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annotate trunk/ga_code.d @ 2:9655c8362b25

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Added the Perceptron class and the perceptron_test testing program.
author revcompgeek
date Sat, 05 Apr 2008 23:41:30 -0600
parents 4b2e8e8a633e
children
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9655c8362b25 Added the Perceptron class and the perceptron_test testing program.
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1 /++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
9655c8362b25 Added the Perceptron class and the perceptron_test testing program.
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2 + Genetic Algorithm Code Test +
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3 + Author: Matt P. +
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4 + Version: 0.5 +
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5 + +
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6 + Runs a genetic algorithm test using a simple code +
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7 + guessing algorithm. +
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8 + +
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9 + Usage: ga_code [options] +
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10 + Options: +
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11 + -h +
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12 + Prints this information. +
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13 + -v +
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14 + Turns on verbose output. +
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15 + -m float +
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16 + Specifies the mutation rate for each generation. +
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17 + Default: 0.05 +
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18 + +
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19 + -d float +
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20 + Specifies the survival rate for each generation. +
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21 + Default: 0.5 +
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22 + +
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23 + -p integer +
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24 + Specifies the population for each generation. +
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25 + Default: 1000 +
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26 + +
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27 + -l integer +
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28 + Specifies how long the code to be guessed is. +
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29 + Default: 20 +
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30 + +
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31 + -n integer +
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32 + Specifies how many possibilities there are for +
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33 + each character of the code string. +
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34 + Default: 20 +
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35 + +
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36 + -r integer +
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37 + Specifies the number of times to repeat the test. +
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38 + Default: 20 +
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39 + +
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40 + -c char +
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41 + Specifies the crossover type +
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42 + s / 1 - One point crossover +
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43 + t / 2 - Two point crossover +
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44 + u / 3 - Uniform crossover +
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45 + Default: s +
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46 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++/
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47
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48
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49 module ga_code;
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50
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51 import aid.ga;
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52 import tango.math.Random;
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53 import tango.math.Math;
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54 import tango.io.Stdout;
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55 //import tango.text.String;
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56 import Float = tango.text.convert.Float;
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57 import Integer = tango.text.convert.Integer;
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58
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59 import bcd.sys.times;
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60
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61 char[] target;
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62
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63 int numChars = 20;
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64 int stringLen = 20;
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65
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66 double average(double[] array){
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67 double avg = 0;
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68 foreach (double v; array)
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69 avg += v;
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70 avg /= array.length;
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71 return avg;
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72 }
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73
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74 double stdDev(double[] array){
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75 double avg = average(array);
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76 double stddev = 0;
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77 foreach (double v; array){
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78 stddev += (v - avg) * (v - avg);
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79 }
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80 stddev = sqrt(stddev/array.length);
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81 return stddev;
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82 }
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83
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84 class Foo {
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85 public double calculateFitness(char[] gene){
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86 double fitness=0;
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87 for (uint i = 0; i < stringLen; i++){
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88 if (gene[i] == target[i])
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89 fitness += 1;
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90 }
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91 return fitness;
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92 }
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93
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94 public char[] getRandomGenotype(){
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95 char[] t;
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96 t.length = stringLen;
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97 for (int i = 0; i < stringLen; i++){
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98 t[i] = Random.shared.next(numChars) + 'a';
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99 }
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100 return t;
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101 }
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102
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103 public char getRandomChar(uint index){
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104 return cast(char)(Random.shared.next(numChars)+'a');
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105 }
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106 }
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107
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108 void usage(){
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109 auto s =
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110 "Usage: ga_test [options] \n"
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111 "Options: \n"
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112 "-h \n"
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113 " Prints this information. \n"
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114 "-v \n"
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115 " Turns on verbose output. \n"
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116 "-m float \n"
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117 " Specifies the mutation rate for each generation. \n"
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118 " Default: 0.05 \n"
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119 " \n"
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120 "-d float \n"
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121 " Specifies the survival rate for each generation. \n"
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122 " Default: 0.5 \n"
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123 " \n"
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124 "-p integer \n"
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125 " Specifies the population for each generation. \n"
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126 " Default: 1000 \n"
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127 " \n"
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128 "-l integer \n"
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129 " Specifies how long the code to be guessed is. \n"
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130 " Default: 20 \n"
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131 " \n"
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132 "-n integer \n"
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133 " Specifies how many possibilities there are for \n"
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134 " each character of the code string. \n"
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135 " Default: 20 \n"
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136 " \n"
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137 "-r integer \n"
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138 " Specifies the number of times to repeat the test.\n"
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139 " Default: 20 \n"
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140 " \n"
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141 "-c char \n"
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142 " Specifies the crossover type \n"
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143 " s / 1 - One point crossover \n"
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144 " t / 2 - Two point crossover \n"
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145 " u / 3 - Uniform crossover \n"
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146 " Default: s ";
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147 Stdout(s).newline;
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148 }
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149
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150 void main(char[][] args){
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151 Foo f = new Foo();
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152 GeneticAlgorithm ga = new GeneticAlgorithm();
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153 ga.calculateFitness = &f.calculateFitness;
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154 ga.getRandomGenotype = &f.getRandomGenotype;
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155 ga.getRandomChar = &f.getRandomChar;
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156 ga.fitnessThreshold = stringLen;
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157 int rep = 20;
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158 bool dotime=true;
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159
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160
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161 for (auto i = 1; i < args.length; i++){
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162 char[] arg = args[i];
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163 switch (arg){
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164 case "-h":
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165 usage();
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166 return;
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167 case "-m":
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168 ga.mutationRate = Float.parse(args[++i]);
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169 break;
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170 case "-d":
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171 ga.survivalRate = Float.parse(args[++i]);
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172 break;
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173 case "-p":
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174 ga.startPopulation = Integer.parse(args[++i]);
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175 break;
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176 case "-l":
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177 stringLen = Integer.parse(args[++i]);
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178 ga.fitnessThreshold = stringLen;
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179 break;
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180 case "-n":
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181 numChars = Integer.parse(args[++i]);
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182 break;
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183 case "-r":
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184 rep = Integer.parse(args[++i]);
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185 break;
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186 case "-v":
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187 ga.verbose = true;
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188 break;
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189 case "-c":
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190 auto t = args[++i];
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191 switch (t){
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192 case "s","1":
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193 ga.crossoverType = 1;
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194 break;
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195 case "t","2":
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196 ga.crossoverType = 2;
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197 break;
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198 default:
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199 ga.crossoverType = 3;
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200 }
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201 break;
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202 case "-b":
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203 ga.bailout = Integer.parse(args[++i]);
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204 break;
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205 case "-t":
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206 dotime = false;
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207 break;
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208 default:
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209 Stdout.format("Unknown parameter: {}",arg).newline;
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210 usage();
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211 return;
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212 }
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213 }
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214 target = ga.getRandomGenotype();
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215
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216 double[] time;
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217 double[] gens;
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218 long start,end;
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219
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220 for(auto i = 0; i < rep; i++){
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221 if(dotime) start = iutime();
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222 uint generations = ga.run();
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223 if(dotime) end = iutime() - start;
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224
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225 if(dotime) time ~= end;
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226 gens ~= generations;
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227 }
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228
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229 if(dotime) Stdout.format("{0}, {1:.5}, {2}, {3:.5}", average(gens),stdDev(gens),average(time),stdDev(time)).newline;
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230 else Stdout.format("{0}, {1:.5}", average(gens),stdDev(gens)).newline; //", {2}, {3:.5}" ,average(time),stdDev(time)
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231 }