/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyright ownership. * The ASF licenses this file to You under the Apache License, Version 2.0 * (the "License"); you may not use this file except in compliance with * the License. You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ package org.apache.commons.math4.ml.clustering.evaluation; import static org.junit.Assert.assertEquals; import static org.junit.Assert.assertFalse; import static org.junit.Assert.assertTrue; import java.util.ArrayList; import java.util.List; import org.apache.commons.math4.ml.clustering.Cluster; import org.apache.commons.math4.ml.clustering.DoublePoint; import org.apache.commons.math4.ml.clustering.evaluation.ClusterEvaluator; import org.apache.commons.math4.ml.clustering.evaluation.SumOfClusterVariances; import org.apache.commons.math4.ml.distance.EuclideanDistance; import org.junit.Before; import org.junit.Test; public class SumOfClusterVariancesTest { private ClusterEvaluator<DoublePoint> evaluator; @Before public void setUp() { evaluator = new SumOfClusterVariances<>(new EuclideanDistance()); } @Test public void testScore() { final DoublePoint[] points1 = new DoublePoint[] { new DoublePoint(new double[] { 1 }), new DoublePoint(new double[] { 2 }), new DoublePoint(new double[] { 3 }) }; final DoublePoint[] points2 = new DoublePoint[] { new DoublePoint(new double[] { 1 }), new DoublePoint(new double[] { 5 }), new DoublePoint(new double[] { 10 }) }; final List<Cluster<DoublePoint>> clusters = new ArrayList<>(); final Cluster<DoublePoint> cluster1 = new Cluster<>(); for (DoublePoint p : points1) { cluster1.addPoint(p); } clusters.add(cluster1); assertEquals(1.0/3.0, evaluator.score(clusters), 1e-6); final Cluster<DoublePoint> cluster2 = new Cluster<>(); for (DoublePoint p : points2) { cluster2.addPoint(p); } clusters.add(cluster2); assertEquals(6.148148148, evaluator.score(clusters), 1e-6); } @Test public void testOrdering() { assertTrue(evaluator.isBetterScore(10, 20)); assertFalse(evaluator.isBetterScore(20, 1)); } }