Package org.apache.commons.math.analysis.interpolation

Source Code of org.apache.commons.math.analysis.interpolation.DividedDifferenceInterpolatorTest

/*
* 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.math.analysis.interpolation;

import org.apache.commons.math.MathException;
import org.apache.commons.math.analysis.Expm1Function;
import org.apache.commons.math.analysis.SinFunction;
import org.apache.commons.math.analysis.UnivariateRealFunction;

import junit.framework.TestCase;

/**
* Testcase for Divided Difference interpolator.
* <p>
* The error of polynomial interpolation is
*     f(z) - p(z) = f^(n)(zeta) * (z-x[0])(z-x[1])...(z-x[n-1]) / n!
* where f^(n) is the n-th derivative of the approximated function and
* zeta is some point in the interval determined by x[] and z.
* <p>
* Since zeta is unknown, f^(n)(zeta) cannot be calculated. But we can bound
* it and use the absolute value upper bound for estimates. For reference,
* see <b>Introduction to Numerical Analysis</b>, ISBN 038795452X, chapter 2.
*
* @version $Revision: 811685 $ $Date: 2009-09-05 13:36:48 -0400 (Sat, 05 Sep 2009) $
*/
public final class DividedDifferenceInterpolatorTest extends TestCase {

    /**
     * Test of interpolator for the sine function.
     * <p>
     * |sin^(n)(zeta)| <= 1.0, zeta in [0, 2*PI]
     */
    public void testSinFunction() throws MathException {
        UnivariateRealFunction f = new SinFunction();
        UnivariateRealInterpolator interpolator = new DividedDifferenceInterpolator();
        double x[], y[], z, expected, result, tolerance;

        // 6 interpolating points on interval [0, 2*PI]
        int n = 6;
        double min = 0.0, max = 2 * Math.PI;
        x = new double[n];
        y = new double[n];
        for (int i = 0; i < n; i++) {
            x[i] = min + i * (max - min) / n;
            y[i] = f.value(x[i]);
        }
        double derivativebound = 1.0;
        UnivariateRealFunction p = interpolator.interpolate(x, y);

        z = Math.PI / 4; expected = f.value(z); result = p.value(z);
        tolerance = Math.abs(derivativebound * partialerror(x, z));
        assertEquals(expected, result, tolerance);

        z = Math.PI * 1.5; expected = f.value(z); result = p.value(z);
        tolerance = Math.abs(derivativebound * partialerror(x, z));
        assertEquals(expected, result, tolerance);
    }

    /**
     * Test of interpolator for the exponential function.
     * <p>
     * |expm1^(n)(zeta)| <= e, zeta in [-1, 1]
     */
    public void testExpm1Function() throws MathException {
        UnivariateRealFunction f = new Expm1Function();
        UnivariateRealInterpolator interpolator = new DividedDifferenceInterpolator();
        double x[], y[], z, expected, result, tolerance;

        // 5 interpolating points on interval [-1, 1]
        int n = 5;
        double min = -1.0, max = 1.0;
        x = new double[n];
        y = new double[n];
        for (int i = 0; i < n; i++) {
            x[i] = min + i * (max - min) / n;
            y[i] = f.value(x[i]);
        }
        double derivativebound = Math.E;
        UnivariateRealFunction p = interpolator.interpolate(x, y);

        z = 0.0; expected = f.value(z); result = p.value(z);
        tolerance = Math.abs(derivativebound * partialerror(x, z));
        assertEquals(expected, result, tolerance);

        z = 0.5; expected = f.value(z); result = p.value(z);
        tolerance = Math.abs(derivativebound * partialerror(x, z));
        assertEquals(expected, result, tolerance);

        z = -0.5; expected = f.value(z); result = p.value(z);
        tolerance = Math.abs(derivativebound * partialerror(x, z));
        assertEquals(expected, result, tolerance);
    }

    /**
     * Test of parameters for the interpolator.
     */
    public void testParameters() throws Exception {
        UnivariateRealInterpolator interpolator = new DividedDifferenceInterpolator();

        try {
            // bad abscissas array
            double x[] = { 1.0, 2.0, 2.0, 4.0 };
            double y[] = { 0.0, 4.0, 4.0, 2.5 };
            UnivariateRealFunction p = interpolator.interpolate(x, y);
            p.value(0.0);
            fail("Expecting MathException - bad abscissas array");
        } catch (MathException ex) {
            // expected
        }
    }

    /**
     * Returns the partial error term (z-x[0])(z-x[1])...(z-x[n-1])/n!
     */
    protected double partialerror(double x[], double z) throws
        IllegalArgumentException {

        if (x.length < 1) {
            throw new IllegalArgumentException
                ("Interpolation array cannot be empty.");
        }
        double out = 1;
        for (int i = 0; i < x.length; i++) {
            out *= (z - x[i]) / (i + 1);
        }
        return out;
    }
}
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