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From "Erik van Ingen (JIRA)" <j...@apache.org>
Subject [jira] Closed: (MATH-305) NPE in KMeansPlusPlusClusterer unittest
Date Mon, 30 Nov 2009 08:13:23 GMT

     [ https://issues.apache.org/jira/browse/MATH-305?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Erik van Ingen closed MATH-305.
-------------------------------


I have tested the fix and I can confirm that it is working in my environment. Thanks a lot!

> NPE in  KMeansPlusPlusClusterer unittest
> ----------------------------------------
>
>                 Key: MATH-305
>                 URL: https://issues.apache.org/jira/browse/MATH-305
>             Project: Commons Math
>          Issue Type: Bug
>    Affects Versions: 2.0
>         Environment: java 6, eclipse, apache commons math trunk
>            Reporter: Erik van Ingen
>             Fix For: 2.1
>
>   Original Estimate: 4h
>  Remaining Estimate: 4h
>
> When running this unittest, I am facing this NPE:
> java.lang.NullPointerException
> 	at org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer.assignPointsToClusters(KMeansPlusPlusClusterer.java:91)
> This is the unittest:
> package org.fao.fisheries.chronicles.calcuation.cluster;
> import static org.junit.Assert.assertEquals;
> import static org.junit.Assert.assertTrue;
> import java.util.Arrays;
> import java.util.List;
> import java.util.Random;
> import org.apache.commons.math.stat.clustering.Cluster;
> import org.apache.commons.math.stat.clustering.EuclideanIntegerPoint;
> import org.apache.commons.math.stat.clustering.KMeansPlusPlusClusterer;
> import org.fao.fisheries.chronicles.input.CsvImportProcess;
> import org.fao.fisheries.chronicles.input.Top200Csv;
> import org.junit.Test;
> public class ClusterAnalysisTest {
> 	@Test
> 	public void testPerformClusterAnalysis2() {
> 		KMeansPlusPlusClusterer<EuclideanIntegerPoint> transformer = new KMeansPlusPlusClusterer<EuclideanIntegerPoint>(
> 				new Random(1746432956321l));
> 		EuclideanIntegerPoint[] points = new EuclideanIntegerPoint[] {
> 				new EuclideanIntegerPoint(new int[] { 1959, 325100 }),
> 				new EuclideanIntegerPoint(new int[] { 1960, 373200 }), };
> 		List<Cluster<EuclideanIntegerPoint>> clusters = transformer.cluster(Arrays.asList(points),
1, 1);
> 		assertEquals(1, clusters.size());
> 	}
> }

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