Package com.cloudera.cdk.morphline.shaded.org.apache.commons.math3.random

Examples of com.cloudera.cdk.morphline.shaded.org.apache.commons.math3.random.Well19937c

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    private Iterator<double[]> createRandomIterator(final long numSamples) {
        return new Iterator<double[]>() {
            /** Data. */
            final Vector3D[] points = rings.getPoints();
            /** RNG. */
            final RandomGenerator rng = new Well19937c();
            /** Number of samples. */
            private long n = 0;

            /** {@inheritDoc} */
            public boolean hasNext() {
                return n < numSamples;
            }

            /** {@inheritDoc} */
            public double[] next() {
                ++n;
                return points[rng.nextInt(points.length)].toArray();
            }

            /** {@inheritDoc} */
            public void remove() {
                throw new MathUnsupportedOperationException();
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     */
    public FDistribution(double numeratorDegreesOfFreedom,
                         double denominatorDegreesOfFreedom,
                         double inverseCumAccuracy)
        throws NotStrictlyPositiveException {
        this(new Well19937c(), numeratorDegreesOfFreedom,
             denominatorDegreesOfFreedom, inverseCumAccuracy);
    }
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     * {@code scale <= 0}.
     * @since 2.1
     */
    public GammaDistribution(double shape, double scale, double inverseCumAccuracy)
        throws NotStrictlyPositiveException {
        this(new Well19937c(), shape, scale, inverseCumAccuracy);
    }
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            };
           
            this.location = new double[] { 0, 0 };
           
            this.measurementNoise = measurementNoise;
            this.rng = new Well19937c(seed);
        }
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     * {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
     * @since 2.1
     */
    public ChiSquaredDistribution(double degreesOfFreedom,
                                  double inverseCumAccuracy) {
        this(new Well19937c(), degreesOfFreedom, inverseCumAccuracy);
    }
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     *
     * @param p probability of success.
     * @throws OutOfRangeException if {@code p <= 0} or {@code p > 1}.
     */
    public GeometricDistribution(double p) {
        this(new Well19937c(), p);
    }
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     * {@code beta <= 0}.
     * @since 2.1
     */
    public WeibullDistribution(double alpha, double beta,
                               double inverseCumAccuracy) {
        this(new Well19937c(), alpha, beta, inverseCumAccuracy);
    }
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     * {@link #DEFAULT_INVERSE_ABSOLUTE_ACCURACY}).
     * @throws NotStrictlyPositiveException if {@code mean <= 0}.
     * @since 2.1
     */
    public ExponentialDistribution(double mean, double inverseCumAccuracy) {
        this(new Well19937c(), mean, inverseCumAccuracy);
    }
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     * @param upper Upper bound (inclusive) of this distribution.
     * @throws NumberIsTooLargeException if {@code lower >= upper}.
     */
    public UniformIntegerDistribution(int lower, int upper)
        throws NumberIsTooLargeException {
        this(new Well19937c(), lower, upper);
    }
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     * @throws NumberIsTooLargeException if {@code numberOfSuccesses > populationSize},
     * or {@code sampleSize > populationSize}.
     */
    public HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize)
    throws NotPositiveException, NotStrictlyPositiveException, NumberIsTooLargeException {
        this(new Well19937c(), populationSize, numberOfSuccesses, sampleSize);
    }
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