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Posted to dev@commons.apache.org by ps...@apache.org on 2004/04/02 22:58:59 UTC
cvs commit: jakarta-commons/math/src/test/org/apache/commons/math/analysis SplineInterpolatorTest.java
psteitz 2004/04/02 12:58:59
Added: math/src/test/org/apache/commons/math/analysis
SplineInterpolatorTest.java
Log:
Initial commit. Replaces InterpolatorTest.
Revision Changes Path
1.1 jakarta-commons/math/src/test/org/apache/commons/math/analysis/SplineInterpolatorTest.java
Index: SplineInterpolatorTest.java
===================================================================
/*
*
* Copyright (c) 2004 The Apache Software Foundation. All rights reserved.
*
* Licensed 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;
import org.apache.commons.math.MathException;
import org.apache.commons.math.TestUtils;
import junit.framework.Test;
import junit.framework.TestCase;
import junit.framework.TestSuite;
/**
* Test the SplineInterpolator.
*
* @version $Revision: 1.1 $ $Date: 2004/04/02 20:58:59 $
*/
public class SplineInterpolatorTest extends TestCase {
/** error tolerance for spline interpolator value at knot points */
protected double knotTolerance = 1E-12;
/** error tolerance for interpolating polynomial coefficients */
protected double coefficientTolerance = 1E-6;
/** error tolerance for interpolated values -- high value is from sin test */
protected double interpolationTolerance = 1E-2;
public SplineInterpolatorTest(String name) {
super(name);
}
public static Test suite() {
TestSuite suite = new TestSuite(SplineInterpolatorTest.class);
suite.setName("UnivariateRealInterpolator Tests");
return suite;
}
public void testInterpolateLinearDegenerateTwoSegment()
throws Exception {
double x[] = { 0.0, 0.5, 1.0 };
double y[] = { 0.0, 0.5, 1.0 };
UnivariateRealInterpolator i = new SplineInterpolator();
UnivariateRealFunction f = i.interpolate(x, y);
verifyInterpolation(f, x, y);
verifyConsistency((PolynomialSplineFunction) f, x);
// Verify coefficients using analytical values
PolynomialFunction polynomials[] = ((PolynomialSplineFunction) f).getPolynomials();
double target[] = {y[0], 1d, 0d, 0d};
TestUtils.assertEquals(polynomials[0].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[1], 1d, 0d, 0d};
TestUtils.assertEquals(polynomials[1].getCoefficients(), target, coefficientTolerance);
// Check interpolation
assertEquals(0.4,f.value(0.4), interpolationTolerance);
}
public void testInterpolateLinearDegenerateThreeSegment()
throws Exception {
double x[] = { 0.0, 0.5, 1.0, 1.5 };
double y[] = { 0.0, 0.5, 1.0, 1.5 };
UnivariateRealInterpolator i = new SplineInterpolator();
UnivariateRealFunction f = i.interpolate(x, y);
verifyInterpolation(f, x, y);
// Verify coefficients using analytical values
PolynomialFunction polynomials[] = ((PolynomialSplineFunction) f).getPolynomials();
double target[] = {y[0], 1d, 0d, 0d};
TestUtils.assertEquals(polynomials[0].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[1], 1d, 0d, 0d};
TestUtils.assertEquals(polynomials[1].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[2], 1d, 0d, 0d};
TestUtils.assertEquals(polynomials[2].getCoefficients(), target, coefficientTolerance);
// Check interpolation
assertEquals(1.4,f.value(1.4), interpolationTolerance);
}
public void testInterpolateLinear() throws Exception {
double x[] = { 0.0, 0.5, 1.0 };
double y[] = { 0.0, 0.5, 0.0 };
UnivariateRealInterpolator i = new SplineInterpolator();
UnivariateRealFunction f = i.interpolate(x, y);
verifyInterpolation(f, x, y);
verifyConsistency((PolynomialSplineFunction) f, x);
// Verify coefficients using analytical values
PolynomialFunction polynomials[] = ((PolynomialSplineFunction) f).getPolynomials();
double target[] = {y[0], 1.5d, 0d, -2d};
TestUtils.assertEquals(polynomials[0].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[1], 0d, -3d, 2d};
TestUtils.assertEquals(polynomials[1].getCoefficients(), target, coefficientTolerance);
}
public void testInterpolateSin() throws Exception {
double x[] =
{
0.0,
Math.PI / 6d,
Math.PI / 2d,
5d * Math.PI / 6d,
Math.PI,
7d * Math.PI / 6d,
3d * Math.PI / 2d,
11d * Math.PI / 6d,
2.d * Math.PI };
double y[] = { 0d, 0.5d, 1d, 0.5d, 0d, -0.5d, -1d, -0.5d, 0d };
UnivariateRealInterpolator i = new SplineInterpolator();
UnivariateRealFunction f = i.interpolate(x, y);
verifyInterpolation(f, x, y);
verifyConsistency((PolynomialSplineFunction) f, x);
/* Check coefficients against values computed using R (version 1.8.1, Red Hat Linux 9)
*
* To replicate in R:
* x[1] <- 0
* x[2] <- pi / 6, etc, same for y[] (could use y <- scan() for y values)
* g <- splinefun(x, y, "natural")
* splinecoef <- eval(expression(z), envir = environment(g))
* print(splinecoef)
*/
PolynomialFunction polynomials[] = ((PolynomialSplineFunction) f).getPolynomials();
double target[] = {y[0], 1.002676d, 0d, -0.17415829d};
TestUtils.assertEquals(polynomials[0].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[1], 8.594367e-01, -2.735672e-01, -0.08707914};
TestUtils.assertEquals(polynomials[1].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[2], 1.471804e-17,-5.471344e-01, 0.08707914};
TestUtils.assertEquals(polynomials[2].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[3], -8.594367e-01, -2.735672e-01, 0.17415829};
TestUtils.assertEquals(polynomials[3].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[4], -1.002676, 6.548562e-17, 0.17415829};
TestUtils.assertEquals(polynomials[4].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[5], -8.594367e-01, 2.735672e-01, 0.08707914};
TestUtils.assertEquals(polynomials[5].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[6], 3.466465e-16, 5.471344e-01, -0.08707914};
TestUtils.assertEquals(polynomials[6].getCoefficients(), target, coefficientTolerance);
target = new double[]{y[7], 8.594367e-01, 2.735672e-01, -0.17415829};
TestUtils.assertEquals(polynomials[7].getCoefficients(), target, coefficientTolerance);
//Check interpolation
assertEquals(Math.sqrt(2d) / 2d,f.value(Math.PI/4d),interpolationTolerance);
assertEquals(Math.sqrt(2d) / 2d,f.value(3d*Math.PI/4d),interpolationTolerance);
}
public void testIllegalArguments() throws MathException {
// Data set arrays of different size.
UnivariateRealInterpolator i = new SplineInterpolator();
try {
double xval[] = { 0.0, 1.0 };
double yval[] = { 0.0, 1.0, 2.0 };
i.interpolate(xval, yval);
fail("Failed to detect data set array with different sizes.");
} catch (IllegalArgumentException iae) {
}
// X values not sorted.
try {
double xval[] = { 0.0, 1.0, 0.5 };
double yval[] = { 0.0, 1.0, 2.0 };
i.interpolate(xval, yval);
fail("Failed to detect unsorted arguments.");
} catch (IllegalArgumentException iae) {
}
}
/**
* verifies that f(x[i]) = y[i] for i = 0..n -1 where n is common length -- skips last point.
*/
protected void verifyInterpolation(UnivariateRealFunction f, double x[], double y[])
throws Exception{
for (int i = 0; i < x.length - 1; i++) {
assertEquals(f.value(x[i]), y[i], knotTolerance);
}
}
/**
* Verifies that interpolating polynomials satisfy consistency requirement:
* adjacent polynomials must agree through two derivatives at knot points
*/
protected void verifyConsistency(PolynomialSplineFunction f, double x[])
throws Exception {
PolynomialFunction polynomials[] = f.getPolynomials();
for (int i = 1; i < x.length - 2; i++) {
// evaluate polynomials and derivatives at x[i + 1]
assertEquals(polynomials[i].value(x[i +1] - x[i]), polynomials[i + 1].value(0), 0.1);
assertEquals(polynomials[i].derivative().value(x[i +1] - x[i]),
polynomials[i + 1].derivative().value(0), 0.5);
assertEquals(polynomials[i].polynomialDerivative().derivative().value(x[i +1] - x[i]),
polynomials[i + 1].polynomialDerivative().derivative().value(0), 0.5);
}
}
}
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