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Java example source code file (MixedListUnivariateImplTest.java)

This example Java source code file (MixedListUnivariateImplTest.java) is included in the alvinalexander.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" TM.

Learn more about this Java project at its project page.

Java - Java tags/keywords

arraylist, bar, descriptivestatistics, footransformer, geometric, listunivariateimpl, mean, mixedlistunivariateimpltest, nan, numbertransformer, string, test, transformermap, util, variance

The MixedListUnivariateImplTest.java Java example source code

/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.commons.math3.stat.descriptive;

import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;


import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.util.NumberTransformer;
import org.apache.commons.math3.util.TransformerMap;
import org.junit.Assert;
import org.junit.Test;

/**
 * Test cases for the {@link ListUnivariateImpl} class.
 *
 */

public final class MixedListUnivariateImplTest {
    private double one = 1;
    private float two = 2;
    private int three = 3;

    private double mean = 2;
    private double sumSq = 18;
    private double sum = 8;
    private double var = 0.666666666666666666667;
    private double std = FastMath.sqrt(var);
    private double n = 4;
    private double min = 1;
    private double max = 3;
    private double tolerance = 10E-15;

    private TransformerMap transformers = new TransformerMap();

    public MixedListUnivariateImplTest() {
        transformers = new TransformerMap();

        transformers.putTransformer(Foo.class, new FooTransformer());

        transformers.putTransformer(Bar.class, new BarTransformer());

    }

    /** test stats */
    @Test
    public void testStats() {
        List<Object> externalList = new ArrayList();

        DescriptiveStatistics u = new ListUnivariateImpl(externalList,transformers);

        Assert.assertEquals("total count", 0, u.getN(), tolerance);
        u.addValue(one);
        u.addValue(two);
        u.addValue(two);
        u.addValue(three);
        Assert.assertEquals("N", n, u.getN(), tolerance);
        Assert.assertEquals("sum", sum, u.getSum(), tolerance);
        Assert.assertEquals("sumsq", sumSq, u.getSumsq(), tolerance);
        Assert.assertEquals("var", var, u.getVariance(), tolerance);
        Assert.assertEquals("std", std, u.getStandardDeviation(), tolerance);
        Assert.assertEquals("mean", mean, u.getMean(), tolerance);
        Assert.assertEquals("min", min, u.getMin(), tolerance);
        Assert.assertEquals("max", max, u.getMax(), tolerance);
        u.clear();
        Assert.assertEquals("total count", 0, u.getN(), tolerance);
    }

    @Test
    public void testN0andN1Conditions() {
        DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<Object>(),transformers);

        Assert.assertTrue(
            "Mean of n = 0 set should be NaN",
            Double.isNaN(u.getMean()));
        Assert.assertTrue(
            "Standard Deviation of n = 0 set should be NaN",
            Double.isNaN(u.getStandardDeviation()));
        Assert.assertTrue(
            "Variance of n = 0 set should be NaN",
            Double.isNaN(u.getVariance()));

        u.addValue(one);

        Assert.assertTrue(
            "Mean of n = 1 set should be value of single item n1, instead it is " + u.getMean() ,
            u.getMean() == one);

        Assert.assertTrue(
            "StdDev of n = 1 set should be zero, instead it is: "
                + u.getStandardDeviation(),
            u.getStandardDeviation() == 0);
        Assert.assertTrue(
            "Variance of n = 1 set should be zero",
            u.getVariance() == 0);
    }

    @Test
    public void testSkewAndKurtosis() {
        ListUnivariateImpl u =
            new ListUnivariateImpl(new ArrayList<Object>(), transformers);

        u.addObject("12.5");
        u.addObject(Integer.valueOf(12));
        u.addObject("11.8");
        u.addObject("14.2");
        u.addObject(new Foo());
        u.addObject("14.5");
        u.addObject(Long.valueOf(21));
        u.addObject("8.2");
        u.addObject("10.3");
        u.addObject("11.3");
        u.addObject(Float.valueOf(14.1f));
        u.addObject("9.9");
        u.addObject("12.2");
        u.addObject(new Bar());
        u.addObject("12.1");
        u.addObject("11");
        u.addObject(Double.valueOf(19.8));
        u.addObject("11");
        u.addObject("10");
        u.addObject("8.8");
        u.addObject("9");
        u.addObject("12.3");


        Assert.assertEquals("mean", 12.40455, u.getMean(), 0.0001);
        Assert.assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
        Assert.assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
        Assert.assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
    }

    @Test
    public void testProductAndGeometricMean() {
        ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<Object>(),transformers);
        u.setWindowSize(10);

        u.addValue(1.0);
        u.addValue(2.0);
        u.addValue(3.0);
        u.addValue(4.0);

        Assert.assertEquals(
            "Geometric mean not expected",
            2.213364,
            u.getGeometricMean(),
            0.00001);

        // Now test rolling - StorelessDescriptiveStatistics should discount the contribution
        // of a discarded element
        for (int i = 0; i < 10; i++) {
            u.addValue(i + 2);
        }
        // Values should be (2,3,4,5,6,7,8,9,10,11)
        Assert.assertEquals(
            "Geometric mean not expected",
            5.755931,
            u.getGeometricMean(),
            0.00001);

    }

    public static final class Foo {
        public String heresFoo() {
            return "14.9";
        }
    }

    public static final class FooTransformer implements NumberTransformer, Serializable {
        private static final long serialVersionUID = -4252248129291326127L;
        public double transform(Object o) {
            return Double.parseDouble(((Foo) o).heresFoo());
        }
    }

    public static final class Bar {
        public String heresBar() {
            return "12.0";
        }
    }

    public static final class BarTransformer implements NumberTransformer, Serializable {
        private static final long serialVersionUID = -1768345377764262043L;
        public double transform(Object o) {
            return Double.parseDouble(((Bar) o).heresBar());
        }
    }

}

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