Example usage for java.util Random nextDouble

List of usage examples for java.util Random nextDouble

  1. HOME
  2. Java
  3. java
  4. java.util.*
  5. Random
  6. 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.storage.hbase.util.HbaseStreamingInput.java

public static void randomScan(String tableName) throws IOException {

    final Semaphore semaphore = new Semaphore(0);
    new Thread(new Runnable() {
        @Override//w  ww  .  j  a  v  a  2  s . c o  m
        public void run() {
            scheduleJob(semaphore, 60000);//1 minutes a batch
        }
    }).start();

    while (true) {
        try {
            semaphore.acquire();
            int waiting = semaphore.drainPermits();
            if (waiting > 0) {
                logger.warn("Too many queries to handle! Blocking " + waiting + " sets of scan requests");
            }
        } catch (InterruptedException e) {
            Thread.currentThread().interrupt();
            e.printStackTrace();
        }

        Random r = new Random();
        Connection conn = getConnection();
        Table table = conn.getTable(TableName.valueOf(tableName));

        long leftBound = getFirstKeyTime(table);
        long rightBound = System.currentTimeMillis();

        for (int t = 0; t < 5; ++t) {
            long start = (long) (leftBound + r.nextDouble() * (rightBound - leftBound));
            long end = start + 600000;//a period of 10 minutes
            logger.info("A scan from " + formatTime(start) + " to " + formatTime(end));

            Scan scan = new Scan();
            scan.setStartRow(Bytes.toBytes(start));
            scan.setStopRow(Bytes.toBytes(end));
            scan.addFamily(CF);
            ResultScanner scanner = table.getScanner(scan);
            long hash = 0;
            int rowCount = 0;
            for (Result result : scanner) {
                Cell cell = result.getColumnLatestCell(CF, QN);
                byte[] value = cell.getValueArray();
                if (cell.getValueLength() != CELL_SIZE) {
                    logger.error("value size invalid!!!!!");
                }

                hash += Arrays.hashCode(Arrays.copyOfRange(value, cell.getValueOffset(),
                        cell.getValueLength() + cell.getValueOffset()));
                rowCount++;
            }
            scanner.close();
            logger.info("Scanned " + rowCount + " rows, the (meaningless) hash for the scan is " + hash);
        }
        table.close();
        conn.close();
    }
}

From source file:org.deeplearning4j.examples.multigpu.video.VideoGenerator.java

private static int[] generateVideo(String path, int nFrames, int width, int height, int numShapes, Random r,
        boolean backgroundNoise, int numDistractorsPerFrame) throws Exception {

    //First: decide where transitions between one shape and another are
    double[] rns = new double[numShapes];
    double sum = 0;
    for (int i = 0; i < numShapes; i++) {
        rns[i] = r.nextDouble();
        sum += rns[i];//from   w  w  w  .j a va2 s  .  c  o m
    }
    for (int i = 0; i < numShapes; i++)
        rns[i] /= sum;

    int[] startFrames = new int[numShapes];
    startFrames[0] = 0;
    for (int i = 1; i < numShapes; i++) {
        startFrames[i] = (int) (startFrames[i - 1] + MIN_FRAMES + rns[i] * (nFrames - numShapes * MIN_FRAMES));
    }

    //Randomly generate shape positions, velocities, colors, and type
    int[] shapeTypes = new int[numShapes];
    int[] initialX = new int[numShapes];
    int[] initialY = new int[numShapes];
    double[] velocityX = new double[numShapes];
    double[] velocityY = new double[numShapes];
    Color[] color = new Color[numShapes];
    for (int i = 0; i < numShapes; i++) {
        shapeTypes[i] = r.nextInt(NUM_SHAPES);
        initialX[i] = SHAPE_MIN_DIST_FROM_EDGE + r.nextInt(width - SHAPE_SIZE - 2 * SHAPE_MIN_DIST_FROM_EDGE);
        initialY[i] = SHAPE_MIN_DIST_FROM_EDGE + r.nextInt(height - SHAPE_SIZE - 2 * SHAPE_MIN_DIST_FROM_EDGE);
        velocityX[i] = -1 + 2 * r.nextDouble();
        velocityY[i] = -1 + 2 * r.nextDouble();
        color[i] = new Color(r.nextFloat(), r.nextFloat(), r.nextFloat());
    }

    //Generate a sequence of BufferedImages with the given shapes, and write them to the video
    SequenceEncoder enc = new SequenceEncoder(new File(path));
    int currShape = 0;
    int[] labels = new int[nFrames];
    for (int i = 0; i < nFrames; i++) {
        if (currShape < numShapes - 1 && i >= startFrames[currShape + 1])
            currShape++;

        BufferedImage bi = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);
        Graphics2D g2d = bi.createGraphics();
        g2d.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON);
        g2d.setBackground(Color.BLACK);

        if (backgroundNoise) {
            for (int x = 0; x < width; x++) {
                for (int y = 0; y < height; y++) {
                    bi.setRGB(x, y, new Color(r.nextFloat() * MAX_NOISE_VALUE, r.nextFloat() * MAX_NOISE_VALUE,
                            r.nextFloat() * MAX_NOISE_VALUE).getRGB());
                }
            }
        }

        g2d.setColor(color[currShape]);

        //Position of shape this frame
        int currX = (int) (initialX[currShape]
                + (i - startFrames[currShape]) * velocityX[currShape] * MAX_VELOCITY);
        int currY = (int) (initialY[currShape]
                + (i - startFrames[currShape]) * velocityY[currShape] * MAX_VELOCITY);

        //Render the shape
        switch (shapeTypes[currShape]) {
        case 0:
            //Circle
            g2d.fill(new Ellipse2D.Double(currX, currY, SHAPE_SIZE, SHAPE_SIZE));
            break;
        case 1:
            //Square
            g2d.fill(new Rectangle2D.Double(currX, currY, SHAPE_SIZE, SHAPE_SIZE));
            break;
        case 2:
            //Arc
            g2d.fill(new Arc2D.Double(currX, currY, SHAPE_SIZE, SHAPE_SIZE, 315, 225, Arc2D.PIE));
            break;
        case 3:
            //Line
            g2d.setStroke(lineStroke);
            g2d.draw(new Line2D.Double(currX, currY, currX + SHAPE_SIZE, currY + SHAPE_SIZE));
            break;
        default:
            throw new RuntimeException();
        }

        //Add some distractor shapes, which are present for one frame only
        for (int j = 0; j < numDistractorsPerFrame; j++) {
            int distractorShapeIdx = r.nextInt(NUM_SHAPES);

            int distractorX = DISTRACTOR_MIN_DIST_FROM_EDGE + r.nextInt(width - SHAPE_SIZE);
            int distractorY = DISTRACTOR_MIN_DIST_FROM_EDGE + r.nextInt(height - SHAPE_SIZE);

            g2d.setColor(new Color(r.nextFloat(), r.nextFloat(), r.nextFloat()));

            switch (distractorShapeIdx) {
            case 0:
                g2d.fill(new Ellipse2D.Double(distractorX, distractorY, SHAPE_SIZE, SHAPE_SIZE));
                break;
            case 1:
                g2d.fill(new Rectangle2D.Double(distractorX, distractorY, SHAPE_SIZE, SHAPE_SIZE));
                break;
            case 2:
                g2d.fill(new Arc2D.Double(distractorX, distractorY, SHAPE_SIZE, SHAPE_SIZE, 315, 225,
                        Arc2D.PIE));
                break;
            case 3:
                g2d.setStroke(lineStroke);
                g2d.draw(new Line2D.Double(distractorX, distractorY, distractorX + SHAPE_SIZE,
                        distractorY + SHAPE_SIZE));
                break;
            default:
                throw new RuntimeException();
            }
        }

        enc.encodeImage(bi);
        g2d.dispose();
        labels[i] = shapeTypes[currShape];
    }
    enc.finish(); //write .mp4

    return labels;
}

From source file:org.apache.hyracks.storage.am.btree.OrderedIndexTestUtils.java

public static String getRandomString(int length, Random rnd) {
    String s = Long.toHexString(Double.doubleToLongBits(rnd.nextDouble()));
    StringBuilder strBuilder = new StringBuilder();
    for (int i = 0; i < s.length() && i < length; i++) {
        strBuilder.append(s.charAt(Math.abs(rnd.nextInt()) % s.length()));
    }/*from w  ww  .ja  v  a 2  s  .  c o m*/
    return strBuilder.toString();
}

From source file:org.apache.mahout.classifier.df.data.Utils.java

/**
 * generates a random vector based on the given attributes.<br>
 * the attributes' values are generated as follows :<br>
 * <ul>/*from   w w  w . j  a  va  2s  . c om*/
 * <li>each IGNORED attribute receives a Double.NaN</li>
 * <li>each NUMERICAL attribute receives a random double</li>
 * <li>each CATEGORICAL and LABEL attribute receives a random integer in the
 * range [0, CATEGORICAL_RANGE[</li>
 * </ul>
 * 
 * @param attrs attributes description
 */
private static double[] randomVector(Random rng, Attribute[] attrs, boolean regression) {
    double[] vector = new double[attrs.length];

    for (int attr = 0; attr < attrs.length; attr++) {
        if (attrs[attr].isIgnored()) {
            vector[attr] = Double.NaN;
        } else if (attrs[attr].isNumerical()) {
            vector[attr] = rng.nextDouble();
        } else if (attrs[attr].isCategorical()) {
            vector[attr] = rng.nextInt(CATEGORICAL_RANGE);
        } else { // LABEL
            if (regression) {
                vector[attr] = rng.nextDouble();
            } else {
                vector[attr] = rng.nextInt(CATEGORICAL_RANGE);
            }
        }
    }

    return vector;
}

From source file:enterprayz.megatools.Tools.java

public static int getRandomInteger(int aStart, int aEnd, Random aRandom) {
    if (aStart > aEnd) {
        throw new IllegalArgumentException("Start cannot exceed End.");
    }//  w  w  w  .java  2  s .  c  o  m
    //get the range, casting to long to avoid overflow problems
    long range = (long) aEnd - (long) aStart + 1;
    // compute a fraction of the range, 0 <= frac < range
    long fraction = (long) (range * aRandom.nextDouble());
    return (int) (fraction + aStart);
}

From source file:edu.iu.kmeans.regroupallgather.KMUtil.java

/**
 * Generate centroids and upload to the cDir
 * /*  w w w .jav  a  2 s . c om*/
 * @param numCentroids
 * @param vectorSize
 * @param configuration
 * @param random
 * @param cenDir
 * @param fs
 * @throws IOException
 */
static void generateCentroids(int numCentroids, int vectorSize, Configuration configuration, Path cenDir,
        FileSystem fs) throws IOException {
    Random random = new Random();
    double[] data = null;
    if (fs.exists(cenDir))
        fs.delete(cenDir, true);
    if (!fs.mkdirs(cenDir)) {
        throw new IOException("Mkdirs failed to create " + cenDir.toString());
    }
    data = new double[numCentroids * vectorSize];
    for (int i = 0; i < data.length; i++) {
        // data[i] = 1000;
        data[i] = random.nextDouble() * 1000;
    }
    Path initClustersFile = new Path(cenDir, Constants.CENTROID_FILE_NAME);
    System.out.println("Generate centroid data." + initClustersFile.toString());
    FSDataOutputStream out = fs.create(initClustersFile, true);
    BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(out));
    for (int i = 0; i < data.length; i++) {
        if ((i % vectorSize) == (vectorSize - 1)) {
            bw.write(data[i] + "");
            bw.newLine();
        } else {
            bw.write(data[i] + " ");
        }
    }
    bw.flush();
    bw.close();
    System.out.println("Wrote centroids data to file");
}

From source file:com.mapr.synth.drive.Car.java

/**
 * Chooses whether to plan a "highway" or "local" segment based on the distance to be traveled.
 *
 * @return True if this should be a highway segment.
 *//*  w  ww . j a  va  2 s .c o m*/
private static boolean pickHighway(double distance, Random rand) {
    // formula was picked heuristically to fit intuition
    // d(km) p
    //   1  0.002472623
    //   2  0.013828044
    //   5  0.121702566
    //   10  0.439414832
    //   20  0.815977791
    //   50  0.977687816
    //   100  0.995981922

    double logOdds = -6 + 2 * log(distance);
    double u = rand.nextDouble();
    return log(u / (1 - u)) < logOdds;
}

From source file:edu.iu.daal_kmeans.regroupallgather.KMUtil.java

/**
 * Generate centroids and upload to the cDir
 * /*from  w ww  .  ja  v  a 2 s . co  m*/
 * @param numCentroids
 * @param vectorSize
 * @param configuration
 * @param random
 * @param cenDir
 * @param fs
 * @throws IOException
 */
static void generateCentroids(int numCentroids, int vectorSize, Configuration configuration, Path cenDir,
        FileSystem fs) throws IOException {
    Random random = new Random();
    double[] data = null;
    if (fs.exists(cenDir))
        fs.delete(cenDir, true);
    if (!fs.mkdirs(cenDir)) {
        throw new IOException("Mkdirs failed to create " + cenDir.toString());
    }
    data = new double[numCentroids * vectorSize];
    for (int i = 0; i < data.length; i++) {
        data[i] = random.nextDouble() * 1000;
    }
    Path initClustersFile = new Path(cenDir, Constants.CENTROID_FILE_NAME);
    System.out.println("Generate centroid data." + initClustersFile.toString());
    FSDataOutputStream out = fs.create(initClustersFile, true);
    BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(out));
    for (int i = 0; i < data.length; i++) {
        if ((i % vectorSize) == (vectorSize - 1)) {
            bw.write(data[i] + "");
            bw.newLine();
        } else {
            bw.write(data[i] + " ");
        }
    }
    bw.flush();
    bw.close();
    System.out.println("Wrote centroids data to file");
}

From source file:net.sf.javaml.tools.DatasetTools.java

/**
 * Creates a random instance using the//from   w  ww  .  ja v  a 2 s.  c o  m
 * {@link DatasetTools#getMinMax(Dataset)} method. The random instance is
 * created by choosing a random value for each attribute (which is between
 * the min and max value of the attribute).
 * 
 * @param data
 *            the data set
 * @return a random instance
 */
public static double[] getRandomInstance(Dataset data, Random r) {
    final int MIN_INDEX = 0;
    final int MAX_INDEX = 1;
    double[][] minMax = getMinMax(data);
    final int noAttributes = minMax.length;
    double[] ret = new double[noAttributes];
    for (int a = 0; a < noAttributes; a++) {
        ret[a] = minMax[a][MIN_INDEX] + (minMax[a][MAX_INDEX] - minMax[a][MIN_INDEX]) * r.nextDouble();
    }
    return ret;
}

From source file:org.apache.mahout.df.data.Utils.java

/**
 * generates a random vector based on the given attributes.<br>
 * the attributes' values are generated as follows :<br>
 * <ul>/* w  w  w  . j  a  v  a  2 s.c  om*/
 * <li>each IGNORED attribute receives a Double.NaN</li>
 * <li>each NUMERICAL attribute receives a random double</li>
 * <li>each CATEGORICAL and LABEL attribute receives a random integer in the
 * range [0, CATEGORICAL_RANGE[</li>
 * </ul>
 * 
 * @param rng
 * @param attrs attributes description
 * @return
 */
private static double[] randomVector(Random rng, Attribute[] attrs) {
    double[] vector = new double[attrs.length];

    for (int attr = 0; attr < attrs.length; attr++) {
        if (attrs[attr].isIgnored()) {
            vector[attr] = Double.NaN;
        } else if (attrs[attr].isNumerical()) {
            vector[attr] = rng.nextDouble();
        } else {
            // CATEGORICAL or LABEL
            vector[attr] = rng.nextInt(CATEGORICAL_RANGE);
        }
    }

    return vector;
}