/*
* 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.commons.math4.stat.descriptive;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
import org.apache.commons.math4.stat.descriptive.DescriptiveStatistics;
import org.apache.commons.math4.util.FastMath;
import org.apache.commons.math4.util.NumberTransformer;
import org.apache.commons.math4.util.TransformerMap;
import org.junit.Assert;
import org.junit.Test;
/**
* Test cases for the {@link ListUnivariateImpl} class.
*/
public final class MixedListUnivariateImplTest {
private final double one = 1;
private final float two = 2;
private final int three = 3;
private final double mean = 2;
private final double sumSq = 18;
private final double sum = 8;
private final double var = 0.666666666666666666667;
private final double std = FastMath.sqrt(var);
private final double n = 4;
private final double min = 1;
private final double max = 3;
private final double tolerance = 10E-15;
private TransformerMap transformers = new TransformerMap();
public MixedListUnivariateImplTest() {
transformers = new TransformerMap();
transformers.putTransformer(Foo.class, new FooTransformer());
transformers.putTransformer(Bar.class, new BarTransformer());
}
/** test stats */
@Test
public void testStats() {
List<Object> externalList = new ArrayList<>();
DescriptiveStatistics u = new ListUnivariateImpl(externalList,transformers);
Assert.assertEquals("total count", 0, u.getN(), tolerance);
u.addValue(one);
u.addValue(two);
u.addValue(two);
u.addValue(three);
Assert.assertEquals("N", n, u.getN(), tolerance);
Assert.assertEquals("sum", sum, u.getSum(), tolerance);
Assert.assertEquals("sumsq", sumSq, u.getSumsq(), tolerance);
Assert.assertEquals("var", var, u.getVariance(), tolerance);
Assert.assertEquals("std", std, u.getStandardDeviation(), tolerance);
Assert.assertEquals("mean", mean, u.getMean(), tolerance);
Assert.assertEquals("min", min, u.getMin(), tolerance);
Assert.assertEquals("max", max, u.getMax(), tolerance);
u.clear();
Assert.assertEquals("total count", 0, u.getN(), tolerance);
}
@Test
public void testN0andN1Conditions() {
DescriptiveStatistics u = new ListUnivariateImpl(new ArrayList<>(),transformers);
Assert.assertTrue(
"Mean of n = 0 set should be NaN",
Double.isNaN(u.getMean()));
Assert.assertTrue(
"Standard Deviation of n = 0 set should be NaN",
Double.isNaN(u.getStandardDeviation()));
Assert.assertTrue(
"Variance of n = 0 set should be NaN",
Double.isNaN(u.getVariance()));
u.addValue(one);
Assert.assertTrue(
"Mean of n = 1 set should be value of single item n1, instead it is " + u.getMean() ,
u.getMean() == one);
Assert.assertTrue(
"StdDev of n = 1 set should be zero, instead it is: "
+ u.getStandardDeviation(),
u.getStandardDeviation() == 0);
Assert.assertTrue(
"Variance of n = 1 set should be zero",
u.getVariance() == 0);
}
@Test
public void testSkewAndKurtosis() {
ListUnivariateImpl u =
new ListUnivariateImpl(new ArrayList<>(), transformers);
u.addObject("12.5");
u.addObject(Integer.valueOf(12));
u.addObject("11.8");
u.addObject("14.2");
u.addObject(new Foo());
u.addObject("14.5");
u.addObject(Long.valueOf(21));
u.addObject("8.2");
u.addObject("10.3");
u.addObject("11.3");
u.addObject(Float.valueOf(14.1f));
u.addObject("9.9");
u.addObject("12.2");
u.addObject(new Bar());
u.addObject("12.1");
u.addObject("11");
u.addObject(Double.valueOf(19.8));
u.addObject("11");
u.addObject("10");
u.addObject("8.8");
u.addObject("9");
u.addObject("12.3");
Assert.assertEquals("mean", 12.40455, u.getMean(), 0.0001);
Assert.assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
Assert.assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
Assert.assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
}
@Test
public void testProductAndGeometricMean() {
ListUnivariateImpl u = new ListUnivariateImpl(new ArrayList<>(),transformers);
u.setWindowSize(10);
u.addValue(1.0);
u.addValue(2.0);
u.addValue(3.0);
u.addValue(4.0);
Assert.assertEquals(
"Geometric mean not expected",
2.213364,
u.getGeometricMean(),
0.00001);
// Now test rolling - StorelessDescriptiveStatistics should discount the contribution
// of a discarded element
for (int i = 0; i < 10; i++) {
u.addValue(i + 2);
}
// Values should be (2,3,4,5,6,7,8,9,10,11)
Assert.assertEquals(
"Geometric mean not expected",
5.755931,
u.getGeometricMean(),
0.00001);
}
public static final class Foo {
public String heresFoo() {
return "14.9";
}
}
public static final class FooTransformer implements NumberTransformer, Serializable {
private static final long serialVersionUID = -4252248129291326127L;
@Override
public double transform(Object o) {
return Double.parseDouble(((Foo) o).heresFoo());
}
}
public static final class Bar {
public String heresBar() {
return "12.0";
}
}
public static final class BarTransformer implements NumberTransformer, Serializable {
private static final long serialVersionUID = -1768345377764262043L;
@Override
public double transform(Object o) {
return Double.parseDouble(((Bar) o).heresBar());
}
}
}