Author: erans
Date: Wed Jul 4 18:00:02 2012
New Revision: 1357353
URL: http://svn.apache.org/viewvc?rev=1357353&view=rev
Log:
MATH-798
Added overridden "fit" method where one can specify the maximum number of
function evaluations.
Modified:
commons/proper/math/trunk/src/changes/changes.xml
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/CurveFitterTest.java
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java
Modified: commons/proper/math/trunk/src/changes/changes.xml
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/changes/changes.xml?rev=1357353&r1=1357352&r2=1357353&view=diff
==============================================================================
--- commons/proper/math/trunk/src/changes/changes.xml (original)
+++ commons/proper/math/trunk/src/changes/changes.xml Wed Jul 4 18:00:02 2012
@@ -52,6 +52,10 @@ If the output is not quite correct, chec
<body>
<release version="3.1" date="TBD" description="
">
+ <action dev="erans" type="fix" issue="MATH-798">
+ Added overridden method in "PolynomialFitter" (package
+ "o.a.c.m.optimization.fitting") to limit the number of evaluations.
+ </action>
<action dev="celestin" type="add" issue="MATH-807">
Added a new constructor to o.a.c.m.utils.IterationManager, allowing
for the specification of a callback function in case the maximum
Modified:
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java?rev=1357353&r1=1357352&r2=1357353&view=diff
==============================================================================
---
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java
(original)
+++
commons/proper/math/trunk/src/main/java/org/apache/commons/math3/optimization/fitting/PolynomialFitter.java
Wed Jul 4 18:00:02 2012
@@ -77,6 +77,23 @@ public class PolynomialFitter extends Cu
*
* @param guess First guess for the coefficients. They must be sorted in
* increasing order of the polynomial's degree.
+ * @param maxEval Maximum number of evaluations of the polynomial.
+ * @return the coefficients of the polynomial that best fits the observed
points.
+ * @throws org.apache.commons.math3.exception.TooManyEvaluationsException
if
+ * the number of evaluations exceeds {@code maxEval}.
+ * @throws org.apache.commons.math3.exception.ConvergenceException
+ * if the algorithm failed to converge.
+ */
+ public double[] fit(int maxEval, double[] guess) {
+ return fit(maxEval, new PolynomialFunction.Parametric(), guess);
+ }
+
+ /**
+ * Get the coefficients of the polynomial fitting the weighted data points.
+ * The degree of the fitting polynomial is {@code guess.length - 1}.
+ *
+ * @param guess First guess for the coefficients. They must be sorted in
+ * increasing order of the polynomial's degree.
* @return the coefficients of the polynomial that best fits the observed
points.
* @throws org.apache.commons.math3.exception.ConvergenceException
* if the algorithm failed to converge.
Modified:
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/CurveFitterTest.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/CurveFitterTest.java?rev=1357353&r1=1357352&r2=1357353&view=diff
==============================================================================
---
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/CurveFitterTest.java
(original)
+++
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/CurveFitterTest.java
Wed Jul 4 18:00:02 2012
@@ -138,69 +138,6 @@ public class CurveFitterTest {
}
- @Test
- public void testMath798() {
- final double tol = 1e-14;
- final SimpleVectorValueChecker checker = new
SimpleVectorValueChecker(tol, tol);
- final double[] init = new double[] { 0, 0 };
- final int maxEval = 3;
-
- final double[] lm = doMath798(new
LevenbergMarquardtOptimizer(checker), maxEval, init);
- final double[] gn = doMath798(new GaussNewtonOptimizer(checker),
maxEval, init);
-
- for (int i = 0; i <= 1; i++) {
- Assert.assertEquals(lm[i], gn[i], tol);
- }
- }
-
- /**
- * @param optimizer Optimizer.
- * @param maxEval Maximum number of function evaluations.
- * @param init First guess.
- * @return the solution found by the given optimizer.
- */
- private double[] doMath798(DifferentiableMultivariateVectorOptimizer
optimizer,
- int maxEval,
- double[] init) {
- final CurveFitter fitter = new CurveFitter(optimizer);
-
- fitter.addObservedPoint(-0.2, -7.12442E-13);
- fitter.addObservedPoint(-0.199, -4.33397E-13);
- fitter.addObservedPoint(-0.198, -2.823E-13);
- fitter.addObservedPoint(-0.197, -1.40405E-13);
- fitter.addObservedPoint(-0.196, -7.80821E-15);
- fitter.addObservedPoint(-0.195, 6.20484E-14);
- fitter.addObservedPoint(-0.194, 7.24673E-14);
- fitter.addObservedPoint(-0.193, 1.47152E-13);
- fitter.addObservedPoint(-0.192, 1.9629E-13);
- fitter.addObservedPoint(-0.191, 2.12038E-13);
- fitter.addObservedPoint(-0.19, 2.46906E-13);
- fitter.addObservedPoint(-0.189, 2.77495E-13);
- fitter.addObservedPoint(-0.188, 2.51281E-13);
- fitter.addObservedPoint(-0.187, 2.64001E-13);
- fitter.addObservedPoint(-0.186, 2.8882E-13);
- fitter.addObservedPoint(-0.185, 3.13604E-13);
- fitter.addObservedPoint(-0.184, 3.14248E-13);
- fitter.addObservedPoint(-0.183, 3.1172E-13);
- fitter.addObservedPoint(-0.182, 3.12912E-13);
- fitter.addObservedPoint(-0.181, 3.06761E-13);
- fitter.addObservedPoint(-0.18, 2.8559E-13);
- fitter.addObservedPoint(-0.179, 2.86806E-13);
- fitter.addObservedPoint(-0.178, 2.985E-13);
- fitter.addObservedPoint(-0.177, 2.67148E-13);
- fitter.addObservedPoint(-0.176, 2.94173E-13);
- fitter.addObservedPoint(-0.175, 3.27528E-13);
- fitter.addObservedPoint(-0.174, 3.33858E-13);
- fitter.addObservedPoint(-0.173, 2.97511E-13);
- fitter.addObservedPoint(-0.172, 2.8615E-13);
- fitter.addObservedPoint(-0.171, 2.84624E-13);
-
- final double[] coeff = fitter.fit(maxEval,
- new PolynomialFunction.Parametric(),
- init);
- return coeff;
- }
-
private static class SimpleInverseFunction implements
ParametricUnivariateFunction {
public double value(double x, double ... parameters) {
Modified:
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java
URL:
http://svn.apache.org/viewvc/commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java?rev=1357353&r1=1357352&r2=1357353&view=diff
==============================================================================
---
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java
(original)
+++
commons/proper/math/trunk/src/test/java/org/apache/commons/math3/optimization/fitting/PolynomialFitterTest.java
Wed Jul 4 18:00:02 2012
@@ -21,6 +21,7 @@ import java.util.Random;
import org.apache.commons.math3.analysis.polynomials.PolynomialFunction;
import org.apache.commons.math3.exception.ConvergenceException;
+import org.apache.commons.math3.exception.TooManyEvaluationsException;
import
org.apache.commons.math3.optimization.DifferentiableMultivariateVectorOptimizer;
import org.apache.commons.math3.optimization.general.GaussNewtonOptimizer;
import
org.apache.commons.math3.optimization.general.LevenbergMarquardtOptimizer;
@@ -108,6 +109,90 @@ public class PolynomialFitterTest {
}
@Test
+ public void testMath798() {
+ final double tol = 1e-14;
+ final SimpleVectorValueChecker checker = new
SimpleVectorValueChecker(tol, tol);
+ final double[] init = new double[] { 0, 0 };
+ final int maxEval = 3;
+
+ final double[] lm = doMath798(new
LevenbergMarquardtOptimizer(checker), maxEval, init);
+ final double[] gn = doMath798(new GaussNewtonOptimizer(checker),
maxEval, init);
+
+ for (int i = 0; i <= 1; i++) {
+ Assert.assertEquals(lm[i], gn[i], tol);
+ }
+ }
+
+ /**
+ * This test shows that the user can set the maximum number of iterations
+ * to avoid running for too long.
+ * But in the test case, the real problem is that the tolerance is way too
+ * stringent.
+ */
+ @Test(expected=TooManyEvaluationsException.class)
+ public void testMath798WithToleranceTooLow() {
+ final double tol = 1e-100;
+ final SimpleVectorValueChecker checker = new
SimpleVectorValueChecker(tol, tol);
+ final double[] init = new double[] { 0, 0 };
+ final int maxEval = 10000; // Trying hard to fit.
+
+ final double[] lm = doMath798(new
LevenbergMarquardtOptimizer(checker), maxEval, init);
+ final double[] gn = doMath798(new GaussNewtonOptimizer(checker),
maxEval, init);
+
+ for (int i = 0; i <= 1; i++) {
+ Assert.assertEquals(lm[i], gn[i], tol);
+ }
+ }
+
+ /**
+ * @param optimizer Optimizer.
+ * @param maxEval Maximum number of function evaluations.
+ * @param init First guess.
+ * @return the solution found by the given optimizer.
+ */
+ private double[] doMath798(DifferentiableMultivariateVectorOptimizer
optimizer,
+ int maxEval,
+ double[] init) {
+ final CurveFitter fitter = new CurveFitter(optimizer);
+
+ fitter.addObservedPoint(-0.2, -7.12442E-13);
+ fitter.addObservedPoint(-0.199, -4.33397E-13);
+ fitter.addObservedPoint(-0.198, -2.823E-13);
+ fitter.addObservedPoint(-0.197, -1.40405E-13);
+ fitter.addObservedPoint(-0.196, -7.80821E-15);
+ fitter.addObservedPoint(-0.195, 6.20484E-14);
+ fitter.addObservedPoint(-0.194, 7.24673E-14);
+ fitter.addObservedPoint(-0.193, 1.47152E-13);
+ fitter.addObservedPoint(-0.192, 1.9629E-13);
+ fitter.addObservedPoint(-0.191, 2.12038E-13);
+ fitter.addObservedPoint(-0.19, 2.46906E-13);
+ fitter.addObservedPoint(-0.189, 2.77495E-13);
+ fitter.addObservedPoint(-0.188, 2.51281E-13);
+ fitter.addObservedPoint(-0.187, 2.64001E-13);
+ fitter.addObservedPoint(-0.186, 2.8882E-13);
+ fitter.addObservedPoint(-0.185, 3.13604E-13);
+ fitter.addObservedPoint(-0.184, 3.14248E-13);
+ fitter.addObservedPoint(-0.183, 3.1172E-13);
+ fitter.addObservedPoint(-0.182, 3.12912E-13);
+ fitter.addObservedPoint(-0.181, 3.06761E-13);
+ fitter.addObservedPoint(-0.18, 2.8559E-13);
+ fitter.addObservedPoint(-0.179, 2.86806E-13);
+ fitter.addObservedPoint(-0.178, 2.985E-13);
+ fitter.addObservedPoint(-0.177, 2.67148E-13);
+ fitter.addObservedPoint(-0.176, 2.94173E-13);
+ fitter.addObservedPoint(-0.175, 3.27528E-13);
+ fitter.addObservedPoint(-0.174, 3.33858E-13);
+ fitter.addObservedPoint(-0.173, 2.97511E-13);
+ fitter.addObservedPoint(-0.172, 2.8615E-13);
+ fitter.addObservedPoint(-0.171, 2.84624E-13);
+
+ final double[] coeff = fitter.fit(maxEval,
+ new PolynomialFunction.Parametric(),
+ init);
+ return coeff;
+ }
+
+ @Test
public void testRedundantSolvable() {
// Levenberg-Marquardt should handle redundant information gracefully
checkUnsolvableProblem(new LevenbergMarquardtOptimizer(), true);
