psteitz 2004/05/10 19:12:11
Modified: math/src/test/org/apache/commons/math/distribution
HypergeometricDistributionTest.java
Log:
Modified to extend DiscreteDistributionAbstractTest. Added degenerate test cases.
Revision Changes Path
1.11 +88 -110
jakarta-commons/math/src/test/org/apache/commons/math/distribution/HypergeometricDistributionTest.java
Index: HypergeometricDistributionTest.java
===================================================================
RCS file:
/home/cvs/jakarta-commons/math/src/test/org/apache/commons/math/distribution/HypergeometricDistributionTest.java,v
retrieving revision 1.10
retrieving revision 1.11
diff -u -r1.10 -r1.11
--- HypergeometricDistributionTest.java 21 Feb 2004 21:35:17 -0000 1.10
+++ HypergeometricDistributionTest.java 11 May 2004 02:12:11 -0000 1.11
@@ -16,15 +16,14 @@
package org.apache.commons.math.distribution;
-import org.apache.commons.math.MathException;
-
-import junit.framework.TestCase;
-
/**
+ * Test cases for HyperGeometriclDistribution.
+ * Extends DiscreteDistributionAbstractTest. See class javadoc for
+ * DiscreteDistributionAbstractTest for details.
+ *
* @version $Revision$ $Date$
*/
-public class HypergeometricDistributionTest extends TestCase {
- private HypergeometricDistribution h;
+public class HypergeometricDistributionTest extends
DiscreteDistributionAbstractTest {
/**
* Constructor for ChiSquareDistributionTest.
@@ -34,109 +33,88 @@
super(name);
}
- /*
- * @see TestCase#setUp()
- */
- protected void setUp() throws Exception {
- super.setUp();
- h =
- DistributionFactory.newInstance().createHypergeometricDistribution(
- 10,
- 5,
- 5);
- }
-
- /*
- * @see TestCase#tearDown()
- */
- protected void tearDown() throws Exception {
- h = null;
- super.tearDown();
+//-------------- Implementations for abstract methods -----------------------
+
+ /** Creates the default discrete distribution instance to use in tests. */
+ public DiscreteDistribution makeDistribution() {
+ return
DistributionFactory.newInstance().createHypergeometricDistribution(10,5, 5);
+ }
+
+ /** Creates the default probability density test input values */
+ public int[] makeDensityTestPoints() {
+ return new int[] {-1, 0, 1, 2, 3, 4, 5, 10};
+ }
+
+ /** Creates the default probability density test expected values */
+ public double[] makeDensityTestValues() {
+ return new double[] {0d, 0.003968d, 0.099206d, 0.396825d, 0.396825d,
+ 0.099206d, 0.003968d, 0d};
+ }
+
+ /** Creates the default cumulative probability density test input values */
+ public int[] makeCumulativeTestPoints() {
+ return makeDensityTestPoints();
+ }
+
+ /** Creates the default cumulative probability density test expected values */
+ public double[] makeCumulativeTestValues() {
+ return new double[] {0d, .003968d, .103175d, .50000d, .896825d, .996032d,
+ 1.00000d, 1d};
+ }
+
+ /** Creates the default inverse cumulative probability test input values */
+ public double[] makeInverseCumulativeTestPoints() {
+ return new double[] {0.001d, 0.010d, 0.025d, 0.050d, 0.100d, 0.999d,
+ 0.990d, 0.975d, 0.950d, 0.900d};
+ }
+
+ /** Creates the default inverse cumulative probability density test expected
values */
+ public int[] makeInverseCumulativeTestValues() {
+ return new int[] {-1, 0, 0, 0, 0, 4, 3, 3, 3, 3};
+ }
+
+ //-------------------- Additional test cases ------------------------------
+
+ /** Verify that if there are no failures, mass is concentrated on sampleSize */
+ public void testDegenerateNoFailures() throws Exception {
+
setDistribution(DistributionFactory.newInstance().createHypergeometricDistribution(5,5,3));
+ setCumulativeTestPoints(new int[] {-1, 0, 1, 3, 10 });
+ setCumulativeTestValues(new double[] {0d, 0d, 0d, 1d, 1d});
+ setDensityTestPoints(new int[] {-1, 0, 1, 3, 10});
+ setDensityTestValues(new double[] {0d, 0d, 0d, 1d, 0d});
+ setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d});
+ setInverseCumulativeTestValues(new int[] {2, 2});
+ verifyDensities();
+ verifyCumulativeProbabilities();
+ verifyInverseCumulativeProbabilities();
+ }
+
+ /** Verify that if there are no successes, mass is concentrated on 0 */
+ public void testDegenerateNoSuccesses() throws Exception {
+
setDistribution(DistributionFactory.newInstance().createHypergeometricDistribution(5,0,3));
+ setCumulativeTestPoints(new int[] {-1, 0, 1, 3, 10 });
+ setCumulativeTestValues(new double[] {0d, 1d, 1d, 1d, 1d});
+ setDensityTestPoints(new int[] {-1, 0, 1, 3, 10});
+ setDensityTestValues(new double[] {0d, 1d, 0d, 0d, 0d});
+ setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d});
+ setInverseCumulativeTestValues(new int[] {-1, -1});
+ verifyDensities();
+ verifyCumulativeProbabilities();
+ verifyInverseCumulativeProbabilities();
+ }
+
+ /** Verify that if sampleSize = populationSize, mass is concentrated on
numberOfSuccesses */
+ public void testDegenerateFullSample() throws Exception {
+
setDistribution(DistributionFactory.newInstance().createHypergeometricDistribution(5,3,5));
+ setCumulativeTestPoints(new int[] {-1, 0, 1, 3, 10 });
+ setCumulativeTestValues(new double[] {0d, 0d, 0d, 1d, 1d});
+ setDensityTestPoints(new int[] {-1, 0, 1, 3, 10});
+ setDensityTestValues(new double[] {0d, 0d, 0d, 1d, 0d});
+ setInverseCumulativeTestPoints(new double[] {0.1d, 0.5d});
+ setInverseCumulativeTestValues(new int[] {2, 2});
+ verifyDensities();
+ verifyCumulativeProbabilities();
+ verifyInverseCumulativeProbabilities();
}
- public void testInverseCumulativeProbability001() {
- testValue(-1, .001);
- }
-
- public void testInverseCumulativeProbability010() {
- testValue(0, .010);
- }
-
- public void testInverseCumulativeProbability025() {
- testValue(0, .025);
- }
-
- public void testInverseCumulativeProbability050() {
- testValue(0, .050);
- }
-
- public void testInverseCumulativeProbability100() {
- testValue(0, .100);
- }
-
- public void testInverseCumulativeProbability999() {
- testValue(4, .999);
- }
-
- public void testInverseCumulativeProbability990() {
- testValue(3, .990);
- }
-
- public void testInverseCumulativeProbability975() {
- testValue(3, .975);
- }
-
- public void testInverseCumulativeProbability950() {
- testValue(3, .950);
- }
-
- public void testInverseCumulativeProbability900() {
- testValue(3, .900);
- }
-
- public void testCumulativeProbability0() {
- testProbability(0, .00400);
- }
-
- public void testCumulativeProbability1() {
- testProbability(1, .10318);
- }
-
- public void testCumulativeProbability2() {
- testProbability(2, .50000);
- }
-
- public void testCumulativeProbability3() {
- testProbability(3, .89683);
- }
-
- public void testCumulativeProbability4() {
- testProbability(4, .99603);
- }
-
- public void testCumulativeProbability5() {
- testProbability(5, 1.00000);
- }
-
- private void testProbability(int x, double expected) {
- try {
- double actual = h.cumulativeProbability(x);
- assertEquals(expected, actual, 10e-4);
- } catch (MathException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
- }
-
- private void testValue(int expected, double p) {
- try {
- int actual = h.inverseCumulativeProbability(p);
- assertEquals(expected, actual);
- assertTrue(h.cumulativeProbability(actual) <= p);
- assertTrue(h.cumulativeProbability(actual + 1) >= p);
- } catch (MathException e) {
- // TODO Auto-generated catch block
- e.printStackTrace();
- }
- }
}
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