Example usage for org.apache.commons.rng.sampling.distribution GaussianSampler GaussianSampler

Introduction

In this page you can find the example usage for org.apache.commons.rng.sampling.distribution GaussianSampler GaussianSampler.

Prototype

public GaussianSampler(NormalizedGaussianSampler normalized, double mean, double standardDeviation) 

Source Link

Usage

From source file:org.apache.commons.rng.examples.jpms.lib.DiceGame.java

/**
 * @param players Number of players./*from   ww  w . j a v  a2  s  . co  m*/
 * @param rounds Number of rounds.
 * @param mu Mean.
 * @param sigma Standard deviation.
 * @param rng RNG.
 */
public DiceGame(int players, int rounds, UniformRandomProvider rng, double mu, double sigma) {
    this.rng = rng;
    this.rounds = rounds;
    this.players = players;
    sampler = new GaussianSampler(new ZigguratNormalizedGaussianSampler(rng), mu, sigma);
}

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From source file:org.apache.commons.rng.examples.sampling.ProbabilityDensityApproximation.java

/**
 * Program entry point./*from w w  w  .  jav  a2 s  .c om*/
 *
 * @param args Argument. They must be provided, in the following order:
 * <ol>
 *  <li>Number of "equal-width" bins.</li>
 *  <li>Number of samples.</li>
 * </ol>
 * @throws IOException if failure occurred while writing to files.
 */
public static void main(String[] args) throws IOException {
    final int numBins = Integer.valueOf(args[0]);
    final long numSamples = Long.valueOf(args[1]);
    final ProbabilityDensityApproximation app = new ProbabilityDensityApproximation(numBins, numSamples);

    final UniformRandomProvider rng = RandomSource.create(RandomSource.XOR_SHIFT_1024_S);

    final double gaussMean = 1;
    final double gaussSigma = 2;
    final double gaussMin = -9;
    final double gaussMax = 11;
    app.createDensity(new GaussianSampler(new ZigguratNormalizedGaussianSampler(rng), gaussMean, gaussSigma),
            gaussMin, gaussMax, "gauss.ziggurat.txt");
    app.createDensity(new GaussianSampler(new MarsagliaNormalizedGaussianSampler(rng), gaussMean, gaussSigma),
            gaussMin, gaussMax, "gauss.marsaglia.txt");
    app.createDensity(new GaussianSampler(new BoxMullerNormalizedGaussianSampler(rng), gaussMean, gaussSigma),
            gaussMin, gaussMax, "gauss.boxmuller.txt");

    final double alphaBeta = 4.3;
    final double betaBeta = 2.1;
    final double betaMin = 0;
    final double betaMax = 1;
    app.createDensity(new ChengBetaSampler(rng, alphaBeta, betaBeta), betaMin, betaMax, "beta.case1.txt");
    final double alphaBetaAlt = 0.5678;
    final double betaBetaAlt = 0.1234;
    app.createDensity(new ChengBetaSampler(rng, alphaBetaAlt, betaBetaAlt), betaMin, betaMax, "beta.case2.txt");

    final double meanExp = 3.45;
    final double expMin = 0;
    final double expMax = 60;
    app.createDensity(new AhrensDieterExponentialSampler(rng, meanExp), expMin, expMax, "exp.txt");

    final double thetaGammaSmallerThanOne = 0.1234;
    final double alphaGamma = 3.456;
    final double gammaMin = 0;
    final double gammaMax1 = 40;
    app.createDensity(new AhrensDieterMarsagliaTsangGammaSampler(rng, alphaGamma, thetaGammaSmallerThanOne),
            gammaMin, gammaMax1, "gamma.case1.txt");
    final double thetaGammaLargerThanOne = 2.345;
    final double gammaMax2 = 70;
    app.createDensity(new AhrensDieterMarsagliaTsangGammaSampler(rng, alphaGamma, thetaGammaLargerThanOne),
            gammaMin, gammaMax2, "gamma.case2.txt");

    final double scalePareto = 23.45;
    final double shapePareto = 0.789;
    final double paretoMin = 23;
    final double paretoMax = 400;
    app.createDensity(new InverseTransformParetoSampler(rng, scalePareto, shapePareto), paretoMin, paretoMax,
            "pareto.txt");

    final double loUniform = -9.876;
    final double hiUniform = 5.432;
    app.createDensity(new ContinuousUniformSampler(rng, loUniform, hiUniform), loUniform, hiUniform,
            "uniform.txt");

    final double scaleLogNormal = 2.345;
    final double shapeLogNormal = 0.1234;
    final double logNormalMin = 5;
    final double logNormalMax = 25;
    app.createDensity(
            new LogNormalSampler(new ZigguratNormalizedGaussianSampler(rng), scaleLogNormal, shapeLogNormal),
            logNormalMin, logNormalMax, "lognormal.ziggurat.txt");
    app.createDensity(
            new LogNormalSampler(new MarsagliaNormalizedGaussianSampler(rng), scaleLogNormal, shapeLogNormal),
            logNormalMin, logNormalMax, "lognormal.marsaglia.txt");
    app.createDensity(
            new LogNormalSampler(new BoxMullerNormalizedGaussianSampler(rng), scaleLogNormal, shapeLogNormal),
            logNormalMin, logNormalMax, "lognormal.boxmuller.txt");
}

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