Package org.apache.commons.math.stat.descriptive

Examples of org.apache.commons.math.stat.descriptive.SummaryStatistics

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    /**
     * Test SummaryStatistics - implementations that do not store the data
     * and use single pass algorithms to compute statistics
    */
    public void testSummaryStatistics() throws Exception {
        SummaryStatistics u = new SummaryStatistics();
        loadStats("data/PiDigits.txt", u);
        assertEquals("PiDigits: std", std, u.getStandardDeviation(), 1E-13);
        assertEquals("PiDigits: mean", mean, u.getMean(), 1E-13);

        loadStats("data/Mavro.txt", u);
        assertEquals("Mavro: std", std, u.getStandardDeviation(), 1E-14);
        assertEquals("Mavro: mean", mean, u.getMean(), 1E-14);

        loadStats("data/Michelso.txt", u);
        assertEquals("Michelso: std", std, u.getStandardDeviation(), 1E-13);
        assertEquals("Michelso: mean", mean, u.getMean(), 1E-13);

        loadStats("data/NumAcc1.txt", u);
        assertEquals("NumAcc1: std", std, u.getStandardDeviation(), 1E-14);
        assertEquals("NumAcc1: mean", mean, u.getMean(), 1E-14);

        loadStats("data/NumAcc2.txt", u);
        assertEquals("NumAcc2: std", std, u.getStandardDeviation(), 1E-14);
        assertEquals("NumAcc2: mean", mean, u.getMean(), 1E-14);
    }
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     * @param statistical summary
     */
    private void loadStats(String resource, Object u) throws Exception {

        DescriptiveStatistics d = null;
        SummaryStatistics s = null;
        if (u instanceof DescriptiveStatistics) {
            d = (DescriptiveStatistics) u;
        } else {
            s = (SummaryStatistics) u;
        }
        u.getClass().getDeclaredMethod(
                "clear", new Class[]{}).invoke(u, new Object[]{});
        mean = Double.NaN;
        std = Double.NaN;

        BufferedReader in =
            new BufferedReader(
                    new InputStreamReader(
                            CertifiedDataTest.class.getResourceAsStream(resource)));

        String line = null;

        for (int j = 0; j < 60; j++) {
            line = in.readLine();
            if (j == 40) {
                mean =
                    Double.parseDouble(
                            line.substring(line.lastIndexOf(":") + 1).trim());
            }
            if (j == 41) {
                std =
                    Double.parseDouble(
                            line.substring(line.lastIndexOf(":") + 1).trim());
            }
        }

        line = in.readLine();

        while (line != null) {
            if (d != null) {
                d.addValue(Double.parseDouble(line.trim()));
            }  else {
                s.addValue(Double.parseDouble(line.trim()));
            }
            line = in.readLine();
        }

        in.close();
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        // Solving Ordinary Differential Equations I (Nonstiff problems),
        // the curves dy/dp = g(b) are in figure 6.5
        FirstOrderIntegrator integ =
            new DormandPrince54Integrator(1.0e-8, 100.0, new double[] { 1.0e-4, 1.0e-4 }, new double[] { 1.0e-4, 1.0e-4 });
        double hP = 1.0e-12;
        SummaryStatistics residualsP0 = new SummaryStatistics();
        SummaryStatistics residualsP1 = new SummaryStatistics();
        for (double b = 2.88; b < 3.08; b += 0.001) {
            Brusselator brusselator = new Brusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            brusselator.setParameter(0, b + hP);
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
        }
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) > 600);
        Assert.assertTrue(residualsP0.getStandardDeviation() > 30);
        Assert.assertTrue((residualsP1.getMax() - residualsP1.getMin()) > 800);
        Assert.assertTrue(residualsP1.getStandardDeviation() > 50);
    }
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    public void testHighAccuracyExternalDifferentiation()
        throws IntegratorException, DerivativeException {
        FirstOrderIntegrator integ =
            new DormandPrince54Integrator(1.0e-8, 100.0, new double[] { 1.0e-10, 1.0e-10 }, new double[] { 1.0e-10, 1.0e-10 });
        double hP = 1.0e-12;
        SummaryStatistics residualsP0 = new SummaryStatistics();
        SummaryStatistics residualsP1 = new SummaryStatistics();
        for (double b = 2.88; b < 3.08; b += 0.001) {
            Brusselator brusselator = new Brusselator(b);
            double[] y = { 1.3, b };
            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            brusselator.setParameter(0, b + hP);
            integ.integrate(brusselator, 0, yP, 20.0, yP);
            residualsP0.addValue((yP[0] - y[0]) / hP - brusselator.dYdP0());
            residualsP1.addValue((yP[1] - y[1]) / hP - brusselator.dYdP1());
        }
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) > 0.02);
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) < 0.03);
        Assert.assertTrue(residualsP0.getStandardDeviation() > 0.003);
        Assert.assertTrue(residualsP0.getStandardDeviation() < 0.004);
        Assert.assertTrue((residualsP1.getMax() - residualsP1.getMin()) > 0.04);
        Assert.assertTrue((residualsP1.getMax() - residualsP1.getMin()) < 0.05);
        Assert.assertTrue(residualsP1.getStandardDeviation() > 0.007);
        Assert.assertTrue(residualsP1.getStandardDeviation() < 0.008);
    }
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    public void testInternalDifferentiation()
        throws IntegratorException, DerivativeException {
        FirstOrderIntegrator integ =
            new DormandPrince54Integrator(1.0e-8, 100.0, new double[] { 1.0e-4, 1.0e-4 }, new double[] { 1.0e-4, 1.0e-4 });
        double hP = 1.0e-12;
        SummaryStatistics residualsP0 = new SummaryStatistics();
        SummaryStatistics residualsP1 = new SummaryStatistics();
        for (double b = 2.88; b < 3.08; b += 0.001) {
            Brusselator brusselator = new Brusselator(b);
            brusselator.setParameter(0, b);
            double[] z = { 1.3, b };
            double[][] dZdZ0 = new double[2][2];
            double[][] dZdP  = new double[2][1];
            double hY = 1.0e-12;
            FirstOrderIntegratorWithJacobians extInt =
                new FirstOrderIntegratorWithJacobians(integ, brusselator, new double[] { b },
                                                      new double[] { hY, hY }, new double[] { hP });
            extInt.setMaxEvaluations(5000);
            extInt.integrate(0, z, new double[][] { { 0.0 }, { 1.0 } }, 20.0, z, dZdZ0, dZdP);
            Assert.assertEquals(5000, extInt.getMaxEvaluations());
            Assert.assertTrue(extInt.getEvaluations() > 1400);
            Assert.assertTrue(extInt.getEvaluations() < 2000);
            Assert.assertEquals(4 * integ.getEvaluations(), extInt.getEvaluations());
            residualsP0.addValue(dZdP[0][0] - brusselator.dYdP0());
            residualsP1.addValue(dZdP[1][0] - brusselator.dYdP1());
        }
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) < 0.02);
        Assert.assertTrue(residualsP0.getStandardDeviation() < 0.003);
        Assert.assertTrue((residualsP1.getMax() - residualsP1.getMin()) < 0.05);
        Assert.assertTrue(residualsP1.getStandardDeviation() < 0.01);
    }
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    @Test
    public void testAnalyticalDifferentiation()
        throws IntegratorException, DerivativeException {
        FirstOrderIntegrator integ =
            new DormandPrince54Integrator(1.0e-8, 100.0, new double[] { 1.0e-4, 1.0e-4 }, new double[] { 1.0e-4, 1.0e-4 });
        SummaryStatistics residualsP0 = new SummaryStatistics();
        SummaryStatistics residualsP1 = new SummaryStatistics();
        for (double b = 2.88; b < 3.08; b += 0.001) {
            Brusselator brusselator = new Brusselator(b);
            brusselator.setParameter(0, b);
            double[] z = { 1.3, b };
            double[][] dZdZ0 = new double[2][2];
            double[][] dZdP  = new double[2][1];
            FirstOrderIntegratorWithJacobians extInt =
                new FirstOrderIntegratorWithJacobians(integ, brusselator);
            extInt.setMaxEvaluations(5000);
            extInt.integrate(0, z, new double[][] { { 0.0 }, { 1.0 } }, 20.0, z, dZdZ0, dZdP);
            Assert.assertEquals(5000, extInt.getMaxEvaluations());
            Assert.assertTrue(extInt.getEvaluations() > 350);
            Assert.assertTrue(extInt.getEvaluations() < 510);
            Assert.assertEquals(integ.getEvaluations(), extInt.getEvaluations());
            residualsP0.addValue(dZdP[0][0] - brusselator.dYdP0());
            residualsP1.addValue(dZdP[1][0] - brusselator.dYdP1());
        }
        Assert.assertTrue((residualsP0.getMax() - residualsP0.getMin()) < 0.014);
        Assert.assertTrue(residualsP0.getStandardDeviation() < 0.003);
        Assert.assertTrue((residualsP1.getMax() - residualsP1.getMin()) < 0.05);
        Assert.assertTrue(residualsP1.getStandardDeviation() < 0.01);
    }
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    private Map<String, Double> certifiedValues;

    @Override
    protected void setUp() throws Exception {
        descriptives = new DescriptiveStatistics();
        summaries = new SummaryStatistics();
        certifiedValues = new HashMap<String, Double>();

        loadData();
    }
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        super(name);
    }

    @Override
    public void setUp() {
        tooShortStats = new SummaryStatistics();
        tooShortStats.addValue(0d);
    }
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    public void testOneSampleT() throws Exception {
        double[] observed =
            {93.0, 103.0, 95.0, 101.0, 91.0, 105.0, 96.0, 94.0, 101.0,  88.0, 98.0, 94.0, 101.0, 92.0, 95.0 };
        double mu = 100.0;
        SummaryStatistics sampleStats = null;
        sampleStats = new SummaryStatistics();
        for (int i = 0; i < observed.length; i++) {
            sampleStats.addValue(observed[i]);
        }

        // Target comparison values computed using R version 1.8.1 (Linux version)
        assertEquals("t statistic",  -2.81976445346,
                testStatistic.t(mu, observed), 10E-10);
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    }

    public void testOneSampleTTest() throws Exception {
        double[] oneSidedP =
            {2d, 0d, 6d, 6d, 3d, 3d, 2d, 3d, -6d, 6d, 6d, 6d, 3d, 0d, 1d, 1d, 0d, 2d, 3d, 3d };
        SummaryStatistics oneSidedPStats = new SummaryStatistics();
        for (int i = 0; i < oneSidedP.length; i++) {
            oneSidedPStats.addValue(oneSidedP[i]);
        }
        // Target comparison values computed using R version 1.8.1 (Linux version)
        assertEquals("one sample t stat", 3.86485535541,
                testStatistic.t(0d, oneSidedP), 10E-10);
        assertEquals("one sample t stat", 3.86485535541,
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