Repository: commons-math Updated Branches: refs/heads/develop dccc12554 -> 819318486
http://git-wip-us.apache.org/repos/asf/commons-math/blob/5c341d9d/src/test/java/org/apache/commons/math4/stat/inference/TestUtilsTest.java ---------------------------------------------------------------------- diff --git a/src/test/java/org/apache/commons/math4/stat/inference/TestUtilsTest.java b/src/test/java/org/apache/commons/math4/stat/inference/TestUtilsTest.java deleted file mode 100644 index b22131e..0000000 --- a/src/test/java/org/apache/commons/math4/stat/inference/TestUtilsTest.java +++ /dev/null @@ -1,559 +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.math4.stat.inference; - -import java.util.ArrayList; -import java.util.List; - -import org.apache.commons.math4.distribution.NormalDistribution; -import org.apache.commons.math4.exception.DimensionMismatchException; -import org.apache.commons.math4.exception.NotPositiveException; -import org.apache.commons.math4.exception.NotStrictlyPositiveException; -import org.apache.commons.math4.exception.NullArgumentException; -import org.apache.commons.math4.exception.NumberIsTooSmallException; -import org.apache.commons.math4.exception.OutOfRangeException; -import org.apache.commons.math4.stat.descriptive.SummaryStatistics; -import org.apache.commons.math4.stat.inference.OneWayAnova; -import org.apache.commons.math4.stat.inference.TestUtils; -import org.apache.commons.math4.util.FastMath; -import org.junit.Assert; -import org.junit.Test; - - -/** - * Test cases for the TestUtils class. - * - */ -public class TestUtilsTest { - - @Test - public void testChiSquare() { - - // Target values computed using R version 1.8.1 - // Some assembly required ;-) - // Use sum((obs - exp)^2/exp) for the chi-square statistic and - // 1 - pchisq(sum((obs - exp)^2/exp), length(obs) - 1) for the p-value - - long[] observed = {10, 9, 11}; - double[] expected = {10, 10, 10}; - Assert.assertEquals("chi-square statistic", 0.2, TestUtils.chiSquare(expected, observed), 10E-12); - Assert.assertEquals("chi-square p-value", 0.904837418036, TestUtils.chiSquareTest(expected, observed), 1E-10); - - long[] observed1 = { 500, 623, 72, 70, 31 }; - double[] expected1 = { 485, 541, 82, 61, 37 }; - Assert.assertEquals( "chi-square test statistic", 9.023307936427388, TestUtils.chiSquare(expected1, observed1), 1E-10); - Assert.assertEquals("chi-square p-value", 0.06051952647453607, TestUtils.chiSquareTest(expected1, observed1), 1E-9); - Assert.assertTrue("chi-square test reject", TestUtils.chiSquareTest(expected1, observed1, 0.07)); - Assert.assertTrue("chi-square test accept", !TestUtils.chiSquareTest(expected1, observed1, 0.05)); - - try { - TestUtils.chiSquareTest(expected1, observed1, 95); - Assert.fail("alpha out of range, OutOfRangeException expected"); - } catch (OutOfRangeException ex) { - // expected - } - - long[] tooShortObs = { 0 }; - double[] tooShortEx = { 1 }; - try { - TestUtils.chiSquare(tooShortEx, tooShortObs); - Assert.fail("arguments too short, DimensionMismatchException expected"); - } catch (DimensionMismatchException ex) { - // expected - } - - // unmatched arrays - long[] unMatchedObs = { 0, 1, 2, 3 }; - double[] unMatchedEx = { 1, 1, 2 }; - try { - TestUtils.chiSquare(unMatchedEx, unMatchedObs); - Assert.fail("arrays have different lengths, DimensionMismatchException expected"); - } catch (DimensionMismatchException ex) { - // expected - } - - // 0 expected count - expected[0] = 0; - try { - TestUtils.chiSquareTest(expected, observed, .01); - Assert.fail("bad expected count, NotStrictlyPositiveException expected"); - } catch (NotStrictlyPositiveException ex) { - // expected - } - - // negative observed count - expected[0] = 1; - observed[0] = -1; - try { - TestUtils.chiSquareTest(expected, observed, .01); - Assert.fail("bad expected count, NotPositiveException expected"); - } catch (NotPositiveException ex) { - // expected - } - - } - - @Test - public void testChiSquareIndependence() { - - // Target values computed using R version 1.8.1 - - long[][] counts = { {40, 22, 43}, {91, 21, 28}, {60, 10, 22}}; - Assert.assertEquals( "chi-square test statistic", 22.709027688, TestUtils.chiSquare(counts), 1E-9); - Assert.assertEquals("chi-square p-value", 0.000144751460134, TestUtils.chiSquareTest(counts), 1E-9); - Assert.assertTrue("chi-square test reject", TestUtils.chiSquareTest(counts, 0.0002)); - Assert.assertTrue("chi-square test accept", !TestUtils.chiSquareTest(counts, 0.0001)); - - long[][] counts2 = {{10, 15}, {30, 40}, {60, 90} }; - Assert.assertEquals( "chi-square test statistic", 0.168965517241, TestUtils.chiSquare(counts2), 1E-9); - Assert.assertEquals("chi-square p-value",0.918987499852, TestUtils.chiSquareTest(counts2), 1E-9); - Assert.assertTrue("chi-square test accept", !TestUtils.chiSquareTest(counts2, 0.1)); - - // ragged input array - long[][] counts3 = { {40, 22, 43}, {91, 21, 28}, {60, 10}}; - try { - TestUtils.chiSquare(counts3); - Assert.fail("Expecting DimensionMismatchException"); - } catch (DimensionMismatchException ex) { - // expected - } - - // insufficient data - long[][] counts4 = {{40, 22, 43}}; - try { - TestUtils.chiSquare(counts4); - Assert.fail("Expecting DimensionMismatchException"); - } catch (DimensionMismatchException ex) { - // expected - } - long[][] counts5 = {{40}, {40}, {30}, {10}}; - try { - TestUtils.chiSquare(counts5); - Assert.fail("Expecting DimensionMismatchException"); - } catch (DimensionMismatchException ex) { - // expected - } - - // negative counts - long[][] counts6 = {{10, -2}, {30, 40}, {60, 90} }; - try { - TestUtils.chiSquare(counts6); - Assert.fail("Expecting NotPositiveException"); - } catch (NotPositiveException ex) { - // expected - } - - // bad alpha - try { - TestUtils.chiSquareTest(counts, 0); - Assert.fail("Expecting OutOfRangeException"); - } catch (OutOfRangeException ex) { - // expected - } - } - - @Test - public void testChiSquareLargeTestStatistic() { - double[] exp = new double[] { - 3389119.5, 649136.6, 285745.4, 25357364.76, 11291189.78, 543628.0, - 232921.0, 437665.75 - }; - - long[] obs = new long[] { - 2372383, 584222, 257170, 17750155, 7903832, 489265, 209628, 393899 - }; - org.apache.commons.math4.stat.inference.ChiSquareTest csti = - new org.apache.commons.math4.stat.inference.ChiSquareTest(); - double cst = csti.chiSquareTest(exp, obs); - Assert.assertEquals("chi-square p-value", 0.0, cst, 1E-3); - Assert.assertEquals( "chi-square test statistic", - 114875.90421929007, TestUtils.chiSquare(exp, obs), 1E-9); - } - - /** Contingency table containing zeros - PR # 32531 */ - @Test - public void testChiSquareZeroCount() { - // Target values computed using R version 1.8.1 - long[][] counts = { {40, 0, 4}, {91, 1, 2}, {60, 2, 0}}; - Assert.assertEquals( "chi-square test statistic", 9.67444662263, - TestUtils.chiSquare(counts), 1E-9); - Assert.assertEquals("chi-square p-value", 0.0462835770603, - TestUtils.chiSquareTest(counts), 1E-9); - } - - private double[] tooShortObs = { 1.0 }; - private double[] emptyObs = {}; - private SummaryStatistics emptyStats = new SummaryStatistics(); - - @Test - public void testOneSampleT() { - double[] observed = - {93.0, 103.0, 95.0, 101.0, 91.0, 105.0, 96.0, 94.0, 101.0, 88.0, 98.0, 94.0, 101.0, 92.0, 95.0 }; - double mu = 100.0; - SummaryStatistics sampleStats = null; - sampleStats = new SummaryStatistics(); - for (int i = 0; i < observed.length; i++) { - sampleStats.addValue(observed[i]); - } - - // Target comparison values computed using R version 1.8.1 (Linux version) - Assert.assertEquals("t statistic", -2.81976445346, - TestUtils.t(mu, observed), 10E-10); - Assert.assertEquals("t statistic", -2.81976445346, - TestUtils.t(mu, sampleStats), 10E-10); - Assert.assertEquals("p value", 0.0136390585873, - TestUtils.tTest(mu, observed), 10E-10); - Assert.assertEquals("p value", 0.0136390585873, - TestUtils.tTest(mu, sampleStats), 10E-10); - - try { - TestUtils.t(mu, (double[]) null); - Assert.fail("arguments too short, NullArgumentException expected"); - } catch (NullArgumentException ex) { - // expected - } - - try { - TestUtils.t(mu, (SummaryStatistics) null); - Assert.fail("arguments too short, NullArgumentException expected"); - } catch (NullArgumentException ex) { - // expected - } - - try { - TestUtils.t(mu, emptyObs); - Assert.fail("arguments too short, NumberIsTooSmallException expected"); - } catch (NumberIsTooSmallException ex) { - // expected - } - - try { - TestUtils.t(mu, emptyStats); - Assert.fail("arguments too short, NumberIsTooSmallException expected"); - } catch (NumberIsTooSmallException ex) { - // expected - } - - try { - TestUtils.t(mu, tooShortObs); - Assert.fail("insufficient data to compute t statistic, NumberIsTooSmallException expected"); - } catch (NumberIsTooSmallException ex) { - // expected - } - try { - TestUtils.tTest(mu, tooShortObs); - Assert.fail("insufficient data to perform t test, NumberIsTooSmallException expected"); - } catch (NumberIsTooSmallException ex) { - // expected - } - - try { - TestUtils.t(mu, (SummaryStatistics) null); - Assert.fail("insufficient data to compute t statistic, NullArgumentException expected"); - } catch (NullArgumentException ex) { - // expected - } - try { - TestUtils.tTest(mu, (SummaryStatistics) null); - Assert.fail("insufficient data to perform t test, NullArgumentException expected"); - } catch (NullArgumentException ex) { - // expected - } - } - - @Test - public void testOneSampleTTest() { - double[] oneSidedP = - {2d, 0d, 6d, 6d, 3d, 3d, 2d, 3d, -6d, 6d, 6d, 6d, 3d, 0d, 1d, 1d, 0d, 2d, 3d, 3d }; - SummaryStatistics oneSidedPStats = new SummaryStatistics(); - for (int i = 0; i < oneSidedP.length; i++) { - oneSidedPStats.addValue(oneSidedP[i]); - } - // Target comparison values computed using R version 1.8.1 (Linux version) - Assert.assertEquals("one sample t stat", 3.86485535541, - TestUtils.t(0d, oneSidedP), 10E-10); - Assert.assertEquals("one sample t stat", 3.86485535541, - TestUtils.t(0d, oneSidedPStats),1E-10); - Assert.assertEquals("one sample p value", 0.000521637019637, - TestUtils.tTest(0d, oneSidedP) / 2d, 10E-10); - Assert.assertEquals("one sample p value", 0.000521637019637, - TestUtils.tTest(0d, oneSidedPStats) / 2d, 10E-5); - Assert.assertTrue("one sample t-test reject", TestUtils.tTest(0d, oneSidedP, 0.01)); - Assert.assertTrue("one sample t-test reject", TestUtils.tTest(0d, oneSidedPStats, 0.01)); - Assert.assertTrue("one sample t-test accept", !TestUtils.tTest(0d, oneSidedP, 0.0001)); - Assert.assertTrue("one sample t-test accept", !TestUtils.tTest(0d, oneSidedPStats, 0.0001)); - - try { - TestUtils.tTest(0d, oneSidedP, 95); - Assert.fail("alpha out of range, OutOfRangeException expected"); - } catch (OutOfRangeException ex) { - // expected - } - - try { - TestUtils.tTest(0d, oneSidedPStats, 95); - Assert.fail("alpha out of range, OutOfRangeException expected"); - } catch (OutOfRangeException ex) { - // expected - } - - } - - @Test - public void testTwoSampleTHeterscedastic() { - double[] sample1 = { 7d, -4d, 18d, 17d, -3d, -5d, 1d, 10d, 11d, -2d }; - double[] sample2 = { -1d, 12d, -1d, -3d, 3d, -5d, 5d, 2d, -11d, -1d, -3d }; - SummaryStatistics sampleStats1 = new SummaryStatistics(); - for (int i = 0; i < sample1.length; i++) { - sampleStats1.addValue(sample1[i]); - } - SummaryStatistics sampleStats2 = new SummaryStatistics(); - for (int i = 0; i < sample2.length; i++) { - sampleStats2.addValue(sample2[i]); - } - - // Target comparison values computed using R version 1.8.1 (Linux version) - Assert.assertEquals("two sample heteroscedastic t stat", 1.60371728768, - TestUtils.t(sample1, sample2), 1E-10); - Assert.assertEquals("two sample heteroscedastic t stat", 1.60371728768, - TestUtils.t(sampleStats1, sampleStats2), 1E-10); - Assert.assertEquals("two sample heteroscedastic p value", 0.128839369622, - TestUtils.tTest(sample1, sample2), 1E-10); - Assert.assertEquals("two sample heteroscedastic p value", 0.128839369622, - TestUtils.tTest(sampleStats1, sampleStats2), 1E-10); - Assert.assertTrue("two sample heteroscedastic t-test reject", - TestUtils.tTest(sample1, sample2, 0.2)); - Assert.assertTrue("two sample heteroscedastic t-test reject", - TestUtils.tTest(sampleStats1, sampleStats2, 0.2)); - Assert.assertTrue("two sample heteroscedastic t-test accept", - !TestUtils.tTest(sample1, sample2, 0.1)); - Assert.assertTrue("two sample heteroscedastic t-test accept", - !TestUtils.tTest(sampleStats1, sampleStats2, 0.1)); - - try { - TestUtils.tTest(sample1, sample2, .95); - Assert.fail("alpha out of range, OutOfRangeException expected"); - } catch (OutOfRangeException ex) { - // expected - } - - try { - TestUtils.tTest(sampleStats1, sampleStats2, .95); - Assert.fail("alpha out of range, OutOfRangeException expected"); - } catch (OutOfRangeException ex) { - // expected - } - - try { - TestUtils.tTest(sample1, tooShortObs, .01); - Assert.fail("insufficient data, NumberIsTooSmallException expected"); - } catch (NumberIsTooSmallException ex) { - // expected - } - - try { - TestUtils.tTest(sampleStats1, (SummaryStatistics) null, .01); - Assert.fail("insufficient data, NullArgumentException expected"); - } catch (NullArgumentException ex) { - // expected - } - - try { - TestUtils.tTest(sample1, tooShortObs); - Assert.fail("insufficient data, NumberIsTooSmallException expected"); - } catch (NumberIsTooSmallException ex) { - // expected - } - - try { - TestUtils.tTest(sampleStats1, (SummaryStatistics) null); - Assert.fail("insufficient data, NullArgumentException expected"); - } catch (NullArgumentException ex) { - // expected - } - - try { - TestUtils.t(sample1, tooShortObs); - Assert.fail("insufficient data, NumberIsTooSmallException expected"); - } catch (NumberIsTooSmallException ex) { - // expected - } - - try { - TestUtils.t(sampleStats1, (SummaryStatistics) null); - Assert.fail("insufficient data, NullArgumentException expected"); - } catch (NullArgumentException ex) { - // expected - } - } - @Test - public void testTwoSampleTHomoscedastic() { - double[] sample1 ={2, 4, 6, 8, 10, 97}; - double[] sample2 = {4, 6, 8, 10, 16}; - SummaryStatistics sampleStats1 = new SummaryStatistics(); - for (int i = 0; i < sample1.length; i++) { - sampleStats1.addValue(sample1[i]); - } - SummaryStatistics sampleStats2 = new SummaryStatistics(); - for (int i = 0; i < sample2.length; i++) { - sampleStats2.addValue(sample2[i]); - } - - // Target comparison values computed using R version 1.8.1 (Linux version) - Assert.assertEquals("two sample homoscedastic t stat", 0.73096310086, - TestUtils.homoscedasticT(sample1, sample2), 10E-11); - Assert.assertEquals("two sample homoscedastic p value", 0.4833963785, - TestUtils.homoscedasticTTest(sampleStats1, sampleStats2), 1E-10); - Assert.assertTrue("two sample homoscedastic t-test reject", - TestUtils.homoscedasticTTest(sample1, sample2, 0.49)); - Assert.assertTrue("two sample homoscedastic t-test accept", - !TestUtils.homoscedasticTTest(sample1, sample2, 0.48)); - } - - @Test - public void testSmallSamples() { - double[] sample1 = {1d, 3d}; - double[] sample2 = {4d, 5d}; - - // Target values computed using R, version 1.8.1 (linux version) - Assert.assertEquals(-2.2360679775, TestUtils.t(sample1, sample2), - 1E-10); - Assert.assertEquals(0.198727388935, TestUtils.tTest(sample1, sample2), - 1E-10); - } - - @Test - public void testPaired() { - double[] sample1 = {1d, 3d, 5d, 7d}; - double[] sample2 = {0d, 6d, 11d, 2d}; - double[] sample3 = {5d, 7d, 8d, 10d}; - - // Target values computed using R, version 1.8.1 (linux version) - Assert.assertEquals(-0.3133, TestUtils.pairedT(sample1, sample2), 1E-4); - Assert.assertEquals(0.774544295819, TestUtils.pairedTTest(sample1, sample2), 1E-10); - Assert.assertEquals(0.001208, TestUtils.pairedTTest(sample1, sample3), 1E-6); - Assert.assertFalse(TestUtils.pairedTTest(sample1, sample3, .001)); - Assert.assertTrue(TestUtils.pairedTTest(sample1, sample3, .002)); - } - - private double[] classA = - {93.0, 103.0, 95.0, 101.0}; - private double[] classB = - {99.0, 92.0, 102.0, 100.0, 102.0}; - private double[] classC = - {110.0, 115.0, 111.0, 117.0, 128.0}; - - private List<double[]> classes = new ArrayList<double[]>(); - private OneWayAnova oneWayAnova = new OneWayAnova(); - - @Test - public void testOneWayAnovaUtils() { - classes.add(classA); - classes.add(classB); - classes.add(classC); - Assert.assertEquals(oneWayAnova.anovaFValue(classes), - TestUtils.oneWayAnovaFValue(classes), 10E-12); - Assert.assertEquals(oneWayAnova.anovaPValue(classes), - TestUtils.oneWayAnovaPValue(classes), 10E-12); - Assert.assertEquals(oneWayAnova.anovaTest(classes, 0.01), - TestUtils.oneWayAnovaTest(classes, 0.01)); - } - @Test - public void testGTestGoodnesOfFit() throws Exception { - double[] exp = new double[]{ - 0.54d, 0.40d, 0.05d, 0.01d - }; - - long[] obs = new long[]{ - 70, 79, 3, 4 - }; - Assert.assertEquals("G test statistic", - 13.144799, TestUtils.g(exp, obs), 1E-5); - double p_gtgf = TestUtils.gTest(exp, obs); - Assert.assertEquals("g-Test p-value", 0.004333, p_gtgf, 1E-5); - - Assert.assertTrue(TestUtils.gTest(exp, obs, 0.05)); -} - - @Test - public void testGTestIndependance() throws Exception { - long[] obs1 = new long[]{ - 268, 199, 42 - }; - - long[] obs2 = new long[]{ - 807, 759, 184 - }; - - double g = TestUtils.gDataSetsComparison(obs1, obs2); - - Assert.assertEquals("G test statistic", - 7.3008170, g, 1E-4); - double p_gti = TestUtils.gTestDataSetsComparison(obs1, obs2); - - Assert.assertEquals("g-Test p-value", 0.0259805, p_gti, 1E-4); - Assert.assertTrue(TestUtils.gTestDataSetsComparison(obs1, obs2, 0.05)); - } - - @Test - public void testRootLogLikelihood() { - // positive where k11 is bigger than expected. - Assert.assertTrue(TestUtils.rootLogLikelihoodRatio(904, 21060, 1144, 283012) > 0.0); - - // negative because k11 is lower than expected - Assert.assertTrue(TestUtils.rootLogLikelihoodRatio(36, 21928, 60280, 623876) < 0.0); - - Assert.assertEquals(FastMath.sqrt(2.772589), TestUtils.rootLogLikelihoodRatio(1, 0, 0, 1), 0.000001); - Assert.assertEquals(-FastMath.sqrt(2.772589), TestUtils.rootLogLikelihoodRatio(0, 1, 1, 0), 0.000001); - Assert.assertEquals(FastMath.sqrt(27.72589), TestUtils.rootLogLikelihoodRatio(10, 0, 0, 10), 0.00001); - - Assert.assertEquals(FastMath.sqrt(39.33052), TestUtils.rootLogLikelihoodRatio(5, 1995, 0, 100000), 0.00001); - Assert.assertEquals(-FastMath.sqrt(39.33052), TestUtils.rootLogLikelihoodRatio(0, 100000, 5, 1995), 0.00001); - - Assert.assertEquals(FastMath.sqrt(4730.737), TestUtils.rootLogLikelihoodRatio(1000, 1995, 1000, 100000), 0.001); - Assert.assertEquals(-FastMath.sqrt(4730.737), TestUtils.rootLogLikelihoodRatio(1000, 100000, 1000, 1995), 0.001); - - Assert.assertEquals(FastMath.sqrt(5734.343), TestUtils.rootLogLikelihoodRatio(1000, 1000, 1000, 100000), 0.001); - Assert.assertEquals(FastMath.sqrt(5714.932), TestUtils.rootLogLikelihoodRatio(1000, 1000, 1000, 99000), 0.001); - } - - @Test - public void testKSOneSample() throws Exception { - final NormalDistribution unitNormal = new NormalDistribution(0d, 1d); - final double[] sample = KolmogorovSmirnovTestTest.gaussian; - final double tol = KolmogorovSmirnovTestTest.TOLERANCE; - Assert.assertEquals(0.3172069207622391, TestUtils.kolmogorovSmirnovTest(unitNormal, sample), tol); - Assert.assertEquals(0.0932947561266756, TestUtils.kolmogorovSmirnovStatistic(unitNormal, sample), tol); - } - - @Test - public void testKSTwoSample() throws Exception { - final double tol = KolmogorovSmirnovTestTest.TOLERANCE; - final double[] smallSample1 = { - 6, 7, 9, 13, 19, 21, 22, 23, 24 - }; - final double[] smallSample2 = { - 10, 11, 12, 16, 20, 27, 28, 32, 44, 54 - }; - Assert - .assertEquals(0.105577085453247, TestUtils.kolmogorovSmirnovTest(smallSample1, smallSample2, false), tol); - final double d = TestUtils.kolmogorovSmirnovStatistic(smallSample1, smallSample2); - Assert.assertEquals(0.5, d, tol); - Assert - .assertEquals(0.105577085453247, TestUtils.exactP(d, smallSample1.length,smallSample2.length, false), tol); - } -}
