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Java example source code file (LoessInterpolatorTest.java)

This example Java source code file (LoessInterpolatorTest.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

loessinterpolator, loessinterpolatortest, test

The LoessInterpolatorTest.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.analysis.interpolation;

import org.apache.commons.math3.util.FastMath;
import org.apache.commons.math3.exception.OutOfRangeException;
import org.apache.commons.math3.exception.DimensionMismatchException;
import org.apache.commons.math3.exception.NoDataException;
import org.apache.commons.math3.exception.NonMonotonicSequenceException;
import org.apache.commons.math3.exception.NotFiniteNumberException;
import org.apache.commons.math3.exception.NumberIsTooSmallException;

import org.junit.Assert;
import org.junit.Test;

/**
 * Test of the LoessInterpolator class.
 */
public class LoessInterpolatorTest {

    @Test
    public void testOnOnePoint() {
        double[] xval = {0.5};
        double[] yval = {0.7};
        double[] res = new LoessInterpolator().smooth(xval, yval);
        Assert.assertEquals(1, res.length);
        Assert.assertEquals(0.7, res[0], 0.0);
    }

    @Test
    public void testOnTwoPoints() {
        double[] xval = {0.5, 0.6};
        double[] yval = {0.7, 0.8};
        double[] res = new LoessInterpolator().smooth(xval, yval);
        Assert.assertEquals(2, res.length);
        Assert.assertEquals(0.7, res[0], 0.0);
        Assert.assertEquals(0.8, res[1], 0.0);
    }

    @Test
    public void testOnStraightLine() {
        double[] xval = {1,2,3,4,5};
        double[] yval = {2,4,6,8,10};
        LoessInterpolator li = new LoessInterpolator(0.6, 2, 1e-12);
        double[] res = li.smooth(xval, yval);
        Assert.assertEquals(5, res.length);
        for(int i = 0; i < 5; ++i) {
            Assert.assertEquals(yval[i], res[i], 1e-8);
        }
    }

    @Test
    public void testOnDistortedSine() {
        int numPoints = 100;
        double[] xval = new double[numPoints];
        double[] yval = new double[numPoints];
        double xnoise = 0.1;
        double ynoise = 0.2;

        generateSineData(xval, yval, xnoise, ynoise);

        LoessInterpolator li = new LoessInterpolator(0.3, 4, 1e-12);

        double[] res = li.smooth(xval, yval);

        // Check that the resulting curve differs from
        // the "real" sine less than the jittered one

        double noisyResidualSum = 0;
        double fitResidualSum = 0;

        for(int i = 0; i < numPoints; ++i) {
            double expected = FastMath.sin(xval[i]);
            double noisy = yval[i];
            double fit = res[i];

            noisyResidualSum += FastMath.pow(noisy - expected, 2);
            fitResidualSum += FastMath.pow(fit - expected, 2);
        }

        Assert.assertTrue(fitResidualSum < noisyResidualSum);
    }

    @Test
    public void testIncreasingBandwidthIncreasesSmoothness() {
        int numPoints = 100;
        double[] xval = new double[numPoints];
        double[] yval = new double[numPoints];
        double xnoise = 0.1;
        double ynoise = 0.1;

        generateSineData(xval, yval, xnoise, ynoise);

        // Check that variance decreases as bandwidth increases

        double[] bandwidths = {0.1, 0.5, 1.0};
        double[] variances = new double[bandwidths.length];
        for (int i = 0; i < bandwidths.length; i++) {
            double bw = bandwidths[i];

            LoessInterpolator li = new LoessInterpolator(bw, 4, 1e-12);

            double[] res = li.smooth(xval, yval);

            for (int j = 1; j < res.length; ++j) {
                variances[i] += FastMath.pow(res[j] - res[j-1], 2);
            }
        }

        for(int i = 1; i < variances.length; ++i) {
            Assert.assertTrue(variances[i] < variances[i-1]);
        }
    }

    @Test
    public void testIncreasingRobustnessItersIncreasesSmoothnessWithOutliers() {
        int numPoints = 100;
        double[] xval = new double[numPoints];
        double[] yval = new double[numPoints];
        double xnoise = 0.1;
        double ynoise = 0.1;

        generateSineData(xval, yval, xnoise, ynoise);

        // Introduce a couple of outliers
        yval[numPoints/3] *= 100;
        yval[2 * numPoints/3] *= -100;

        // Check that variance decreases as the number of robustness
        // iterations increases

        double[] variances = new double[4];
        for (int i = 0; i < 4; i++) {
            LoessInterpolator li = new LoessInterpolator(0.3, i, 1e-12);

            double[] res = li.smooth(xval, yval);

            for (int j = 1; j < res.length; ++j) {
                variances[i] += FastMath.abs(res[j] - res[j-1]);
            }
        }

        for(int i = 1; i < variances.length; ++i) {
            Assert.assertTrue(variances[i] < variances[i-1]);
        }
    }

    @Test(expected=DimensionMismatchException.class)
    public void testUnequalSizeArguments() {
        new LoessInterpolator().smooth(new double[] {1,2,3}, new double[] {1,2,3,4});
    }

    @Test(expected=NoDataException.class)
    public void testEmptyData() {
        new LoessInterpolator().smooth(new double[] {}, new double[] {});
    }

    @Test(expected=NonMonotonicSequenceException.class)
    public void testNonStrictlyIncreasing1() {
        new LoessInterpolator().smooth(new double[] {4,3,1,2}, new double[] {3,4,5,6});
    }

    @Test(expected=NonMonotonicSequenceException.class)
    public void testNonStrictlyIncreasing2() {
        new LoessInterpolator().smooth(new double[] {1,2,2,3}, new double[] {3,4,5,6});
    }

    @Test(expected=NotFiniteNumberException.class)
    public void testNotAllFiniteReal1() {
        new LoessInterpolator().smooth(new double[] {1,2,Double.NaN}, new double[] {3,4,5});
    }

    @Test(expected=NotFiniteNumberException.class)
    public void testNotAllFiniteReal2() {
        new LoessInterpolator().smooth(new double[] {1,2,Double.POSITIVE_INFINITY}, new double[] {3,4,5});
    }

    @Test(expected=NotFiniteNumberException.class)
    public void testNotAllFiniteReal3() {
        new LoessInterpolator().smooth(new double[] {1,2,Double.NEGATIVE_INFINITY}, new double[] {3,4,5});
    }

    @Test(expected=NotFiniteNumberException.class)
    public void testNotAllFiniteReal4() {
        new LoessInterpolator().smooth(new double[] {3,4,5}, new double[] {1,2,Double.NaN});
    }

    @Test(expected=NotFiniteNumberException.class)
    public void testNotAllFiniteReal5() {
        new LoessInterpolator().smooth(new double[] {3,4,5}, new double[] {1,2,Double.POSITIVE_INFINITY});
    }

    @Test(expected=NotFiniteNumberException.class)
    public void testNotAllFiniteReal6() {
        new LoessInterpolator().smooth(new double[] {3,4,5}, new double[] {1,2,Double.NEGATIVE_INFINITY});
    }

    @Test(expected=NumberIsTooSmallException.class)
    public void testInsufficientBandwidth() {
        LoessInterpolator li = new LoessInterpolator(0.1, 3, 1e-12);
        li.smooth(new double[] {1,2,3,4,5,6,7,8,9,10,11,12}, new double[] {1,2,3,4,5,6,7,8,9,10,11,12});
    }

    @Test(expected=OutOfRangeException.class)
    public void testCompletelyIncorrectBandwidth1() {
        new LoessInterpolator(-0.2, 3, 1e-12);
    }

    @Test(expected=OutOfRangeException.class)
    public void testCompletelyIncorrectBandwidth2() {
        new LoessInterpolator(1.1, 3, 1e-12);
    }

    @Test
    public void testMath296withoutWeights() {
        double[] xval = {
                0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0,
                 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2.0};
        double[] yval = {
                0.47, 0.48, 0.55, 0.56, -0.08, -0.04, -0.07, -0.07,
                -0.56, -0.46, -0.56, -0.52, -3.03, -3.08, -3.09,
                -3.04, 3.54, 3.46, 3.36, 3.35};
        // Output from R, rounded to .001
        double[] yref = {
                0.461, 0.499, 0.541, 0.308, 0.175, -0.042, -0.072,
                -0.196, -0.311, -0.446, -0.557, -1.497, -2.133,
                -3.08, -3.09, -0.621, 0.982, 3.449, 3.389, 3.336
        };
        LoessInterpolator li = new LoessInterpolator(0.3, 4, 1e-12);
        double[] res = li.smooth(xval, yval);
        Assert.assertEquals(xval.length, res.length);
        for(int i = 0; i < res.length; ++i) {
            Assert.assertEquals(yref[i], res[i], 0.02);
        }
    }

    private void generateSineData(double[] xval, double[] yval, double xnoise, double ynoise) {
        double dx = 2 * FastMath.PI / xval.length;
        double x = 0;
        for(int i = 0; i < xval.length; ++i) {
            xval[i] = x;
            yval[i] = FastMath.sin(x) + (2 * FastMath.random() - 1) * ynoise;
            x += dx * (1 + (2 * FastMath.random() - 1) * xnoise);
        }
    }
}

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