Examples of com.cloudera.cdk.morphline.shaded.org.apache.commons.math3.random.Well1024a

Package com.cloudera.cdk.morphline.shaded.org.apache.commons.math3.random

Examples of com.cloudera.cdk.morphline.shaded.org.apache.commons.math3.random.Well1024a

org.apache.commons.math3.random.Well1024a
ro.umontreal.ca/~lecuyer/myftp/papers/wellrng.pdf">Improved Long-Period Generators Based on Linear Recurrences Modulo 2 ACM Transactions on Mathematical Software, 32, 1 (2006). The errata for the paper are in wellrng-errata.txt.
@see WELL Random number generator @version $Id: Well1024a.java 1416643 2012-12-03 19:37:14Z tn $ @since 2.2

    public void testPositiveOctantByVertices() {
        double tol = 0.01;
        double sinTol = FastMath.sin(tol);
        SphericalPolygonsSet octant = new SphericalPolygonsSet(tol, S2Point.PLUS_I, S2Point.PLUS_J, S2Point.PLUS_K);
        UnitSphereRandomVectorGenerator random =
                new UnitSphereRandomVectorGenerator(3, new Well1024a(0xb8fc5acc91044308l));
        for (int i = 0; i < 1000; ++i) {
            Vector3D v = new Vector3D(random.nextVector());
            if ((v.getX() > sinTol) && (v.getY() > sinTol) && (v.getZ() > sinTol)) {
                Assert.assertEquals(Location.INSIDE, octant.checkPoint(new S2Point(v)));
            } else if ((v.getX() < -sinTol) || (v.getY() < -sinTol) || (v.getZ() < -sinTol)) {

View Full Code Here

        SphericalPolygonsSet plusZ = new SphericalPolygonsSet(Vector3D.PLUS_K, tol);
        SphericalPolygonsSet threeOctants =
                (SphericalPolygonsSet) factory.difference(plusZ, factory.intersection(plusX, plusY));


        UnitSphereRandomVectorGenerator random =
                new UnitSphereRandomVectorGenerator(3, new Well1024a(0x9c9802fde3cbcf25l));
        for (int i = 0; i < 1000; ++i) {
            Vector3D v = new Vector3D(random.nextVector());
            if (((v.getX() < -sinTol) || (v.getY() < -sinTol)) && (v.getZ() > sinTol)) {
                Assert.assertEquals(Location.INSIDE, threeOctants.checkPoint(new S2Point(v)));
            } else if (((v.getX() > sinTol) && (v.getY() > sinTol)) || (v.getZ() < -sinTol)) {

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        boundary.add(create(Vector3D.MINUS_K, Vector3D.MINUS_J, Vector3D.MINUS_I,  tol, 0.0, 0.5 * FastMath.PI));


        SphericalPolygonsSet polygon = new SphericalPolygonsSet(boundary, tol);


        UnitSphereRandomVectorGenerator random =
                new UnitSphereRandomVectorGenerator(3, new Well1024a(0xcc5ce49949e0d3ecl));
        for (int i = 0; i < 1000; ++i) {
            Vector3D v = new Vector3D(random.nextVector());
            if ((v.getX() < -sinTol) && (v.getY() < -sinTol) && (v.getZ() < -sinTol)) {
                Assert.assertEquals(Location.INSIDE, polygon.checkPoint(new S2Point(v)));
            } else if ((v.getX() < sinTol) && (v.getY() < sinTol) && (v.getZ() < sinTol)) {

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    @Test
    public void testLinearCombination2DSDS() {
        // 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(0xc6af886975069f11l);


        for (int i = 0; i < 10000; ++i) {
            final DerivativeStructure[] u = new DerivativeStructure[4];
            final DerivativeStructure[] v = new DerivativeStructure[4];
            for (int j = 0; j < u.length; ++j) {
                u[j] = new DerivativeStructure(u.length, 1, j, 1e17 * random.nextDouble());
                v[j] = new DerivativeStructure(u.length, 1, 1e17 * random.nextDouble());
            }


            DerivativeStructure lin = u[0].linearCombination(u[0], v[0], u[1], v[1]);
            double ref = u[0].getValue() * v[0].getValue() +
                         u[1].getValue() * v[1].getValue();

View Full Code Here


    @Test
    public void testLinearCombination2DoubleDS() {
        // 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(0xc6af886975069f11l);


        for (int i = 0; i < 10000; ++i) {
            final double[] u = new double[4];
            final DerivativeStructure[] v = new DerivativeStructure[4];
            for (int j = 0; j < u.length; ++j) {
                u[j] = 1e17 * random.nextDouble();
                v[j] = new DerivativeStructure(u.length, 1, j, 1e17 * random.nextDouble());
            }


            DerivativeStructure lin = v[0].linearCombination(u[0], v[0], u[1], v[1]);
            double ref = u[0] * v[0].getValue() +
                         u[1] * v[1].getValue();

View Full Code Here


    @Test
    public void testLinearCombination2() {
        // 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();
            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

    @Test
    public void testShuffleTail() {
        final int[] orig = new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 };
        final int[] list = orig.clone();
        final int start = 4;
        MathArrays.shuffle(list, start, MathArrays.Position.TAIL, new Well1024a(7654321L));


        // Ensure that all entries below index "start" did not move.
        for (int i = 0; i < start; i++) {
            Assert.assertEquals(orig[i], list[i]);
        }

View Full Code Here

    @Test
    public void testShuffleHead() {
        final int[] orig = new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 };
        final int[] list = orig.clone();
        final int start = 4;
        MathArrays.shuffle(list, start, MathArrays.Position.HEAD, new Well1024a(1234567L));


        // Ensure that all entries above index "start" did not move.
        for (int i = start + 1; i < orig.length; i++) {
            Assert.assertEquals(orig[i], list[i]);
        }

View Full Code Here


    @Test
    public void testLinearCombination2DoubleDS() {
        // 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(0xc6af886975069f11l);


        for (int i = 0; i < 10000; ++i) {
            final double[] u = new double[4];
            final DerivativeStructure[] v = new DerivativeStructure[4];
            for (int j = 0; j < u.length; ++j) {
                u[j] = 1e17 * random.nextDouble();
                v[j] = new DerivativeStructure(u.length, 1, j, 1e17 * random.nextDouble());
            }


            DerivativeStructure lin = v[0].linearCombination(u[0], v[0], u[1], v[1]);
            double ref = u[0] * v[0].getValue() +
                         u[1] * v[1].getValue();

View Full Code Here


    @Test
    public void testCrossProduct() {
        // we compare accurate versus naive cross product implementations
        // on regular vectors (i.e. not extreme cases like in the previous test)
        Well1024a random = new Well1024a(885362227452043214l);
        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();
            Vector3D cNaive = new Vector3D(uy * vz - uz * vy, uz * vx - ux * vz, ux * vy - uy * vx);
            Vector3D cAccurate = new Vector3D(ux, uy, uz).crossProduct(new Vector3D(vx, vy, vz));
            Assert.assertEquals(0.0, cAccurate.distance(cNaive), 6.0e-15 * cAccurate.getNorm());
        }
    }

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