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

Introduction

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

Prototype

public double getMean() 

Source Link

Document

Returns the <a href="http://www.xycoon.com/arithmetic_mean.htm"> arithmetic mean </a> of the available values

Usage

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

public static double getDirectDistanceMean(List<DynModeTrip> trips) {

    DescriptiveStatistics directDistanceStats = new DescriptiveStatistics();

    for (DynModeTrip trip : trips) {
        if (trip.getToLinkId() == null) {
            continue;
        }/*from   w w  w . j av a  2s.c  o  m*/

        directDistanceStats.addValue(trip.getUnsharedDistanceEstimate_m());
    }
    return directDistanceStats.getMean();
}

---

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   w  w w.j  a  va 2s . c  om*/
    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.drt.analysis.DynModeTripsAnalyser.java

/**
 * @param vehicleDistances//from w  w  w  .  ja  v a2  s  .  c  o  m
 * @param string
 * @return
 */
public static String summarizeVehicles(Map<Id<Vehicle>, double[]> vehicleDistances, String del) {
    DecimalFormat format = new DecimalFormat();
    format.setDecimalFormatSymbols(new DecimalFormatSymbols(Locale.US));
    format.setMinimumIntegerDigits(1);
    format.setMaximumFractionDigits(2);
    format.setGroupingUsed(false);

    DescriptiveStatistics driven = new DescriptiveStatistics();
    DescriptiveStatistics revenue = new DescriptiveStatistics();
    DescriptiveStatistics occupied = new DescriptiveStatistics();
    DescriptiveStatistics empty = new DescriptiveStatistics();

    for (double[] dist : vehicleDistances.values()) {
        driven.addValue(dist[0]);
        revenue.addValue(dist[1]);
        occupied.addValue(dist[2]);
        double emptyD = dist[0] - dist[2];
        empty.addValue(emptyD);
    }
    double d_r_d_t = revenue.getSum() / driven.getSum();
    // bw.write("iteration;vehicles;totalDistance;totalEmptyDistance;emptyRatio;totalRevenueDistance;averageDrivenDistance;averageEmptyDistance;averageRevenueDistance");
    String result = vehicleDistances.size() + del + format.format(driven.getSum()) + del
            + format.format(empty.getSum()) + del + format.format(empty.getSum() / driven.getSum()) + del
            + format.format(revenue.getSum()) + del + format.format(driven.getMean()) + del
            + format.format(empty.getMean()) + del + format.format(revenue.getMean()) + del
            + format.format(d_r_d_t);
    return result;
}

---

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());
}

---

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}.
 * //from   w w w  .  j  a  va  2s. co m
 * @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);
}

---

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

/**
 * Asserts that the statistical distribution satisfies the properties of an
 * integer-valued uniform distribution between {@code min} and {@code max}.
 * /*from  w ww .j a  v  a2s.  co  m*/
 * @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(int min, int max, DescriptiveStatistics statistics) {
    int n = max - min + 1;
    int nn = n * n;

    Assert.assertEquals((min + max) / 2.0, statistics.getMean(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals((nn - 1) / 12.0, statistics.getVariance(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(0.0, statistics.getSkewness(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(-(6.0 * (nn + 1)) / (5.0 * (nn - 1)), statistics.getKurtosis(),
            TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(min, statistics.getMin(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(max, statistics.getMax(), TestThresholds.STATISTICS_EPS);
}

---

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

/**
 * Asserts that the statistical distribution satisfies the properties of a
 * Gaussian distribution with the specified mean and standard deviation.
 * /*from w w  w.j  a  v  a2  s  .  co  m*/
 * @param mu the mean value of the distribution
 * @param sigma the standard deviation of the distribution
 * @param statistics the captures statistics of a sampled distribution
 */
private void testGaussianDistribution(double mu, double sigma, DescriptiveStatistics statistics) {
    Assert.assertEquals(mu, statistics.getMean(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(sigma * sigma, statistics.getVariance(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(0.0, statistics.getSkewness(), TestThresholds.STATISTICS_EPS);
    Assert.assertEquals(0.0, statistics.getKurtosis(), TestThresholds.STATISTICS_EPS);
}

---

From source file:org.moeaframework.TestUtils.java

/**
 * Asserts that the statistical distribution satisfies the properties of an
 * integer-valued uniform distribution between {@code min} and {@code max}.
 * /* w ww  .j  av  a  2  s.c o m*/
 * @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
 */
public static void assertUniformDistribution(int min, int max, DescriptiveStatistics statistics) {
    int n = max - min + 1;
    int nn = n * n;

    assertEquals((min + max) / 2.0, statistics.getMean());
    assertEquals((nn - 1) / 12.0, statistics.getVariance());
    assertEquals(0.0, statistics.getSkewness());
    assertEquals(-(6.0 * (nn + 1)) / (5.0 * (nn - 1)), statistics.getKurtosis());
    assertEquals(min, statistics.getMin());
    assertEquals(max, statistics.getMax());
}

---

From source file:org.moeaframework.util.sequence.SequenceTest.java

/**
 * Asserts that the collected statistics appear to be from a uniform
 * distribution.//from  w  ww. j  a va2s .c o m
 * 
 * @param min the minimum value
 * @param max the maximum value
 * @param statistics the collected statistics
 */
public 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);
}

---

From source file:org.mot.common.math.CalculatorFactory.java

public Double getAverage(Double[] data, Integer windowSize) {
    // Create a DescriptiveStats instance and set the window size to 100
    DescriptiveStatistics stats = new DescriptiveStatistics();
    stats.setWindowSize(windowSize);/*w  w  w . java  2  s  .c om*/

    for (int i = 0; i < data.length; i++) {
        if (data[i] != null) {
            stats.addValue(data[i]);
        } else {
            break;
        }
    }
    return stats.getMean();
}

---

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