Examples with StatSummary utilities.StatSummary used on opensource projects

Example 76 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class EvoSGATest method main.

public static void main(String[] args) {
    EvoAlg evoAlg = new CompactSlidingGA();
    evoAlg = new NTupleBanditEA();
    // evoAlg = new SlidingMeanEDA();
    evoAlg = new GridSearch();
    StatSummary ss = new StatSummary("Overall results: " + evoAlg.getClass().getSimpleName());
    int nTrials = 1;
    for (int i = 0; i < nTrials; i++) {
        ss.add(runTrial(evoAlg));
    }
    System.out.println(ss);
}

Example 77 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class GridSearch method runTrial.

@Override
public int[] runTrial(SolutionEvaluator evaluator, int nEvals) {
    searchSpace = evaluator.searchSpace();
    logger = new EvolutionLogger();
    double searchSpaceSize = SearchSpaceUtil.size(searchSpace);
    double samplesPerPoint = nEvals / searchSpaceSize;
    System.out.println("Search space size = " + searchSpaceSize);
    System.out.println("Evaluation budget = " + nEvals);
    System.out.format("Samples per point  = %.2f\n", samplesPerPoint);
    if (samplesPerPoint < 1)
        throw new RuntimeException("Cannot run GridSearch with less than 1 sample per point");
    // otherwise we're ok to proceed ...
    // the idea is that we'll search each point for as much as we have budget
    // but do this in a breadth-first way
    // and we'll record each one in a StatSummary object - so need an array of these
    StatSummary[] results = new StatSummary[(int) searchSpaceSize];
    for (int i = 0; i < results.length; i++) {
        results[i] = new StatSummary();
    }
    for (int i = 0; i < nEvals; i++) {
        // each time pick the next point in the search space
        // evaluate it, and add it to the stats
        int index = i % (int) searchSpaceSize;
        int[] solution = SearchSpaceUtil.nthPoint(searchSpace, index);
        double fitness = evaluator.evaluate(solution);
        results[index].add(fitness);
    }
    // 
    // iterate over the points to find the best one
    Picker<Integer> picker = new Picker<>(Picker.MAX_FIRST);
    for (int i = 0; i < results.length; i++) {
        picker.add(results[i].mean(), i);
    }
    int best = picker.getBest();
    System.out.println("Best index = " + best);
    System.out.println("Best stats: " + results[best]);
    int[] solution = SearchSpaceUtil.nthPoint(searchSpace, best);
    System.out.println("Best solution: " + Arrays.toString(solution));
    return solution;
}

Example 78 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class OneMaxTestResampled method countOnesNoisy.

public StatSummary countOnesNoisy(int[] x, int nResamples) {
    StatSummary ss = new StatSummary();
    int nOnes = countOnes(x);
    for (int i = 0; i < nResamples; i++) {
        ss.add(nOnes + random.nextGaussian() * noiseStdDev);
    }
    return ss;
}

Example 79 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class OneMaxTestResampled method run.

public Integer run(int nEvals) {
    int i = 0;
    while (i < nEvals) {
        // randomly mutate the best yet
        int[] mut = randMut(bestYet);
        // if it's better then adopt the mutation as the new best
        // add in the noise to the decision
        StatSummary ssMut = countOnesNoisy(mut, nActualSamples);
        StatSummary ssBestYet = countOnesNoisy(bestYet, nActualSamples);
        i += ssMut.n() + ssBestYet.n();
        if (ssMut.mean() >= ssBestYet.mean()) {
            bestYet = mut;
        }
        // this does a noise-free check
        if (countOnes(bestYet) == bestYet.length) {
            // both the bestYet and the mutated copy each time
            return i;
        }
    }
    // failed to find a solution
    return null;
}

Example 80 with StatSummary

use of utilities.StatSummary in project SimpleAsteroids by ljialin.

the class RMHCMazeTest method main.

public static void main(String[] args) {
    int dim = 225;
    int nReps = 30;
    StatSummary ss = new StatSummary();
    ElapsedTimer t = new ElapsedTimer();
    for (int i = 0; i < nReps; i++) {
        double score = runTest(dim);
        System.out.println(i + "\t " + score);
        ss.add(score);
    }
    // BarChart.display(means, "OneMax Scaling");
    System.out.println(t);
    System.out.println(ss);
}