Example usage for org.apache.commons.math.stat.descriptive.rank Max evaluate

Introduction

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

Prototype

@Override
public double evaluate(final double[] values) 

Source Link

Document

This default implementation calls #clear , then invokes #increment in a loop over the the input array, and then uses #getResult to compute the return value.

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 testMax() {

    Max max = new Max();

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

        List<DataDouble> list = generate();
        assertEquals(max.evaluate(Stats.toDouble(list)), Stats.max(list));
    }/*from   ww w  .j a  va2s  . co  m*/
}

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From source file:net.sf.jtmt.clustering.Cluster.java

/**
 * Gets the complete linkage distance./*from w  w w  .  j av  a2  s.  com*/
 *
 * @param doc the doc
 * @return the complete linkage distance
 */
public double getCompleteLinkageDistance(RealMatrix doc) {
    Max max = new Max();
    if (docs.size() == 0) {
        return 0.0D;
    }
    double[] distances = new double[docs.size()];
    for (int i = 0; i < distances.length; i++) {
        RealMatrix clusterDoc = docs.get(docNames.get(i));
        distances[i] = clusterDoc.subtract(doc).getFrobeniusNorm();
    }
    return max.evaluate(distances);
}

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