/**
* 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.mahout.clustering;
import org.apache.mahout.common.MahoutTestCase;
import org.apache.mahout.common.distance.DistanceMeasure;
import org.apache.mahout.common.distance.ManhattanDistanceMeasure;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.SequentialAccessSparseVector;
import org.apache.mahout.math.Vector;
import org.junit.Test;
public final class TestClusterInterface extends MahoutTestCase {
private static final DistanceMeasure measure = new ManhattanDistanceMeasure();
@Test
public void testClusterAsFormatString() {
double[] d = { 1.1, 2.2, 3.3 };
Vector m = new DenseVector(d);
Cluster cluster = new org.apache.mahout.clustering.kmeans.Kluster(m, 123, measure);
String formatString = cluster.asFormatString(null);
assertTrue(formatString.contains("\"r\":[]"));
assertTrue(formatString.contains("\"c\":[1.1,2.2,3.3]"));
assertTrue(formatString.contains("\"n\":0"));
assertTrue(formatString.contains("\"identifier\":\"CL-123\""));
}
@Test
public void testClusterAsFormatStringSparse() {
double[] d = { 1.1, 0.0, 3.3 };
Vector m = new SequentialAccessSparseVector(3);
m.assign(d);
Cluster cluster = new org.apache.mahout.clustering.kmeans.Kluster(m, 123, measure);
String formatString = cluster.asFormatString(null);
assertTrue(formatString.contains("\"r\":[]"));
assertTrue(formatString.contains("\"c\":[{\"0\":1.1},{\"2\":3.3}]"));
assertTrue(formatString.contains("\"n\":0"));
assertTrue(formatString.contains("\"identifier\":\"CL-123\""));
}
@Test
public void testClusterAsFormatStringWithBindings() {
double[] d = { 1.1, 2.2, 3.3 };
Vector m = new DenseVector(d);
Cluster cluster = new org.apache.mahout.clustering.kmeans.Kluster(m, 123, measure);
String[] bindings = { "fee", null, "foo" };
String formatString = cluster.asFormatString(bindings);
assertTrue(formatString.contains("\"r\":[]"));
assertTrue(formatString.contains("\"c\":[{\"fee\":1.1},{\"1\":2.2},{\"foo\":3.3}]"));
assertTrue(formatString.contains("\"n\":0"));
assertTrue(formatString.contains("\"identifier\":\"CL-123\""));
}
@Test
public void testClusterAsFormatStringSparseWithBindings() {
double[] d = { 1.1, 0.0, 3.3 };
Vector m = new SequentialAccessSparseVector(3);
m.assign(d);
Cluster cluster = new org.apache.mahout.clustering.kmeans.Kluster(m, 123, measure);
String formatString = cluster.asFormatString(null);
assertTrue(formatString.contains("\"r\":[]"));
assertTrue(formatString.contains("\"c\":[{\"0\":1.1},{\"2\":3.3}]"));
assertTrue(formatString.contains("\"n\":0"));
assertTrue(formatString.contains("\"identifier\":\"CL-123\""));
}
}