Example usage for java.util Random nextDouble

Introduction

In this page you can find the example usage for java.util Random nextDouble.

Prototype

public double nextDouble() 

Source Link

Document

Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.

Usage

From source file:org.apache.kylin.measure.percentile.PercentileCounterTest.java

@Test
public void testTDigest() {
    double compression = 100;
    double quantile = 0.5;

    PercentileCounter counter = new PercentileCounter(compression, quantile);
    TDigest tDigest = TDigest.createAvlTreeDigest(compression);

    Random random = new Random();
    int dataSize = 10000;
    List<Double> dataset = Lists.newArrayListWithCapacity(dataSize);
    for (int i = 0; i < dataSize; i++) {
        double d = random.nextDouble();
        counter.add(d);/*from  www  .  ja v a 2 s.  com*/
        tDigest.add(d);
    }
    double actualResult = counter.getResultEstimate();

    Collections.sort(dataset);
    double expectedResult = tDigest.quantile(quantile);

    assertEquals(expectedResult, actualResult, 0);
}

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From source file:pl.mg6.android.maps.extensions.demo.LaunchTimeTestActivity.java

@Override
protected void onCreate(Bundle savedInstanceState) {
    super.onCreate(savedInstanceState);
    setContentView(R.layout.launch_time_test);

    FragmentManager fm = getSupportFragmentManager();
    SupportMapFragment f = (SupportMapFragment) fm.findFragmentById(R.id.map);
    GoogleMap map = f.getExtendedMap();/*from  w  w  w  .  j a  va 2s.  co m*/

    int clusteringType = getIntent().getIntExtra(EXTRA_CLUSTERING_TYPE, CLUSTERING_DISABLED);

    ClusteringSettings settings = new ClusteringSettings();
    switch (clusteringType) {
    case CLUSTERING_DISABLED_DYNAMIC:
        settings.enabled(false).addMarkersDynamically(true);
        break;
    case CLUSTERING_ENABLED:
        settings.clusterOptionsProvider(new DemoClusterOptionsProvider(getResources()));
        break;
    case CLUSTERING_ENABLED_DYNAMIC:
        settings.clusterOptionsProvider(new DemoClusterOptionsProvider(getResources()))
                .addMarkersDynamically(true);
        break;
    default:
        settings.enabled(false);
    }

    map.setClustering(settings);

    Random r = new Random(0);
    MarkerOptions options = new MarkerOptions();

    long start = SystemClock.uptimeMillis();
    for (int i = 0; i < MARKERS_COUNT; i++) {
        LatLng position = new LatLng(r.nextDouble() * 170 - 85, r.nextDouble() * 360 - 180);
        map.addMarker(options.position(position));
    }
    long end = SystemClock.uptimeMillis();
    long time = end - start;
    float zoom = map.getCameraPosition().zoom;
    String format = "Time adding %d markers (option: %d, zoom: %.1f): %d";
    String text = String.format(Locale.US, format, MARKERS_COUNT, clusteringType, zoom, time);
    Log.i(TAG, text);
}

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From source file:com.comphenix.xp.SampleRange.java

private int sampleIntReduced(Random rnd) {
    double value = sampleDouble(rnd);

    // Probability of adding the fraction
    double fraction = value - Math.floor(value);
    double toAdd = rnd.nextDouble() < fraction ? Math.signum(value) : 0;

    return (int) value + (int) toAdd;
}

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From source file:ffx.utilities.BlockAverager.java

/**
 * Uncorrelated process: x = 5 + 2 * rand(N,1) - 1 Correlated process: x(1)
 * = 0; x(t+1) = 0.95 * x(t) + 2 * rand(N,1) - 1; shift all up by 5
 *///from  w w  w .  ja  v  a  2s .c om
public static void generateTestData(String filename, int size) throws IOException {
    logger.info(format(" Generating test data set of size: %d.", size));
    File outFile = new File(filename);
    if (outFile.exists()) {
        logger.severe("Outfile already exists.");
    }
    Random rng = new Random();
    double[] uncor = new double[size];
    double[] corr = new double[size];
    corr[0] = 0.0;
    for (int i = 0; i < size; i++) {
        uncor[i] = 5 + (2 * rng.nextDouble() - 1);
        if (i > 0) {
            corr[i] = 0.95 * corr[i - 1] + (2 * rng.nextDouble() - 1);
        }
    }
    for (int i = 0; i < size; i++) {
        corr[i] += 5.0;
    }
    BufferedWriter bw = new BufferedWriter(new FileWriter(outFile));
    for (int i = 0; i < size; i++) {
        bw.write(format(" %4d  %6.4f  %6.4f", i, uncor[i], corr[i]));
        bw.newLine();
    }
    bw.close();
    logger.info(format("    Data saved to: %s", filename));
}

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From source file:com.insightml.data.samples.AbstractSamples.java

@Override
public final Pair<ISamples<S, E>, ISamples<S, E>> sample(final double ratio, final Random random) {
    Check.num(ratio, 0.01, 0.95);/*from  w  w w . ja v  a 2  s . com*/
    final int n = size();
    if (featureNames() == null) {
        final List<S> list = new LinkedList<>();
        for (int i = 0; i < n; ++i) {
            if (random.nextDouble() <= ratio) {
                list.add(get(i));
            }
        }
        return new Pair<>(new Samples<>(list), null);
    }
    final IntArray list = new IntArray(n);
    for (int i = 0; i < n; ++i) {
        if (random.nextDouble() <= ratio) {
            list.add(i);
        }
    }
    return new Pair<>(subset(list.toArray()), null);
}

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From source file:co.com.estacionsannicolas.initializer.SeedDataInitializer.java

private Date getRandomBirthDate() {
    long seventyYearsInMillis = 70L * 365L * 24L * 60L * 60L * 1000L;
    Random random = new Random();
    long randomYearOffsetInMillis = (long) (random.nextDouble() * seventyYearsInMillis);
    return new Date(System.currentTimeMillis() - randomYearOffsetInMillis);
}

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From source file:com.polytech4A.cuttingstock.core.solver.SimulatedAnnealing.java

/**
 * Simulate Annealing Algorithm.//from  ww  w . j  av  a2s.c  om
 *
 * @param solution First Solution of the Algorithm, it's also best solution for beginning.
 * @return bestsolution Found.
 */
public Solution simulateAnnealing(Solution solution) {
    Solution bestSolution = solution;
    Result bestCost = simplex.minimize(solution);
    Solution randomSolution;
    Result randomSolutionCost;
    Solution currentSolution = solution;
    Result currentCost = bestCost.clone();
    int step = (int) nbIterations / 100;
    int progress = 10;
    logger.info("First Cost = " + bestCost);
    double deltaF;
    for (int j = 0; j < 100; j++) {
        for (int i = 0; i < step; i++) {
            randomSolution = generateBetterNeighbour(currentSolution);
            randomSolutionCost = randomSolution.getCost();
            deltaF = currentCost.getCost() - randomSolutionCost.getCost();
            if (deltaF >= 0) {
                currentSolution = randomSolution;
                currentCost = randomSolutionCost;
                if (currentCost.getCost() < bestCost.getCost()) {
                    bestSolution = currentSolution;
                    bestCost = currentCost;
                }
            } else {
                Random random = new Random(System.currentTimeMillis());
                double p = random.nextDouble();
                double exp = FastMath.exp((-deltaF) / temperature);
                if (p <= exp) {
                    currentSolution = randomSolution;
                    currentCost = randomSolutionCost;
                }
            }
        }
        temperature *= mu;
        if (j % progress == 0) {
            int pourcent = j / progress;
            pourcent *= 10;
            StringBuffer stbf = new StringBuffer();
            stbf.append("CSV;").append(temperature).append(";temperature;").append(bestCost.getCost())
                    .append(";bestcost;").append(pourcent).append("%...");
            logger.info(stbf.toString());
        }
    }
    logger.info("Best Cost :" + bestCost);
    return bestSolution;
}

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From source file:org.apache.kylin.measure.percentile.PercentileCounterTest.java

@Test
public void testBasic() {
    int times = 1;
    int compression = 100;
    for (int t = 0; t < times; t++) {
        PercentileCounter counter = new PercentileCounter(compression, 0.5);
        Random random = new Random();
        int dataSize = 10000;
        List<Double> dataset = Lists.newArrayListWithCapacity(dataSize);
        for (int i = 0; i < dataSize; i++) {
            double d = random.nextDouble();
            counter.add(d);//from   w  w w.j  ava2  s  .  c  o  m
            dataset.add(d);
        }
        Collections.sort(dataset);

        double actualResult = counter.getResultEstimate();
        double expectedResult = MathUtil.findMedianInSortedList(dataset);
        assertEquals(expectedResult, actualResult, 0.001);
    }
}

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From source file:org.orekit.frames.FrameTest.java

private void checkNoTransform(Transform transform, Random random) {
    for (int i = 0; i < 100; ++i) {
        Vector3D a = new Vector3D(random.nextDouble(), random.nextDouble(), random.nextDouble());
        Vector3D b = transform.transformVector(a);
        Assert.assertEquals(0, a.subtract(b).getNorm(), 1.0e-10);
        Vector3D c = transform.transformPosition(a);
        Assert.assertEquals(0, a.subtract(c).getNorm(), 1.0e-10);
    }/*  w w  w. j ava2 s. c  o  m*/
}

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From source file:eu.amidst.core.exponentialfamily.EF_SparseDirichlet.java

/**
 * {@inheritDoc}//from   ww w  . j a v a  2  s .  com
 */
@Override
public EF_UnivariateDistribution randomInitialization(Random random) {
    for (int i = 0; i < this.nOfStates; i++) {
        this.getNaturalParameters().set(i, 5 * random.nextDouble() + 1 + 1e-5);
    }
    fixNumericalInstability();
    this.updateMomentFromNaturalParameters();

    return this;
}

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