Package org.apache.commons.math3.random

Examples of org.apache.commons.math3.random.MersenneTwister.nextDouble()

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        final ISAACRandom rand = new ISAACRandom(10L);// Seed can be changed
        final SimpleRegression whole = new SimpleRegression(includeIntercept);// regression of the whole set
        final SimpleRegression parts = new SimpleRegression(includeIntercept);// regression with parts.

        for (int s = 0; s < sets; s++) {// loop through each subset of data.
            final double coef = rand.nextDouble();
            final SimpleRegression sub = new SimpleRegression(includeIntercept);// sub regression
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                final double x = rand.nextDouble();
                final double y = x * coef + rand.nextDouble();// some noise
                sub.addData(x, y);
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        for (int s = 0; s < sets; s++) {// loop through each subset of data.
            final double coef = rand.nextDouble();
            final SimpleRegression sub = new SimpleRegression(includeIntercept);// sub regression
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                final double x = rand.nextDouble();
                final double y = x * coef + rand.nextDouble();// some noise
                sub.addData(x, y);
                whole.addData(x, y);
            }
            parts.append(sub);
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        for (int s = 0; s < sets; s++) {// loop through each subset of data.
            final double coef = rand.nextDouble();
            final SimpleRegression sub = new SimpleRegression(includeIntercept);// sub regression
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                final double x = rand.nextDouble();
                final double y = x * coef + rand.nextDouble();// some noise
                sub.addData(x, y);
                whole.addData(x, y);
            }
            parts.append(sub);
            Assert.assertTrue(equals(parts, whole, 1E-6));
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        final ISAACRandom rand = new ISAACRandom(10L);// Seed can be changed
        final SimpleRegression whole = new SimpleRegression(includeIntercept);// regression of the whole set
        final SimpleRegression parts = new SimpleRegression(includeIntercept);// regression with parts.

        for (int s = 0; s < sets; s++) {// loop through each subset of data.
            final double coef = rand.nextDouble();
            final SimpleRegression sub = new SimpleRegression(includeIntercept);// sub regression
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                final double x = rand.nextDouble();
                final double y = x * coef + rand.nextDouble();// some noise
                sub.addData(x, y);
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        for (int s = 0; s < sets; s++) {// loop through each subset of data.
            final double coef = rand.nextDouble();
            final SimpleRegression sub = new SimpleRegression(includeIntercept);// sub regression
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                final double x = rand.nextDouble();
                final double y = x * coef + rand.nextDouble();// some noise
                sub.addData(x, y);
                whole.addData(x, y);
            }
            parts.append(sub);
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        for (int s = 0; s < sets; s++) {// loop through each subset of data.
            final double coef = rand.nextDouble();
            final SimpleRegression sub = new SimpleRegression(includeIntercept);// sub regression
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                final double x = rand.nextDouble();
                final double y = x * coef + rand.nextDouble();// some noise
                sub.addData(x, y);
                whole.addData(x, y);
            }
            parts.append(sub);
            Assert.assertTrue(equals(parts, whole, 1E-6));
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        ISAACRandom rand = new ISAACRandom(10L);// Seed can be changed
        for (int s = 0; s < num_sets; s++) {// loop through sets of samlpes
            StorelessBivariateCovariance covs = new StorelessBivariateCovariance();
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                double x = rand.nextDouble();
                double y = rand.nextDouble();
                covs.increment(x, y);// add sample to the subset
                cov.increment(x, y);// add sample to the superset
            }
           chk.append(covs);
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        ISAACRandom rand = new ISAACRandom(10L);// Seed can be changed
        for (int s = 0; s < num_sets; s++) {// loop through sets of samlpes
            StorelessBivariateCovariance covs = new StorelessBivariateCovariance();
            for (int i = 0; i < 5; i++) { // loop through individual samlpes.
                double x = rand.nextDouble();
                double y = rand.nextDouble();
                covs.increment(x, y);// add sample to the subset
                cov.increment(x, y);// add sample to the superset
            }
           chk.append(covs);
        }
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        // create the cloud container
        List<Vector2D> points = new ArrayList<Vector2D>(size);
        // fill the cloud with a random distribution of points
        for (int i = 0; i < size; i++) {
            points.add(new Vector2D(FastMath.round(random.nextDouble() * 400 + 100),
                    FastMath.round(random.nextDouble() * 400 + 100)));
        }
       
        return points;
    }
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        // create the cloud container
        List<Vector2D> points = new ArrayList<Vector2D>(size);
        // fill the cloud with a random distribution of points
        for (int i = 0; i < size; i++) {
            points.add(new Vector2D(FastMath.round(random.nextDouble() * 400 + 100),
                    FastMath.round(random.nextDouble() * 400 + 100)));
        }
       
        return points;
    }

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