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1   /*
2    * Licensed to the Apache Software Foundation (ASF) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The ASF licenses this file to You under the Apache License, Version 2.0
6    * (the "License"); you may not use this file except in compliance with
7    * the License.  You may obtain a copy of the License at
8    *
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   *
11   * Unless required by applicable law or agreed to in writing, software
12   * distributed under the License is distributed on an "AS IS" BASIS,
13   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14   * See the License for the specific language governing permissions and
15   * limitations under the License.
16   */
17  package org.apache.commons.math4.legacy.stat.descriptive.moment;
18  
19  import org.apache.commons.math4.legacy.stat.descriptive.StorelessUnivariateStatisticAbstractTest;
20  import org.apache.commons.math4.legacy.stat.descriptive.UnivariateStatistic;
21  import org.junit.Assert;
22  import org.junit.Test;
23  
24  /**
25   * Test cases for the {@link UnivariateStatistic} class.
26   */
27  public class MeanTest extends StorelessUnivariateStatisticAbstractTest{
28  
29      protected Mean stat;
30  
31      /**
32       * {@inheritDoc}
33       */
34      @Override
35      public UnivariateStatistic getUnivariateStatistic() {
36          return new Mean();
37      }
38  
39      /**
40       * {@inheritDoc}
41       */
42      @Override
43      public double expectedValue() {
44          return this.mean;
45      }
46  
47      /**Expected value for  the testArray defined in UnivariateStatisticAbstractTest */
48      public double expectedWeightedValue() {
49          return this.weightedMean;
50      }
51  
52      @Test
53      public void testSmallSamples() {
54          Mean mean = new Mean();
55          Assert.assertTrue(Double.isNaN(mean.getResult()));
56          mean.increment(1d);
57          Assert.assertEquals(1d, mean.getResult(), 0);
58      }
59  
60      @Test
61      public void testWeightedMean() {
62          Mean mean = new Mean();
63          Assert.assertEquals(expectedWeightedValue(), mean.evaluate(testArray, testWeightsArray, 0, testArray.length), getTolerance());
64          Assert.assertEquals(expectedValue(), mean.evaluate(testArray, identicalWeightsArray, 0, testArray.length), getTolerance());
65      }
66  }