Examples of org.apache.commons.math3.random.Well1024a.nextDouble()

Class org.apache.commons.math3.random.Well1024a

Examples of org.apache.commons.math3.random.Well1024a.nextDouble()

org.apache.commons.math3.random.Well1024a.nextDouble()
Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence. @return the next pseudorandom, uniformly distributeddouble value between 0.0 and 1.0 from this random number generator's sequence

            final double ux = 1e17 * random.nextDouble();
            final double uy = 1e17 * random.nextDouble();
            final double uz = 1e17 * random.nextDouble();
            final double vx = 1e17 * random.nextDouble();
            final double vy = 1e17 * random.nextDouble();
            final double vz = 1e17 * random.nextDouble();
            final double sInline = MathArrays.linearCombination(ux, vx,
                                                                uy, vy,
                                                                uz, vz);
            final double sArray = MathArrays.linearCombination(new double[] {ux, uy, uz},
                                                               new double[] {vx, vy, vz});

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        // we compare accurate versus naive dot product implementations
        // on regular vectors (i.e. not extreme cases like in the previous test)
        Well1024a random = new Well1024a(553267312521321234l);


        for (int i = 0; i < 10000; ++i) {
            final double ux = 1e17 * random.nextDouble();
            final double uy = 1e17 * random.nextDouble();
            final double uz = 1e17 * random.nextDouble();
            final double vx = 1e17 * random.nextDouble();
            final double vy = 1e17 * random.nextDouble();
            final double vz = 1e17 * random.nextDouble();

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        // on regular vectors (i.e. not extreme cases like in the previous test)
        Well1024a random = new Well1024a(553267312521321234l);


        for (int i = 0; i < 10000; ++i) {
            final double ux = 1e17 * random.nextDouble();
            final double uy = 1e17 * random.nextDouble();
            final double uz = 1e17 * random.nextDouble();
            final double vx = 1e17 * random.nextDouble();
            final double vy = 1e17 * random.nextDouble();
            final double vz = 1e17 * random.nextDouble();
            final double sInline = MathArrays.linearCombination(ux, vx,

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        Well1024a random = new Well1024a(553267312521321234l);


        for (int i = 0; i < 10000; ++i) {
            final double ux = 1e17 * random.nextDouble();
            final double uy = 1e17 * random.nextDouble();
            final double uz = 1e17 * random.nextDouble();
            final double vx = 1e17 * random.nextDouble();
            final double vy = 1e17 * random.nextDouble();
            final double vz = 1e17 * random.nextDouble();
            final double sInline = MathArrays.linearCombination(ux, vx,
                                                                uy, vy,

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        for (int i = 0; i < 10000; ++i) {
            final double ux = 1e17 * random.nextDouble();
            final double uy = 1e17 * random.nextDouble();
            final double uz = 1e17 * random.nextDouble();
            final double vx = 1e17 * random.nextDouble();
            final double vy = 1e17 * random.nextDouble();
            final double vz = 1e17 * random.nextDouble();
            final double sInline = MathArrays.linearCombination(ux, vx,
                                                                uy, vy,
                                                                uz, vz);

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        for (int i = 0; i < 10000; ++i) {
            final double ux = 1e17 * random.nextDouble();
            final double uy = 1e17 * random.nextDouble();
            final double uz = 1e17 * random.nextDouble();
            final double vx = 1e17 * random.nextDouble();
            final double vy = 1e17 * random.nextDouble();
            final double vz = 1e17 * random.nextDouble();
            final double sInline = MathArrays.linearCombination(ux, vx,
                                                                uy, vy,
                                                                uz, vz);
            final double sArray = MathArrays.linearCombination(new double[] {ux, uy, uz},

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            final double ux = 1e17 * random.nextDouble();
            final double uy = 1e17 * random.nextDouble();
            final double uz = 1e17 * random.nextDouble();
            final double vx = 1e17 * random.nextDouble();
            final double vy = 1e17 * random.nextDouble();
            final double vz = 1e17 * random.nextDouble();
            final double sInline = MathArrays.linearCombination(ux, vx,
                                                                uy, vy,
                                                                uz, vz);
            final double sArray = MathArrays.linearCombination(new double[] {ux, uy, uz},
                                                               new double[] {vx, vy, vz});

View Full Code Here

    public void testDotProduct() {
        // we compare accurate versus naive dot product implementations
        // on regular vectors (i.e. not extreme cases like in the previous test)
        Well1024a random = new Well1024a(553267312521321234l);
        for (int i = 0; i < 10000; ++i) {
            double ux = 10000 * random.nextDouble();
            double uy = 10000 * random.nextDouble();
            double uz = 10000 * random.nextDouble();
            double vx = 10000 * random.nextDouble();
            double vy = 10000 * random.nextDouble();
            double vz = 10000 * random.nextDouble();

View Full Code Here

        // we compare accurate versus naive dot product implementations
        // on regular vectors (i.e. not extreme cases like in the previous test)
        Well1024a random = new Well1024a(553267312521321234l);
        for (int i = 0; i < 10000; ++i) {
            double ux = 10000 * random.nextDouble();
            double uy = 10000 * random.nextDouble();
            double uz = 10000 * random.nextDouble();
            double vx = 10000 * random.nextDouble();
            double vy = 10000 * random.nextDouble();
            double vz = 10000 * random.nextDouble();
            double sNaive = ux * vx + uy * vy + uz * vz;

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        // on regular vectors (i.e. not extreme cases like in the previous test)
        Well1024a random = new Well1024a(553267312521321234l);
        for (int i = 0; i < 10000; ++i) {
            double ux = 10000 * random.nextDouble();
            double uy = 10000 * random.nextDouble();
            double uz = 10000 * random.nextDouble();
            double vx = 10000 * random.nextDouble();
            double vy = 10000 * random.nextDouble();
            double vz = 10000 * random.nextDouble();
            double sNaive = ux * vx + uy * vy + uz * vz;
            double sAccurate = new Vector3D(ux, uy, uz).dotProduct(new Vector3D(vx, vy, vz));

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