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MATH-800 

Deprecated "PolynomialFitter" and adapted unit test to use "CurveFitter"
directly.


git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@1347184 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Gilles Sadowski 2012-06-06 22:33:42 +00:00
parent 60c60e05f8
commit 6525baf194
2 changed files with 28 additions and 13 deletions
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8
src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java
View File

@ -26,8 +26,14 @@ import org.apache.commons.math3.optimization.DifferentiableMultivariateVectorOpt
* searched by a least square estimator.</p>
* @version $Id$
* @since 2.0
*
* @deprecated Since 3.1 (to be removed in 4.0, see <a href="https://issues.apache.org/jira/browse/MATH-800">MATH-800</a>).
* Please use {@link CurveFitter} directly, by passing an instance of
* {@link org.apache.commons.math3.analysis.polynomials.PolynomialFunction.Parametric PolynomialFunction.Parametric}
* as an argument to the
* {@link CurveFitter#fit(int,org.apache.commons.math3.analysis.ParametricUnivariateFunction,double[]) fit}
* method.
*/
public class PolynomialFitter extends CurveFitter {
/** Polynomial degree. */
private final int degree;

33
src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java
View File

@ -24,11 +24,16 @@ import org.apache.commons.math3.exception.ConvergenceException;
import org.apache.commons.math3.optimization.DifferentiableMultivariateVectorOptimizer;
import org.apache.commons.math3.optimization.general.GaussNewtonOptimizer;
import org.apache.commons.math3.optimization.general.LevenbergMarquardtOptimizer;
import org.apache.commons.math3.optimization.SimpleVectorValueChecker;
import org.apache.commons.math3.util.FastMath;
import org.junit.Test;
import org.junit.Assert;
/**
* Test for class {@link CurveFitter} where the function to fit is a
* polynomial.
*/
public class PolynomialFitterTest {
@Test
@ -37,13 +42,15 @@ public class PolynomialFitterTest {
for (int degree = 1; degree < 10; ++degree) {
PolynomialFunction p = buildRandomPolynomial(degree, randomizer);
PolynomialFitter fitter =
new PolynomialFitter(degree, new LevenbergMarquardtOptimizer());
CurveFitter fitter = new CurveFitter(new LevenbergMarquardtOptimizer());
for (int i = 0; i <= degree; ++i) {
fitter.addObservedPoint(1.0, i, p.value(i));
}
PolynomialFunction fitted = new PolynomialFunction(fitter.fit());
final double[] init = new double[degree + 1];
PolynomialFunction fitted = new PolynomialFunction(fitter.fit(Integer.MAX_VALUE,
new PolynomialFunction.Parametric(),
init));
for (double x = -1.0; x < 1.0; x += 0.01) {
double error = FastMath.abs(p.value(x) - fitted.value(x)) /
@ -60,14 +67,16 @@ public class PolynomialFitterTest {
for (int degree = 0; degree < 10; ++degree) {
PolynomialFunction p = buildRandomPolynomial(degree, randomizer);
PolynomialFitter fitter =
new PolynomialFitter(degree, new LevenbergMarquardtOptimizer());
CurveFitter fitter = new CurveFitter(new LevenbergMarquardtOptimizer());
for (double x = -1.0; x < 1.0; x += 0.01) {
fitter.addObservedPoint(1.0, x,
p.value(x) + 0.1 * randomizer.nextGaussian());
}
PolynomialFunction fitted = new PolynomialFunction(fitter.fit());
final double[] init = new double[degree + 1];
PolynomialFunction fitted = new PolynomialFunction(fitter.fit(Integer.MAX_VALUE,
new PolynomialFunction.Parametric(),
init));
for (double x = -1.0; x < 1.0; x += 0.01) {
double error = FastMath.abs(p.value(x) - fitted.value(x)) /
@ -77,7 +86,6 @@ public class PolynomialFitterTest {
}
}
Assert.assertTrue(maxError > 0.01);
}
@Test
@ -89,9 +97,7 @@ public class PolynomialFitterTest {
@Test
public void testRedundantUnsolvable() {
// Gauss-Newton should not be able to solve redundant information
DifferentiableMultivariateVectorOptimizer optimizer =
new GaussNewtonOptimizer(true);
checkUnsolvableProblem(optimizer, false);
checkUnsolvableProblem(new GaussNewtonOptimizer(true, new SimpleVectorValueChecker(1e-15, 1e-15)), false);
}
private void checkUnsolvableProblem(DifferentiableMultivariateVectorOptimizer optimizer,
@ -100,7 +106,7 @@ public class PolynomialFitterTest {
for (int degree = 0; degree < 10; ++degree) {
PolynomialFunction p = buildRandomPolynomial(degree, randomizer);
PolynomialFitter fitter = new PolynomialFitter(degree, optimizer);
CurveFitter fitter = new CurveFitter(optimizer);
// reusing the same point over and over again does not bring
// information, the problem cannot be solved in this case for
@ -111,7 +117,10 @@ public class PolynomialFitterTest {
}
try {
fitter.fit();
final double[] init = new double[degree + 1];
fitter.fit(Integer.MAX_VALUE,
new PolynomialFunction.Parametric(),
init);
Assert.assertTrue(solvable || (degree == 0));
} catch(ConvergenceException e) {
Assert.assertTrue((! solvable) && (degree > 0));