praktikum-holons/jars/jfreechart-1.0.19/tests/org/jfree/data/statistics/StatisticsTest.java

/* ===========================================================
 * JFreeChart : a free chart library for the Java(tm) platform
 * ===========================================================
 *
 * (C) Copyright 2000-2013, by Object Refinery Limited and Contributors.
 *
 * Project Info:  http://www.jfree.org/jfreechart/index.html
 *
 * This library is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as published by
 * the Free Software Foundation; either version 2.1 of the License, or
 * (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful, but
 * WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY
 * or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public
 * License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with this library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301,
 * USA.
 *
 * [Oracle and Java are registered trademarks of Oracle and/or its affiliates. 
 * Other names may be trademarks of their respective owners.]
 *
 * -------------------
 * StatisticsTest.java
 * -------------------
 * (C) Copyright 2004-2013, by Object Refinery Limited and Contributors.
 *
 * Original Author:  David Gilbert (for Object Refinery Limited);
 * Contributor(s):   -;
 *
 * Changes
 * -------
 * 25-Mar-2004 : Version 1 (DG);
 * 04-Oct-2004 : Eliminated NumberUtils usage (DG);
 *
 */

package org.jfree.data.statistics;

import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;

import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.List;
import org.junit.Test;

/**
 * Tests for the {@link Statistics} class.
 */
public class StatisticsTest {

    /**
     * Some checks for the calculateMean(Number[]) and
     * calculateMean(Number[], boolean) methods.
     */
    @Test
    public void testCalculateMean_Array() {

        // try null array
        boolean pass = false;
        try {
            Statistics.calculateMean((Number[]) null);
        }
        catch (IllegalArgumentException e) {
            pass = true;
        }
        assertTrue(pass);

        pass = false;
        try {
            Statistics.calculateMean((Number[]) null, false);
        }
        catch (IllegalArgumentException e) {
            pass = true;
        }
        assertTrue(pass);

        // try an array containing no items
        assertTrue(Double.isNaN(Statistics.calculateMean(new Number[0])));
        assertTrue(Double.isNaN(Statistics.calculateMean(new Number[0],
                false)));

        // try an array containing a single Number
        Number[] values = new Number[] {new Double(1.0)};
        assertEquals(1.0, Statistics.calculateMean(values), EPSILON);
        assertEquals(1.0, Statistics.calculateMean(values, true), EPSILON);
        assertEquals(1.0, Statistics.calculateMean(values, false), EPSILON);

        // try an array containing a single Number and a null
        values = new Number[] {new Double(1.0), null};
        assertTrue(Double.isNaN(Statistics.calculateMean(values)));
        assertTrue(Double.isNaN(Statistics.calculateMean(values, true)));
        assertEquals(1.0, Statistics.calculateMean(values, false), EPSILON);

        // try an array containing a single Number and a NaN
        values = new Number[] {new Double(1.0), new Double(Double.NaN)};
        assertTrue(Double.isNaN(Statistics.calculateMean(values)));
        assertTrue(Double.isNaN(Statistics.calculateMean(values, true)));
        assertEquals(1.0, Statistics.calculateMean(values, false), EPSILON);
    }

    /**
     * Some checks for the calculateMean(Collection) and
     * calculateMean(Collection, boolean) methods.
     */
    @Test
    public void testCalculateMean_Collection() {

        // try a null collection
        boolean pass = false;
        try {
            Statistics.calculateMean((Collection) null);
        }
        catch (IllegalArgumentException e) {
            pass = true;
        }
        assertTrue(pass);

        pass = false;
        try {
            Statistics.calculateMean((Collection) null, false);
        }
        catch (IllegalArgumentException e) {
            pass = true;
        }
        assertTrue(pass);

        // try an empty collection
        List values = new ArrayList();
        assertTrue(Double.isNaN(Statistics.calculateMean(values)));
        assertTrue(Double.isNaN(Statistics.calculateMean(values, true)));
        assertTrue(Double.isNaN(Statistics.calculateMean(values, false)));

        // try a collection with a single number
        values.add(new Double(9.0));
        assertEquals(9.0, Statistics.calculateMean(values), EPSILON);
        assertEquals(9.0, Statistics.calculateMean(values, true), EPSILON);
        assertEquals(9.0, Statistics.calculateMean(values, false), EPSILON);

        // try a collection with a single number plus a null
        values.add(null);
        assertTrue(Double.isNaN(Statistics.calculateMean(values)));
        assertTrue(Double.isNaN(Statistics.calculateMean(values, true)));
        assertEquals(9.0, Statistics.calculateMean(values, false), EPSILON);

        // try a collection with a single number plus a NaN
        values.clear();
        values.add(new Double(9.0));
        values.add(new Double(Double.NaN));
        assertTrue(Double.isNaN(Statistics.calculateMean(values)));
        assertTrue(Double.isNaN(Statistics.calculateMean(values, true)));
        assertEquals(9.0, Statistics.calculateMean(values, false), EPSILON);

        // try a collection with several numbers
        values = new ArrayList();
        values.add(new Double(9.0));
        values.add(new Double(3.0));
        values.add(new Double(2.0));
        values.add(new Double(2.0));
        double mean = Statistics.calculateMean(values);
        assertEquals(4.0, mean, EPSILON);

        // a Collection containing a NaN will return Double.NaN for the result
        values.add(new Double(Double.NaN));
        assertTrue(Double.isNaN(Statistics.calculateMean(values)));
    }

    static final double EPSILON = 0.0000000001;

    /**
     * Some checks for the calculateMedian(List, boolean) method.
     */
    @Test
    public void testCalculateMedian() {

        // check null list
        assertTrue(Double.isNaN(Statistics.calculateMedian(null, false)));
        assertTrue(Double.isNaN(Statistics.calculateMedian(null, true)));

        // check empty list
        List list = new ArrayList();
        assertTrue(Double.isNaN(Statistics.calculateMedian(list, false)));
        assertTrue(Double.isNaN(Statistics.calculateMedian(list, true)));

        // check list containing null
        list.add(null);
        boolean pass = false;
        try {
            Statistics.calculateMedian(list, false);
        }
        catch (NullPointerException e) {
            pass = true;
        }
        assertTrue(pass);

        pass = false;
        try {
            Statistics.calculateMedian(list, true);
        }
        catch (NullPointerException e) {
            pass = true;
        }
        assertTrue(pass);

        // check a list containing a non-Number object
        list.clear();
        list.add("Not a number");
        pass = false;
        try {
            Statistics.calculateMedian(list, false);
        }
        catch (ClassCastException e) {
            pass = true;
        }
        assertTrue(pass);

        pass = false;
        try {
            Statistics.calculateMedian(list, true);
        }
        catch (ClassCastException e) {
            pass = true;
        }
        assertTrue(pass);

    }

    /**
     * A test for the calculateMedian() method.
     */
    @Test
    public void testCalculateMedian1() {
        List values = new ArrayList();
        values.add(new Double(1.0));
        double median = Statistics.calculateMedian(values);
        assertEquals(1.0, median, 0.0000001);
    }

    /**
     * A test for the calculateMedian() method.
     */
    @Test
    public void testCalculateMedian2() {
        List values = new ArrayList();
        values.add(new Double(2.0));
        values.add(new Double(1.0));
        double median = Statistics.calculateMedian(values);
        assertEquals(1.5, median, 0.0000001);
    }

    /**
     * A test for the calculateMedian() method.
     */
    @Test
    public void testCalculateMedian3() {
        List values = new ArrayList();
        values.add(new Double(1.0));
        values.add(new Double(2.0));
        values.add(new Double(3.0));
        values.add(new Double(6.0));
        values.add(new Double(5.0));
        values.add(new Double(4.0));
        double median = Statistics.calculateMedian(values);
        assertEquals(3.5, median, 0.0000001);
    }

    /**
     * A test for the calculateMedian() method.
     */
    @Test
    public void testCalculateMedian4() {
        List values = new ArrayList();
        values.add(new Double(7.0));
        values.add(new Double(2.0));
        values.add(new Double(3.0));
        values.add(new Double(5.0));
        values.add(new Double(4.0));
        values.add(new Double(6.0));
        values.add(new Double(1.0));
        double median = Statistics.calculateMedian(values);
        assertEquals(4.0, median, 0.0000001);
    }

    /**
     * A test using some real data that caused a problem at one point.
     */
    @Test
    public void testCalculateMedian5() {
        List values = new ArrayList();
        values.add(new Double(11.228692993861783));
        values.add(new Double(11.30823353859889));
        values.add(new Double(11.75312904769314));
        values.add(new Double(11.825102897465314));
        values.add(new Double(10.184252778401783));
        values.add(new Double(12.207951828057766));
        values.add(new Double(10.68841994040566));
        values.add(new Double(12.099522004479438));
        values.add(new Double(11.508874945056881));
        values.add(new Double(12.052517729558513));
        values.add(new Double(12.401481645578734));
        values.add(new Double(12.185377793028543));
        values.add(new Double(10.666372951930315));
        values.add(new Double(11.680978041499548));
        values.add(new Double(11.06528277406718));
        values.add(new Double(11.36876492904596));
        values.add(new Double(11.927565516175939));
        values.add(new Double(11.39307785978655));
        values.add(new Double(11.989603679523857));
        values.add(new Double(12.009834360354864));
        values.add(new Double(10.653351822461559));
        values.add(new Double(11.851776254376754));
        values.add(new Double(11.045441544755946));
        values.add(new Double(11.993674040560624));
        values.add(new Double(12.898219965238944));
        values.add(new Double(11.97095782819647));
        values.add(new Double(11.73234406745488));
        values.add(new Double(11.649006017243991));
        values.add(new Double(12.20549704915365));
        values.add(new Double(11.799723639384919));
        values.add(new Double(11.896208658005628));
        values.add(new Double(12.164149111823424));
        values.add(new Double(12.042795103513766));
        values.add(new Double(12.114839532596426));
        values.add(new Double(12.166609097075824));
        values.add(new Double(12.183017546225935));
        values.add(new Double(11.622009125845342));
        values.add(new Double(11.289365786738633));
        values.add(new Double(12.462984323671568));
        values.add(new Double(11.573494921030598));
        values.add(new Double(10.862867940485804));
        values.add(new Double(12.018186939664872));
        values.add(new Double(10.418046849313018));
        values.add(new Double(11.326344465881341));
        double median = Statistics.calculateMedian(values, true);
        assertEquals(11.812413268425116, median, 0.000001);
        Collections.sort(values);
        double median2 = Statistics.calculateMedian(values, false);
        assertEquals(11.812413268425116, median2, 0.000001);
    }

    /**
     * A test for the calculateMedian() method.
     */
    @Test
    public void testCalculateMedian6() {
        List values = new ArrayList();
        values.add(new Double(7.0));
        values.add(new Double(2.0));
        values.add(new Double(3.0));
        values.add(new Double(5.0));
        values.add(new Double(4.0));
        values.add(new Double(6.0));
        values.add(new Double(1.0));
        double median = Statistics.calculateMedian(values, 0, 2);
        assertEquals(3.0, median, 0.0000001);
    }

    /**
     * A simple test for the correlation calculation.
     */
    @Test
    public void testCorrelation1() {
        Number[] data1 = new Number[3];
        data1[0] = new Double(1);
        data1[1] = new Double(2);
        data1[2] = new Double(3);
        Number[] data2 = new Number[3];
        data2[0] = new Double(1);
        data2[1] = new Double(2);
        data2[2] = new Double(3);
        double r = Statistics.getCorrelation(data1, data2);
        assertEquals(1.0, r, 0.00000001);
    }

    /**
     * A simple test for the correlation calculation.
     *
     * http://trochim.human.cornell.edu/kb/statcorr.htm
     */
    @Test
    public void testCorrelation2() {
        Number[] data1 = new Number[20];
        data1[0] = new Double(68);
        data1[1] = new Double(71);
        data1[2] = new Double(62);
        data1[3] = new Double(75);
        data1[4] = new Double(58);
        data1[5] = new Double(60);
        data1[6] = new Double(67);
        data1[7] = new Double(68);
        data1[8] = new Double(71);
        data1[9] = new Double(69);
        data1[10] = new Double(68);
        data1[11] = new Double(67);
        data1[12] = new Double(63);
        data1[13] = new Double(62);
        data1[14] = new Double(60);
        data1[15] = new Double(63);
        data1[16] = new Double(65);
        data1[17] = new Double(67);
        data1[18] = new Double(63);
        data1[19] = new Double(61);
        Number[] data2 = new Number[20];
        data2[0] = new Double(4.1);
        data2[1] = new Double(4.6);
        data2[2] = new Double(3.8);
        data2[3] = new Double(4.4);
        data2[4] = new Double(3.2);
        data2[5] = new Double(3.1);
        data2[6] = new Double(3.8);
        data2[7] = new Double(4.1);
        data2[8] = new Double(4.3);
        data2[9] = new Double(3.7);
        data2[10] = new Double(3.5);
        data2[11] = new Double(3.2);
        data2[12] = new Double(3.7);
        data2[13] = new Double(3.3);
        data2[14] = new Double(3.4);
        data2[15] = new Double(4.0);
        data2[16] = new Double(4.1);
        data2[17] = new Double(3.8);
        data2[18] = new Double(3.4);
        data2[19] = new Double(3.6);
        double r = Statistics.getCorrelation(data1, data2);
        assertEquals(0.7306356862792885, r, 0.000000000001);
    }

    /**
     * Some checks for the getStdDev() method.
     */
    @Test
    public void testGetStdDev() {

        // try null argument
        boolean pass = false;
        try {
            Statistics.getStdDev(null);
        }
        catch (IllegalArgumentException e) {
            pass = true;
        }
        assertTrue(pass);

        // try zero length array
        pass = false;
        try {
            Statistics.getStdDev(new Double[0]);
        }
        catch (IllegalArgumentException e) {
            pass = true;
        }
        assertTrue(pass);

        // try single value
        assertTrue(Double.isNaN(Statistics.getStdDev(new Double[]
                {new Double(1.0)})));
    }

}