MATH-170. added SynchronizedDescriptiveStatistics class.
git-svn-id: https://svn.apache.org/repos/asf/commons/proper/math/trunk@590564 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Brent Worden
parent
2e8332522e
commit
6afeedf161
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@ -1,251 +1,39 @@
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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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* contributor license agreements. See the NOTICE file distributed with this
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* work for additional information regarding copyright ownership. The ASF
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* licenses this file to You under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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* http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law
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* or agreed to in writing, software distributed under the License is
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* distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the specific language
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* governing permissions and 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.Test;
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import junit.framework.TestCase;
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import junit.framework.TestSuite;
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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 {@link Univariate} class.
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*
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* @version $Revision$ $Date$
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* @version $Revision$ $Date: 2007-08-16 15:36:33 -0500 (Thu, 16 Aug
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* 2007) $
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*/
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public final class DescriptiveStatisticsImplTest extends TestCase {
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private double one = 1;
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private float two = 2;
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private int three = 3;
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private double mean = 2;
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private double sumSq = 18;
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private double sum = 8;
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private double var = 0.666666666666666666667;
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private double std = Math.sqrt(var);
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private double n = 4;
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private double min = 1;
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private double max = 3;
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private double tolerance = 10E-15;
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public final class DescriptiveStatisticsImplTest extends DescriptiveStatisticsTest {
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public DescriptiveStatisticsImplTest(String name) {
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super(name);
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}
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public void setUp() {
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}
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public static Test suite() {
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TestSuite suite = new TestSuite(DescriptiveStatisticsImplTest.class);
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suite.setName("DescriptiveStatistics Tests");
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suite.setName("DescriptiveStatisticsImpl Tests");
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return suite;
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}
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/** test stats */
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public void testStats() {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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assertEquals("total count",0,u.getN(),tolerance);
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u.addValue(one);
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u.addValue(two);
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u.addValue(two);
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u.addValue(three);
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assertEquals("N",n,u.getN(),tolerance);
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assertEquals("sum",sum,u.getSum(),tolerance);
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assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
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assertEquals("var",var,u.getVariance(),tolerance);
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assertEquals("std",std,u.getStandardDeviation(),tolerance);
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assertEquals("mean",mean,u.getMean(),tolerance);
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assertEquals("min",min,u.getMin(),tolerance);
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assertEquals("max",max,u.getMax(),tolerance);
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u.clear();
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assertEquals("total count",0,u.getN(),tolerance);
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protected DescriptiveStatistics createDescriptiveStatistics() {
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return new DescriptiveStatisticsImpl();
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}
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public void testN0andN1Conditions() throws Exception {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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assertTrue("Mean of n = 0 set should be NaN",
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Double.isNaN( u.getMean() ) );
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assertTrue("Standard Deviation of n = 0 set should be NaN",
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Double.isNaN( u.getStandardDeviation() ) );
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assertTrue("Variance of n = 0 set should be NaN",
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Double.isNaN(u.getVariance() ) );
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u.addValue(one);
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assertTrue( "Mean of n = 1 set should be value of single item n1",
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u.getMean() == one);
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assertTrue( "StdDev of n = 1 set should be zero, instead it is: "
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+ u.getStandardDeviation(), u.getStandardDeviation() == 0);
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assertTrue( "Variance of n = 1 set should be zero",
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u.getVariance() == 0);
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}
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public void testSkewAndKurtosis() {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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double[] testArray =
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{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
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9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
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for( int i = 0; i < testArray.length; i++) {
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u.addValue( testArray[i]);
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}
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assertEquals("mean", 12.40455, u.getMean(), 0.0001);
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assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
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assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
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assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
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}
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public void testProductAndGeometricMean() throws Exception {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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u.setWindowSize(10);
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u.addValue( 1.0 );
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u.addValue( 2.0 );
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u.addValue( 3.0 );
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u.addValue( 4.0 );
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//assertEquals( "Product not expected",
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// 24.0, u.getProduct(), Double.MIN_VALUE );
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assertEquals( "Geometric mean not expected",
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2.213364, u.getGeometricMean(), 0.00001 );
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// Now test rolling - StorelessDescriptiveStatistics should discount the contribution
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// of a discarded element
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for( int i = 0; i < 10; i++ ) {
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u.addValue( i + 2 );
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}
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// Values should be (2,3,4,5,6,7,8,9,10,11)
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//assertEquals( "Product not expected", 39916800.0,
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// u.getProduct(), 0.00001 );
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assertEquals( "Geometric mean not expected", 5.755931,
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u.getGeometricMean(), 0.00001 );
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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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}
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tstGetSortedValues(test4);
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}
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for (int i = 0; i < 10; i++) {
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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++) {
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test4[j] = (double) testi[j];
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}
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tstGetSortedValues(test4);
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}
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}
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private void tstGetSortedValues(double[] test) {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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for (int i = 0; i < test.length; i++) {
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u.addValue(test[i]);
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}
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double[] sorted = u.getSortedValues();
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if (sorted.length != test.length) {
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fail("wrong length for sorted values array");
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}
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for (int i = 0; i < sorted.length-1; i++) {
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if (sorted[i] > sorted[i+1]) {
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fail("sorted values out of sequence");
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}
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}
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}
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public void testPercentiles() {
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double[] test = {5,4,3,2,1};
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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for (int i = 0; i < test.length; i++) {
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u.addValue(test[i]);
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}
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assertEquals("expecting min",1,u.getPercentile(5),10E-12);
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assertEquals("expecting max",5,u.getPercentile(99),10E-12);
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assertEquals("expecting middle",3,u.getPercentile(50),10E-12);
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try {
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u.getPercentile(0);
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fail("expecting IllegalArgumentException for getPercentile(0)");
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} catch (IllegalArgumentException ex) {
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;
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}
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try {
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u.getPercentile(120);
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fail("expecting IllegalArgumentException for getPercentile(120)");
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} catch (IllegalArgumentException ex) {
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;
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}
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u.clear();
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double[] test2 = {1,2,3,4};
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for (int i = 0; i < test2.length; i++) {
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u.addValue(test2[i]);
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}
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assertEquals("Q1",1.25,u.getPercentile(25),10E-12);
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assertEquals("Q3",3.75,u.getPercentile(75),10E-12);
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assertEquals("Q2",2.5,u.getPercentile(50),10E-12);
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u.clear();
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double[] test3 = {1};
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for (int i = 0; i < test3.length; i++) {
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u.addValue(test3[i]);
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}
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assertEquals("Q1",1,u.getPercentile(25),10E-12);
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assertEquals("Q3",1,u.getPercentile(75),10E-12);
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assertEquals("Q2",1,u.getPercentile(50),10E-12);
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u.clear();
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RandomData rd = new RandomDataImpl();
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int[] testi = rd.nextPermutation(100,100); // will contain 0-99
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for (int j = 0; j < testi.length; j++) {
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u.addValue((double) testi[j]); //OK, laugh at me for the cast
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}
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for (int i = 1; i < 100; i++) {
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assertEquals("percentile " + i,
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(double) i-1 + (double) i*(.01), u.getPercentile(i),10E-12);
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}
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u.clear();
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double[] test4 = {1,2,3,4,100};
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for (int i = 0; i < test4.length; i++) {
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u.addValue(test4[i]);
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}
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assertEquals("80th",80.8,u.getPercentile(80),10E-12);
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u.clear();
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assertTrue("empty value set should return NaN",
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Double.isNaN(u.getPercentile(50)));
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}
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}
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@ -29,122 +29,40 @@ import org.apache.commons.math.random.RandomDataImpl;
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*
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* @version $Revision$ $Date$
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*/
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public final class DescriptiveStatisticsTest extends TestCase {
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private double one = 1;
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private float two = 2;
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private int three = 3;
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private double mean = 2;
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private double sumSq = 18;
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private double sum = 8;
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public abstract class DescriptiveStatisticsTest extends TestCase {
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private double var = 0.666666666666666666667;
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private double std = Math.sqrt(var);
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private double n = 4;
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private double min = 1;
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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 DescriptiveStatisticsTest(String name) {
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super(name);
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}
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public void setUp() {
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}
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public static Test suite() {
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TestSuite suite = new TestSuite(DescriptiveStatisticsTest.class);
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suite.setName("Descriptive Statistics Tests");
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return suite;
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}
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/** test stats */
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public void testStats() {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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assertEquals("total count",0,u.getN(),tolerance);
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u.addValue(one);
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u.addValue(two);
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u.addValue(two);
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u.addValue(three);
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assertEquals("N",n,u.getN(),tolerance);
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assertEquals("sum",sum,u.getSum(),tolerance);
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assertEquals("sumsq",sumSq,u.getSumsq(),tolerance);
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assertEquals("var",var,u.getVariance(),tolerance);
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assertEquals("std",std,u.getStandardDeviation(),tolerance);
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assertEquals("mean",mean,u.getMean(),tolerance);
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assertEquals("min",min,u.getMin(),tolerance);
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assertEquals("max",max,u.getMax(),tolerance);
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u.clear();
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assertEquals("total count",0,u.getN(),tolerance);
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}
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protected abstract DescriptiveStatistics createDescriptiveStatistics();
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public void testN0andN1Conditions() throws Exception {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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assertTrue("Mean of n = 0 set should be NaN",
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Double.isNaN( u.getMean() ) );
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assertTrue("Standard Deviation of n = 0 set should be NaN",
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Double.isNaN( u.getStandardDeviation() ) );
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assertTrue("Variance of n = 0 set should be NaN",
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Double.isNaN(u.getVariance() ) );
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u.addValue(one);
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assertTrue( "Mean of n = 1 set should be value of single item n1",
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u.getMean() == one);
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assertTrue( "StdDev of n = 1 set should be zero, instead it is: "
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+ u.getStandardDeviation(), u.getStandardDeviation() == 0);
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assertTrue( "Variance of n = 1 set should be zero",
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u.getVariance() == 0);
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}
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public void testSkewAndKurtosis() {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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double[] testArray =
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{ 12.5, 12, 11.8, 14.2, 14.9, 14.5, 21, 8.2, 10.3, 11.3, 14.1,
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9.9, 12.2, 12, 12.1, 11, 19.8, 11, 10, 8.8, 9, 12.3 };
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for( int i = 0; i < testArray.length; i++) {
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u.addValue( testArray[i]);
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}
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assertEquals("mean", 12.40455, u.getMean(), 0.0001);
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assertEquals("variance", 10.00236, u.getVariance(), 0.0001);
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assertEquals("skewness", 1.437424, u.getSkewness(), 0.0001);
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assertEquals("kurtosis", 2.37719, u.getKurtosis(), 0.0001);
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}
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public void testProductAndGeometricMean() throws Exception {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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u.setWindowSize(10);
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u.addValue( 1.0 );
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u.addValue( 2.0 );
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u.addValue( 3.0 );
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u.addValue( 4.0 );
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//assertEquals( "Product not expected",
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// 24.0, u.getProduct(), Double.MIN_VALUE );
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assertEquals( "Geometric mean not expected",
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2.213364, u.getGeometricMean(), 0.00001 );
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// Now test rolling - StorelessDescriptiveStatistics should discount the contribution
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// of a discarded element
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for( int i = 0; i < 10; i++ ) {
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u.addValue( i + 2 );
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}
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// Values should be (2,3,4,5,6,7,8,9,10,11)
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//assertEquals( "Product not expected", 39916800.0,
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// u.getProduct(), 0.00001 );
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assertEquals( "Geometric mean not expected", 5.755931,
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u.getGeometricMean(), 0.00001 );
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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 = DescriptiveStatistics.newInstance();
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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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@ -219,28 +137,54 @@ public final class DescriptiveStatisticsTest extends TestCase {
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}
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}
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public void testN0andN1Conditions() throws Exception {
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DescriptiveStatistics u = createDescriptiveStatistics();
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assertTrue("Mean of n = 0 set should be NaN",
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Double.isNaN( u.getMean() ) );
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assertTrue("Standard Deviation of n = 0 set should be NaN",
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Double.isNaN( u.getStandardDeviation() ) );
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assertTrue("Variance of n = 0 set should be NaN",
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Double.isNaN(u.getVariance() ) );
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private void tstGetSortedValues(double[] test) {
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DescriptiveStatistics u = DescriptiveStatistics.newInstance();
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u.setWindowSize(test.length);
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for (int i = 0; i < test.length; i++) {
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u.addValue(test[i]);
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u.addValue(one);
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assertTrue( "Mean of n = 1 set should be value of single item n1",
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u.getMean() == one);
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assertTrue( "StdDev of n = 1 set should be zero, instead it is: "
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+ u.getStandardDeviation(), u.getStandardDeviation() == 0);
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assertTrue( "Variance of n = 1 set should be zero",
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u.getVariance() == 0);
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}
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double[] sorted = u.getSortedValues();
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if (sorted.length != test.length) {
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fail("wrong length for sorted values array");
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public void testNewInstanceClassNull() {
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try {
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DescriptiveStatistics.newInstance((Class)null);
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fail("null is not a valid descriptive statistics class");
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} catch (NullPointerException ex) {
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// success
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} catch (Exception ex) {
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fail();
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}
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for (int i = 0; i < sorted.length-1; i++) {
|
||||
if (sorted[i] > sorted[i+1]) {
|
||||
fail("sorted values out of sequence");
|
||||
|
||||
}
|
||||
|
||||
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 = DescriptiveStatistics.newInstance();
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
u.setWindowSize(110);
|
||||
for (int i = 0; i < test.length; i++) {
|
||||
u.addValue(test[i]);
|
||||
|
|
@ -302,9 +246,38 @@ public final class DescriptiveStatisticsTest extends TestCase {
|
|||
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 = DescriptiveStatistics.newInstance();
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
assertEquals("total count",0,u.getN(),tolerance);
|
||||
u.addValue(one);
|
||||
u.addValue(two);
|
||||
|
|
@ -327,49 +300,58 @@ public final class DescriptiveStatisticsTest extends TestCase {
|
|||
assertEquals("total count",0,u2.getN(),tolerance);
|
||||
}
|
||||
|
||||
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 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);
|
||||
}
|
||||
|
||||
public void testNewInstanceClassValid() {
|
||||
try {
|
||||
DescriptiveStatistics u = DescriptiveStatistics.newInstance(
|
||||
DescriptiveStatisticsImpl.class);
|
||||
assertNotNull(u);
|
||||
assertTrue(u instanceof DescriptiveStatisticsImpl);
|
||||
} catch (InstantiationException ex) {
|
||||
fail();
|
||||
} catch (IllegalAccessException ex) {
|
||||
fail();
|
||||
}
|
||||
/** 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 testWindowSize() {
|
||||
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
|
||||
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());
|
||||
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 = DescriptiveStatistics.newInstance();
|
||||
DescriptiveStatistics u = createDescriptiveStatistics();
|
||||
u.setWindowSize(2);
|
||||
|
||||
u.addValue(1.0);
|
||||
|
|
@ -385,18 +367,37 @@ public final class DescriptiveStatisticsTest extends TestCase {
|
|||
assertEquals(3.0, u.getMean(), tolerance);
|
||||
}
|
||||
|
||||
public void testToString() {
|
||||
DescriptiveStatistics u = DescriptiveStatistics.newInstance();
|
||||
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]);
|
||||
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");
|
||||
}
|
||||
}
|
||||
assertTrue(u.toString().indexOf("NaN") == -1);
|
||||
assertTrue(u.toString().startsWith("DescriptiveStatistics"));
|
||||
}
|
||||
|
||||
}
|
||||
|
|
|
|||
|
|
@ -95,6 +95,9 @@ Commons Math Release Notes</title>
|
|||
MaxIterationsExceededException and return 0 or 1, resp. if the argument
|
||||
is more than 20 standard deviations from the mean.
|
||||
</action>
|
||||
<action dev="brentworden" type="update" issue="MATH-170" due-to="David J. M. Karlsen">
|
||||
Added SynchronizedDescriptiveStatistics class.
|
||||
</action>
|
||||
</release>
|
||||
<release version="1.1" date="2005-12-17"
|
||||
description="This is a maintenance release containing bug fixes and enhancements.
|
||||
|
|
|
|||
|
|
@ -198,6 +198,15 @@ while (line != null) {
|
|||
}
|
||||
}
|
||||
in.close();
|
||||
</source>
|
||||
</dd>
|
||||
<dt>Compute statistics in a thread-safe manner</dt>
|
||||
<br/>
|
||||
<dd>Use a <code>ThreadSafeDescriptiveStatistics</code> instance
|
||||
<source>
|
||||
// Create a SynchronizedDescriptiveStatistics instance and
|
||||
// use as any other DescriptiveStatistics instance
|
||||
DescriptiveStatistics stats = DescriptiveStatistics.newInstance(SynchronizedDescriptiveStatistics.class);
|
||||
</source>
|
||||
</dd>
|
||||
</dl>
|
||||
|
|
|
|||
Loading…
Reference in New Issue