use of org.evosuite.ga.Chromosome in project evosuite by EvoSuite.
the class SPEA2Test method testZDT4.
@SuppressWarnings({ "rawtypes", "unchecked" })
@Test
public void testZDT4() throws IOException {
Properties.MUTATION_RATE = 1d / 10d;
Properties.POPULATION = 100;
Properties.SEARCH_BUDGET = 250;
Properties.STOPPING_CONDITION = StoppingCondition.MAXGENERATIONS;
Properties.CROSSOVER_RATE = 0.9;
Properties.RANDOM_SEED = 1l;
ChromosomeFactory<?> factory = new RandomFactory(true, 10, -5.0, 5.0);
GeneticAlgorithm<?> ga = new SPEA2(factory);
BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
ts.setMaximize(false);
ga.setSelectionFunction(ts);
ga.setCrossOverFunction(new SBXCrossover());
Problem p = new ZDT4();
final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
final FitnessFunction f2 = (FitnessFunction) p.getFitnessFunctions().get(1);
ga.addFitnessFunction(f1);
ga.addFitnessFunction(f2);
// execute
ga.generateSolution();
List<Chromosome> chromosomes = (List<Chromosome>) ga.getPopulation();
Collections.sort(chromosomes, new Comparator<Chromosome>() {
@Override
public int compare(Chromosome arg0, Chromosome arg1) {
return Double.compare(arg0.getFitness(f1), arg1.getFitness(f1));
}
});
double[][] front = new double[Properties.POPULATION][2];
for (int i = 0; i < chromosomes.size(); i++) {
Chromosome chromosome = chromosomes.get(i);
System.out.printf("%f,%f\n", chromosome.getFitness(f1), chromosome.getFitness(f2));
front[i][0] = Double.valueOf(chromosome.getFitness(f1));
front[i][1] = Double.valueOf(chromosome.getFitness(f2));
}
// load True Pareto Front
double[][] trueParetoFront = Metrics.readFront("ZDT4.pf");
GenerationalDistance gd = new GenerationalDistance();
double gdd = gd.evaluate(front, trueParetoFront);
System.out.println("GenerationalDistance: " + gdd);
assertEquals(0.00, gdd, 0.01);
Spacing sp = new Spacing();
double spd = sp.evaluate(front);
System.out.println("SpacingFront: " + spd);
assertEquals(0.71, spd, 0.01);
}
use of org.evosuite.ga.Chromosome in project evosuite by EvoSuite.
the class SCH2IntTest method testSCH2.
/**
* Testing NSGA-II with SCH2 Problem
*
* @throws IOException
* @throws NumberFormatException
*/
@Test
public void testSCH2() throws NumberFormatException, IOException {
Properties.MUTATION_RATE = 1d / 1d;
ChromosomeFactory<?> factory = new RandomFactory(false, 1, -5.0, 10.0);
GeneticAlgorithm<?> ga = new NSGAII(factory);
BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
ts.setMaximize(false);
ga.setSelectionFunction(ts);
ga.setCrossOverFunction(new SBXCrossover());
Problem p = new SCH2();
final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
final FitnessFunction f2 = (FitnessFunction) p.getFitnessFunctions().get(1);
ga.addFitnessFunction(f1);
ga.addFitnessFunction(f2);
// execute
ga.generateSolution();
List<Chromosome> chromosomes = (List<Chromosome>) ga.getPopulation();
Collections.sort(chromosomes, new Comparator<Chromosome>() {
@Override
public int compare(Chromosome arg0, Chromosome arg1) {
return Double.compare(arg0.getFitness(f1), arg1.getFitness(f1));
}
});
double[][] front = new double[Properties.POPULATION][2];
int index = 0;
for (Chromosome chromosome : chromosomes) {
System.out.printf("%f,%f\n", chromosome.getFitness(f1), chromosome.getFitness(f2));
front[index][0] = Double.valueOf(chromosome.getFitness(f1));
front[index][1] = Double.valueOf(chromosome.getFitness(f2));
index++;
}
// load True Pareto Front
double[][] trueParetoFront = Metrics.readFront("Schaffer2.pf");
GenerationalDistance gd = new GenerationalDistance();
double gdd = gd.evaluate(front, trueParetoFront);
System.out.println("GenerationalDistance: " + gdd);
Assert.assertEquals(gdd, 0.0004, 0.0001);
Spacing sp = new Spacing();
double spd = sp.evaluate(front);
double spdt = sp.evaluate(trueParetoFront);
System.out.println("SpacingFront (" + spd + ") - SpacingTrueFront (" + spdt + ") = " + Math.abs(spd - spdt));
Assert.assertEquals(Math.abs(spd - spdt), 0.05, 0.05);
}
use of org.evosuite.ga.Chromosome in project evosuite by EvoSuite.
the class TestThreeHump method testThreeHump.
/**
* Testing NSGA-II with ThreeHump Problem
*
* @throws IOException
* @throws NumberFormatException
*/
@Test
public void testThreeHump() throws NumberFormatException, IOException {
Properties.MUTATION_RATE = 1d / 2d;
ChromosomeFactory<?> factory = new RandomFactory(false, 2, -5.0, 5.0);
// GeneticAlgorithm<?> ga = new NSGAII(factory);
GeneticAlgorithm<?> ga = new NSGAII(factory);
BinaryTournamentSelectionCrowdedComparison ts = new BinaryTournamentSelectionCrowdedComparison();
// BinaryTournament ts = new BinaryTournament();
ga.setSelectionFunction(ts);
ga.setCrossOverFunction(new SBXCrossover());
Problem p = new ThreeHump();
final FitnessFunction f1 = (FitnessFunction) p.getFitnessFunctions().get(0);
ga.addFitnessFunction(f1);
// execute
ga.generateSolution();
List<Chromosome> chromosomes = (List<Chromosome>) ga.getPopulation();
Collections.sort(chromosomes, new Comparator<Chromosome>() {
@Override
public int compare(Chromosome arg0, Chromosome arg1) {
return Double.compare(arg0.getFitness(f1), arg1.getFitness(f1));
}
});
for (Chromosome chromosome : chromosomes) Assert.assertEquals(chromosome.getFitness(f1), 0.000, 0.001);
for (Chromosome chromosome : chromosomes) {
NSGAChromosome nsga_c = (NSGAChromosome) chromosome;
DoubleVariable x = (DoubleVariable) nsga_c.getVariables().get(0);
DoubleVariable y = (DoubleVariable) nsga_c.getVariables().get(1);
System.out.printf("%f,%f : %f\n", x.getValue(), y.getValue(), chromosome.getFitness(f1));
}
}
use of org.evosuite.ga.Chromosome in project evosuite by EvoSuite.
the class ReportGenerator method iteration.
/**
* {@inheritDoc}
*/
@Override
public void iteration(GeneticAlgorithm<?> algorithm) {
StatisticEntry entry = statistics.get(statistics.size() - 1);
Chromosome best = algorithm.getBestIndividual();
entry.fitness_history.add(best.getFitness());
entry.size_history.add(best.size());
double average = 0.0;
for (Chromosome individual : algorithm.getPopulation()) {
average += individual.size();
}
entry.average_length_history.add(average / algorithm.getPopulation().size());
// TODO: Need to get data of average size in here - how? Pass population
// as parameter?
entry.age++;
}
use of org.evosuite.ga.Chromosome in project evosuite by EvoSuite.
the class SearchStatistics method iteration.
/**
* {@inheritDoc}
*/
@Override
public void iteration(GeneticAlgorithm<?> algorithm) {
super.iteration(algorithm);
StatisticEntry entry = statistics.get(statistics.size() - 1);
Chromosome best = algorithm.getBestIndividual();
if (best instanceof TestSuiteChromosome) {
entry.length_history.add(((TestSuiteChromosome) best).totalLengthOfTestCases());
entry.coverage_history.add(((TestSuiteChromosome) best).getCoverage());
entry.tests_executed.add(MaxTestsStoppingCondition.getNumExecutedTests());
entry.statements_executed.add(MaxStatementsStoppingCondition.getNumExecutedStatements());
entry.fitness_evaluations.add(MaxFitnessEvaluationsStoppingCondition.getNumFitnessEvaluations());
entry.timeStamps.add(System.currentTimeMillis() - entry.creationTime);
}
}
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