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https://issues.apache.org/jira/browse/MATH-283?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Michael Nischt updated MATH-283:
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Attachment: MultiDirectionalCorrectStartTest.java
the failing unit test
> MultiDirectional optimzation loops forver if started at the correct solution
> ----------------------------------------------------------------------------
>
> Key: MATH-283
> URL: https://issues.apache.org/jira/browse/MATH-283
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: 2.0
> Environment: none specific for the issue (it's a programming bug)
> Reporter: Michael Nischt
> Priority: Blocker
> Attachments: MultiDirectionalCorrectStartTest.java
>
> Original Estimate: 24h
> Remaining Estimate: 24h
>
> MultiDirectional.iterateSimplex loops forever if the starting point is the
> correct solution.
> see the following test case (testMultiDirectionalCorrectStart) as an example
> {quote}
> public class MultiDirectionalCorrectStartTest
> {
> @Test
> public void testMultiDirectionalIncorrectStart()
> throws FunctionEvaluationException, OptimizationException
> {
> // works fine
> try
> {
> testMultiDirectionalWithStart(0.1, 0.1);
> }
> catch(Exception e) { fail(e.getMessage()); }
> }
> @Test
> public void testMultiDirectionalCorrectStart()
> throws FunctionEvaluationException, OptimizationException
> {
> // fails because MultiDirectional.iterateSimplex is looping forever
> // the while(true) should be replaced with a convergence check
> try
> {
> testMultiDirectionalWithStart(0.0, 0.0);
> }
> catch(Exception e) { fail(e.getMessage()); }
> }
> private void testMultiDirectionalWithStart(double xStart, double yStart)
> throws FunctionEvaluationException, OptimizationException
> {
> MultiDirectional multiDirectional = new MultiDirectional();
> multiDirectional.setMaxIterations(100);
> multiDirectional.setMaxEvaluations(1000);
> final Gaussian2D function = new Gaussian2D();
> RealPointValuePair estimate = multiDirectional.optimize(function,
> GoalType.MAXIMIZE, new double[]
> {xStart, yStart} );
> final double EPSILON = 1e-5;
> final double expectedMaximum = function.getMaximum();
> final double actualMaximum = estimate.getValue();
> assertEquals(expectedMaximum, actualMaximum, EPSILON);
> final double[] expectedPosition = function.getMaximumPosition();
> final double[] actualPosition = estimate.getPoint();
> assertEquals(expectedPosition[0], actualPosition[0], EPSILON );
> assertEquals(expectedPosition[1], actualPosition[1], EPSILON );
>
> }
> static class Gaussian2D implements MultivariateRealFunction
> {
> private static final double[] maximumPosition = { 0, 0 };
> private final double std = 1;
>
> public double getMaximum()
> {
> return value(maximumPosition);
> }
> public double[] getMaximumPosition()
> {
> return maximumPosition.clone();
> }
> public double value(double[] point)
> {
> final double x = point[0], y = point[1];
> return 1/(2*Math.PI*std*std)*Math.exp(-(x*x + y*y) / (2*std*std));
> }
> }
> }
> {quote}
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