Example usage for java.util Random Random

Introduction

In this page you can find the example usage for java.util Random Random.

Prototype

public Random(long seed) 

Source Link

Document

Creates a new random number generator using a single long seed.

Usage

From source file:Main.java

public static void genRandom(long seed, int factor, int offset, float array[], int stride, int skip) {
    Random r = new Random(seed);
    for (int i = 0; i < array.length / stride; i++) {
        for (int j = 0; j < stride; j++) {
            if (j >= stride - skip)
                array[i * stride + j] = 0;
            else//from  ww w. java  2 s  . c  om
                array[i * stride + j] = r.nextFloat() * factor + offset;
        }
    }
}

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From source file:Main.java

/**
 * Fills the array with random longs.  If signed is true, negative values can be generated.
 * The values will fit within 'numberOfBits'.  This is useful for conversion tests.
 *///ww w .j  ava 2 s . com
public static void genRandomLongs(long seed, long array[], boolean signed, int numberOfBits) {
    long positiveMask = numberOfBits == 64 ? -1 : ((1l << numberOfBits) - 1);
    long negativeMask = ~positiveMask;
    Random r = new Random(seed);
    for (int i = 0; i < array.length; i++) {
        long l = r.nextLong();
        if (signed && l < 0) {
            l = l | negativeMask;
        } else {
            l = l & positiveMask;
        }
        array[i] = l;
    }
    // Seed a few special numbers we want to be sure to test.
    array[r.nextInt(array.length)] = 0l;
    array[r.nextInt(array.length)] = 1l;
    array[r.nextInt(array.length)] = positiveMask;
    if (signed) {
        array[r.nextInt(array.length)] = negativeMask;
        array[r.nextInt(array.length)] = -1;
    }
}

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From source file:Main.java

/**
 * Fills the array with random floats.  Values will be between min (inclusive) and
 * max (inclusive).//from  www  . j a  v  a 2s  .  co m
 */
public static void genRandomFloats(long seed, float min, float max, float array[], boolean includeExtremes) {
    Random r = new Random(seed);
    int minExponent = Math.min(Math.getExponent(min), 0);
    int maxExponent = Math.max(Math.getExponent(max), 0);
    if (minExponent < -6 || maxExponent > 6) {
        // Use an exponential distribution
        int exponentDiff = maxExponent - minExponent;
        for (int i = 0; i < array.length; i++) {
            float mantissa = r.nextFloat();
            int exponent = minExponent + r.nextInt(maxExponent - minExponent);
            int sign = (min >= 0) ? 1 : 1 - r.nextInt(2) * 2; // -1 or 1
            float rand = sign * mantissa * (float) Math.pow(2.0, exponent);
            if (rand < min || rand > max) {
                continue;
            }
            array[i] = rand;
        }
    } else {
        // Use a linear distribution
        for (int i = 0; i < array.length; i++) {
            float rand = r.nextFloat();
            array[i] = min + rand * (max - min);
        }
    }
    // Seed a few special numbers we want to be sure to test.
    for (int i = 0; i < sInterestingDoubles.length; i++) {
        float f = (float) sInterestingDoubles[i];
        if (min <= f && f <= max) {
            array[r.nextInt(array.length)] = f;
        }
    }
    array[r.nextInt(array.length)] = min;
    array[r.nextInt(array.length)] = max;
    if (includeExtremes) {
        array[r.nextInt(array.length)] = Float.NaN;
        array[r.nextInt(array.length)] = Float.POSITIVE_INFINITY;
        array[r.nextInt(array.length)] = Float.NEGATIVE_INFINITY;
        array[r.nextInt(array.length)] = Float.MIN_VALUE;
        array[r.nextInt(array.length)] = Float.MIN_NORMAL;
        array[r.nextInt(array.length)] = Float.MAX_VALUE;
        array[r.nextInt(array.length)] = -Float.MIN_VALUE;
        array[r.nextInt(array.length)] = -Float.MIN_NORMAL;
        array[r.nextInt(array.length)] = -Float.MAX_VALUE;
    }
}

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From source file:Main.java

/**
 * Fills the array with random doubles.  Values will be between min (inclusive) and
 * max (inclusive).//ww w  . j a  va2  s . c o  m
 */
public static void genRandomDoubles(long seed, double min, double max, double array[],
        boolean includeExtremes) {
    Random r = new Random(seed);
    int minExponent = Math.min(Math.getExponent(min), 0);
    int maxExponent = Math.max(Math.getExponent(max), 0);
    if (minExponent < -6 || maxExponent > 6) {
        // Use an exponential distribution
        int exponentDiff = maxExponent - minExponent;
        for (int i = 0; i < array.length; i++) {
            double mantissa = r.nextDouble();
            int exponent = minExponent + r.nextInt(maxExponent - minExponent);
            int sign = (min >= 0) ? 1 : 1 - r.nextInt(2) * 2; // -1 or 1
            double rand = sign * mantissa * Math.pow(2.0, exponent);
            if (rand < min || rand > max) {
                continue;
            }
            array[i] = rand;
        }
    } else {
        // Use a linear distribution
        for (int i = 0; i < array.length; i++) {
            double rand = r.nextDouble();
            array[i] = min + rand * (max - min);
        }
    }
    // Seed a few special numbers we want to be sure to test.
    for (int i = 0; i < sInterestingDoubles.length; i++) {
        double d = sInterestingDoubles[i];
        if (min <= d && d <= max) {
            array[r.nextInt(array.length)] = d;
        }
    }
    array[r.nextInt(array.length)] = min;
    array[r.nextInt(array.length)] = max;
    if (includeExtremes) {
        array[r.nextInt(array.length)] = Double.NaN;
        array[r.nextInt(array.length)] = Double.POSITIVE_INFINITY;
        array[r.nextInt(array.length)] = Double.NEGATIVE_INFINITY;
        array[r.nextInt(array.length)] = Double.MIN_VALUE;
        array[r.nextInt(array.length)] = Double.MIN_NORMAL;
        array[r.nextInt(array.length)] = Double.MAX_VALUE;
        array[r.nextInt(array.length)] = -Double.MIN_VALUE;
        array[r.nextInt(array.length)] = -Double.MIN_NORMAL;
        array[r.nextInt(array.length)] = -Double.MAX_VALUE;
    }
}

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From source file:ml.shifu.shifu.core.binning.DynamicBinningTest.java

public static List<NumBinInfo> createNumBinInfos(int binCnt) {
    Random rd = new Random(System.currentTimeMillis());

    List<Double> thresholds = new ArrayList<Double>(binCnt - 1);
    for (int i = 0; i < binCnt - 1; i++) {
        thresholds.add(rd.nextGaussian() * 200);
    }/*from www.  j  av  a  2s  .c  o m*/

    Collections.sort(thresholds);

    List<NumBinInfo> binInfoList = NumBinInfo.constructNumBinfo(StringUtils.join(thresholds, ':'), ':');
    for (NumBinInfo binInfo : binInfoList) {
        if (rd.nextDouble() > 0.45) {
            int total = rd.nextInt() % 1000;
            int positive = (int) (total * rd.nextDouble());
            binInfo.setTotalInstCnt(total);
            binInfo.setPositiveInstCnt(positive);
        }
    }

    return binInfoList;
}

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From source file:Main.java

public static void shuffle(final Object[] array, final long seed) {
    final Random r = new Random(seed);
    final int limit = array.length;
    for (int i = 0; i < limit; ++i) {
        swap(array, i, r.nextInt(limit));
    }/* w  w w.j ava 2 s  . co  m*/
}

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From source file:io.cortical.retina.model.TestDataHarness.java

/**
 * Create dummy  {@link Fingerprint}./*from   w w w  .j  a  va2  s  .  c om*/
 * 
 * @return dummy fingerprint.
 */
public static Fingerprint createFingerprint() {
    Random random = new Random(SEED);
    Set<Integer> positionSet = new LinkedHashSet<>();
    while (positionSet.size() <= FINGERPRINT_LENGTH) {
        positionSet.add(random.nextInt(MAX_POSITION));
    }

    Integer[] positionsInteger = new Integer[FINGERPRINT_LENGTH];
    positionsInteger = positionSet.toArray(positionsInteger);
    sort(positionsInteger);
    return new Fingerprint(ArrayUtils.toPrimitive(positionsInteger));
}

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From source file:Main.java

private static double randomDouble() {
    Random random = new Random(0);
    return -5.0 + random.nextDouble() * 10;
}

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From source file:Util.java

public static long[][] getBinomialDistribution(int min, int max, long total) {
    Random rand = new Random(System.currentTimeMillis());
    int n = max - min;
    long[][] ret = new long[2][n + 1];
    int mean = (n + 1) / 2;
    float p = 1;//w  w w  .  j a v  a  2s . c o  m
    if (n > 0) {
        p = (float) mean / (float) n;
    }

    long count = 0;
    for (int i = 0; i <= n; i++) {
        double p_i = combination(n, i) * Math.pow(p, i) * Math.pow((1 - p), (n - i));
        long count_i = (long) (total * p_i);
        ret[0][i] = i + min;
        ret[1][i] = count_i;
        count += count_i;
    }

    while (count < total) {
        int i = rand.nextInt(n + 1);
        ret[1][i]++;
        count++;
    }

    return ret;
}

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From source file:Util.java

public static long[][] getDiscreteUniformDistribution(int min, int max, long total) {
    Random rand = new Random(System.currentTimeMillis());
    int span = max - min + 1;
    long avg = total / span;
    long[][] ret = new long[2][span];

    if (avg >= 1) {
        long count = 0;
        for (int i = 0; i < span; i++) {
            ret[0][i] = min + i;/*w ww. ja  v  a2 s  .c  o  m*/
            ret[1][i] = avg;
            count += avg;
        }

        if (count < total) {
            avg = span / (total - count);
            int a = (int) avg;
            int k = 0;
            while (count < total) {
                int i = rand.nextInt(span);
                ret[1][a * k]++;
                k++;
                count++;
            }
        }
    } else {
        for (int i = 0; i < span; i++) {
            ret[0][i] = min + i;
        }
        long count = 0;
        avg = span / total;
        while (count < total) {
            long k = count * avg;
            int kk = (int) k;
            ret[1][kk] = 1;
            count++;
            // int i = rand.nextInt(span);
            // if (ret[1][i] == 0) {
            // ret[1][i] = 1;
            // count++;
            // }
        }
    }
    return ret;
}

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