Examples of org.apache.commons.math3.stat.descriptive.summary.Sum

Package org.apache.commons.math3.stat.descriptive.summary

Examples of org.apache.commons.math3.stat.descriptive.summary.Sum

org.apache.commons.math3.stat.descriptive.summary.Sum
Returns the sum of the available values.
If there are no values in the dataset, then 0 is returned. If any of the values are NaN, then NaN is returned.

Note that this implementation is not synchronized. If multiple threads access an instance of this class concurrently, and at least one of the threads invokes the increment() or clear() method, it must be synchronized externally.

        dest.secondMoment = source.secondMoment.copy();
        dest.n = source.n;


        // Keep commons-math supplied statistics with embedded moments in synch
        if (source.getVarianceImpl() instanceof Variance) {
            dest.varianceImpl = new Variance(dest.secondMoment);
        } else {
            dest.varianceImpl = source.varianceImpl.copy();
        }
        if (source.meanImpl instanceof Mean) {
            dest.meanImpl = new Mean(dest.secondMoment);

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        sumLogImpl  = new StorelessUnivariateStatistic[k];
        geoMeanImpl = new StorelessUnivariateStatistic[k];
        meanImpl    = new StorelessUnivariateStatistic[k];


        for (int i = 0; i < k; ++i) {
            sumImpl[i]     = new Sum();
            sumSqImpl[i]   = new SumOfSquares();
            minImpl[i]     = new Min();
            maxImpl[i]     = new Max();
            sumLogImpl[i]  = new SumOfLogs();
            geoMeanImpl[i] = new GeometricMean();

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     */
    @Override
    public double evaluate(final double[] values,final int begin, final int length)
    throws MathIllegalArgumentException {
        if (test(values, begin, length)) {
            Sum sum = new Sum();
            double sampleSize = length;


            // Compute initial estimate using definitional formula
            double xbar = sum.evaluate(values, begin, length) / sampleSize;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {
                correction += values[i] - xbar;

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     * @since 2.1
     */
    public double evaluate(final double[] values, final double[] weights,
                           final int begin, final int length) throws MathIllegalArgumentException {
        if (test(values, weights, begin, length)) {
            Sum sum = new Sum();


            // Compute initial estimate using definitional formula
            double sumw = sum.evaluate(weights,begin,length);
            double xbarw = sum.evaluate(values, weights, begin, length) / sumw;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {
                correction += weights[i] * (values[i] - xbarw);

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        Assert.assertEquals(u, v);
        Assert.assertEquals(v, u);


        // Check implementation pointers are preserved
        u.clear();
        u.setSumImpl(new Sum());
        SummaryStatistics.copy(u,v);
        Assert.assertEquals(u.getSumImpl(), v.getSumImpl());


    }

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    }


    @Test
    public void testSetterInjection() {
        SummaryStatistics u = createSummaryStatistics();
        u.setMeanImpl(new Sum());
        u.setSumLogImpl(new Sum());
        u.addValue(1);
        u.addValue(3);
        Assert.assertEquals(4, u.getMean(), 1E-14);
        Assert.assertEquals(4, u.getSumOfLogs(), 1E-14);
        Assert.assertEquals(FastMath.exp(2), u.getGeometricMean(), 1E-14);

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    public void testSetterIllegalState() {
        SummaryStatistics u = createSummaryStatistics();
        u.addValue(1);
        u.addValue(3);
        try {
            u.setMeanImpl(new Sum());
            Assert.fail("Expecting IllegalStateException");
        } catch (IllegalStateException ex) {
            // expected
        }
    }

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            TestUtils.assertEquals(new Min().evaluate(values), dstats.getMin(), tol);
            TestUtils.assertEquals(dstats.getStandardDeviation(), sstats.getStandardDeviation(), tol);
            TestUtils.assertEquals(dstats.getVariance(), sstats.getVariance(), tol);
            TestUtils.assertEquals(new Variance().evaluate(values), dstats.getVariance(), tol);
            TestUtils.assertEquals(dstats.getSum(), sstats.getSum(), tol);
            TestUtils.assertEquals(new Sum().evaluate(values), dstats.getSum(), tol);
            TestUtils.assertEquals(dstats.getSumsq(), sstats.getSumsq(), tol);
            TestUtils.assertEquals(new SumOfSquares().evaluate(values), dstats.getSumsq(), tol);
            TestUtils.assertEquals(dstats.getPopulationVariance(), sstats.getPopulationVariance(), tol);
            TestUtils.assertEquals(new Variance(false).evaluate(values), dstats.getPopulationVariance(), tol);
        }

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        sumLogImpl  = new StorelessUnivariateStatistic[k];
        geoMeanImpl = new StorelessUnivariateStatistic[k];
        meanImpl    = new StorelessUnivariateStatistic[k];


        for (int i = 0; i < k; ++i) {
            sumImpl[i]     = new Sum();
            sumSqImpl[i]   = new SumOfSquares();
            minImpl[i]     = new Min();
            maxImpl[i]     = new Max();
            sumLogImpl[i]  = new SumOfLogs();
            geoMeanImpl[i] = new GeometricMean();

View Full Code Here

     *  parameters are not valid
     */
    @Override
    public double evaluate(final double[] values,final int begin, final int length) {
        if (test(values, begin, length)) {
            Sum sum = new Sum();
            double sampleSize = length;


            // Compute initial estimate using definitional formula
            double xbar = sum.evaluate(values, begin, length) / sampleSize;


            // Compute correction factor in second pass
            double correction = 0;
            for (int i = begin; i < begin + length; i++) {
                correction += values[i] - xbar;

View Full Code Here

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org.apache.commons.math3.analysis.differentiation.MultivariateDifferentiableVectorFunction

org.apache.commons.math3.analysis.function.HarmonicOscillator

org.apache.commons.math3.analysis.function.Sin

org.apache.commons.math3.analysis.function.Sinc

org.apache.commons.math3.analysis.MultivariateFunction

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org.apache.commons.math3.analysis.UnivariateFunction

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