Examples of org.apache.commons.math3.stat.descriptive.SummaryStatistics.addValue()

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

Class org.apache.commons.math3.stat.descriptive.SummaryStatistics

Examples of org.apache.commons.math3.stat.descriptive.SummaryStatistics.addValue()

org.apache.commons.math3.stat.descriptive.SummaryStatistics.addValue()
Add a value to the data @param value the value to add

            integ.integrate(brusselator, 0, y, 20.0, y);
            double[] yP = { 1.3, b + hP };
            brusselator.setParameter("b", 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);

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//            Assert.assertEquals(5000, integ.getMaxEvaluations());
//            Assert.assertTrue(integ.getEvaluations() > 1500);
//            Assert.assertTrue(integ.getEvaluations() < 2100);
//            Assert.assertEquals(4 * integ.getEvaluations(), integ.getEvaluations());
            residualsP0.addValue(dZdP[0] - brusselator.dYdP0());
            residualsP1.addValue(dZdP[1] - 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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            jacob.getCurrentParameterJacobian(Brusselator.B, dZdP);
//            Assert.assertEquals(5000, integ.getMaxEvaluations());
//            Assert.assertTrue(integ.getEvaluations() > 350);
//            Assert.assertTrue(integ.getEvaluations() < 510);
            residualsP0.addValue(dZdP[0] - brusselator.dYdP0());
            residualsP1.addValue(dZdP[1] - 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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        while (line != null) {
            if (d != null) {
                d.addValue(Double.parseDouble(line.trim()));
            }  else {
                s.addValue(Double.parseDouble(line.trim()));
            }
            line = in.readLine();
        }


        resourceAsStream.close();

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        } catch (MathIllegalArgumentException ex) {
            // ignored
        }
        SummaryStatistics u = new SummaryStatistics();
        for (int i = 0; i < largeSampleSize; i++) {
            u.addValue(randomData.nextGaussian(0, 1));
        }
        double xbar = u.getMean();
        double s = u.getStandardDeviation();
        double n = u.getN();
        /*

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    List<Long> timestamps = getSortedTimestamps(entries);


    SummaryStatistics stats = new SummaryStatistics();
    for (int i = 0; i < timestamps.size() - 1; i++) {
      long diff = Math.abs(timestamps.get(i) - timestamps.get(i + 1));
      stats.addValue(diff);
    }
    return (long) stats.getMean();
  }


  public static List<Long> getSortedTimestamps(List<FeedEntry> entries) {

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      Map<ScoreType, Double> scores = rouge.evaluate();


      rss.addValue(scores.get(ScoreType.R));
      pss.addValue(scores.get(ScoreType.P));
      fss.addValue(scores.get(ScoreType.F));
  }


  boolean calculateConfidenceInterval = parsedArgs.getBoolean(Config.CONFIDENCE.toString());
  double confidence = 0;
  if (calculateConfidenceInterval)

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    private void tstGen(double tolerance)throws Exception {
        empiricalDistribution.load(url);
        empiricalDistribution.reSeed(1000);
        SummaryStatistics stats = new SummaryStatistics();
        for (int i = 1; i < 1000; i++) {
            stats.addValue(empiricalDistribution.getNextValue());
        }
        Assert.assertEquals("mean", 5.069831575018909, stats.getMean(),tolerance);
        Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(),tolerance);
    }

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    private void tstDoubleGen(double tolerance)throws Exception {
        empiricalDistribution2.load(dataArray);
        empiricalDistribution2.reSeed(1000);
        SummaryStatistics stats = new SummaryStatistics();
        for (int i = 1; i < 1000; i++) {
            stats.addValue(empiricalDistribution2.getNextValue());
        }
        Assert.assertEquals("mean", 5.069831575018909, stats.getMean(), tolerance);
        Assert.assertEquals("std dev", 1.0173699343977738, stats.getStandardDeviation(), tolerance);
    }
}

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        final int len = methods.length;
        final StatisticalSummary[] stats = new StatisticalSummary[len];
        for (int j = 0; j < len; j++) {
            final SummaryStatistics s = new SummaryStatistics();
            for (int k = 0; k < repeatStat; k++) {
                s.addValue(times[j][k][0]);
            }
            stats[j] = s.getSummary();
        }


        return stats;

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