List of usage examples for java.util Random nextDouble
public double nextDouble()
From source file:jprobix.ui.SPlotFinal.java
private static XYDataset samplexydataset2() { int cols = 20; int rows = 20; double[][] values = new double[cols][rows]; XYSeriesCollection xySeriesCollection = new XYSeriesCollection(); XYSeries series = new XYSeries("Random"); Random rand = new Random(); for (int i = 0; i < values.length; i++) { for (int j = 0; j < values.length; j++) { double x = Math.round(rand.nextDouble() * 500); double y = Math.round(rand.nextDouble() * 500); series.add(x, y);//from w ww. j av a2 s . co m } } xySeriesCollection.addSeries(series); return xySeriesCollection; }
From source file:audio.cords.old.RegressionDemo.java
private static XYSeriesCollection getTestData() { Random rg = new Random(); XYSeriesCollection data = new XYSeriesCollection(); for (int i = 1; i <= 3; i++) { XYSeries series = new XYSeries("Series " + i); double a = rg.nextDouble() - .5; int b = rg.nextInt(20) - 10; for (int j = 1; j <= 20; j++) { double x = j + (rg.nextDouble() - .5); double y = a * j + b + (rg.nextDouble() - .5) * 2; series.add(x, y);//from w w w.j a va 2 s . co m } data.addSeries(series); } return data; }
From source file:com.clust4j.TestSuite.java
public static Array2DRowRealMatrix getRandom(final int rows, final int cols) { final Random rand = new Random(); final double[][] data = new double[rows][cols]; for (int i = 0; i < rows; i++) for (int j = 0; j < cols; j++) data[i][j] = rand.nextDouble() * (rand.nextDouble() > 0.5 ? -1 : 1); return new Array2DRowRealMatrix(data, false); }
From source file:org.meteoinfo.math.RandomUtil.java
/** * Get random array - one dimension/*from w ww .j a v a 2 s . c o m*/ * * @param n Array length * @return Result array */ public static Array rand(int n) { Array r = Array.factory(DataType.DOUBLE, new int[] { n }); Random rd = new Random(); for (int i = 0; i < r.getSize(); i++) { r.setDouble(i, rd.nextDouble()); } return r; }
From source file:com.example.geomesa.kafka.KafkaLoadTester.java
public static SimpleFeature createFeature(SimpleFeatureBuilder builder, int i, String visibility) { final String[] PEOPLE_NAMES = { "James", "John", "Peter", "Hannah", "Claire", "Gabriel" }; final Random random = new Random(); Double lat = random.nextDouble() * 180 - 90; builder.reset();//from w w w . ja v a 2s . co m builder.add(PEOPLE_NAMES[i % PEOPLE_NAMES.length]); // name builder.add((int) Math.round(random.nextDouble() * 110)); // age builder.add(random.nextDouble()); builder.add(lat); builder.add(new Date()); // dtg builder.add(WKTUtils$.MODULE$.read("POINT(" + -180.0 + " " + lat + ")")); // geom SimpleFeature feat = builder.buildFeature(Integer.toString(i)); if (visibility != null) { feat.getUserData().put("geomesa.feature.visibility", visibility); } return feat; }
From source file:org.deeplearning4j.examples.recurrent.character.LSTMCharModellingExample.java
/** Given a probability distribution over discrete classes, sample from the distribution * and return the generated class index. * @param distribution Probability distribution over classes. Must sum to 1.0 *//*www . j a v a 2 s. c o m*/ public static int sampleFromDistribution(double[] distribution, Random rng) { double d = 0.0; double sum = 0.0; for (int t = 0; t < 10; t++) { d = rng.nextDouble(); sum = 0.0; for (int i = 0; i < distribution.length; i++) { sum += distribution[i]; if (d <= sum) return i; } //If we haven't found the right index yet, maybe the sum is slightly //lower than 1 due to rounding error, so try again. } //Should be extremely unlikely to happen if distribution is a valid probability distribution throw new IllegalArgumentException("Distribution is invalid? d=" + d + ", sum=" + sum); }
From source file:org.matsim.contrib.parking.parkingsearch.ParkingUtils.java
public static Coord getRandomPointAlongLink(Random rnd, Link link) { Coord fromNodeCoord = link.getFromNode().getCoord(); Coord toNodeCoord = link.getToNode().getCoord(); double r = rnd.nextDouble(); double x = (fromNodeCoord.getX() * r) + (toNodeCoord.getX() * (1 - r)); double y = (fromNodeCoord.getY() * r) + (toNodeCoord.getY() * (1 - r)); return new Coord(x, y); }
From source file:org.meteoinfo.math.RandomUtil.java
/** * Get random array/*from w w w .j a v a2 s . com*/ * * @param shape Shape * @return Array Result array */ public static Array rand(List<Integer> shape) { int[] ashape = new int[shape.size()]; for (int i = 0; i < shape.size(); i++) { ashape[i] = shape.get(i); } Array a = Array.factory(DataType.DOUBLE, ashape); Random rd = new Random(); for (int i = 0; i < a.getSize(); i++) { a.setDouble(i, rd.nextDouble()); } return a; }
From source file:edu.berkeley.sparrow.examples.BackendBenchmarkProfiler.java
/** * This generates an arrival delay according to an exponential distribution with * average 1\{@code lambda}. Generating arrival delays from such a distribution creates * a Poission process with an average arrival rate of {@code lambda} events per second. *//*from w w w.j av a 2 s .co m*/ public static double generateInterarrivalDelay(Random r, double lambda) { double u = r.nextDouble(); return -Math.log(u) / lambda; }
From source file:org.apache.metron.statistics.sampling.UniformSamplerTest.java
@BeforeClass public static void beforeClass() { Random rng = new Random(0); GaussianRandomGenerator gen = new GaussianRandomGenerator(new MersenneTwister(0)); for (int i = 0; i < SAMPLE_SIZE; ++i) { double us = 10 * rng.nextDouble(); uniformSample.add(us);//from w w w. j av a 2 s .c o m uniformStats.addValue(us); double gs = 10 * gen.nextNormalizedDouble(); gaussianSample.add(gs); gaussianStats.addValue(gs); } }