Example usage for org.apache.commons.math3.random EmpiricalDistribution EmpiricalDistribution

Introduction

In this page you can find the example usage for org.apache.commons.math3.random EmpiricalDistribution EmpiricalDistribution.

Prototype

public EmpiricalDistribution() 

Source Link

Document

Creates a new EmpiricalDistribution with the default bin count.

Usage

From source file:org.apache.solr.client.solrj.io.eval.EmpiricalDistributionEvaluator.java

@Override
public Object doWork(Object value) throws IOException {

    if (!(value instanceof List<?>)) {
        throw new StreamEvaluatorException("List value expected but found type %s for value %s",
                value.getClass().getName(), value.toString());
    }//  w  ww .  ja v  a  2  s. c  om

    EmpiricalDistribution empiricalDistribution = new EmpiricalDistribution();

    double[] backingValues = ((List<?>) value).stream()
            .mapToDouble(innerValue -> ((BigDecimal) innerValue).doubleValue()).sorted().toArray();
    empiricalDistribution.load(backingValues);

    return empiricalDistribution;
}

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From source file:org.apache.solr.client.solrj.io.stream.eval.EmpiricalDistributionEvaluatorTest.java

@Test
public void test() throws IOException {
    double[] l1 = new double[] { 3.4, 4.5, 6.7 };
    double[] l2 = new double[] { 1.2, 3.2, 3 };

    values.clear();/*from  w  w w.  j  a va  2 s. co  m*/
    values.put("l1", l1);
    values.put("l2", l2);

    EmpiricalDistribution dist = new EmpiricalDistribution();
    dist.load(l1);
    Assert.assertEquals(dist.getNumericalMean(),
            ((EmpiricalDistribution) factory.constructEvaluator("emp(l1)").evaluate(new Tuple(values)))
                    .getNumericalMean());
}

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