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/*
* 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.math3.ml.clustering;
import java.util.Arrays;
import java.util.List;
import org.junit.Assert;
import org.junit.Test;
public class MultiKMeansPlusPlusClustererTest {
@Test
public void dimension2() {
MultiKMeansPlusPlusClusterer<DoublePoint> transformer =
new MultiKMeansPlusPlusClusterer<DoublePoint>(
new KMeansPlusPlusClusterer<DoublePoint>(3, 10), 5);
DoublePoint[] points = new DoublePoint[] {
// first expected cluster
new DoublePoint(new int[] { -15, 3 }),
new DoublePoint(new int[] { -15, 4 }),
new DoublePoint(new int[] { -15, 5 }),
new DoublePoint(new int[] { -14, 3 }),
new DoublePoint(new int[] { -14, 5 }),
new DoublePoint(new int[] { -13, 3 }),
new DoublePoint(new int[] { -13, 4 }),
new DoublePoint(new int[] { -13, 5 }),
// second expected cluster
new DoublePoint(new int[] { -1, 0 }),
new DoublePoint(new int[] { -1, -1 }),
new DoublePoint(new int[] { 0, -1 }),
new DoublePoint(new int[] { 1, -1 }),
new DoublePoint(new int[] { 1, -2 }),
// third expected cluster
new DoublePoint(new int[] { 13, 3 }),
new DoublePoint(new int[] { 13, 4 }),
new DoublePoint(new int[] { 14, 4 }),
new DoublePoint(new int[] { 14, 7 }),
new DoublePoint(new int[] { 16, 5 }),
new DoublePoint(new int[] { 16, 6 }),
new DoublePoint(new int[] { 17, 4 }),
new DoublePoint(new int[] { 17, 7 })
};
List<CentroidCluster<DoublePoint>> clusters = transformer.cluster(Arrays.asList(points));
Assert.assertEquals(3, clusters.size());
boolean cluster1Found = false;
boolean cluster2Found = false;
boolean cluster3Found = false;
double epsilon = 1e-6;
for (CentroidCluster<DoublePoint> cluster : clusters) {
Clusterable center = cluster.getCenter();
double[] point = center.getPoint();
if (point[0] < 0) {
cluster1Found = true;
Assert.assertEquals(8, cluster.getPoints().size());
Assert.assertEquals(-14, point[0], epsilon);
Assert.assertEquals( 4, point[1], epsilon);
} else if (point[1] < 0) {
cluster2Found = true;
Assert.assertEquals(5, cluster.getPoints().size());
Assert.assertEquals( 0, point[0], epsilon);
Assert.assertEquals(-1, point[1], epsilon);
} else {
cluster3Found = true;
Assert.assertEquals(8, cluster.getPoints().size());
Assert.assertEquals(15, point[0], epsilon);
Assert.assertEquals(5, point[1], epsilon);
}
}
Assert.assertTrue(cluster1Found);
Assert.assertTrue(cluster2Found);
Assert.assertTrue(cluster3Found);
}
}