Example usage for org.apache.mahout.math.jet.random Uniform Uniform

Introduction

In this page you can find the example usage for org.apache.mahout.math.jet.random Uniform Uniform.

Prototype

public Uniform(double min, double max, Random randomGenerator) 

Source Link

Document

Constructs a uniform distribution with the given minimum and maximum.

Usage

From source file:com.clearspring.analytics.stream.quantile.TDigestTest.java

License:Apache License

@Test
public void testUniform() {
    Random gen = RandomUtils.getRandom();
    for (int i = 0; i < repeats(); i++) {
        runTest(new Uniform(0, 1, gen), 100, new double[] { 0.001, 0.01, 0.1, 0.5, 0.9, 0.99, 0.999 },
                "uniform", true, gen);
    }/*from w ww .  ja  v a 2  s.  co  m*/
}

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From source file:com.clearspring.analytics.stream.quantile.TDigestTest.java

License:Apache License

@Test
public void testNarrowNormal() {
    // this mixture of a uniform and normal distribution has a very narrow peak which is centered
    // near the median.  Our system should be scale invariant and work well regardless.
    final Random gen = RandomUtils.getRandom();
    AbstractContinousDistribution mix = new AbstractContinousDistribution() {
        AbstractContinousDistribution normal = new Normal(0, 1e-5, gen);
        AbstractContinousDistribution uniform = new Uniform(-1, 1, gen);

        @Override//from   ww  w  .ja  va2s  .c  o  m
        public double nextDouble() {
            double x;
            if (gen.nextDouble() < 0.5) {
                x = uniform.nextDouble();
            } else {
                x = normal.nextDouble();
            }
            return x;
        }
    };

    for (int i = 0; i < repeats(); i++) {
        runTest(mix, 100, new double[] { 0.001, 0.01, 0.1, 0.3, 0.5, 0.7, 0.9, 0.99, 0.999 }, "mixture", false,
                gen);
    }
}

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From source file:com.clearspring.analytics.stream.quantile.TDigestTest.java

License:Apache License

@Test
public void compareToQDigest() {
    Random rand = RandomUtils.getRandom();

    for (int i = 0; i < repeats(); i++) {
        compare(new Gamma(0.1, 0.1, rand), "gamma", 1L << 48, rand);
        compare(new Uniform(0, 1, rand), "uniform", 1L << 48, rand);
    }//  w w w.  j  a  va2s  .com
}

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From source file:com.mapr.synth.samplers.DateSampler.java

License:Apache License

@SuppressWarnings("UnusedDeclaration")
public void setStart(String start) throws ParseException {
    this.start = df.parse(start).getTime();
    base = new Uniform(0, this.end - this.start, RandomUtils.getRandom());
}

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From source file:com.mapr.synth.samplers.DateSampler.java

License:Apache License

@SuppressWarnings("UnusedDeclaration")
public void setEnd(String end) throws ParseException {
    this.end = df.parse(end).getTime();
    base = new Uniform(0, this.end - this.start, RandomUtils.getRandom());
}

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From source file:com.tdunning.math.stats.ArrayDigestTest.java

License:Apache License

@Test
public void testUniform() {
    Random gen = RandomUtils.getRandom();
    for (int i = 0; i < repeats(); i++) {
        runTest(factory, new Uniform(0, 1, gen), 100, new double[] { 0.001, 0.01, 0.1, 0.5, 0.9, 0.99, 0.999 },
                "uniform", true);
    }//from www . j  ava 2  s. c  o  m
}

---

From source file:com.tdunning.math.stats.ArrayDigestTest.java

License:Apache License

@Test
public void testNarrowNormal() {
    // this mixture of a uniform and normal distribution has a very narrow peak which is centered
    // near the median.  Our system should be scale invariant and work well regardless.
    final Random gen = RandomUtils.getRandom();
    AbstractContinousDistribution mix = new AbstractContinousDistribution() {
        AbstractContinousDistribution normal = new Normal(0, 1e-5, gen);
        AbstractContinousDistribution uniform = new Uniform(-1, 1, gen);

        @Override//from  w  w  w  . j  a v a2s.  c  om
        public double nextDouble() {
            double x;
            if (gen.nextDouble() < 0.5) {
                x = uniform.nextDouble();
            } else {
                x = normal.nextDouble();
            }
            return x;
        }
    };

    for (int i = 0; i < repeats(); i++) {
        runTest(factory, mix, 100, new double[] { 0.001, 0.01, 0.1, 0.3, 0.5, 0.7, 0.9, 0.99, 0.999 },
                "mixture", false);
    }
}

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From source file:com.tdunning.math.stats.ArrayDigestTest.java

License:Apache License

@Test
public void compareToQDigest() throws FileNotFoundException {
    Random rand = RandomUtils.getRandom();
    PrintWriter out = new PrintWriter(new FileOutputStream("qd-array-comparison.csv"));
    try {//w ww . java2 s. c o m
        out.printf("tag\tcompression\tq\te1\tcdf.vs.q\tsize\tqd.size\n");

        for (int i = 0; i < repeats(); i++) {
            compareQD(out, new Gamma(0.1, 0.1, rand), "gamma", 1L << 48);
            compareQD(out, new Uniform(0, 1, rand), "uniform", 1L << 48);
        }
    } finally {
        out.close();
    }
}

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From source file:com.tdunning.math.stats.ArrayDigestTest.java

License:Apache License

@Test
public void compareToStreamingQuantile() throws FileNotFoundException {
    Random rand = RandomUtils.getRandom();

    PrintWriter out = new PrintWriter(new FileOutputStream("sk-array-comparison.csv"));
    try {//from   w  w  w. j a  v a2 s.com
        out.printf("tag\tcompression\tq\te1\tcdf.vs.q\tsize\tsk.size\n");
        for (int i = 0; i < repeats(); i++) {
            compareSQ(out, new Gamma(0.1, 0.1, rand), "gamma", 1L << 48);
            compareSQ(out, new Uniform(0, 1, rand), "uniform", 1L << 48);
        }
    } finally {
        out.close();
    }
}

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From source file:com.tdunning.math.stats.AVLTreeDigestTest.java

License:Apache License

@Test
public void compareToQDigest() throws FileNotFoundException {
    Random rand = RandomUtils.getRandom();
    PrintWriter out = new PrintWriter(new FileOutputStream("qd-tree-comparison.csv"));
    try {//from www  . ja  v a2 s . co  m
        for (int i = 0; i < repeats(); i++) {
            compareQD(out, new Gamma(0.1, 0.1, rand), "gamma", 1L << 48);
            compareQD(out, new Uniform(0, 1, rand), "uniform", 1L << 48);
        }
    } finally {
        out.close();
    }
}

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