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Java example source code file (GaussianCurveFitterTest.java)

This example Java source code file (GaussianCurveFitterTest.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

dataset1, dataset2, dataset3, dataset4, dataset5, gaussiancurvefitter, gaussiancurvefittertest, test, too, weightedobservedpoints

The GaussianCurveFitterTest.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.fitting;

import org.apache.commons.math3.exception.MathIllegalArgumentException;
import org.apache.commons.math3.exception.TooManyIterationsException;
import org.junit.Assert;
import org.junit.Test;

/**
 * Tests {@link GaussianCurveFitter}.
 *
 */
public class GaussianCurveFitterTest {
    /** Good data. */
    protected static final double[][] DATASET1 = new double[][] {
        {4.0254623,  531026.0},
        {4.02804905, 664002.0},
        {4.02934242, 787079.0},
        {4.03128248, 984167.0},
        {4.03386923, 1294546.0},
        {4.03580929, 1560230.0},
        {4.03839603, 1887233.0},
        {4.0396894,  2113240.0},
        {4.04162946, 2375211.0},
        {4.04421621, 2687152.0},
        {4.04550958, 2862644.0},
        {4.04744964, 3078898.0},
        {4.05003639, 3327238.0},
        {4.05132976, 3461228.0},
        {4.05326982, 3580526.0},
        {4.05585657, 3576946.0},
        {4.05779662, 3439750.0},
        {4.06038337, 3220296.0},
        {4.06167674, 3070073.0},
        {4.0636168,  2877648.0},
        {4.06620355, 2595848.0},
        {4.06749692, 2390157.0},
        {4.06943698, 2175960.0},
        {4.07202373, 1895104.0},
        {4.0733171,  1687576.0},
        {4.07525716, 1447024.0},
        {4.0778439,  1130879.0},
        {4.07978396, 904900.0},
        {4.08237071, 717104.0},
        {4.08366408, 620014.0}
    };
    /** Poor data: right of peak not symmetric with left of peak. */
    protected static final double[][] DATASET2 = new double[][] {
        {-20.15,   1523.0},
        {-19.65,   1566.0},
        {-19.15,   1592.0},
        {-18.65,   1927.0},
        {-18.15,   3089.0},
        {-17.65,   6068.0},
        {-17.15,  14239.0},
        {-16.65,  34124.0},
        {-16.15,  64097.0},
        {-15.65, 110352.0},
        {-15.15, 164742.0},
        {-14.65, 209499.0},
        {-14.15, 267274.0},
        {-13.65, 283290.0},
        {-13.15, 275363.0},
        {-12.65, 258014.0},
        {-12.15, 225000.0},
        {-11.65, 200000.0},
        {-11.15, 190000.0},
        {-10.65, 185000.0},
        {-10.15, 180000.0},
        { -9.65, 179000.0},
        { -9.15, 178000.0},
        { -8.65, 177000.0},
        { -8.15, 176000.0},
        { -7.65, 175000.0},
        { -7.15, 174000.0},
        { -6.65, 173000.0},
        { -6.15, 172000.0},
        { -5.65, 171000.0},
        { -5.15, 170000.0}
    };
    /** Poor data: long tails. */
    protected static final double[][] DATASET3 = new double[][] {
        {-90.15,   1513.0},
        {-80.15,   1514.0},
        {-70.15,   1513.0},
        {-60.15,   1514.0},
        {-50.15,   1513.0},
        {-40.15,   1514.0},
        {-30.15,   1513.0},
        {-20.15,   1523.0},
        {-19.65,   1566.0},
        {-19.15,   1592.0},
        {-18.65,   1927.0},
        {-18.15,   3089.0},
        {-17.65,   6068.0},
        {-17.15,  14239.0},
        {-16.65,  34124.0},
        {-16.15,  64097.0},
        {-15.65, 110352.0},
        {-15.15, 164742.0},
        {-14.65, 209499.0},
        {-14.15, 267274.0},
        {-13.65, 283290.0},
        {-13.15, 275363.0},
        {-12.65, 258014.0},
        {-12.15, 214073.0},
        {-11.65, 182244.0},
        {-11.15, 136419.0},
        {-10.65,  97823.0},
        {-10.15,  58930.0},
        { -9.65,  35404.0},
        { -9.15,  16120.0},
        { -8.65,   9823.0},
        { -8.15,   5064.0},
        { -7.65,   2575.0},
        { -7.15,   1642.0},
        { -6.65,   1101.0},
        { -6.15,    812.0},
        { -5.65,    690.0},
        { -5.15,    565.0},
        {  5.15,    564.0},
        { 15.15,    565.0},
        { 25.15,    564.0},
        { 35.15,    565.0},
        { 45.15,    564.0},
        { 55.15,    565.0},
        { 65.15,    564.0},
        { 75.15,    565.0}
    };
    /** Poor data: right of peak is missing. */
    protected static final double[][] DATASET4 = new double[][] {
        {-20.15,   1523.0},
        {-19.65,   1566.0},
        {-19.15,   1592.0},
        {-18.65,   1927.0},
        {-18.15,   3089.0},
        {-17.65,   6068.0},
        {-17.15,  14239.0},
        {-16.65,  34124.0},
        {-16.15,  64097.0},
        {-15.65, 110352.0},
        {-15.15, 164742.0},
        {-14.65, 209499.0},
        {-14.15, 267274.0},
        {-13.65, 283290.0}
    };
    /** Good data, but few points. */
    protected static final double[][] DATASET5 = new double[][] {
        {4.0254623,  531026.0},
        {4.03128248, 984167.0},
        {4.03839603, 1887233.0},
        {4.04421621, 2687152.0},
        {4.05132976, 3461228.0},
        {4.05326982, 3580526.0},
        {4.05779662, 3439750.0},
        {4.0636168,  2877648.0},
        {4.06943698, 2175960.0},
        {4.07525716, 1447024.0},
        {4.08237071, 717104.0},
        {4.08366408, 620014.0}
    };

    /**
     * Basic.
     */
    @Test
    public void testFit01() {
        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        double[] parameters = fitter.fit(createDataset(DATASET1).toList());

        Assert.assertEquals(3496978.1837704973, parameters[0], 1e-4);
        Assert.assertEquals(4.054933085999146, parameters[1], 1e-4);
        Assert.assertEquals(0.015039355620304326, parameters[2], 1e-4);
    }

    @Test
    public void testWithMaxIterations1() {
        final int maxIter = 20;
        final double[] init = { 3.5e6, 4.2, 0.1 };

        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        double[] parameters = fitter
            .withMaxIterations(maxIter)
            .withStartPoint(init)
            .fit(createDataset(DATASET1).toList());

        Assert.assertEquals(3496978.1837704973, parameters[0], 1e-2);
        Assert.assertEquals(4.054933085999146, parameters[1], 1e-4);
        Assert.assertEquals(0.015039355620304326, parameters[2], 1e-4);
    }

    @Test(expected=TooManyIterationsException.class)
    public void testWithMaxIterations2() {
        final int maxIter = 1; // Too few iterations.
        final double[] init = { 3.5e6, 4.2, 0.1 };

        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        fitter.withMaxIterations(maxIter)
              .withStartPoint(init)
              .fit(createDataset(DATASET1).toList());
    }

    @Test
    public void testWithStartPoint() {
        final double[] init = { 3.5e6, 4.2, 0.1 };

        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        double[] parameters = fitter
            .withStartPoint(init)
            .fit(createDataset(DATASET1).toList());

        Assert.assertEquals(3496978.1837704973, parameters[0], 1e-2);
        Assert.assertEquals(4.054933085999146, parameters[1], 1e-4);
        Assert.assertEquals(0.015039355620304326, parameters[2], 1e-4);
    }

    /**
     * Zero points is not enough observed points.
     */
    @Test(expected=MathIllegalArgumentException.class)
    public void testFit02() {
        GaussianCurveFitter.create().fit(new WeightedObservedPoints().toList());
    }

    /**
     * Two points is not enough observed points.
     */
    @Test(expected=MathIllegalArgumentException.class)
    public void testFit03() {
        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        fitter.fit(createDataset(new double[][] {
                    {4.0254623,  531026.0},
                    {4.02804905, 664002.0}
                }).toList());
    }

    /**
     * Poor data: right of peak not symmetric with left of peak.
     */
    @Test
    public void testFit04() {
        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        double[] parameters = fitter.fit(createDataset(DATASET2).toList());

        Assert.assertEquals(233003.2967252038, parameters[0], 1e-4);
        Assert.assertEquals(-10.654887521095983, parameters[1], 1e-4);
        Assert.assertEquals(4.335937353196641, parameters[2], 1e-4);
    }

    /**
     * Poor data: long tails.
     */
    @Test
    public void testFit05() {
        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        double[] parameters = fitter.fit(createDataset(DATASET3).toList());

        Assert.assertEquals(283863.81929180305, parameters[0], 1e-4);
        Assert.assertEquals(-13.29641995105174, parameters[1], 1e-4);
        Assert.assertEquals(1.7297330293549908, parameters[2], 1e-4);
    }

    /**
     * Poor data: right of peak is missing.
     */
    @Test
    public void testFit06() {
        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        double[] parameters = fitter.fit(createDataset(DATASET4).toList());

        Assert.assertEquals(285250.66754309234, parameters[0], 1e-4);
        Assert.assertEquals(-13.528375695228455, parameters[1], 1e-4);
        Assert.assertEquals(1.5204344894331614, parameters[2], 1e-4);
    }

    /**
     * Basic with smaller dataset.
     */
    @Test
    public void testFit07() {
        GaussianCurveFitter fitter = GaussianCurveFitter.create();
        double[] parameters = fitter.fit(createDataset(DATASET5).toList());

        Assert.assertEquals(3514384.729342235, parameters[0], 1e-4);
        Assert.assertEquals(4.054970307455625, parameters[1], 1e-4);
        Assert.assertEquals(0.015029412832160017, parameters[2], 1e-4);
    }

    @Test
    public void testMath519() {
        // The optimizer will try negative sigma values but "GaussianCurveFitter"
        // will catch the raised exceptions and return NaN values instead.

        final double[] data = {
            1.1143831578403364E-29,
            4.95281403484594E-28,
            1.1171347211930288E-26,
            1.7044813962636277E-25,
            1.9784716574832164E-24,
            1.8630236407866774E-23,
            1.4820532905097742E-22,
            1.0241963854632831E-21,
            6.275077366673128E-21,
            3.461808994532493E-20,
            1.7407124684715706E-19,
            8.056687953553974E-19,
            3.460193945992071E-18,
            1.3883326374011525E-17,
            5.233894983671116E-17,
            1.8630791465263745E-16,
            6.288759227922111E-16,
            2.0204433920597856E-15,
            6.198768938576155E-15,
            1.821419346860626E-14,
            5.139176445538471E-14,
            1.3956427429045787E-13,
            3.655705706448139E-13,
            9.253753324779779E-13,
            2.267636001476696E-12,
            5.3880460095836855E-12,
            1.2431632654852931E-11
        };

        final WeightedObservedPoints obs = new WeightedObservedPoints();
        for (int i = 0; i < data.length; i++) {
            obs.add(i, data[i]);
        }
        final double[] p = GaussianCurveFitter.create().fit(obs.toList());

        Assert.assertEquals(53.1572792, p[1], 1e-7);
        Assert.assertEquals(5.75214622, p[2], 1e-8);
    }

    @Test
    public void testMath798() {
        // When the data points are not commented out below, the fit stalls.
        // This is expected however, since the whole dataset hardly looks like
        // a Gaussian.
        // When commented out, the fit proceeds fine.

        final WeightedObservedPoints obs = new WeightedObservedPoints();

        obs.add(0.23, 395.0);
        //obs.add(0.68, 0.0);
        obs.add(1.14, 376.0);
        //obs.add(1.59, 0.0);
        obs.add(2.05, 163.0);
        //obs.add(2.50, 0.0);
        obs.add(2.95, 49.0);
        //obs.add(3.41, 0.0);
        obs.add(3.86, 16.0);
        //obs.add(4.32, 0.0);
        obs.add(4.77, 1.0);

        final double[] p = GaussianCurveFitter.create().fit(obs.toList());

        // Values are copied from a previous run of this test.
        Assert.assertEquals(420.8397296167364, p[0], 1e-12);
        Assert.assertEquals(0.603770729862231, p[1], 1e-15);
        Assert.assertEquals(1.0786447936766612, p[2], 1e-14);
    }

    /**
     * Adds the specified points to specified <code>GaussianCurveFitter
     * instance.
     *
     * @param points Data points where first dimension is a point index and
     *        second dimension is an array of length two representing the point
     *        with the first value corresponding to X and the second value
     *        corresponding to Y.
     * @return the collection of observed points.
     */
    private static WeightedObservedPoints createDataset(double[][] points) {
        final WeightedObservedPoints obs = new WeightedObservedPoints();
        for (int i = 0; i < points.length; i++) {
            obs.add(points[i][0], points[i][1]);
        }
        return obs;
    }
}

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