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.latticesoft.util.common.NumeralUtil.java

/**
 * Generates next random double/* w  w  w.  j a va2 s . c o  m*/
 * @param start
 * @return the generated double
 */
public static double getRandomDouble(double start, double end) {
    Random rand = new Random(System.currentTimeMillis());
    double d = rand.nextDouble();
    if (end > start) {
        d = d * (end - start) + start;
    }
    return d;
}

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From source file:org.broad.igv.gwas.GWASParser.java

public static void generateUnsortedGWASData() throws Exception {
    Random random = new Random(12345);
    int numFeats = 100;
    String headerLine = StringUtils.join(new String[] { "Chr", "bp", "p", "snp" }, "\t");

    PrintWriter writer = new PrintWriter("random.gwas");
    writer.println(headerLine);/*from  w ww.ja  va2  s  . co  m*/
    for (int ii = 0; ii < numFeats; ii++) {
        String chr = String.format("chr%d", random.nextInt(20));
        String location = String.format("%d", random.nextInt(Integer.MAX_VALUE));
        String pVal = String.format("%2.8f", random.nextDouble() / 1000.0d);
        String rsID = String.format("rs%d", random.nextInt(100000));

        String line = StringUtils.join(new String[] { chr, location, pVal, rsID }, "\t");

        writer.println(line);
    }

    writer.flush();
    writer.close();

}

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From source file:org.apache.mahout.clustering.lda.LDADriver.java

private static void writeInitialState(Path statePath, int numTopics, int numWords) throws IOException {
    Configuration job = new Configuration();
    FileSystem fs = statePath.getFileSystem(job);

    DoubleWritable v = new DoubleWritable();

    Random random = RandomUtils.getRandom();

    for (int k = 0; k < numTopics; ++k) {
        Path path = new Path(statePath, "part-" + k);
        SequenceFile.Writer writer = new SequenceFile.Writer(fs, job, path, IntPairWritable.class,
                DoubleWritable.class);

        double total = 0.0; // total number of pseudo counts we made
        for (int w = 0; w < numWords; ++w) {
            IntPairWritable kw = new IntPairWritable(k, w);
            // A small amount of random noise, minimized by having a floor.
            double pseudocount = random.nextDouble() + 1.0E-8;
            total += pseudocount;/*from w  w  w.  java  2 s  .c o  m*/
            v.set(Math.log(pseudocount));
            writer.append(kw, v);
        }
        IntPairWritable kTsk = new IntPairWritable(k, TOPIC_SUM_KEY);
        v.set(Math.log(total));
        writer.append(kTsk, v);

        writer.close();
    }
}

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From source file:org.brekka.stillingar.example.FieldTypesDOMTest.java

private static Testing writeConfig() {
    Random r = new Random();
    ConfigurationDocument doc = ConfigurationDocument.Factory.newInstance();
    Configuration newConfiguration = doc.addNewConfiguration();
    FeatureFlagType featureFlag = newConfiguration.addNewFeatureFlag();
    featureFlag.setKey("turbo");
    featureFlag.setBooleanValue(true);//w  w w  .ja v  a  2s  . co  m
    Testing testing = newConfiguration.addNewTesting();
    testing.setAnyURI("http://brekka.org/" + RandomStringUtils.randomAlphanumeric(10));
    testing.setBoolean(r.nextBoolean());
    testing.setByte((byte) r.nextInt());
    Calendar cal = Calendar.getInstance();
    testing.setDate(cal);
    testing.setDateTime(cal);
    testing.setDecimal(BigDecimal.valueOf(r.nextDouble()));
    testing.setDouble(r.nextDouble());
    testing.setFloat(r.nextFloat());
    testing.setInt(r.nextInt());
    testing.setInteger(BigInteger.valueOf(r.nextLong()));
    testing.setLanguage("en");
    testing.setLong(r.nextLong());
    testing.setShort((short) r.nextInt());
    testing.setString(RandomStringUtils.randomAlphanumeric(24));
    testing.setTime(cal);
    testing.setUUID(UUID.randomUUID().toString());
    testing.setPeriod(new GDuration("P5Y2M10DT15H"));
    byte[] binary = new byte[32];
    r.nextBytes(binary);
    testing.setBinary(binary);
    TestSupport.write(doc);
    return testing;
}

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From source file:isl.FIMS.utils.Utils.java

public static String generateRandomPassword() {
    // Pick from some letters that won't be easily mistaken for each
    // other. So, for example, omit o O and 0, 1 l and L.
    String letters = "abcdefghjkmnpqrstuvwxyzABCDEFGHJKMNPQRSTUVWXYZ23456789+@";

    String pw = "";
    for (int i = 0; i < PASSWORD_LENGTH; i++) {
        Random r = new Random();

        int index = (int) (r.nextDouble() * letters.length());
        pw += letters.substring(index, index + 1);
    }//from w  ww .  j a v  a 2s .c  o  m
    return pw;
}

---

From source file:org.locationtech.geomesa.examples.KafkaQuickStart.java

public static void addSimpleFeatures(SimpleFeatureType sft, FeatureStore producerFS)
        throws InterruptedException, IOException {
    final int MIN_X = -180;
    final int MAX_X = 180;
    final int MIN_Y = -90;
    final int MAX_Y = 90;
    final int DX = 2;
    final int DY = 1;
    final String[] PEOPLE_NAMES = { "James", "John", "Peter", "Hannah", "Claire", "Gabriel" };
    final long SECONDS_PER_YEAR = 365L * 24L * 60L * 60L;
    final Random random = new Random();
    final DateTime MIN_DATE = new DateTime(2015, 1, 1, 0, 0, 0, DateTimeZone.forID("UTC"));

    SimpleFeatureBuilder builder = new SimpleFeatureBuilder(sft);
    DefaultFeatureCollection featureCollection = new DefaultFeatureCollection();

    // creates and updates two SimpleFeatures.
    // the first time this for loop runs the two SimpleFeatures are created.
    // in the subsequent iterations of the for loop, the two SimpleFeatures are updated.
    int numFeatures = (MAX_X - MIN_X) / DX;
    for (int i = 1; i <= numFeatures; i++) {
        builder.add(PEOPLE_NAMES[i % PEOPLE_NAMES.length]); // name
        builder.add((int) Math.round(random.nextDouble() * 110)); // age
        builder.add(MIN_DATE.plusSeconds((int) Math.round(random.nextDouble() * SECONDS_PER_YEAR)).toDate()); // dtg
        builder.add(WKTUtils$.MODULE$.read("POINT(" + (MIN_X + DX * i) + " " + (MIN_Y + DY * i) + ")")); // geom
        SimpleFeature feature1 = builder.buildFeature("1");

        builder.add(PEOPLE_NAMES[(i + 1) % PEOPLE_NAMES.length]); // name
        builder.add((int) Math.round(random.nextDouble() * 110)); // age
        builder.add(MIN_DATE.plusSeconds((int) Math.round(random.nextDouble() * SECONDS_PER_YEAR)).toDate()); // dtg
        builder.add(WKTUtils$.MODULE$.read("POINT(" + (MIN_X + DX * i) + " " + (MAX_Y - DY * i) + ")")); // geom
        SimpleFeature feature2 = builder.buildFeature("2");

        // write the SimpleFeatures to Kafka
        featureCollection.add(feature1);
        featureCollection.add(feature2);
        producerFS.addFeatures(featureCollection);
        featureCollection.clear();/*from  www.jav a  2  s.c o m*/

        // wait 200 ms in between updating SimpleFeatures to simulate a stream of data
        Thread.sleep(200);
    }
}

---

From source file:com.asakusafw.runtime.stage.input.DefaultSplitCombiner.java

private static void initializeGene(Environment env, Gene gene) {
    assert env != null;
    assert gene != null;
    Random random = env.random;
    int[] schema = gene.schema;
    for (int i = 0; i < schema.length; i++) {
        if (random.nextDouble() < env.locality) {
            schema[i] = env.getRandomLocalSlot(env.splits[i]);
        } else {// www  .  ja  v a2s .c o m
            schema[i] = env.getRandomSlot();
        }
        assert 0 <= schema[i] && schema[i] < env.slots.length;
    }
    gene.eval();
}

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From source file:lirmm.inria.fr.math.BigSparseRealMatrix.java

/**
 * Generate a sparse matrix of random values.
 *
 * @param rowDimension Number of rows of the matrix.
 * @param columnDimension Number of columns of the matrix.
 * @param sparsity Percentage of data in the matrix.
 * @return An instance of BigSparseRealMatrix.
 *///from  w w w. j a va2  s  . c  o  m
public static BigSparseRealMatrix randomGenerateMatrix(int rowDimension, int columnDimension, double sparsity) {
    BigSparseRealMatrix m = new BigSparseRealMatrix(rowDimension, columnDimension);
    long lrow = (long) rowDimension;
    long lcolumn = (long) columnDimension;
    long total = (long) (lrow * lcolumn * sparsity / 100);
    Random r = new Random();
    for (long i = 0; i < total; i++) {
        int row = r.nextInt(rowDimension);
        int col = r.nextInt(columnDimension);
        while (m.getEntry(row, col) != 0) {
            row = r.nextInt(rowDimension);
            col = r.nextInt(columnDimension);
        }
        m.setEntry(row, col, r.nextDouble());
    }
    return m;
}

---

From source file:com.example.geomesa.kafka.KafkaQuickStart.java

public static void addSimpleFeatures(SimpleFeatureType sft, FeatureStore producerFS, String visibility)
        throws InterruptedException, IOException {
    final int MIN_X = -180;
    final int MAX_X = 180;
    final int MIN_Y = -90;
    final int MAX_Y = 90;
    final int DX = 2;
    final int DY = 1;
    final String[] PEOPLE_NAMES = { "James", "John", "Peter", "Hannah", "Claire", "Gabriel" };
    final long SECONDS_PER_YEAR = 365L * 24L * 60L * 60L;
    final Random random = new Random();
    final ZonedDateTime MIN_DATE = ZonedDateTime.of(2015, 1, 1, 0, 0, 0, 0, ZoneOffset.UTC);

    SimpleFeatureBuilder builder = new SimpleFeatureBuilder(sft);
    DefaultFeatureCollection featureCollection = new DefaultFeatureCollection();

    // creates and updates two SimpleFeatures.
    // the first time this for loop runs the two SimpleFeatures are created.
    // in the subsequent iterations of the for loop, the two SimpleFeatures are updated.
    int numFeatures = (MAX_X - MIN_X) / DX;
    for (int i = 1; i <= numFeatures; i++) {
        builder.add(PEOPLE_NAMES[i % PEOPLE_NAMES.length]); // name
        builder.add((int) Math.round(random.nextDouble() * 110)); // age
        builder.add(Date.from(//  ww w  . java 2s .c  om
                MIN_DATE.plusSeconds((int) Math.round(random.nextDouble() * SECONDS_PER_YEAR)).toInstant())); // dtg
        builder.add(WKTUtils$.MODULE$.read("POINT(" + (MIN_X + DX * i) + " " + (MIN_Y + DY * i) + ")")); // geom
        SimpleFeature feature1 = builder.buildFeature("1");
        feature1.getUserData().put(Hints.USE_PROVIDED_FID, Boolean.TRUE);

        builder.add(PEOPLE_NAMES[(i + 1) % PEOPLE_NAMES.length]); // name
        builder.add((int) Math.round(random.nextDouble() * 110)); // age
        builder.add(Date.from(
                MIN_DATE.plusSeconds((int) Math.round(random.nextDouble() * SECONDS_PER_YEAR)).toInstant())); // dtg
        builder.add(WKTUtils$.MODULE$.read("POINT(" + (MIN_X + DX * i) + " " + (MAX_Y - DY * i) + ")")); // geom
        SimpleFeature feature2 = builder.buildFeature("2");
        feature2.getUserData().put(Hints.USE_PROVIDED_FID, Boolean.TRUE);

        if (visibility != null) {
            feature1.getUserData().put("geomesa.feature.visibility", visibility);
            feature2.getUserData().put("geomesa.feature.visibility", visibility);
        }

        // write the SimpleFeatures to Kafka
        featureCollection.add(feature1);
        featureCollection.add(feature2);
        producerFS.addFeatures(featureCollection);
        featureCollection.clear();

        // wait 100 ms in between updating SimpleFeatures to simulate a stream of data
        Thread.sleep(100);
    }
}

---

From source file:com.example.geomesa.kafka08.KafkaQuickStart.java

public static void addSimpleFeatures(SimpleFeatureType sft, FeatureStore producerFS, String visibility)
        throws InterruptedException, IOException {
    final int MIN_X = -180;
    final int MAX_X = 180;
    final int MIN_Y = -90;
    final int MAX_Y = 90;
    final int DX = 2;
    final int DY = 1;
    final String[] PEOPLE_NAMES = { "James", "John", "Peter", "Hannah", "Claire", "Gabriel" };
    final long SECONDS_PER_YEAR = 365L * 24L * 60L * 60L;
    final Random random = new Random();
    final DateTime MIN_DATE = new DateTime(2015, 1, 1, 0, 0, 0, DateTimeZone.forID("UTC"));

    SimpleFeatureBuilder builder = new SimpleFeatureBuilder(sft);
    DefaultFeatureCollection featureCollection = new DefaultFeatureCollection();

    // creates and updates two SimpleFeatures.
    // the first time this for loop runs the two SimpleFeatures are created.
    // in the subsequent iterations of the for loop, the two SimpleFeatures are updated.
    int numFeatures = (MAX_X - MIN_X) / DX;
    for (int i = 1; i <= numFeatures; i++) {
        builder.add(PEOPLE_NAMES[i % PEOPLE_NAMES.length]); // name
        builder.add((int) Math.round(random.nextDouble() * 110)); // age
        builder.add(MIN_DATE.plusSeconds((int) Math.round(random.nextDouble() * SECONDS_PER_YEAR)).toDate()); // dtg
        builder.add(WKTUtils$.MODULE$.read("POINT(" + (MIN_X + DX * i) + " " + (MIN_Y + DY * i) + ")")); // geom
        SimpleFeature feature1 = builder.buildFeature("1");

        builder.add(PEOPLE_NAMES[(i + 1) % PEOPLE_NAMES.length]); // name
        builder.add((int) Math.round(random.nextDouble() * 110)); // age
        builder.add(MIN_DATE.plusSeconds((int) Math.round(random.nextDouble() * SECONDS_PER_YEAR)).toDate()); // dtg
        builder.add(WKTUtils$.MODULE$.read("POINT(" + (MIN_X + DX * i) + " " + (MAX_Y - DY * i) + ")")); // geom
        SimpleFeature feature2 = builder.buildFeature("2");

        if (visibility != null) {
            feature1.getUserData().put("geomesa.feature.visibility", visibility);
            feature2.getUserData().put("geomesa.feature.visibility", visibility);
        }//from   w  w  w  .  j a va  2  s. c  om

        // write the SimpleFeatures to Kafka
        featureCollection.add(feature1);
        featureCollection.add(feature2);
        producerFS.addFeatures(featureCollection);
        featureCollection.clear();

        // wait 100 ms in between updating SimpleFeatures to simulate a stream of data
        Thread.sleep(100);
    }
}

---

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