235 lenw = 2*n*(10 + n) + 11*nclin; |
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236 else |
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237 lenw = 2*n*(n + 10) + nclin*(n + 11) + ncnln*(2*n + 21); |
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238 |
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239 int *iw = new int [leniw]; |
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240 double *w = new double [lenw]; |
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241 |
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242 user_phi = phi.objective_function (); |
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243 user_grad = phi.gradient_function (); |
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244 user_g = nlc.function (); |
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245 user_jac = nlc.jacobian_function (); |
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246 |
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247 // Solve the damn thing. |
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248 |
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249 if (user_jac == NULL && user_grad == NULL) |
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250 F77_FCN (npoptn) ("Derivative Level = 0", 20L); |
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251 else if (user_jac == NULL && user_grad != NULL) |
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252 F77_FCN (npoptn) ("Derivative Level = 1", 20L); |
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253 else if (user_jac != NULL && user_grad == NULL) |
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254 F77_FCN (npoptn) ("Derivative Level = 2", 20L); |
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255 else if (user_jac != NULL && user_grad != NULL) |
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256 F77_FCN (npoptn) ("Derivative Level = 3", 20L); |
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257 |
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258 int attempt = 0; |
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259 while (attempt++ < 5) |
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260 { |
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261 |
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262 F77_FCN (npsol) (&n, &nclin, &ncnln, &nrowa, &nrowj, &nrowr, pclin, |
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263 clow, cup, npsol_confun, npsol_objfun, &inform, |
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264 &iter, istate, c, cjac, pclambda, &objf, objgrd, r, |
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265 px, iw, &leniw, w, &lenw); |
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266 |
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267 if (inform == 6 || inform == 1) |
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268 continue; |
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269 else |
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270 break; |
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271 } |
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272 |
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273 // See how it went. |
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274 |
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275 return x; |
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276 } |
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277 |
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278 Vector |
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279 NPSOL::minimize (const Vector& xnew) |
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280 { |
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281 x = xnew; |
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282 return minimize (); |
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283 } |
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284 |
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285 Vector |
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286 NPSOL::minimize (const Vector& xnew, double& objf) |
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287 { |
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288 x = xnew; |
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289 return minimize (objf); |
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290 } |
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291 |
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292 Vector |
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293 NPSOL::minimize (const Vector& xnew, double& objf, int& inform) |
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294 { |
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295 x = xnew; |
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296 return minimize (objf, inform); |
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297 } |
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298 |
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299 Vector |
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300 NPSOL::minimize (const Vector& xnew, double& objf, int& inform, Vector& lambda) |
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301 { |
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302 x = xnew; |
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303 return minimize (objf, inform, lambda); |
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304 } |
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305 |
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306 NPSOL& |
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307 NPSOL::option (char *s) |
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308 { |
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309 long len = strlen (s); |
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310 F77_FCN (npoptn) (s, len); |
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311 return *this; |
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312 } |
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313 |
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314 void |
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315 NPSOL::set_default_options (void) |
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316 { |
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317 F77_FCN (npoptn) ("Nolist", 6L); |
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318 F77_FCN (npoptn) ("Defaults", 8L); |
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319 F77_FCN (npoptn) ("Print Level 0", 13L); |
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320 } |
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321 |
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322 #endif /* NPSOL_MISSING */ |
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323 |
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324 /* |
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325 ;;; Local Variables: *** |
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326 ;;; mode: C++ *** |
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327 ;;; page-delimiter: "^/\\*" *** |
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328 ;;; End: *** |
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329 */ |
