Example usage for org.apache.commons.math3.stat.descriptive.rank Percentile Percentile

Introduction

In this page you can find the example usage for org.apache.commons.math3.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:org.hawkular.metrics.core.impl.GaugeBucketedOutputMapper.java

@Override
protected GaugeBucketDataPoint newPointInstance(long from, long to, List<DataPoint<Double>> dataPoints) {
    double[] values = new double[dataPoints.size()];
    for (ListIterator<DataPoint<Double>> iterator = dataPoints.listIterator(); iterator.hasNext();) {
        DataPoint<Double> gaugeData = iterator.next();
        values[iterator.previousIndex()] = gaugeData.getValue();
    }//from   w w w . j  ava2  s. co m

    Percentile percentile = new Percentile();
    percentile.setData(values);

    return new GaugeBucketDataPoint.Builder(from, to).setMin(new Min().evaluate(values))
            .setAvg(new Mean().evaluate(values)).setMedian(percentile.evaluate(50.0))
            .setMax(new Max().evaluate(values)).setPercentile95th(percentile.evaluate(95.0)).build();
}

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From source file:org.jpmml.evaluator.DoubleVector.java

public double percentile(int percentile) {

    if (this.values == null) {
        throw new IllegalStateException();
    }//from  w w  w .ja v  a2 s.c o m

    double[] data = new double[this.size];

    System.arraycopy(this.values, 0, data, 0, data.length);

    Arrays.sort(data);

    Percentile statistic = new Percentile();
    statistic.setData(data);

    return statistic.evaluate(percentile);
}

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From source file:org.jpmml.evaluator.functions.PercentileFunction.java

static private Double evaluate(Collection<?> values, int quantile) {
    List<Double> doubleValues = Lists.newArrayList();

    for (Object value : values) {
        Double doubleValue = (Double) TypeUtil.parseOrCast(DataType.DOUBLE, value);

        doubleValues.add(doubleValue);/* w  w w.  j a  v a  2  s.  com*/
    }

    double[] data = Doubles.toArray(doubleValues);

    // The data must be (at least partially) ordered
    Arrays.sort(data);

    Percentile percentile = new Percentile();
    percentile.setData(data);

    return percentile.evaluate(quantile);
}

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From source file:org.jpmml.evaluator.RegressionAggregator.java

static double median(List<Double> values) {
    double[] data = Doubles.toArray(values);

    // The data must be ordered
    Arrays.sort(data);/*from  w  w  w  .j  a v a2s  .c o  m*/

    Percentile percentile = new Percentile();
    percentile.setData(data);

    return percentile.evaluate(50);
}

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From source file:org.opencloudengine.flamingo.mapreduce.util.MathUtils.java

/**
 * Percentile? .//from  w w  w.  java2  s . com
 *
 * @param values   ? 
 * @param quantile ?  Quantile
 * @return Percentile
 */
public static double percentile(double[] values, double quantile) {
    Percentile percentile = new Percentile();
    return percentile.evaluate(values, quantile);
}

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From source file:org.openjdk.jmh.util.ListStatistics.java

@Override
public double getPercentile(double rank) {
    if (count == 0) {
        return Double.NaN;
    }/*from   w  w  w  . jav  a 2  s. com*/

    if (rank == 0) {
        return getMin();
    }

    // trim
    values = Arrays.copyOf(values, count);

    Percentile p = new Percentile();
    return p.evaluate(values, rank);
}

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From source file:org.orbisgis.sos.LeqStats.java

/**
 * Compute Leq stats using specified range.double[][] classRanges = ;
 * @param laOccurrencesRanges Min-Max range ex: new double[][]{{Double.MIN_VALUE, 45}, {45, 55}, {55, 65}, {65, 75},{75, Double.MAX_VALUE}}
 * @return LeqOccurrences instance//from ww  w  . j  av a2  s .  c o  m
 */
public LeqOccurrences computeLeqOccurrences(double[][] laOccurrencesRanges) {
    // Compute invert sum of class occurrences
    List<Double> classList = new ArrayList<>(leqClass.size());
    List<Integer> classValue = new ArrayList<>(leqClass.size());
    long sum = 0;
    double[] values = new double[rmsSumCount];
    int valCounter = 0;
    for (Map.Entry<Integer, AtomicInteger> entry : leqClass.entrySet()) {
        double leq = entry.getKey() * classStep;
        classList.add(leq);
        classValue.add(0, entry.getValue().get());
        sum += entry.getValue().get();
        for (int classValCount = 0; classValCount < entry.getValue().get(); classValCount++) {
            values[valCounter++] = leq;
        }
    }
    List<Double> sumClassValuePerc = new ArrayList<>(classValue.size());
    double invSum = 0.;
    for (int classVal : classValue) {
        invSum += classVal / (double) sum;
        sumClassValuePerc.add(0, invSum);
    }
    Percentile percentile = new Percentile();
    percentile.setData(values);
    // Fetch level at each lae
    double la10 = percentile.evaluate(100 - 10);
    double la50 = percentile.evaluate(50);
    double la90 = percentile.evaluate(100 - 90);

    // Sum percentage between provided laOccurrancesRanges
    List<Double> laOccurrencesRangesValue = new ArrayList<>();
    if (laOccurrencesRanges != null) {
        for (double[] range : laOccurrencesRanges) {
            double min = range[0];
            double max = range[1];
            double sumClass = 0;
            for (int idClass = 0; idClass < sumClassValuePerc.size(); idClass++) {
                if (classList.get(idClass) >= min) {
                    if (classList.get(idClass) < max) {
                        sumClass += classValue.get(sumClassValuePerc.size() - 1 - idClass) / (double) sum;
                    } else {
                        break;
                    }
                }
            }
            laOccurrencesRangesValue.add(sumClass);
        }
    }

    return new LeqOccurrences(la10, la50, la90, laOccurrencesRangesValue);
}

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From source file:uk.ac.diamond.scisoft.ncd.passerelle.actors.forkjoin.NcdImageStatsForkJoinTransformer.java

public NcdImageStatsForkJoinTransformer(CompositeEntity container, String name)
        throws NameDuplicationException, IllegalActionException {
    super(container, name);

    maskParam = new Parameter(this, "maskParam", new ObjectToken());
    sectorROIParam = new ROIParameter(this, "sectorROIParam");

    radiiMap = new HashMap<>(numSamples);
    percentile = new Percentile();
    percentiles = new double[numBins + 1];
    distance = new EuclideanDistance();
    resBins = new ArrayList<Set<Pair<Integer, Integer>>>(numBins);
}

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