Example usage for org.apache.commons.math.stat.descriptive DescriptiveStatistics DescriptiveStatistics

Introduction

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

Prototype

public DescriptiveStatistics(DescriptiveStatistics original) 

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Copy constructor.

Usage

From source file:com.jivesoftware.os.mlogger.core.Timer.java

public Timer(int sampleWindowSize) {
    this.stats = new DescriptiveStatistics(sampleWindowSize);
}

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From source file:asr.failure.FailureDetector.java

/**
 * Create a detector.// www.j  av a  2s . c o m
 * 
 * @param windowSize size of sampling window
 * @param minSamples minimum samples required for returning phi
 */
public FailureDetector(int windowSize, long minSamples) {
    samples = new DescriptiveStatistics(windowSize);
    this.minSamples = minSamples;
}

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From source file:jsprit.core.util.BenchmarkResult.java

public BenchmarkResult(BenchmarkInstance instance, int runs, double[] results, double[] compTimes,
        double[] vehicles) {
    super();//from  ww  w.j  av  a 2s  .co m
    this.results = results;
    this.runs = runs;
    this.times = compTimes;
    this.instance = instance;
    this.vehicles = vehicles;
    this.statsResults = new DescriptiveStatistics(results);
    this.statsTimes = new DescriptiveStatistics(times);
    this.statsVehicles = new DescriptiveStatistics(vehicles);
}

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From source file:dr.evomodel.epidemiology.casetocase.periodpriors.OneOverStDevPeriodPriorDistribution.java

public double calculateLogLikelihood(double[] values) {

    DescriptiveStatistics stats = new DescriptiveStatistics(values);

    logL = -Math.log(stats.getStandardDeviation());

    return logL;/*from  w w w  .j  av  a 2s  . c om*/

}

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From source file:com.luciddreamingapp.beta.util.audio.SimpleAudioAnalyser.java

/**
 * Create a WindMeter instance./*from   ww  w.  j a v  a 2s .com*/
 * 
  * @param   parent          Parent surface.
 */
public SimpleAudioAnalyser() {

    //   parentSurface = parent;

    audioReader = new AudioReader();
    statSound = new DescriptiveStatistics(60);
    statPower = new DescriptiveStatistics(60);

    // spectrumAnalyser = new FFTTransformer(inputBlockSize, windowFunction);

    biasRange = new float[2];
}

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From source file:com.google.caliper.runner.ConsoleResultProcessor.java

@Override
public void processTrial(Trial trial) {
    ImmutableListMultimap<String, Measurement> measurementsIndex = new ImmutableListMultimap.Builder<String, Measurement>()
            .orderKeysBy(Ordering.natural())
            .putAll(Multimaps.index(trial.measurements(), new Function<Measurement, String>() {
                @Override//from w  ww .j a v  a2 s  .  c o  m
                public String apply(Measurement input) {
                    return input.description();
                }
            })).build();
    for (Entry<String, Collection<Measurement>> entry : measurementsIndex.asMap().entrySet()) {
        Collection<Measurement> measurements = entry.getValue();
        ImmutableSet<String> units = FluentIterable.from(measurements)
                .transform(new Function<Measurement, String>() {
                    @Override
                    public String apply(Measurement input) {
                        return input.value().unit();
                    }
                }).toSet();
        double[] weightedValues = new double[measurements.size()];
        int i = 0;
        for (Measurement measurement : measurements) {
            weightedValues[i] = measurement.value().magnitude() / measurement.weight();
            i++;
        }
        Percentile percentile = new Percentile();
        percentile.setData(weightedValues);
        DescriptiveStatistics descriptiveStatistics = new DescriptiveStatistics(weightedValues);
        String unit = Iterables.getOnlyElement(units);
        stdout.printf("  %s%s: min=%.2f, 1st qu.=%.2f, median=%.2f, mean=%.2f, 3rd qu.=%.2f, max=%.2f%n",
                entry.getKey(), unit.isEmpty() ? "" : "(" + unit + ")", descriptiveStatistics.getMin(),
                percentile.evaluate(25), percentile.evaluate(50), descriptiveStatistics.getMean(),
                percentile.evaluate(75), descriptiveStatistics.getMax());
    }

    instrumentSpecs.add(trial.instrumentSpec());
    Scenario scenario = trial.scenario();
    vmSpecs.add(scenario.vmSpec());
    benchmarkSpecs.add(scenario.benchmarkSpec());
    numMeasurements += trial.measurements().size();
}

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From source file:dk.ilios.spanner.model.Trial.java

/**
 * Mark Trial as done and calculate results.
 *///  ww  w  .  ja  v a2s . co  m
public void calculateResults() {
    checkResultsCalculated(false);

    double[] weightedValues = new double[measurements.size()];
    int i = 0;
    for (Measurement measurement : measurements) {
        weightedValues[i] = measurement.value().magnitude() / measurement.weight();
        i++;
    }
    percentile = new Percentile();
    percentile.setData(weightedValues);
    descriptiveStatistics = new DescriptiveStatistics(weightedValues);
    if (experiment.getBaseline() != null) {
        experiment.getBaseline().calculateResults();
    }
    resultsCalculated = true;
}

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From source file:dk.ilios.spanner.internal.ConsoleOutput.java

/**
 * Prints a summary of a successful trial result.
 *//*from  ww  w .  ja  v a 2 s  .c  o  m*/
void processTrial(Trial.Result result) {
    Trial baseline = result.getExperiment().getBaseline();

    trialsCompleted++;

    stdout.printf("Trial Report (%d of %d):%n  Experiment %s%n", trialsCompleted, numberOfTrials,
            result.getExperiment());
    if (!result.getTrialMessages().isEmpty()) {
        stdout.println("  Messages:");
        for (String message : result.getTrialMessages()) {
            stdout.print("    ");
            stdout.println(message);
        }
    }
    Trial trial = result.getTrial();

    // Group measurements by their description
    // TODO Why? All measurements for a single trial should have the same description
    ImmutableListMultimap<String, Measurement> measurementsIndex = new ImmutableListMultimap.Builder<String, Measurement>()
            .orderKeysBy(Ordering.natural())
            .putAll(Multimaps.index(trial.measurements(), new Function<Measurement, String>() {
                @Override
                public String apply(Measurement input) {
                    return input.description();
                }
            })).build();

    stdout.println("  Results:");
    for (Map.Entry<String, Collection<Measurement>> entry : measurementsIndex.asMap().entrySet()) {

        Collection<Measurement> measurements = entry.getValue();
        String unit = measurements.iterator().next().value().unit();

        double[] weightedValues = new double[measurements.size()];
        int i = 0;
        for (Measurement measurement : measurements) {
            weightedValues[i] = measurement.value().magnitude() / measurement.weight();
            i++;
        }
        Percentile percentile = new Percentile();
        percentile.setData(weightedValues);
        DescriptiveStatistics descriptiveStatistics = new DescriptiveStatistics(weightedValues);
        stdout.printf("    %s%s: min=%.2f, 1st qu.=%.2f, median=%.2f (%s), mean=%.2f, 3rd qu.=%.2f, max=%.2f%n",
                entry.getKey(), unit.isEmpty() ? "" : "(" + unit + ")", descriptiveStatistics.getMin(),
                percentile.evaluate(25), percentile.evaluate(50),
                calculateDiff(percentile.evaluate(50), baseline), descriptiveStatistics.getMean(),
                percentile.evaluate(75), descriptiveStatistics.getMax());
    }

    instrumentSpecs.add(trial.instrumentSpec());
    Scenario scenario = trial.scenario();
    benchmarkSpecs.add(scenario.benchmarkSpec());
    numMeasurements += trial.measurements().size();
}

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From source file:com.google.caliper.runner.ConsoleOutput.java

/**
 * Prints a summary of a successful trial result.
 *///  w  ww. j  a va2s . c om
void processTrial(TrialResult result) {
    trialsCompleted++;
    stdout.printf("Trial Report (%d of %d):%n  Experiment %s%n", trialsCompleted, numberOfTrials,
            result.getExperiment());
    if (!result.getTrialMessages().isEmpty()) {
        stdout.println("  Messages:");
        for (String message : result.getTrialMessages()) {
            stdout.print("    ");
            stdout.println(message);
        }
    }
    Trial trial = result.getTrial();
    ImmutableListMultimap<String, Measurement> measurementsIndex = new ImmutableListMultimap.Builder<String, Measurement>()
            .orderKeysBy(Ordering.natural())
            .putAll(Multimaps.index(trial.measurements(), new Function<Measurement, String>() {
                @Override
                public String apply(Measurement input) {
                    return input.description();
                }
            })).build();
    stdout.println("  Results:");
    for (Entry<String, Collection<Measurement>> entry : measurementsIndex.asMap().entrySet()) {
        Collection<Measurement> measurements = entry.getValue();
        ImmutableSet<String> units = FluentIterable.from(measurements)
                .transform(new Function<Measurement, String>() {
                    @Override
                    public String apply(Measurement input) {
                        return input.value().unit();
                    }
                }).toSet();
        double[] weightedValues = new double[measurements.size()];
        int i = 0;
        for (Measurement measurement : measurements) {
            weightedValues[i] = measurement.value().magnitude() / measurement.weight();
            i++;
        }
        Percentile percentile = new Percentile();
        percentile.setData(weightedValues);
        DescriptiveStatistics descriptiveStatistics = new DescriptiveStatistics(weightedValues);
        String unit = Iterables.getOnlyElement(units);
        stdout.printf("    %s%s: min=%.2f, 1st qu.=%.2f, median=%.2f, mean=%.2f, 3rd qu.=%.2f, max=%.2f%n",
                entry.getKey(), unit.isEmpty() ? "" : "(" + unit + ")", descriptiveStatistics.getMin(),
                percentile.evaluate(25), percentile.evaluate(50), descriptiveStatistics.getMean(),
                percentile.evaluate(75), descriptiveStatistics.getMax());
    }

    instrumentSpecs.add(trial.instrumentSpec());
    Scenario scenario = trial.scenario();
    vmSpecs.add(scenario.vmSpec());
    benchmarkSpecs.add(scenario.benchmarkSpec());
    numMeasurements += trial.measurements().size();
}

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From source file:org.apache.gossip.accrual.FailureDetector.java

public FailureDetector(long minimumSamples, int windowSize, String distribution) {
    descriptiveStatistics = new DescriptiveStatistics(windowSize);
    this.minimumSamples = minimumSamples;
    this.distribution = distribution;
}

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