Package org.apache.mahout.math.jet.random

Examples of org.apache.mahout.math.jet.random.Uniform

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    @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);
        }
    }
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        // 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
            public double nextDouble() {
                double x;
                if (gen.nextDouble() < 0.5) {
                    x = uniform.nextDouble();
                } else {
                    x = normal.nextDouble();
                }
                return x;
            }
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        Random rand = RandomUtils.getRandom();
        PrintWriter out = new PrintWriter(new FileOutputStream("qd-tree-comparison.csv"));
        try {
            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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        PrintWriter out = new PrintWriter(new FileOutputStream("sq-tree-comparison.csv"));
        try {

            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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    @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);
        }
    }
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        // 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
            public double nextDouble() {
                double x;
                if (gen.nextDouble() < 0.5) {
                    x = uniform.nextDouble();
                } else {
                    x = normal.nextDouble();
                }
                return x;
            }
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        try {
            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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        PrintWriter out = new PrintWriter(new FileOutputStream("sk-array-comparison.csv"));
        try {
            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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    @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);
        }
    }
View Full Code Here
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        // 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
            public double nextDouble() {
                double x;
                if (gen.nextDouble() < 0.5) {
                    x = uniform.nextDouble();
                } else {
                    x = normal.nextDouble();
                }
                return x;
            }
View Full Code Here
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