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

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

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

org.apache.commons.math.stat.descriptive.summary.Sum
Returns the sum of the available values.
If there are no values in the dataset, or 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.
@version $Revision: 1006299 $ $Date: 2010-10-10 16:47:17 +0200 (dim. 10 oct. 2010) $

  StorelessUnivariateStatistic[] stats;


  public Stat() {
    min = new Min();
    max = new Max();
    sum = new Sum();
    mean = new Mean();
    sd = new StandardDeviation();


    stats = new StorelessUnivariateStatistic[] {min, max, sum, mean, sd};
  }

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        assertEquals(u, v);
        assertEquals(v, u);


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


    }

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        TestUtils.assertEquals("max",s.getMax(),u.getMax(),tolerance);
    }


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

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

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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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            }
        }


        int dfwg = 0;
        double sswg = 0;
        Sum totsum = new Sum();
        SumOfSquares totsumsq = new SumOfSquares();
        int totnum = 0;


        for (double[] data : categoryData) {


            Sum sum = new Sum();
            SumOfSquares sumsq = new SumOfSquares();
            int num = 0;


            for (int i = 0; i < data.length; i++) {
                double val = data[i];


                // within category
                num++;
                sum.increment(val);
                sumsq.increment(val);


                // for all categories
                totnum++;
                totsum.increment(val);
                totsumsq.increment(val);
            }
            dfwg += num - 1;
            double ss = sumsq.getResult() - sum.getResult() * sum.getResult() / num;
            sswg += ss;
        }
        double sst = totsumsq.getResult() - totsum.getResult() *
            totsum.getResult()/totnum;
        double ssbg = sst - sswg;

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     *  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;

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     * @since 2.1
     */
    public double evaluate(final double[] values, final double[] weights,
                           final int begin, final int length) {
        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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    /**
     * Construct a SummaryStatistics
     */
    public SummaryStatisticsImpl() {
        sum = new Sum();
        sumsq = new SumOfSquares();
        min = new Min();
        max = new Max();
        sumLog = new SumOfLogs();
        geoMean = new GeometricMean();

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    /**
     * Returns the sum of the values that have been added to Univariate.
     * @return The sum or Double.NaN if no values have been added
     */
    public double getSum() {
        return apply(new Sum());
    }

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