removed deprecated factory methods and classes
they were replaced by setter injection as of 1.2 git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/branches/MATH_2_0@651230 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Luc Maisonobe
parent
5ae0852fe0
commit
cffe7c6cc6
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@ -20,7 +20,6 @@ import java.io.Serializable;
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import java.lang.reflect.InvocationTargetException;
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import java.util.Arrays;
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import org.apache.commons.discovery.tools.DiscoverClass;
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import org.apache.commons.math.stat.descriptive.moment.GeometricMean;
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import org.apache.commons.math.stat.descriptive.moment.Kurtosis;
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import org.apache.commons.math.stat.descriptive.moment.Mean;
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@ -56,8 +55,8 @@ import org.apache.commons.math.util.ResizableDoubleArray;
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public class DescriptiveStatistics implements StatisticalSummary, Serializable {
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/** Serialization UID */
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private static final long serialVersionUID = -2734185686570407433L;
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private static final long serialVersionUID = 4133067267405273064L;
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/** hold the window size **/
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protected int windowSize = INFINITE_WINDOW;
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@ -112,39 +111,6 @@ public class DescriptiveStatistics implements StatisticalSummary, Serializable {
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setWindowSize(window);
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}
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/**
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* Create an instance of a <code>DescriptiveStatistics</code>
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* @param cls the type of <code>DescriptiveStatistics</code> object to
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* create.
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* @return a new instance.
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* @throws InstantiationException is thrown if the object can not be
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* created.
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* @throws IllegalAccessException is thrown if the type's default
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* constructor is not accessible.
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* @deprecated to be removed in commons-math 2.0
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*/
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public static DescriptiveStatistics newInstance(Class cls) throws InstantiationException, IllegalAccessException {
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return (DescriptiveStatistics)cls.newInstance();
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}
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/**
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* Create an instance of a <code>DescriptiveStatistics</code>
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* @return a new DescriptiveStatistics instance.
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* @deprecated to be removed in commons-math 2.0
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*/
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public static DescriptiveStatistics newInstance() {
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DescriptiveStatistics factory = null;
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try {
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DiscoverClass dc = new DiscoverClass();
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factory = (DescriptiveStatistics) dc.newInstance(
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DescriptiveStatistics.class,
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"org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl");
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} catch(Throwable t) {
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return new DescriptiveStatisticsImpl();
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}
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return factory;
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}
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/**
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* Represents an infinite window size. When the {@link #getWindowSize()}
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* returns this value, there is no limit to the number of data values
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@ -15,7 +15,6 @@ package org.apache.commons.math.stat.descriptive;
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import java.io.Serializable;
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import org.apache.commons.discovery.tools.DiscoverClass;
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import org.apache.commons.math.stat.descriptive.moment.GeometricMean;
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import org.apache.commons.math.stat.descriptive.moment.Mean;
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import org.apache.commons.math.stat.descriptive.moment.SecondMoment;
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@ -55,37 +54,7 @@ import org.apache.commons.math.util.MathUtils;
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public class SummaryStatistics implements StatisticalSummary, Serializable {
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/** Serialization UID */
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private static final long serialVersionUID = -3346512372447011854L;
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/**
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* Create an instance of a <code>SummaryStatistics</code>
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* @param cls the type of <code>SummaryStatistics</code> object to create.
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* @return a new instance.
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* @deprecated to be removed in commons-math 2.0
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* @throws InstantiationException is thrown if the object can not be
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* created.
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* @throws IllegalAccessException is thrown if the type's default
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* constructor is not accessible.
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*/
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public static SummaryStatistics newInstance(Class cls) throws InstantiationException, IllegalAccessException {
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return (SummaryStatistics)cls.newInstance();
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}
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/**
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* Create an instance of a <code>SummaryStatistics</code>
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* @return a new SummaryStatistics instance.
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* @deprecated to be removed in commons-math 2.0
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*/
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public static SummaryStatistics newInstance() {
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SummaryStatistics instance = null;
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try {
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DiscoverClass dc = new DiscoverClass();
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instance = (SummaryStatistics)dc.newInstance(SummaryStatistics.class, "org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl");
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} catch (Throwable t) {
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return new SummaryStatisticsImpl();
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}
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return instance;
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}
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private static final long serialVersionUID = -2021321786743555871L;
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/**
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* Construct a SummaryStatistics instance
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@ -19,7 +19,6 @@ package org.apache.commons.math.stat.inference;
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import org.apache.commons.math.MathException;
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import org.apache.commons.math.distribution.ChiSquaredDistribution;
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import org.apache.commons.math.distribution.ChiSquaredDistributionImpl;
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import org.apache.commons.math.distribution.DistributionFactory;
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/**
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* Implements Chi-Square test statistics defined in the
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@ -329,16 +328,6 @@ public class ChiSquareTestImpl implements UnknownDistributionChiSquareTest {
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}
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//--------------------- Protected methods ---------------------------------
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/**
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* Gets a DistributionFactory to use in creating ChiSquaredDistribution instances.
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* @deprecated inject ChiSquaredDistribution instances directly instead of
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* using a factory.
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*/
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protected DistributionFactory getDistributionFactory() {
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return DistributionFactory.newInstance();
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}
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//--------------------- Private array methods -- should find a utility home for these
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/**
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@ -17,7 +17,6 @@
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package org.apache.commons.math.stat.inference;
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import org.apache.commons.math.MathException;
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import org.apache.commons.math.distribution.DistributionFactory;
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import org.apache.commons.math.distribution.TDistribution;
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import org.apache.commons.math.distribution.TDistributionImpl;
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import org.apache.commons.math.stat.StatUtils;
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@ -919,15 +918,6 @@ public class TTestImpl implements TTest {
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//----------------------------------------------- Protected methods
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/**
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* Gets a DistributionFactory to use in creating TDistribution instances.
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* @return a distribution factory.
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* @deprecated inject TDistribution directly instead of using a factory.
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*/
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protected DistributionFactory getDistributionFactory() {
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return DistributionFactory.newInstance();
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}
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/**
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* Computes approximate degrees of freedom for 2-sample t-test.
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*
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@ -1,67 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.stat.inference;
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import org.apache.commons.discovery.tools.DiscoverClass;
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/**
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* Abstract factory to create inference test instances.
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*
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* @since 1.1
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* @version $Revision$ $Date$
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* @deprecated as of 1.2, pluggability of test instances is now provided through
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* constructors and setters.
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*/
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public abstract class TestFactory {
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/**
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* Default constructor.
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*/
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protected TestFactory() {
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super();
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}
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/**
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* Create an instance of a <code>TestFactory</code>
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*
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* @return a new factory.
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*/
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public static TestFactory newInstance() {
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TestFactory factory = null;
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try {
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DiscoverClass dc = new DiscoverClass();
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factory = (TestFactory) dc.newInstance(
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TestFactory.class,
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"org.apache.commons.math.stat.inference.TestFactoryImpl");
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} catch(Throwable t) {
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return new TestFactoryImpl();
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}
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return factory;
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}
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/**
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* Create a TTest instance.
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*
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* @return a new TTest instance
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*/
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public abstract TTest createTTest();
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/**
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* Create a ChiSquareTest instance.
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*
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* @return a new ChiSquareTest instance
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*/
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public abstract ChiSquareTest createChiSquareTest();
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}
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@ -1,55 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.stat.inference;
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/**
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* A concrete inference test factory. This is the default factory used by
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* Commons-Math.
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*
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* @deprecated as of 1.2, pluggability of test instances is now provided through
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* constructors and setters.
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* @since 1.1
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* @version $Revision$ $Date$
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*/
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public class TestFactoryImpl extends TestFactory {
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/**
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* Default constructor.
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*/
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public TestFactoryImpl() {
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super();
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}
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/**
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* Create a TTest instance.
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*
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* @return a new TTest instance
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*/
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public TTest createTTest() {
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return new TTestImpl();
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}
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/**
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* Create a ChiSquareTest instance.
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*
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* @return a new ChiSquareTest instance
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*/
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public ChiSquareTest createChiSquareTest() {
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return new ChiSquareTestImpl();
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}
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}
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@ -1,398 +0,0 @@
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/*
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* Licensed to the Apache Software Foundation (ASF) under one or more
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* contributor license agreements. See the NOTICE file distributed with
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* this work for additional information regarding copyright ownership.
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* The ASF licenses this file to You under the Apache License, Version 2.0
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* (the "License"); you may not use this file except in compliance with
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* the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.commons.math.stat.descriptive;
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import junit.framework.TestCase;
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import org.apache.commons.math.TestUtils;
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import org.apache.commons.math.random.RandomData;
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import org.apache.commons.math.random.RandomDataImpl;
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/**
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* Test cases for the DescriptiveStatistics implementations.
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*
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* @version $Revision$ $Date$
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* @deprecated should be moved down into DescriptiveStatisticsTest
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* when DescriptiveStatisticsImpl is removed in 2.0
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*/
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public abstract class DescriptiveStatisticsAbstractTest extends TestCase {
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private double var = 0.666666666666666666667;
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private double max = 3;
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private double mean = 2;
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private double min = 1;
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private double n = 4;
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private double one = 1;
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private double std = Math.sqrt(var);
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private double sum = 8;
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private double sumSq = 18;
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private int three = 3;
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private double tolerance = 10E-15;
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private float two = 2;
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public DescriptiveStatisticsAbstractTest(String name) {
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super(name);
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}
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protected abstract DescriptiveStatistics createDescriptiveStatistics();
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public void setUp() {
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}
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public void testAddValue() {
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double[] test1 = {5,4,3,2,1,0};
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double[] test2 = {5,2,1,0,4,3};
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DescriptiveStatistics stats = createDescriptiveStatistics();
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stats.setWindowSize(12);
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for(int i = 0; i < test1.length; i++){
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stats.addValue(test1[i]);
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}
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double[] test3 = stats.getValues();
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for(int i = 0; i < 6; i++){
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assertEquals( "Added value ["+i+"] not equal",
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test3[i], test1[i],0.0);
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//System.out.println(test3[i] + " "+test1[i]);
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}
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for(int i = 0; i < test2.length; i++){
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stats.addValue(test2[i]);
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}
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test3 = stats.getValues();
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for(int i = 6; i < 12; i++){
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assertEquals( "Added value ["+i+"] not equal",
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test3[i], test2[i-6],0.0);
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//System.out.println(test3[i] + " "+test2[i-6]);
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}
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for(int i = 0; i < test2.length; i++){
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stats.addValue(test2[i]);
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}
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test3 = stats.getValues();
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|
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for(int i = 0; i < 6; i++){
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assertEquals( "Added value ["+i+"] not equal",
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test3[i], test2[i],0.0);
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//System.out.println(test3[i] + " "+test2[i]);
|
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}
|
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|
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for(int i = 6; i < 12; i++){
|
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assertEquals( "Added value ["+i+"] not equal",
|
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test3[i], test2[i-6],0.0);
|
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//System.out.println(test3[i] + " "+test2[i-6]);
|
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}
|
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|
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}
|
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|
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public void testGetSortedValues() {
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double[] test1 = {5,4,3,2,1};
|
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double[] test2 = {5,2,1,3,4,0};
|
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double[] test3 = {1};
|
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int[] testi = null;
|
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double[] test4 = null;
|
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RandomData rd = new RandomDataImpl();
|
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tstGetSortedValues(test1);
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tstGetSortedValues(test2);
|
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tstGetSortedValues(test3);
|
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for (int i = 0; i < 10; i++) {
|
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testi = rd.nextPermutation(10,6);
|
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test4 = new double[6];
|
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for (int j = 0; j < testi.length; j++) {
|
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test4[j] = (double) testi[j];
|
||||
}
|
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tstGetSortedValues(test4);
|
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}
|
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for (int i = 0; i < 10; i++) {
|
||||
testi = rd.nextPermutation(10,5);
|
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test4 = new double[5];
|
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for (int j = 0; j < testi.length; j++) {
|
||||
test4[j] = (double) testi[j];
|
||||
}
|
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tstGetSortedValues(test4);
|
||||
}
|
||||
}
|
||||
|
||||
public void testN0andN1Conditions() throws Exception {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
|
||||
assertTrue("Mean of n = 0 set should be NaN",
|
||||
Double.isNaN( u.getMean() ) );
|
||||
assertTrue("Standard Deviation of n = 0 set should be NaN",
|
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Double.isNaN( u.getStandardDeviation() ) );
|
||||
assertTrue("Variance of n = 0 set should be NaN",
|
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Double.isNaN(u.getVariance() ) );
|
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|
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u.addValue(one);
|
||||
|
||||
assertTrue( "Mean of n = 1 set should be value of single item n1",
|
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u.getMean() == one);
|
||||
assertTrue( "StdDev of n = 1 set should be zero, instead it is: "
|
||||
+ u.getStandardDeviation(), u.getStandardDeviation() == 0);
|
||||
assertTrue( "Variance of n = 1 set should be zero",
|
||||
u.getVariance() == 0);
|
||||
}
|
||||
|
||||
public void testNewInstanceClassNull() {
|
||||
try {
|
||||
DescriptiveStatistics.newInstance((Class)null);
|
||||
fail("null is not a valid descriptive statistics class");
|
||||
} catch (NullPointerException ex) {
|
||||
// success
|
||||
} catch (Exception ex) {
|
||||
fail();
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
public void testNewInstanceClassValid() {
|
||||
try {
|
||||
DescriptiveStatistics u = DescriptiveStatistics.newInstance(
|
||||
DescriptiveStatisticsImpl.class);
|
||||
assertNotNull(u);
|
||||
assertTrue(u instanceof DescriptiveStatisticsImpl);
|
||||
} catch (InstantiationException ex) {
|
||||
fail();
|
||||
} catch (IllegalAccessException ex) {
|
||||
fail();
|
||||
}
|
||||
}
|
||||
|
||||
public void testPercentiles() {
|
||||
double[] test = {5,4,3,2,1};
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
u.setWindowSize(110);
|
||||
for (int i = 0; i < test.length; i++) {
|
||||
u.addValue(test[i]);
|
||||
}
|
||||
assertEquals("expecting min",1,u.getPercentile(5),10E-12);
|
||||
assertEquals("expecting max",5,u.getPercentile(99),10E-12);
|
||||
assertEquals("expecting middle",3,u.getPercentile(50),10E-12);
|
||||
try {
|
||||
u.getPercentile(0);
|
||||
fail("expecting IllegalArgumentException for getPercentile(0)");
|
||||
} catch (IllegalArgumentException ex) {
|
||||
;
|
||||
}
|
||||
try {
|
||||
u.getPercentile(120);
|
||||
fail("expecting IllegalArgumentException for getPercentile(120)");
|
||||
} catch (IllegalArgumentException ex) {
|
||||
;
|
||||
}
|
||||
|
||||
u.clear();
|
||||
double[] test2 = {1,2,3,4};
|
||||
for (int i = 0; i < test2.length; i++) {
|
||||
u.addValue(test2[i]);
|
||||
}
|
||||
assertEquals("Q1",1.25,u.getPercentile(25),10E-12);
|
||||
assertEquals("Q3",3.75,u.getPercentile(75),10E-12);
|
||||
assertEquals("Q2",2.5,u.getPercentile(50),10E-12);
|
||||
|
||||
u.clear();
|
||||
double[] test3 = {1};
|
||||
for (int i = 0; i < test3.length; i++) {
|
||||
u.addValue(test3[i]);
|
||||
}
|
||||
assertEquals("Q1",1,u.getPercentile(25),10E-12);
|
||||
assertEquals("Q3",1,u.getPercentile(75),10E-12);
|
||||
assertEquals("Q2",1,u.getPercentile(50),10E-12);
|
||||
|
||||
u.clear();
|
||||
RandomData rd = new RandomDataImpl();
|
||||
int[] testi = rd.nextPermutation(100,100); // will contain 0-99
|
||||
for (int j = 0; j < testi.length; j++) {
|
||||
u.addValue((double) testi[j]); //OK, laugh at me for the cast
|
||||
}
|
||||
for (int i = 1; i < 100; i++) {
|
||||
assertEquals("percentile " + i,
|
||||
(double) i-1 + (double) i*(.01), u.getPercentile(i),10E-12);
|
||||
}
|
||||
|
||||
u.clear();
|
||||
double[] test4 = {1,2,3,4,100};
|
||||
for (int i = 0; i < test4.length; i++) {
|
||||
u.addValue(test4[i]);
|
||||
}
|
||||
assertEquals("80th",80.8,u.getPercentile(80),10E-12);
|
||||
|
||||
u.clear();
|
||||
assertTrue("empty value set should return NaN",
|
||||
Double.isNaN(u.getPercentile(50)));
|
||||
}
|
||||
|
||||
|
||||
|
||||
public void testProductAndGeometricMean() throws Exception {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
u.setWindowSize(10);
|
||||
|
||||
u.addValue( 1.0 );
|
||||
u.addValue( 2.0 );
|
||||
u.addValue( 3.0 );
|
||||
u.addValue( 4.0 );
|
||||
|
||||
//assertEquals( "Product not expected",
|
||||
// 24.0, u.getProduct(), Double.MIN_VALUE );
|
||||
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)
|
||||
|
||||
//assertEquals( "Product not expected", 39916800.0,
|
||||
// u.getProduct(), 0.00001 );
|
||||
assertEquals( "Geometric mean not expected", 5.755931,
|
||||
u.getGeometricMean(), 0.00001 );
|
||||
}
|
||||
|
||||
/** test stats */
|
||||
public void testSerialization() {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
u.addValue(one);
|
||||
u.addValue(two);
|
||||
|
||||
DescriptiveStatistics u2 = (DescriptiveStatistics)TestUtils.serializeAndRecover(u);
|
||||
|
||||
u2.addValue(two);
|
||||
u2.addValue(three);
|
||||
|
||||
assertEquals("N",n,u2.getN(),tolerance);
|
||||
assertEquals("sum",sum,u2.getSum(),tolerance);
|
||||
assertEquals("sumsq",sumSq,u2.getSumsq(),tolerance);
|
||||
assertEquals("var",var,u2.getVariance(),tolerance);
|
||||
assertEquals("std",std,u2.getStandardDeviation(),tolerance);
|
||||
assertEquals("mean",mean,u2.getMean(),tolerance);
|
||||
assertEquals("min",min,u2.getMin(),tolerance);
|
||||
assertEquals("max",max,u2.getMax(),tolerance);
|
||||
|
||||
u2.clear();
|
||||
assertEquals("total count",0,u2.getN(),tolerance);
|
||||
}
|
||||
|
||||
public void testSkewAndKurtosis() {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
|
||||
double[] testArray =
|
||||
{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
|
||||
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
|
||||
for( int i = 0; i < testArray.length; i++) {
|
||||
u.addValue( testArray[i]);
|
||||
}
|
||||
|
||||
assertEquals("mean", 12.40455, u.getMean(), 0.0001);
|
||||
assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
|
||||
assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
|
||||
assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
|
||||
}
|
||||
|
||||
/** test stats */
|
||||
public void testStats() {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
u.addValue(one);
|
||||
u.addValue(two);
|
||||
u.addValue(two);
|
||||
u.addValue(three);
|
||||
assertEquals("N",n,u.getN(),tolerance);
|
||||
assertEquals("sum",sum,u.getSum(),tolerance);
|
||||
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
|
||||
assertEquals("var",var,u.getVariance(),tolerance);
|
||||
assertEquals("std",std,u.getStandardDeviation(),tolerance);
|
||||
assertEquals("mean",mean,u.getMean(),tolerance);
|
||||
assertEquals("min",min,u.getMin(),tolerance);
|
||||
assertEquals("max",max,u.getMax(),tolerance);
|
||||
u.clear();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
}
|
||||
|
||||
public void testToString() {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
assertTrue(u.toString().indexOf("NaN") > 0);
|
||||
assertTrue(u.toString().startsWith("DescriptiveStatistics"));
|
||||
double[] testArray =
|
||||
{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
|
||||
9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
|
||||
for( int i = 0; i < testArray.length; i++) {
|
||||
u.addValue( testArray[i]);
|
||||
}
|
||||
assertTrue(u.toString().indexOf("NaN") == -1);
|
||||
assertTrue(u.toString().startsWith("DescriptiveStatistics"));
|
||||
}
|
||||
|
||||
public void testWindowing() {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
u.setWindowSize(2);
|
||||
|
||||
u.addValue(1.0);
|
||||
assertEquals(1.0, u.getMean(), tolerance);
|
||||
|
||||
u.addValue(2.0);
|
||||
assertEquals(1.5, u.getMean(), tolerance);
|
||||
|
||||
u.addValue(3.0);
|
||||
assertEquals(2.5, u.getMean(), tolerance);
|
||||
|
||||
u.setWindowSize(1);
|
||||
assertEquals(3.0, u.getMean(), tolerance);
|
||||
}
|
||||
|
||||
public void testWindowSize() {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
u.setWindowSize(1234);
|
||||
assertEquals(1234, u.getWindowSize());
|
||||
|
||||
u.addValue(1.0);
|
||||
u.addValue(2.0);
|
||||
u.addValue(3.0);
|
||||
u.addValue(4.0);
|
||||
u.addValue(5.0);
|
||||
assertEquals(5, u.getN());
|
||||
|
||||
u.setWindowSize(DescriptiveStatistics.INFINITE_WINDOW);
|
||||
assertEquals(5, u.getN());
|
||||
}
|
||||
|
||||
private void tstGetSortedValues(double[] test) {
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
u.setWindowSize(test.length);
|
||||
for (int i = 0; i < test.length; i++) {
|
||||
u.addValue(test[i]);
|
||||
}
|
||||
double[] sorted = u.getSortedValues();
|
||||
if (sorted.length != test.length) {
|
||||
fail("wrong length for sorted values array");
|
||||
}
|
||||
for (int i = 0; i < sorted.length-1; i++) {
|
||||
if (sorted[i] > sorted[i+1]) {
|
||||
fail("sorted values out of sequence");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
|
@ -1,40 +0,0 @@
|
|||
/*
|
||||
* 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.math.stat.descriptive;
|
||||
|
||||
import junit.framework.Test;
|
||||
import junit.framework.TestSuite;
|
||||
|
||||
/**
|
||||
* Test cases for the DescriptiveStatisticsImpl class.
|
||||
* @deprecated - to be removed in 2.0 with DescriptiveStatisticsImpl
|
||||
* @version $Revision$ $Date: 2007-08-16 15:36:33 -0500 (Thu, 16 Aug
|
||||
* 2007) $
|
||||
*/
|
||||
public final class DescriptiveStatisticsImplTest extends DescriptiveStatisticsAbstractTest {
|
||||
|
||||
public DescriptiveStatisticsImplTest(String name) {
|
||||
super(name);
|
||||
}
|
||||
|
||||
public static Test suite() {
|
||||
TestSuite suite = new TestSuite(DescriptiveStatisticsImplTest.class);
|
||||
suite.setName("DescriptiveStatisticsImpl Tests");
|
||||
return suite;
|
||||
}
|
||||
|
||||
protected DescriptiveStatistics createDescriptiveStatistics() {
|
||||
return new DescriptiveStatisticsImpl();
|
||||
}
|
||||
}
|
||||
|
|
@ -14,19 +14,18 @@
|
|||
package org.apache.commons.math.stat.descriptive;
|
||||
|
||||
import junit.framework.Test;
|
||||
import junit.framework.TestCase;
|
||||
import junit.framework.TestSuite;
|
||||
|
||||
import org.apache.commons.math.stat.descriptive.rank.Percentile;
|
||||
|
||||
/**
|
||||
* Test cases for the DescriptiveStatistics class.
|
||||
* When DescriptiveStatisticsImpl is removed, this class should replace
|
||||
* DescriptiveStatisticsAbstractTest
|
||||
*
|
||||
* @version $Revision: 592121 $ $Date: 2007-08-16 15:36:33 -0500 (Thu, 16 Aug
|
||||
* 2007) $
|
||||
*/
|
||||
public final class DescriptiveStatisticsTest extends DescriptiveStatisticsAbstractTest {
|
||||
public class DescriptiveStatisticsTest extends TestCase {
|
||||
|
||||
public DescriptiveStatisticsTest(String name) {
|
||||
super(name);
|
||||
|
|
|
|||
|
|
@ -1,228 +0,0 @@
|
|||
/*
|
||||
* 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.math.stat.descriptive;
|
||||
|
||||
|
||||
import junit.framework.TestCase;
|
||||
|
||||
import org.apache.commons.math.TestUtils;
|
||||
/**
|
||||
* Test cases for the {@link SummaryStatisticsImpl} class.
|
||||
*
|
||||
* @version $Revision: 602305 $ $Date: 2007-12-08 03:51:23 +0100 (sam., 08 déc. 2007) $
|
||||
* @deprecated should be moved down into SummaryStatisticsTest
|
||||
* when SummaryStatisticsImpl is removed in 2.0
|
||||
*/
|
||||
|
||||
public abstract class SummaryStatisticsAbstractTest extends TestCase {
|
||||
private double one = 1;
|
||||
private float twoF = 2;
|
||||
private long twoL = 2;
|
||||
private int three = 3;
|
||||
private double mean = 2;
|
||||
private double sumSq = 18;
|
||||
private double sum = 8;
|
||||
private double var = 0.666666666666666666667;
|
||||
private double std = Math.sqrt(var);
|
||||
private double n = 4;
|
||||
private double min = 1;
|
||||
private double max = 3;
|
||||
private double tolerance = 10E-15;
|
||||
|
||||
public SummaryStatisticsAbstractTest(String name) {
|
||||
super(name);
|
||||
}
|
||||
|
||||
protected abstract SummaryStatistics createSummaryStatistics();
|
||||
|
||||
/** test stats */
|
||||
public void testStats() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
u.addValue(one);
|
||||
u.addValue(twoF);
|
||||
u.addValue(twoL);
|
||||
u.addValue(three);
|
||||
assertEquals("N",n,u.getN(),tolerance);
|
||||
assertEquals("sum",sum,u.getSum(),tolerance);
|
||||
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
|
||||
assertEquals("var",var,u.getVariance(),tolerance);
|
||||
assertEquals("std",std,u.getStandardDeviation(),tolerance);
|
||||
assertEquals("mean",mean,u.getMean(),tolerance);
|
||||
assertEquals("min",min,u.getMin(),tolerance);
|
||||
assertEquals("max",max,u.getMax(),tolerance);
|
||||
u.clear();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
}
|
||||
|
||||
public void testN0andN1Conditions() throws Exception {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
assertTrue("Mean of n = 0 set should be NaN",
|
||||
Double.isNaN( u.getMean() ) );
|
||||
assertTrue("Standard Deviation of n = 0 set should be NaN",
|
||||
Double.isNaN( u.getStandardDeviation() ) );
|
||||
assertTrue("Variance of n = 0 set should be NaN",
|
||||
Double.isNaN(u.getVariance() ) );
|
||||
|
||||
/* n=1 */
|
||||
u.addValue(one);
|
||||
assertTrue("mean should be one (n = 1)",
|
||||
u.getMean() == one);
|
||||
assertTrue("geometric should be one (n = 1) instead it is " + u.getGeometricMean(),
|
||||
u.getGeometricMean() == one);
|
||||
assertTrue("Std should be zero (n = 1)",
|
||||
u.getStandardDeviation() == 0.0);
|
||||
assertTrue("variance should be zero (n = 1)",
|
||||
u.getVariance() == 0.0);
|
||||
|
||||
/* n=2 */
|
||||
u.addValue(twoF);
|
||||
assertTrue("Std should not be zero (n = 2)",
|
||||
u.getStandardDeviation() != 0.0);
|
||||
assertTrue("variance should not be zero (n = 2)",
|
||||
u.getVariance() != 0.0);
|
||||
|
||||
}
|
||||
|
||||
public void testProductAndGeometricMean() throws Exception {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
u.addValue( 1.0 );
|
||||
u.addValue( 2.0 );
|
||||
u.addValue( 3.0 );
|
||||
u.addValue( 4.0 );
|
||||
|
||||
assertEquals( "Geometric mean not expected", 2.213364,
|
||||
u.getGeometricMean(), 0.00001 );
|
||||
}
|
||||
|
||||
public void testNaNContracts() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
assertTrue("mean not NaN",Double.isNaN(u.getMean()));
|
||||
assertTrue("min not NaN",Double.isNaN(u.getMin()));
|
||||
assertTrue("std dev not NaN",Double.isNaN(u.getStandardDeviation()));
|
||||
assertTrue("var not NaN",Double.isNaN(u.getVariance()));
|
||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
||||
|
||||
u.addValue(1.0);
|
||||
|
||||
assertEquals( "mean not expected", 1.0,
|
||||
u.getMean(), Double.MIN_VALUE);
|
||||
assertEquals( "variance not expected", 0.0,
|
||||
u.getVariance(), Double.MIN_VALUE);
|
||||
assertEquals( "geometric mean not expected", 1.0,
|
||||
u.getGeometricMean(), Double.MIN_VALUE);
|
||||
|
||||
u.addValue(-1.0);
|
||||
|
||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
||||
|
||||
u.addValue(0.0);
|
||||
|
||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
||||
|
||||
//FiXME: test all other NaN contract specs
|
||||
}
|
||||
|
||||
public void testGetSummary() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
StatisticalSummary summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
u.addValue(1d);
|
||||
summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
u.addValue(2d);
|
||||
summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
u.addValue(2d);
|
||||
summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
}
|
||||
|
||||
public void testSerialization() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
// Empty test
|
||||
TestUtils.checkSerializedEquality(u);
|
||||
SummaryStatistics s = (SummaryStatistics) TestUtils.serializeAndRecover(u);
|
||||
StatisticalSummary summary = s.getSummary();
|
||||
verifySummary(u, summary);
|
||||
|
||||
// Add some data
|
||||
u.addValue(2d);
|
||||
u.addValue(1d);
|
||||
u.addValue(3d);
|
||||
u.addValue(4d);
|
||||
u.addValue(5d);
|
||||
|
||||
// Test again
|
||||
TestUtils.checkSerializedEquality(u);
|
||||
s = (SummaryStatistics) TestUtils.serializeAndRecover(u);
|
||||
summary = s.getSummary();
|
||||
verifySummary(u, summary);
|
||||
|
||||
}
|
||||
|
||||
public void testEqualsAndHashCode() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
SummaryStatistics t = null;
|
||||
int emptyHash = u.hashCode();
|
||||
assertTrue("reflexive", u.equals(u));
|
||||
assertFalse("non-null compared to null", u.equals(t));
|
||||
assertFalse("wrong type", u.equals(new Double(0)));
|
||||
t = createSummaryStatistics();
|
||||
assertTrue("empty instances should be equal", t.equals(u));
|
||||
assertTrue("empty instances should be equal", u.equals(t));
|
||||
assertEquals("empty hash code", emptyHash, t.hashCode());
|
||||
|
||||
// Add some data to u
|
||||
u.addValue(2d);
|
||||
u.addValue(1d);
|
||||
u.addValue(3d);
|
||||
u.addValue(4d);
|
||||
assertFalse("different n's should make instances not equal", t.equals(u));
|
||||
assertFalse("different n's should make instances not equal", u.equals(t));
|
||||
assertTrue("different n's should make hashcodes different",
|
||||
u.hashCode() != t.hashCode());
|
||||
|
||||
//Add data in same order to t
|
||||
t.addValue(2d);
|
||||
t.addValue(1d);
|
||||
t.addValue(3d);
|
||||
t.addValue(4d);
|
||||
assertTrue("summaries based on same data should be equal", t.equals(u));
|
||||
assertTrue("summaries based on same data should be equal", u.equals(t));
|
||||
assertEquals("summaries based on same data should have same hashcodes",
|
||||
u.hashCode(), t.hashCode());
|
||||
|
||||
// Clear and make sure summaries are indistinguishable from empty summary
|
||||
u.clear();
|
||||
t.clear();
|
||||
assertTrue("empty instances should be equal", t.equals(u));
|
||||
assertTrue("empty instances should be equal", u.equals(t));
|
||||
assertEquals("empty hash code", emptyHash, t.hashCode());
|
||||
assertEquals("empty hash code", emptyHash, u.hashCode());
|
||||
}
|
||||
|
||||
private void verifySummary(SummaryStatistics u, StatisticalSummary s) {
|
||||
assertEquals("N",s.getN(),u.getN());
|
||||
TestUtils.assertEquals("sum",s.getSum(),u.getSum(),tolerance);
|
||||
TestUtils.assertEquals("var",s.getVariance(),u.getVariance(),tolerance);
|
||||
TestUtils.assertEquals("std",s.getStandardDeviation(),u.getStandardDeviation(),tolerance);
|
||||
TestUtils.assertEquals("mean",s.getMean(),u.getMean(),tolerance);
|
||||
TestUtils.assertEquals("min",s.getMin(),u.getMin(),tolerance);
|
||||
TestUtils.assertEquals("max",s.getMax(),u.getMax(),tolerance);
|
||||
}
|
||||
}
|
||||
|
|
@ -25,7 +25,7 @@ import junit.framework.TestSuite;
|
|||
* @version $Revision$ $Date$
|
||||
*/
|
||||
|
||||
public final class SummaryStatisticsImplTest extends SummaryStatisticsAbstractTest {
|
||||
public final class SummaryStatisticsImplTest extends SummaryStatisticsTest {
|
||||
|
||||
public SummaryStatisticsImplTest(String name) {
|
||||
super(name);
|
||||
|
|
|
|||
|
|
@ -18,34 +18,225 @@ package org.apache.commons.math.stat.descriptive;
|
|||
|
||||
|
||||
import junit.framework.Test;
|
||||
import junit.framework.TestCase;
|
||||
import junit.framework.TestSuite;
|
||||
|
||||
import org.apache.commons.math.TestUtils;
|
||||
import org.apache.commons.math.stat.descriptive.moment.Mean;
|
||||
import org.apache.commons.math.stat.descriptive.summary.Sum;
|
||||
/**
|
||||
* Test cases for the {@link SummaryStatistics} class.
|
||||
* When SummaryStatisticsImpl is removed in math 2.0, test cases from
|
||||
* SummaryStatisticsImplTest should be merged into this class.
|
||||
*
|
||||
* @version $Revision: 566833 $ $Date: 2007-08-16 13:36:33 -0700 (Thu, 16 Aug 2007) $
|
||||
*/
|
||||
|
||||
public final class SummaryStatisticsTest extends SummaryStatisticsAbstractTest {
|
||||
public class SummaryStatisticsTest extends TestCase {
|
||||
|
||||
private double one = 1;
|
||||
private float twoF = 2;
|
||||
private long twoL = 2;
|
||||
private int three = 3;
|
||||
private double mean = 2;
|
||||
private double sumSq = 18;
|
||||
private double sum = 8;
|
||||
private double var = 0.666666666666666666667;
|
||||
private double std = Math.sqrt(var);
|
||||
private double n = 4;
|
||||
private double min = 1;
|
||||
private double max = 3;
|
||||
private double tolerance = 10E-15;
|
||||
|
||||
public SummaryStatisticsTest(String name) {
|
||||
super(name);
|
||||
}
|
||||
|
||||
public static Test suite() {
|
||||
TestSuite suite = new TestSuite(SummaryStatisticsTest.class);
|
||||
suite.setName("SummaryStatistics tests");
|
||||
return suite;
|
||||
}
|
||||
|
||||
public SummaryStatisticsTest(String name) {
|
||||
super(name);
|
||||
}
|
||||
|
||||
protected SummaryStatistics createSummaryStatistics() {
|
||||
return new SummaryStatistics();
|
||||
}
|
||||
|
||||
|
||||
/** test stats */
|
||||
public void testStats() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
u.addValue(one);
|
||||
u.addValue(twoF);
|
||||
u.addValue(twoL);
|
||||
u.addValue(three);
|
||||
assertEquals("N",n,u.getN(),tolerance);
|
||||
assertEquals("sum",sum,u.getSum(),tolerance);
|
||||
assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
|
||||
assertEquals("var",var,u.getVariance(),tolerance);
|
||||
assertEquals("std",std,u.getStandardDeviation(),tolerance);
|
||||
assertEquals("mean",mean,u.getMean(),tolerance);
|
||||
assertEquals("min",min,u.getMin(),tolerance);
|
||||
assertEquals("max",max,u.getMax(),tolerance);
|
||||
u.clear();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
}
|
||||
|
||||
public void testN0andN1Conditions() throws Exception {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
assertTrue("Mean of n = 0 set should be NaN",
|
||||
Double.isNaN( u.getMean() ) );
|
||||
assertTrue("Standard Deviation of n = 0 set should be NaN",
|
||||
Double.isNaN( u.getStandardDeviation() ) );
|
||||
assertTrue("Variance of n = 0 set should be NaN",
|
||||
Double.isNaN(u.getVariance() ) );
|
||||
|
||||
/* n=1 */
|
||||
u.addValue(one);
|
||||
assertTrue("mean should be one (n = 1)",
|
||||
u.getMean() == one);
|
||||
assertTrue("geometric should be one (n = 1) instead it is " + u.getGeometricMean(),
|
||||
u.getGeometricMean() == one);
|
||||
assertTrue("Std should be zero (n = 1)",
|
||||
u.getStandardDeviation() == 0.0);
|
||||
assertTrue("variance should be zero (n = 1)",
|
||||
u.getVariance() == 0.0);
|
||||
|
||||
/* n=2 */
|
||||
u.addValue(twoF);
|
||||
assertTrue("Std should not be zero (n = 2)",
|
||||
u.getStandardDeviation() != 0.0);
|
||||
assertTrue("variance should not be zero (n = 2)",
|
||||
u.getVariance() != 0.0);
|
||||
|
||||
}
|
||||
|
||||
public void testProductAndGeometricMean() throws Exception {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
u.addValue( 1.0 );
|
||||
u.addValue( 2.0 );
|
||||
u.addValue( 3.0 );
|
||||
u.addValue( 4.0 );
|
||||
|
||||
assertEquals( "Geometric mean not expected", 2.213364,
|
||||
u.getGeometricMean(), 0.00001 );
|
||||
}
|
||||
|
||||
public void testNaNContracts() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
assertTrue("mean not NaN",Double.isNaN(u.getMean()));
|
||||
assertTrue("min not NaN",Double.isNaN(u.getMin()));
|
||||
assertTrue("std dev not NaN",Double.isNaN(u.getStandardDeviation()));
|
||||
assertTrue("var not NaN",Double.isNaN(u.getVariance()));
|
||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
||||
|
||||
u.addValue(1.0);
|
||||
|
||||
assertEquals( "mean not expected", 1.0,
|
||||
u.getMean(), Double.MIN_VALUE);
|
||||
assertEquals( "variance not expected", 0.0,
|
||||
u.getVariance(), Double.MIN_VALUE);
|
||||
assertEquals( "geometric mean not expected", 1.0,
|
||||
u.getGeometricMean(), Double.MIN_VALUE);
|
||||
|
||||
u.addValue(-1.0);
|
||||
|
||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
||||
|
||||
u.addValue(0.0);
|
||||
|
||||
assertTrue("geom mean not NaN",Double.isNaN(u.getGeometricMean()));
|
||||
|
||||
//FiXME: test all other NaN contract specs
|
||||
}
|
||||
|
||||
public void testGetSummary() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
StatisticalSummary summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
u.addValue(1d);
|
||||
summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
u.addValue(2d);
|
||||
summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
u.addValue(2d);
|
||||
summary = u.getSummary();
|
||||
verifySummary(u, summary);
|
||||
}
|
||||
|
||||
public void testSerialization() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
// Empty test
|
||||
TestUtils.checkSerializedEquality(u);
|
||||
SummaryStatistics s = (SummaryStatistics) TestUtils.serializeAndRecover(u);
|
||||
StatisticalSummary summary = s.getSummary();
|
||||
verifySummary(u, summary);
|
||||
|
||||
// Add some data
|
||||
u.addValue(2d);
|
||||
u.addValue(1d);
|
||||
u.addValue(3d);
|
||||
u.addValue(4d);
|
||||
u.addValue(5d);
|
||||
|
||||
// Test again
|
||||
TestUtils.checkSerializedEquality(u);
|
||||
s = (SummaryStatistics) TestUtils.serializeAndRecover(u);
|
||||
summary = s.getSummary();
|
||||
verifySummary(u, summary);
|
||||
|
||||
}
|
||||
|
||||
public void testEqualsAndHashCode() {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
SummaryStatistics t = null;
|
||||
int emptyHash = u.hashCode();
|
||||
assertTrue("reflexive", u.equals(u));
|
||||
assertFalse("non-null compared to null", u.equals(t));
|
||||
assertFalse("wrong type", u.equals(new Double(0)));
|
||||
t = createSummaryStatistics();
|
||||
assertTrue("empty instances should be equal", t.equals(u));
|
||||
assertTrue("empty instances should be equal", u.equals(t));
|
||||
assertEquals("empty hash code", emptyHash, t.hashCode());
|
||||
|
||||
// Add some data to u
|
||||
u.addValue(2d);
|
||||
u.addValue(1d);
|
||||
u.addValue(3d);
|
||||
u.addValue(4d);
|
||||
assertFalse("different n's should make instances not equal", t.equals(u));
|
||||
assertFalse("different n's should make instances not equal", u.equals(t));
|
||||
assertTrue("different n's should make hashcodes different",
|
||||
u.hashCode() != t.hashCode());
|
||||
|
||||
//Add data in same order to t
|
||||
t.addValue(2d);
|
||||
t.addValue(1d);
|
||||
t.addValue(3d);
|
||||
t.addValue(4d);
|
||||
assertTrue("summaries based on same data should be equal", t.equals(u));
|
||||
assertTrue("summaries based on same data should be equal", u.equals(t));
|
||||
assertEquals("summaries based on same data should have same hashcodes",
|
||||
u.hashCode(), t.hashCode());
|
||||
|
||||
// Clear and make sure summaries are indistinguishable from empty summary
|
||||
u.clear();
|
||||
t.clear();
|
||||
assertTrue("empty instances should be equal", t.equals(u));
|
||||
assertTrue("empty instances should be equal", u.equals(t));
|
||||
assertEquals("empty hash code", emptyHash, t.hashCode());
|
||||
assertEquals("empty hash code", emptyHash, u.hashCode());
|
||||
}
|
||||
|
||||
private void verifySummary(SummaryStatistics u, StatisticalSummary s) {
|
||||
assertEquals("N",s.getN(),u.getN());
|
||||
TestUtils.assertEquals("sum",s.getSum(),u.getSum(),tolerance);
|
||||
TestUtils.assertEquals("var",s.getVariance(),u.getVariance(),tolerance);
|
||||
TestUtils.assertEquals("std",s.getStandardDeviation(),u.getStandardDeviation(),tolerance);
|
||||
TestUtils.assertEquals("mean",s.getMean(),u.getMean(),tolerance);
|
||||
TestUtils.assertEquals("min",s.getMin(),u.getMin(),tolerance);
|
||||
TestUtils.assertEquals("max",s.getMax(),u.getMax(),tolerance);
|
||||
}
|
||||
|
||||
public void testSetterInjection() throws Exception {
|
||||
SummaryStatistics u = createSummaryStatistics();
|
||||
u.setMeanImpl(new Sum());
|
||||
|
|
|
|||
|
|
@ -21,7 +21,7 @@ import junit.framework.TestSuite;
|
|||
* @version $Revision$ $Date: 2007-08-16 15:36:33 -0500 (Thu, 16 Aug
|
||||
* 2007) $
|
||||
*/
|
||||
public final class SynchronizedDescriptiveStatisticsTest extends DescriptiveStatisticsAbstractTest {
|
||||
public final class SynchronizedDescriptiveStatisticsTest extends DescriptiveStatisticsTest {
|
||||
|
||||
public SynchronizedDescriptiveStatisticsTest(String name) {
|
||||
super(name);
|
||||
|
|
|
|||
|
|
@ -21,7 +21,7 @@ import junit.framework.TestSuite;
|
|||
* @version $Revision: 592121 $ $Date: 2007-08-16 15:36:33 -0500 (Thu, 16 Aug
|
||||
* 2007) $
|
||||
*/
|
||||
public final class SynchronizedSummaryStatisticsTest extends SummaryStatisticsAbstractTest {
|
||||
public final class SynchronizedSummaryStatisticsTest extends SummaryStatisticsTest {
|
||||
|
||||
public SynchronizedSummaryStatisticsTest(String name) {
|
||||
super(name);
|
||||
|
|
|
|||
Loading…
Reference in New Issue