/**
* 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.
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package org.apache.mahout.clustering.kmeans;
import java.util.Collection;
import java.util.List;
import com.google.common.collect.Sets;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.mapreduce.Job;
import org.apache.mahout.clustering.Cluster;
import org.apache.mahout.clustering.ClusteringTestUtils;
import org.apache.mahout.clustering.iterator.ClusterWritable;
import org.apache.mahout.common.MahoutTestCase;
import org.apache.mahout.common.distance.ManhattanDistanceMeasure;
import org.apache.mahout.common.iterator.sequencefile.SequenceFileValueIterable;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.VectorWritable;
import org.junit.Before;
import org.junit.Test;
import com.google.common.collect.Lists;
public final class TestRandomSeedGenerator extends MahoutTestCase {
private static final double[][] RAW = {{1, 1}, {2, 1}, {1, 2}, {2, 2},
{3, 3}, {4, 4}, {5, 4}, {4, 5}, {5, 5}};
private FileSystem fs;
private static List<VectorWritable> getPoints() {
List<VectorWritable> points = Lists.newArrayList();
for (double[] fr : RAW) {
Vector vec = new RandomAccessSparseVector(fr.length);
vec.assign(fr);
points.add(new VectorWritable(vec));
}
return points;
}
@Override
@Before
public void setUp() throws Exception {
super.setUp();
Configuration conf = new Configuration();
fs = FileSystem.get(conf);
}
/** Story: test random seed generation generates 4 clusters with proper ids and data */
@Test
public void testRandomSeedGenerator() throws Exception {
List<VectorWritable> points = getPoints();
Job job = new Job();
Configuration conf = job.getConfiguration();
job.setMapOutputValueClass(VectorWritable.class);
Path input = getTestTempFilePath("random-input");
Path output = getTestTempDirPath("random-output");
ClusteringTestUtils.writePointsToFile(points, input, fs, conf);
RandomSeedGenerator.buildRandom(conf, input, output, 4, new ManhattanDistanceMeasure());
int clusterCount = 0;
Collection<Integer> set = Sets.newHashSet();
for (ClusterWritable clusterWritable :
new SequenceFileValueIterable<ClusterWritable>(new Path(output, "part-randomSeed"), true, conf)) {
clusterCount++;
Cluster cluster = clusterWritable.getValue();
int id = cluster.getId();
assertTrue(set.add(id)); // validate unique id's
Vector v = cluster.getCenter();
assertVectorEquals(RAW[id], v); // validate values match
}
assertEquals(4, clusterCount); // validate sample count
}
private static void assertVectorEquals(double[] raw, Vector v) {
assertEquals(raw.length, v.size());
for (int i=0; i < raw.length; i++) {
assertEquals(raw[i], v.getQuick(i), EPSILON);
}
}
}