psteitz 2004/05/30 15:13:35
Modified: math/src/test/org/apache/commons/math/distribution
TDistributionTest.java
Log:
Modified to extend ContinuousDistributionAbstract test, improved coverage.
Revision Changes Path
1.14 +58 -122
jakarta-commons/math/src/test/org/apache/commons/math/distribution/TDistributionTest.java
Index: TDistributionTest.java
===================================================================
RCS file:
/home/cvs/jakarta-commons/math/src/test/org/apache/commons/math/distribution/TDistributionTest.java,v
retrieving revision 1.13
retrieving revision 1.14
diff -u -r1.13 -r1.14
--- TDistributionTest.java 28 Feb 2004 21:58:33 -0000 1.13
+++ TDistributionTest.java 30 May 2004 22:13:35 -0000 1.14
@@ -15,149 +15,85 @@
*/
package org.apache.commons.math.distribution;
-import org.apache.commons.math.MathException;
-
-import junit.framework.TestCase;
-
/**
+ * Test cases for TDistribution.
+ * Extends ContinuousDistributionAbstractTest. See class javadoc for
+ * ContinuousDistributionAbstractTest for details.
+ *
* @version $Revision$ $Date$
*/
-public class TDistributionTest extends TestCase {
- private TDistribution t;
+public class TDistributionTest extends ContinuousDistributionAbstractTest {
/**
- * Constructor for ChiSquareDistributionTest.
+ * Constructor for TDistributionTest.
* @param name
*/
public TDistributionTest(String name) {
super(name);
}
- /*
- * @see TestCase#setUp()
- */
- protected void setUp() throws Exception {
- super.setUp();
- t = DistributionFactory.newInstance().createTDistribution(5.0);
- }
-
- /*
- * @see TestCase#tearDown()
- */
- protected void tearDown() throws Exception {
- t = null;
- super.tearDown();
- }
-
- public void testInverseCumulativeProbability001() {
- testValue(-5.893, .001);
- }
-
- public void testInverseCumulativeProbability010() {
- testValue(-3.365, .010);
- }
-
- public void testInverseCumulativeProbability025() {
- testValue(-2.571, .025);
- }
-
- public void testInverseCumulativeProbability050() {
- testValue(-2.015, .050);
- }
-
- public void testInverseCumulativeProbability100() {
- testValue(-1.476, .100);
- }
-
- public void testInverseCumulativeProbability999() {
- testValue(5.893, .999);
- }
-
- public void testInverseCumulativeProbability990() {
- testValue(3.365, .990);
- }
-
- public void testInverseCumulativeProbability975() {
- testValue(2.571, .975);
- }
-
- public void testInverseCumulativeProbability950() {
- testValue(2.015, .950);
- }
-
- public void testInverseCumulativeProbability900() {
- testValue(1.476, .900);
- }
-
- public void testCumulativeProbability001() {
- testProbability(-5.893, .001);
- }
-
- public void testCumulativeProbability010() {
- testProbability(-3.365, .010);
- }
-
- public void testCumulativeProbability025() {
- testProbability(-2.571, .025);
- }
-
- public void testCumulativeProbability050() {
- testProbability(-2.015, .050);
- }
-
- public void testCumulativeProbability100() {
- testProbability(-1.476, .100);
- }
-
- public void testCumulativeProbability999() {
- testProbability(5.893, .999);
- }
-
- public void testCumulativeProbability990() {
- testProbability(3.365, .990);
- }
-
- public void testCumulativeProbability975() {
- testProbability(2.571, .975);
+//-------------- Implementations for abstract methods -----------------------
+
+ /** Creates the default continuous distribution instance to use in tests. */
+ public ContinuousDistribution makeDistribution() {
+ return DistributionFactory.newInstance().createTDistribution(5.0);
+ }
+
+ /** Creates the default cumulative probability distribution test input values */
+ public double[] makeCumulativeTestPoints() {
+ // quantiles computed using R version 1.8.1 (linux version)
+ return new double[] {-5.89343,-3.36493, -2.570582, -2.015048,
+ -1.475884, 5.89343, 3.36493, 2.570582,
+ 2.015048, 1.475884};
}
-
- public void testCumulativeProbability950() {
- testProbability(2.015, .950);
+
+ /** Creates the default cumulative probability density test expected values */
+ public double[] makeCumulativeTestValues() {
+ return new double[] {0.001d, 0.01d, 0.025d, 0.05d, 0.1d, 0.999d,
+ 0.990d, 0.975d, 0.950d, 0.900d};
}
-
- public void testCumulativeProbability900() {
- testProbability(1.476, .900);
+
+ // --------------------- Override tolerance --------------
+ protected void setup() throws Exception {
+ super.setUp();
+ setTolerance(1E-6);
}
+ //---------------------------- Additional test cases -------------------------
/**
* @see <a href="http://nagoya.apache.org/bugzilla/show_bug.cgi?id=27243";>
* Bug report that prompted this unit test.</a>
*/
- public void testCumulativeProbabilityAgaintStackOverflow() {
- try {
- TDistributionImpl td = new TDistributionImpl(5.);
- double est;
- est = td.cumulativeProbability(.1);
- est = td.cumulativeProbability(.01);
- } catch(MathException ex) {
- fail(ex.getMessage());
- }
+ public void testCumulativeProbabilityAgaintStackOverflow() throws Exception {
+ TDistributionImpl td = new TDistributionImpl(5.);
+ double est;
+ est = td.cumulativeProbability(.1);
+ est = td.cumulativeProbability(.01);
}
- private void testProbability(double x, double expected) {
- try {
- double actual = t.cumulativeProbability(x);
- assertEquals(expected, actual, 10e-4);
- } catch (MathException e) {
- fail(e.getMessage());
- }
+ public void testSmallDf() throws Exception {
+ setDistribution(DistributionFactory.newInstance().createTDistribution(1d));
+ setTolerance(1E-4);
+ // quantiles computed using R version 1.8.1 (linux version)
+ setCumulativeTestPoints(new double[] {-318.3088, -31.82052, -12.70620,
-6.313752,
+ -3.077684, 318.3088, 31.82052, 12.70620,
+ 6.313752, 3.077684});
+ setInverseCumulativeTestValues(getCumulativeTestPoints());
+ verifyCumulativeProbabilities();
+ verifyInverseCumulativeProbabilities();
}
- private void testValue(double expected, double p) {
+
+ public void testDfAccessors() {
+ TDistribution distribution = (TDistribution) getDistribution();
+ assertEquals(5d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
+ distribution.setDegreesOfFreedom(4d);
+ assertEquals(4d, distribution.getDegreesOfFreedom(), Double.MIN_VALUE);
try {
- double actual = t.inverseCumulativeProbability(p);
- assertEquals(expected, actual, 10e-4);
- } catch (MathException e) {
- fail(e.getMessage());
+ distribution.setDegreesOfFreedom(0d);
+ fail("Expecting IllegalArgumentException for df = 0");
+ } catch (IllegalArgumentException ex) {
+ // expected
}
- }
+ }
+
}
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