Example usage for org.apache.commons.math.stat.descriptive.rank Percentile Percentile

Introduction

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

Prototype

public Percentile() 

Source Link

Document

Constructs a Percentile with a default quantile value of 50.0.

Usage

From source file:com.discursive.jccook.math.StatExample.java

public static void main(String[] args) {
    double[] values = new double[] { 2.3, 5.4, 6.2, 7.3, 23.3 };

    System.out.println("min: " + StatUtils.min(values));
    System.out.println("max: " + StatUtils.max(values));
    System.out.println("mean: " + StatUtils.mean(values));
    System.out.println("product: " + StatUtils.product(values));
    System.out.println("sum: " + StatUtils.sum(values));
    System.out.println("variance: " + StatUtils.variance(values));

    // Measures from previous example
    Min min = new Min();
    System.out.println("min: " + min.evaluate(values));
    Max max = new Max();
    System.out.println("max: " + max.evaluate(values));
    Mean mean = new Mean();
    System.out.println("mean: " + mean.evaluate(values));
    Product product = new Product();
    System.out.println("product: " + product.evaluate(values));
    Sum sum = new Sum();
    System.out.println("sum: " + sum.evaluate(values));
    Variance variance = new Variance();
    System.out.println("variance: " + variance.evaluate(values));

    // New measures
    Percentile percentile = new Percentile();
    System.out.println("80 percentile value: " + percentile.evaluate(values, 80.0));
    GeometricMean geoMean = new GeometricMean();
    System.out.println("geometric mean: " + geoMean.evaluate(values));
    StandardDeviation stdDev = new StandardDeviation();
    System.out.println("standard dev: " + stdDev.evaluate(values));
    Skewness skewness = new Skewness();
    System.out.println("skewness: " + skewness.evaluate(values));
    Kurtosis kurtosis = new Kurtosis();
    System.out.println("kurtosis: " + kurtosis.evaluate(values));

}

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From source file:fr.ens.transcriptome.corsen.util.StatTest.java

public void testPercentile() {

    Percentile percentile = new Percentile();

    for (int j = 0; j < 10; j++) {
        for (int i = 0; i < 98; i++) {

            List<DataDouble> list = generate();
            double p = random.nextInt(99) + 1;

            assertEquals(percentile.evaluate(Stats.toDouble(list), p), Stats.percentile(list, p));

        }//  w  w w .j ava 2 s .  c  o m
    }

}

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From source file:geogebra.kernel.statistics.AlgoPercentile.java

protected final void compute() {

    //==========================
    // validation
    size = inputList.size();//from   w w  w . j  a  v a2  s. c o m
    if (!inputList.isDefined() || size == 0) {
        result.setUndefined();
        return;
    }

    if (value == null) {
        result.setUndefined();
        return;
    } else {
        val = value.getDouble() * 100;
    }

    if (val <= 0 || val > 100) {
        result.setUndefined();
        return;
    }

    //==========================
    // compute result

    inputArray = new double[size];

    // load input value array from  geoList
    for (int i = 0; i < size; i++) {
        GeoElement geo = inputList.get(i);
        if (geo.isNumberValue()) {
            NumberValue num = (NumberValue) geo;
            inputArray[i] = num.getDouble();
        } else {
            result.setUndefined();
            return;
        }
    }

    if (percentile == null)
        percentile = new Percentile();

    percentile.setData(inputArray);
    result.setValue(percentile.evaluate(val));
}

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From source file:geogebra.common.kernel.statistics.AlgoPercentile.java

@Override
public final void compute() {

    // ==========================
    // validation
    size = inputList.size();//from ww  w  . j a  va2s. c om
    if (!inputList.isDefined() || size == 0) {
        result.setUndefined();
        return;
    }

    if (value == null) {
        result.setUndefined();
        return;
    }
    val = value.getDouble() * 100;

    if (val <= 0 || val > 100) {
        result.setUndefined();
        return;
    }

    // ==========================
    // compute result

    inputArray = new double[size];

    // load input value array from geoList
    for (int i = 0; i < size; i++) {
        GeoElement geo = inputList.get(i);
        if (geo instanceof NumberValue) {
            NumberValue num = (NumberValue) geo;
            inputArray[i] = num.getDouble();
        } else {
            result.setUndefined();
            return;
        }
    }

    if (percentile == null)
        percentile = new Percentile();

    percentile.setData(inputArray);
    result.setValue(percentile.evaluate(val));
}

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From source file:fr.ens.transcriptome.corsen.util.StatTest.java

public void testFirstQuartile() {

    Percentile percentile = new Percentile();

    for (int i = 0; i < 1000; i++) {

        List<DataDouble> list = generate();
        assertEquals(percentile.evaluate(Stats.toDouble(list), 25.0), Stats.firstQuartile(list));
    }/*from  www. j  a  v  a  2s  . co  m*/
}

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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 w  w  .j  a v  a2 s  .  co 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:fr.ens.transcriptome.corsen.util.StatTest.java

public void testThirdQuartile() {

    Percentile percentile = new Percentile();

    for (int i = 0; i < 1000; i++) {

        List<DataDouble> list = generate();
        assertEquals(percentile.evaluate(Stats.toDouble(list), 75.0), Stats.thirdQuartile(list));
    }/* ww  w  .  j ava  2 s  . c o  m*/
}

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

/**
 * Mark Trial as done and calculate results.
 *///  w  w  w . j a va2 s .c o 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;
}

---

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

/**
 * Prints a summary of a successful trial result.
 *//*  w ww  .ja  v a 2  s .co  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();
}

---

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

/**
 * Prints a summary of a successful trial result.
 *///from  ww w  .j  a  va  2  s .  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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