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jfreechart example source code file (RegressionTests.java)

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

Java - jfreechart tags/keywords

regressiontests, test, test, testcase, xydataset, xydataset, xyseries, xyseries, xyseriescollection, xyseriescollection

The jfreechart RegressionTests.java source code

/* ===========================================================
 * JFreeChart : a free chart library for the Java(tm) platform
 * ===========================================================
 *
 * (C) Copyright 2000-2008, 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.
 *
 * [Java is a trademark or registered trademark of Sun Microsystems, Inc.
 * in the United States and other countries.]
 *
 * --------------------
 * RegressionTests.java
 * --------------------
 * (C) Copyright 2002-2008, by Object Refinery Limited and Contributors.
 *
 * Original Author:  David Gilbert (for Object Refinery Limited);
 * Contributor(s):   -;
 *
 * Changes
 * -------
 * 30-Sep-2002 : Version 1 (DG);
 * 17-Oct-2002 : Fixed errors reported by Checkstyle (DG);
 *
 */

package org.jfree.data.statistics.junit;

import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;

import org.jfree.data.statistics.Regression;
import org.jfree.data.xy.XYDataset;
import org.jfree.data.xy.XYSeries;
import org.jfree.data.xy.XYSeriesCollection;

/**
 * Tests for the {@link Regression} class.
 */
public class RegressionTests extends TestCase {

    /**
     * Returns the tests as a test suite.
     *
     * @return The test suite.
     */
    public static Test suite() {
        return new TestSuite(RegressionTests.class);
    }

    /**
     * Constructs a new set of tests.
     *
     * @param name  the name of the tests.
     */
    public RegressionTests(String name) {
        super(name);
    }

    /**
     * Checks the results of an OLS regression on sample dataset 1.
     */
    public void testOLSRegression1a() {

        double[][] data = createSampleData1();
        double[] result1 = Regression.getOLSRegression(data);
        assertEquals(.25680930, result1[0], 0.0000001);
        assertEquals(0.72792106, result1[1], 0.0000001);

    }

    /**
     * Checks the results of an OLS regression on sample dataset 1 AFTER
     * converting it to an XYSeries.
     */
    public void testOLSRegression1b() {

        double[][] data = createSampleData1();

        XYSeries series = new XYSeries("Test");
        for (int i = 0; i < 11; i++) {
            series.add(data[i][0], data[i][1]);
        }
        XYDataset ds = new XYSeriesCollection(series);
        double[] result2 = Regression.getOLSRegression(ds, 0);

        assertEquals(.25680930, result2[0], 0.0000001);
        assertEquals(0.72792106, result2[1], 0.0000001);

    }

    /**
     * Checks the results of a power regression on sample dataset 1.
     */
    public void testPowerRegression1a() {

        double[][] data = createSampleData1();
        double[] result = Regression.getPowerRegression(data);
        assertEquals(0.91045813, result[0], 0.0000001);
        assertEquals(0.88918346, result[1], 0.0000001);

    }

    /**
     * Checks the results of a power regression on sample dataset 1 AFTER
     * converting it to an XYSeries.
     */
    public void testPowerRegression1b() {

        double[][] data = createSampleData1();

        XYSeries series = new XYSeries("Test");
        for (int i = 0; i < 11; i++) {
            series.add(data[i][0], data[i][1]);
        }
        XYDataset ds = new XYSeriesCollection(series);
        double[] result = Regression.getPowerRegression(ds, 0);

        assertEquals(0.91045813, result[0], 0.0000001);
        assertEquals(0.88918346, result[1], 0.0000001);

    }

    /**
     * Checks the results of an OLS regression on sample dataset 2.
     */
    public void testOLSRegression2a() {

        double[][] data = createSampleData2();
        double[] result = Regression.getOLSRegression(data);
        assertEquals(53.9729697, result[0], 0.0000001);
        assertEquals(-4.1823030, result[1], 0.0000001);

    }

    /**
     * Checks the results of an OLS regression on sample dataset 2 AFTER
     * converting it to an XYSeries.
     */
    public void testOLSRegression2b() {

        double[][] data = createSampleData2();

        XYSeries series = new XYSeries("Test");
        for (int i = 0; i < 10; i++) {
            series.add(data[i][0], data[i][1]);
        }
        XYDataset ds = new XYSeriesCollection(series);
        double[] result = Regression.getOLSRegression(ds, 0);

        assertEquals(53.9729697, result[0], 0.0000001);
        assertEquals(-4.1823030, result[1], 0.0000001);

    }

    /**
     * Checks the results of a power regression on sample dataset 2.
     */
    public void testPowerRegression2a() {

        double[][] data = createSampleData2();
        double[] result = Regression.getPowerRegression(data);
        assertEquals(106.1241681, result[0], 0.0000001);
        assertEquals(-0.8466615, result[1], 0.0000001);

    }

    /**
     * Checks the results of a power regression on sample dataset 2 AFTER
     * converting it to an XYSeries.
     */
    public void testPowerRegression2b() {

        double[][] data = createSampleData2();

        XYSeries series = new XYSeries("Test");
        for (int i = 0; i < 10; i++) {
            series.add(data[i][0], data[i][1]);
        }
        XYDataset ds = new XYSeriesCollection(series);
        double[] result = Regression.getPowerRegression(ds, 0);

        assertEquals(106.1241681, result[0], 0.0000001);
        assertEquals(-0.8466615, result[1], 0.0000001);

    }

    /**
     * Creates and returns a sample dataset.
     * <P>
     * The data is taken from Table 11.2, page 313 of "Understanding Statistics"
     * by Ott and Mendenhall (Duxbury Press).
     *
     * @return The sample data.
     */
    private double[][] createSampleData1() {

        double[][] result = new double[11][2];

        result[0][0] = 2.00;
        result[0][1] = 1.60;
        result[1][0] = 2.25;
        result[1][1] = 2.00;
        result[2][0] = 2.60;
        result[2][1] = 1.80;
        result[3][0] = 2.65;
        result[3][1] = 2.80;
        result[4][0] = 2.80;
        result[4][1] = 2.10;
        result[5][0] = 3.10;
        result[5][1] = 2.00;
        result[6][0] = 2.90;
        result[6][1] = 2.65;
        result[7][0] = 3.25;
        result[7][1] = 2.25;
        result[8][0] = 3.30;
        result[8][1] = 2.60;
        result[9][0] = 3.60;
        result[9][1] = 3.00;
        result[10][0] = 3.25;
        result[10][1] = 3.10;

        return result;

    }

    /**
     * Creates a sample data set.
     *
     * @return The sample data.
     */
    private double[][] createSampleData2() {

        double[][] result = new double[10][2];

        result[0][0] = 2;
        result[0][1] = 56.27;
        result[1][0] = 3;
        result[1][1] = 41.32;
        result[2][0] = 4;
        result[2][1] = 31.45;
        result[3][0] = 5;
        result[3][1] = 30.05;
        result[4][0] = 6;
        result[4][1] = 24.69;
        result[5][0] = 7;
        result[5][1] = 19.78;
        result[6][0] = 8;
        result[6][1] = 20.94;
        result[7][0] = 9;
        result[7][1] = 16.73;
        result[8][0] = 10;
        result[8][1] = 14.21;
        result[9][0] = 11;
        result[9][1] = 12.44;

        return result;

    }

}

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