001 /* 002 * Licensed to the Apache Software Foundation (ASF) under one or more 003 * contributor license agreements. See the NOTICE file distributed with 004 * this work for additional information regarding copyright ownership. 005 * The ASF licenses this file to You under the Apache License, Version 2.0 006 * (the "License"); you may not use this file except in compliance with 007 * the License. You may obtain a copy of the License at 008 * 009 * http://www.apache.org/licenses/LICENSE-2.0 010 * 011 * Unless required by applicable law or agreed to in writing, software 012 * distributed under the License is distributed on an "AS IS" BASIS, 013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 014 * See the License for the specific language governing permissions and 015 * limitations under the License. 016 */ 017 package org.apache.commons.math.stat.descriptive.moment; 018 019 import junit.framework.Test; 020 import junit.framework.TestSuite; 021 022 import org.apache.commons.math.stat.descriptive.StorelessUnivariateStatisticAbstractTest; 023 import org.apache.commons.math.stat.descriptive.UnivariateStatistic; 024 025 /** 026 * Test cases for the {@link UnivariateStatistic} class. 027 * @version $Revision: 762087 $ $Date: 2009-04-05 10:20:18 -0400 (Sun, 05 Apr 2009) $ 028 */ 029 public class GeometricMeanTest extends StorelessUnivariateStatisticAbstractTest{ 030 031 protected GeometricMean stat; 032 033 /** 034 * @param name 035 */ 036 public GeometricMeanTest(String name) { 037 super(name); 038 } 039 040 public static Test suite() { 041 TestSuite suite = new TestSuite(GeometricMeanTest.class); 042 suite.setName("Mean Tests"); 043 return suite; 044 } 045 046 /** 047 * {@inheritDoc} 048 */ 049 @Override 050 public UnivariateStatistic getUnivariateStatistic() { 051 return new GeometricMean(); 052 } 053 054 /** 055 * {@inheritDoc} 056 */ 057 @Override 058 public double expectedValue() { 059 return this.geoMean; 060 } 061 062 public void testSpecialValues() { 063 GeometricMean mean = new GeometricMean(); 064 // empty 065 assertTrue(Double.isNaN(mean.getResult())); 066 067 // finite data 068 mean.increment(1d); 069 assertFalse(Double.isNaN(mean.getResult())); 070 071 // add 0 -- makes log sum blow to minus infinity, should make 0 072 mean.increment(0d); 073 assertEquals(0d, mean.getResult(), 0); 074 075 // add positive infinity - note the minus infinity above 076 mean.increment(Double.POSITIVE_INFINITY); 077 assertTrue(Double.isNaN(mean.getResult())); 078 079 // clear 080 mean.clear(); 081 assertTrue(Double.isNaN(mean.getResult())); 082 083 // positive infinity by itself 084 mean.increment(Double.POSITIVE_INFINITY); 085 assertEquals(Double.POSITIVE_INFINITY, mean.getResult(), 0); 086 087 // negative value -- should make NaN 088 mean.increment(-2d); 089 assertTrue(Double.isNaN(mean.getResult())); 090 } 091 092 }