Example usage for org.apache.commons.rng.sampling.distribution ContinuousSampler sample

Introduction

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

Prototype

double sample();

Source Link

Document

Creates a sample.

Usage

From source file:org.apache.commons.rng.examples.jmh.distribution.SamplersPerformance.java

/**
 * Exercises a continuous sampler./*from w  w w  . ja  va 2s.  c o  m*/
 *
 * @param sampler Sampler.
 * @param bh Data sink.
 */
private void runSample(ContinuousSampler sampler, Blackhole bh) {
    for (int i = 0; i < NUM_SAMPLES; i++) {
        bh.consume(sampler.sample());
    }
}

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

/**
 * @param sampler Sampler./*from   www  .  j ava 2 s  .  c  o  m*/
 * @param min Right abscissa of the first bin: every sample smaller
 * than that value will increment an additional bin (of infinite width)
 * placed before the first "equal-width" bin.
 * @param Left abscissa of the last bin: every sample larger than or
 * equal to that value will increment an additional bin (of infinite
 * width) placed after the last "equal-width" bin.
 * @param output Filename.
 */
private void createDensity(ContinuousSampler sampler, double min, double max, String outputFile)
        throws IOException {
    final double binSize = (max - min) / numBins;
    final long[] histogram = new long[numBins];

    long n = 0;
    long belowMin = 0;
    long aboveMax = 0;
    while (++n < numSamples) {
        final double r = sampler.sample();

        if (r < min) {
            ++belowMin;
            continue;
        }

        if (r >= max) {
            ++aboveMax;
            continue;
        }

        final int binIndex = (int) ((r - min) / binSize);
        ++histogram[binIndex];
    }

    final double binHalfSize = 0.5 * binSize;
    final double norm = 1 / (binSize * numSamples);

    final PrintWriter out = new PrintWriter(outputFile);
    out.println("# Sampler: " + sampler);
    out.println("# Number of bins: " + numBins);
    out.println("# Min: " + min + " (fraction of samples below: " + (belowMin / (double) numSamples) + ")");
    out.println("# Max: " + max + " (fraction of samples above: " + (aboveMax / (double) numSamples) + ")");
    out.println("# Bin width: " + binSize);
    out.println("# Histogram normalization factor: " + norm);
    out.println("#");
    out.println("# " + (min - binHalfSize) + " " + (belowMin * norm));
    for (int i = 0; i < numBins; i++) {
        out.println((min + (i + 1) * binSize - binHalfSize) + " " + (histogram[i] * norm));
    }
    out.println("# " + (max + binHalfSize) + " " + (aboveMax * norm));
    out.close();
}

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

/**
 * Program entry point./*w w  w. j  a v  a  2s. c o  m*/
 *
 * @param args Unused.
 */
public static void main(String[] args) {
    final float lo = 0.1f;
    final int bands = 2;
    float hi = lo;
    for (int i = 0; i < bands; i++) {
        hi = Math.nextUp(hi);
    }
    System.out.printf("# lo=%.10e hi=%.10e", lo, hi);
    System.out.println();

    final UniformSamplingVisualCheck app = new UniformSamplingVisualCheck();

    while (true) {
        System.out.printf("%.16e\t", app.rng.nextDouble());

        for (ContinuousSampler s : app.samplers) {
            while (true) {
                final double r = s.sample();
                if (r < lo || r > hi) {
                    // Discard numbers outside the tiny region.
                    continue;
                }

                System.out.printf("%.16e ", r);
                break;
            }
        }

        System.out.println();
    }
}

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