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.jetspeed.security.mfa.impl.CaptchaImageResource.java

public void init() {
    boolean emptyBackground = true;
    if (config.isUseImageBackground() && background != null) {
        ByteArrayInputStream is = new ByteArrayInputStream(background);
        JPEGImgDecoder decoder = new DefaultJPEGImgDecoder();
        try {/*w ww.j  a  va 2s .c  o  m*/
            this.image = decoder.decodeAsBufferedImage(is);
            this.width = image.getWidth();
            this.height = image.getHeight();
            emptyBackground = false;
        } catch (Exception e) {
            emptyBackground = true;
        }
    }
    if (emptyBackground) {
        this.width = config.getTextMarginLeft() * 2;
        this.height = config.getTextMarginBottom() * 6;
    }
    char[] chars = challengeId.toCharArray();
    charAttsList = new ArrayList();
    TextLayout text = null;
    AffineTransform textAt = null;
    String[] fontNames = config.getFontNames();
    for (int i = 0; i < chars.length; i++) {
        // font name
        String fontName = (fontNames.length == 1) ? fontNames[0] : fontNames[randomInt(0, fontNames.length)];

        // rise
        int rise = config.getTextRiseRange();
        if (rise > 0) {
            rise = randomInt(config.getTextMarginBottom(),
                    config.getTextMarginBottom() + config.getTextRiseRange());
        }

        if (config.getTextShear() > 0.0 || config.getTextRotation() > 0) {
            // rotation
            double dRotation = 0.0;
            if (config.getTextRotation() > 0) {
                dRotation = Math.toRadians(randomInt(-(config.getTextRotation()), config.getTextRotation()));
            }

            // shear
            double shearX = 0.0;
            double shearY = 0.0;
            if (config.getTextShear() > 0.0) {
                Random ran = new Random();
                shearX = ran.nextDouble() * config.getTextShear();
                shearY = ran.nextDouble() * config.getTextShear();
            }
            CharAttributes cf = new CharAttributes(chars[i], fontName, dRotation, rise, shearX, shearY);
            charAttsList.add(cf);
            text = new TextLayout(chars[i] + "", getFont(fontName),
                    new FontRenderContext(null, config.isFontAntialiasing(), false));
            textAt = new AffineTransform();
            if (config.getTextRotation() > 0)
                textAt.rotate(dRotation);
            if (config.getTextShear() > 0.0)
                textAt.shear(shearX, shearY);
        } else {
            CharAttributes cf = new CharAttributes(chars[i], fontName, 0, rise, 0.0, 0.0);
            charAttsList.add(cf);
        }
        if (emptyBackground) {
            Shape shape = text.getOutline(textAt);
            //                this.width += text.getBounds().getWidth();
            this.width += (int) shape.getBounds2D().getWidth();
            this.width += config.getTextSpacing() + 1;
            if (this.height < (int) shape.getBounds2D().getHeight() + rise) {
                this.height = (int) shape.getBounds2D().getHeight() + rise;
            }
        }
    }
    if (emptyBackground) {
        this.image = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);
        Graphics2D gfx = (Graphics2D) this.image.getGraphics();
        gfx.setBackground(Color.WHITE);
        gfx.clearRect(0, 0, width, height);
    }
}

---

From source file:org.jtransforms.utils.IOUtils.java

/**
 * Fills 2D matrix with random numbers.// w w  w .j a  v a  2s .co  m
* @param n1  rows
* @param n2  columns
* @param m   2D matrix
*/
public static void fillMatrix_2D(long n1, long n2, double[] m) {
    Random r = new Random(2);
    for (int i = 0; i < n1; i++) {
        for (int j = 0; j < n2; j++) {
            m[(int) (i * n2 + j)] = r.nextDouble();
        }
    }
}

---

From source file:org.jtransforms.utils.IOUtils.java

/**
 * Fills 2D matrix with random numbers.//ww w. j  a va  2  s.c om
* @param n1  rows
* @param n2  columns
* @param m   2D matrix
*/
public static void fillMatrix_2D(long n1, long n2, DoubleLargeArray m) {
    Random r = new Random(2);
    for (long i = 0; i < n1; i++) {
        for (long j = 0; j < n2; j++) {
            m.setDouble(i * n2 + j, r.nextDouble());
        }
    }
}

---

From source file:tml.vectorspace.factorisation.MultiDimensionalScalingNR.java

public Instances scale(Instances instances) {
    // approximation error
    error = 0.0;// w  w w  .  ja  va 2 s  .  c  o m
    double error_previous;

    // number of points
    int n = instances.numInstances();

    // distance between points in the p-dimensional layout
    d = new Matrix(n, n);
    Matrix d_previous;

    // dissimilarity between vectors
    d_hat = new Matrix(n, n);

    // points instances
    FastVector attributes = new FastVector(p);
    attributes.addElement(new Attribute("X"));
    attributes.addElement(new Attribute("Y"));
    Instances x = new Instances("MDS", attributes, instances.numInstances());
    Instances x_previous;

    // initialise points sequence
    ArrayList<Integer> kseq = new ArrayList<Integer>();
    for (int k = 0; k < n; k++) {
        kseq.add(k);
    }

    // initialise x
    if (initialX != null) {
        x = new Instances(initialX);

    } else {
        Random rand = new Random();
        for (int k = 0; k < n; k++) {
            Instance x_inst = new Instance(p);
            x_inst.setValue(X, rand.nextDouble() - rand.nextInt(1));
            x_inst.setValue(Y, rand.nextDouble() - rand.nextInt(1));
            x.add(x_inst);
        }
    }

    // calculate d
    for (int j = 0; j < n; j++) {
        for (int i = 0; i < j; i++) {
            double distance = this.distance(x.instance(i), x.instance(j));
            d.set(i, j, distance);
            d.set(j, i, distance);

            double dissimilarity = this.dissimilarity(instances.instance(i), instances.instance(j));
            d_hat.set(i, j, dissimilarity);
            d_hat.set(j, i, dissimilarity);

            if (d_hat.get(i, j) != 0) {
                error += Math.pow(d.get(i, j) - d_hat.get(i, j), 2) / Math.pow(d_hat.get(i, j), 2);
            }
        }
    }

    // record previous results
    error_previous = error;
    d_previous = d.copy();
    x_previous = new Instances(x);

    // start of Newton-Raphson method
    logger.info("Starting Newton-Raphson MDS.");
    for (int iter = 0; iter < maxIterations; iter++) {
        // randomise points sequence to ensure faster convergence
        Collections.shuffle(kseq);
        for (int k : kseq) {
            Matrix gradient = new Matrix(p, 1);
            Matrix hessian = new Matrix(p, p);

            // calculate gradient vector
            for (int a = 0; a < p; a++) {
                double sum = 0;
                for (int l = 0; l < n; l++) {
                    if (k != l) {
                        if (d.get(k, l) != 0 && d_hat.get(k, l) != 0) {
                            sum += ((d.get(k, l) - d_hat.get(k, l))
                                    / (d.get(k, l) * Math.pow(d_hat.get(k, l), 2)))
                                    * (x.instance(k).value(a) - x.instance(l).value(a));
                        }
                    }
                }
                gradient.set(a, 0, 2 * sum);
            }

            // calculate hessian matrix
            for (int a = 0; a < p; a++) {
                for (int b = 0; b < p; b++) {
                    double sum = 0.0;
                    if (a != b) {
                        for (int l = 0; l < n; l++) {
                            if (k != l) {
                                if (d.get(k, l) != 0 && d_hat.get(k, l) != 0) {
                                    sum += ((x.instance(k).value(a) - x.instance(l).value(a))
                                            * (x.instance(k).value(b) - x.instance(l).value(b)))
                                            / (Math.pow(d.get(k, l), 3) * d_hat.get(k, l));
                                }
                            }
                        }
                        sum = 2 * sum;
                    } else {
                        for (int l = 0; l < n; l++) {
                            if (k != l) {
                                if (d_hat.get(k, l) != 0 && d.get(k, l) != 0) {
                                    sum += (1.0 / Math.pow(d_hat.get(k, l), 2)) - (Math.pow(d.get(k, l), 2)
                                            - Math.pow((x.instance(k).value(a) - x.instance(l).value(a)), 2))
                                            / (Math.pow(d.get(k, l), 3) * d_hat.get(k, l));
                                }
                            }
                        }
                        sum = 2 * sum;
                    }
                    hessian.set(a, b, sum);
                }
            }

            // update x
            Matrix x_k = new Matrix(x.instance(k).toDoubleArray(), p);
            Matrix x_k_tilda = x_k.minus(hessian.inverse().times(gradient));
            x.instance(k).setValue(X, x_k_tilda.get(X, 0));
            x.instance(k).setValue(Y, x_k_tilda.get(Y, 0));
        }

        // calculate d and error
        error = 0;
        for (int j = 0; j < n; j++) {
            for (int i = 0; i < j; i++) {
                double distance = this.distance(x.instance(i), x.instance(j));
                d.set(i, j, distance);
                d.set(j, i, distance);

                if (d_hat.get(i, j) != 0) {
                    error += Math.pow(d.get(i, j) - d_hat.get(i, j), 2) / Math.pow(d_hat.get(i, j), 2);
                }
            }
        }

        if (error < error_previous) {
            logger.debug(iter + ".\t error " + error);
            if (error_previous - error <= tolerence) {
                break;
            }

            error_previous = error;
            d_previous = d.copy();
            x_previous = new Instances(x);
        } else // invalidates last run
        {
            x = new Instances(x_previous);
            d = d_previous.copy();
        }
    }

    logger.info("Finished Newton-Raphson MDS.");
    return x;
}

---

From source file:org.apache.hadoop.hive.ql.exec.vector.VectorRandomRowSource.java

public static Object randomObject(int column, Random r, PrimitiveCategory[] primitiveCategories,
        PrimitiveTypeInfo[] primitiveTypeInfos, String[] alphabets, boolean addEscapables,
        String needsEscapeStr) {//from   ww w .j  a  va 2 s . co  m
    PrimitiveCategory primitiveCategory = primitiveCategories[column];
    PrimitiveTypeInfo primitiveTypeInfo = primitiveTypeInfos[column];
    try {
        switch (primitiveCategory) {
        case BOOLEAN:
            return Boolean.valueOf(r.nextInt(1) == 1);
        case BYTE:
            return Byte.valueOf((byte) r.nextInt());
        case SHORT:
            return Short.valueOf((short) r.nextInt());
        case INT:
            return Integer.valueOf(r.nextInt());
        case LONG:
            return Long.valueOf(r.nextLong());
        case DATE:
            return RandomTypeUtil.getRandDate(r);
        case FLOAT:
            return Float.valueOf(r.nextFloat() * 10 - 5);
        case DOUBLE:
            return Double.valueOf(r.nextDouble() * 10 - 5);
        case STRING:
        case CHAR:
        case VARCHAR: {
            String result;
            if (alphabets != null && alphabets[column] != null) {
                result = RandomTypeUtil.getRandString(r, alphabets[column], r.nextInt(10));
            } else {
                result = RandomTypeUtil.getRandString(r);
            }
            if (addEscapables && result.length() > 0) {
                int escapeCount = 1 + r.nextInt(2);
                for (int i = 0; i < escapeCount; i++) {
                    int index = r.nextInt(result.length());
                    String begin = result.substring(0, index);
                    String end = result.substring(index);
                    Character needsEscapeChar = needsEscapeStr.charAt(r.nextInt(needsEscapeStr.length()));
                    result = begin + needsEscapeChar + end;
                }
            }
            switch (primitiveCategory) {
            case STRING:
                return result;
            case CHAR:
                return new HiveChar(result, ((CharTypeInfo) primitiveTypeInfo).getLength());
            case VARCHAR:
                return new HiveChar(result, ((VarcharTypeInfo) primitiveTypeInfo).getLength());
            default:
                throw new Error("Unknown primitive category " + primitiveCategory);
            }
        }
        case BINARY:
            return getRandBinary(r, 1 + r.nextInt(100));
        case TIMESTAMP:
            return RandomTypeUtil.getRandTimestamp(r);
        case INTERVAL_YEAR_MONTH:
            return getRandIntervalYearMonth(r);
        case INTERVAL_DAY_TIME:
            return getRandIntervalDayTime(r);
        case DECIMAL:
            return getRandHiveDecimal(r, (DecimalTypeInfo) primitiveTypeInfo);
        default:
            throw new Error("Unknown primitive category " + primitiveCategory);
        }
    } catch (Exception e) {
        throw new RuntimeException("randomObject failed on column " + column + " type " + primitiveCategory, e);
    }
}

---

From source file:edu.stanford.muse.util.EmailUtils.java

private static Map<String, String> sample(Map<String, String> full, double p) {
    Random rand = new Random();
    Map<String, String> sample = new LinkedHashMap<>();
    for (String e : full.keySet()) {
        if (rand.nextDouble() < p)
            sample.put(e, full.get(e));/*from  w  w  w.j a v  a 2  s  .com*/
    }
    return sample;
}

---

From source file:RosAdProgram.model.Model.java

public int mask(double probability, int data) {
    int shiftVariable = 1;
    int tempMask = 0;
    int tempBitError = 0; //  ?   
    Random randomNumberGenerator = new Random();
    for (int i = 0; i != 8; shiftVariable = shiftVariable << 1, i++) {
        //System.out.println(" "+i);
        if (randomNumberGenerator.nextDouble() > probability) {
            if (i == 0) { //? ? ? 
                //System.out.format("\n i = %d ? ? %h ",i, tempMask );
                tempMask = tempMask | shiftVariable; //  ?  ? ? ?
                tempBitError++; // ? ?  
                // System.out.format(" %h .  %h\n", shiftVariable,tempMask );
            } else { // ?   
                     //System.out.format("i = %d ? ? %h ",i, tempMask );

                tempMask = tempMask | shiftVariable;
                tempBitError++;//from ww w  .  ja va 2 s . co m

                //System.out.format(" %h .  %h\n", shiftVariable,tempMask );
            }
        } else {
            //System.out.println("  ("+i+")");
        }
    }
    setBitError(tempBitError); //  ? ? 
    if (tempBitError != 0) { // ?    ,   ?   .
        setBlockErrorFlag(true); //?   . ???  ?  .
        setByteError(1); //  ? ? 
    }
    //        System.out.format("\n\n\n ? ? = %h\n", tempMask );
    //        System.out.format("\n\n\n  = %h\n", data);
    //        System.out.format("\n\n\n  ? = %h\n", data ^ tempMask);
    //        System.out.println("-----------------------------------------------");
    return data ^ tempMask;
}

---

From source file:br.fapesp.myutils.MyUtils.java

public static double[] uniformlySample(double low, double high, int nsamples, Random rng, long seed) {
    double[] samples = new double[nsamples];
    Random r;

    if (rng == null)
        r = new Random(seed);
    else/*ww  w  .ja v a 2 s  .  com*/
        r = rng;

    for (int i = 0; i < nsamples; i++)
        samples[i] = r.nextDouble() * (high - low) + low;

    return samples;
}

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From source file:edu.cornell.med.icb.goby.modes.ReformatCompactReadsMode.java

/**
 * @param lo lower limit of range/*  www .j  a  v a2s  .  c  o m*/
 * @param hi upper limit of range
 * @return a random integer in the range <STRONG>lo</STRONG>,
 *         <STRONG>lo</STRONG>+1, ... ,<STRONG>hi</STRONG>
 */
private int chooseRandom(final Random random, final int lo, final int hi) {
    final double r = random.nextDouble();
    final int result = (int) ((long) lo + (long) ((1L + (long) hi - (long) lo) * r));
    assert result >= lo && result <= hi;
    return result;
}

---

From source file:org.jtransforms.utils.IOUtils.java

/**
 * Fills 3D matrix with random numbers.//from w w  w.j  a  va  2s .co  m
* @param n1  slices
* @param n2  rows
* @param n3  columns
* @param m   3D matrix
*/
public static void fillMatrix_3D(long n1, long n2, long n3, double[][][] m) {
    Random r = new Random(2);
    for (int i = 0; i < n1; i++) {
        for (int j = 0; j < n2; j++) {
            for (int k = 0; k < n3; k++) {
                m[i][j][k] = r.nextDouble();
            }
        }
    }
}

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