/**
* 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.common.distance;
import org.apache.mahout.common.MahoutTestCase;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.Vector;
import org.junit.Test;
public final class TestMinkowskiMeasure extends MahoutTestCase {
@Test
public void testMeasure() {
DistanceMeasure minkowskiDistanceMeasure = new MinkowskiDistanceMeasure(1.5);
DistanceMeasure manhattanDistanceMeasure = new ManhattanDistanceMeasure();
DistanceMeasure euclideanDistanceMeasure = new EuclideanDistanceMeasure();
Vector[] vectors = {
new DenseVector(new double[]{1, 0, 0, 0, 0, 0}),
new DenseVector(new double[]{1, 1, 1, 0, 0, 0}),
new DenseVector(new double[]{1, 1, 1, 1, 1, 1})
};
double[][] minkowskiDistanceMatrix = new double[3][3];
double[][] manhattanDistanceMatrix = new double[3][3];
double[][] euclideanDistanceMatrix = new double[3][3];
for (int a = 0; a < 3; a++) {
for (int b = 0; b < 3; b++) {
minkowskiDistanceMatrix[a][b] = minkowskiDistanceMeasure.distance(vectors[a], vectors[b]);
manhattanDistanceMatrix[a][b] = manhattanDistanceMeasure.distance(vectors[a], vectors[b]);
euclideanDistanceMatrix[a][b] = euclideanDistanceMeasure.distance(vectors[a], vectors[b]);
}
}
for (int a = 0; a < 3; a++) {
for (int b = 0; b < 3; b++) {
assertTrue(minkowskiDistanceMatrix[a][b] <= manhattanDistanceMatrix[a][b]);
assertTrue(minkowskiDistanceMatrix[a][b] >= euclideanDistanceMatrix[a][b]);
}
}
assertEquals(0.0, minkowskiDistanceMatrix[0][0], EPSILON);
assertTrue(minkowskiDistanceMatrix[0][0] < minkowskiDistanceMatrix[0][1]);
assertTrue(minkowskiDistanceMatrix[0][1] < minkowskiDistanceMatrix[0][2]);
}
}