From 6525baf1941d083b931f9f31f4bde8daffeaea5c Mon Sep 17 00:00:00 2001 From: Gilles Sadowski Date: Wed, 6 Jun 2012 22:33:42 +0000 Subject: [PATCH] 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 --- .../fitting/PolynomialFitter.java | 8 ++++- .../fitting/PolynomialFitterTest.java | 33 ++++++++++++------- 2 files changed, 28 insertions(+), 13 deletions(-) diff --git a/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java b/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java index f5fd4451c..20b339619 100644 --- a/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java +++ b/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java @@ -26,8 +26,14 @@ import org.apache.commons.math3.optimization.DifferentiableMultivariateVectorOpt * searched by a least square estimator.

* @version $Id$ * @since 2.0 + * + * @deprecated Since 3.1 (to be removed in 4.0, see MATH-800). + * 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; diff --git a/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java b/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java index 97566672d..d7f8f6c69 100644 --- a/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java +++ b/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java @@ -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));