Package org.apache.mahout.math.jet.random

Examples of org.apache.mahout.math.jet.random.AbstractContinousDistribution.nextDouble()

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        TDigest dist = new TDigest((double) 1000, gen);
        long t0 = System.nanoTime();
        List<Double> data = Lists.newArrayList();
        for (int i1 = 0; i1 < 100000; i1++) {
            double x = mix.nextDouble();
            data.add(x);
            dist.add(x);
        }

        System.out.printf("# %fus per point\n", (System.nanoTime() - t0) * 1e-3 / 100000);
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  private static OnlineSummarizer gamma(int n, double shape) {
    OnlineSummarizer x = new OnlineSummarizer();
    Random gen = RandomUtils.getRandom();
    AbstractContinousDistribution gamma = new Gamma(shape, shape, gen);
    for (int i = 0; i < n; i++) {
      x.add(gamma.nextDouble());
    }
    return x;
  }

}
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        TDigest dist = new TDigest((double) 1000);
        long t0 = System.nanoTime();
        Multiset<Double> data = HashMultiset.create();
        for (int i1 = 0; i1 < 100000; i1++) {
            double x = mix.nextDouble();
            data.add(x);
            dist.add(x);
        }

        System.out.printf("# %fus per point\n", (System.nanoTime() - t0) * 1e-3 / 100000);
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  private static double[] gamma(int n, double shape) {
    double[] r = new double[n];
    Random gen = RandomUtils.getRandom();
    AbstractContinousDistribution gamma = new Gamma(shape, shape, gen);
    for (int i = 0; i < n; i++) {
      r[i] = gamma.nextDouble();
    }
    return r;
  }
}
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        };

        TreeDigest dist = new TreeDigest((double) 1000);
        List<Double> data = Lists.newArrayList();
        for (int i1 = 0; i1 < 100000; i1++) {
            double x = mix.nextDouble();
            data.add(x);
        }

        long t0 = System.nanoTime();
        for (double x : data) {
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        for (int run = 0; run < 3 * repeats(); run++) {
            TDigest dist = new ArrayDigest(32, (double) 1000);
            List<Double> data = Lists.newArrayList();
            for (int i1 = 0; i1 < 100000; i1++) {
                data.add(mix.nextDouble());
            }

            long t0 = System.nanoTime();
            for (double x : data) {
                dist.add(x);
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        };

        AVLTreeDigest dist = new AVLTreeDigest((double) 1000);
        List<Double> data = Lists.newArrayList();
        for (int i1 = 0; i1 < 100000; i1++) {
            double x = mix.nextDouble();
            data.add(x);
        }

        long t0 = System.nanoTime();
        for (double x : data) {
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        double[] y = new double[10000];
        double[] z = new double[10000];
        AbstractContinousDistribution dist = gnd.posteriorDistribution();
        for (int i = 0; i < 10000; i++) {
            x[i] = gnd.nextDouble();
            y[i] = dist.nextDouble();
            z[i] = gen.nextGaussian() * 2 + 1;
        }

        Arrays.sort(x);
        Arrays.sort(y);
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