Example usage for org.apache.commons.math3.distribution EnumeratedDistribution EnumeratedDistribution

Introduction

In this page you can find the example usage for org.apache.commons.math3.distribution EnumeratedDistribution EnumeratedDistribution.

Prototype

public EnumeratedDistribution(final RandomGenerator rng, final List<Pair<T, Double>> pmf)
        throws NotPositiveException, MathArithmeticException, NotFiniteNumberException, NotANumberException 

Source Link

Document

Create an enumerated distribution using the given random number generator and probability mass function enumeration.

Usage

From source file:cc.kave.commons.pointsto.evaluation.UsagePruning.java

/**
 * @return The number of pruned usages//w ww  .jav a  2s .  c  o  m
 */
public int prune(final int maxUsages, Map<ProjectIdentifier, List<Usage>> usages) {
    final int initialNumUsages = usages.values().stream().mapToInt(Collection::size).sum();
    int numUsages = initialNumUsages;

    if (numUsages > maxUsages) {
        Random rnd = new Random(rndGenerator.nextLong());
        List<Pair<ProjectIdentifier, Double>> projectUsageCounts = new ArrayList<>(usages.size());
        for (Map.Entry<ProjectIdentifier, List<Usage>> entry : usages.entrySet()) {
            projectUsageCounts.add(Pair.create(entry.getKey(), (double) entry.getValue().size()));
            Collections.shuffle(entry.getValue(), rnd);
        }
        EnumeratedDistribution<ProjectIdentifier> distribution = new EnumeratedDistribution<>(rndGenerator,
                projectUsageCounts);

        while (numUsages > maxUsages) {
            ProjectIdentifier project = distribution.sample();
            List<Usage> projectUsages = usages.get(project);
            if (!projectUsages.isEmpty()) {
                projectUsages.remove(projectUsages.size() - 1);
                --numUsages;
            }
        }
    }

    return initialNumUsages - numUsages;
}

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From source file:cc.kave.commons.pointsto.evaluation.cv.StratifiedProjectsCVFoldBuilder.java

@Override
public List<List<Usage>> createFolds(Map<ProjectIdentifier, List<Usage>> projectUsages) {
    EnumeratedDistribution<ProjectIdentifier> projectDistribution;
    List<Pair<ProjectIdentifier, Double>> projectProbabilities = new ArrayList<>(projectUsages.size());

    // initialize distributions
    long totalUsages = 0;
    for (Map.Entry<ProjectIdentifier, List<Usage>> project : projectUsages.entrySet()) {
        projectProbabilities//w w  w .  j ava 2 s  .  c o  m
                .add(new Pair<ProjectIdentifier, Double>(project.getKey(), (double) project.getValue().size()));
        totalUsages += project.getValue().size();
    }
    // normalization of the probability mass is done by the constructor
    projectDistribution = new EnumeratedDistribution<>(rndGenerator, projectProbabilities);

    shuffleUsages(projectUsages.values());

    List<List<Usage>> folds = new ArrayList<>(numFolds);
    int avgFoldSize = (int) (totalUsages / numFolds);
    for (int f = 0; f < numFolds - 1; ++f) {
        List<Usage> fold = new ArrayList<>(avgFoldSize);
        folds.add(fold);

        for (int i = 0; i < avgFoldSize; ++i) {
            ProjectIdentifier project;
            List<Usage> usages;
            do {
                project = projectDistribution.sample();
                usages = projectUsages.get(project);
            } while (usages.isEmpty());

            int lastIndex = usages.size() - 1;
            Usage usage = usages.remove(lastIndex);
            fold.add(usage);
        }
    }
    // add remaining usages to the last fold
    List<Usage> lastFold = new ArrayList<>(avgFoldSize);
    folds.add(lastFold);
    for (List<Usage> usages : projectUsages.values()) {
        lastFold.addAll(usages);
        usages.clear();
    }
    Collections.shuffle(lastFold, new Random(rndGenerator.nextLong()));

    return folds;
}

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From source file:cc.kave.commons.pointsto.evaluation.cv.StratifiedMethodsCVFoldBuilder.java

private EnumeratedDistribution<ICoReMethodName> buildDistribution(Map<ICoReMethodName, Integer> methods) {
    List<Pair<ICoReMethodName, Double>> methodProbabilities = new ArrayList<>(methods.size());

    for (Map.Entry<ICoReMethodName, Integer> methodEntry : methods.entrySet()) {
        methodProbabilities.add(Pair.create(methodEntry.getKey(), (double) methodEntry.getValue()));
    }//  w w w  .  ja  v  a2s. com

    // probabilities are normalized by the constructor
    return new EnumeratedDistribution<>(rndGenerator, methodProbabilities);
}

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From source file:io.coala.random.impl.RandomDistributionFactoryImpl.java

@Override
public <T> RandomDistribution<T> getEnumerated(final RandomNumberStream rng,
        final List<ProbabilityMass<T, Number>> probabilities) {
    final List<Pair<T, Double>> pmf = new ArrayList<>();
    if (probabilities != null)
        for (ProbabilityMass<T, Number> p : probabilities)
            pmf.add(Pair.create(p.getValue(), p.getMass().doubleValue()));
    final EnumeratedDistribution<T> dist = new EnumeratedDistribution<T>(
            RandomNumberStream.Util.asCommonsRandomGenerator(rng), pmf);
    return new RandomDistribution<T>() {
        @Override//from w  ww.j  a  v  a2 s .com
        public T draw() {
            return dist.sample();
        }
    };
}

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