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Example 41 with Chromosome

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);
}
Also used : ZDT4(org.evosuite.ga.problems.multiobjective.ZDT4) Chromosome(org.evosuite.ga.Chromosome) TestSuiteChromosome(org.evosuite.testsuite.TestSuiteChromosome) FitnessFunction(org.evosuite.ga.FitnessFunction) Spacing(org.evosuite.ga.problems.metrics.Spacing) GenerationalDistance(org.evosuite.ga.problems.metrics.GenerationalDistance) BinaryTournamentSelectionCrowdedComparison(org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison) Problem(org.evosuite.ga.problems.Problem) ArrayList(java.util.ArrayList) List(java.util.List) SBXCrossover(org.evosuite.ga.operators.crossover.SBXCrossover) Test(org.junit.Test)

Example 42 with Chromosome

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);
}
Also used : Chromosome(org.evosuite.ga.Chromosome) NSGAChromosome(org.evosuite.ga.NSGAChromosome) FitnessFunction(org.evosuite.ga.FitnessFunction) Spacing(org.evosuite.ga.problems.metrics.Spacing) RandomFactory(org.evosuite.ga.metaheuristics.RandomFactory) NSGAII(org.evosuite.ga.metaheuristics.NSGAII) GenerationalDistance(org.evosuite.ga.problems.metrics.GenerationalDistance) BinaryTournamentSelectionCrowdedComparison(org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison) Problem(org.evosuite.ga.problems.Problem) List(java.util.List) SBXCrossover(org.evosuite.ga.operators.crossover.SBXCrossover) Test(org.junit.Test)

Example 43 with Chromosome

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));
    }
}
Also used : NSGAChromosome(org.evosuite.ga.NSGAChromosome) Chromosome(org.evosuite.ga.Chromosome) NSGAChromosome(org.evosuite.ga.NSGAChromosome) FitnessFunction(org.evosuite.ga.FitnessFunction) RandomFactory(org.evosuite.ga.metaheuristics.RandomFactory) NSGAII(org.evosuite.ga.metaheuristics.NSGAII) BinaryTournamentSelectionCrowdedComparison(org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison) Problem(org.evosuite.ga.problems.Problem) List(java.util.List) DoubleVariable(org.evosuite.ga.variables.DoubleVariable) SBXCrossover(org.evosuite.ga.operators.crossover.SBXCrossover) Test(org.junit.Test)

Example 44 with Chromosome

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++;
}
Also used : TestChromosome(org.evosuite.testcase.TestChromosome) Chromosome(org.evosuite.ga.Chromosome)

Example 45 with Chromosome

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);
    }
}
Also used : Chromosome(org.evosuite.ga.Chromosome) TestChromosome(org.evosuite.testcase.TestChromosome)

Aggregations

Chromosome (org.evosuite.ga.Chromosome)60 Test (org.junit.Test)41 TestSuiteChromosome (org.evosuite.testsuite.TestSuiteChromosome)32 ArrayList (java.util.ArrayList)29 Neighbourhood (org.evosuite.ga.Neighbourhood)20 FitnessFunction (org.evosuite.ga.FitnessFunction)15 List (java.util.List)13 SBXCrossover (org.evosuite.ga.operators.crossover.SBXCrossover)13 BinaryTournamentSelectionCrowdedComparison (org.evosuite.ga.operators.selection.BinaryTournamentSelectionCrowdedComparison)13 Problem (org.evosuite.ga.problems.Problem)13 NSGAChromosome (org.evosuite.ga.NSGAChromosome)12 NSGAII (org.evosuite.ga.metaheuristics.NSGAII)12 RandomFactory (org.evosuite.ga.metaheuristics.RandomFactory)12 GenerationalDistance (org.evosuite.ga.problems.metrics.GenerationalDistance)9 Spacing (org.evosuite.ga.problems.metrics.Spacing)9 TestChromosome (org.evosuite.testcase.TestChromosome)6 BranchCoverageSuiteFitness (org.evosuite.coverage.branch.BranchCoverageSuiteFitness)5 LineCoverageSuiteFitness (org.evosuite.coverage.line.LineCoverageSuiteFitness)5 DoubleVariable (org.evosuite.ga.variables.DoubleVariable)4 EvoSuite (org.evosuite.EvoSuite)3