Example usage for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getMin

Introduction

In this page you can find the example usage for org.apache.commons.math3.stat.descriptive DescriptiveStatistics getMin.

Prototype

public double getMin() 

Source Link

Document

Returns the minimum of the available values

Usage

From source file:org.jenetics.stat.DoubleMomentStatisticsTest.java

@Test(dataProvider = "parallelSampleCounts")
public void parallelSummary(final Integer sampleCounts, final Double epsilon) {
    final List<Double> numbers = numbers(sampleCounts);

    final DescriptiveStatistics expected = new DescriptiveStatistics();
    numbers.forEach(expected::addValue);

    final DoubleMomentStatistics summary = numbers.parallelStream()
            .collect(toDoubleMomentStatistics(Double::doubleValue));

    Assert.assertEquals(summary.getCount(), numbers.size());
    assertEqualsDouble(min(summary.getMin()), expected.getMin(), 0.0);
    assertEqualsDouble(max(summary.getMax()), expected.getMax(), 0.0);
    assertEqualsDouble(summary.getSum(), expected.getSum(), epsilon);
    assertEqualsDouble(summary.getMean(), expected.getMean(), epsilon);
    assertEqualsDouble(summary.getVariance(), expected.getVariance(), epsilon);
    assertEqualsDouble(summary.getSkewness(), expected.getSkewness(), epsilon);
    assertEqualsDouble(summary.getKurtosis(), expected.getKurtosis(), epsilon);
}

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From source file:org.jenetics.stat.IntMomentStatisticsTest.java

@Test(dataProvider = "sampleCounts")
public void summary(final Integer sampleCounts, final Double epsilon) {
    final List<Integer> numbers = numbers(sampleCounts);

    final DescriptiveStatistics expected = new DescriptiveStatistics();
    numbers.forEach(expected::addValue);

    final IntMomentStatistics summary = numbers.stream().collect(toIntMomentStatistics(Integer::intValue));

    Assert.assertEquals(summary.getCount(), numbers.size());
    assertEqualsDouble(min(summary.getMin()), expected.getMin(), 0.0);
    assertEqualsDouble(max(summary.getMax()), expected.getMax(), 0.0);
    assertEqualsDouble(summary.getSum(), expected.getSum(), epsilon);
    assertEqualsDouble(summary.getMean(), expected.getMean(), epsilon);
    assertEqualsDouble(summary.getVariance(), expected.getVariance(), epsilon);
    assertEqualsDouble(summary.getSkewness(), expected.getSkewness(), epsilon);
    assertEqualsDouble(summary.getKurtosis(), expected.getKurtosis(), epsilon);
}

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From source file:org.jenetics.stat.IntMomentStatisticsTest.java

@Test(dataProvider = "parallelSampleCounts")
public void parallelSummary(final Integer sampleCounts, final Double epsilon) {
    final List<Integer> numbers = numbers(sampleCounts);

    final DescriptiveStatistics expected = new DescriptiveStatistics();
    numbers.forEach(expected::addValue);

    final IntMomentStatistics summary = numbers.parallelStream()
            .collect(toIntMomentStatistics(Integer::intValue));

    Assert.assertEquals(summary.getCount(), numbers.size());
    assertEqualsDouble(min(summary.getMin()), expected.getMin(), 0.0);
    assertEqualsDouble(max(summary.getMax()), expected.getMax(), 0.0);
    assertEqualsDouble(summary.getSum(), expected.getSum(), epsilon);
    assertEqualsDouble(summary.getMean(), expected.getMean(), epsilon);
    assertEqualsDouble(summary.getVariance(), expected.getVariance(), epsilon);
    assertEqualsDouble(summary.getSkewness(), expected.getSkewness(), epsilon);
    assertEqualsDouble(summary.getKurtosis(), expected.getKurtosis(), epsilon);
}

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From source file:org.jenetics.stat.LongMomentStatisticsTest.java

@Test(dataProvider = "sampleCounts")
public void summary(final Integer sampleCounts, final Double epsilon) {
    final List<Long> numbers = numbers(sampleCounts);

    final DescriptiveStatistics expected = new DescriptiveStatistics();
    numbers.forEach(expected::addValue);

    final LongMomentStatistics summary = numbers.stream().collect(toLongMomentStatistics(Long::longValue));

    Assert.assertEquals(summary.getCount(), numbers.size());
    assertEqualsDouble(min(summary.getMin()), expected.getMin(), 0.0);
    assertEqualsDouble(max(summary.getMax()), expected.getMax(), 0.0);
    assertEqualsDouble(summary.getSum(), expected.getSum(), epsilon);
    assertEqualsDouble(summary.getMean(), expected.getMean(), epsilon);
    assertEqualsDouble(summary.getVariance(), expected.getVariance(), epsilon);
    assertEqualsDouble(summary.getSkewness(), expected.getSkewness(), epsilon);
    assertEqualsDouble(summary.getKurtosis(), expected.getKurtosis(), epsilon);
}

---

From source file:org.jenetics.stat.LongMomentStatisticsTest.java

@Test(dataProvider = "parallelSampleCounts")
public void parallelSummary(final Integer sampleCounts, final Double epsilon) {
    final List<Long> numbers = numbers(sampleCounts);

    final DescriptiveStatistics expected = new DescriptiveStatistics();
    numbers.forEach(expected::addValue);

    final LongMomentStatistics summary = numbers.stream().collect(toLongMomentStatistics(Long::longValue));

    Assert.assertEquals(summary.getCount(), numbers.size());
    assertEqualsDouble(min(summary.getMin()), expected.getMin(), 0.0);
    assertEqualsDouble(max(summary.getMax()), expected.getMax(), 0.0);
    assertEqualsDouble(summary.getSum(), expected.getSum(), epsilon);
    assertEqualsDouble(summary.getMean(), expected.getMean(), epsilon);
    assertEqualsDouble(summary.getVariance(), expected.getVariance(), epsilon);
    assertEqualsDouble(summary.getSkewness(), expected.getSkewness(), epsilon);
    assertEqualsDouble(summary.getKurtosis(), expected.getKurtosis(), epsilon);
}

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From source file:org.lightjason.agentspeak.action.buildin.math.statistic.EStatisticValue.java

/**
 * returns a statistic value/*from  www . j  a v a2s.c  o m*/
 *
 * @param p_statistic statistic object
 * @return statistic value
 */
public final double value(final DescriptiveStatistics p_statistic) {
    switch (this) {
    case GEOMETRICMEAN:
        return p_statistic.getGeometricMean();

    case MAX:
        return p_statistic.getMax();

    case MIN:
        return p_statistic.getMin();

    case COUNT:
        return p_statistic.getN();

    case POPULATIONVARIANCE:
        return p_statistic.getPopulationVariance();

    case QUADRATICMEAN:
        return p_statistic.getQuadraticMean();

    case STANDARDDEVIATION:
        return p_statistic.getStandardDeviation();

    case SUM:
        return p_statistic.getSum();

    case SUMSQUARE:
        return p_statistic.getSumsq();

    case VARIANCE:
        return p_statistic.getVariance();

    case MEAN:
        return p_statistic.getMean();

    case KURTIOSIS:
        return p_statistic.getKurtosis();

    default:
        throw new CIllegalStateException(
                org.lightjason.agentspeak.common.CCommon.languagestring(this, "unknown", this));
    }
}

---

From source file:org.lightjason.agentspeak.action.builtin.math.statistic.EStatisticValue.java

/**
 * returns a statistic value/*from   www  .  j  a v a 2  s  . com*/
 *
 * @param p_statistic statistic object
 * @return statistic value
 */
public final double value(@Nonnull final DescriptiveStatistics p_statistic) {
    switch (this) {
    case GEOMETRICMEAN:
        return p_statistic.getGeometricMean();

    case MAX:
        return p_statistic.getMax();

    case MIN:
        return p_statistic.getMin();

    case COUNT:
        return p_statistic.getN();

    case POPULATIONVARIANCE:
        return p_statistic.getPopulationVariance();

    case QUADRATICMEAN:
        return p_statistic.getQuadraticMean();

    case STANDARDDEVIATION:
        return p_statistic.getStandardDeviation();

    case SUM:
        return p_statistic.getSum();

    case SUMSQUARE:
        return p_statistic.getSumsq();

    case VARIANCE:
        return p_statistic.getVariance();

    case MEAN:
        return p_statistic.getMean();

    case KURTIOSIS:
        return p_statistic.getKurtosis();

    default:
        throw new CIllegalStateException(
                org.lightjason.agentspeak.common.CCommon.languagestring(this, "unknown", this));
    }
}

---

From source file:org.matsim.contrib.drt.analysis.DynModeTripsAnalyser.java

public static void analyseWaitTimes(String fileName, List<DynModeTrip> trips, int binsize_s) {
    Collections.sort(trips);/*from  ww w.jav a  2 s. c o  m*/
    if (trips.size() == 0)
        return;
    int startTime = ((int) (trips.get(0).getDepartureTime() / binsize_s)) * binsize_s;
    int endTime = ((int) (trips.get(trips.size() - 1).getDepartureTime() / binsize_s) + binsize_s) * binsize_s;
    Map<Double, List<DynModeTrip>> splitTrips = splitTripsIntoBins(trips, startTime, endTime, binsize_s);

    DecimalFormat format = new DecimalFormat();
    format.setDecimalFormatSymbols(new DecimalFormatSymbols(Locale.US));
    format.setMinimumIntegerDigits(1);
    format.setMaximumFractionDigits(2);
    format.setGroupingUsed(false);

    SimpleDateFormat sdf2 = new SimpleDateFormat("HH:mm:ss");

    BufferedWriter bw = IOUtils.getBufferedWriter(fileName + ".csv");
    TimeSeriesCollection dataset = new TimeSeriesCollection();
    TimeSeriesCollection datasetrequ = new TimeSeriesCollection();
    TimeSeries averageWaitC = new TimeSeries("average");
    TimeSeries medianWait = new TimeSeries("median");
    TimeSeries p_5Wait = new TimeSeries("5th percentile");
    TimeSeries p_95Wait = new TimeSeries("95th percentile");
    TimeSeries requests = new TimeSeries("Ride requests");

    try {
        bw.write("timebin;trips;average_wait;min;p_5;p_25;median;p_75;p_95;max");
        for (Entry<Double, List<DynModeTrip>> e : splitTrips.entrySet()) {
            long rides = 0;
            double averageWait = 0;
            double min = 0;
            double p_5 = 0;
            double p_25 = 0;
            double median = 0;
            double p_75 = 0;
            double p_95 = 0;
            double max = 0;
            if (!e.getValue().isEmpty()) {
                DescriptiveStatistics stats = new DescriptiveStatistics();
                for (DynModeTrip t : e.getValue()) {
                    stats.addValue(t.getWaitTime());
                }
                rides = stats.getN();
                averageWait = stats.getMean();
                min = stats.getMin();
                p_5 = stats.getPercentile(5);
                p_25 = stats.getPercentile(25);
                median = stats.getPercentile(50);
                p_75 = stats.getPercentile(75);
                p_95 = stats.getPercentile(95);
                max = stats.getMax();

            }
            Minute h = new Minute(sdf2.parse(Time.writeTime(e.getKey())));

            medianWait.addOrUpdate(h, Double.valueOf(median));
            averageWaitC.addOrUpdate(h, Double.valueOf(averageWait));
            p_5Wait.addOrUpdate(h, Double.valueOf(p_5));
            p_95Wait.addOrUpdate(h, Double.valueOf(p_95));
            requests.addOrUpdate(h, rides * 3600. / binsize_s);// normalised [req/h]
            bw.newLine();
            bw.write(Time.writeTime(e.getKey()) + ";" + rides + ";" + format.format(averageWait) + ";"
                    + format.format(min) + ";" + format.format(p_5) + ";" + format.format(p_25) + ";"
                    + format.format(median) + ";" + format.format(p_75) + ";" + format.format(p_95) + ";"
                    + format.format(max));

        }
        bw.flush();
        bw.close();
        dataset.addSeries(averageWaitC);
        dataset.addSeries(medianWait);
        dataset.addSeries(p_5Wait);
        dataset.addSeries(p_95Wait);
        datasetrequ.addSeries(requests);
        JFreeChart chart = chartProfile(splitTrips.size(), dataset, "Waiting times", "Wait time (s)");
        JFreeChart chart2 = chartProfile(splitTrips.size(), datasetrequ, "Ride requests per hour",
                "Requests per hour (req/h)");
        ChartSaveUtils.saveAsPNG(chart, fileName, 1500, 1000);
        ChartSaveUtils.saveAsPNG(chart2, fileName + "_requests", 1500, 1000);

    } catch (IOException | ParseException e) {

        e.printStackTrace();
    }

}

---

From source file:org.matsim.contrib.taxi.util.stats.TaxiStatsWriter.java

private void addStats(CSVLineBuilder lineBuilder, String format1, String format2, DescriptiveStatistics stats) {
    lineBuilder.addf(format1, stats.getMean()).//
            addf(format1, stats.getStandardDeviation()).//
            addEmpty().//
            addf(format2, stats.getMin()). //
            addf(format2, stats.getPercentile(2)). //
            addf(format2, stats.getPercentile(5)). //
            addf(format2, stats.getPercentile(25)). //
            addf(format2, stats.getPercentile(50)). //
            addf(format2, stats.getPercentile(75)). //
            addf(format2, stats.getPercentile(95)). //
            addf(format2, stats.getPercentile(98)). //
            addf(format2, stats.getMax());
}

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From source file:org.moeaframework.core.PRNGTest.java

/**
 * Asserts that the statistical distribution satisfies the properties of a
 * real-valued uniform distribution between {@code min} and {@code max}.
 * // w  ww .  java 2s  .c om
 * @param min the minimum bounds of the uniform distribution
 * @param max the maximum bounds of the uniform distribution
 * @param statistics the captures statistics of a sampled distribution
 */
private void testUniformDistribution(double min, double max, DescriptiveStatistics statistics) {
    Assert.assertEquals((min + max) / 2.0, statistics.getMean(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(Math.pow(max - min, 2.0) / 12.0, statistics.getVariance(),
            TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(0.0, statistics.getSkewness(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(-6.0 / 5.0, statistics.getKurtosis(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(min, statistics.getMin(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(max, statistics.getMax(), TestThresholds.STATISTICS_EPS);
}

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