1 | /* |
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2 | Copyright 20010 by Sean Luke and George Mason University |
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3 | Licensed under the Academic Free License version 3.0 |
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4 | See the file "LICENSE" for more information |
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5 | */ |
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6 | package ec.gp.ge; |
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7 | |
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8 | import ec.*; |
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9 | import ec.gp.*; |
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10 | import ec.gp.koza.*; |
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11 | import ec.simple.*; |
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12 | import ec.coevolve.*; |
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13 | import ec.util.*; |
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14 | |
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15 | /* |
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16 | * GEProblem.java |
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17 | * |
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18 | * Created: Sat Oct 16 23:21:01 EDT 2010 |
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19 | * By: Joseph Zelibor III, Eric Kangas, and Sean Luke |
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20 | */ |
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21 | |
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22 | /** |
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23 | GEProblem is a special replacement for Problem which performs GE mapping. You do not subclass |
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24 | from GEProblem. Rather, create a GPProblem subclass and set it to be the 'problem' parameter of the GEProblem. |
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25 | The GEProblem will convert the GEIndividual into a GPIndividual, then pass this GPIndividual to the GPProblem |
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26 | to be evaluated. |
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27 | |
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28 | <p>The procedure is as follows. Let's say your GPProblem is the Artificial Ant problem. Instead of saying... |
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29 | |
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30 | <p><tt>eval.problem = ec.app.ant.Ant<br> |
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31 | eval.problem = ec.app.ant.Ant<br> |
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32 | eval.problem.data = ec.app.ant.AntData<br> |
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33 | eval.problem.moves = 400<br> |
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34 | eval.problem.file = santafe.trl |
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35 | </tt> |
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36 | |
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37 | <p>... you instead make your problem a GEProblem like this: |
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38 | |
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39 | <p><tt>eval.problem = ec.gp.ge.GEProblem</tt> |
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40 | |
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41 | <p>... and then you hang the Ant problem, and all its subsidiary data, as the 'problem' parameter from the GEProblem like so: |
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42 | |
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43 | <p><tt>eval.problem.problem = ec.app.ant.Ant<br> |
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44 | eval.problem.problem.data = ec.app.ant.AntData<br> |
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45 | eval.problem.problem.moves = 400<br> |
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46 | eval.problem.problem.file = santafe.trl |
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47 | </tt> |
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48 | |
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49 | <p>Everything else should be handled for you. GEProblem is also compatible with the MasterProblem procedure |
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50 | for distributed evaluation, and is also both a SimpleProblemForm and a GroupedProblemForm. We've got you covered. |
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51 | |
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52 | <p><b>Parameters</b><br> |
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53 | <table> |
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54 | <tr><td valign=top><i>base</i>.<tt>problem</tt><br> |
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55 | <font size=-1>classname, inherits from GPProblem</font></td> |
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56 | <td valign=top>(The GPProblem which actually performs the evaluation of the mapped GPIndividual)</td></tr> |
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57 | </table> |
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58 | */ |
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59 | |
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60 | public class GEProblem extends Problem implements SimpleProblemForm, GroupedProblemForm |
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61 | { |
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62 | public final static String P_PROBLEM = "problem"; |
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63 | public GPProblem problem; |
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64 | |
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65 | public void setup(EvolutionState state, Parameter base) |
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66 | { |
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67 | problem = (GPProblem)state.parameters.getInstanceForParameter(base.push(P_PROBLEM), null, GPProblem.class); |
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68 | problem.setup(state, base.push(P_PROBLEM)); |
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69 | } |
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70 | |
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71 | public Object clone() |
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72 | { |
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73 | GEProblem other = (GEProblem)(super.clone()); |
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74 | other.problem = (GPProblem)(problem.clone()); |
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75 | return other; |
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76 | } |
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77 | |
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78 | public void prepareToEvaluate(final EvolutionState state, final int threadnum) |
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79 | { |
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80 | problem.prepareToEvaluate(state, threadnum); |
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81 | } |
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82 | |
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83 | public void finishEvaluating(final EvolutionState state, final int threadnum) |
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84 | { |
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85 | problem.finishEvaluating(state, threadnum); |
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86 | } |
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87 | |
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88 | public void initializeContacts( EvolutionState state ) |
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89 | { |
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90 | problem.initializeContacts(state); |
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91 | } |
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92 | |
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93 | public void reinitializeContacts( EvolutionState state ) |
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94 | { |
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95 | problem.reinitializeContacts(state); |
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96 | } |
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97 | |
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98 | public void closeContacts(EvolutionState state, int result) |
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99 | { |
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100 | problem.closeContacts(state, result); |
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101 | } |
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102 | |
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103 | public boolean canEvaluate() |
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104 | { |
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105 | return problem.canEvaluate(); |
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106 | } |
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107 | |
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108 | public void preprocessPopulation(final EvolutionState state, Population pop, final boolean countVictoriesOnly) |
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109 | { |
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110 | if (!(problem instanceof GroupedProblemForm)) |
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111 | state.output.fatal("GEProblem's underlying Problem is not a GroupedProblemForm"); |
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112 | ((GroupedProblemForm)problem).preprocessPopulation(state, pop, countVictoriesOnly); |
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113 | } |
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114 | |
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115 | public void postprocessPopulation(final EvolutionState state, Population pop, final boolean countVictoriesOnly) |
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116 | { |
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117 | ((GroupedProblemForm)problem).preprocessPopulation(state, pop, countVictoriesOnly); |
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118 | } |
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119 | |
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120 | /** Default version assumes that every individual is a GEIndividual. |
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121 | The underlying problem.evaluate() must be prepared for the possibility that some |
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122 | GPIndividuals handed it are in fact null, meaning that they couldn't be extracted |
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123 | from the GEIndividual string. You should assign them bad fitness in some appropriate way. |
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124 | */ |
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125 | public void evaluate(final EvolutionState state, |
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126 | final Individual[] ind, // the individuals to evaluate together |
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127 | final boolean[] updateFitness, // should this individuals' fitness be updated? |
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128 | final boolean countVictoriesOnly, // don't bother updating Fitness with socres, just victories |
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129 | final int[] subpops, |
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130 | final int threadnum) |
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131 | { |
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132 | // the default version assumes that every subpopulation is a GE Individual |
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133 | GPIndividual[] gpi = new GPIndividual[ind.length]; |
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134 | for(int i = 0; i < gpi.length; i++) |
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135 | { |
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136 | GEIndividual indiv = (GEIndividual) ind[i]; |
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137 | GESpecies species = (GESpecies) (ind[i].species); |
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138 | |
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139 | // warning: gpi[i] may be null |
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140 | gpi[i] = species.map(state, indiv, threadnum); |
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141 | } |
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142 | |
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143 | ((GroupedProblemForm)problem).evaluate(state, gpi, updateFitness, countVictoriesOnly, subpops, threadnum); |
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144 | |
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145 | for(int i = 0; i < gpi.length; i++) |
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146 | { |
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147 | // Now we need to move the evaluated flag from the GPIndividual |
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148 | // to the GEIndividual, and also for good measure, let's copy over |
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149 | // the GPIndividual's fitness because even though the mapping function |
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150 | // set the two Individuals to share the same fitness, it's possible |
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151 | // that the evaluation function may have replaced the fitness. |
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152 | ind[i].fitness = gpi[i].fitness; |
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153 | ind[i].evaluated = gpi[i].evaluated; |
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154 | } |
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155 | } |
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156 | |
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157 | public void evaluate(final EvolutionState state, |
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158 | final Individual ind, |
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159 | final int subpopulation, |
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160 | final int threadnum) |
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161 | { |
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162 | if (!(problem instanceof SimpleProblemForm)) |
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163 | state.output.fatal("GEProblem's underlying Problem is not a SimpleProblemForm"); |
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164 | |
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165 | GEIndividual indiv = (GEIndividual) ind; |
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166 | GESpecies species = (GESpecies) (ind.species); |
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167 | GPIndividual gpi = species.map(state, indiv, threadnum); |
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168 | if (gpi == null) |
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169 | { |
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170 | KozaFitness fitness = (KozaFitness) (ind.fitness); |
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171 | fitness.setStandardizedFitness(state, Float.MAX_VALUE); |
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172 | } |
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173 | else |
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174 | { |
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175 | ((SimpleProblemForm)problem).evaluate(state, gpi, subpopulation, threadnum); |
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176 | // Now we need to move the evaluated flag from the GPIndividual |
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177 | // to the GEIndividual, and also for good measure, let's copy over |
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178 | // the GPIndividual's fitness because even though the mapping function |
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179 | // set the two Individuals to share the same fitness, it's possible |
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180 | // that the evaluation function may have replaced the fitness. |
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181 | ind.fitness = gpi.fitness; |
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182 | ind.evaluated = gpi.evaluated; |
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183 | } |
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184 | } |
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185 | |
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186 | public void describe(final EvolutionState state, |
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187 | final Individual ind, |
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188 | final int subpopulation, |
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189 | final int threadnum, |
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190 | final int log) |
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191 | { |
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192 | GEIndividual indiv = (GEIndividual) ind; |
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193 | GESpecies species = (GESpecies) (ind.species); |
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194 | GPIndividual gpi = species.map(state, indiv, threadnum); |
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195 | if (gpi != null) |
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196 | { |
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197 | problem.describe(state, gpi, subpopulation, threadnum, log); |
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198 | |
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199 | // though this is probably not necessary for describe(...), |
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200 | // for good measure we're doing the same rigamarole that we |
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201 | // did for evaluate(...) above. |
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202 | ind.fitness = gpi.fitness; |
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203 | ind.evaluated = gpi.evaluated; |
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204 | } |
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205 | } |
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206 | } |
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