List of usage examples for java.util Random nextDouble
public double nextDouble()
From source file:com.mapr.synth.drive.Producer.java
@Override public void run() { Random rand = new Random(3); GeoPoint start = new GeoPoint((rand.nextDouble() - 0.5) * Math.PI / 2, rand.nextDouble() * Math.PI * 2); final Vector3D east = start.east(); final Vector3D north = start.north(east); GeoPoint end = new GeoPoint(start.as3D().add(east.scalarMultiply(-12.0 / Constants.EARTH_RADIUS_KM)) .add(north.scalarMultiply(7.0 / Constants.EARTH_RADIUS_KM))); Vector3D zz = project(east, north, end.as3D()); System.out.printf("==> %.2f %.2f\n", zz.getX(), zz.getY()); while (true) { double t = 0; final Car car = new Car(); System.out.printf("%.2f\n", start.distance(end)); car.driveTo(rand, t, start, end, new Car.Callback() { @Override//from w w w.j av a2s. c om void call(double t, Engine eng, GeoPoint position) { final Vector3D here = project(east, north, position.as3D()); try { output.put(new Trails.State(new Engine(eng), here)); } catch (InterruptedException e) { throw new RuntimeException("Interrupted", e); } } }); } }
From source file:org.owasp.benchmark.testcode.BenchmarkTest01699.java
double getNextNumber(java.util.Random generator) { return generator.nextDouble(); }
From source file:edu.umass.cs.gigapaxos.testing.TESTPaxosConfig.java
/** * Sets consistent, random groups starting with the same random seed. * /*from w w w . j av a 2 s .c om*/ * @param numGroups */ public static void setRandomGroups(int numGroups) { // if(!getCleanDB()) return; Random r = new Random(RANDOM_SEED); for (int i = 0; i < Math.min(Config.getGlobalInt(TC.PRE_CONFIGURED_GROUPS), numGroups); i++) { groups.put(Config.getGlobalString(TC.TEST_GUID_PREFIX) + i, defaultGroup); if (i == 0) continue;// first group is always default group TreeSet<Integer> members = new TreeSet<Integer>(); for (int id : TESTPaxosConfig.getNodes()) { if (r.nextDouble() > Config.getGlobalDouble(TC.NODE_INCLUSION_PROB)) { members.add(id); } } TESTPaxosConfig.setGroup(TESTPaxosConfig.getGroupName(i), members); } }
From source file:de.terministic.serein.core.genome.recombination.UniformCrossover.java
@SuppressWarnings({ "rawtypes", "unchecked" })
@Override/* w w w . j a v a2 s .com*/
G recombine(G g1, G g2, Random random) {
List result = new ArrayList();
for (int i = 0; i < g1.size(); i++) {
if (random.nextDouble() < dominance) {
result.add(g1.getGenes().get(i));
} else {
result.add(g2.getGenes().get(i));
}
}
return (G) g1.createInstance(result);
}
From source file:org.orcid.core.manager.impl.OrcidGenerationManagerImpl.java
private long getRandomNumber() { Random random = new Random(); // XXX Need to test edge cases return (long) (ORCID_BASE_MIN + (random.nextDouble() * (ORCID_BASE_MAX - ORCID_BASE_MIN + 1))); }
From source file:br.upe.ecomp.doss.algorithm.pso.PSOParticle.java
/** * Updates the current velocity of the particle. * //from w w w . ja va 2 s .com * @param inertialWeight The inertia weight * @param bestParticleNeighborhood The best particle in the neighborhood * @param c1 The cognitive component * @param c2 The social component * @param problem The problem that we are trying to solve. */ public void updateVelocity(double inertialWeight, double[] bestParticleNeighborhood, double c1, double c2, Problem problem) { Random random = new Random(); double r1 = random.nextDouble(); double r2 = random.nextDouble(); double[] pBest = getBestPosition(); for (int i = 0; i < getDimensions(); i++) { velocity[i] = inertialWeight * velocity[i] + c1 * r1 * (pBest[i] - getCurrentPosition()[i]) + c2 * r2 * (bestParticleNeighborhood[i] - getCurrentPosition()[i]); double maxVelocity = (problem.getUpperBound(i) - problem.getLowerBound(i)) * velocityClampingPercent; velocity[i] = (velocity[i] > maxVelocity) ? maxVelocity : velocity[i]; velocity[i] = (velocity[i] < -maxVelocity) ? -maxVelocity : velocity[i]; } }
From source file:br.upe.ecomp.doss.algorithm.chargedpso.ChargedPSOParticle.java
/** * Updates the current velocity of the particle. * //w w w.ja v a2 s . c o m * @param inertialWeight The inertia weight * @param bestParticleNeighborhood The best particle in the neighborhood * @param c1 The cognitive component * @param c2 The social component */ public void updateVelocity(double inertialWeight, double[] bestParticleNeighborhood, double c1, double c2, double[] acceleration) { Random random = new Random(); double r1 = random.nextDouble(); double r2 = random.nextDouble(); double[] velocity = getVelocity(); double[] pBest = getBestPosition(); for (int i = 0; i < getDimensions(); i++) { velocity[i] = inertialWeight * velocity[i] + c1 * r1 * (pBest[i] - getCurrentPosition()[i]) + c2 * r2 * (bestParticleNeighborhood[i] - getCurrentPosition()[i]) + acceleration[i]; } setVelocity(velocity); }
From source file:com.facebook.presto.operator.aggregation.TestBootstrappedAggregation.java
@Test public void testSum() throws Exception { int sum = 1_000; PageBuilder builder = new PageBuilder(ImmutableList.of(BIGINT, BIGINT)); Random rand = new Random(0); for (int i = 0; i < sum; i++) { if (rand.nextDouble() < 0.5) { builder.getBlockBuilder(0).appendLong(1); builder.getBlockBuilder(1).appendLong(2); }/*from w w w . jav a2 s. c o m*/ } AggregationFunction function = new DeterministicBootstrappedAggregation(createTestingBlockEncodingManager(), LONG_SUM); assertApproximateAggregation(function, 1, 0.99, (double) sum, builder.build()); }
From source file:ro.hasna.ts.math.ml.distance.SaxEuclideanDistanceTest.java
@Test public void testEquality() throws Exception { int n = 128;//from ww w. j a v a2s . c o m double a[] = new double[n]; double b[] = new double[n]; Random random = new Random(); for (int i = 0; i < n; i++) { a[i] = i; b[i] = 100 + i + random.nextDouble(); } double result = distance.compute(sax.transform(a), sax.transform(b)); Assert.assertEquals(0, result, TimeSeriesPrecision.EPSILON); }
From source file:ar.org.neuroph.core.Weight.java
public void randomize(Random generator) { this.value = generator.nextDouble(); }