Example usage for org.apache.commons.math3.distribution RealDistribution sample

Introduction

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

Prototype

double sample();

Source Link

Document

Generate a random value sampled from this distribution.

Usage

From source file:io.coala.math3.Math3ProbabilityDistribution.java

@SafeVarargs
public static <S> Math3ProbabilityDistribution<Double> of(final RealDistribution dist, // final PseudoRandom stream,
        final S... args) {
    Objects.requireNonNull(dist);
    final Math3ProbabilityDistribution<Double> result = new Math3ProbabilityDistribution<Double>() {
        @Override/*from ww  w . j  a  v a 2s  .co  m*/
        public Double draw() {
            return Double.valueOf(dist.sample());
        }
    };
    //      result.stream = stream;
    return result;
}

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From source file:com.vsthost.rnd.jdeoptim.utils.Utils.java

/**
 * Creates a random population./*from w w  w . j a v  a 2  s.  co  m*/
 *
 * @param size The size of the population to be created.
 * @param dimension The dimension of the candidate (length of each candidate) to be created.
 * @param lower The lower boundary.
 * @param upper The upper boundary.
 * @param distribution The distribution to be sampled from.
 * @return A random population.
 */
public static double[][] randomPopulation(int size, int dimension, double[] lower, double[] upper,
        RealDistribution distribution) {
    // Create the population matrix:
    final double[][] population = new double[size][dimension];

    // Iterate over population and populate each candidate:
    for (int c = 0; c < size; c++) {
        // Iterate over dimensions and populate candidate elements:
        for (int d = 0; d < dimension; d++) {
            // Get the minimum possible value:
            final double min = lower[d];

            // Get the maximum possible value:
            final double max = upper[d];

            // Create a random value within the range:
            // TODO: For better performance, memoize (max - min).
            population[c][d] = min + ((max - min) * distribution.sample());
        }
    }

    // Done, return the population:
    return population;
}

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From source file:cz.cuni.mff.d3s.spl.interpretation.DistributionLearningInterpretation.java

private void showDistribution(RealDistribution distr) {
    assert debug != null;
    for (int i = 0; i < 10; i++) {
        debug.printf("  %.3f", distr.sample());
    }/*from w  ww  . j av  a  2s. c  om*/
    debug.println();
}

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From source file:cz.cuni.mff.spl.evaluator.statistics.KolmogorovSmirnovTestFlag.java

/**
 * Adds random jitter to {@code data} using deviates sampled from {@code dist}.
 * <p>//from   w  w w  .  j  a v a  2 s . co m
 * Note that jitter is applied in-place - i.e., the array
 * values are overwritten with the result of applying jitter.</p>
 *
 * @param data input/output data array - entries overwritten by the method
 * @param dist probability distribution to sample for jitter values
 * @throws NullPointerException if either of the parameters is null
 */
private static void jitter(double[] data, RealDistribution dist) {
    for (int i = 0; i < data.length; i++) {
        data[i] += dist.sample();
    }
}

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From source file:mtsar.processors.answer.KOSAggregator.java

private Map<Integer, Double> converge(Table<Integer, Integer, Short> graph, int kMax) {
    final RealDistribution distribution = new NormalDistribution(1, 1);

    Table<Integer, Integer, Double> ys = HashBasedTable.create(graph.rowKeySet().size(),
            graph.columnKeySet().size());

    for (final Table.Cell<Integer, Integer, Short> cell : graph.cellSet()) {
        ys.put(cell.getRowKey(), cell.getColumnKey(), distribution.sample());
    }/*from   w ww.j  av  a2  s .c o  m*/

    for (int k = 1; k <= kMax; k++) {
        final Table<Integer, Integer, Double> xs = tasksUpdate(graph, ys);
        if (k < kMax)
            ys = workersUpdate(graph, xs);
    }

    final Map<Integer, Double> estimations = new HashMap<>();

    for (final Integer taskId : graph.rowKeySet()) {
        double sumProduct = 0.0;

        final Map<Integer, Double> workers = ys.row(taskId);
        for (final Map.Entry<Integer, Double> worker : workers.entrySet()) {
            sumProduct += graph.get(taskId, worker.getKey()) * worker.getValue();
        }

        estimations.put(taskId, sumProduct);
    }

    return estimations;
}

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

@Override
public RandomNumberDistribution<Double> getExponential(final RandomNumberStream rng, final Number mean) {
    final RealDistribution dist = new ExponentialDistribution(
            RandomNumberStream.Util.asCommonsRandomGenerator(rng), mean.doubleValue());
    return new RandomNumberDistribution<Double>() {
        @Override//from   w  w  w. ja v  a  2s.  c om
        public Double draw() {
            return dist.sample();
        }
    };
}

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

@Override
public RandomNumberDistribution<Double> getT(final RandomNumberStream rng, final Number degreesOfFreedom) {
    final RealDistribution dist = new TDistribution(RandomNumberStream.Util.asCommonsRandomGenerator(rng),
            degreesOfFreedom.doubleValue());
    return new RandomNumberDistribution<Double>() {
        @Override/* ww w .  j  av  a2 s.  co m*/
        public Double draw() {
            return dist.sample();
        }
    };
}

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

@Override
public RandomNumberDistribution<Double> getLevy(final RandomNumberStream rng, final Number mu, final Number c) {
    final RealDistribution dist = new LevyDistribution(RandomNumberStream.Util.asCommonsRandomGenerator(rng),
            mu.doubleValue(), c.doubleValue());
    return new RandomNumberDistribution<Double>() {
        @Override/*from  w  w w  .jav a 2 s . c o m*/
        public Double draw() {
            return dist.sample();
        }
    };
}

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

@Override
public RandomNumberDistribution<Double> getChiSquared(final RandomNumberStream rng,
        final Number degreesOfFreedom) {
    final RealDistribution dist = new ChiSquaredDistribution(
            RandomNumberStream.Util.asCommonsRandomGenerator(rng), degreesOfFreedom.doubleValue());
    return new RandomNumberDistribution<Double>() {
        @Override/*ww w . j a v  a 2  s .  c  om*/
        public Double draw() {
            return dist.sample();
        }
    };
}

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

@Override
public RandomNumberDistribution<Double> getNormal(final RandomNumberStream rng, final Number mean,
        final Number sd) {
    final RealDistribution dist = new NormalDistribution(RandomNumberStream.Util.asCommonsRandomGenerator(rng),
            mean.doubleValue(), sd.doubleValue());
    return new RandomNumberDistribution<Double>() {
        @Override/*from  w  ww . j  ava 2 s  . co m*/
        public Double draw() {
            return dist.sample();
        }
    };
}

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