it.units.malelab.sse.Main.java Source code

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Here is the source code for it.units.malelab.sse.Main.java

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package it.units.malelab.sse;

import com.google.common.collect.ArrayListMultimap;
import com.google.common.collect.Multimap;
import it.units.malelab.sse.language.Operation;
import it.units.malelab.sse.language.VirtualMachine;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.Random;
import org.apache.commons.math3.genetics.BinaryMutation;
import org.apache.commons.math3.genetics.Chromosome;
import org.apache.commons.math3.genetics.ElitisticListPopulation;
import org.apache.commons.math3.genetics.FixedGenerationCount;
import org.apache.commons.math3.genetics.OnePointCrossover;
import org.apache.commons.math3.genetics.Population;
import org.apache.commons.math3.genetics.TournamentSelection;
import org.apache.commons.math3.random.JDKRandomGenerator;

/**
 *
 * @author eric
 */
public class Main {

    public static void main(String[] args) throws IOException {
        Random random = new Random(1);
        VirtualMachine vm = new VirtualMachine(4, 4, 400);
        List<Map<Boolean, List<String>>> datasets = new ArrayList<>();
        datasets.add(Util.loadStrings("/home/eric/Documenti/esperimenti/datasets/Bills-Date.txt", random));
        datasets.add(Util.loadStrings("/home/eric/Documenti/esperimenti/datasets/Log-IP.txt", random));
        datasets.add(Util.loadStrings("/home/eric/Documenti/esperimenti/datasets/Twitter-URL.txt", random));

        Evaluator evaluator = new Evaluator(vm, datasets, 1, 10);

        MyGeneticAlgorithm ga = new MyGeneticAlgorithm(new OnePointCrossover<Integer>(), 0.2, new BinaryMutation(),
                0.6, new TournamentSelection(10), evaluator);
        MyGeneticAlgorithm.setRandomGenerator(new JDKRandomGenerator(1));

        List<Chromosome> chromosomes = new ArrayList<>();
        for (int i = 0; i < 2000; i++) {
            chromosomes.add(new OperationsChromosome(evaluator));
        }
        Population population = new ElitisticListPopulation(chromosomes, chromosomes.size(), 0.99);
        Population finalPopulation = ga.evolve(population, new FixedGenerationCount(10000));
        List<Operation> operations = ((OperationsChromosome) finalPopulation.getFittestChromosome())
                .getOperations();
        for (int i = 0; i < operations.size(); i++) {
            System.out.printf("%4d: %s\n", i, operations.get(i));
        }

    }

}