/** * 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]); } }