Examples of RandomDataImpl


Examples of org.apache.commons.math.random.RandomDataImpl

    public void testWithInitialCapacity() {

        ResizableDoubleArray eDA2 = new ResizableDoubleArray(2);
        assertEquals("Initial number of elements should be 0", 0, eDA2.getNumElements());

        RandomData randomData = new RandomDataImpl();
        int iterations = randomData.nextInt(100, 1000);

        for( int i = 0; i < iterations; i++) {
            eDA2.addElement( i );
        }
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Examples of org.apache.commons.math.random.RandomDataImpl

    public void testWithInitialCapacityAndExpansionFactor() {

        ResizableDoubleArray eDA3 = new ResizableDoubleArray(3, 3.0f, 3.5f);
        assertEquals("Initial number of elements should be 0", 0, eDA3.getNumElements() );

        RandomData randomData = new RandomDataImpl();
        int iterations = randomData.nextInt(100, 3000);

        for( int i = 0; i < iterations; i++) {
            eDA3.addElement( i );
        }
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Examples of org.apache.commons.math.random.RandomDataImpl

        }
      }
    }
    state.getMap().remove(LAST_SETTING);
    state.getMap().remove(LAST_TABLE_SETTING);
    RandomData random = new RandomDataImpl();
    if (random.nextInt(0, 1) == 0) {
      changeTableSetting(random, state, props);
    } else {
      changeSetting(random, state, props);
    }
  }
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Examples of org.apache.commons.math.random.RandomDataImpl

        final int len = 10;        // length of values array
        final double mu = 0;       // mean of test data
        final double sigma = 5;    // std dev of test data
        double[] values = new double[len];
        double[] weights = new double[len];
        RandomData randomData = new RandomDataImpl();

        // Fill weights array with random int values between 1 and 5
        int[] intWeights = new int[len];
        for (int i = 0; i < len; i++) {
            intWeights[i] = randomData.nextInt(1, 5);
            weights[i] = intWeights[i];
        }

        // Fill values array with random data from N(mu, sigma)
        // and fill valuesList with values from values array with
        // values[i] repeated weights[i] times, each i
        List<Double> valuesList = new ArrayList<Double>();
        for (int i = 0; i < len; i++) {
            double value = randomData.nextGaussian(mu, sigma);
            values[i] = value;
            for (int j = 0; j < intWeights[i]; j++) {
                valuesList.add(new Double(value));
            }
        }
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Examples of org.apache.commons.math.random.RandomDataImpl

        int[] primeList = {19, 23, 53, 67, 73, 79, 101, 103, 111, 131};
        ArrayList<Integer> primes = new ArrayList<Integer>();
        for (int i = 0; i < primeList.length; i++) {
            primes.add(Integer.valueOf(primeList[i]));
        }
        RandomDataImpl randomData = new RandomDataImpl();
        for (int i = 0; i < 20; i++) {
            Object[] sample = randomData.nextSample(primes, 4);
            int p1 = ((Integer) sample[0]).intValue();
            int p2 = ((Integer) sample[1]).intValue();
            int p3 = ((Integer) sample[2]).intValue();
            int p4 = ((Integer) sample[3]).intValue();
            int i1 = p1 * p2 * p3;
 
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Examples of org.apache.commons.math.random.RandomDataImpl

     * Make sure that permuted arrays do not hash to the same value.
     */
    public void testPermutedArrayHash() {
        double[] original = new double[10];
        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 {
            int[] permutation = random.nextPermutation(10, 10);
            for (int i = 0; i < 10; i++) {
                if (i != permutation[i]) {
                    isIdentity = false;
                }
                permuted[i] = original[permutation[i]];
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Examples of org.apache.commons.math.random.RandomDataImpl

        }
      }
    }
    state.getMap().remove(LAST_SETTING);
    state.getMap().remove(LAST_TABLE_SETTING);
    RandomData random = new RandomDataImpl();
    if (random.nextInt(0, 1) == 0) {
      changeTableSetting(random, state, props);
    } else {
      changeSetting(random, state, props);
    }
  }
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Examples of org.apache.commons.math.random.RandomDataImpl

     */
    public NaturalRanking(TiesStrategy tiesStrategy) {
        super();
        this.tiesStrategy = tiesStrategy;
        nanStrategy = DEFAULT_NAN_STRATEGY;
        randomData = new RandomDataImpl();
    }
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Examples of org.apache.commons.math.random.RandomDataImpl

     */
    public NaturalRanking(NaNStrategy nanStrategy, TiesStrategy tiesStrategy) {
        super();
        this.nanStrategy = nanStrategy;
        this.tiesStrategy = tiesStrategy;
        randomData = new RandomDataImpl();
    }
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Examples of org.apache.commons.math.random.RandomDataImpl

     */
    public NaturalRanking(RandomGenerator randomGenerator) {
        super();
        this.tiesStrategy = TiesStrategy.RANDOM;
        nanStrategy = DEFAULT_NAN_STRATEGY;
        randomData = new RandomDataImpl(randomGenerator);
    }
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