Package org.apache.commons.math3.random

Examples of org.apache.commons.math3.random.RandomGenerator

63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
*  - allow editing of the point set
*/
public class GeometryExample {

    public static List<Vector2D> createRandomPoints(int size) {
        RandomGenerator random = new MersenneTwister();

        // 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;
    }
View Full Code Here
240
241
242
243
244
245
246
247
248
249
250
                                   new GammaDistribution(5, 1),
                                   new GammaDistribution(9, 0.5));
            container.add(comp, c);

            c.gridx++;
            RandomGenerator rng = new MersenneTwister(0);
            comp = createComponent("Levy", 0, 3,
                                   new String[] { "c=0.5", "c=1", "c=2", "c=4", "c=8" },
                                   new LevyDistribution(rng, 0, 0.5),
                                   new LevyDistribution(rng, 0, 1),
                                   new LevyDistribution(rng, 0, 2),
View Full Code Here
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
     * Creates a new random Polygon of the given length.
     */
    public static Polygon randomPolygon(int length) {
        final int polygonSize = 4 + 2 * length;

        final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();
       
        Polygon p = new Polygon();
        p.data = new float[polygonSize];

        p.data[0] = random.nextFloat(); // r
        p.data[1] = random.nextFloat(); // g
        p.data[2] = random.nextFloat(); // b
        p.data[3] = FastMath.max(0.2f, random.nextFloat() * random.nextFloat()); // a
       
        float px = random.nextFloat();
        float py = random.nextFloat();
       
        for (int k = 0; k < length; k++) {
            p.data[4 + 2*k] = px + (random.nextFloat() - 0.5f);
            p.data[5 + 2*k] = py + (random.nextFloat() - 0.5f);
        }
        return p;
    }
View Full Code Here
188
189
190
191
192
193
194
195
196
197
198
           
            setLayout(new GridBagLayout());
           
            int nSamples = 1500;
           
            RandomGenerator rng = new Well19937c(0);
            List<List<DoublePoint>> datasets = new ArrayList<List<DoublePoint>>();

            datasets.add(normalize(makeCircles(nSamples, true, 0.04, 0.5, rng), -1, 1, -1, 1));
            datasets.add(normalize(makeMoons(nSamples, true, 0.04, rng), -1, 2, -1, 1));
            datasets.add(normalize(makeBlobs(nSamples, 3, 1.0, -10, 10, true, rng), -12, 12, -12, 12));
View Full Code Here
50
51
52
53
54
55
56
57
58
59
60
                                      double y,
                                      double radius,
                                      double xSigma,
                                      double ySigma,
                                      long seed) {
        final RandomGenerator rng = new Well44497b(seed);
        this.radius = radius;
        cX = new NormalDistribution(rng, x, xSigma,
                                    NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        cY = new NormalDistribution(rng, y, ySigma,
                                    NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
View Full Code Here
58
59
60
61
62
63
64
65
66
67
68
                                            double b,
                                            double sigma,
                                            double lo,
                                            double hi,
                                            long seed) {
        final RandomGenerator rng = new Well44497b(seed);
        slope = a;
        intercept = b;
        error = new NormalDistribution(rng, 0, sigma,
                                       NormalDistribution.DEFAULT_INVERSE_ABSOLUTE_ACCURACY);
        x = new UniformRealDistribution(rng, lo, hi,
View Full Code Here
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
        final List<T> parent2Rep = second.getRepresentation();
        // and of the children
        final List<T> child1Rep = new ArrayList<T>(length);
        final List<T> child2Rep = new ArrayList<T>(length);

        final RandomGenerator random = GeneticAlgorithm.getRandomGenerator();

        for (int index = 0; index < length; index++) {

            if (random.nextDouble() < ratio) {
                // swap the bits -> take other parent
                child1Rep.add(parent2Rep.get(index));
                child2Rep.add(parent1Rep.get(index));
            } else {
                child1Rep.add(parent1Rep.get(index));
View Full Code Here
169
170
171
172
173
174
175
176
177
178
179
180
        TestUtils.assertEquals(correctRanks, ranks, 0d);
    }

    @Test
    public void testNaNsFixedTiesRandom() {
        RandomGenerator randomGenerator = new JDKRandomGenerator();
        randomGenerator.setSeed(1000);
        NaturalRanking ranking = new NaturalRanking(NaNStrategy.FIXED,
                randomGenerator);
        double[] ranks = ranking.rank(exampleData);
        double[] correctRanks = { 5, 3, 6, 7, 3, 8, Double.NaN, 1, 2 };
        TestUtils.assertEquals(correctRanks, ranks, 0d);
View Full Code Here
390
391
392
393
394
395
396
397
398
399
400
        }
    }

    @Test
    public void testLinearCombinationFaFa() {
        RandomGenerator r = new Well1024a(0xfafal);
        for (int i = 0; i < 50; ++i) {
            double[] aD = generateDouble(r, 10);
            double[] bD = generateDouble(r, 10);
            T[] aF      = toFieldArray(aD);
            T[] bF      = toFieldArray(bD);
View Full Code Here
403
404
405
406
407
408
409
410
411
412
413
        }
    }

    @Test
    public void testLinearCombinationDaFa() {
        RandomGenerator r = new Well1024a(0xdafal);
        for (int i = 0; i < 50; ++i) {
            double[] aD = generateDouble(r, 10);
            double[] bD = generateDouble(r, 10);
            T[] bF      = toFieldArray(bD);
            checkRelative(MathArrays.linearCombination(aD, bD),
View Full Code Here
TOP

Related Classes of org.apache.commons.math3.random.RandomGenerator

  • net.myrrix.online.factorizer.als.AlternatingLeastSquares
  • net.myrrix.online.som.SelfOrganizingMaps
  • org.apache.commons.math3.analysis.differentiation.DerivativeStructure
  • org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction
  • org.apache.commons.math3.analysis.function.HarmonicOscillator
  • org.apache.commons.math3.analysis.function.LogitTest
  • org.apache.commons.math3.analysis.function.Sin
  • org.apache.commons.math3.analysis.function.Sinc
  • org.apache.commons.math3.analysis.interpolation.BicubicSplineInterpolatingFunctionTest
  • org.apache.commons.math3.analysis.interpolation.BicubicSplineInterpolatorTest
    • Copyright © 2018 www.massapicom. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.