List of nextUniform() Examples

Examples of nextUniform()

cc.mallet.util.Randoms.nextUniform()
Return a random double in the range 0 to 1, inclusive, uniformly sampled from that range. The mean of this distribution is 0.5. The variance is 1/12.
org.apache.commons.math.random.RandomData.nextUniform()
tl.nist.gov/div898/handbook/eda/section3/eda3662.htm"> Uniform Distribution lower and upper - lower are the location and scale parameters, respectively.

Preconditions:
- lower < upper (otherwise an IllegalArgumentException is thrown.)
@param lower lower endpoint of the interval of support @param upper upper endpoint of the interval of support @return uniformly distributed random value between lowerand upper (exclusive)
org.apache.commons.math.random.RandomDataImpl.nextUniform()
{@inheritDoc}
Algorithm Description: scales the output of Random.nextDouble(), but rejects 0 values (i.e., will generate another random double if Random.nextDouble() returns 0). This is necessary to provide a symmetric output interval (both endpoints excluded).
@param lower the lower bound. @param upper the upper bound. @return a uniformly distributed random value from the interval (lower,upper) @throws NumberIsTooLargeException if {@code lower >= upper}.
org.apache.commons.math3.random.RandomData.nextUniform()
tl.nist.gov/div898/handbook/eda/section3/eda3662.htm"> Uniform Distribution {@code lower} and {@code upper - lower} are the location and scale parameters, respectively.
@param lower the exclusive lower bound of the support @param upper the exclusive upper bound of the support @return a uniformly distributed random value between lower and upper(exclusive) @throws NumberIsTooLargeException if {@code lower >= upper} @throws NotFiniteNumberException if one of the bounds is infinite @throws NotANumberException if one of the bounds is NaN
org.apache.commons.math3.random.RandomDataImpl.nextUniform()
{@inheritDoc}
Algorithm Description: scales the output of Random.nextDouble(), but rejects 0 values (i.e., will generate another random double if Random.nextDouble() returns 0). This is necessary to provide a symmetric output interval (both endpoints excluded).

Examples of org.apache.commons.math.random.RandomDataImpl.nextUniform()

        double[] permuted = new double[10];
        RandomDataImpl random = new RandomDataImpl();
        
        // Generate 10 distinct random values
        for (int i = 0; i < 10; i++) {
            original[i] = random.nextUniform(i + 0.5, i + 0.75);
        }
        
        // Generate a random permutation, making sure it is not the identity
        boolean isIdentity = true;
        do {

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Examples of org.apache.commons.math.random.RandomDataImpl.nextUniform()

    private double[] generateSample() {
        final RandomData randomData = new RandomDataImpl();
        final int sampleSize = randomData.nextInt(10,100);
        double[] out = new double[sampleSize];
        for (int i = 0; i < out.length; i++) {
            out[i] = randomData.nextUniform(-100, 100);
        }
        return out;     
    }
    
    /**

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Examples of org.apache.commons.math3.random.RandomData.nextUniform()

    private double[] generateSample() {
        final RandomData randomData = new RandomDataImpl();
        final int sampleSize = randomData.nextInt(10,100);
        double[] out = new double[sampleSize];
        for (int i = 0; i < out.length; i++) {
            out[i] = randomData.nextUniform(-100, 100);
        }
        return out;
    }


    /**

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Examples of org.apache.commons.math3.random.RandomDataImpl.nextUniform()

        double[] permuted = new double[10];
        RandomDataImpl random = new RandomDataImpl();


        // Generate 10 distinct random values
        for (int i = 0; i < 10; i++) {
            original[i] = random.nextUniform(i + 0.5, i + 0.75);
        }


        // Generate a random permutation, making sure it is not the identity
        boolean isIdentity = true;
        do {

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Examples of org.apache.commons.math3.random.RandomDataImpl.nextUniform()

    private double[] generateSample() {
        final RandomData randomData = new RandomDataImpl();
        final int sampleSize = randomData.nextInt(10,100);
        double[] out = new double[sampleSize];
        for (int i = 0; i < out.length; i++) {
            out[i] = randomData.nextUniform(-100, 100);
        }
        return out;
    }


    /**

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