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

Class org.apache.commons.math.random.RandomDataImpl

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

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}.

        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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    if (range.getMinimumNumber() instanceof Long && range.getMaximumNumber() instanceof Long) {
      result = randomData.nextLong(range.getMinimumLong(), range.getMaximumLong());
    }


    if (range.getMinimumNumber() instanceof Float && range.getMaximumNumber() instanceof Float) {
      result = randomData.nextUniform(range.getMinimumFloat(), range.getMaximumFloat());
    }


    if (range.getMinimumNumber() instanceof Double && range.getMaximumNumber() instanceof Double) {
      result = randomData.nextUniform(range.getMinimumDouble(), range.getMaximumDouble());
    }

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    if (range.getMinimumNumber() instanceof Float && range.getMaximumNumber() instanceof Float) {
      result = randomData.nextUniform(range.getMinimumFloat(), range.getMaximumFloat());
    }


    if (range.getMinimumNumber() instanceof Double && range.getMaximumNumber() instanceof Double) {
      result = randomData.nextUniform(range.getMinimumDouble(), range.getMaximumDouble());
    }


    return result;
  }

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        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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    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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        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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    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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